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Sample records for regression trees rt

  1. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  2. Dynamic travel time estimation using regression trees.

    Science.gov (United States)

    2008-10-01

    This report presents a methodology for travel time estimation by using regression trees. The dissemination of travel time information has become crucial for effective traffic management, especially under congested road conditions. In the absence of c...

  3. Regression analysis using dependent Polya trees.

    Science.gov (United States)

    Schörgendorfer, Angela; Branscum, Adam J

    2013-11-30

    Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

  4. Reconstructing missing daily precipitation data using regression trees and artificial neural networks

    Science.gov (United States)

    Incomplete meteorological data has been a problem in environmental modeling studies. The objective of this work was to develop a technique to reconstruct missing daily precipitation data in the central part of Chesapeake Bay Watershed using regression trees (RT) and artificial neural networks (ANN)....

  5. Short-term load forecasting with increment regression tree

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jingfei; Stenzel, Juergen [Darmstadt University of Techonology, Darmstadt 64283 (Germany)

    2006-06-15

    This paper presents a new regression tree method for short-term load forecasting. Both increment and non-increment tree are built according to the historical data to provide the data space partition and input variable selection. Support vector machine is employed to the samples of regression tree nodes for further fine regression. Results of different tree nodes are integrated through weighted average method to obtain the comprehensive forecasting result. The effectiveness of the proposed method is demonstrated through its application to an actual system. (author)

  6. Variance to mean ratio, R(t), for poisson processes on phylogenetic trees.

    Science.gov (United States)

    Goldman, N

    1994-09-01

    The ratio of expected variance to mean, R(t), of numbers of DNA base substitutions for contemporary sequences related by a "star" phylogeny is widely seen as a measure of the adherence of the sequences' evolution to a Poisson process with a molecular clock, as predicted by the "neutral theory" of molecular evolution under certain conditions. A number of estimators of R(t) have been proposed, all predicted to have mean 1 and distributions based on the chi 2. Various genes have previously been analyzed and found to have values of R(t) far in excess of 1, calling into question important aspects of the neutral theory. In this paper, I use Monte Carlo simulation to show that the previously suggested means and distributions of estimators of R(t) are highly inaccurate. The analysis is applied to star phylogenies and to general phylogenetic trees, and well-known gene sequences are reanalyzed. For star phylogenies the results show that Kimura's estimators ("The Neutral Theory of Molecular Evolution," Cambridge Univ. Press, Cambridge, 1983) are unsatisfactory for statistical testing of R(t), but confirm the accuracy of Bulmer's correction factor (Genetics 123: 615-619, 1989). For all three nonstar phylogenies studied, attained values of all three estimators of R(t), although larger than 1, are within their true confidence limits under simple Poisson process models. This shows that lineage effects can be responsible for high estimates of R(t), restoring some limited confidence in the molecular clock and showing that the distinction between lineage and molecular clock effects is vital.(ABSTRACT TRUNCATED AT 250 WORDS)

  7. Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis

    Directory of Open Access Journals (Sweden)

    Carlos Augusto Zangrando Toneli

    2011-09-01

    Full Text Available Sub-pixel analysis is capable of generating continuous fields, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation.

  8. Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression.

    Science.gov (United States)

    Chen, Guangchao; Li, Xuehua; Chen, Jingwen; Zhang, Ya-Nan; Peijnenburg, Willie J G M

    2014-12-01

    Biodegradation is the principal environmental dissipation process of chemicals. As such, it is a dominant factor determining the persistence and fate of organic chemicals in the environment, and is therefore of critical importance to chemical management and regulation. In the present study, the authors developed in silico methods assessing biodegradability based on a large heterogeneous set of 825 organic compounds, using the techniques of the C4.5 decision tree, the functional inner regression tree, and logistic regression. External validation was subsequently carried out by 2 independent test sets of 777 and 27 chemicals. As a result, the functional inner regression tree exhibited the best predictability with predictive accuracies of 81.5% and 81.0%, respectively, on the training set (825 chemicals) and test set I (777 chemicals). Performance of the developed models on the 2 test sets was subsequently compared with that of the Estimation Program Interface (EPI) Suite Biowin 5 and Biowin 6 models, which also showed a better predictability of the functional inner regression tree model. The model built in the present study exhibits a reasonable predictability compared with existing models while possessing a transparent algorithm. Interpretation of the mechanisms of biodegradation was also carried out based on the models developed. © 2014 SETAC.

  9. Regression tree analysis for predicting body weight of Nigerian Muscovy duck (Cairina moschata

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    Oguntunji Abel Olusegun

    2017-01-01

    Full Text Available Morphometric parameters and their indices are central to the understanding of the type and function of livestock. The present study was conducted to predict body weight (BWT of adult Nigerian Muscovy ducks from nine (9 morphometric parameters and seven (7 body indices and also to identify the most important predictor of BWT among them using regression tree analysis (RTA. The experimental birds comprised of 1,020 adult male and female Nigerian Muscovy ducks randomly sampled in Rain Forest (203, Guinea Savanna (298 and Derived Savanna (519 agro-ecological zones. Result of RTA revealed that compactness; body girth and massiveness were the most important independent variables in predicting BWT and were used in constructing RT. The combined effect of the three predictors was very high and explained 91.00% of the observed variation of the target variable (BWT. The optimal regression tree suggested that Muscovy ducks with compactness >5.765 would be fleshy and have highest BWT. The result of the present study could be exploited by animal breeders and breeding companies in selection and improvement of BWT of Muscovy ducks.

  10. Iron Supplementation and Altitude: Decision Making Using a Regression Tree

    Directory of Open Access Journals (Sweden)

    Laura A. Garvican-Lewis, Andrew D. Govus, Peter Peeling, Chris R. Abbiss, Christopher J. Gore

    2016-03-01

    Full Text Available Altitude exposure increases the body’s need for iron (Gassmann and Muckenthaler, 2015, primarily to support accelerated erythropoiesis, yet clear supplementation guidelines do not exist. Athletes are typically recommended to ingest a daily oral iron supplement to facilitate altitude adaptations, and to help maintain iron balance. However, there is some debate as to whether athletes with otherwise healthy iron stores should be supplemented, due in part to concerns of iron overload. Excess iron in vital organs is associated with an increased risk of a number of conditions including cancer, liver disease and heart failure. Therefore clear guidelines are warranted and athletes should be discouraged from ‘self-prescribing” supplementation without medical advice. In the absence of prospective-controlled studies, decision tree analysis can be used to describe a data set, with the resultant regression tree serving as guide for clinical decision making. Here, we present a regression tree in the context of iron supplementation during altitude exposure, to examine the association between pre-altitude ferritin (Ferritin-Pre and the haemoglobin mass (Hbmass response, based on daily iron supplement dose. De-identified ferritin and Hbmass data from 178 athletes engaged in altitude training were extracted from the Australian Institute of Sport (AIS database. Altitude exposure was predominantly achieved via normobaric Live high: Train low (n = 147 at a simulated altitude of 3000 m for 2 to 4 weeks. The remaining athletes engaged in natural altitude training at venues ranging from 1350 to 2800 m for 3-4 weeks. Thus, the “hypoxic dose” ranged from ~890 km.h to ~1400 km.h. Ethical approval was granted by the AIS Human Ethics Committee, and athletes provided written informed consent. An in depth description and traditional analysis of the complete data set is presented elsewhere (Govus et al., 2015. Iron supplementation was prescribed by a sports physician

  11. Data to support "Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations & Biological Condition"

    Data.gov (United States)

    U.S. Environmental Protection Agency — Spreadsheets are included here to support the manuscript "Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition". This...

  12. Comparing Methodologies for Developing an Early Warning System: Classification and Regression Tree Model versus Logistic Regression. REL 2015-077

    Science.gov (United States)

    Koon, Sharon; Petscher, Yaacov

    2015-01-01

    The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules by…

  13. Using ROC curves to compare neural networks and logistic regression for modeling individual noncatastrophic tree mortality

    Science.gov (United States)

    Susan L. King

    2003-01-01

    The performance of two classifiers, logistic regression and neural networks, are compared for modeling noncatastrophic individual tree mortality for 21 species of trees in West Virginia. The output of the classifier is usually a continuous number between 0 and 1. A threshold is selected between 0 and 1 and all of the trees below the threshold are classified as...

  14. Simultaneous detection of three pome fruit tree viruses by one-step multiplex quantitative RT-PCR.

    Science.gov (United States)

    Malandraki, Ioanna; Beris, Despoina; Isaioglou, Ioannis; Olmos, Antonio; Varveri, Christina; Vassilakos, Nikon

    2017-01-01

    A one-step multiplex real-time reverse transcription polymerase chain reaction (RT-qPCR) based on TaqMan probes was developed for the simultaneous detection of Apple mosaic virus (ApMV), Apple stem pitting virus (ASPV) and Apple stem grooving virus (ASGV) in total RNA of pome trees extracted with a CTAB method. The sensitivity of the method was established using in vitro synthesized viral transcripts serially diluted in RNA from healthy, virus-tested (negative) pome trees. The three viruses were simultaneously detected up to a 10-4 dilution of total RNA from a naturally triple-infected apple tree prepared in total RNA of healthy apple tissue. The newly developed RT-qPCR assay was at least one hundred times more sensitive than conventional single RT-PCRs. The assay was validated with 36 field samples for which nine triple and 11 double infections were detected. All viruses were detected simultaneously in composite samples at least up to the ratio of 1:150 triple-infected to healthy pear tissue, suggesting the assay has the capacity to examine rapidly a large number of samples in pome tree certification programs and surveys for virus presence.

  15. Regression: The Apple Does Not Fall Far From the Tree.

    Science.gov (United States)

    Vetter, Thomas R; Schober, Patrick

    2018-05-15

    Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.

  16. Regression Nodes: Extending attack trees with data from social sciences

    NARCIS (Netherlands)

    Bullee, Jan-Willem; Montoya, L.; Pieters, Wolter; Junger, Marianne; Hartel, Pieter H.

    In the field of security, attack trees are often used to assess security vulnerabilities probabilistically in relation to multi-step attacks. The nodes are usually connected via AND-gates, where all children must be executed, or via OR-gates, where only one action is necessary for the attack step to

  17. The process and utility of classification and regression tree methodology in nursing research.

    Science.gov (United States)

    Kuhn, Lisa; Page, Karen; Ward, John; Worrall-Carter, Linda

    2014-06-01

    This paper presents a discussion of classification and regression tree analysis and its utility in nursing research. Classification and regression tree analysis is an exploratory research method used to illustrate associations between variables not suited to traditional regression analysis. Complex interactions are demonstrated between covariates and variables of interest in inverted tree diagrams. Discussion paper. English language literature was sourced from eBooks, Medline Complete and CINAHL Plus databases, Google and Google Scholar, hard copy research texts and retrieved reference lists for terms including classification and regression tree* and derivatives and recursive partitioning from 1984-2013. Classification and regression tree analysis is an important method used to identify previously unknown patterns amongst data. Whilst there are several reasons to embrace this method as a means of exploratory quantitative research, issues regarding quality of data as well as the usefulness and validity of the findings should be considered. Classification and regression tree analysis is a valuable tool to guide nurses to reduce gaps in the application of evidence to practice. With the ever-expanding availability of data, it is important that nurses understand the utility and limitations of the research method. Classification and regression tree analysis is an easily interpreted method for modelling interactions between health-related variables that would otherwise remain obscured. Knowledge is presented graphically, providing insightful understanding of complex and hierarchical relationships in an accessible and useful way to nursing and other health professions. © 2013 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

  18. Estimation of Tree Cover in an Agricultural Parkland of Senegal Using Rule-Based Regression Tree Modeling

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    Stefanie M. Herrmann

    2013-10-01

    Full Text Available Field trees are an integral part of the farmed parkland landscape in West Africa and provide multiple benefits to the local environment and livelihoods. While field trees have received increasing interest in the context of strengthening resilience to climate variability and change, the actual extent of farmed parkland and spatial patterns of tree cover are largely unknown. We used the rule-based predictive modeling tool Cubist® to estimate field tree cover in the west-central agricultural region of Senegal. A collection of rules and associated multiple linear regression models was constructed from (1 a reference dataset of percent tree cover derived from very high spatial resolution data (2 m Orbview as the dependent variable, and (2 ten years of 10-day 250 m Moderate Resolution Imaging Spectrometer (MODIS Normalized Difference Vegetation Index (NDVI composites and derived phenological metrics as independent variables. Correlation coefficients between modeled and reference percent tree cover of 0.88 and 0.77 were achieved for training and validation data respectively, with absolute mean errors of 1.07 and 1.03 percent tree cover. The resulting map shows a west-east gradient from high tree cover in the peri-urban areas of horticulture and arboriculture to low tree cover in the more sparsely populated eastern part of the study area. A comparison of current (2000s tree cover along this gradient with historic cover as seen on Corona images reveals dynamics of change but also areas of remarkable stability of field tree cover since 1968. The proposed modeling approach can help to identify locations of high and low tree cover in dryland environments and guide ground studies and management interventions aimed at promoting the integration of field trees in agricultural systems.

  19. Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

    Science.gov (United States)

    Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

    2009-01-01

    Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

  20. A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements

    Directory of Open Access Journals (Sweden)

    Suduan Chen

    2014-01-01

    Full Text Available As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

  1. A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements.

    Science.gov (United States)

    Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De

    2014-01-01

    As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

  2. Prediction of radiation levels in residences: A methodological comparison of CART [Classification and Regression Tree Analysis] and conventional regression

    International Nuclear Information System (INIS)

    Janssen, I.; Stebbings, J.H.

    1990-01-01

    In environmental epidemiology, trace and toxic substance concentrations frequently have very highly skewed distributions ranging over one or more orders of magnitude, and prediction by conventional regression is often poor. Classification and Regression Tree Analysis (CART) is an alternative in such contexts. To compare the techniques, two Pennsylvania data sets and three independent variables are used: house radon progeny (RnD) and gamma levels as predicted by construction characteristics in 1330 houses; and ∼200 house radon (Rn) measurements as predicted by topographic parameters. CART may identify structural variables of interest not identified by conventional regression, and vice versa, but in general the regression models are similar. CART has major advantages in dealing with other common characteristics of environmental data sets, such as missing values, continuous variables requiring transformations, and large sets of potential independent variables. CART is most useful in the identification and screening of independent variables, greatly reducing the need for cross-tabulations and nested breakdown analyses. There is no need to discard cases with missing values for the independent variables because surrogate variables are intrinsic to CART. The tree-structured approach is also independent of the scale on which the independent variables are measured, so that transformations are unnecessary. CART identifies important interactions as well as main effects. The major advantages of CART appear to be in exploring data. Once the important variables are identified, conventional regressions seem to lead to results similar but more interpretable by most audiences. 12 refs., 8 figs., 10 tabs

  3. A stepwise regression tree for nonlinear approximation: applications to estimating subpixel land cover

    Science.gov (United States)

    Huang, C.; Townshend, J.R.G.

    2003-01-01

    A stepwise regression tree (SRT) algorithm was developed for approximating complex nonlinear relationships. Based on the regression tree of Breiman et al . (BRT) and a stepwise linear regression (SLR) method, this algorithm represents an improvement over SLR in that it can approximate nonlinear relationships and over BRT in that it gives more realistic predictions. The applicability of this method to estimating subpixel forest was demonstrated using three test data sets, on all of which it gave more accurate predictions than SLR and BRT. SRT also generated more compact trees and performed better than or at least as well as BRT at all 10 equal forest proportion interval ranging from 0 to 100%. This method is appealing to estimating subpixel land cover over large areas.

  4. Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis.

    Science.gov (United States)

    Lo, Benjamin W Y; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H

    2016-01-01

    Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56-2.45, P tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.

  5. Combining logistic regression with classification and regression tree to predict quality of care in a home health nursing data set.

    Science.gov (United States)

    Guo, Huey-Ming; Shyu, Yea-Ing Lotus; Chang, Her-Kun

    2006-01-01

    In this article, the authors provide an overview of a research method to predict quality of care in home health nursing data set. The results of this study can be visualized through classification an regression tree (CART) graphs. The analysis was more effective, and the results were more informative since the home health nursing dataset was analyzed with a combination of the logistic regression and CART, these two techniques complete each other. And the results more informative that more patients' characters were related to quality of care in home care. The results contributed to home health nurse predict patient outcome in case management. Improved prediction is needed for interventions to be appropriately targeted for improved patient outcome and quality of care.

  6. Assessment of wastewater treatment facility compliance with decreasing ammonia discharge limits using a regression tree model.

    Science.gov (United States)

    Suchetana, Bihu; Rajagopalan, Balaji; Silverstein, JoAnn

    2017-11-15

    A regression tree-based diagnostic approach is developed to evaluate factors affecting US wastewater treatment plant compliance with ammonia discharge permit limits using Discharge Monthly Report (DMR) data from a sample of 106 municipal treatment plants for the period of 2004-2008. Predictor variables used to fit the regression tree are selected using random forests, and consist of the previous month's effluent ammonia, influent flow rates and plant capacity utilization. The tree models are first used to evaluate compliance with existing ammonia discharge standards at each facility and then applied assuming more stringent discharge limits, under consideration in many states. The model predicts that the ability to meet both current and future limits depends primarily on the previous month's treatment performance. With more stringent discharge limits predicted ammonia concentration relative to the discharge limit, increases. In-sample validation shows that the regression trees can provide a median classification accuracy of >70%. The regression tree model is validated using ammonia discharge data from an operating wastewater treatment plant and is able to accurately predict the observed ammonia discharge category approximately 80% of the time, indicating that the regression tree model can be applied to predict compliance for individual treatment plants providing practical guidance for utilities and regulators with an interest in controlling ammonia discharges. The proposed methodology is also used to demonstrate how to delineate reliable sources of demand and supply in a point source-to-point source nutrient credit trading scheme, as well as how planners and decision makers can set reasonable discharge limits in future. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Risk Factors of Falls in Community-Dwelling Older Adults: Logistic Regression Tree Analysis

    Science.gov (United States)

    Yamashita, Takashi; Noe, Douglas A.; Bailer, A. John

    2012-01-01

    Purpose of the Study: A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors. Design and Methods: A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used.…

  8. What Satisfies Students?: Mining Student-Opinion Data with Regression and Decision Tree Analysis

    Science.gov (United States)

    Thomas, Emily H.; Galambos, Nora

    2004-01-01

    To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The…

  9. Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis

    Science.gov (United States)

    Cohen, Ira L.; Liu, Xudong; Hudson, Melissa; Gillis, Jennifer; Cavalari, Rachel N. S.; Romanczyk, Raymond G.; Karmel, Bernard Z.; Gardner, Judith M.

    2016-01-01

    In order to improve discrimination accuracy between Autism Spectrum Disorder (ASD) and similar neurodevelopmental disorders, a data mining procedure, Classification and Regression Trees (CART), was used on a large multi-site sample of PDD Behavior Inventory (PDDBI) forms on children with and without ASD. Discrimination accuracy exceeded 80%,…

  10. One-step multiplex quantitative RT-PCR for the simultaneous detection of viroids and phytoplasmas of pome fruit trees.

    Science.gov (United States)

    Malandraki, Ioanna; Varveri, Christina; Olmos, Antonio; Vassilakos, Nikon

    2015-03-01

    A one-step multiplex real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) based on TaqMan chemistry was developed for the simultaneous detection of Pear blister canker viroid and Apple scar skin viroid along with universal detection of phytoplasmas, in pome trees. Total nucleic acids (TNAs) extraction was performed according to a modified CTAB protocol. Primers and TaqMan MGB probes for specific detection of the two viroids were designed in this study, whereas for phytoplasma detection published universal primers and probe were used, with the difference that the later was modified to carry a MGB quencher. The pathogens were detected simultaneously in 10-fold serial dilutions of TNAs from infected plant material into TNAs of healthy plant up to dilutions 10(-5) for viroids and 10(-4) for phytoplasmas. The multiplex real-time assay was at least 10 times more sensitive than conventional protocols for viroid and phytoplasma detection. Simultaneous detection of the three targets was achieved in composite samples at least up to a ratio of 1:100 triple-infected to healthy tissue, demonstrating that the developed assay has the potential to be used for rapid and massive screening of viroids and phytoplasmas of pome fruit trees in the frame of certification schemes and surveys. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Regression Trees Identify Relevant Interactions: Can This Improve the Predictive Performance of Risk Adjustment?

    Science.gov (United States)

    Buchner, Florian; Wasem, Jürgen; Schillo, Sonja

    2017-01-01

    Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  12. Development of hybrid genetic-algorithm-based neural networks using regression trees for modeling air quality inside a public transportation bus.

    Science.gov (United States)

    Kadiyala, Akhil; Kaur, Devinder; Kumar, Ashok

    2013-02-01

    The present study developed a novel approach to modeling indoor air quality (IAQ) of a public transportation bus by the development of hybrid genetic-algorithm-based neural networks (also known as evolutionary neural networks) with input variables optimized from using the regression trees, referred as the GART approach. This study validated the applicability of the GART modeling approach in solving complex nonlinear systems by accurately predicting the monitored contaminants of carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), sulfur dioxide (SO2), 0.3-0.4 microm sized particle numbers, 0.4-0.5 microm sized particle numbers, particulate matter (PM) concentrations less than 1.0 microm (PM10), and PM concentrations less than 2.5 microm (PM2.5) inside a public transportation bus operating on 20% grade biodiesel in Toledo, OH. First, the important variables affecting each monitored in-bus contaminant were determined using regression trees. Second, the analysis of variance was used as a complimentary sensitivity analysis to the regression tree results to determine a subset of statistically significant variables affecting each monitored in-bus contaminant. Finally, the identified subsets of statistically significant variables were used as inputs to develop three artificial neural network (ANN) models. The models developed were regression tree-based back-propagation network (BPN-RT), regression tree-based radial basis function network (RBFN-RT), and GART models. Performance measures were used to validate the predictive capacity of the developed IAQ models. The results from this approach were compared with the results obtained from using a theoretical approach and a generalized practicable approach to modeling IAQ that included the consideration of additional independent variables when developing the aforementioned ANN models. The hybrid GART models were able to capture majority of the variance in the monitored in-bus contaminants. The genetic

  13. A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

    Science.gov (United States)

    Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen. Fitzgerald

    2012-01-01

    Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

  14. Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees

    Directory of Open Access Journals (Sweden)

    Chen Xiaoyu

    2007-12-01

    Full Text Available Abstract Background In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression. Results We develop a Bayesian network approach for identifying cis-regulatory modules likely to regulate tissue-specific expression. The network integrates predicted transcription factor binding site information, transcription factor expression data, and target gene expression data. At its core is a regression tree modeling the effect of combinations of transcription factors bound to a module. A new unsupervised EM-like algorithm is developed to learn the parameters of the network, including the regression tree structure. Conclusion Our approach is shown to accurately identify known human liver and erythroid-specific modules. When applied to the prediction of tissue-specific modules in 10 different tissues, the network predicts a number of important transcription factor combinations whose concerted binding is associated to specific expression.

  15. Capacitance Regression Modelling Analysis on Latex from Selected Rubber Tree Clones

    International Nuclear Information System (INIS)

    Rosli, A D; Baharudin, R; Hashim, H; Khairuzzaman, N A; Mohd Sampian, A F; Abdullah, N E; Kamaru'zzaman, M; Sulaiman, M S

    2015-01-01

    This paper investigates the capacitance regression modelling performance of latex for various rubber tree clones, namely clone 2002, 2008, 2014 and 3001. Conventionally, the rubber tree clones identification are based on observation towards tree features such as shape of leaf, trunk, branching habit and pattern of seeds texture. The former method requires expert persons and very time-consuming. Currently, there is no sensing device based on electrical properties that can be employed to measure different clones from latex samples. Hence, with a hypothesis that the dielectric constant of each clone varies, this paper discusses the development of a capacitance sensor via Capacitance Comparison Bridge (known as capacitance sensor) to measure an output voltage of different latex samples. The proposed sensor is initially tested with 30ml of latex sample prior to gradually addition of dilution water. The output voltage and capacitance obtained from the test are recorded and analyzed using Simple Linear Regression (SLR) model. This work outcome infers that latex clone of 2002 has produced the highest and reliable linear regression line with determination coefficient of 91.24%. In addition, the study also found that the capacitive elements in latex samples deteriorate if it is diluted with higher volume of water. (paper)

  16. Identifying Generalizable Image Segmentation Parameters for Urban Land Cover Mapping through Meta-Analysis and Regression Tree Modeling

    Directory of Open Access Journals (Sweden)

    Brian A. Johnson

    2018-01-01

    Full Text Available The advent of very high resolution (VHR satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA have led to many new opportunities for fine-scale land cover mapping, especially in urban areas. Image segmentation is an important step in the GEOBIA framework, so great time/effort is often spent to ensure that computer-generated image segments closely match real-world objects of interest. In the remote sensing community, segmentation is frequently performed using the multiresolution segmentation (MRS algorithm, which is tuned through three user-defined parameters (the scale, shape/color, and compactness/smoothness parameters. The scale parameter (SP is the most important parameter and governs the average size of generated image segments. Existing automatic methods to determine suitable SPs for segmentation are scene-specific and often computationally intensive, so an approach to estimating appropriate SPs that is generalizable (i.e., not scene-specific could speed up the GEOBIA workflow considerably. In this study, we attempted to identify generalizable SPs for five common urban land cover types (buildings, vegetation, roads, bare soil, and water through meta-analysis and nonlinear regression tree (RT modeling. First, we performed a literature search of recent studies that employed GEOBIA for urban land cover mapping and extracted the MRS parameters used, the image properties (i.e., spatial and radiometric resolutions, and the land cover classes mapped. Using this data extracted from the literature, we constructed RT models for each land cover class to predict suitable SP values based on the: image spatial resolution, image radiometric resolution, shape/color parameter, and compactness/smoothness parameter. Based on a visual and quantitative analysis of results, we found that for all land cover classes except water, relatively accurate SPs could be identified using our RT modeling results. The main advantage of our

  17. [Hyperspectral Estimation of Apple Tree Canopy LAI Based on SVM and RF Regression].

    Science.gov (United States)

    Han, Zhao-ying; Zhu, Xi-cun; Fang, Xian-yi; Wang, Zhuo-yuan; Wang, Ling; Zhao, Geng-Xing; Jiang, Yuan-mao

    2016-03-01

    Leaf area index (LAI) is the dynamic index of crop population size. Hyperspectral technology can be used to estimate apple canopy LAI rapidly and nondestructively. It can be provide a reference for monitoring the tree growing and yield estimation. The Red Fuji apple trees of full bearing fruit are the researching objects. Ninety apple trees canopies spectral reflectance and LAI values were measured by the ASD Fieldspec3 spectrometer and LAI-2200 in thirty orchards in constant two years in Qixia research area of Shandong Province. The optimal vegetation indices were selected by the method of correlation analysis of the original spectral reflectance and vegetation indices. The models of predicting the LAI were built with the multivariate regression analysis method of support vector machine (SVM) and random forest (RF). The new vegetation indices, GNDVI527, ND-VI676, RVI682, FD-NVI656 and GRVI517 and the previous two main vegetation indices, NDVI670 and NDVI705, are in accordance with LAI. In the RF regression model, the calibration set decision coefficient C-R2 of 0.920 and validation set decision coefficient V-R2 of 0.889 are higher than the SVM regression model by 0.045 and 0.033 respectively. The root mean square error of calibration set C-RMSE of 0.249, the root mean square error validation set V-RMSE of 0.236 are lower than that of the SVM regression model by 0.054 and 0.058 respectively. Relative analysis of calibrating error C-RPD and relative analysis of validation set V-RPD reached 3.363 and 2.520, 0.598 and 0.262, respectively, which were higher than the SVM regression model. The measured and predicted the scatterplot trend line slope of the calibration set and validation set C-S and V-S are close to 1. The estimation result of RF regression model is better than that of the SVM. RF regression model can be used to estimate the LAI of red Fuji apple trees in full fruit period.

  18. Building interpretable predictive models for pediatric hospital readmission using Tree-Lasso logistic regression.

    Science.gov (United States)

    Jovanovic, Milos; Radovanovic, Sandro; Vukicevic, Milan; Van Poucke, Sven; Delibasic, Boris

    2016-09-01

    Quantification and early identification of unplanned readmission risk have the potential to improve the quality of care during hospitalization and after discharge. However, high dimensionality, sparsity, and class imbalance of electronic health data and the complexity of risk quantification, challenge the development of accurate predictive models. Predictive models require a certain level of interpretability in order to be applicable in real settings and create actionable insights. This paper aims to develop accurate and interpretable predictive models for readmission in a general pediatric patient population, by integrating a data-driven model (sparse logistic regression) and domain knowledge based on the international classification of diseases 9th-revision clinical modification (ICD-9-CM) hierarchy of diseases. Additionally, we propose a way to quantify the interpretability of a model and inspect the stability of alternative solutions. The analysis was conducted on >66,000 pediatric hospital discharge records from California, State Inpatient Databases, Healthcare Cost and Utilization Project between 2009 and 2011. We incorporated domain knowledge based on the ICD-9-CM hierarchy in a data driven, Tree-Lasso regularized logistic regression model, providing the framework for model interpretation. This approach was compared with traditional Lasso logistic regression resulting in models that are easier to interpret by fewer high-level diagnoses, with comparable prediction accuracy. The results revealed that the use of a Tree-Lasso model was as competitive in terms of accuracy (measured by area under the receiver operating characteristic curve-AUC) as the traditional Lasso logistic regression, but integration with the ICD-9-CM hierarchy of diseases provided more interpretable models in terms of high-level diagnoses. Additionally, interpretations of models are in accordance with existing medical understanding of pediatric readmission. Best performing models have

  19. A regression tree for identifying combinations of fall risk factors associated to recurrent falling: a cross-sectional elderly population-based study.

    Science.gov (United States)

    Kabeshova, A; Annweiler, C; Fantino, B; Philip, T; Gromov, V A; Launay, C P; Beauchet, O

    2014-06-01

    Regression tree (RT) analyses are particularly adapted to explore the risk of recurrent falling according to various combinations of fall risk factors compared to logistic regression models. The aims of this study were (1) to determine which combinations of fall risk factors were associated with the occurrence of recurrent falls in older community-dwellers, and (2) to compare the efficacy of RT and multiple logistic regression model for the identification of recurrent falls. A total of 1,760 community-dwelling volunteers (mean age ± standard deviation, 71.0 ± 5.1 years; 49.4 % female) were recruited prospectively in this cross-sectional study. Age, gender, polypharmacy, use of psychoactive drugs, fear of falling (FOF), cognitive disorders and sad mood were recorded. In addition, the history of falls within the past year was recorded using a standardized questionnaire. Among 1,760 participants, 19.7 % (n = 346) were recurrent fallers. The RT identified 14 nodes groups and 8 end nodes with FOF as the first major split. Among participants with FOF, those who had sad mood and polypharmacy formed the end node with the greatest OR for recurrent falls (OR = 6.06 with p falls (OR = 0.25 with p factors for recurrent falls, the combination most associated with recurrent falls involving FOF, sad mood and polypharmacy. The FOF emerged as the risk factor strongly associated with recurrent falls. In addition, RT and multiple logistic regression were not sensitive enough to identify the majority of recurrent fallers but appeared efficient in detecting individuals not at risk of recurrent falls.

  20. Perceived Organizational Support for Enhancing Welfare at Work: A Regression Tree Model

    Science.gov (United States)

    Giorgi, Gabriele; Dubin, David; Perez, Javier Fiz

    2016-01-01

    When trying to examine outcomes such as welfare and well-being, research tends to focus on main effects and take into account limited numbers of variables at a time. There are a number of techniques that may help address this problem. For example, many statistical packages available in R provide easy-to-use methods of modeling complicated analysis such as classification and tree regression (i.e., recursive partitioning). The present research illustrates the value of recursive partitioning in the prediction of perceived organizational support in a sample of more than 6000 Italian bankers. Utilizing the tree function party package in R, we estimated a regression tree model predicting perceived organizational support from a multitude of job characteristics including job demand, lack of job control, lack of supervisor support, training, etc. The resulting model appears particularly helpful in pointing out several interactions in the prediction of perceived organizational support. In particular, training is the dominant factor. Another dimension that seems to influence organizational support is reporting (perceived communication about safety and stress concerns). Results are discussed from a theoretical and methodological point of view. PMID:28082924

  1. Prediction of survival to discharge following cardiopulmonary resuscitation using classification and regression trees.

    Science.gov (United States)

    Ebell, Mark H; Afonso, Anna M; Geocadin, Romergryko G

    2013-12-01

    To predict the likelihood that an inpatient who experiences cardiopulmonary arrest and undergoes cardiopulmonary resuscitation survives to discharge with good neurologic function or with mild deficits (Cerebral Performance Category score = 1). Classification and Regression Trees were used to develop branching algorithms that optimize the ability of a series of tests to correctly classify patients into two or more groups. Data from 2007 to 2008 (n = 38,092) were used to develop candidate Classification and Regression Trees models to predict the outcome of inpatient cardiopulmonary resuscitation episodes and data from 2009 (n = 14,435) to evaluate the accuracy of the models and judge the degree of over fitting. Both supervised and unsupervised approaches to model development were used. 366 hospitals participating in the Get With the Guidelines-Resuscitation registry. Adult inpatients experiencing an index episode of cardiopulmonary arrest and undergoing cardiopulmonary resuscitation in the hospital. The five candidate models had between 8 and 21 nodes and an area under the receiver operating characteristic curve from 0.718 to 0.766 in the derivation group and from 0.683 to 0.746 in the validation group. One of the supervised models had 14 nodes and classified 27.9% of patients as very unlikely to survive neurologically intact or with mild deficits (Tree models that predict survival to discharge with good neurologic function or with mild deficits following in-hospital cardiopulmonary arrest. Models like this can assist physicians and patients who are considering do-not-resuscitate orders.

  2. Malignancy Risk Assessment in Patients with Thyroid Nodules Using Classification and Regression Trees

    Directory of Open Access Journals (Sweden)

    Shokouh Taghipour Zahir

    2013-01-01

    Full Text Available Purpose. We sought to investigate the utility of classification and regression trees (CART classifier to differentiate benign from malignant nodules in patients referred for thyroid surgery. Methods. Clinical and demographic data of 271 patients referred to the Sadoughi Hospital during 2006–2011 were collected. In a two-step approach, a CART classifier was employed to differentiate patients with a high versus low risk of thyroid malignancy. The first step served as the screening procedure and was tailored to produce as few false negatives as possible. The second step identified those with the lowest risk of malignancy, chosen from a high risk population. Sensitivity, specificity, positive and negative predictive values (PPV and NPV of the optimal tree were calculated. Results. In the first step, age, sex, and nodule size contributed to the optimal tree. Ultrasonographic features were employed in the second step with hypoechogenicity and/or microcalcifications yielding the highest discriminatory ability. The combined tree produced a sensitivity and specificity of 80.0% (95% CI: 29.9–98.9 and 94.1% (95% CI: 78.9–99.0, respectively. NPV and PPV were 66.7% (41.1–85.6 and 97.0% (82.5–99.8, respectively. Conclusion. CART classifier reliably identifies patients with a low risk of malignancy who can avoid unnecessary surgery.

  3. The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees

    DEFF Research Database (Denmark)

    Brunori, Paolo; Hufe, Paul; Mahler, Daniel Gerszon

    2017-01-01

    the risk of arbitrary and ad-hoc model selection. Second, they provide a standardized way of trading off upward and downward biases in inequality of opportunity estimations. Finally, regression trees can be graphically represented; their structure is immediate to read and easy to understand. This will make...... the measurement of inequality of opportunity more easily comprehensible to a large audience. These advantages are illustrated by an empirical application based on the 2011 wave of the European Union Statistics on Income and Living Conditions....

  4. Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

    Science.gov (United States)

    Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

    2012-01-01

    In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

  5. Exploring the predictive power of interaction terms in a sophisticated risk equalization model using regression trees.

    Science.gov (United States)

    van Veen, S H C M; van Kleef, R C; van de Ven, W P M M; van Vliet, R C J A

    2018-02-01

    This study explores the predictive power of interaction terms between the risk adjusters in the Dutch risk equalization (RE) model of 2014. Due to the sophistication of this RE-model and the complexity of the associations in the dataset (N = ~16.7 million), there are theoretically more than a million interaction terms. We used regression tree modelling, which has been applied rarely within the field of RE, to identify interaction terms that statistically significantly explain variation in observed expenses that is not already explained by the risk adjusters in this RE-model. The interaction terms identified were used as additional risk adjusters in the RE-model. We found evidence that interaction terms can improve the prediction of expenses overall and for specific groups in the population. However, the prediction of expenses for some other selective groups may deteriorate. Thus, interactions can reduce financial incentives for risk selection for some groups but may increase them for others. Furthermore, because regression trees are not robust, additional criteria are needed to decide which interaction terms should be used in practice. These criteria could be the right incentive structure for risk selection and efficiency or the opinion of medical experts. Copyright © 2017 John Wiley & Sons, Ltd.

  6. Application of Logistic Regression Tree Model in Determining Habitat Distribution of Astragalus verus

    Directory of Open Access Journals (Sweden)

    M. Saki

    2013-03-01

    Full Text Available The relationship between plant species and environmental factors has always been a central issue in plant ecology. With rising power of statistical techniques, geo-statistics and geographic information systems (GIS, the development of predictive habitat distribution models of organisms has rapidly increased in ecology. This study aimed to evaluate the ability of Logistic Regression Tree model to create potential habitat map of Astragalus verus. This species produces Tragacanth and has economic value. A stratified- random sampling was applied to 100 sites (50 presence- 50 absence of given species, and produced environmental and edaphic factors maps by using Kriging and Inverse Distance Weighting methods in the ArcGIS software for the whole study area. Relationships between species occurrence and environmental factors were determined by Logistic Regression Tree model and extended to the whole study area. The results indicated species occurrence has strong correlation with environmental factors such as mean daily temperature and clay, EC and organic carbon content of the soil. Species occurrence showed direct relationship with mean daily temperature and clay and organic carbon, and inverse relationship with EC. Model accuracy was evaluated both by Cohen’s kappa statistics (κ and by area under Receiver Operating Characteristics curve based on independent test data set. Their values (kappa=0.9, Auc of ROC=0.96 indicated the high power of LRT to create potential habitat map on local scales. This model, therefore, can be applied to recognize potential sites for rangeland reclamation projects.

  7. Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

    Directory of Open Access Journals (Sweden)

    Kritski Afrânio

    2006-02-01

    Full Text Available Abstract Background Smear negative pulmonary tuberculosis (SNPT accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. Methods The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. Results It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. Conclusion The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources.

  8. Application of Boosting Regression Trees to Preliminary Cost Estimation in Building Construction Projects

    Directory of Open Access Journals (Sweden)

    Yoonseok Shin

    2015-01-01

    Full Text Available Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project.

  9. Prediction of cannabis and cocaine use in adolescence using decision trees and logistic regression

    Directory of Open Access Journals (Sweden)

    Alfonso L. Palmer

    2010-01-01

    Full Text Available Spain is one of the European countries with the highest prevalence of cannabis and cocaine use among young people. The aim of this study was to investigate the factors related to the consumption of cocaine and cannabis among adolescents. A questionnaire was administered to 9,284 students between 14 and 18 years of age in Palma de Mallorca (47.1% boys and 52.9% girls whose mean age was 15.59 years. Logistic regression and decision trees were carried out in order to model the consumption of cannabis and cocaine. The results show the use of legal substances and committing fraudulence or theft are the main variables that raise the odds of consuming cannabis. In boys, cannabis consumption and a family history of drug use increase the odds of consuming cocaine, whereas in girls the use of alcohol, behaviours of fraudulence or theft and difficulty in some personal skills influence their odds of consuming cocaine. Finally, ease of access to the substance greatly raises the odds of consuming cocaine and cannabis in both genders. Decision trees highlight the role of consuming other substances and committing fraudulence or theft. The results of this study gain importance when it comes to putting into practice effective prevention programmes.

  10. Building optimal regression tree by ant colony system-genetic algorithm: Application to modeling of melting points

    Energy Technology Data Exchange (ETDEWEB)

    Hemmateenejad, Bahram, E-mail: hemmatb@sums.ac.ir [Department of Chemistry, Shiraz University, Shiraz (Iran, Islamic Republic of); Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz (Iran, Islamic Republic of); Shamsipur, Mojtaba [Department of Chemistry, Razi University, Kermanshah (Iran, Islamic Republic of); Zare-Shahabadi, Vali [Young Researchers Club, Mahshahr Branch, Islamic Azad University, Mahshahr (Iran, Islamic Republic of); Akhond, Morteza [Department of Chemistry, Shiraz University, Shiraz (Iran, Islamic Republic of)

    2011-10-17

    Highlights: {yields} Ant colony systems help to build optimum classification and regression trees. {yields} Using of genetic algorithm operators in ant colony systems resulted in more appropriate models. {yields} Variable selection in each terminal node of the tree gives promising results. {yields} CART-ACS-GA could model the melting point of organic materials with prediction errors lower than previous models. - Abstract: The classification and regression trees (CART) possess the advantage of being able to handle large data sets and yield readily interpretable models. A conventional method of building a regression tree is recursive partitioning, which results in a good but not optimal tree. Ant colony system (ACS), which is a meta-heuristic algorithm and derived from the observation of real ants, can be used to overcome this problem. The purpose of this study was to explore the use of CART and its combination with ACS for modeling of melting points of a large variety of chemical compounds. Genetic algorithm (GA) operators (e.g., cross averring and mutation operators) were combined with ACS algorithm to select the best solution model. In addition, at each terminal node of the resulted tree, variable selection was done by ACS-GA algorithm to build an appropriate partial least squares (PLS) model. To test the ability of the resulted tree, a set of approximately 4173 structures and their melting points were used (3000 compounds as training set and 1173 as validation set). Further, an external test set containing of 277 drugs was used to validate the prediction ability of the tree. Comparison of the results obtained from both trees showed that the tree constructed by ACS-GA algorithm performs better than that produced by recursive partitioning procedure.

  11. Integrating classification trees with local logistic regression in Intensive Care prognosis.

    Science.gov (United States)

    Abu-Hanna, Ameen; de Keizer, Nicolette

    2003-01-01

    Health care effectiveness and efficiency are under constant scrutiny especially when treatment is quite costly as in the Intensive Care (IC). Currently there are various international quality of care programs for the evaluation of IC. At the heart of such quality of care programs lie prognostic models whose prediction of patient mortality can be used as a norm to which actual mortality is compared. The current generation of prognostic models in IC are statistical parametric models based on logistic regression. Given a description of a patient at admission, these models predict the probability of his or her survival. Typically, this patient description relies on an aggregate variable, called a score, that quantifies the severity of illness of the patient. The use of a parametric model and an aggregate score form adequate means to develop models when data is relatively scarce but it introduces the risk of bias. This paper motivates and suggests a method for studying and improving the performance behavior of current state-of-the-art IC prognostic models. Our method is based on machine learning and statistical ideas and relies on exploiting information that underlies a score variable. In particular, this underlying information is used to construct a classification tree whose nodes denote patient sub-populations. For these sub-populations, local models, most notably logistic regression ones, are developed using only the total score variable. We compare the performance of this hybrid model to that of a traditional global logistic regression model. We show that the hybrid model not only provides more insight into the data but also has a better performance. We pay special attention to the precision aspect of model performance and argue why precision is more important than discrimination ability.

  12. Using boosted regression trees to predict the near-saturated hydraulic conductivity of undisturbed soils

    Science.gov (United States)

    Koestel, John; Bechtold, Michel; Jorda, Helena; Jarvis, Nicholas

    2015-04-01

    The saturated and near-saturated hydraulic conductivity of soil is of key importance for modelling water and solute fluxes in the vadose zone. Hydraulic conductivity measurements are cumbersome at the Darcy scale and practically impossible at larger scales where water and solute transport models are mostly applied. Hydraulic conductivity must therefore be estimated from proxy variables. Such pedotransfer functions are known to work decently well for e.g. water retention curves but rather poorly for near-saturated and saturated hydraulic conductivities. Recently, Weynants et al. (2009, Revisiting Vereecken pedotransfer functions: Introducing a closed-form hydraulic model. Vadose Zone Journal, 8, 86-95) reported a coefficients of determination of 0.25 (validation with an independent data set) for the saturated hydraulic conductivity from lab-measurements of Belgian soil samples. In our study, we trained boosted regression trees on a global meta-database containing tension-disk infiltrometer data (see Jarvis et al. 2013. Influence of soil, land use and climatic factors on the hydraulic conductivity of soil. Hydrology & Earth System Sciences, 17, 5185-5195) to predict the saturated hydraulic conductivity (Ks) and the conductivity at a tension of 10 cm (K10). We found coefficients of determination of 0.39 and 0.62 under a simple 10-fold cross-validation for Ks and K10. When carrying out the validation folded over the data-sources, i.e. the source publications, we found that the corresponding coefficients of determination reduced to 0.15 and 0.36, respectively. We conclude that the stricter source-wise cross-validation should be applied in future pedotransfer studies to prevent overly optimistic validation results. The boosted regression trees also allowed for an investigation of relevant predictors for estimating the near-saturated hydraulic conductivity. We found that land use and bulk density were most important to predict Ks. We also observed that Ks is large in fine

  13. Measuring the satisfaction of intensive care unit patient families in Morocco: a regression tree analysis.

    Science.gov (United States)

    Damghi, Nada; Khoudri, Ibtissam; Oualili, Latifa; Abidi, Khalid; Madani, Naoufel; Zeggwagh, Amine Ali; Abouqal, Redouane

    2008-07-01

    Meeting the needs of patients' family members becomes an essential part of responsibilities of intensive care unit physicians. The aim of this study was to evaluate the satisfaction of patients' family members using the Arabic version of the Society of Critical Care Medicine's Family Needs Assessment questionnaire and to assess the predictors of family satisfaction using the classification and regression tree method. The authors conducted a prospective study. This study was conducted at a 12-bed medical intensive care unit in Morocco. Family representatives (n = 194) of consecutive patients with a length of stay >48 hrs were included in the study. Intervention was the Society of Critical Care Medicine's Family Needs Assessment questionnaire. Demographic data for relatives included age, gender, relationship with patients, education level, and intensive care unit commuting time. Clinical data for patients included age, gender, diagnoses, intensive care unit length of stay, Acute Physiology and Chronic Health Evaluation, MacCabe index, Therapeutic Interventioning Scoring System, and mechanical ventilation. The Arabic version of the Society of Critical Care Medicine's Family Needs Assessment questionnaire was administered between the third and fifth days after admission. Of family representatives, 81% declared being satisfied with information provided by physicians, 27% would like more information about the diagnosis, 30% about prognosis, and 45% about treatment. In univariate analysis, family satisfaction (small Society of Critical Care Medicine's Family Needs Assessment questionnaire score) increased with a lower family education level (p = .005), when the information was given by a senior physician (p = .014), and when the Society of Critical Care Medicine's Family Needs Assessment questionnaire was administered by an investigator (p = .002). Multivariate analysis (classification and regression tree) showed that the education level was the predominant factor

  14. Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

    Science.gov (United States)

    Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

    2015-01-01

    Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

  15. City housing atmospheric pollutant impact on emergency visit for asthma: A classification and regression tree approach.

    Science.gov (United States)

    Mazenq, Julie; Dubus, Jean-Christophe; Gaudart, Jean; Charpin, Denis; Viudes, Gilles; Noel, Guilhem

    2017-11-01

    Particulate matter, nitrogen dioxide (NO 2 ) and ozone are recognized as the three pollutants that most significantly affect human health. Asthma is a multifactorial disease. However, the place of residence has rarely been investigated. We compared the impact of air pollution, measured near patients' homes, on emergency department (ED) visits for asthma or trauma (controls) within the Provence-Alpes-Côte-d'Azur region. Variables were selected using classification and regression trees on asthmatic and control population, 3-99 years, visiting ED from January 1 to December 31, 2013. Then in a nested case control study, randomization was based on the day of ED visit and on defined age groups. Pollution, meteorological, pollens and viral data measured that day were linked to the patient's ZIP code. A total of 794,884 visits were reported including 6250 for asthma and 278,192 for trauma. Factors associated with an excess risk of emergency visit for asthma included short-term exposure to NO 2 , female gender, high viral load and a combination of low temperature and high humidity. Short-term exposures to high NO 2 concentrations, as assessed close to the homes of the patients, were significantly associated with asthma-related ED visits in children and adults. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Differential Diagnosis of Erythmato-Squamous Diseases Using Classification and Regression Tree.

    Science.gov (United States)

    Maghooli, Keivan; Langarizadeh, Mostafa; Shahmoradi, Leila; Habibi-Koolaee, Mahdi; Jebraeily, Mohamad; Bouraghi, Hamid

    2016-10-01

    Differential diagnosis of Erythmato-Squamous Diseases (ESD) is a major challenge in the field of dermatology. The ESD diseases are placed into six different classes. Data mining is the process for detection of hidden patterns. In the case of ESD, data mining help us to predict the diseases. Different algorithms were developed for this purpose. we aimed to use the Classification and Regression Tree (CART) to predict differential diagnosis of ESD. we used the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. For this purpose, the dermatology data set from machine learning repository, UCI was obtained. The Clementine 12.0 software from IBM Company was used for modelling. In order to evaluation of the model we calculate the accuracy, sensitivity and specificity of the model. The proposed model had an accuracy of 94.84% (. 24.42) in order to correct prediction of the ESD disease. Results indicated that using of this classifier could be useful. But, it would be strongly recommended that the combination of machine learning methods could be more useful in terms of prediction of ESD.

  17. Groundwater level prediction of landslide based on classification and regression tree

    Directory of Open Access Journals (Sweden)

    Yannan Zhao

    2016-09-01

    Full Text Available According to groundwater level monitoring data of Shuping landslide in the Three Gorges Reservoir area, based on the response relationship between influential factors such as rainfall and reservoir level and the change of groundwater level, the influential factors of groundwater level were selected. Then the classification and regression tree (CART model was constructed by the subset and used to predict the groundwater level. Through the verification, the predictive results of the test sample were consistent with the actually measured values, and the mean absolute error and relative error is 0.28 m and 1.15% respectively. To compare the support vector machine (SVM model constructed using the same set of factors, the mean absolute error and relative error of predicted results is 1.53 m and 6.11% respectively. It is indicated that CART model has not only better fitting and generalization ability, but also strong advantages in the analysis of landslide groundwater dynamic characteristics and the screening of important variables. It is an effective method for prediction of ground water level in landslides.

  18. Automated Detection of Connective Tissue by Tissue Counter Analysis and Classification and Regression Trees

    Directory of Open Access Journals (Sweden)

    Josef Smolle

    2001-01-01

    Full Text Available Objective: To evaluate the feasibility of the CART (Classification and Regression Tree procedure for the recognition of microscopic structures in tissue counter analysis. Methods: Digital microscopic images of H&E stained slides of normal human skin and of primary malignant melanoma were overlayed with regularly distributed square measuring masks (elements and grey value, texture and colour features within each mask were recorded. In the learning set, elements were interactively labeled as representing either connective tissue of the reticular dermis, other tissue components or background. Subsequently, CART models were based on these data sets. Results: Implementation of the CART classification rules into the image analysis program showed that in an independent test set 94.1% of elements classified as connective tissue of the reticular dermis were correctly labeled. Automated measurements of the total amount of tissue and of the amount of connective tissue within a slide showed high reproducibility (r=0.97 and r=0.94, respectively; p < 0.001. Conclusions: CART procedure in tissue counter analysis yields simple and reproducible classification rules for tissue elements.

  19. KLASIFIKASI KARAKTERISTIK KECELAKAAN LALU LINTAS DI KOTA DENPASAR DENGAN PENDEKATAN CLASSIFICATION AND REGRESSION TREES (CART

    Directory of Open Access Journals (Sweden)

    I GEDE AGUS JIWADIANA

    2015-11-01

    Full Text Available The aim of this research is to determine the classification characteristics of traffic accidents in Denpasar city in January-July 2014 by using Classification And Regression Trees (CART. Then, for determine the explanatory variables into the main classifier of CART. The result showed that optimum CART generate three terminal node. First terminal node, there are 12 people were classified as heavy traffic accident characteritics with single accident, and second terminal nodes, there are 68 people were classified as minor traffic accident characteristics by type of traffic accident front-rear, front-front, front-side, pedestrians, side-side and location of traffic accident in district road and sub-district road. For third terminal node, there are 291 people were classified as medium traffic accident characteristics by type of traffic accident front-rear, front-front, front-side, pedestrians, side-side and location of traffic accident in municipality road and explanatory variables into the main splitter to make of CART is type of traffic accident with maximum homogeneity measure of 0.03252.

  20. Estimating carbon and showing impacts of drought using satellite data in regression-tree models

    Science.gov (United States)

    Boyte, Stephen; Wylie, Bruce K.; Howard, Danny; Dahal, Devendra; Gilmanov, Tagir G.

    2018-01-01

    Integrating spatially explicit biogeophysical and remotely sensed data into regression-tree models enables the spatial extrapolation of training data over large geographic spaces, allowing a better understanding of broad-scale ecosystem processes. The current study presents annual gross primary production (GPP) and annual ecosystem respiration (RE) for 2000–2013 in several short-statured vegetation types using carbon flux data from towers that are located strategically across the conterminous United States (CONUS). We calculate carbon fluxes (annual net ecosystem production [NEP]) for each year in our study period, which includes 2012 when drought and higher-than-normal temperatures influence vegetation productivity in large parts of the study area. We present and analyse carbon flux dynamics in the CONUS to better understand how drought affects GPP, RE, and NEP. Model accuracy metrics show strong correlation coefficients (r) (r ≥ 94%) between training and estimated data for both GPP and RE. Overall, average annual GPP, RE, and NEP are relatively constant throughout the study period except during 2012 when almost 60% less carbon is sequestered than normal. These results allow us to conclude that this modelling method effectively estimates carbon dynamics through time and allows the exploration of impacts of meteorological anomalies and vegetation types on carbon dynamics.

  1. Regression trees modeling and forecasting of PM10 air pollution in urban areas

    Science.gov (United States)

    Stoimenova, M.; Voynikova, D.; Ivanov, A.; Gocheva-Ilieva, S.; Iliev, I.

    2017-10-01

    Fine particulate matter (PM10) air pollution is a serious problem affecting the health of the population in many Bulgarian cities. As an example, the object of this study is the pollution with PM10 of the town of Pleven, Northern Bulgaria. The measured concentrations of this air pollutant for this city consistently exceeded the permissible limits set by European and national legislation. Based on data for the last 6 years (2011-2016), the analysis shows that this applies both to the daily limit of 50 micrograms per cubic meter and the allowable number of daily concentration exceedances to 35 per year. Also, the average annual concentration of PM10 exceeded the prescribed norm of no more than 40 micrograms per cubic meter. The aim of this work is to build high performance mathematical models for effective prediction and forecasting the level of PM10 pollution. The study was conducted with the powerful flexible data mining technique Classification and Regression Trees (CART). The values of PM10 were fitted with respect to meteorological data such as maximum and minimum air temperature, relative humidity, wind speed and direction and others, as well as with time and autoregressive variables. As a result the obtained CART models demonstrate high predictive ability and fit the actual data with up to 80%. The best models were applied for forecasting the level pollution for 3 to 7 days ahead. An interpretation of the modeling results is presented.

  2. Predicting number of hospitalization days based on health insurance claims data using bagged regression trees.

    Science.gov (United States)

    Xie, Yang; Schreier, Günter; Chang, David C W; Neubauer, Sandra; Redmond, Stephen J; Lovell, Nigel H

    2014-01-01

    Healthcare administrators worldwide are striving to both lower the cost of care whilst improving the quality of care given. Therefore, better clinical and administrative decision making is needed to improve these issues. Anticipating outcomes such as number of hospitalization days could contribute to addressing this problem. In this paper, a method was developed, using large-scale health insurance claims data, to predict the number of hospitalization days in a population. We utilized a regression decision tree algorithm, along with insurance claim data from 300,000 individuals over three years, to provide predictions of number of days in hospital in the third year, based on medical admissions and claims data from the first two years. Our method performs well in the general population. For the population aged 65 years and over, the predictive model significantly improves predictions over a baseline method (predicting a constant number of days for each patient), and achieved a specificity of 70.20% and sensitivity of 75.69% in classifying these subjects into two categories of 'no hospitalization' and 'at least one day in hospital'.

  3. A rapid silica spin column-based method of RNA extraction from fruit trees for RT-PCR detection of viruses.

    Science.gov (United States)

    Yang, Fan; Wang, Guoping; Xu, Wenxing; Hong, Ni

    2017-09-01

    Efficient recovery of high quality RNA is very important for successful RT-PCR detection of plant RNA viruses. High levels of polyphenols and polysaccharides in plant tissues can irreversibly bind to and/or co-precipitate with RNA, which influences RNA isolation. In this study, a silica spin column-based RNA isolation method was developed by using commercially available silica columns combined with the application of a tissue lysis solution, and binding and washing buffers with high concentration guanidinium thiocyanate (GuSCN, 50% w/v), which helps remove plant proteins, polysaccharides and polyphenolic compounds. The method was successfully used to extract high quality RNA from citrus (Citrus aurantifolia), grapevine (Vitis vinifera), peach (Prunus persica), pear (Pyrus spp.), taro (Colocosia esculenta) and tobacco (Nicotiana benthamiana) samples. The method was comparable to conventional CTAB method in RNA isolation efficiency, but it was more sample-adaptable and cost-effective than commercial kits. High quality RNA isolated using silica spin column-based method was successfully used for the RT-PCR and/or multiplex RT-PCR amplification of woody fruit tree viruses and a viroid. The study provided a useful tool for the detection and characterization of plant viruses. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Identification of Sexually Abused Female Adolescents at Risk for Suicidal Ideations: A Classification and Regression Tree Analysis

    Science.gov (United States)

    Brabant, Marie-Eve; Hebert, Martine; Chagnon, Francois

    2013-01-01

    This study explored the clinical profiles of 77 female teenager survivors of sexual abuse and examined the association of abuse-related and personal variables with suicidal ideations. Analyses revealed that 64% of participants experienced suicidal ideations. Findings from classification and regression tree analysis indicated that depression,…

  5. Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral data

    Science.gov (United States)

    Andrew T. Hudak; Nicholas L. Crookston; Jeffrey S. Evans; Michael K. Falkowski; Alistair M. S. Smith; Paul E. Gessler; Penelope Morgan

    2006-01-01

    We compared the utility of discrete-return light detection and ranging (lidar) data and multispectral satellite imagery, and their integration, for modeling and mapping basal area and tree density across two diverse coniferous forest landscapes in north-central Idaho. We applied multiple linear regression models subset from a suite of 26 predictor variables derived...

  6. What Satisfies Students? Mining Student-Opinion Data with Regression and Decision-Tree Analysis. AIR 2002 Forum Paper.

    Science.gov (United States)

    Thomas, Emily H.; Galambos, Nora

    To investigate how students' characteristics and experiences affect satisfaction, this study used regression and decision-tree analysis with the CHAID algorithm to analyze student opinion data from a sample of 1,783 college students. A data-mining approach identifies the specific aspects of students' university experience that most influence three…

  7. Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods.

    Science.gov (United States)

    Amini, Payam; Maroufizadeh, Saman; Samani, Reza Omani; Hamidi, Omid; Sepidarkish, Mahdi

    2017-06-01

    Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods. This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6-21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used. The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB ( p logistic regression model for the classification of risk groups for PTB.

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

    Science.gov (United States)

    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

  9. Regression Tree-Based Methodology for Customizing Building Energy Benchmarks to Individual Commercial Buildings

    Science.gov (United States)

    Kaskhedikar, Apoorva Prakash

    According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement. Energy Benchmarking offers initial building energy performance assessment without rigorous evaluation. Energy benchmarking tools based on the Commercial Buildings Energy Consumption Survey (CBECS) database are investigated in this thesis. This study proposes a new benchmarking methodology based on decision trees, where a relationship between the energy use intensities (EUI) and building parameters (continuous and categorical) is developed for different building types. This methodology was applied to medium office and school building types contained in the CBECS database. The Random Forest technique was used to find the most influential parameters that impact building energy use intensities. Subsequently, correlations which were significant were identified between EUIs and CBECS variables. Other than floor area, some of the important variables were number of workers, location, number of PCs and main cooling equipment. The coefficient of variation was used to evaluate the effectiveness of the new model. The customization technique proposed in this thesis was compared with another benchmarking model that is widely used by building owners and designers namely, the ENERGY STAR's Portfolio Manager. This tool relies on the standard Linear Regression methods which is only able to handle continuous variables. The model proposed uses data mining technique and was found to perform slightly better than the Portfolio Manager. The broader impacts of the new benchmarking methodology proposed is that it allows for identifying important categorical variables, and then incorporating them in a local, as against a global, model framework for EUI

  10. Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients.

    Science.gov (United States)

    Aguiar, Fabio S; Almeida, Luciana L; Ruffino-Netto, Antonio; Kritski, Afranio Lineu; Mello, Fernanda Cq; Werneck, Guilherme L

    2012-08-07

    Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in

  11. Schistosoma mansoni reinfection: Analysis of risk factors by classification and regression tree (CART modeling.

    Directory of Open Access Journals (Sweden)

    Andréa Gazzinelli

    Full Text Available Praziquantel (PZQ is an effective chemotherapy for schistosomiasis mansoni and a mainstay for its control and potential elimination. However, it does not prevent against reinfection, which can occur rapidly in areas with active transmission. A guide to ranking the risk factors for Schistosoma mansoni reinfection would greatly contribute to prioritizing resources and focusing prevention and control measures to prevent rapid reinfection. The objective of the current study was to explore the relationship among the socioeconomic, demographic, and epidemiological factors that can influence reinfection by S. mansoni one year after successful treatment with PZQ in school-aged children in Northeastern Minas Gerais state Brazil. Parasitological, socioeconomic, demographic, and water contact information were surveyed in 506 S. mansoni-infected individuals, aged 6 to 15 years, resident in these endemic areas. Eligible individuals were treated with PZQ until they were determined to be negative by the absence of S. mansoni eggs in the feces on two consecutive days of Kato-Katz fecal thick smear. These individuals were surveyed again 12 months from the date of successful treatment with PZQ. A classification and regression tree modeling (CART was then used to explore the relationship between socioeconomic, demographic, and epidemiological variables and their reinfection status. The most important risk factor identified for S. mansoni reinfection was their "heavy" infection at baseline. Additional analyses, excluding heavy infection status, showed that lower socioeconomic status and a lower level of education of the household head were also most important risk factors for S. mansoni reinfection. Our results provide an important contribution toward the control and possible elimination of schistosomiasis by identifying three major risk factors that can be used for targeted treatment and monitoring of reinfection. We suggest that control measures that target

  12. Comprehensive database of diameter-based biomass regressions for North American tree species

    Science.gov (United States)

    Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

    2004-01-01

    A database consisting of 2,640 equations compiled from the literature for predicting the biomass of trees and tree components from diameter measurements of species found in North America. Bibliographic information, geographic locations, diameter limits, diameter and biomass units, equation forms, statistical errors, and coefficients are provided for each equation,...

  13. Boosted regression trees, multivariate adaptive regression splines and their two-step combinations with multiple linear regression or partial least squares to predict blood-brain barrier passage: a case study.

    Science.gov (United States)

    Deconinck, E; Zhang, M H; Petitet, F; Dubus, E; Ijjaali, I; Coomans, D; Vander Heyden, Y

    2008-02-18

    The use of some unconventional non-linear modeling techniques, i.e. classification and regression trees and multivariate adaptive regression splines-based methods, was explored to model the blood-brain barrier (BBB) passage of drugs and drug-like molecules. The data set contains BBB passage values for 299 structural and pharmacological diverse drugs, originating from a structured knowledge-based database. Models were built using boosted regression trees (BRT) and multivariate adaptive regression splines (MARS), as well as their respective combinations with stepwise multiple linear regression (MLR) and partial least squares (PLS) regression in two-step approaches. The best models were obtained using combinations of MARS with either stepwise MLR or PLS. It could be concluded that the use of combinations of a linear with a non-linear modeling technique results in some improved properties compared to the individual linear and non-linear models and that, when the use of such a combination is appropriate, combinations using MARS as non-linear technique should be preferred over those with BRT, due to some serious drawbacks of the BRT approaches.

  14. Variances in the projections, resulting from CLIMEX, Boosted Regression Trees and Random Forests techniques

    Science.gov (United States)

    Shabani, Farzin; Kumar, Lalit; Solhjouy-fard, Samaneh

    2017-08-01

    The aim of this study was to have a comparative investigation and evaluation of the capabilities of correlative and mechanistic modeling processes, applied to the projection of future distributions of date palm in novel environments and to establish a method of minimizing uncertainty in the projections of differing techniques. The location of this study on a global scale is in Middle Eastern Countries. We compared the mechanistic model CLIMEX (CL) with the correlative models MaxEnt (MX), Boosted Regression Trees (BRT), and Random Forests (RF) to project current and future distributions of date palm ( Phoenix dactylifera L.). The Global Climate Model (GCM), the CSIRO-Mk3.0 (CS) using the A2 emissions scenario, was selected for making projections. Both indigenous and alien distribution data of the species were utilized in the modeling process. The common areas predicted by MX, BRT, RF, and CL from the CS GCM were extracted and compared to ascertain projection uncertainty levels of each individual technique. The common areas identified by all four modeling techniques were used to produce a map indicating suitable and unsuitable areas for date palm cultivation for Middle Eastern countries, for the present and the year 2100. The four different modeling approaches predict fairly different distributions. Projections from CL were more conservative than from MX. The BRT and RF were the most conservative methods in terms of projections for the current time. The combination of the final CL and MX projections for the present and 2100 provide higher certainty concerning those areas that will become highly suitable for future date palm cultivation. According to the four models, cold, hot, and wet stress, with differences on a regional basis, appears to be the major restrictions on future date palm distribution. The results demonstrate variances in the projections, resulting from different techniques. The assessment and interpretation of model projections requires reservations

  15. Classification and regression tree (CART model to predict pulmonary tuberculosis in hospitalized patients

    Directory of Open Access Journals (Sweden)

    Aguiar Fabio S

    2012-08-01

    Full Text Available Abstract Background Tuberculosis (TB remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART model was generated and validated. The area under the ROC curve (AUC, sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with

  16. Analysis of the impact of recreational trail usage for prioritising management decisions: a regression tree approach

    Science.gov (United States)

    Tomczyk, Aleksandra; Ewertowski, Marek; White, Piran; Kasprzak, Leszek

    2016-04-01

    The dual role of many Protected Natural Areas in providing benefits for both conservation and recreation poses challenges for management. Although recreation-based damage to ecosystems can occur very quickly, restoration can take many years. The protection of conservation interests at the same as providing for recreation requires decisions to be made about how to prioritise and direct management actions. Trails are commonly used to divert visitors from the most important areas of a site, but high visitor pressure can lead to increases in trail width and a concomitant increase in soil erosion. Here we use detailed field data on condition of recreational trails in Gorce National Park, Poland, as the basis for a regression tree analysis to determine the factors influencing trail deterioration, and link specific trail impacts with environmental, use related and managerial factors. We distinguished 12 types of trails, characterised by four levels of degradation: (1) trails with an acceptable level of degradation; (2) threatened trails; (3) damaged trails; and (4) heavily damaged trails. Damaged trails were the most vulnerable of all trails and should be prioritised for appropriate conservation and restoration. We also proposed five types of monitoring of recreational trail conditions: (1) rapid inventory of negative impacts; (2) monitoring visitor numbers and variation in type of use; (3) change-oriented monitoring focusing on sections of trail which were subjected to changes in type or level of use or subjected to extreme weather events; (4) monitoring of dynamics of trail conditions; and (5) full assessment of trail conditions, to be carried out every 10-15 years. The application of the proposed framework can enhance the ability of Park managers to prioritise their trail management activities, enhancing trail conditions and visitor safety, while minimising adverse impacts on the conservation value of the ecosystem. A.M.T. was supported by the Polish Ministry of

  17. Multiple Additive Regression Trees a Methodology for Predictive Data Mining for Fraud Detection

    National Research Council Canada - National Science Library

    da

    2002-01-01

    ...) is using new and innovative techniques for fraud detection. Their primary techniques for fraud detection are the data mining tools of classification trees and neural networks as well as methods for pooling the results of multiple model fits...

  18. [Application of regression tree in analyzing the effects of climate factors on NDVI in loess hilly area of Shaanxi Province].

    Science.gov (United States)

    Liu, Yang; Lü, Yi-he; Zheng, Hai-feng; Chen, Li-ding

    2010-05-01

    Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan' an City, the main meteorological variables affecting the annual and interannual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI, and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation, but could not build quantitative relations between NDVI and meteorological variables, which limited its further and wider application.

  19. On the quantitative relationships between environmental parameters and heavy metals pollution in Mediterranean soils using GIS regression-trees

    DEFF Research Database (Denmark)

    Bou Kheir, Rania; Shomar, B.; Greve, Mogens Humlekrog

    2014-01-01

    Soil heavy metal pollution has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study used Geographic Information Systems (GIS) and regression-tree modeling (196 trees) to precisely quantify...... the relationships between four toxic heavy metals (Ni, Cr, Cd and As) and sixteen environmental parameters (e.g., parent material, slope gradient, proximity to roads, etc.) in the soils of northern Lebanon (as a case study of Mediterranean landscapes), and to detect the most important parameters that can be used...... between 68% and 100%), surroundings of waste areas (48 – 92%), proximity to roads (45 – 82%) and parent materials (57 – 73%) considerably influenced all investigated heavy metals, which is not the case of hydromorphological and soil properties. For instance, hydraulic conductivity (18 – 41%) and pH (23...

  20. Downscaling soil moisture over East Asia through multi-sensor data fusion and optimization of regression trees

    Science.gov (United States)

    Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung

    2017-04-01

    Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An

  1. Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units

    International Nuclear Information System (INIS)

    Kropat, Georg; Bochud, Francois; Jaboyedoff, Michel; Laedermann, Jean-Pascal; Murith, Christophe; Palacios, Martha; Baechler, Sébastien

    2015-01-01

    Purpose: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. Method: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). Results: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. Conclusion: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables

  2. Analisis Perbandingan Teknik Support Vector Regression (SVR) Dan Decision Tree C4.5 Dalam Data Mining

    OpenAIRE

    Astuti, Yuniar Andi

    2011-01-01

    This study examines techniques Support Vector Regression and Decision Tree C4.5 has been used in studies in various fields, in order to know the advantages and disadvantages of both techniques that appear in Data Mining. From the ten studies that use both techniques, the results of the analysis showed that the accuracy of the SVR technique for 59,64% and C4.5 for 76,97% So in this study obtained a statement that C4.5 is better than SVR 097038020

  3. A Comparison of Logistic Regression, Neural Networks, and Classification Trees Predicting Success of Actuarial Students

    Science.gov (United States)

    Schumacher, Phyllis; Olinsky, Alan; Quinn, John; Smith, Richard

    2010-01-01

    The authors extended previous research by 2 of the authors who conducted a study designed to predict the successful completion of students enrolled in an actuarial program. They used logistic regression to determine the probability of an actuarial student graduating in the major or dropping out. They compared the results of this study with those…

  4. New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

    Science.gov (United States)

    L.R. Iverson; A.M. Prasad; A. Liaw

    2004-01-01

    More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

  5. Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

    Science.gov (United States)

    Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu

    2018-02-01

    A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.

  6. APPLICATION OF MULTIPLE LOGISTIC REGRESSION, BAYESIAN LOGISTIC AND CLASSIFICATION TREE TO IDENTIFY THE SIGNIFICANT FACTORS INFLUENCING CRASH SEVERITY

    Directory of Open Access Journals (Sweden)

    MILAD TAZIK

    2017-11-01

    Full Text Available Identifying cases in which road crashes result in fatality or injury of drivers may help improve their safety. In this study, datasets of crashes happened in TehranQom freeway, Iran, were examined by three models (multiple logistic regression, Bayesian logistic and classification tree to analyse the contribution of several variables to fatal accidents. For multiple logistic regression and Bayesian logistic models, the odds ratio was calculated for each variable. The model which best suited the identification of accident severity was determined based on AIC and DIC criteria. Based on the results of these two models, rollover crashes (OR = 14.58, %95 CI: 6.8-28.6, not using of seat belt (OR = 5.79, %95 CI: 3.1-9.9, exceeding speed limits (OR = 4.02, %95 CI: 1.8-7.9 and being female (OR = 2.91, %95 CI: 1.1-6.1 were the most important factors in fatalities of drivers. In addition, the results of the classification tree model have verified the findings of the other models.

  7. Online monitoring and conditional regression tree test: Useful tools for a better understanding of combined sewer network behavior.

    Science.gov (United States)

    Bersinger, T; Bareille, G; Pigot, T; Bru, N; Le Hécho, I

    2018-06-01

    A good knowledge of the dynamic of pollutant concentration and flux in a combined sewer network is necessary when considering solutions to limit the pollutants discharged by combined sewer overflow (CSO) into receiving water during wet weather. Identification of the parameters that influence pollutant concentration and flux is important. Nevertheless, few studies have obtained satisfactory results for the identification of these parameters using statistical tools. Thus, this work uses a large database of rain events (116 over one year) obtained via continuous measurement of rainfall, discharge flow and chemical oxygen demand (COD) estimated using online turbidity for the identification of these parameters. We carried out a statistical study of the parameters influencing the maximum COD concentration, the discharge flow and the discharge COD flux. In this study a new test was used that has never been used in this field: the conditional regression tree test. We have demonstrated that the antecedent dry weather period, the rain event average intensity and the flow before the event are the three main factors influencing the maximum COD concentration during a rainfall event. Regarding the discharge flow, it is mainly influenced by the overall rainfall height but not by the maximum rainfall intensity. Finally, COD discharge flux is influenced by the discharge volume and the maximum COD concentration. Regression trees seem much more appropriate than common tests like PCA and PLS for this type of study as they take into account the thresholds and cumulative effects of various parameters as a function of the target variable. These results could help to improve sewer and CSO management in order to decrease the discharge of pollutants into receiving waters. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Using multiobjective tradeoff sets and Multivariate Regression Trees to identify critical and robust decisions for long term water utility planning

    Science.gov (United States)

    Smith, R.; Kasprzyk, J. R.; Balaji, R.

    2017-12-01

    In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.

  9. Identifying Domain-General and Domain-Specific Predictors of Low Mathematics Performance: A Classification and Regression Tree Analysis

    Directory of Open Access Journals (Sweden)

    David J. Purpura

    2017-12-01

    Full Text Available Many children struggle to successfully acquire early mathematics skills. Theoretical and empirical evidence has pointed to deficits in domain-specific skills (e.g., non-symbolic mathematics skills or domain-general skills (e.g., executive functioning and language as underlying low mathematical performance. In the current study, we assessed a sample of 113 three- to five-year old preschool children on a battery of domain-specific and domain-general factors in the fall and spring of their preschool year to identify Time 1 (fall factors associated with low performance in mathematics knowledge at Time 2 (spring. We used the exploratory approach of classification and regression tree analyses, a strategy that uses step-wise partitioning to create subgroups from a larger sample using multiple predictors, to identify the factors that were the strongest classifiers of low performance for younger and older preschool children. Results indicated that the most consistent classifier of low mathematics performance at Time 2 was children’s Time 1 mathematical language skills. Further, other distinct classifiers of low performance emerged for younger and older children. These findings suggest that risk classification for low mathematics performance may differ depending on children’s age.

  10. Identifying the critical success factors in the coverage of low vision services using the classification analysis and regression tree methodology.

    Science.gov (United States)

    Chiang, Peggy Pei-Chia; Xie, Jing; Keeffe, Jill Elizabeth

    2011-04-25

    To identify the critical success factors (CSF) associated with coverage of low vision services. Data were collected from a survey distributed to Vision 2020 contacts, government, and non-government organizations (NGOs) in 195 countries. The Classification and Regression Tree Analysis (CART) was used to identify the critical success factors of low vision service coverage. Independent variables were sourced from the survey: policies, epidemiology, provision of services, equipment and infrastructure, barriers to services, human resources, and monitoring and evaluation. Socioeconomic and demographic independent variables: health expenditure, population statistics, development status, and human resources in general, were sourced from the World Health Organization (WHO), World Bank, and the United Nations (UN). The findings identified that having >50% of children obtaining devices when prescribed (χ(2) = 44; P 3 rehabilitation workers per 10 million of population (χ(2) = 4.50; P = 0.034), higher percentage of population urbanized (χ(2) = 14.54; P = 0.002), a level of private investment (χ(2) = 14.55; P = 0.015), and being fully funded by government (χ(2) = 6.02; P = 0.014), are critical success factors associated with coverage of low vision services. This study identified the most important predictors for countries with better low vision coverage. The CART is a useful and suitable methodology in survey research and is a novel way to simplify a complex global public health issue in eye care.

  11. Modelling daily dissolved oxygen concentration using least square support vector machine, multivariate adaptive regression splines and M5 model tree

    Science.gov (United States)

    Heddam, Salim; Kisi, Ozgur

    2018-04-01

    In the present study, three types of artificial intelligence techniques, least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5T) are applied for modeling daily dissolved oxygen (DO) concentration using several water quality variables as inputs. The DO concentration and water quality variables data from three stations operated by the United States Geological Survey (USGS) were used for developing the three models. The water quality data selected consisted of daily measured of water temperature (TE, °C), pH (std. unit), specific conductance (SC, μS/cm) and discharge (DI cfs), are used as inputs to the LSSVM, MARS and M5T models. The three models were applied for each station separately and compared to each other. According to the results obtained, it was found that: (i) the DO concentration could be successfully estimated using the three models and (ii) the best model among all others differs from one station to another.

  12. An Optimal Sample Data Usage Strategy to Minimize Overfitting and Underfitting Effects in Regression Tree Models Based on Remotely-Sensed Data

    Directory of Open Access Journals (Sweden)

    Yingxin Gu

    2016-11-01

    Full Text Available Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any dataset and identify an appropriate number of rules in the regression tree model that will improve its accuracy and robustness. Landsat 8 data and Moderate-Resolution Imaging Spectroradiometer-scaled Normalized Difference Vegetation Index (NDVI were used to develop regression tree models. A Python procedure was designed to generate random replications of model parameter options across a range of model development data sizes and rule number constraints. The mean absolute difference (MAD between the predicted and actual NDVI (scaled NDVI, value from 0–200 and its variability across the different randomized replications were calculated to assess the accuracy and stability of the models. In our case study, a six-rule regression tree model developed from 80% of the sample data had the lowest MAD (MADtraining = 2.5 and MADtesting = 2.4, which was suggested as the optimal model. This study demonstrates how the training data and rule number selections impact model accuracy and provides important guidance for future remote-sensing-based ecosystem modeling.

  13. Trees

    Science.gov (United States)

    Al-Khaja, Nawal

    2007-01-01

    This is a thematic lesson plan for young learners about palm trees and the importance of taking care of them. The two part lesson teaches listening, reading and speaking skills. The lesson includes parts of a tree; the modal auxiliary, can; dialogues and a role play activity.

  14. GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models.

    Science.gov (United States)

    Chen, Wei; Li, Hui; Hou, Enke; Wang, Shengquan; Wang, Guirong; Panahi, Mahdi; Li, Tao; Peng, Tao; Guo, Chen; Niu, Chao; Xiao, Lele; Wang, Jiale; Xie, Xiaoshen; Ahmad, Baharin Bin

    2018-09-01

    The aim of the current study was to produce groundwater spring potential maps using novel ensemble weights-of-evidence (WoE) with logistic regression (LR) and functional tree (FT) models. First, a total of 66 springs were identified by field surveys, out of which 70% of the spring locations were used for training the models and 30% of the spring locations were employed for the validation process. Second, a total of 14 affecting factors including aspect, altitude, slope, plan curvature, profile curvature, stream power index (SPI), topographic wetness index (TWI), sediment transport index (STI), lithology, normalized difference vegetation index (NDVI), land use, soil, distance to roads, and distance to streams was used to analyze the spatial relationship between these affecting factors and spring occurrences. Multicollinearity analysis and feature selection of the correlation attribute evaluation (CAE) method were employed to optimize the affecting factors. Subsequently, the novel ensembles of the WoE, LR, and FT models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) curves, standard error, confidence interval (CI) at 95%, and significance level P were employed to validate and compare the performance of three models. Overall, all three models performed well for groundwater spring potential evaluation. The prediction capability of the FT model, with the highest AUC values, the smallest standard errors, the narrowest CIs, and the smallest P values for the training and validation datasets, is better compared to those of other models. The groundwater spring potential maps can be adopted for the management of water resources and land use by planners and engineers. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: laying a foundation for monitoring

    Science.gov (United States)

    Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.

    2012-01-01

    agebrush ecosystems in North America have experienced extensive degradation since European settlement. Further degradation continues from exotic invasive plants, altered fire frequency, intensive grazing practices, oil and gas development, and climate change – adding urgency to the need for ecosystem-wide understanding. Remote sensing is often identified as a key information source to facilitate ecosystem-wide characterization, monitoring, and analysis; however, approaches that characterize sagebrush with sufficient and accurate local detail across large enough areas to support this paradigm are unavailable. We describe the development of a new remote sensing sagebrush characterization approach for the state of Wyoming, U.S.A. This approach integrates 2.4 m QuickBird, 30 m Landsat TM, and 56 m AWiFS imagery into the characterization of four primary continuous field components including percent bare ground, percent herbaceous cover, percent litter, and percent shrub, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata Wyomingensis), and shrub height using a regression tree. According to an independent accuracy assessment, primary component root mean square error (RMSE) values ranged from 4.90 to 10.16 for 2.4 m QuickBird, 6.01 to 15.54 for 30 m Landsat, and 6.97 to 16.14 for 56 m AWiFS. Shrub and herbaceous components outperformed the current data standard called LANDFIRE, with a shrub RMSE value of 6.04 versus 12.64 and a herbaceous component RMSE value of 12.89 versus 14.63. This approach offers new advancements in sagebrush characterization from remote sensing and provides a foundation to quantitatively monitor these components into the future.

  16. Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

    International Nuclear Information System (INIS)

    Althuwaynee, Omar F; Pradhan, Biswajeet; Ahmad, Noordin

    2014-01-01

    This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies

  17. Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

    Science.gov (United States)

    Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

    2014-06-01

    This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

  18. Penalized regression techniques for prediction: a case study for predicting tree mortality using remotely sensed vegetation indices

    NARCIS (Netherlands)

    Lazaridis, D.C.; Verbesselt, J.; Robinson, A.P.

    2011-01-01

    Constructing models can be complicated when the available fitting data are highly correlated and of high dimension. However, the complications depend on whether the goal is prediction instead of estimation. We focus on predicting tree mortality (measured as the number of dead trees) from change

  19. Metabolic activity of tree saps of different origin towards cultured human cells in the light of grade correspondence analysis and multiple regression modeling

    Directory of Open Access Journals (Sweden)

    Artur Wnorowski

    2017-06-01

    Full Text Available Tree saps are nourishing biological media commonly used for beverage and syrup production. Although the nutritional aspect of tree saps is widely acknowledged, the exact relationship between the sap composition, origin, and effect on the metabolic rate of human cells is still elusive. Thus, we collected saps from seven different tree species and conducted composition-activity analysis. Saps from trees of Betulaceae, but not from Salicaceae, Sapindaceae, nor Juglandaceae families, were increasing the metabolic rate of HepG2 cells, as measured using tetrazolium-based assay. Content of glucose, fructose, sucrose, chlorides, nitrates, sulphates, fumarates, malates, and succinates in sap samples varied across different tree species. Grade correspondence analysis clustered trees based on the saps’ chemical footprint indicating its usability in chemotaxonomy. Multiple regression modeling showed that glucose and fumarate present in saps from silver birch (Betula pendula Roth., black alder (Alnus glutinosa Gaertn., and European hornbeam (Carpinus betulus L. are positively affecting the metabolic activity of HepG2 cells.

  20. Regionalization of meso-scale physically based nitrogen modeling outputs to the macro-scale by the use of regression trees

    Science.gov (United States)

    Künne, A.; Fink, M.; Kipka, H.; Krause, P.; Flügel, W.-A.

    2012-06-01

    In this paper, a method is presented to estimate excess nitrogen on large scales considering single field processes. The approach was implemented by using the physically based model J2000-S to simulate the nitrogen balance as well as the hydrological dynamics within meso-scale test catchments. The model input data, the parameterization, the results and a detailed system understanding were used to generate the regression tree models with GUIDE (Loh, 2002). For each landscape type in the federal state of Thuringia a regression tree was calibrated and validated using the model data and results of excess nitrogen from the test catchments. Hydrological parameters such as precipitation and evapotranspiration were also used to predict excess nitrogen by the regression tree model. Hence they had to be calculated and regionalized as well for the state of Thuringia. Here the model J2000g was used to simulate the water balance on the macro scale. With the regression trees the excess nitrogen was regionalized for each landscape type of Thuringia. The approach allows calculating the potential nitrogen input into the streams of the drainage area. The results show that the applied methodology was able to transfer the detailed model results of the meso-scale catchments to the entire state of Thuringia by low computing time without losing the detailed knowledge from the nitrogen transport modeling. This was validated with modeling results from Fink (2004) in a catchment lying in the regionalization area. The regionalized and modeled excess nitrogen correspond with 94%. The study was conducted within the framework of a project in collaboration with the Thuringian Environmental Ministry, whose overall aim was to assess the effect of agro-environmental measures regarding load reduction in the water bodies of Thuringia to fulfill the requirements of the European Water Framework Directive (Bäse et al., 2007; Fink, 2006; Fink et al., 2007).

  1. Galectin-3 and Beclin1/Atg6 genes in human cancers: using cDNA tissue panel, qRT-PCR, and logistic regression model to identify cancer cell biomarkers.

    Directory of Open Access Journals (Sweden)

    Halliday A Idikio

    Full Text Available Cancer biomarkers are sought to support cancer diagnosis, predict cancer patient response to treatment and survival. Identifying reliable biomarkers for predicting cancer treatment response needs understanding of all aspects of cancer cell death and survival. Galectin-3 and Beclin1 are involved in two coordinated pathways of programmed cell death, apoptosis and autophagy and are linked to necroptosis/necrosis. The aim of the study was to quantify galectin-3 and Beclin1 mRNA in human cancer tissue cDNA panels and determine their utility as biomarkers of cancer cell survival.A panel of 96 cDNAs from eight (8 different normal and cancer tissue types were used for quantitative real-time polymerase chain reaction (qRT-PCR using ABI7900HT. Miner2.0, a web-based 4- and 3-parameter logistic regression software was used to derive individual well polymerase chain reaction efficiencies (E and cycle threshold (Ct values. Miner software derived formula was used to calculate mRNA levels and then fold changes. The ratios of cancer to normal tissue levels of galectin-3 and Beclin1 were calculated (using the mean for each tissue type. Relative mRNA expressions for galectin-3 were higher than for Beclin1 in all tissue (normal and cancer types. In cancer tissues, breast, kidney, thyroid and prostate had the highest galectin-3 mRNA levels compared to normal tissues. High levels of Beclin1 mRNA levels were in liver and prostate cancers when compared to normal tissues. Breast, kidney and thyroid cancers had high galectin-3 levels and low Beclin1 levels.Galectin-3 expression patterns in normal and cancer tissues support its reported roles in human cancer. Beclin1 expression pattern supports its roles in cancer cell survival and in treatment response. qRT-PCR analysis method used may enable high throughput studies to generate molecular biomarker sets for diagnosis and predicting cancer treatment response.

  2. Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria

    Science.gov (United States)

    Dyer, Betsey D.; Kahn, Michael J.; LeBlanc, Mark D.

    2008-01-01

    Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results. PMID:19054742

  3. An Introduction to Recursive Partitioning: Rationale, Application, and Characteristics of Classification and Regression Trees, Bagging, and Random Forests

    Science.gov (United States)

    Strobl, Carolin; Malley, James; Tutz, Gerhard

    2009-01-01

    Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and…

  4. Partitioning of Multivariate Phenotypes using Regression Trees Reveals Complex Patterns of Adaptation to Climate across the Range of Black Cottonwood (Populus trichocarpa

    Directory of Open Access Journals (Sweden)

    Regis Wendpouire Oubida

    2015-03-01

    Full Text Available Local adaptation to climate in temperate forest trees involves the integration of multiple physiological, morphological, and phenological traits. Latitudinal clines are frequently observed for these traits, but environmental constraints also track longitude and altitude. We combined extensive phenotyping of 12 candidate adaptive traits, multivariate regression trees, quantitative genetics, and a genome-wide panel of SNP markers to better understand the interplay among geography, climate, and adaptation to abiotic factors in Populus trichocarpa. Heritabilities were low to moderate (0.13 to 0.32 and population differentiation for many traits exceeded the 99th percentile of the genome-wide distribution of FST, suggesting local adaptation. When climate variables were taken as predictors and the 12 traits as response variables in a multivariate regression tree analysis, evapotranspiration (Eref explained the most variation, with subsequent splits related to mean temperature of the warmest month, frost-free period (FFP, and mean annual precipitation (MAP. These grouping matched relatively well the splits using geographic variables as predictors: the northernmost groups (short FFP and low Eref had the lowest growth, and lowest cold injury index; the southern British Columbia group (low Eref and intermediate temperatures had average growth and cold injury index; the group from the coast of California and Oregon (high Eref and FFP had the highest growth performance and the highest cold injury index; and the southernmost, high-altitude group (with high Eref and low FFP performed poorly, had high cold injury index, and lower water use efficiency. Taken together, these results suggest variation in both temperature and water availability across the range shape multivariate adaptive traits in poplar.

  5. Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey.

    Science.gov (United States)

    Ozge, C; Toros, F; Bayramkaya, E; Camdeviren, H; Sasmaz, T

    2006-08-01

    The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Using in-class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed.

  6. Binary Logistic Regression Versus Boosted Regression Trees in Assessing Landslide Susceptibility for Multiple-Occurring Regional Landslide Events: Application to the 2009 Storm Event in Messina (Sicily, southern Italy).

    Science.gov (United States)

    Lombardo, L.; Cama, M.; Maerker, M.; Parisi, L.; Rotigliano, E.

    2014-12-01

    This study aims at comparing the performances of Binary Logistic Regression (BLR) and Boosted Regression Trees (BRT) methods in assessing landslide susceptibility for multiple-occurrence regional landslide events within the Mediterranean region. A test area was selected in the north-eastern sector of Sicily (southern Italy), corresponding to the catchments of the Briga and the Giampilieri streams both stretching for few kilometres from the Peloritan ridge (eastern Sicily, Italy) to the Ionian sea. This area was struck on the 1st October 2009 by an extreme climatic event resulting in thousands of rapid shallow landslides, mainly of debris flows and debris avalanches types involving the weathered layer of a low to high grade metamorphic bedrock. Exploiting the same set of predictors and the 2009 landslide archive, BLR- and BRT-based susceptibility models were obtained for the two catchments separately, adopting a random partition (RP) technique for validation; besides, the models trained in one of the two catchments (Briga) were tested in predicting the landslide distribution in the other (Giampilieri), adopting a spatial partition (SP) based validation procedure. All the validation procedures were based on multi-folds tests so to evaluate and compare the reliability of the fitting, the prediction skill, the coherence in the predictor selection and the precision of the susceptibility estimates. All the obtained models for the two methods produced very high predictive performances, with a general congruence between BLR and BRT in the predictor importance. In particular, the research highlighted that BRT-models reached a higher prediction performance with respect to BLR-models, for RP based modelling, whilst for the SP-based models the difference in predictive skills between the two methods dropped drastically, converging to an analogous excellent performance. However, when looking at the precision of the probability estimates, BLR demonstrated to produce more robust

  7. Quantifying the ability of environmental parameters to predict soil texture fractions using regression-tree model with GIS and LIDAR data

    DEFF Research Database (Denmark)

    Greve, Mogens Humlekrog; Bou Kheir, Rania; Greve, Mette Balslev

    2012-01-01

    Soil texture is an important soil characteristic that drives crop production and field management, and is the basis for environmental monitoring (including soil quality and sustainability, hydrological and ecological processes, and climate change simulations). The combination of coarse sand, fine...... sand, silt, and clay in soil determines its textural classification. This study used Geographic Information Systems (GIS) and regression-tree modeling to precisely quantify the relationships between the soil texture fractions and different environmental parameters on a national scale, and to detect...... precipitation, seasonal precipitation to statistically explain soil texture fractions field/laboratory measurements (45,224 sampling sites) in the area of interest (Denmark). The developed strongest relationships were associated with clay and silt, variance being equal to 60%, followed by coarse sand (54...

  8. Predictors of adherence with self-care guidelines among persons with type 2 diabetes: results from a logistic regression tree analysis.

    Science.gov (United States)

    Yamashita, Takashi; Kart, Cary S; Noe, Douglas A

    2012-12-01

    Type 2 diabetes is known to contribute to health disparities in the U.S. and failure to adhere to recommended self-care behaviors is a contributing factor. Intervention programs face difficulties as a result of patient diversity and limited resources. With data from the 2005 Behavioral Risk Factor Surveillance System, this study employs a logistic regression tree algorithm to identify characteristics of sub-populations with type 2 diabetes according to their reported frequency of adherence to four recommended diabetes self-care behaviors including blood glucose monitoring, foot examination, eye examination and HbA1c testing. Using Andersen's health behavior model, need factors appear to dominate the definition of which sub-groups were at greatest risk for low as well as high adherence. Findings demonstrate the utility of easily interpreted tree diagrams to design specific culturally appropriate intervention programs targeting sub-populations of diabetes patients who need to improve their self-care behaviors. Limitations and contributions of the study are discussed.

  9. Comparing pseudo-absences generation techniques in Boosted Regression Trees models for conservation purposes: A case study on amphibians in a protected area.

    Directory of Open Access Journals (Sweden)

    Francesco Cerasoli

    Full Text Available Boosted Regression Trees (BRT is one of the modelling techniques most recently applied to biodiversity conservation and it can be implemented with presence-only data through the generation of artificial absences (pseudo-absences. In this paper, three pseudo-absences generation techniques are compared, namely the generation of pseudo-absences within target-group background (TGB, testing both the weighted (WTGB and unweighted (UTGB scheme, and the generation at random (RDM, evaluating their performance and applicability in distribution modelling and species conservation. The choice of the target group fell on amphibians, because of their rapid decline worldwide and the frequent lack of guidelines for conservation strategies and regional-scale planning, which instead could be provided through an appropriate implementation of SDMs. Bufo bufo, Salamandrina perspicillata and Triturus carnifex were considered as target species, in order to perform our analysis with species having different ecological and distributional characteristics. The study area is the "Gran Sasso-Monti della Laga" National Park, which hosts 15 Natura 2000 sites and represents one of the most important biodiversity hotspots in Europe. Our results show that the model calibration ameliorates when using the target-group based pseudo-absences compared to the random ones, especially when applying the WTGB. Contrarily, model discrimination did not significantly vary in a consistent way among the three approaches with respect to the tree target species. Both WTGB and RDM clearly isolate the highly contributing variables, supplying many relevant indications for species conservation actions. Moreover, the assessment of pairwise variable interactions and their three-dimensional visualization further increase the amount of useful information for protected areas' managers. Finally, we suggest the use of RDM as an admissible alternative when it is not possible to individuate a suitable set of

  10. Modeling Forest Structural Parameters in the Mediterranean Pines of Central Spain using QuickBird-2 Imagery and Classification and Regression Tree Analysis (CART

    Directory of Open Access Journals (Sweden)

    José A. Delgado

    2012-01-01

    Full Text Available Forest structural parameters such as quadratic mean diameter, basal area, and number of trees per unit area are important for the assessment of wood volume and biomass and represent key forest inventory attributes. Forest inventory information is required to support sustainable management, carbon accounting, and policy development activities. Digital image processing of remotely sensed imagery is increasingly utilized to assist traditional, more manual, methods in the estimation of forest structural attributes over extensive areas, also enabling evaluation of change over time. Empirical attribute estimation with remotely sensed data is frequently employed, yet with known limitations, especially over complex environments such as Mediterranean forests. In this study, the capacity of high spatial resolution (HSR imagery and related techniques to model structural parameters at the stand level (n = 490 in Mediterranean pines in Central Spain is tested using data from the commercial satellite QuickBird-2. Spectral and spatial information derived from multispectral and panchromatic imagery (2.4 m and 0.68 m sided pixels, respectively served to model structural parameters. Classification and Regression Tree Analysis (CART was selected for the modeling of attributes. Accurate models were produced of quadratic mean diameter (QMD (R2 = 0.8; RMSE = 0.13 m with an average error of 17% while basal area (BA models produced an average error of 22% (RMSE = 5.79 m2/ha. When the measured number of trees per unit area (N was categorized, as per frequent forest management practices, CART models correctly classified 70% of the stands, with all other stands classified in an adjacent class. The accuracy of the attributes estimated here is expected to be better when canopy cover is more open and attribute values are at the lower end of the range present, as related in the pattern of the residuals found in this study. Our findings indicate that attributes derived from

  11. Predictors of success of external cephalic version and cephalic presentation at birth among 1253 women with non-cephalic presentation using logistic regression and classification tree analyses.

    Science.gov (United States)

    Hutton, Eileen K; Simioni, Julia C; Thabane, Lehana

    2017-08-01

    Among women with a fetus with a non-cephalic presentation, external cephalic version (ECV) has been shown to reduce the rate of breech presentation at birth and cesarean birth. Compared with ECV at term, beginning ECV prior to 37 weeks' gestation decreases the number of infants in a non-cephalic presentation at birth. The purpose of this secondary analysis was to investigate factors associated with a successful ECV procedure and to present this in a clinically useful format. Data were collected as part of the Early ECV Pilot and Early ECV2 Trials, which randomized 1776 women with a fetus in breech presentation to either early ECV (34-36 weeks' gestation) or delayed ECV (at or after 37 weeks). The outcome of interest was successful ECV, defined as the fetus being in a cephalic presentation immediately following the procedure, as well as at the time of birth. The importance of several factors in predicting successful ECV was investigated using two statistical methods: logistic regression and classification and regression tree (CART) analyses. Among nulliparas, non-engagement of the presenting part and an easily palpable fetal head were independently associated with success. Among multiparas, non-engagement of the presenting part, gestation less than 37 weeks and an easily palpable fetal head were found to be independent predictors of success. These findings were consistent with results of the CART analyses. Regardless of parity, descent of the presenting part was the most discriminating factor in predicting successful ECV and cephalic presentation at birth. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

  12. Estimating Dbh of Trees Employing Multiple Linear Regression of the best Lidar-Derived Parameter Combination Automated in Python in a Natural Broadleaf Forest in the Philippines

    Science.gov (United States)

    Ibanez, C. A. G.; Carcellar, B. G., III; Paringit, E. C.; Argamosa, R. J. L.; Faelga, R. A. G.; Posilero, M. A. V.; Zaragosa, G. P.; Dimayacyac, N. A.

    2016-06-01

    Diameter-at-Breast-Height Estimation is a prerequisite in various allometric equations estimating important forestry indices like stem volume, basal area, biomass and carbon stock. LiDAR Technology has a means of directly obtaining different forest parameters, except DBH, from the behavior and characteristics of point cloud unique in different forest classes. Extensive tree inventory was done on a two-hectare established sample plot in Mt. Makiling, Laguna for a natural growth forest. Coordinates, height, and canopy cover were measured and types of species were identified to compare to LiDAR derivatives. Multiple linear regression was used to get LiDAR-derived DBH by integrating field-derived DBH and 27 LiDAR-derived parameters at 20m, 10m, and 5m grid resolutions. To know the best combination of parameters in DBH Estimation, all possible combinations of parameters were generated and automated using python scripts and additional regression related libraries such as Numpy, Scipy, and Scikit learn were used. The combination that yields the highest r-squared or coefficient of determination and lowest AIC (Akaike's Information Criterion) and BIC (Bayesian Information Criterion) was determined to be the best equation. The equation is at its best using 11 parameters at 10mgrid size and at of 0.604 r-squared, 154.04 AIC and 175.08 BIC. Combination of parameters may differ among forest classes for further studies. Additional statistical tests can be supplemented to help determine the correlation among parameters such as Kaiser- Meyer-Olkin (KMO) Coefficient and the Barlett's Test for Spherecity (BTS).

  13. Understanding how roadside concentrations of NOx are influenced by the background levels, traffic density, and meteorological conditions using Boosted Regression Trees

    Science.gov (United States)

    Sayegh, Arwa; Tate, James E.; Ropkins, Karl

    2016-02-01

    Oxides of Nitrogen (NOx) is a major component of photochemical smog and its constituents are considered principal traffic-related pollutants affecting human health. This study investigates the influence of background concentrations of NOx, traffic density, and prevailing meteorological conditions on roadside concentrations of NOx at UK urban, open motorway, and motorway tunnel sites using the statistical approach Boosted Regression Trees (BRT). BRT models have been fitted using hourly concentration, traffic, and meteorological data for each site. The models predict, rank, and visualise the relationship between model variables and roadside NOx concentrations. A strong relationship between roadside NOx and monitored local background concentrations is demonstrated. Relationships between roadside NOx and other model variables have been shown to be strongly influenced by the quality and resolution of background concentrations of NOx, i.e. if it were based on monitored data or modelled prediction. The paper proposes a direct method of using site-specific fundamental diagrams for splitting traffic data into four traffic states: free-flow, busy-flow, congested, and severely congested. Using BRT models, the density of traffic (vehicles per kilometre) was observed to have a proportional influence on the concentrations of roadside NOx, with different fitted regression line slopes for the different traffic states. When other influences are conditioned out, the relationship between roadside concentrations and ambient air temperature suggests NOx concentrations reach a minimum at around 22 °C with high concentrations at low ambient air temperatures which could be associated to restricted atmospheric dispersion and/or to changes in road traffic exhaust emission characteristics at low ambient air temperatures. This paper uses BRT models to study how different critical factors, and their relative importance, influence the variation of roadside NOx concentrations. The paper

  14. Identifying changes in dissolved organic matter content and characteristics by fluorescence spectroscopy coupled with self-organizing map and classification and regression tree analysis during wastewater treatment.

    Science.gov (United States)

    Yu, Huibin; Song, Yonghui; Liu, Ruixia; Pan, Hongwei; Xiang, Liancheng; Qian, Feng

    2014-10-01

    The stabilization of latent tracers of dissolved organic matter (DOM) of wastewater was analyzed by three-dimensional excitation-emission matrix (EEM) fluorescence spectroscopy coupled with self-organizing map and classification and regression tree analysis (CART) in wastewater treatment performance. DOM of water samples collected from primary sedimentation, anaerobic, anoxic, oxic and secondary sedimentation tanks in a large-scale wastewater treatment plant contained four fluorescence components: tryptophan-like (C1), tyrosine-like (C2), microbial humic-like (C3) and fulvic-like (C4) materials extracted by self-organizing map. These components showed good positive linear correlations with dissolved organic carbon of DOM. C1 and C2 were representative components in the wastewater, and they were removed to a higher extent than those of C3 and C4 in the treatment process. C2 was a latent parameter determined by CART to differentiate water samples of oxic and secondary sedimentation tanks from the successive treatment units, indirectly proving that most of tyrosine-like material was degraded by anaerobic microorganisms. C1 was an accurate parameter to comprehensively separate the samples of the five treatment units from each other, indirectly indicating that tryptophan-like material was decomposed by anaerobic and aerobic bacteria. EEM fluorescence spectroscopy in combination with self-organizing map and CART analysis can be a nondestructive effective method for characterizing structural component of DOM fractions and monitoring organic matter removal in wastewater treatment process. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Relação entre diferentes caracteres de plantas jovens de seringueira Correlations and regressions studies among juvenile rubber tree characters

    Directory of Open Access Journals (Sweden)

    César Lavorenti

    1990-01-01

    Full Text Available O presente trabalho foi realizado com o objetivo de determinar a existência e as magnitudes de correlações e regressões lineares simples em plântulas jovens de seringueira (Hevea spp., para melhor condução de seleção nos futuros trabalhos de melhoramento. Foram utilizadas médias de produção de borracha seca por plântulas por corte, através do teste Hamaker-Morris-Mann (P; circunferência do caule (CC; espessura de casca (EC; número de anéis (NA; diâmetro dos vasos (DV; densidade dos vasos laticíleros (D e distância média entre anéis de vasos consecutivos (DMEAVC em um viveiro de cruzamento com três anos e meio de idade. Os resultados mostraram, entre outros fatores, que as correlações lineares simples de P com CC, EC, NA, D, DV e DMEAVC foram, respectivamente, r =t 0,61, 0,34, 0,28, 0,29, 0,43 e -0,13. As correlações de CC com EC, NA, D, DV e DMEAVC foram: 0,65, 0,22, 0,37, 0,33 e 0,096 respectivamente. Estudos de regressão linear simples de P com CC, EC, NA, DV, D e DMEAVC sugerem que CC foi o caráter independente mais significativo, contribuindo com 36% da variação em P. Em relação ao vigor, a regressão de CC com os respectivos caracteres sugere que EC foi o único caráter que contribuiu significativamente para a variação de CC com 42%. As altas correlações observadas da produção com circunferência do caule e com espessura de casca evidenciam a possibilidade de obter genótipos jovens de boa capacidade produtiva e grande vigor, através de seleção precoce dessas variáveis.This study was undertaken aiming to determine the existence of linear correlations, based on simple regression studies for a better improvement of young rubber tree (Hevea spp. breeding and selection. The characters studied were: yield of dry rubber per tapping by Hamaker-Morris-Mann test tapping (P, mean gurth (CC, bark thickness (EC, number of latex vessel rings (NA, diameter of latex vesseis (DV, density of latex vesseis per 5mm

  16. [Study on sensitivity of climatic factors on influenza A (H1N1) based on classification and regression tree and wavelet analysis].

    Science.gov (United States)

    Xiao, Hong; Lin, Xiao-ling; Dai, Xiang-yu; Gao, Li-dong; Chen, Bi-yun; Zhang, Xi-xing; Zhu, Pei-juan; Tian, Huai-yu

    2012-05-01

    To analyze the periodicity of pandemic influenza A (H1N1) in Changsha in year 2009 and its correlation with sensitive climatic factors. The information of 5439 cases of influenza A (H1N1) and synchronous meteorological data during the period between May 22th and December 31st in year 2009 (223 days in total) in Changsha city were collected. The classification and regression tree (CART) was employed to screen the sensitive climatic factors on influenza A (H1N1); meanwhile, cross wavelet transform and wavelet coherence analysis were applied to assess and compare the periodicity of the pandemic disease and its association with the time-lag phase features of the sensitive climatic factors. The results of CART indicated that the daily minimum temperature and daily absolute humidity were the sensitive climatic factors for the popularity of influenza A (H1N1) in Changsha. The peak of the incidence of influenza A (H1N1) was in the period between October and December (Median (M) = 44.00 cases per day), simultaneously the daily minimum temperature (M = 13°C) and daily absolute humidity (M = 6.69 g/m(3)) were relatively low. The results of wavelet analysis demonstrated that a period of 16 days was found in the epidemic threshold in Changsha, while the daily minimum temperature and daily absolute humidity were the relatively sensitive climatic factors. The number of daily reported patients was statistically relevant to the daily minimum temperature and daily absolute humidity. The frequency domain was mostly in the period of (16 ± 2) days. In the initial stage of the disease (from August 9th and September 8th), a 6-day lag was found between the incidence and the daily minimum temperature. In the peak period of the disease, the daily minimum temperature and daily absolute humidity were negatively relevant to the incidence of the disease. In the pandemic period, the incidence of influenza A (H1N1) showed periodic features; and the sensitive climatic factors did have a "driving

  17. Repeated measurements of blood lactate concentration as a prognostic marker in horses with acute colitis evaluated with classification and regression trees (CART) and random forest analysis

    DEFF Research Database (Denmark)

    Petersen, Mette Bisgaard; Tolver, Anders; Husted, Louise

    2016-01-01

    -off value of 7 mmol/L had a sensitivity of 0.66 and a specificity of 0.92 in predicting survival. In independent test data, the sensitivity was 0.69 and the specificity was 0.76. At the observed survival rate (38%), the optimal decision tree identified horses as non-survivors when the Lac at admission...... admitted with acute colitis (trees, as well as random...

  18. A Classification Regression Tree Analysis to Reduce Balance Impairments and Falls in the Older population: Impact on Resource Utilization and Clinical Decision-Making in USA Rehabilitation Service Delivery

    Directory of Open Access Journals (Sweden)

    Lucinda Pfalzer

    2013-06-01

    Full Text Available Background/Purpose: Over 1/3 of adults over age 65 experiences at least one fall each year. This pilot report uses a classification regression tree analysis (CART to model the outcomes for balance/risk of falls from the Gentiva® Safe Strides® Program (SSP. Methods/Outcomes: SSP is a home-based balance/fall prevention program designed to treat root causes of a patient

  19. Dual Regression

    OpenAIRE

    Spady, Richard; Stouli, Sami

    2012-01-01

    We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

  20. Hybrid regression trees applied to the monitoring of dynamic safety of isolated networks with large eolic production contribution; Utilizacao de arvores de regressao hibridas na monitorizacao da seguranca dinamica de redes isoladas com grande producao eolica

    Energy Technology Data Exchange (ETDEWEB)

    Lopes, J.A Pecas; Vasconcelos, Maria Helena O.P. de [Instituto de Engenharia de Sistemas e Computadores (INESC), Porto (Portugal). E-mail: jpl@riff.fe.up.pt; hvasconcelos@inescn.pt

    1999-07-01

    This paper describes in a synthetic manner the technology adopted to define structures used in the fast evaluation of dynamic safety of isolated network with high level of eolic production contribution. This methodology uses hybrid regression trees, which allows the quantification the endurance connected to the dynamic behavior of these networks by emulating the frequency minimum deviation that will be experienced by the system when submitted toa pre-defined perturbation. Also, new procedures for data automatic generation are presented, which will be used for construction and measurements of the evaluation structures performance. The paper describes the Terceira island - Acores archipelago network study case.

  1. Regression Phalanxes

    OpenAIRE

    Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

    2017-01-01

    Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

  2. Comparing Kriging and Regression Approaches for Mapping Soil Clay Content in a diverse Danish Landscape

    DEFF Research Database (Denmark)

    Adhikari, Kabindra; Bou Kheir, Rania; Greve, Mette Balslev

    2013-01-01

    Information on the spatial variability of soil texture including soil clay content in a landscape is very important for agricultural and environmental use. Different prediction techniques are available to assess and map spatial variability of soil properties, but selecting the most suitable techn...... the prediction in OKst compared with that in OK, whereas RT showed the lowest performance of all (R2 = 0.52; RMSE = 0.52; and RPD = 1.17). We found RKrr to be an effective prediction method and recommend this method for any future soil mapping activities in Denmark....... technique at a given site has always been a major issue in all soil mapping applications. We studied the prediction performance of ordinary kriging (OK), stratified OK (OKst), regression trees (RT), and rule-based regression kriging (RKrr) for digital mapping of soil clay content at 30.4-m grid size using 6...

  3. Aproximación a la metodología basada en árboles de decisión (CART: Mortalidad hospitalaria del infarto agudo de miocardio Approach to the methodology of classification and regression trees

    Directory of Open Access Journals (Sweden)

    Javier Trujillano

    2008-02-01

    Full Text Available Objetivo: : Realizar una aproximación a la metodología de árboles de decisión tipo CART (Classification and Regression Trees desarrollando un modelo para calcular la probabilidad de muerte hospitalaria en infarto agudo de miocardio (IAM. Método: Se utiliza el conjunto mínimo básico de datos al alta hospitalaria (CMBD de Andalucía, Cataluña, Madrid y País Vasco de los años 2001 y 2002, que incluye los casos con IAM como diagnóstico principal. Los 33.203 pacientes se dividen aleatoriamente (70 y 30 % en grupo de desarrollo (GD = 23.277 y grupo de validación (GV = 9.926. Como CART se utiliza un modelo inductivo basado en el algoritmo de Breiman, con análisis de sensibilidad mediante el índice de Gini y sistema de validación cruzada. Se compara con un modelo de regresión logística (RL y una red neuronal artificial (RNA (multilayer perceptron. Los modelos desarrollados se contrastan en el GV y sus propiedades se comparan con el área bajo la curva ROC (ABC (intervalo de confianza del 95%. Resultados: En el GD el CART con ABC = 0,85 (0,86-0,88, RL 0,87 (0,86-0,88 y RNA 0,85 (0,85-0,86. En el GV el CART con ABC = 0,85 (0,85-0,88, RL 0,86 (0,85-0,88 y RNA 0,84 (0,83-0,86. Conclusiones: Los 3 modelos obtienen resultados similares en su capacidad de discriminación. El modelo CART ofrece como ventaja su simplicidad de uso y de interpretación, ya que las reglas de decisión que generan pueden aplicarse sin necesidad de procesos matemáticos.Objective: To provide an overview of decision trees based on CART (Classification and Regression Trees methodology. As an example, we developed a CART model intended to estimate the probability of intrahospital death from acute myocardial infarction (AMI. Method: We employed the minimum data set (MDS of Andalusia, Catalonia, Madrid and the Basque Country (2001-2002, which included 33,203 patients with a diagnosis of AMI. The 33,203 patients were randomly divided (70% and 30% into the development (DS

  4. Autistic Regression

    Science.gov (United States)

    Matson, Johnny L.; Kozlowski, Alison M.

    2010-01-01

    Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

  5. The Application of Classification and Regression Trees for the Triage of Women for Referral to Colposcopy and the Estimation of Risk for Cervical Intraepithelial Neoplasia: A Study Based on 1625 Cases with Incomplete Data from Molecular Tests

    Directory of Open Access Journals (Sweden)

    Abraham Pouliakis

    2015-01-01

    Full Text Available Objective. Nowadays numerous ancillary techniques detecting HPV DNA and mRNA compete with cytology; however no perfect test exists; in this study we evaluated classification and regression trees (CARTs for the production of triage rules and estimate the risk for cervical intraepithelial neoplasia (CIN in cases with ASCUS+ in cytology. Study Design. We used 1625 cases. In contrast to other approaches we used missing data to increase the data volume, obtain more accurate results, and simulate real conditions in the everyday practice of gynecologic clinics and laboratories. The proposed CART was based on the cytological result, HPV DNA typing, HPV mRNA detection based on NASBA and flow cytometry, p16 immunocytochemical expression, and finally age and parous status. Results. Algorithms useful for the triage of women were produced; gynecologists could apply these in conjunction with available examination results and conclude to an estimation of the risk for a woman to harbor CIN expressed as a probability. Conclusions. The most important test was the cytological examination; however the CART handled cases with inadequate cytological outcome and increased the diagnostic accuracy by exploiting the results of ancillary techniques even if there were inadequate missing data. The CART performance was better than any other single test involved in this study.

  6. The Application of Classification and Regression Trees for the Triage of Women for Referral to Colposcopy and the Estimation of Risk for Cervical Intraepithelial Neoplasia: A Study Based on 1625 Cases with Incomplete Data from Molecular Tests.

    Science.gov (United States)

    Pouliakis, Abraham; Karakitsou, Efrossyni; Chrelias, Charalampos; Pappas, Asimakis; Panayiotides, Ioannis; Valasoulis, George; Kyrgiou, Maria; Paraskevaidis, Evangelos; Karakitsos, Petros

    2015-01-01

    Nowadays numerous ancillary techniques detecting HPV DNA and mRNA compete with cytology; however no perfect test exists; in this study we evaluated classification and regression trees (CARTs) for the production of triage rules and estimate the risk for cervical intraepithelial neoplasia (CIN) in cases with ASCUS+ in cytology. We used 1625 cases. In contrast to other approaches we used missing data to increase the data volume, obtain more accurate results, and simulate real conditions in the everyday practice of gynecologic clinics and laboratories. The proposed CART was based on the cytological result, HPV DNA typing, HPV mRNA detection based on NASBA and flow cytometry, p16 immunocytochemical expression, and finally age and parous status. Algorithms useful for the triage of women were produced; gynecologists could apply these in conjunction with available examination results and conclude to an estimation of the risk for a woman to harbor CIN expressed as a probability. The most important test was the cytological examination; however the CART handled cases with inadequate cytological outcome and increased the diagnostic accuracy by exploiting the results of ancillary techniques even if there were inadequate missing data. The CART performance was better than any other single test involved in this study.

  7. Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

    Directory of Open Access Journals (Sweden)

    Santana Isabel

    2011-08-01

    Full Text Available Abstract Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI, but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.

  8. Linear regression

    CERN Document Server

    Olive, David J

    2017-01-01

    This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

  9. Classification and Regression Tree Analysis of Clinical Patterns that Predict Survival in 127 Chinese Patients with Advanced Non-small Cell Lung Cancer Treated by Gefitinib Who Failed to Previous Chemotherapy

    Directory of Open Access Journals (Sweden)

    Ziping WANG

    2011-09-01

    Full Text Available Background and objective It has been proven that gefitinib produces only 10%-20% tumor regression in heavily pretreated, unselected non-small cell lung cancer (NSCLC patients as the second- and third-line setting. Asian, female, nonsmokers and adenocarcinoma are favorable factors; however, it is difficult to find a patient satisfying all the above clinical characteristics. The aim of this study is to identify novel predicting factors, and to explore the interactions between clinical variables and their impact on the survival of Chinese patients with advanced NSCLC who were heavily treated with gefitinib in the second- or third-line setting. Methods The clinical and follow-up data of 127 advanced NSCLC patients referred to the Cancer Hospital & Institute, Chinese Academy of Medical Sciences from March 2005 to March 2010 were analyzed. Multivariate analysis of progression-free survival (PFS was performed using recursive partitioning, which is referred to as the classification and regression tree (CART analysis. Results The median PFS of 127 eligible consecutive advanced NSCLC patients was 8.0 months (95%CI: 5.8-10.2. CART was performed with an initial split on first-line chemotherapy outcomes and a second split on patients’ age. Three terminal subgroups were formed. The median PFS of the three subsets ranged from 1.0 month (95%CI: 0.8-1.2 for those with progressive disease outcome after the first-line chemotherapy subgroup, 10 months (95%CI: 7.0-13.0 in patients with a partial response or stable disease in first-line chemotherapy and age <70, and 22.0 months for patients obtaining a partial response or stable disease in first-line chemotherapy at age 70-81 (95%CI: 3.8-40.1. Conclusion Partial response, stable disease in first-line chemotherapy and age ≥ 70 are closely correlated with long-term survival treated by gefitinib as a second- or third-line setting in advanced NSCLC. CART can be used to identify previously unappreciated patient

  10. DIF Trees: Using Classification Trees to Detect Differential Item Functioning

    Science.gov (United States)

    Vaughn, Brandon K.; Wang, Qiu

    2010-01-01

    A nonparametric tree classification procedure is used to detect differential item functioning for items that are dichotomously scored. Classification trees are shown to be an alternative procedure to detect differential item functioning other than the use of traditional Mantel-Haenszel and logistic regression analysis. A nonparametric…

  11. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Study on the Image Quality Comparison between in Digital RT and Film RT

    International Nuclear Information System (INIS)

    Park, Sang Ki; Ahn, Yean Shik; Gil, Doo Song

    2011-01-01

    Conventional film radiographic test has been generally and widely used in the inspection on the weldment for quality assurance. On the other hand, since the analog RT is well known for typical time and cost consuming method with complex process of inspection, the industry has researched various ways how to improve radiographic test technology. In this study, we verified the fact that digital RT provides a lot more benefit in effectively detecting defects, ever film details, through digital processing of image enhancement, compared to film RT. As a result, we reached conclusion that digital RT is positively able to replace the film RT in industry in part or in whole

  13. Node Ranking Tool - NoRT

    Science.gov (United States)

    2018-03-23

    NoRT) that was developed as part of the Applied Network Science 6.2 base program work unit at NRL, Code 5580. We explain the theory of NoRT and how...to use it. 23-03-2018 Memorandum Report TOPSIS, Social Network, Sensor Network, Centrality, Diffusion, Disease, Virus, Expectation , Pandemic...base program work unit at NRL. We explain the theory of NoRT and how to use it. Index Terms TOPSIS, Social Network, Sensor Network, Centrality, Diffusion

  14. Regression: A Bibliography.

    Science.gov (United States)

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  15. rt: Berliner Messe / Rob Cowan

    Index Scriptorium Estoniae

    Cowan, Rob

    1998-01-01

    Uuest heliplaadist "Pärt: Berliner Messe. The Beatitudes. Annum per Annum. Magnificat. Seven Magnificat Antiphons. De profundis. Polyphony / Steven Layton with Andrew Lucas" Hyperion CDA66960 (74 minutes:DDD)

  16. Arvo Pärt. Litany / Peter Korfmacher

    Index Scriptorium Estoniae

    Korfmacher, Peter

    1996-01-01

    Uuest heliplaadist "Pärt, Arvo. Litany; Psalom; Trisagion. Hilliard Ensemble, Estonian Philharmonic Chamber Choir, Tallinn Chamber Orchestra, Tõnu Kaljuste"; Lithuanian Chamber Orchestra, Saulius Sondeckis. ECM 1592/449 810-2

  17. rt: Fratres / Robert Cowan

    Index Scriptorium Estoniae

    Cowan, Robert

    1995-01-01

    Uuest heliplaadist "Pärt: Fratres (seven versions). Festina Lente. Cantus in Memory of Benjamin Britten. Summa. Peter Manning (vn.), France Springuel (vc.), Mireille Gleizes (pf.), I Fiamminghi. Telare CD CD80387 (79 minutes)

  18. Flowering Trees

    Indian Academy of Sciences (India)

    Flowering Trees. Boswellia serrata Roxb. ex Colebr. (Indian Frankincense tree) of Burseraceae is a large-sized deciduous tree that is native to India. Bark is thin, greenish-ash-coloured that exfoliates into smooth papery flakes. Stem exudes pinkish resin ... Fruit is a three-valved capsule. A green gum-resin exudes from the ...

  19. Flowering Trees

    Indian Academy of Sciences (India)

    IAS Admin

    Flowering Trees. Ailanthus excelsa Roxb. (INDIAN TREE OF. HEAVEN) of Simaroubaceae is a lofty tree with large pinnately compound alternate leaves, which are ... inflorescences, unisexual and greenish-yellow. Fruits are winged, wings many-nerved. Wood is used in making match sticks. 1. Male flower; 2. Female flower.

  20. Flowering Trees

    Indian Academy of Sciences (India)

    Flowering Trees. Gyrocarpus americanus Jacq. (Helicopter Tree) of Hernandiaceae is a moderate size deciduous tree that grows to about 12 m in height with a smooth, shining, greenish-white bark. The leaves are ovate, rarely irregularly ... flowers which are unpleasant smelling. Fruit is a woody nut with two long thin wings.

  1. Flowering Trees

    Indian Academy of Sciences (India)

    More Details Fulltext PDF. Volume 8 Issue 8 August 2003 pp 112-112 Flowering Trees. Zizyphus jujuba Lam. of Rhamnaceae · More Details Fulltext PDF. Volume 8 Issue 9 September 2003 pp 97-97 Flowering Trees. Moringa oleifera · More Details Fulltext PDF. Volume 8 Issue 10 October 2003 pp 100-100 Flowering Trees.

  2. Tree compression with top trees

    DEFF Research Database (Denmark)

    Bille, Philip; Gørtz, Inge Li; Landau, Gad M.

    2013-01-01

    We introduce a new compression scheme for labeled trees based on top trees [3]. Our compression scheme is the first to simultaneously take advantage of internal repeats in the tree (as opposed to the classical DAG compression that only exploits rooted subtree repeats) while also supporting fast...

  3. Tree compression with top trees

    DEFF Research Database (Denmark)

    Bille, Philip; Gørtz, Inge Li; Landau, Gad M.

    2015-01-01

    We introduce a new compression scheme for labeled trees based on top trees. Our compression scheme is the first to simultaneously take advantage of internal repeats in the tree (as opposed to the classical DAG compression that only exploits rooted subtree repeats) while also supporting fast...

  4. Standardized comparison of the relative impacts of HIV-1 reverse transcriptase (RT) mutations on nucleoside RT inhibitor susceptibility.

    Science.gov (United States)

    Melikian, George L; Rhee, Soo-Yon; Taylor, Jonathan; Fessel, W Jeffrey; Kaufman, David; Towner, William; Troia-Cancio, Paolo V; Zolopa, Andrew; Robbins, Gregory K; Kagan, Ron; Israelski, Dennis; Shafer, Robert W

    2012-05-01

    Determining the phenotypic impacts of reverse transcriptase (RT) mutations on individual nucleoside RT inhibitors (NRTIs) has remained a statistical challenge because clinical NRTI-resistant HIV-1 isolates usually contain multiple mutations, often in complex patterns, complicating the task of determining the relative contribution of each mutation to HIV drug resistance. Furthermore, the NRTIs have highly variable dynamic susceptibility ranges, making it difficult to determine the relative effect of an RT mutation on susceptibility to different NRTIs. In this study, we analyzed 1,273 genotyped HIV-1 isolates for which phenotypic results were obtained using the PhenoSense assay (Monogram, South San Francisco, CA). We used a parsimonious feature selection algorithm, LASSO, to assess the possible contributions of 177 mutations that occurred in 10 or more isolates in our data set. We then used least-squares regression to quantify the impact of each LASSO-selected mutation on each NRTI. Our study provides a comprehensive view of the most common NRTI resistance mutations. Because our results were standardized, the study provides the first analysis that quantifies the relative phenotypic effects of NRTI resistance mutations on each of the NRTIs. In addition, the study contains new findings on the relative impacts of thymidine analog mutations (TAMs) on susceptibility to abacavir and tenofovir; the impacts of several known but incompletely characterized mutations, including E40F, V75T, Y115F, and K219R; and a tentative role in reduced NRTI susceptibility for K64H, a novel NRTI resistance mutation.

  5. [Analysis of the characteristics of the older adults with depression using data mining decision tree analysis].

    Science.gov (United States)

    Park, Myonghwa; Choi, Sora; Shin, A Mi; Koo, Chul Hoi

    2013-02-01

    The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.

  6. MINIX4RT: Real-Time Semaphores

    OpenAIRE

    Pessolani, Pablo Andrés

    2007-01-01

    MINIX4RT es una extensión del conocido Sistema Operativo MINIX que incorpora servicios de Tiempo Real Estricto en un nuevo microkernel pero manteniendo compatibilidad con las versiones anteriores del MINIX estándar. Los semáforos son el mecanismo primitivo para la sincronización y exclusion mutua en varios sistemas operativos, pero MINIX no brinda esa facilidad. Se adicionaron semáforos a MINIX4RT y, como éste es un Sistema Operativo de Tiempo Real, deben reunir ciertos requisitos de procesam...

  7. Artist - analytical RT inspection simulation tool

    International Nuclear Information System (INIS)

    Bellon, C.; Jaenisch, G.R.

    2007-01-01

    The computer simulation of radiography is applicable for different purposes in NDT such as for the qualification of NDT systems, the prediction of its reliability, the optimization of system parameters, feasibility analysis, model-based data interpretation, education and training of NDT/NDE personnel, and others. Within the framework of the integrated project FilmFree the radiographic testing (RT) simulation software developed by BAM is being further developed to meet practical requirements for inspection planning in digital industrial radiology. It combines analytical modelling of the RT inspection process with the CAD-orientated object description applicable to various industrial sectors such as power generation, railways and others. (authors)

  8. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  9. Tree Nut Allergies

    Science.gov (United States)

    ... Blog Vision Awards Common Allergens Tree Nut Allergy Tree Nut Allergy Learn about tree nut allergy, how ... a Tree Nut Label card . Allergic Reactions to Tree Nuts Tree nuts can cause a severe and ...

  10. rt, Arvo. Fratres / Rainer Wagner

    Index Scriptorium Estoniae

    Wagner, Rainer

    1995-01-01

    Uuest heliplaadist "Pärt, Arvo. Fratres, Cantus (in Memory of Benjamin Britten), summa, Festina Lente; Peter Manning, France Springuel, Mireille Gleizes, Huub Righarts, I Fiamminghi, Rudolf Werthen" (AD: 1994) Telarc/in-akustik CD 80 387 (WD: 79'00")

  11. rt, Arvo: "Litany" / Barry Witherden

    Index Scriptorium Estoniae

    Witherden, Barry

    1996-01-01

    Uuest heliplaadist "Pärt, Arvo: "Litany". Litany. Psalom. Trisagion. The Hilliard Ensemble, Tallinn Chamber Orchestra, Estonian Philharmonic Chamber Orchestra, Estonian Philharmonic Chamber Choir, Tõnu Kaljuste. Orchestre de chambre de Lituanie, Saulius Sondeckis". ECM New Series ECM 1592, distribution Polygram 449 810-2 (CD:158F)

  12. Forført af hjernen?

    DEFF Research Database (Denmark)

    Lieberoth, Andreas

    2013-01-01

    Blandingen af offentlig interesse, gode mediehistorier og smarte sælgere har ført til sejlivede neuromyter, der ikke bare distraherer almindelige mennesker, men også fører til udbredte misforståelser blandt professionelle som lærere og plejepersonale. I bedste fald leder neuromyter til spild af t...

  13. rt, Arvo: "Litany" / Patric Wiklacz

    Index Scriptorium Estoniae

    Wiklacz, Patric

    1996-01-01

    Uuest heliplaadist "Pärt, Arvo: "Litany". Litany. Psalom. Trisagion. The Hilliard Ensemble, Orchestre de chambre de Tallinn, Choeur de chambre Philharmonique d'Estonie, Tõnu Kaljuste. Orchestre de chambre de Lituanie, Saulius Sondeckis. ECM New Series ECM 1592, distribution Polygram 449 810-2 (CD:158F)

  14. Flowering Trees

    Indian Academy of Sciences (India)

    medium-sized handsome tree with a straight bole that branches at the top. Leaves are once pinnate, with two to three pairs of leaflets. Young parts of the tree are velvety. Inflorescence is a branched raceme borne at the branch ends. Flowers are large, white, attractive, and fragrant. Corolla is funnel-shaped. Fruit is an ...

  15. Flowering Trees

    Indian Academy of Sciences (India)

    Cassia siamia Lamk. (Siamese tree senna) of Caesalpiniaceae is a small or medium size handsome tree. Leaves are alternate, pinnately compound and glandular, upto 18 cm long with 8–12 pairs of leaflets. Inflorescence is axillary or terminal and branched. Flowering lasts for a long period from March to February. Fruit is ...

  16. Flowering Trees

    Indian Academy of Sciences (India)

    Flowering Trees. Cerbera manghasL. (SEA MANGO) of Apocynaceae is a medium-sized evergreen coastal tree with milky latex. The bark is grey-brown, thick and ... Fruit is large. (5–10 cm long), oval containing two flattened seeds and resembles a mango, hence the name Mangas or. Manghas. Leaves and fruits contain ...

  17. Flowering Trees

    Indian Academy of Sciences (India)

    user

    Flowering Trees. Gliricidia sepium(Jacq.) Kunta ex Walp. (Quickstick) of Fabaceae is a small deciduous tree with. Pinnately compound leaves. Flower are prroduced in large number in early summer on terminal racemes. They are attractive, pinkish-white and typically like bean flowers. Fruit is a few-seeded flat pod.

  18. Flowering Trees

    Indian Academy of Sciences (India)

    Flowering Trees. Acrocarpus fraxinifolius Wight & Arn. (PINK CEDAR, AUSTRALIAN ASH) of. Caesalpiniaceae is a lofty unarmed deciduous native tree that attains a height of 30–60m with buttresses. Bark is thin and light grey. Leaves are compound and bright red when young. Flowers in dense, erect, axillary racemes.

  19. Talking Trees

    Science.gov (United States)

    Tolman, Marvin

    2005-01-01

    Students love outdoor activities and will love them even more when they build confidence in their tree identification and measurement skills. Through these activities, students will learn to identify the major characteristics of trees and discover how the pace--a nonstandard measuring unit--can be used to estimate not only distances but also the…

  20. Drawing Trees

    DEFF Research Database (Denmark)

    Halkjær From, Andreas; Schlichtkrull, Anders; Villadsen, Jørgen

    2018-01-01

    We formally prove in Isabelle/HOL two properties of an algorithm for laying out trees visually. The first property states that removing layout annotations recovers the original tree. The second property states that nodes are placed at least a unit of distance apart. We have yet to formalize three...

  1. Flowering Trees

    Indian Academy of Sciences (India)

    Srimath

    Grevillea robusta A. Cunn. ex R. Br. (Sil- ver Oak) of Proteaceae is a daintily lacy ornamental tree while young and growing into a mighty tree (45 m). Young shoots are silvery grey and the leaves are fern- like. Flowers are golden-yellow in one- sided racemes (10 cm). Fruit is a boat- shaped, woody follicle.

  2. Regression analysis by example

    CERN Document Server

    Chatterjee, Samprit

    2012-01-01

    Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

  3. Phylogenetic trees

    OpenAIRE

    Baños, Hector; Bushek, Nathaniel; Davidson, Ruth; Gross, Elizabeth; Harris, Pamela E.; Krone, Robert; Long, Colby; Stewart, Allen; Walker, Robert

    2016-01-01

    We introduce the package PhylogeneticTrees for Macaulay2 which allows users to compute phylogenetic invariants for group-based tree models. We provide some background information on phylogenetic algebraic geometry and show how the package PhylogeneticTrees can be used to calculate a generating set for a phylogenetic ideal as well as a lower bound for its dimension. Finally, we show how methods within the package can be used to compute a generating set for the join of any two ideals.

  4. Classificação geométrica de galáxias bianeladas através do metódo CART (Classification And Regression Trees)

    Science.gov (United States)

    Ormeño, M. I.; Faúndez-Abans, M.; Cavada, G.

    2003-08-01

    A importância deste trabalho deve-se à seleção de objetos ainda não tratados particularmente como uma família e ao emprego de procedimento estatístico robusto que não precisa de pressupostos ou condições de contorno. Contribui, assim, ao melhor entendimento do cenário das Galáxias Aneladas do diagrama de Hubble via classificação e estudo de subclasses. Selecionaram-se 100 galáxias possuidoras de dois anéis do Catalog of Southern Ringed Galaxies compilado por Ronald Buta, de modo a construir uma amostra completa em termos de conhecimento dos semi-eixos dos anéis interno e externo projetados no plano do céu. Visando uma possível classificação destas galáxias aneladas normais em famílias de acordo com as características geométricas dos anéis, empregou-se primeiramente a Análise de Aglomerados (ferramenta de classificação: medições de semelhança em um espaço bidimensional) para explorar a possível existência de famílias. As variáveis analisadas foram: os diâmetros interiores menores d(I) e maiores D(I), os diâmetros exteriores menores d(E) e maiores D(E), e os ângulos de inclinação dos semi-eixos maiores interiores q(I) e exteriores q(E) dos anéis. Como metodologia de discriminação, empregou-se a construção de Árvores de Classificação. As árvores de classificação constituem um método de discriminação alternativo aos modelos clássicos, tais como a Análise Discriminante e a Regressão Logística, onde uma base de dados é dividida em partições (subgrupos) da árvore por ação de um predictor (variável específica). Os pacotes estatísticos utilizados para o processamento da informação foram: SAS versão 8.0 (Statistical Analisys System) e CART versão 3.6.3. Esta análise estatística sugere a existência de três possíveis famílias de galáxias bianeladas, com base apenas na geometria dos anéis. Como forma exploratória inicial deste resultado, a construção de um diagrama BT (magnitude total) versus o

  5. Decision trees in epidemiological research

    Directory of Open Access Journals (Sweden)

    Ashwini Venkatasubramaniam

    2017-09-01

    Full Text Available Abstract Background In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. Main text We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART technique and the newer Conditional Inference tree (CTree technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Conclusions Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation.

  6. Decision trees in epidemiological research.

    Science.gov (United States)

    Venkatasubramaniam, Ashwini; Wolfson, Julian; Mitchell, Nathan; Barnes, Timothy; JaKa, Meghan; French, Simone

    2017-01-01

    In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART) technique and the newer Conditional Inference tree (CTree) technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation.

  7. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

  8. Electron Tree

    DEFF Research Database (Denmark)

    Appelt, Ane L; Rønde, Heidi S

    2013-01-01

    The photo shows a close-up of a Lichtenberg figure – popularly called an “electron tree” – produced in a cylinder of polymethyl methacrylate (PMMA). Electron trees are created by irradiating a suitable insulating material, in this case PMMA, with an intense high energy electron beam. Upon discharge......, during dielectric breakdown in the material, the electrons generate branching chains of fractures on leaving the PMMA, producing the tree pattern seen. To be able to create electron trees with a clinical linear accelerator, one needs to access the primary electron beam used for photon treatments. We...... appropriated a linac that was being decommissioned in our department and dismantled the head to circumvent the target and ion chambers. This is one of 24 electron trees produced before we had to stop the fun and allow the rest of the accelerator to be disassembled....

  9. Flowering Trees

    Indian Academy of Sciences (India)

    Srimath

    shaped corolla. Fruit is large, ellipsoidal, green with a hard and smooth shell containing numerous flattened seeds, which are embedded in fleshy pulp. Calabash tree is commonly grown in the tropical gardens of the world as a botanical oddity.

  10. Understanding logistic regression analysis

    OpenAIRE

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

  11. Introduction to regression graphics

    CERN Document Server

    Cook, R Dennis

    2009-01-01

    Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

  12. Alternative Methods of Regression

    CERN Document Server

    Birkes, David

    2011-01-01

    Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

  13. Sodium sulphite inhibition of potato and cherry polyphenolics in nucleic acid extraction for virus detection by RT-PCR.

    Science.gov (United States)

    Singh, R P; Nie, X; Singh, M; Coffin, R; Duplessis, P

    2002-01-01

    Phenolic compounds from plant tissues inhibit reverse transcription-polymerase chain reaction (RT-PCR). Multiple-step protocols using several additives to inhibit polyphenolic compounds during nucleic acid extraction are common, but time consuming and laborious. The current research highlights that the inclusion of 0.65 to 0.70% of sodium sulphite in the extraction buffer minimizes the pigmentation of nucleic acid extracts and improves the RT-PCR detection of Potato virus Y (PVY) and Potato leafroll virus (PLRV) in potato (Solanum tuberosum) tubers and Prune dwarf virus (PDV) and Prunus necrotic ringspot virus (PNRSV) in leaves and bark in the sweet cherry (Prunus avium) tree. Substituting sodium sulphite in the nucleic acid extraction buffer eliminated the use of proteinase K during extraction. Reagents phosphate buffered saline (PBS)-Tween 20 and polyvinylpyrrolidone (PVP) were also no longer required during RT or PCR phase. The resultant nucleic acid extracts were suitable for both duplex and multiplex RT-PCR. This simple and less expensive nucleic acid extraction protocol has proved very effective for potato cv. Russet Norkotah, which contains a high amount of polyphenolics. Comparing commercially available RNA extraction kits (Catrimox and RNeasy), the sodium sulphite based extraction protocol yielded two to three times higher amounts of RNA, while maintaining comparable virus detection by RT-PCR. The sodium sulphite based extraction protocol was equally effective in potato tubers, and in leaves and bark from the cherry tree.

  14. Boosted beta regression.

    Directory of Open Access Journals (Sweden)

    Matthias Schmid

    Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

  15. Decision tree modeling using R.

    Science.gov (United States)

    Zhang, Zhongheng

    2016-08-01

    In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building.

  16. Understanding logistic regression analysis.

    Science.gov (United States)

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

  17. Applied linear regression

    CERN Document Server

    Weisberg, Sanford

    2013-01-01

    Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

  18. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  19. Flowering Trees

    Indian Academy of Sciences (India)

    deciduous tree with irregularly-shaped trunk, greyish-white scaly bark and milky latex. Leaves in opposite pairs are simple, oblong and whitish beneath. Flowers that occur in branched inflorescence are white, 2–. 3cm across and fragrant. Calyx is glandular inside. Petals bear numerous linear white scales, the corollary.

  20. Flowering Trees

    Indian Academy of Sciences (India)

    Berrya cordifolia (Willd.) Burret (Syn. B. ammonilla Roxb.) – Trincomali Wood of Tiliaceae is a tall evergreen tree with straight trunk, smooth brownish-grey bark and simple broad leaves. Inflorescence is much branched with white flowers. Stamens are many with golden yellow anthers. Fruit is a capsule with six spreading ...

  1. Flowering Trees

    Indian Academy of Sciences (India)

    Canthium parviflorum Lam. of Rubiaceae is a large shrub that often grows into a small tree with conspicuous spines. Leaves are simple, in pairs at each node and are shiny. Inflorescence is an axillary few-flowered cymose fascicle. Flowers are small (less than 1 cm across), 4-merous and greenish-white. Fruit is ellipsoid ...

  2. Flowering Trees

    Indian Academy of Sciences (India)

    sriranga

    Hook.f. ex Brandis (Yellow. Cadamba) of Rubiaceae is a large and handsome deciduous tree. Leaves are simple, large, orbicular, and drawn abruptly at the apex. Flowers are small, yellowish and aggregate into small spherical heads. The corolla is funnel-shaped with five stamens inserted at its mouth. Fruit is a capsule.

  3. Flowering Trees

    Indian Academy of Sciences (India)

    Celtis tetrandra Roxb. of Ulmaceae is a moderately large handsome deciduous tree with green branchlets and grayish-brown bark. Leaves are simple with three to four secondary veins running parallel to the mid vein. Flowers are solitary, male, female and bisexual and inconspicuous. Fruit is berry-like, small and globose ...

  4. Flowering Trees

    Indian Academy of Sciences (India)

    IAS Admin

    Aglaia elaeagnoidea (A.Juss.) Benth. of Meliaceae is a small-sized evergreen tree of both moist and dry deciduous forests. The leaves are alternate and pinnately compound, terminating in a single leaflet. Leaflets are more or less elliptic with entire margin. Flowers are small on branched inflorescence. Fruit is a globose ...

  5. Flowering Trees

    Indian Academy of Sciences (India)

    user

    Flowers are borne on stiff bunches terminally on short shoots. They are 2-3 cm across, white, sweet-scented with light-brown hairy sepals and many stamens. Loquat fruits are round or pear-shaped, 3-5 cm long and are edible. A native of China, Loquat tree is grown in parks as an ornamental and also for its fruits.

  6. Flowering Trees

    Indian Academy of Sciences (India)

    mid-sized slow-growing evergreen tree with spreading branches that form a dense crown. The bark is smooth, thick, dark and flakes off in large shreds. Leaves are thick, oblong, leathery and bright red when young. The female flowers are drooping and are larger than male flowers. Fruit is large, red in color and velvety.

  7. Flowering Trees

    Indian Academy of Sciences (India)

    Andira inermis (wright) DC. , Dog Almond of Fabaceae is a handsome lofty evergreen tree. Leaves are alternate and pinnately compound with 4–7 pairs of leaflets. Flowers are fragrant and are borne on compact branched inflorescences. Fruit is ellipsoidal one-seeded drupe that is peculiar to members of this family.

  8. Flowering Trees

    Indian Academy of Sciences (India)

    narrow towards base. Flowers are large and attrac- tive, but emit unpleasant foetid smell. They appear in small numbers on erect terminal clusters and open at night. Stamens are numerous, pink or white. Style is slender and long, terminating in a small stigma. Fruit is green, ovoid and indistinctly lobed. Flowering Trees.

  9. Flowering Trees

    Indian Academy of Sciences (India)

    Muntingia calabura L. (Singapore cherry) of. Elaeocarpaceae is a medium size handsome ever- green tree. Leaves are simple and alternate with sticky hairs. Flowers are bisexual, bear numerous stamens, white in colour and arise in the leaf axils. Fruit is a berry, edible with several small seeds embedded in a fleshy pulp ...

  10. ~{owering 'Trees

    Indian Academy of Sciences (India)

    . Stamens are fused into a purple staminal tube that is toothed. Fruit is about 0.5 in. across, nearly globose, generally 5-seeded, green but yellow when ripe, quite smooth at first but wrinkled in drying, remaining long on the tree ajier ripening.

  11. Tree Mortality

    Science.gov (United States)

    Mark J. Ambrose

    2012-01-01

    Tree mortality is a natural process in all forest ecosystems. However, extremely high mortality also can be an indicator of forest health issues. On a regional scale, high mortality levels may indicate widespread insect or disease problems. High mortality may also occur if a large proportion of the forest in a particular region is made up of older, senescent stands....

  12. Flowering Trees

    Indian Academy of Sciences (India)

    Guaiacum officinale L. (LIGNUM-VITAE) of Zygophyllaceae is a dense-crowned, squat, knobbly, rough and twisted medium-sized ev- ergreen tree with mottled bark. The wood is very hard and resinous. Leaves are compound. The leaflets are smooth, leathery, ovate-ellipti- cal and appear in two pairs. Flowers (about 1.5.

  13. Power lies in interdisciplinary cooperation / Kärt Summatavet ; interv. Kärt Blumberg

    Index Scriptorium Estoniae

    Summatavet, Kärt, 1963-

    2008-01-01

    Ehtekunstnik Kärt Summatavet oma uudsest meetodist ehete valmistamisel - paberil oleva kujutise ülekandmisest arvuti abil metallile, mille ta töötas väljas oma doktoritöö raames Soomes Helsingi Kunsti- ja Disainiülikoolis ning mis pälvis Soulis toimunud ülemaailmsel naisleiutajate konkursil hõbemedali

  14. Understanding poisson regression.

    Science.gov (United States)

    Hayat, Matthew J; Higgins, Melinda

    2014-04-01

    Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

  15. Eucalipto, madeira serrada, metodologia de amostragem, regressão multivariada. Log sampling of Eucalyptus grandis trees submitted to selection for sawn timber and energy purposes Amostragem de toras de árvores de Eucalyptus grandis selecionadas para finalidades de serraria e energia

    Directory of Open Access Journals (Sweden)

    Paulo Eduardo Telles dos Santos

    2010-06-01

    Full Text Available By the assessment of ten technological traits of eucalypt wood for sawn timber and energy purposes,
    it was developed a multivariate statistical procedure in order to determine the sequence of logs to be sampled, in such a way to represent all statistical variation contained within the tree and, accordingly, to establish the appropriate sampling intensity. In the present work, it was used a total of 40 logs from four trees of Eucalyptus grandis provenance Concórdia-SC aged 18 years. By using principal components regression analysis and stepwise selection techniques, it was showed that only two logs, corresponding to the first (0.05 m to 2.60 m and fourth (8.85 m to 11.40 m positions into the tree, contained 99.2 % of the total variation detected originally. In the case of adopting a single log, the recommendation was over the fourth log, which represented 97.5 % of the total
    amount of the original variation. For the referred  population, the statistical procedure contributed substantially to reduce the high time-consuming and financial costs that are normally associated to studies oriented to this goal, without affecting the original statistical information exhibited by the whole group of logs that would be usually sampled.A partir da avaliação de dez características tecnológicas de madeira de eucalipto para fins de serraria e energia, desenvolveu-se procedimento estatístico multivariado para se determinar a seqüência de toras a ser amostrada, de forma a representar acumuladamente toda a variação estatística presente na árvore e, com isso, estabelecer a intensidade adequada de amostragem. Neste estudo, foram utilizadas 40 toras oriundas de quatro árvores de Eucalyptus grandis aos 18 anos de idade procedentes de Concórdia, SC. Com o uso de técnicas de regressão multivariada de componentes principais e seleção por etapas, chegou-se à conclusão que amostrandose apenas duas toras, correspondentes à primeira (0,05 m a 2

  16. Vector regression introduced

    Directory of Open Access Journals (Sweden)

    Mok Tik

    2014-06-01

    Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

  17. Multicollinearity and Regression Analysis

    Science.gov (United States)

    Daoud, Jamal I.

    2017-12-01

    In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

  18. Current and potential tree locations in tree line ecotone of Changbai Mountains, Northeast China: the controlling effects of topography.

    Science.gov (United States)

    Zong, Shengwei; Wu, Zhengfang; Xu, Jiawei; Li, Ming; Gao, Xiaofeng; He, Hongshi; Du, Haibo; Wang, Lei

    2014-01-01

    Tree line ecotone in the Changbai Mountains has undergone large changes in the past decades. Tree locations show variations on the four sides of the mountains, especially on the northern and western sides, which has not been fully explained. Previous studies attributed such variations to the variations in temperature. However, in this study, we hypothesized that topographic controls were responsible for causing the variations in the tree locations in tree line ecotone of the Changbai Mountains. To test the hypothesis, we used IKONOS images and WorldView-1 image to identify the tree locations and developed a logistic regression model using topographical variables to identify the dominant controls of the tree locations. The results showed that aspect, wetness, and slope were dominant controls for tree locations on western side of the mountains, whereas altitude, SPI, and aspect were the dominant factors on northern side. The upmost altitude a tree can currently reach was 2140 m asl on the northern side and 2060 m asl on western side. The model predicted results showed that habitats above the current tree line on the both sides were available for trees. Tree recruitments under the current tree line may take advantage of the available habitats at higher elevations based on the current tree location. Our research confirmed the controlling effects of topography on the tree locations in the tree line ecotone of Changbai Mountains and suggested that it was essential to assess the tree response to topography in the research of tree line ecotone.

  19. Minimax Regression Quantiles

    DEFF Research Database (Denmark)

    Bache, Stefan Holst

    A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....

  20. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....

  1. Surface tree languages and parallel derivation trees

    NARCIS (Netherlands)

    Engelfriet, Joost

    1976-01-01

    The surface tree languages obtained by top-down finite state transformation of monadic trees are exactly the frontier-preserving homomorphic images of sets of derivation trees of ETOL systems. The corresponding class of tree transformation languages is therefore equal to the class of ETOL languages.

  2. Multiple linear regression analysis

    Science.gov (United States)

    Edwards, T. R.

    1980-01-01

    Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

  3. Bayesian logistic regression analysis

    NARCIS (Netherlands)

    Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.

    2012-01-01

    In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an

  4. Linear Regression Analysis

    CERN Document Server

    Seber, George A F

    2012-01-01

    Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.

  5. Nonlinear Regression with R

    CERN Document Server

    Ritz, Christian; Parmigiani, Giovanni

    2009-01-01

    R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. This book provides a coherent treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology.

  6. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Bounded Gaussian process regression

    DEFF Research Database (Denmark)

    Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan

    2013-01-01

    We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...... with the proposed explicit noise-model extension....

  8. and Multinomial Logistic Regression

    African Journals Online (AJOL)

    This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).

  9. Mechanisms of neuroblastoma regression

    Science.gov (United States)

    Brodeur, Garrett M.; Bagatell, Rochelle

    2014-01-01

    Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

  10. Log and tree sawing times for hardwood mills

    Science.gov (United States)

    Everette D. Rast

    1974-01-01

    Data on 6,850 logs and 1,181 trees were analyzed to predict sawing times. For both logs and trees, regression equations were derived that express (in minutes) sawing time per log or tree and per Mbf. For trees, merchantable height is expressed in number of logs as well as in feet. One of the major uses for the tables of average sawing times is as a bench mark against...

  11. Trees are good, but…

    Science.gov (United States)

    E.G. McPherson; F. Ferrini

    2010-01-01

    We know that “trees are good,” and most people believe this to be true. But if this is so, why are so many trees neglected, and so many tree wells empty? An individual’s attitude toward trees may result from their firsthand encounters with specific trees. Understanding how attitudes about trees are shaped, particularly aversion to trees, is critical to the business of...

  12. Experiment vs simulation RT WFNDEC 2014 benchmark: CIVA results

    International Nuclear Information System (INIS)

    Tisseur, D.; Costin, M.; Rattoni, B.; Vienne, C.; Vabre, A.; Cattiaux, G.; Sollier, T.

    2015-01-01

    The French Atomic Energy Commission and Alternative Energies (CEA) has developed for years the CIVA software dedicated to simulation of NDE techniques such as Radiographic Testing (RT). RT modelling is achieved in CIVA using combination of a determinist approach based on ray tracing for transmission beam simulation and a Monte Carlo model for the scattered beam computation. Furthermore, CIVA includes various detectors models, in particular common x-ray films and a photostimulable phosphor plates. This communication presents the results obtained with the configurations proposed in the World Federation of NDEC 2014 RT modelling benchmark with the RT models implemented in the CIVA software

  13. Experiment vs simulation RT WFNDEC 2014 benchmark: CIVA results

    Energy Technology Data Exchange (ETDEWEB)

    Tisseur, D., E-mail: david.tisseur@cea.fr; Costin, M., E-mail: david.tisseur@cea.fr; Rattoni, B., E-mail: david.tisseur@cea.fr; Vienne, C., E-mail: david.tisseur@cea.fr; Vabre, A., E-mail: david.tisseur@cea.fr; Cattiaux, G., E-mail: david.tisseur@cea.fr [CEA LIST, CEA Saclay 91191 Gif sur Yvette Cedex (France); Sollier, T. [Institut de Radioprotection et de Sûreté Nucléaire, B.P.17 92262 Fontenay-Aux-Roses (France)

    2015-03-31

    The French Atomic Energy Commission and Alternative Energies (CEA) has developed for years the CIVA software dedicated to simulation of NDE techniques such as Radiographic Testing (RT). RT modelling is achieved in CIVA using combination of a determinist approach based on ray tracing for transmission beam simulation and a Monte Carlo model for the scattered beam computation. Furthermore, CIVA includes various detectors models, in particular common x-ray films and a photostimulable phosphor plates. This communication presents the results obtained with the configurations proposed in the World Federation of NDEC 2014 RT modelling benchmark with the RT models implemented in the CIVA software.

  14. Ridge Regression Signal Processing

    Science.gov (United States)

    Kuhl, Mark R.

    1990-01-01

    The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.

  15. Subset selection in regression

    CERN Document Server

    Miller, Alan

    2002-01-01

    Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...

  16. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  17. Regression in organizational leadership.

    Science.gov (United States)

    Kernberg, O F

    1979-02-01

    The choice of good leaders is a major task for all organizations. Inforamtion regarding the prospective administrator's personality should complement questions regarding his previous experience, his general conceptual skills, his technical knowledge, and the specific skills in the area for which he is being selected. The growing psychoanalytic knowledge about the crucial importance of internal, in contrast to external, object relations, and about the mutual relationships of regression in individuals and in groups, constitutes an important practical tool for the selection of leaders.

  18. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  19. Mamma diagnostics for MTRA (medical-radiological personnel)/RT (radiologists); Mammadiagnostik fuer MTRA/RT

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, Uwe; Baum, Friedemann

    2014-07-01

    The text book on mamma diagnostics for MTRA (medical-radiological personnel)/RT (radiologists) covers the following issues: Anatomy, development and physiology of mammary glands; tumor development an breast cancer risk; pathology, non-imaging diagnostics; mammography: physical-technical fundamentals; mammography: analogue technique; mammography: digital technique; mammography: quality assurance; mammography: legal questions and radiation protection; mammography: new developments; mammography: setting technique; mammography: use and appraisal; mamma-sonography: technique and methodology; mamma-sonography: assignment and appraisal, mamma-NMR: technique and methodology; mamma-NMR: assignment and appraisal lymph node diagnostics; mamma interventions; biopsy; mamma interventions: marking examination concepts; therapeutic concepts; hygienic concepts; communication and interaction.

  20. Modular tree automata

    DEFF Research Database (Denmark)

    Bahr, Patrick

    2012-01-01

    Tree automata are traditionally used to study properties of tree languages and tree transformations. In this paper, we consider tree automata as the basis for modular and extensible recursion schemes. We show, using well-known techniques, how to derive from standard tree automata highly modular...

  1. Simple street tree sampling

    Science.gov (United States)

    David J. Nowak; Jeffrey T. Walton; James Baldwin; Jerry. Bond

    2015-01-01

    Information on street trees is critical for management of this important resource. Sampling of street tree populations provides an efficient means to obtain street tree population information. Long-term repeat measures of street tree samples supply additional information on street tree changes and can be used to report damages from catastrophic events. Analyses of...

  2. Reverse transcriptase-quantitative polymerase chain reaction (RT ...

    African Journals Online (AJOL)

    The reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a highly specific polymerase chain reaction (PCR) method that allows one to detect very low transcription levels of functional gene(s) in soil. RT-qPCR helps us to know the active members of the microbial community, and their activities can be ...

  3. Steganalysis using logistic regression

    Science.gov (United States)

    Lubenko, Ivans; Ker, Andrew D.

    2011-02-01

    We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.

  4. SEPARATION PHENOMENA LOGISTIC REGRESSION

    Directory of Open Access Journals (Sweden)

    Ikaro Daniel de Carvalho Barreto

    2014-03-01

    Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.

  5. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface......-product we obtain fast access to the baseline hazards (compared to survival::basehaz()) and predictions of survival probabilities, their confidence intervals and confidence bands. Confidence intervals and confidence bands are based on point-wise asymptotic expansions of the corresponding statistical...

  6. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

  7. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  8. City of Pittsburgh Trees

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Trees cared for and managed by the City of Pittsburgh Department of Public Works Forestry Division. Tree Benefits are calculated using the National Tree Benefit...

  9. Aid and growth regressions

    DEFF Research Database (Denmark)

    Hansen, Henrik; Tarp, Finn

    2001-01-01

    This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy....... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes.......This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy...

  10. Primary tumor regression speed after radiotherapy and its prognostic significance in nasopharyngeal carcinoma: a retrospective study

    International Nuclear Information System (INIS)

    Zhang, Ning; Liu, Dong-Sheng; Chen, Yong; Liang, Shao-Bo; Deng, Yan-Ming; Lu, Rui-Liang; Chen, Hai-Yang; Zhao, Hai; Lv, Zhi-Qian; Liang, Shao-Qiang; Yang, Lin

    2014-01-01

    To observe the primary tumor (PT) regression speed after radiotherapy (RT) in nasopharyngeal carcinoma (NPC) and evaluate its prognostic significance. One hundred and eighty-eight consecutive newly diagnosed NPC patients were reviewed retrospectively. All patients underwent magnetic resonance imaging and fiberscope examination of the nasopharynx before RT, during RT when the accumulated dose was 46–50 Gy, at the end of RT, and 3–4 months after RT. Of 188 patients, 40.4% had complete response of PT (CRPT), 44.7% had partial response of PT (PRPT), and 14.9% had stable disease of PT (SDPT) at the end of RT. The 5-year overall survival (OS) rates for patients with CRPT, PRPT, and SDPT at the end of RT were 84.0%, 70.7%, and 44.3%, respectively (P < 0.001, hazard ratio [HR] = 2.177, 95% confidence interval [CI] = 1.480-3.202). The 5-year failure-free survival (FFS) and distant metastasis-free survival (DMFS) rates also differed significantly (87.8% vs. 74.3% vs. 52.7%, P = 0.001, HR = 2.148, 95% CI, 1.384-3.333; 91.7% vs. 84.7% vs. 66.1%, P = 0.004, HR = 2.252, 95% CI = 1.296-3.912). The 5-year local relapse–free survival (LRFS) rates were not significantly different (95.8% vs. 86.0% vs. 81.8%, P = 0.137, HR = 1.975, 95% CI, 0.976-3.995). By multivariate analyses, the PT regression speed at the end of RT was the only independent prognostic factor of OS, FFS, and DMFS (P < 0.001, P = 0.001, and P = 0.004, respectively). The 5-year FFS rates for patients with CRPT during RT and CRPT only at the end of RT were 80.2% and 97.1%, respectively (P = 0.033). For patients with persistent PT at the end of RT, the 5-year LRFS rates of patients without and with boost irradiation were 87.1% and 84.6%, respectively (P = 0.812). PT regression speed at the end of RT was an independent prognostic factor of OS, FFS, and DMFS in NPC patients. Immediate strengthening treatment may be provided to patients with poor tumor regression at the end of RT

  11. Modified Regression Correlation Coefficient for Poisson Regression Model

    Science.gov (United States)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  12. Canonical variate regression.

    Science.gov (United States)

    Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun

    2016-07-01

    In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  13. Categorizing ideas about trees: a tree of trees.

    Science.gov (United States)

    Fisler, Marie; Lecointre, Guillaume

    2013-01-01

    The aim of this study is to explore whether matrices and MP trees used to produce systematic categories of organisms could be useful to produce categories of ideas in history of science. We study the history of the use of trees in systematics to represent the diversity of life from 1766 to 1991. We apply to those ideas a method inspired from coding homologous parts of organisms. We discretize conceptual parts of ideas, writings and drawings about trees contained in 41 main writings; we detect shared parts among authors and code them into a 91-characters matrix and use a tree representation to show who shares what with whom. In other words, we propose a hierarchical representation of the shared ideas about trees among authors: this produces a "tree of trees." Then, we categorize schools of tree-representations. Classical schools like "cladists" and "pheneticists" are recovered but others are not: "gradists" are separated into two blocks, one of them being called here "grade theoreticians." We propose new interesting categories like the "buffonian school," the "metaphoricians," and those using "strictly genealogical classifications." We consider that networks are not useful to represent shared ideas at the present step of the study. A cladogram is made for showing who is sharing what with whom, but also heterobathmy and homoplasy of characters. The present cladogram is not modelling processes of transmission of ideas about trees, and here it is mostly used to test for proximity of ideas of the same age and for categorization.

  14. MZC Gel Inhibits SHIV-RT and HSV-2 in Macaque Vaginal Mucosa and SHIV-RT in Rectal Mucosa.

    Science.gov (United States)

    Calenda, Giulia; Villegas, Guillermo; Barnable, Patrick; Litterst, Claudia; Levendosky, Keith; Gettie, Agegnehu; Cooney, Michael L; Blanchard, James; Fernández-Romero, José A; Zydowsky, Thomas M; Teleshova, Natalia

    2017-03-01

    The Population Council's microbicide gel MZC (also known as PC-1005) containing MIV-150 and zinc acetate dihydrate (ZA) in carrageenan (CG) has shown promise as a broad-spectrum microbicide against HIV, herpes simplex virus (HSV), and human papillomavirus. Previous data show antiviral activity against these viruses in cell-based assays, prevention of vaginal and rectal simian-human immunodeficiency virus reverse transcriptase (SHIV-RT) infection, and reduction of vaginal HSV shedding in rhesus macaques and also excellent antiviral activity against HSV and human papillomavirus in murine models. Recently, we demonstrated that MZC is safe and effective against SHIV-RT in macaque vaginal explants. Here we established models of ex vivo SHIV-RT/HSV-2 coinfection of vaginal mucosa and SHIV-RT infection of rectal mucosa in macaques (challenge of rectal mucosa with HSV-2 did not result in reproducible tissue infection), evaluated antiviral activity of MZC, and compared quantitative polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay readouts for monitoring SHIV-RT infection. MZC (at nontoxic dilutions) significantly inhibited SHIV-RT in vaginal and rectal mucosas and HSV-2 in vaginal mucosa when present during viral challenge. Analysis of SHIV-RT infection and MZC activity by 1-step simian immunodeficiency virus gag quantitative RT-PCR and p27 enzyme-linked immunosorbent assay demonstrated similar virus growth dynamics and MZC activity by both methods and higher sensitivity of quantitative RT-PCR. Our data provide more evidence that MZC is a promising dual compartment multipurpose prevention technology candidate.

  15. Urban tree growth modeling

    Science.gov (United States)

    E. Gregory McPherson; Paula J. Peper

    2012-01-01

    This paper describes three long-term tree growth studies conducted to evaluate tree performance because repeated measurements of the same trees produce critical data for growth model calibration and validation. Several empirical and process-based approaches to modeling tree growth are reviewed. Modeling is more advanced in the fields of forestry and...

  16. Keeping trees as assets

    Science.gov (United States)

    Kevin T. Smith

    2009-01-01

    Landscape trees have real value and contribute to making livable communities. Making the most of that value requires providing trees with the proper care and attention. As potentially large and long-lived organisms, trees benefit from commitment to regular care that respects the natural tree system. This system captures, transforms, and uses energy to survive, grow,...

  17. rt, Arvo: "Miserere", "Festina lente" / Volkmar Fischer

    Index Scriptorium Estoniae

    Fischer, Volkmar

    1991-01-01

    Uuest heliplaadist Pärt, Arvo: "Miserere", "Festina lente", "Sarah Was Ninety Years Old". The Hilliard Ensemble. Orchester der Beethovenhalle Bonn. Dirigent Dennis Russel Davies (ECM Records, distr Amigo)

  18. rt, Arvo: Seven Magnificat Antiphons / Barry Witherden

    Index Scriptorium Estoniae

    Witherden, Barry

    1996-01-01

    Uuest heliplaadist "Pärt, Arvo: Seven Magnificat Antiphons. Magnificat. Summa; Tormis, Veljo: The Curse Upon Iron. Karelian Destiny. BBC Singers, Bo Holton". Collins Classics 1472-2 (61 minutes: DDD)

  19. Reverse transcriptase-quantitative polymerase chain reaction (RT ...

    African Journals Online (AJOL)

    zino

    2014-02-05

    Feb 5, 2014 ... ecological studies - A review ... The objective of this review is to assess the importance of RT-qPCR in soil related ... phenol extraction step with heat inactivation of the added .... Real time polymerase chain reaction (PCR).

  20. rt, Arvo. Litany; Psalom; Trisagion / Andreas Obst

    Index Scriptorium Estoniae

    Obst, Andreas

    1996-01-01

    rt, Arvo. Litany; Psalom; Trisagion. Hilliard Ensemble, Estonian Philharmonic Chamber Choir, Tallinn Chamber Orchestra, Tõnu Kaljuste; Lithuanian Chamber Orchestra, Saulius Sondeckis. ECM 1592/449 810-2

  1. rt, Arvo: Litany. Psalom. Trisagion / Robert Cowan

    Index Scriptorium Estoniae

    Cowan, Robert

    1996-01-01

    Uuest heliplaadist "Pärt, Arvo: Litany. Psalom. Trisagion. Hilliard Ensemble, Estonian Philharmonic Chamber Choir, Tallinn Chamber Orchestra, Tõnu Kaljuste; Lithuanian Chamber Orchestra, Saulius Sondeckis" ECM New Series 449 810-4; 449 810-2 (42 minutes: DDD)

  2. rt, Arvo: "Beatus". Statuit ei Dominus / Patric Wiklacz

    Index Scriptorium Estoniae

    Wiklacz, Patric

    1997-01-01

    Uuest heliplaadist "Pärt, Arvo: "Beatus". Statuit ei Dominus. Missa syllabica. Beatus Petronius. 7 Magnificat-Antiphonen. De profundis. Memento. Cantate Domino. Solfeggio. Estonian Philharmonic Chamber Choir, T. Kaljuste". Virgin Classics 545 276-2 (CD:167F)

  3. The value of research : telling the R&T story

    Science.gov (United States)

    2009-07-01

    The Federal Highway Administration (FHWA) plays a leadership role in shaping and executing a National Research and Technology (R&T) program. The agency also acts as a convener; collaborations with State, industry, and academic partners provide the fo...

  4. Milan Kundera poeediparukaga faun / Kärt Hellerma

    Index Scriptorium Estoniae

    Hellerma, Kärt, 1956-

    1996-01-01

    Arvustus: Kundera, Milan. Surematus. Tln. : Monokkel, 1995. Ilmunud ka kogumikus: Hellerma, Kärt. Kohanenud kirjandus : valik kirjanduskriitikat 1987-2006. Eesti Keele Sihtasutus : Tallinn, 2006. Lk. 176-179

  5. Kuidas sünnib pealkiri? / Pärt Lias

    Index Scriptorium Estoniae

    Lias, Pärt

    2003-01-01

    Eesti kirjanikud vastavad Pärt Liase küsimusele oma teoste pealkirjade saamisloo kohta: Doris Kareva, Ilona Laaman, Eha Lättemäe, Priidu Beier, Oskar Kruus, Jaan Kruusvall, Paul-Eerik Rummo ja Andres Vanapa (1); Triin Soomets, Priit Aimla, Aarne Puu, Einar Sander, Jüri Tuulik ja Ülo Tuulik (2); Nikolai Baturin, Leo Metsar, Toomas Vint, Leonid Stolovitš ja Pärt Lias (3)

  6. Hyperthermic Fibrinolysis with rt-PA: In Vitro Results

    International Nuclear Information System (INIS)

    Schwarzenberg, Helmut; Mueller-Huelsbeck, Stefan; Brossman, Joachim; Christian Glueer, Claus; Bruhn, Hans Dieter; Heller, Martin

    1998-01-01

    Purpose: To investigate the influence of hyperthermia up to 45 deg. C on fibrinolysis with recombinant tissue-type plasminogen activator (rt-PA). Methods: Standardized fibrin clots were incubated in a water bath for 5 hr with either rt-PA (test group) or 0.9% sodium chloride (control group) and blood plasma at temperatures of 30-45 deg. C. Concentrations of D-dimer and time to complete clot lysis were measured.Results: The activity of fibrinolysis with rt-PA rose with increasing temperature: time to lysis approximately halved from 30 deg. C to 40 deg. C and the concentration of D-dimer tripled. In the control group clot size did not change.Conclusions: Activity of rt-PA-induced fibrinolysis rises distinctly with higher temperatures. Since even healthy subjects show a physiologic decline in body temperature in the extremities, in patients with occlusive arterial disease decreased activity of fibrinolysis with rt-PA can be expected. Controlled hyperthermia may improve fibrinolysis with rt-PA and should be investigated in vivo

  7. NASA SPoRT GOES-R Proving Ground Activities

    Science.gov (United States)

    Stano, Geoffrey T.; Fuell, Kevin K.; Jedloec, Gary J.

    2010-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) program is a partner with the GOES-R Proving Ground (PG) helping prepare forecasters understand the unique products to come from the GOES-R instrument suite. SPoRT is working collaboratively with other members of the GOES-R PG team and Algorithm Working Group (AWG) scientists to develop and disseminate a suite of proxy products that address specific forecast problems for the WFOs, Regional and National Support Centers, and other NOAA users. These products draw on SPoRT s expertise with the transition and evaluation of products into operations from the MODIS instrument and the North Alabama Lightning Mapping Array (NALMA). The MODIS instrument serves as an excellent proxy for the Advanced Baseline Imager (ABI) that will be aboard GOES-R. SPoRT has transitioned and evaluated several multi-channel MODIS products. The true and false color products are being used in natural hazard detection by several SPoRT partners to provide better observation of land features, such as fires, smoke plumes, and snow cover. Additionally, many of SPoRT s partners are coastal offices and already benefit from the MODIS sea surface temperature composite. This, along with other surface feature observations will be developed into ABI proxy products for diagnostic use in the forecast process as well as assimilation into forecast models. In addition to the MODIS instrument, the NALMA has proven very valuable to WFOs with access to these total lightning data. These data provide situational awareness and enhanced warning decision making to improve lead times for severe thunderstorm and tornado warnings. One effort by SPoRT scientists includes a lightning threat product to create short-term model forecasts of lightning activity. Additionally, SPoRT is working with the AWG to create GLM proxy data from several of the ground based total lightning networks, such as the NALMA. The evaluation will focus on the vastly improved spatial

  8. Selection of reference genes for qRT-PCR analysis of gene expression in sea cucumber Apostichopus japonicus during aestivation

    Science.gov (United States)

    Zhao, Ye; Chen, Muyan; Wang, Tianming; Sun, Lina; Xu, Dongxue; Yang, Hongsheng

    2014-11-01

    Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a technique that is widely used for gene expression analysis, and its accuracy depends on the expression stability of the internal reference genes used as normalization factors. However, many applications of qRT-PCR used housekeeping genes as internal controls without validation. In this study, the expression stability of eight candidate reference genes in three tissues (intestine, respiratory tree, and muscle) of the sea cucumber Apostichopus japonicus was assessed during normal growth and aestivation using the geNorm, NormFinder, delta CT, and RefFinder algorithms. The results indicate that the reference genes exhibited significantly different expression patterns among the three tissues during aestivation. In general, the β-tubulin (TUBB) gene was relatively stable in the intestine and respiratory tree tissues. The optimal reference gene combination for intestine was 40S ribosomal protein S18 (RPS18), TUBB, and NADH dehydrogenase (NADH); for respiratory tree, it was β-actin (ACTB), TUBB, and succinate dehydrogenase cytochrome B small subunit (SDHC); and for muscle it was α-tubulin (TUBA) and NADH dehydrogenase [ubiquinone] 1 α subcomplex subunit 13 (NDUFA13). These combinations of internal control genes should be considered for use in further studies of gene expression in A. japonicus during aestivation.

  9. Polynomial regression analysis and significance test of the regression function

    International Nuclear Information System (INIS)

    Gao Zhengming; Zhao Juan; He Shengping

    2012-01-01

    In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

  10. Recursive Algorithm For Linear Regression

    Science.gov (United States)

    Varanasi, S. V.

    1988-01-01

    Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.

  11. Predicting Potential Changes in Suitable Habitat and Distribution by 2100 for Tree Species of the Eastern United States

    Science.gov (United States)

    Louis R Iverson; Anantha M. Prasad; Mark W. Schwartz; Mark W. Schwartz

    2005-01-01

    We predict current distribution and abundance for tree species present in eastern North America, and subsequently estimate potential suitable habitat for those species under a changed climate with 2 x CO2. We used a series of statistical models (i.e., Regression Tree Analysis (RTA), Multivariate Adaptive Regression Splines (MARS), Bagging Trees (...

  12. Fault tree handbook

    International Nuclear Information System (INIS)

    Haasl, D.F.; Roberts, N.H.; Vesely, W.E.; Goldberg, F.F.

    1981-01-01

    This handbook describes a methodology for reliability analysis of complex systems such as those which comprise the engineered safety features of nuclear power generating stations. After an initial overview of the available system analysis approaches, the handbook focuses on a description of the deductive method known as fault tree analysis. The following aspects of fault tree analysis are covered: basic concepts for fault tree analysis; basic elements of a fault tree; fault tree construction; probability, statistics, and Boolean algebra for the fault tree analyst; qualitative and quantitative fault tree evaluation techniques; and computer codes for fault tree evaluation. Also discussed are several example problems illustrating the basic concepts of fault tree construction and evaluation

  13. There's Life in Hazard Trees

    Science.gov (United States)

    Mary Torsello; Toni McLellan

    The goals of hazard tree management programs are to maximize public safety and maintain a healthy sustainable tree resource. Although hazard tree management frequently targets removal of trees or parts of trees that attract wildlife, it can take into account a diversity of tree values. With just a little extra planning, hazard tree management can be highly beneficial...

  14. Transferability of decision trees for land cover classification in a ...

    African Journals Online (AJOL)

    This paper attempts to derive classification rules from training data of four Landsat-8 scenes by using the classification and regression tree (CART) implementation of the decision tree algorithm. The transferability of the ruleset was evaluated by classifying two adjacent scenes. The classification of the four mosaicked scenes ...

  15. Developing Models to Forcast Sales of Natural Christmas Trees

    Science.gov (United States)

    Lawrence D. Garrett; Thomas H. Pendleton

    1977-01-01

    A study of practices for marketing Christmas trees in Winston-Salem, North Carolina, and Denver, Colorado, revealed that such factors as retail lot competition, tree price, consumer traffic, and consumer income were very important in determining a particular retailer's sales. Analyses of 4 years of market data were used in developing regression models for...

  16. Modeling Caribbean tree stem diameters from tree height and crown width measurements

    Science.gov (United States)

    Thomas Brandeis; KaDonna Randolph; Mike Strub

    2009-01-01

    Regression models to predict diameter at breast height (DBH) as a function of tree height and maximum crown radius were developed for Caribbean forests based on data collected by the U.S. Forest Service in the Commonwealth of Puerto Rico and Territory of the U.S. Virgin Islands. The model predicting DBH from tree height fit reasonably well (R2 = 0.7110), with...

  17. Combining Alphas via Bounded Regression

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2015-11-01

    Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.

  18. Regression in autistic spectrum disorders.

    Science.gov (United States)

    Stefanatos, Gerry A

    2008-12-01

    A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.

  19. Covering tree with stars

    DEFF Research Database (Denmark)

    Baumbach, Jan; Guo, Jiong; Ibragimov, Rashid

    2015-01-01

    We study the tree edit distance problem with edge deletions and edge insertions as edit operations. We reformulate a special case of this problem as Covering Tree with Stars (CTS): given a tree T and a set of stars, can we connect the stars in by adding edges between them such that the resulting...... tree is isomorphic to T? We prove that in the general setting, CST is NP-complete, which implies that the tree edit distance considered here is also NP-hard, even when both input trees having diameters bounded by 10. We also show that, when the number of distinct stars is bounded by a constant k, CTS...

  20. Linear regression in astronomy. I

    Science.gov (United States)

    Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh

    1990-01-01

    Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.

  1. Advanced statistics: linear regression, part I: simple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

  2. Modelling Dynamic Topologies via Extensions of VDM-RT

    DEFF Research Database (Denmark)

    Nielsen, Claus Ballegård

    Only a few formal methods include descriptions of the network topology that the modelled system is deployed onto. In VDM Real-Time (VDM-RT) this has been enabled for distributed systems that have a static structure. However, when modelling dynamic systems this fixed topology becomes an issue....... Systems with highly distributed and alternating relationships cannot be expressed correctly in a static model. This document describes how VDM-RT can be extended with new language constructs to enable the description of dynamic reconfiguration of the network topology during the runtime execution...... of a model. The extension is developed on the basis of a case study involving a dynamic system that has a constant changing system topology. With a basis in the case study a model is developed that uses the static version of VDM-RT in order to reveal the limitations of the language. The case study...

  3. Soft-Rt: software for IMRT simulations based on MCNPX

    International Nuclear Information System (INIS)

    Ferreira F, T. C.; Campos, T.

    2015-10-01

    Intensity Modulated Radiation Therapy (IMRT) is an advanced treatment technique, widely used in external radiotherapy. This paper presents the Soft-Rt which allows the simulation of an entire IMRT treatment protocol. The Soft-Rt performs a full three-dimensional rendering of a set of patient images, including the definitions of region of interest with organs in risk, and the target tumor volume and margins (PTV). Thus, a more accurate analysis and planning can be performed, taking into account the features and orientation of the radiation beams. The exposed tissues as well as the amount of absorbed dose is depicted in healthy and/or cancerous tissues. As conclusion, Soft-Rt can predict dose on the PTV accurately, preserving the surrounding healthy tissues. Soft-Rt is coupled with SISCODES code. The SISCODES code is firstly applied to segment the set of CT or MRI patient images in distinct tissues pointing out its respective density and chemical compositions. Later, the voxel model is export to the Soft-Rt IMRT planning module in which a full treatment planning is created. All geometrical parameters are sent to the general purpose Monte Carlo transport code - MCNP - to simulate the interaction of each incident beam towards to the PTV avoiding organs in risk. The normalized dose results are exported to the Soft-Rt out-module, in which the three-dimensional model visualization is shown in a transparent glass procedure adopting gray scale for the dependence on the mass density of the correlated tissue; while, a color scale to depict dose values in a superimpose protocol. (Author)

  4. AWIPS II Application Development, a SPoRT Perspective

    Science.gov (United States)

    Burks, Jason E.; Smith, Matthew; McGrath, Kevin M.

    2014-01-01

    The National Weather Service (NWS) is deploying its next-generation decision support system, called AWIPS II (Advanced Weather Interactive Processing System II). NASA's Short-term Prediction Research and Transition (SPoRT) Center has developed several software 'plug-ins' to extend the capabilities of AWIPS II. SPoRT aims to continue its mission of improving short-term forecasts by providing NASA and NOAA products on the decision support system used at NWS weather forecast offices (WFOs). These products are not included in the standard Satellite Broadcast Network feed provided to WFOs. SPoRT has had success in providing support to WFOs as they have transitioned to AWIPS II. Specific examples of transitioning SPoRT plug-ins to WFOs with newly deployed AWIPS II systems will be presented. Proving Ground activities (GOES-R and JPSS) will dominate SPoRT's future AWIPS II activities, including tool development as well as enhancements to existing products. In early 2012 SPoRT initiated the Experimental Product Development Team, a group of AWIPS II developers from several institutions supporting NWS forecasters with innovative products. The results of the team's spring and fall 2013 meeting will be presented. Since AWIPS II developers now include employees at WFOs, as well as many other institutions related to weather forecasting, the NWS has dealt with a multitude of software governance issues related to the difficulties of multiple remotely collaborating software developers. This presentation will provide additional examples of Research-to-Operations plugins, as well as an update on how governance issues are being handled in the AWIPS II developer community.

  5. Soft-Rt: software for IMRT simulations based on MCNPX

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira F, T. C. [Centro de Desenvolvimento da Tecnologia Nuclear / CNEN, Av. Pte. Antonio Carlos 6627, 31270-901 Belo Horizonte, Minas Gerais (Brazil); Campos, T., E-mail: tcff01@gmail.com [Universidade Federal de Minas Gerais, Departamento de Engenharia Nuclear, Programa de Pos Graduacao em Ciencias e Tecnicas Nucleares, Av. Pte. Antonio Carlos 6627, 31270-901 Belo Horizonte, Minas Gerais (Brazil)

    2015-10-15

    Intensity Modulated Radiation Therapy (IMRT) is an advanced treatment technique, widely used in external radiotherapy. This paper presents the Soft-Rt which allows the simulation of an entire IMRT treatment protocol. The Soft-Rt performs a full three-dimensional rendering of a set of patient images, including the definitions of region of interest with organs in risk, and the target tumor volume and margins (PTV). Thus, a more accurate analysis and planning can be performed, taking into account the features and orientation of the radiation beams. The exposed tissues as well as the amount of absorbed dose is depicted in healthy and/or cancerous tissues. As conclusion, Soft-Rt can predict dose on the PTV accurately, preserving the surrounding healthy tissues. Soft-Rt is coupled with SISCODES code. The SISCODES code is firstly applied to segment the set of CT or MRI patient images in distinct tissues pointing out its respective density and chemical compositions. Later, the voxel model is export to the Soft-Rt IMRT planning module in which a full treatment planning is created. All geometrical parameters are sent to the general purpose Monte Carlo transport code - MCNP - to simulate the interaction of each incident beam towards to the PTV avoiding organs in risk. The normalized dose results are exported to the Soft-Rt out-module, in which the three-dimensional model visualization is shown in a transparent glass procedure adopting gray scale for the dependence on the mass density of the correlated tissue; while, a color scale to depict dose values in a superimpose protocol. (Author)

  6. Trees and highway safety.

    Science.gov (United States)

    2011-03-01

    To minimize the severity of run-off-road collisions of vehicles with trees, departments of transportation (DOTs) : commonly establish clear zones for trees and other fixed objects. Caltrans clear zone on freeways is 30 feet : minimum (40 feet pref...

  7. RT-PCR Detection of HIV in Republic of Macedonia

    Directory of Open Access Journals (Sweden)

    Golubinka Bosevska

    2008-11-01

    Full Text Available The aim of the study was to detect HIV RNA in seropositive patients using RT-PCR method and thus, to establish PCR methodology in the routine laboratory works.The total of 33 examined persons were divided in two groups: 1 13 persons seropositive for HIV; and 2 20 healthy persons - randomly selected blood donors that made the case control group. The subjects age was between 25 and 52 years (average 38,5.ELFA test for combined detection of HIV p24 antigen and anti HIV-1 + 2 IgG and ELISA test for detection of antibodies against HIV-1 and HIV-2, were performed for each examined person. RNA from the whole blood was extracted using a commercial kit based on salt precipitation. Detection of HIV RNA was performed using RT-PCR kit. Following nested PCR, the product was separated by electrophoresis in 1,5 % agarose gel. The result was scored positive if the band of 210bp was visible regardless of intensity Measures of precaution were taken during all the steps of the work and HIV infected materials were disposed of accordingly.In the group of blood donors ELFA, ELISA and RT-PCR were negative. Assuming that prevalence of HIV infection is zero, the clinical specificity of RT-PCR is 100 %. The analytical specificity of RT-PCR method was tested against Hepatitis C and B, Human Papiloma Virus, Cytomegalovirus, Herpes Simplex Virus, Rubella Virus, Mycobacterium tuberculosis, Chlamydia trachomatis. None of these templates yielded amplicon. In the group of 13 seropositive persons, 33 samples were analyzed. HIV RNA was detected in 15 samples. ELISA and ELFA test were positive in all samples. Different aliquots of the samples were tested independently and showed the same results. After different periods of storing the RNA samples at -70°C, RT-PCR reaction was identical to the one performed initially. The obtained amplicons were maintained frozen at -20°C for a week and the subsequently performed electrophoresis was identical to the previous one. The reaction is

  8. Decision-Tree Program

    Science.gov (United States)

    Buntine, Wray

    1994-01-01

    IND computer program introduces Bayesian and Markov/maximum-likelihood (MML) methods and more-sophisticated methods of searching in growing trees. Produces more-accurate class-probability estimates important in applications like diagnosis. Provides range of features and styles with convenience for casual user, fine-tuning for advanced user or for those interested in research. Consists of four basic kinds of routines: data-manipulation, tree-generation, tree-testing, and tree-display. Written in C language.

  9. Linear regression in astronomy. II

    Science.gov (United States)

    Feigelson, Eric D.; Babu, Gutti J.

    1992-01-01

    A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

  10. Time-adaptive quantile regression

    DEFF Research Database (Denmark)

    Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

    2008-01-01

    and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

  11. Minnesota's Forest Trees. Revised.

    Science.gov (United States)

    Miles, William R.; Fuller, Bruce L.

    This bulletin describes 46 of the more common trees found in Minnesota's forests and windbreaks. The bulletin contains two tree keys, a summer key and a winter key, to help the reader identify these trees. Besides the two keys, the bulletin includes an introduction, instructions for key use, illustrations of leaf characteristics and twig…

  12. D2-tree

    DEFF Research Database (Denmark)

    Brodal, Gerth Stølting; Sioutas, Spyros; Pantazos, Kostas

    2015-01-01

    We present a new overlay, called the Deterministic Decentralized tree (D2-tree). The D2-tree compares favorably to other overlays for the following reasons: (a) it provides matching and better complexities, which are deterministic for the supported operations; (b) the management of nodes (peers...

  13. Covering tree with stars

    DEFF Research Database (Denmark)

    Baumbach, Jan; Guo, Jian-Ying; Ibragimov, Rashid

    2013-01-01

    We study the tree edit distance problem with edge deletions and edge insertions as edit operations. We reformulate a special case of this problem as Covering Tree with Stars (CTS): given a tree T and a set of stars, can we connect the stars in by adding edges between them such that the resulting ...

  14. Winter Birch Trees

    Science.gov (United States)

    Sweeney, Debra; Rounds, Judy

    2011-01-01

    Trees are great inspiration for artists. Many art teachers find themselves inspired and maybe somewhat obsessed with the natural beauty and elegance of the lofty tree, and how it changes through the seasons. One such tree that grows in several regions and always looks magnificent, regardless of the time of year, is the birch. In this article, the…

  15. Total well dominated trees

    DEFF Research Database (Denmark)

    Finbow, Arthur; Frendrup, Allan; Vestergaard, Preben D.

    cardinality then G is a total well dominated graph. In this paper we study composition and decomposition of total well dominated trees. By a reversible process we prove that any total well dominated tree can both be reduced to and constructed from a family of three small trees....

  16. Retro-regression--another important multivariate regression improvement.

    Science.gov (United States)

    Randić, M

    2001-01-01

    We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

  17. Quantile regression theory and applications

    CERN Document Server

    Davino, Cristina; Vistocco, Domenico

    2013-01-01

    A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and

  18. TreePics: visualizing trees with pictures

    Directory of Open Access Journals (Sweden)

    Nicolas Puillandre

    2017-09-01

    Full Text Available While many programs are available to edit phylogenetic trees, associating pictures with branch tips in an efficient and automatic way is not an available option. Here, we present TreePics, a standalone software that uses a web browser to visualize phylogenetic trees in Newick format and that associates pictures (typically, pictures of the voucher specimens to the tip of each branch. Pictures are visualized as thumbnails and can be enlarged by a mouse rollover. Further, several pictures can be selected and displayed in a separate window for visual comparison. TreePics works either online or in a full standalone version, where it can display trees with several thousands of pictures (depending on the memory available. We argue that TreePics can be particularly useful in a preliminary stage of research, such as to quickly detect conflicts between a DNA-based phylogenetic tree and morphological variation, that may be due to contamination that needs to be removed prior to final analyses, or the presence of species complexes.

  19. Distribution of cavity trees in midwestern old-growth and second-growth forests

    Science.gov (United States)

    Zhaofei Fan; Stephen R. Shifley; Martin A. Spetich; Frank R. Thompson; David R. Larsen

    2003-01-01

    We used classification and regression tree analysis to determine the primary variables associated with the occurrence of cavity trees and the hierarchical structure among those variables. We applied that information to develop logistic models predicting cavity tree probability as a function of diameter, species group, and decay class. Inventories of cavity abundance in...

  20. A comparison of random forest regression and multiple linear regression for prediction in neuroscience.

    Science.gov (United States)

    Smith, Paul F; Ganesh, Siva; Liu, Ping

    2013-10-30

    Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Kirjanduskriitikute suvemängud / Kärt Hellerma

    Index Scriptorium Estoniae

    Hellerma, Kärt, 1956-

    2007-01-01

    Arvustus: Lodge, David. Ühest kohast teise / tlk. Aet Varik. Tallinn : Varrak, 2005 ; Lodge, David. Väike maailm / tlk. Kersti Unt. Tallinn : Varrak, 1996 ; Lodge, David. Väärt töö / tlk. Kersti Unt. Tallinn : Varrak, 2006

  2. Future of the reprocessing business at the RT-1 plant

    International Nuclear Information System (INIS)

    Bukharin, O.

    1995-01-01

    Economic viability of reprocessing operations at the RT-1 plant is provided by the contracts with nuclear utilities from Finland and Hungary. Finland will stop sending fuel to Mayak for reprocessing after 1996. Hungary will be capable to resolve the problem of spent fuel domestically some time in the future. This increases vulnerability of the reprocessing business at Mayak to future political uncertainties. (author)

  3. RT-PCR Protocols - Methods in Molecular Biology

    Directory of Open Access Journals (Sweden)

    Manuela Monti

    2011-03-01

    Full Text Available “The first record I have of it, is when I made a computer file which I usually did whenever I had an idea, that would have been on the Monday when I got back, and I called it Chain Reaction.POL, meaning polymerase. That was the identifier for it and later I called the thing the Polymerase Chain Reaction, which a lot of people thought was a dumb name for it, but it stuck, and it became PCR”. With these words the Nobel prize winner, Kary Mullis, explains how he named the PCR: one of the most important techniques ever invented and currently used in molecular biology. This book “RT-PCR Protocols” covers a wide range of aspects important for the setting of a PCR experiment for both beginners and advanced users. In my opinion the book is very well structured in three different sections. The first one describes the different technologies now available, like competitive RT-PCR, nested RT-PCR or RT-PCR for cloning. An important part regards the usage of PCR in single cell mouse embryos, stressing how important...........

  4. rt, Arvo: De profundis. Missa Sillabica / Patric Wiklacz

    Index Scriptorium Estoniae

    Wiklacz, Patric

    1997-01-01

    Uuest heliplaadist "Pärt, Arvo: De profundis. Missa Sillabica. Solfeggio. And one of the Pharisees. Cantate Domino. Summa. 7 Antiennes du Magnificat. The Beautitudes. Magnificat. Christopher Bowers-Broadbent (org.), Daniel Kennedy (perc.). Theatre of Voices / Paul Hillier (bass)" Harmonia Mundi HMU907 182 F (CD:165F). 1996. TT:1h 16'06"

  5. Narr kui ajastu metafoor / Kärt Hellerma

    Index Scriptorium Estoniae

    Hellerma, Kärt, 1956-

    2001-01-01

    William Shakespeare'i "Kuningas Lear" (lav. Priit Pedajas) ja Pedro Calder̤n de la Barca "Elu on unenägu" (lav. Ingo Normet) Eesti Draamateatris. Ilmunud ka kogumikus : Hellerma, Kärt. Avanenud ruum. Tallinn : Eesti Keele Sihtasutus, 2006, lk. 213-216. Pealk. Narr kui meie aja kangelane

  6. rt: Chamber and Orchestral Works / Robert Cowan

    Index Scriptorium Estoniae

    Cowan, Robert

    1994-01-01

    Uuest heliplaadist "Pärt: Chamber and Orchestral Works. Bournemouth Sinfonietta, Richard Studt. EMI Eminence CD CD-EMX 2221; Fratres; Cantus in memory of Benjamin Britten; Summa; Spiegel im Spiegel; Festina lente; Tabula Rasa; Fratres - selected comparison: Bachmann, Kibonoff (12/94)(CATA) 09026 61824-2. Kremer, Jarrett (ECM) 817 764-2

  7. 25 kaadrit sekundis / Liis Auväärt

    Index Scriptorium Estoniae

    Auväärt, Liis

    2009-01-01

    Nukufilmis käib töö filmiga "Lisa Limone & Maroc Orange", režissöör Mait Laas, animaatorid Triin Sarapik-Kivi, Märt Kivi, operaator Ragnar Neljandi, nukumeistrid Heigo Eeriksoo, Taivo Müürsep, Ene Mellow ja Kreeta Käeri. Dekoratsioonimeistrid Mait Erik ja Roman Kuznetsov

  8. rt, Arvo: De profundis / Barry Witherden

    Index Scriptorium Estoniae

    Witherden, Barry

    1997-01-01

    Uuest heliplaadist "Pärt, Arvo: De profundis. Missa Sillabica. Solfeggio. And one of the Pharisees. Cantate Domino. Summa. Seven Magnificat Antiphons. The Beautitudes. Magnificat. Christopher Bowers-Broadbent (org.), Daniel Kennedy (perc.). Theatre of Voices / Paul Hillier (bass)". Harmonia Mundi HMU40 7182; HMU90 7182 (76 minutes:DDD)

  9. Torm Balti merel / Märt Treier ; interv. Inge Pitsner

    Index Scriptorium Estoniae

    Treier, Märt, 1975-

    2004-01-01

    TV3 näitab saksa poliitilist põnevusfilmi "Balti torm" ("Baltic Storm"), mis kujutab parvlaev "Estonia" hukku : stsenarist, produtsent Jutta Rabe : režissöör Reuben Leder. Filmi eel on teles Märt Treieri saade "Tormist sündinud tormid"

  10. Karje kunstniku südamest / Kärt Hellerma

    Index Scriptorium Estoniae

    Hellerma, Kärt, 1956-

    1997-01-01

    Arvustus: Dinesen, Isak [Blixen, Karen]. Babette'i pidusöök / tlk. Piret Peiker. Tallinn : Varrak, 1996. Ilmunud ka kogumikus: Hellerma, Kärt. Kohanenud kirjandus : valik kirjanduskriitikat 1987-2006. Eesti Keele Sihtasutus : Tallinn, 2006. Lk. 167-169

  11. Interspecific variation in tree seedlings establishment in canopy gaps in relation to tree density

    Energy Technology Data Exchange (ETDEWEB)

    Reader, R.J.; Bonser, S.P.; Duralia, T.E.; Bricker, B.D. [Guelph Univ., ON (Canada). Dept. of Botany

    1995-10-01

    We tested whether interspecific variation in tree seedling establishment in canopy gaps was significantly related to interspecific variation in tree density, for seven deciduous forest tree species (Quercus alba, Hamamelis virginiana, Acer rubrum, Sassafras albidum, Quercus rubra, Prunus serotina, Ostrya virginiana). For each species, seedling establishment was calculated as the difference in seedling density before experimental gap creation versus three years after gap creation. In each of the six experimentally-created gap types (33% or 66% removal of tree basal area from 0.01ha, 0.05ha or 0.20ha patches), differences in seedling establishment among species were significantly related to differences in their density in the tree canopy. A regression model with log{sub e} tree density as the independent variable accounted for between 93% and 98% of interspecific variation in seedling establishment. Our results provide empirical support for models of tree dynamics in gaps that assume seedling establishment depends on canopy tree density. 17 refs, 1 fig, 3 tabs

  12. Panel Smooth Transition Regression Models

    DEFF Research Database (Denmark)

    González, Andrés; Terasvirta, Timo; Dijk, Dick van

    We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...

  13. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin

    2017-01-19

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  14. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

    2017-01-01

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  15. Logistic Regression: Concept and Application

    Science.gov (United States)

    Cokluk, Omay

    2010-01-01

    The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

  16. Spectra of chemical trees

    International Nuclear Information System (INIS)

    Balasubramanian, K.

    1982-01-01

    A method is developed for obtaining the spectra of trees of NMR and chemical interests. The characteristic polynomials of branched trees can be obtained in terms of the characteristic polynomials of unbranched trees and branches by pruning the tree at the joints. The unbranched trees can also be broken down further until a tree containing just two vertices is obtained. The effectively reduces the order of the secular determinant of the tree used at the beginning to determinants of orders atmost equal to the number of vertices in the branch containing the largest number of vertices. An illustrative example of a NMR graph is given for which the 22 x 22 secular determinant is reduced to determinants of orders atmost 4 x 4 in just the second step of the algorithm. The tree pruning algorithm can be applied even to trees with no symmetry elements and such a factoring can be achieved. Methods developed here can be elegantly used to find if two trees are cospectral and to construct cospectral trees

  17. Refining discordant gene trees.

    Science.gov (United States)

    Górecki, Pawel; Eulenstein, Oliver

    2014-01-01

    Evolutionary studies are complicated by discordance between gene trees and the species tree in which they evolved. Dealing with discordant trees often relies on comparison costs between gene and species trees, including the well-established Robinson-Foulds, gene duplication, and deep coalescence costs. While these costs have provided credible results for binary rooted gene trees, corresponding cost definitions for non-binary unrooted gene trees, which are frequently occurring in practice, are challenged by biological realism. We propose a natural extension of the well-established costs for comparing unrooted and non-binary gene trees with rooted binary species trees using a binary refinement model. For the duplication cost we describe an efficient algorithm that is based on a linear time reduction and also computes an optimal rooted binary refinement of the given gene tree. Finally, we show that similar reductions lead to solutions for computing the deep coalescence and the Robinson-Foulds costs. Our binary refinement of Robinson-Foulds, gene duplication, and deep coalescence costs for unrooted and non-binary gene trees together with the linear time reductions provided here for computing these costs significantly extends the range of trees that can be incorporated into approaches dealing with discordance.

  18. Fungible weights in logistic regression.

    Science.gov (United States)

    Jones, Jeff A; Waller, Niels G

    2016-06-01

    In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  19. Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

    International Nuclear Information System (INIS)

    Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei

    2007-01-01

    Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age

  20. Tumor regression patterns in retinoblastoma

    International Nuclear Information System (INIS)

    Zafar, S.N.; Siddique, S.N.; Zaheer, N.

    2016-01-01

    To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)

  1. Development of molecular tests for the detection of ILAR and latent viruses in fruit trees.

    Science.gov (United States)

    Roussel, S; Kummert, J; Dutrecq, O; Lepoivre, P; Jijakli, M H

    2004-01-01

    The detection throughout the year of latent and ILAR viruses in fruit tress by classical serological tests appear to be unreliable. We have developed RT-PCR tests for a reliable detection of latent and ILAR viruses in fruit trees. These assays were then simplified to allow the direct use of crude plant extracts instead of total RNA preparations, and the analyses of pooled samples. In this way, such RT-PCR protocols are suitable for a routine diagnosis of latent and ILAR viruses in fruit tree certification.

  2. Regression to Causality : Regression-style presentation influences causal attribution

    DEFF Research Database (Denmark)

    Bordacconi, Mats Joe; Larsen, Martin Vinæs

    2014-01-01

    of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

  3. Arvo Pärt jagab preemia koolidele / Rebekka Lotman, Eva Kübar ; kommenteerinud Arvo Pärt

    Index Scriptorium Estoniae

    Lotman, Rebekka, 1978-

    2009-01-01

    Kultuuriministeerium tegi ettepaneku anda Arvo Pärdile elutööpreemia, millega kaasneva rahasumma lubas Pärt kinkida Rakvere ja Paide muusikakoolile. Elutööpreemiad saavad veel Ellen Niit ja Aarne Üksküla

  4. rt Haamer: Tsahknal pole Overalliga mingisugust seost / Märt Haamer ; intervjueerinud Jan Jõgis-Laats

    Index Scriptorium Estoniae

    Haamer, Märt, 1973-

    2009-01-01

    Overall Eesti juhi Märt Haameri väitel pole Anders Tsahkna ühtegi riigihanget Overalli ettevõtetele suunanud. Overalli omandusse kuuluv firma Gennet Lab on olnud alltöövõtja paaris E-tervise Sihtasutuse korraldatud hankes

  5. Regression analysis with categorized regression calibrated exposure: some interesting findings

    Directory of Open Access Journals (Sweden)

    Hjartåker Anette

    2006-07-01

    Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

  6. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  7. Logic regression and its extensions.

    Science.gov (United States)

    Schwender, Holger; Ruczinski, Ingo

    2010-01-01

    Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

  8. Abstract Expression Grammar Symbolic Regression

    Science.gov (United States)

    Korns, Michael F.

    This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.

  9. Quantile Regression With Measurement Error

    KAUST Repository

    Wei, Ying; Carroll, Raymond J.

    2009-01-01

    . The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a

  10. IND - THE IND DECISION TREE PACKAGE

    Science.gov (United States)

    Buntine, W.

    1994-01-01

    A common approach to supervised classification and prediction in artificial intelligence and statistical pattern recognition is the use of decision trees. A tree is "grown" from data using a recursive partitioning algorithm to create a tree which has good prediction of classes on new data. Standard algorithms are CART (by Breiman Friedman, Olshen and Stone) and ID3 and its successor C4 (by Quinlan). As well as reimplementing parts of these algorithms and offering experimental control suites, IND also introduces Bayesian and MML methods and more sophisticated search in growing trees. These produce more accurate class probability estimates that are important in applications like diagnosis. IND is applicable to most data sets consisting of independent instances, each described by a fixed length vector of attribute values. An attribute value may be a number, one of a set of attribute specific symbols, or it may be omitted. One of the attributes is delegated the "target" and IND grows trees to predict the target. Prediction can then be done on new data or the decision tree printed out for inspection. IND provides a range of features and styles with convenience for the casual user as well as fine-tuning for the advanced user or those interested in research. IND can be operated in a CART-like mode (but without regression trees, surrogate splits or multivariate splits), and in a mode like the early version of C4. Advanced features allow more extensive search, interactive control and display of tree growing, and Bayesian and MML algorithms for tree pruning and smoothing. These often produce more accurate class probability estimates at the leaves. IND also comes with a comprehensive experimental control suite. IND consists of four basic kinds of routines: data manipulation routines, tree generation routines, tree testing routines, and tree display routines. The data manipulation routines are used to partition a single large data set into smaller training and test sets. The

  11. From Rasch scores to regression

    DEFF Research Database (Denmark)

    Christensen, Karl Bang

    2006-01-01

    Rasch models provide a framework for measurement and modelling latent variables. Having measured a latent variable in a population a comparison of groups will often be of interest. For this purpose the use of observed raw scores will often be inadequate because these lack interval scale propertie....... This paper compares two approaches to group comparison: linear regression models using estimated person locations as outcome variables and latent regression models based on the distribution of the score....

  12. Testing Heteroscedasticity in Robust Regression

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2011-01-01

    Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf

  13. Regression methods for medical research

    CERN Document Server

    Tai, Bee Choo

    2013-01-01

    Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the

  14. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

  15. Performance Evaluation of Irbene RT-16 Radio Telescope Receiving System

    Directory of Open Access Journals (Sweden)

    Bleiders M.

    2017-12-01

    Full Text Available In the present paper, recent measurement results of refurbished Irbene RT-16 radio telescope receiving system performance are presented. The aim of the research is to evaluate characteristics of RT-16, which will allow carrying out necessary amplitude calibration in both single dish and VLBI observations, to improve the performance of existing system as well as to monitor, control and compare performance if possible changes in the receiving system will occur in future. The evaluated receiving system is 16 m Cassegrain antenna equipped with a cryogenic receiver with frequency range from 4.5 to 8.8 GHz, which is divided into four sub-bands. Multiple calibration sessions have been carried out by observing stable astronomical sources with known flux density by using in-house made total power registration backend. First, pointing offset calibration has been carried out and pointing model coefficients calculated and applied. Then, amplitude calibration, namely antenna sensitivity, calibration diode equivalent flux density and gain curve measurements have been carried out by observing calibration sources at different antenna elevations at each of the receiver sub-bands. Beam patterns have also been evaluated at different frequency bands. As a whole, acquired data will serve as a reference point for comparison in future performance evaluation of RT-16.

  16. NASA SPoRT JPSS PG Activities in Alaska

    Science.gov (United States)

    Berndt, Emily; Molthan, Andrew; Fuell, Kevin; McGrath, Kevin; Smith, Matt; LaFontaine, Frank; Leroy, Anita; White, Kris

    2018-01-01

    SPoRT (NASA's Short-term Prediction Research and Transition Center) has collaboratively worked with Alaska WFOs (Weather Forecast Offices) to introduce RGB (Red/Green/Blue false color image) imagery to prepare for NOAA-20 (National Oceanic and Atmospheric Administration, JPSS (Joint Polar Satellite System) series-20 satellite) VIIRS (Visible Infrared Imaging Radiometer Suite) and improve forecasting aviation-related hazards. Last R2O/O2R (Research-to-Operations/Operations-to-Research) steps include incorporating NOAA-20 VIIRS in RGB suite and fully transitioning client-side RGB processing to GINA (Geographic Information Network of Alaska) and Alaska Region. Alaska Region WFOs have been part of the successful R2O/O2R story to assess the use of NESDIS (National Environmental Satellite, Data, and Information Service) Snowfall Rate product in operations. SPoRT introduced passive microwave rain rate and IMERG (Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement)) (IMERG) to Alaska WFOs for use in radar-void areas and assessing flooding potential. SPoRT has been part of the multi-organization collaborative effort to introduce Gridded NUCAPS (NOAA Unique CrIS/ATMS (Crosstrack Infrared Sounder/Advanced Technology Microwave Sounder) Processing System) to the Anchorage CWSU (Center Weather Service Unit) to assess Cold Air Aloft events, [and as part of NOAA's PG (Product Generation) effort].

  17. WE-H-207B-04: Strategies for Adaptive RT

    Energy Technology Data Exchange (ETDEWEB)

    Green, O. [Washington University School of Medicine (United States)

    2016-06-15

    In recent years, steady progress has been made towards the implementation of MRI in external beam radiation therapy for processes ranging from treatment simulation to in-room guidance. Novel procedures relying mostly on MR data are currently implemented in the clinic. This session will cover topics such as (a) commissioning and quality control of the MR in-room imagers and simulators specific to RT, (b) treatment planning requirements, constraints and challenges when dealing with various MR data, (c) quantification of organ motion with an emphasis on treatment delivery guidance, and (d) MR-driven strategies for adaptive RT workflows. The content of the session was chosen to address both educational and practical key aspects of MR guidance. Learning Objectives: Good understanding of MR testing recommended for in-room MR imaging as well as image data validation for RT chain (e.g. image transfer, filtering for consistency, spatial accuracy, manipulation for task specific); Familiarity with MR-based planning procedures: motivation, core workflow requirements, current status, challenges; Overview of the current methods for the quantification of organ motion; Discussion on approaches for adaptive treatment planning and delivery. T. Stanescu - License agreement with Modus Medical Devices to develop a phantom for the quantification of MR image system-related distortions.; T. Stanescu, N/A.

  18. WE-H-207B-00: MRgRT

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2016-06-15

    In recent years, steady progress has been made towards the implementation of MRI in external beam radiation therapy for processes ranging from treatment simulation to in-room guidance. Novel procedures relying mostly on MR data are currently implemented in the clinic. This session will cover topics such as (a) commissioning and quality control of the MR in-room imagers and simulators specific to RT, (b) treatment planning requirements, constraints and challenges when dealing with various MR data, (c) quantification of organ motion with an emphasis on treatment delivery guidance, and (d) MR-driven strategies for adaptive RT workflows. The content of the session was chosen to address both educational and practical key aspects of MR guidance. Learning Objectives: Good understanding of MR testing recommended for in-room MR imaging as well as image data validation for RT chain (e.g. image transfer, filtering for consistency, spatial accuracy, manipulation for task specific); Familiarity with MR-based planning procedures: motivation, core workflow requirements, current status, challenges; Overview of the current methods for the quantification of organ motion; Discussion on approaches for adaptive treatment planning and delivery. T. Stanescu - License agreement with Modus Medical Devices to develop a phantom for the quantification of MR image system-related distortions.; T. Stanescu, N/A.

  19. GOKaRT: Graphical Online Search Tool for Maps

    Directory of Open Access Journals (Sweden)

    Mechthild Schüler

    2008-09-01

    Full Text Available The map department of the Staats- und Universitätsbibliothek Göttingen together with the Berlin State Library propose a project to develop a web-based graphic cataloguing and search system for maps, to be funded by the German Research Foundation. This tool shall be made available to all map holdings in archives, libraries, university departments and museums in Germany as a comfortable means for the administration of map holdings and as a search tool. Sheets belonging to map series as well as single maps (old and new will be registered cooperatively by the participants with simple tools. This cooperation in data maintenance will facilitate the work especially for understaffed map holdings. Depending on the type of map there are four different mechanisms for map reference. For map series electronic index sheets are used which will show information regarding the various issues of the map sheets. Due to the intuitive graphic search entry GOKaRT-users will easily find the required maps of a certain region available in a chosen holding. User administration modules ensure comfortable handling. GOKaRT is being developed on the basis of licence-free open source programmes. In case financing is provided by the German Research Foundation, GOKaRT can be used free of charge internationally. This would require a contract stipulating data exchange between the partners as well as permanent storage and usability of the data.

  20. WE-H-207B-00: MRgRT

    International Nuclear Information System (INIS)

    2016-01-01

    In recent years, steady progress has been made towards the implementation of MRI in external beam radiation therapy for processes ranging from treatment simulation to in-room guidance. Novel procedures relying mostly on MR data are currently implemented in the clinic. This session will cover topics such as (a) commissioning and quality control of the MR in-room imagers and simulators specific to RT, (b) treatment planning requirements, constraints and challenges when dealing with various MR data, (c) quantification of organ motion with an emphasis on treatment delivery guidance, and (d) MR-driven strategies for adaptive RT workflows. The content of the session was chosen to address both educational and practical key aspects of MR guidance. Learning Objectives: Good understanding of MR testing recommended for in-room MR imaging as well as image data validation for RT chain (e.g. image transfer, filtering for consistency, spatial accuracy, manipulation for task specific); Familiarity with MR-based planning procedures: motivation, core workflow requirements, current status, challenges; Overview of the current methods for the quantification of organ motion; Discussion on approaches for adaptive treatment planning and delivery. T. Stanescu - License agreement with Modus Medical Devices to develop a phantom for the quantification of MR image system-related distortions.; T. Stanescu, N/A

  1. WE-H-207B-04: Strategies for Adaptive RT

    International Nuclear Information System (INIS)

    Green, O.

    2016-01-01

    In recent years, steady progress has been made towards the implementation of MRI in external beam radiation therapy for processes ranging from treatment simulation to in-room guidance. Novel procedures relying mostly on MR data are currently implemented in the clinic. This session will cover topics such as (a) commissioning and quality control of the MR in-room imagers and simulators specific to RT, (b) treatment planning requirements, constraints and challenges when dealing with various MR data, (c) quantification of organ motion with an emphasis on treatment delivery guidance, and (d) MR-driven strategies for adaptive RT workflows. The content of the session was chosen to address both educational and practical key aspects of MR guidance. Learning Objectives: Good understanding of MR testing recommended for in-room MR imaging as well as image data validation for RT chain (e.g. image transfer, filtering for consistency, spatial accuracy, manipulation for task specific); Familiarity with MR-based planning procedures: motivation, core workflow requirements, current status, challenges; Overview of the current methods for the quantification of organ motion; Discussion on approaches for adaptive treatment planning and delivery. T. Stanescu - License agreement with Modus Medical Devices to develop a phantom for the quantification of MR image system-related distortions.; T. Stanescu, N/A

  2. The valuative tree

    CERN Document Server

    Favre, Charles

    2004-01-01

    This volume is devoted to a beautiful object, called the valuative tree and designed as a powerful tool for the study of singularities in two complex dimensions. Its intricate yet manageable structure can be analyzed by both algebraic and geometric means. Many types of singularities, including those of curves, ideals, and plurisubharmonic functions, can be encoded in terms of positive measures on the valuative tree. The construction of these measures uses a natural tree Laplace operator of independent interest.

  3. Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

    Directory of Open Access Journals (Sweden)

    Drzewiecki Wojciech

    2016-12-01

    Full Text Available In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques.

  4. Coded Splitting Tree Protocols

    DEFF Research Database (Denmark)

    Sørensen, Jesper Hemming; Stefanovic, Cedomir; Popovski, Petar

    2013-01-01

    This paper presents a novel approach to multiple access control called coded splitting tree protocol. The approach builds on the known tree splitting protocols, code structure and successive interference cancellation (SIC). Several instances of the tree splitting protocol are initiated, each...... instance is terminated prematurely and subsequently iterated. The combined set of leaves from all the tree instances can then be viewed as a graph code, which is decodable using belief propagation. The main design problem is determining the order of splitting, which enables successful decoding as early...

  5. Morocco - Fruit Tree Productivity

    Data.gov (United States)

    Millennium Challenge Corporation — Date Tree Irrigation Project: The specific objectives of this evaluation are threefold: - Performance evaluation of project activities, like the mid-term evaluation,...

  6. Wood density variation and tree ring distinctness in Gmelina arborea trees by x-ray densitometry

    Directory of Open Access Journals (Sweden)

    Roger Moya

    2009-03-01

    Full Text Available Due to its relationship with other properties, wood density is the main wood quality parameter. Modern, accuratemethods such as X-ray densitometry - are applied to determine the spatial distribution of density in wood sections and to evaluatewood quality. The objectives of this study were to determinate the influence of growing conditions on wood density variation andtree ring demarcation of gmelina trees from fast growing plantations in Costa Rica. The wood density was determined by X-raydensitometry method. Wood samples were cut from gmelina trees and were exposed to low X-rays. The radiographic films weredeveloped and scanned using a 256 gray scale with 1000 dpi resolution and the wood density was determined by CRAD and CERDsoftware. The results showed tree-ring boundaries were distinctly delimited in trees growing in site with rainfall lower than 2510 mm/year. It was demonstrated that tree age, climatic conditions and management of plantation affects wood density and its variability. Thespecific effect of variables on wood density was quantified by for multiple regression method. It was determined that tree yearexplained 25.8% of the total variation of density and 19.9% were caused by climatic condition where the tree growing. Wood densitywas less affected by the intensity of forest management with 5.9% of total variation.

  7. System of programming units for the K556RT4 and K556RT5 fixed programmed memory devices

    International Nuclear Information System (INIS)

    Bobkov, S.G.; Ermolin, Yu.V.; Kantserov, V.A.; Strigin, V.B.

    1983-01-01

    The programming system of constant programmable memory devices K556RT4 and K556RT5 that consist of two units (a programming device and an electrothermotraining unit) is described. The modules are made in the KAMAK standard. The programming device takes up 2 normal places, while the electrothermotraining block takes up 1 place. As information recording is done using a computer the time for programming is reduced and the possibility of errors is limited as compared with the manual method. The computer introduces the whole word to be recorded, not the separate parts, in the programming device. The transition to a new digit of a given word in the programming device is done automatically. This reduces the expense of computer time and accelerates the programming of microdiagrams

  8. Logistic regression for dichotomized counts.

    Science.gov (United States)

    Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

    2016-12-01

    Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

  9. Are trees long-lived?

    Science.gov (United States)

    Kevin T. Smith

    2009-01-01

    Trees and tree care can capture the best of people's motivations and intentions. Trees are living memorials that help communities heal at sites of national tragedy, such as Oklahoma City and the World Trade Center. We mark the places of important historical events by the trees that grew nearby even if the original tree, such as the Charter Oak in Connecticut or...

  10. Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

    Science.gov (United States)

    Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

    2011-01-01

    Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

  11. Producing The New Regressive Left

    DEFF Research Database (Denmark)

    Crone, Christine

    members, this thesis investigates a growing political trend and ideological discourse in the Arab world that I have called The New Regressive Left. On the premise that a media outlet can function as a forum for ideology production, the thesis argues that an analysis of this material can help to trace...... the contexture of The New Regressive Left. If the first part of the thesis lays out the theoretical approach and draws the contextual framework, through an exploration of the surrounding Arab media-and ideoscapes, the second part is an analytical investigation of the discourse that permeates the programmes aired...... becomes clear from the analytical chapters is the emergence of the new cross-ideological alliance of The New Regressive Left. This emerging coalition between Shia Muslims, religious minorities, parts of the Arab Left, secular cultural producers, and the remnants of the political,strategic resistance...

  12. A Matlab program for stepwise regression

    Directory of Open Access Journals (Sweden)

    Yanhong Qi

    2016-03-01

    Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

  13. Correlation and simple linear regression.

    Science.gov (United States)

    Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

    2003-06-01

    In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

  14. Regression filter for signal resolution

    International Nuclear Information System (INIS)

    Matthes, W.

    1975-01-01

    The problem considered is that of resolving a measured pulse height spectrum of a material mixture, e.g. gamma ray spectrum, Raman spectrum, into a weighed sum of the spectra of the individual constituents. The model on which the analytical formulation is based is described. The problem reduces to that of a multiple linear regression. A stepwise linear regression procedure was constructed. The efficiency of this method was then tested by transforming the procedure in a computer programme which was used to unfold test spectra obtained by mixing some spectra, from a library of arbitrary chosen spectra, and adding a noise component. (U.K.)

  15. Nonparametric Mixture of Regression Models.

    Science.gov (United States)

    Huang, Mian; Li, Runze; Wang, Shaoli

    2013-07-01

    Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the US house price index data is illustrated for the proposed methodology.

  16. Fragmentation of random trees

    International Nuclear Information System (INIS)

    Kalay, Z; Ben-Naim, E

    2015-01-01

    We study fragmentation of a random recursive tree into a forest by repeated removal of nodes. The initial tree consists of N nodes and it is generated by sequential addition of nodes with each new node attaching to a randomly-selected existing node. As nodes are removed from the tree, one at a time, the tree dissolves into an ensemble of separate trees, namely, a forest. We study statistical properties of trees and nodes in this heterogeneous forest, and find that the fraction of remaining nodes m characterizes the system in the limit N→∞. We obtain analytically the size density ϕ s of trees of size s. The size density has power-law tail ϕ s ∼s −α with exponent α=1+(1/m). Therefore, the tail becomes steeper as further nodes are removed, and the fragmentation process is unusual in that exponent α increases continuously with time. We also extend our analysis to the case where nodes are added as well as removed, and obtain the asymptotic size density for growing trees. (paper)

  17. The tree BVOC index

    Science.gov (United States)

    J.R. Simpson; E.G. McPherson

    2011-01-01

    Urban trees can produce a number of benefits, among them improved air quality. Biogenic volatile organic compounds (BVOCs) emitted by some species are ozone precursors. Modifying future tree planting to favor lower-emitting species can reduce these emissions and aid air management districts in meeting federally mandated emissions reductions for these compounds. Changes...

  18. Tree growth visualization

    Science.gov (United States)

    L. Linsen; B.J. Karis; E.G. McPherson; B. Hamann

    2005-01-01

    In computer graphics, models describing the fractal branching structure of trees typically exploit the modularity of tree structures. The models are based on local production rules, which are applied iteratively and simultaneously to create a complex branching system. The objective is to generate three-dimensional scenes of often many realistic- looking and non-...

  19. Flowering T Flowering Trees

    Indian Academy of Sciences (India)

    Adansonia digitata L. ( The Baobab Tree) of Bombacaceae is a tree with swollen trunk that attains a dia. of 10m. Leaves are digitately compound with leaflets up to 18cm. long. Flowers are large, solitary, waxy white, and open at dusk. They open in 30 seconds and are bat pollinated. Stamens are many. Fruit is about 30 cm ...

  20. Fault tree graphics

    International Nuclear Information System (INIS)

    Bass, L.; Wynholds, H.W.; Porterfield, W.R.

    1975-01-01

    Described is an operational system that enables the user, through an intelligent graphics terminal, to construct, modify, analyze, and store fault trees. With this system, complex engineering designs can be analyzed. This paper discusses the system and its capabilities. Included is a brief discussion of fault tree analysis, which represents an aspect of reliability and safety modeling

  1. Tree biology and dendrochemistry

    Science.gov (United States)

    Kevin T. Smith; Walter C. Shortle

    1996-01-01

    Dendrochemistry, the interpretation of elemental analysis of dated tree rings, can provide a temporal record of environmental change. Using the dendrochemical record requires an understanding of tree biology. In this review, we pose four questions concerning assumptions that underlie recent dendrochemical research: 1) Does the chemical composition of the wood directly...

  2. Individual tree control

    Science.gov (United States)

    Harvey A. Holt

    1989-01-01

    Controlling individual unwanted trees in forest stands is a readily accepted method for improving the value of future harvests. The practice is especially important in mixed hardwood forests where species differ considerably in value and within species individual trees differ in quality. Individual stem control is a mechanical or chemical weeding operation that...

  3. Trees and Climate Change

    OpenAIRE

    Dettenmaier, Megan; Kuhns, Michael; Unger, Bethany; McAvoy, Darren

    2017-01-01

    This fact sheet describes the complex relationship between forests and climate change based on current research. It explains ways that trees can mitigate some of the risks associated with climate change. It details the impacts that forests are having on the changing climate and discuss specific ways that trees can be used to reduce or counter carbon emissions directly and indirectly.

  4. Structural Equation Model Trees

    Science.gov (United States)

    Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

    2013-01-01

    In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…

  5. Matching Subsequences in Trees

    DEFF Research Database (Denmark)

    Bille, Philip; Gørtz, Inge Li

    2009-01-01

    Given two rooted, labeled trees P and T the tree path subsequence problem is to determine which paths in P are subsequences of which paths in T. Here a path begins at the root and ends at a leaf. In this paper we propose this problem as a useful query primitive for XML data, and provide new...

  6. Environmental tritium in trees

    International Nuclear Information System (INIS)

    Brown, R.M.

    1979-01-01

    The distribution of environmental tritium in the free water and organically bound hydrogen of trees growing in the vicinity of the Chalk River Nuclear Laboratories (CRNL) has been studied. The regional dispersal of HTO in the atmosphere has been observed by surveying the tritium content of leaf moisture. Measurement of the distribution of organically bound tritium in the wood of tree ring sequences has given information on past concentrations of HTO taken up by trees growing in the CRNL Liquid Waste Disposal Area. For samples at background environmental levels, cellulose separation and analysis was done. The pattern of bomb tritium in precipitation of 1955-68 was observed to be preserved in the organically bound tritium of a tree ring sequence. Reactor tritium was discernible in a tree growing at a distance of 10 km from CRNL. These techniques provide convenient means of monitoring dispersal of HTO from nuclear facilities. (author)

  7. Generalising tree traversals and tree transformations to DAGs

    DEFF Research Database (Denmark)

    Bahr, Patrick; Axelsson, Emil

    2017-01-01

    We present a recursion scheme based on attribute grammars that can be transparently applied to trees and acyclic graphs. Our recursion scheme allows the programmer to implement a tree traversal or a tree transformation and then apply it to compact graph representations of trees instead. The resul......We present a recursion scheme based on attribute grammars that can be transparently applied to trees and acyclic graphs. Our recursion scheme allows the programmer to implement a tree traversal or a tree transformation and then apply it to compact graph representations of trees instead...... as the complementing theory with a number of examples....

  8. Measuring performance in health care: case-mix adjustment by boosted decision trees.

    Science.gov (United States)

    Neumann, Anke; Holstein, Josiane; Le Gall, Jean-Roger; Lepage, Eric

    2004-10-01

    The purpose of this paper is to investigate the suitability of boosted decision trees for the case-mix adjustment involved in comparing the performance of various health care entities. First, we present logistic regression, decision trees, and boosted decision trees in a unified framework. Second, we study in detail their application for two common performance indicators, the mortality rate in intensive care and the rate of potentially avoidable hospital readmissions. For both examples the technique of boosting decision trees outperformed standard prognostic models, in particular linear logistic regression models, with regard to predictive power. On the other hand, boosting decision trees was computationally demanding and the resulting models were rather complex and needed additional tools for interpretation. Boosting decision trees represents a powerful tool for case-mix adjustment in health care performance measurement. Depending on the specific priorities set in each context, the gain in predictive power might compensate for the inconvenience in the use of boosted decision trees.

  9. Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

    Science.gov (United States)

    Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

    2008-01-01

    This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

  10. Detection and Analysis of Circular RNAs by RT-PCR.

    Science.gov (United States)

    Panda, Amaresh C; Gorospe, Myriam

    2018-03-20

    Gene expression in eukaryotic cells is tightly regulated at the transcriptional and posttranscriptional levels. Posttranscriptional processes, including pre-mRNA splicing, mRNA export, mRNA turnover, and mRNA translation, are controlled by RNA-binding proteins (RBPs) and noncoding (nc)RNAs. The vast family of ncRNAs comprises diverse regulatory RNAs, such as microRNAs and long noncoding (lnc)RNAs, but also the poorly explored class of circular (circ)RNAs. Although first discovered more than three decades ago by electron microscopy, only the advent of high-throughput RNA-sequencing (RNA-seq) and the development of innovative bioinformatic pipelines have begun to allow the systematic identification of circRNAs (Szabo and Salzman, 2016; Panda et al ., 2017b; Panda et al ., 2017c). However, the validation of true circRNAs identified by RNA sequencing requires other molecular biology techniques including reverse transcription (RT) followed by conventional or quantitative (q) polymerase chain reaction (PCR), and Northern blot analysis (Jeck and Sharpless, 2014). RT-qPCR analysis of circular RNAs using divergent primers has been widely used for the detection, validation, and sometimes quantification of circRNAs (Abdelmohsen et al ., 2015 and 2017; Panda et al ., 2017b). As detailed here, divergent primers designed to span the circRNA backsplice junction sequence can specifically amplify the circRNAs and not the counterpart linear RNA. In sum, RT-PCR analysis using divergent primers allows direct detection and quantification of circRNAs.

  11. Cactus: An Introduction to Regression

    Science.gov (United States)

    Hyde, Hartley

    2008-01-01

    When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…

  12. Regression Models for Repairable Systems

    Czech Academy of Sciences Publication Activity Database

    Novák, Petr

    2015-01-01

    Roč. 17, č. 4 (2015), s. 963-972 ISSN 1387-5841 Institutional support: RVO:67985556 Keywords : Reliability analysis * Repair models * Regression Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.782, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/novak-0450902.pdf

  13. Survival analysis II: Cox regression

    NARCIS (Netherlands)

    Stel, Vianda S.; Dekker, Friedo W.; Tripepi, Giovanni; Zoccali, Carmine; Jager, Kitty J.

    2011-01-01

    In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the

  14. Kernel regression with functional response

    OpenAIRE

    Ferraty, Frédéric; Laksaci, Ali; Tadj, Amel; Vieu, Philippe

    2011-01-01

    We consider kernel regression estimate when both the response variable and the explanatory one are functional. The rates of uniform almost complete convergence are stated as function of the small ball probability of the predictor and as function of the entropy of the set on which uniformity is obtained.

  15. MINIX4RT: real-time interprocess communications facilities

    OpenAIRE

    Pessolani, Pablo Andrés

    2006-01-01

    MINIX4RT es una extensión del conocido Sistema Operativo MINIX que incorpora servicios de Tiempo Real Estricto en un nuevo microkernel pero manteniendo compatibilidad con las versiones anteriores del MINIX estándar. La Comunicación entre Procesos es un mecanismo que permite hacer extensible a un Sistema Operativo, pero debe estar libre de Inversión de Prioridades para ser utilizado en aplicaciones de Tiempo Real. Como las primitivas de MINIX no disponen de esta funcionalidad, se incorporar...

  16. Applications of LANCE Data at SPoRT

    Science.gov (United States)

    Molthan, Andrew

    2014-01-01

    Short term Prediction Research and Transition (SPoRT) Center: Mission: Apply NASA and NOAA measurement systems and unique Earth science research to improve the accuracy of short term weather prediction at the regional/local scale. Goals: Evaluate and assess the utility of NASA and NOAA Earth science data and products and unique research capabilities to address operational weather forecast problems; Provide an environment which enables the development and testing of new capabilities to improve short term weather forecasts on a regional scale; Help ensure successful transition of new capabilities to operational weather entities for the benefit of society

  17. SMAP Data Assimilation at NASA SPoRT

    Science.gov (United States)

    Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

    2016-01-01

    The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.

  18. Quantitation of TGF-beta1 mRNA in porcine mesangial cells by comparative kinetic RT/PCR: comparison with ribonuclease protection assay and in situ hybridization.

    Science.gov (United States)

    Ceol, M; Forino, M; Gambaro, G; Sauer, U; Schleicher, E D; D'Angelo, A; Anglani, F

    2001-01-01

    Gene expression can be examined with different techniques including ribonuclease protection assay (RPA), in situ hybridisation (ISH), and quantitative reverse transcription-polymerase chain reaction (RT/PCR). These methods differ considerably in their sensitivity and precision in detecting and quantifying low abundance mRNA. Although there is evidence that RT/PCR can be performed in a quantitative manner, the quantitative capacity of this method is generally underestimated. To demonstrate that the comparative kinetic RT/PCR strategy-which uses a housekeeping gene as internal standard-is a quantitative method to detect significant differences in mRNA levels between different samples, the inhibitory effect of heparin on phorbol 12-myristate 13-acetate (PMA)-induced-TGF-beta1 mRNA expression was evaluated by RT/PCR and RPA, the standard method of mRNA quantification, and the results were compared. The reproducibility of RT/PCR amplification was calculated by comparing the quantity of G3PDH and TGF-beta1 PCR products, generated during the exponential phases, estimated from two different RT/PCR (G3PDH, r = 0.968, P = 0.0000; TGF-beta1, r = 0.966, P = 0.0000). The quantitative capacity of comparative kinetic RT/PCR was demonstrated by comparing the results obtained from RPA and RT/PCR using linear regression analysis. Starting from the same RNA extraction, but using only 1% of the RNA for the RT/PCR compared to RPA, significant correlation was observed (r = 0.984, P = 0.0004). Moreover the morphometric analysis of ISH signal was applied for the semi-quantitative evaluation of the expression and localisation of TGF-beta1 mRNA in the entire cell population. Our results demonstrate the close similarity of the RT/PCR and RPA methods in giving quantitative information on mRNA expression and indicate the possibility to adopt the comparative kinetic RT/PCR as reliable quantitative method of mRNA analysis. Copyright 2001 Wiley-Liss, Inc.

  19. An overview of decision tree applied to power systems

    DEFF Research Database (Denmark)

    Liu, Leo; Rather, Zakir Hussain; Chen, Zhe

    2013-01-01

    The corrosive volume of available data in electric power systems motivate the adoption of data mining techniques in the emerging field of power system data analytics. The mainstream of data mining algorithm applied to power system, Decision Tree (DT), also named as Classification And Regression...... Tree (CART), has gained increasing interests because of its high performance in terms of computational efficiency, uncertainty manageability, and interpretability. This paper presents an overview of a variety of DT applications to power systems for better interfacing of power systems with data...... analytics. The fundamental knowledge of CART algorithm is also introduced which is then followed by examples of both classification tree and regression tree with the help of case study for security assessment of Danish power system....

  20. Characteristics of the tree-drawing test in chronic schizophrenia.

    Science.gov (United States)

    Kaneda, Ayako; Yasui-Furukori, Norio; Saito, Manabu; Sugawara, Norio; Nakagami, Taku; Furukori, Hanako; Kaneko, Sunao

    2010-04-01

    A tree-drawing test acts as both a projective psychological examination as well as a supplementary psychodiagnostic tool. There is little information relating the characteristics of schizophrenia and the tree-drawing test. The present study compared the structural and morphological differences in the results of the tree-drawing test between schizophrenic patients and healthy individuals, as well as between schizophrenic patients who responded well to treatment and those who responded poorly. The subjects included 202 chronic schizophrenic patients and 113 healthy individuals. The schizophrenic patients were categorized as 'good responders' or 'poor responders' based on their response to medical treatments. The tree-drawing test was performed on all subjects. The tree drawn by each subject was analyzed structurally and morphologically. There were significant differences between the trunk and branches drawn by schizophrenic patients and those drawn by healthy controls. There were no significant differences between the good responders and the poor responders in any aspect of the tree drawings. Multiple regression models showed that the ratio of the tree area to the total area of the drawing paper, the width of the trunk, the trunk base opening, and the size of the branch ends were significantly associated with schizophrenia. The present study suggests that the trees drawn by schizophrenic patients are significantly different from those drawn by healthy individuals, but among schizophrenic patients, it is difficult to distinguish between good responders and poor responders using the tree-drawing test.

  1. A recursive algorithm for trees and forests

    OpenAIRE

    Guo, Song; Guo, Victor J. W.

    2017-01-01

    Trees or rooted trees have been generously studied in the literature. A forest is a set of trees or rooted trees. Here we give recurrence relations between the number of some kind of rooted forest with $k$ roots and that with $k+1$ roots on $\\{1,2,\\ldots,n\\}$. Classical formulas for counting various trees such as rooted trees, bipartite trees, tripartite trees, plane trees, $k$-ary plane trees, $k$-edge colored trees follow immediately from our recursive relations.

  2. Phylogenetic trees in bioinformatics

    Energy Technology Data Exchange (ETDEWEB)

    Burr, Tom L [Los Alamos National Laboratory

    2008-01-01

    Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including: the types of data used to represent each OTU; the use ofprobabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that fmding the best tree(s) to describe the genetic data for each OTU is computationally demanding. Bioinformatics is too large a field to review here. We focus on that aspect of bioinformatics that includes study of similarities in genetic data from multiple OTUs. Although research questions are diverse, a common underlying challenge is to estimate the evolutionary history of the OTUs. Therefore, this paper reviews the role of phylogenetic tree estimation in bioinformatics, available methods and software, and identifies areas for additional research and development.

  3. Skewed Binary Search Trees

    DEFF Research Database (Denmark)

    Brodal, Gerth Stølting; Moruz, Gabriel

    2006-01-01

    It is well-known that to minimize the number of comparisons a binary search tree should be perfectly balanced. Previous work has shown that a dominating factor over the running time for a search is the number of cache faults performed, and that an appropriate memory layout of a binary search tree...... can reduce the number of cache faults by several hundred percent. Motivated by the fact that during a search branching to the left or right at a node does not necessarily have the same cost, e.g. because of branch prediction schemes, we in this paper study the class of skewed binary search trees....... For all nodes in a skewed binary search tree the ratio between the size of the left subtree and the size of the tree is a fixed constant (a ratio of 1/2 gives perfect balanced trees). In this paper we present an experimental study of various memory layouts of static skewed binary search trees, where each...

  4. The SPoRT concept of bracing for idiopathic scoliosis.

    Science.gov (United States)

    Zaina, Fabio; Fusco, Claudia; Atanasio, Salvatore; Negrini, Stefano

    2011-01-01

    The SPoRT (acronym: Symmetrical, Patient-oriented, Rigid, Three-dimensional, active) concept of bracing is a new way to build braces based on our 20 years of experience and the biomechanical principles of scoliosis correction, inclusive of the Sibilla and Sforzesco braces. The concept always requires a custom brace, which is made according to the patient's individual requirements. New technologies such as CAD-CAM can be applied, and often for better results, without the customary use of prebuilt forms whose measurements are stored in databases. Once the initial draft brace is completed, a final test must be made on the patient to modify and adapt it, depending on his or her real interaction between the body and the brace. The results that are today available on the SPoRT concept relate to the Sforzesco brace and are necessarily short-term, because the first treated patients are now reaching the fourth-year follow-up examination and haven't yet completed their treatments. On the basis of the initial evaluations, we can state that the Sforzesco brace is more effective than the Lyon brace after 6 months of treatment and that the Sforzesco brace is equally effective as the Risser Plast brace.

  5. Used mixed oxide fuel reprocessing at RT-1 plant

    Energy Technology Data Exchange (ETDEWEB)

    Kolupaev, D.; Logunov, M.; Mashkin, A.; Bugrov, K.; Korchenkin, K. [FSUE PA ' Mayak' , 30, Lenins str, Ozersk, 460065 (Russian Federation); Shadrin, A.; Dvoeglazov, K. [ITCP ' PRORYV' , 2/8 Malaya Krasmoselskay str, Moscow, 107140 (Russian Federation)

    2016-07-01

    Reprocessing of the mixed uranium-plutonium spent nuclear fuel of the BN-600 reactor was performed at the RT-1 plant twice, in 2012 and 2014. In total, 8 fuel assemblies with a burn-up from 73 to 89 GW day/t and the cooling time from 17 to 21 years were reprocessed. The reprocessing included the stages of dissolution, clarification, extraction separation of U and Pu with purification from the fission products, refining of uranium and plutonium at the relevant refining cycles. Dissolution of the fuel composition of MOX used nuclear fuel (UNF) in nitric acid solutions in the presence of fluoride ion has occurred with the full transfer of actinides into solution. Due to the high content of Pu extraction separation of U and Pu was carried out on a nuclear-safe equipment designed for the reprocessing of highly enriched U spent nuclear fuel and Pu refining. Technological processes of extraction, separation and refining of actinides proceeded without deviations from the normal mode. The output flow of the extraction outlets in their compositions corresponded to the regulatory norms and remained at the level of the compositions of the streams resulting from the reprocessing of fuel types typical for the RT-1 plant. No increased losses of Pu into waste have been registered during the reprocessing of BN-600 MOX UNF an compare with VVER-440 uranium UNF reprocessing. (authors)

  6. Request for regular monitoring of the symbiotic variable RT Cru

    Science.gov (United States)

    Waagen, Elizabeth O.

    2014-08-01

    Dr. Margarita Karovska (Harvard-Smithsonian Center for Astrophysics) and colleagues have requested AAVSO observer assistance in their campaign on the symbiotic variable RT Cru (member of a new class of hard X-ray emitting symbiotic binaries). Weekly or more frequent monitoring (B, V, and visual) beginning now is requested in support of upcoming Chandra observations still to be scheduled. "We plan Chandra observations of RT Cru in the near future that will help us understand the characteristics of the accretion onto the white dwarf in this sub-class of symbiotics. This is an important step for determining the precursor conditions for formation of a fraction of asymmetric Planetary Nebulae, and the potential of symbiotic systems as progenitors of at least a fraction of Type Ia supernovae." Finder charts with sequence may be created using the AAVSO Variable Star Plotter (http://www.aavso.org/vsp). Observations should be submitted to the AAVSO International Database. See full Alert Notice for more details and observations.

  7. More Trees, More Poverty? The Socioeconomic Effects of Tree Plantations in Chile, 2001-2011

    Science.gov (United States)

    Andersson, Krister; Lawrence, Duncan; Zavaleta, Jennifer; Guariguata, Manuel R.

    2016-01-01

    Tree plantations play a controversial role in many nations' efforts to balance goals for economic development, ecological conservation, and social justice. This paper seeks to contribute to this debate by analyzing the socioeconomic impact of such plantations. We focus our study on Chile, a country that has experienced extraordinary growth of industrial tree plantations. Our analysis draws on a unique dataset with longitudinal observations collected in 180 municipal territories during 2001-2011. Employing panel data regression techniques, we find that growth in plantation area is associated with higher than average rates of poverty during this period.

  8. Global variation in woodpecker species richness shaped by tree availability

    DEFF Research Database (Denmark)

    Ilsoe, Sigrid Kistrup; Kissling, W. Daniel; Fjeldsa, Jon

    2017-01-01

    . Location: Global. Methods: We used spatial and non-spatial regressions to test for relationships between broad-scale woodpecker species richness and predictor variables describing current and deep-time availability of trees, current climate, Quaternary climate change, human impact, topographical...... a negative indirect effect on woodpecker species richness. Main conclusions: Global species richness of woodpeckers is primarily shaped by current tree cover and precipitation, reflecting a strong biotic association between woodpeckers and trees. Human influence can have a negative effect on woodpecker....... As an example, woodpeckers (Picidae) are closely associated with trees and woody habitats because of multiple morphological and ecological specializations. In this study, we test whether this strong biotic association causes woodpecker diversity to be closely linked to tree availability at a global scale...

  9. Arvo Pärt: Kui kannatab üks inimene, siis kannatab kogu maailm! / Arvo Pärt, Nora Pärt ; intervjueerinud Yana Toom, Maarja-Liis Arujärv, Aleksandr Zukerman ; kommenteerinud Edgar Savisaar

    Index Scriptorium Estoniae

    Pärt, Arvo, 1935-

    2010-01-01

    Arvo Pärt ja tema abikaasa Nora Pärt andsid Türgis enne Pärdi uudisteose "Aadama itk" esiettekannet intervjuu, kus rääkisid nii nende raskustest Läände elama asumisel kui uudisteose sügavamast mõttest

  10. The gravity apple tree

    International Nuclear Information System (INIS)

    Aldama, Mariana Espinosa

    2015-01-01

    The gravity apple tree is a genealogical tree of the gravitation theories developed during the past century. The graphic representation is full of information such as guides in heuristic principles, names of main proponents, dates and references for original articles (See under Supplementary Data for the graphic representation). This visual presentation and its particular classification allows a quick synthetic view for a plurality of theories, many of them well validated in the Solar System domain. Its diachronic structure organizes information in a shape of a tree following similarities through a formal concept analysis. It can be used for educational purposes or as a tool for philosophical discussion. (paper)

  11. Visualizing phylogenetic tree landscapes.

    Science.gov (United States)

    Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A

    2017-02-02

    Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D

  12. Quantile Regression With Measurement Error

    KAUST Repository

    Wei, Ying

    2009-08-27

    Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The method corrects the measurement error induced bias by constructing joint estimating equations that simultaneously hold for all the quantile levels. An iterative EM-type estimation algorithm to obtain the solutions to such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure. © 2009 American Statistical Association.

  13. Global Dynamics and International Cooperation Needs of RT Development and Utilization for the Establishment of the Northeast Asia RT Hub in Korea

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Y. K.; Oh, G. B.; Yun, S. W.; Yang, M. H.; Ryu, J. S.; Choi, S. J.; Choi, S. G

    2005-11-15

    In an effort to achieve the objectives, the following scopes were categorized for in-depth study. First, analysis framework was developed for RT capacity development and international technology cooperation strategy. RT survey checklist and international technology cooperation was analyzed with interviewing and reports of domestic participants recently. Second, RT strategic environment was analyze for East-Asia hub competition/cooperation and developing nations using analysis framework. Korean RT was analyzed using SWOT analysis for establishment of RT hub in Korea. Third, East-Asian nations were classified analyzed by RT categories in standpoint of our country. Technology status and future cooperation plan were discussed about RT application for bio-medicine. Products/technology seminar related to an export was hold about support plan of admission/sales for functional food HemoHIM. This study can be utilized in the establishment of RT hub and development strategy. And it can be also utilized in promotion devising of domestic RT and planning setup for obtaing the international competitive power.

  14. Global Dynamics and International Cooperation Needs of RT Development and Utilization for the Establishment of the Northeast Asia RT Hub in Korea

    International Nuclear Information System (INIS)

    Kim, Y. K.; Oh, G. B.; Yun, S. W.; Yang, M. H.; Ryu, J. S.; Choi, S. J.; Choi, S. G.

    2005-11-01

    In an effort to achieve the objectives, the following scopes were categorized for in-depth study. First, analysis framework was developed for RT capacity development and international technology cooperation strategy. RT survey checklist and international technology cooperation was analyzed with interviewing and reports of domestic participants recently. Second, RT strategic environment was analyze for East-Asia hub competition/cooperation and developing nations using analysis framework. Korean RT was analyzed using SWOT analysis for establishment of RT hub in Korea. Third, East-Asian nations were classified analyzed by RT categories in standpoint of our country. Technology status and future cooperation plan were discussed about RT application for bio-medicine. Products/technology seminar related to an export was hold about support plan of admission/sales for functional food HemoHIM. This study can be utilized in the establishment of RT hub and development strategy. And it can be also utilized in promotion devising of domestic RT and planning setup for obtaing the international competitive power

  15. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

    The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

  16. Regression algorithm for emotion detection

    OpenAIRE

    Berthelon , Franck; Sander , Peter

    2013-01-01

    International audience; We present here two components of a computational system for emotion detection. PEMs (Personalized Emotion Maps) store links between bodily expressions and emotion values, and are individually calibrated to capture each person's emotion profile. They are an implementation based on aspects of Scherer's theoretical complex system model of emotion~\\cite{scherer00, scherer09}. We also present a regression algorithm that determines a person's emotional feeling from sensor m...

  17. Directional quantile regression in R

    Czech Academy of Sciences Publication Activity Database

    Boček, Pavel; Šiman, Miroslav

    2017-01-01

    Roč. 53, č. 3 (2017), s. 480-492 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : multivariate quantile * regression quantile * halfspace depth * depth contour Subject RIV: BD - Theory of Information OBOR OECD: Applied mathematics Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf

  18. Generalized allometric regression to estimate biomass of Populus in short-rotation coppice

    Energy Technology Data Exchange (ETDEWEB)

    Ben Brahim, Mohammed; Gavaland, Andre; Cabanettes, Alain [INRA Centre de Toulouse, Castanet-Tolosane Cedex (France). Unite Agroforesterie et Foret Paysanne

    2000-07-01

    Data from four different stands were combined to establish a single generalized allometric equation to estimate above-ground biomass of individual Populus trees grown on short-rotation coppice. The generalized model was performed using diameter at breast height, the mean diameter and the mean height of each site as dependent variables and then compared with the stand-specific regressions using F-test. Results showed that this single regression estimates tree biomass well at each stand and does not introduce bias with increasing diameter.

  19. Polylinear regression analysis in radiochemistry

    International Nuclear Information System (INIS)

    Kopyrin, A.A.; Terent'eva, T.N.; Khramov, N.N.

    1995-01-01

    A number of radiochemical problems have been formulated in the framework of polylinear regression analysis, which permits the use of conventional mathematical methods for their solution. The authors have considered features of the use of polylinear regression analysis for estimating the contributions of various sources to the atmospheric pollution, for studying irradiated nuclear fuel, for estimating concentrations from spectral data, for measuring neutron fields of a nuclear reactor, for estimating crystal lattice parameters from X-ray diffraction patterns, for interpreting data of X-ray fluorescence analysis, for estimating complex formation constants, and for analyzing results of radiometric measurements. The problem of estimating the target parameters can be incorrect at certain properties of the system under study. The authors showed the possibility of regularization by adding a fictitious set of data open-quotes obtainedclose quotes from the orthogonal design. To estimate only a part of the parameters under consideration, the authors used incomplete rank models. In this case, it is necessary to take into account the possibility of confounding estimates. An algorithm for evaluating the degree of confounding is presented which is realized using standard software or regression analysis

  20. Gaussian Process Regression Model in Spatial Logistic Regression

    Science.gov (United States)

    Sofro, A.; Oktaviarina, A.

    2018-01-01

    Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

  1. Tree-growth analyses to estimate tree species' drought tolerance

    NARCIS (Netherlands)

    Eilmann, B.; Rigling, A.

    2012-01-01

    Climate change is challenging forestry management and practices. Among other things, tree species with the ability to cope with more extreme climate conditions have to be identified. However, while environmental factors may severely limit tree growth or even cause tree death, assessing a tree

  2. Big trees, old trees, and growth factor tables

    Science.gov (United States)

    Kevin T. Smith

    2018-01-01

    The potential for a tree to reach a great size and to live a long life frequently captures the public's imagination. Sometimes the desire to know the age of an impressively large tree is simple curiosity. For others, the date-of-tree establishment can make a big diff erence for management, particularly for trees at historic sites or those mentioned in property...

  3. A bijection between phylogenetic trees and plane oriented recursive trees

    OpenAIRE

    Prodinger, Helmut

    2017-01-01

    Phylogenetic trees are binary nonplanar trees with labelled leaves, and plane oriented recursive trees are planar trees with an increasing labelling. Both families are enumerated by double factorials. A bijection is constructed, using the respective representations a 2-partitions and trapezoidal words.

  4. A Suffix Tree Or Not a Suffix Tree?

    DEFF Research Database (Denmark)

    Starikovskaya, Tatiana; Vildhøj, Hjalte Wedel

    2015-01-01

    In this paper we study the structure of suffix trees. Given an unlabeled tree r on n nodes and suffix links of its internal nodes, we ask the question “Is r a suffix tree?”, i.e., is there a string S whose suffix tree has the same topological structure as r? We place no restrictions on S, in part...

  5. NLCD 2001 - Tree Canopy

    Data.gov (United States)

    Minnesota Department of Natural Resources — The National Land Cover Database 2001 tree canopy layer for Minnesota (mapping zones 39-42, 50-51) was produced through a cooperative project conducted by the...

  6. Trees for future forests

    DEFF Research Database (Denmark)

    Lobo, Albin

    Climate change creates new challenges in forest management. The increase in temperature may in the long run be beneficial for the forests in the northern latitudes, but the high rate at which climate change is predicted to proceed will make adaptation difficult because trees are long living sessile...... organisms. The aim of the present thesis is therefore to explore genetic resilience and phenotypic plasticity mechanisms that allows trees to adapt and evolve with changing climates. The thesis focus on the abiotic factors associated with climate change, especially raised temperatures and lack...... age of these tree species and the uncertainty around the pace and effect of climate, it remains an open question if the native populations can respond fast enough. Phenotypic plasticity through epigenetic regulation of spring phenology is found to be present in a tree species which might act...

  7. Value tree analysis

    International Nuclear Information System (INIS)

    Keeney, R.; Renn, O.; Winterfeldt, D. von; Kotte, U.

    1985-01-01

    What are the targets and criteria on which national energy policy should be based. What priorities should be set, and how can different social interests be matched. To answer these questions, a new instrument of decision theory is presented which has been applied with good results to controversial political issues in the USA. The new technique is known under the name of value tree analysis. Members of important West German organisations (BDI, VDI, RWE, the Catholic and Protestant Church, Deutscher Naturschutzring, and ecological research institutions) were asked about the goals of their organisations. These goals were then ordered systematically and arranged in a hierarchical tree structure. The value trees of different groups can be combined into a catalogue of social criteria of acceptability and policy assessment. The authors describe the philosophy and methodology of value tree analysis and give an outline of its application in the development of a socially acceptable energy policy. (orig.) [de

  8. Management and Development of the RT Research Facilities and Infrastructures

    International Nuclear Information System (INIS)

    Kim, Won Ho; Nho, Young Chang; Kim, Jae Sung

    2009-01-01

    The purpose of this project are to operate the core facilities of the research for the Radiation Technology in stable and to assist the research activities efficiently in the industry, academic, and research laboratory. By developing the infrastructure of the national radio technology industry, we can activate the researching area of the RT and the related industry, and obtain the primary and original technology. The key point in the study of the RT and the assistance of the industry, academic, and research laboratory for the RT area smoothly, is managing the various of unique radiation facilities in our country. The gamma Phytotron and Gene Bank are essential in the agribiology because these facilities are used to preserve and utilize the genes and to provide an experimental field for the environment and biotechnology. The Radiation Fusion Technology research supporting facilities are the core support facilities, and are used to develop the high-tech fusion areas. In addition, the most advanced analytical instruments, whose costs are very high, should be managed in stable and be utilized in supporting works, and the experimental animal supporting laboratory and Gamma Cell have to be maintained in high level and managed in stable also. The ARTI have been developed the 30MeV cyclotron during 2005∼2006, aimed to produce radioisotopes and to research the beam applications as a result of the project, 'Establishment of the Infrastructure for the Atomic Energy Research Expansion', collaborated with the Korea Institute of Radiological and Medical Sciences. In addition, the ARTI is in the progress of establishing cyclotron integrated complex as a core research facility, using a proton beam to produce radioisotopes and to support a various research areas. The measurement and evaluation of the irradiation dose, and irradiation supporting technology of the Good Irradiation Practice(GIP) are essential in various researching areas. One thing to remember is that the publicity

  9. Arquitectura de los árboles Tree architecture

    Directory of Open Access Journals (Sweden)

    Francis Hallé

    2010-12-01

    understand what a tree is: this mechanism turns a tree into a colony; «reiterated trees» (RT grow on top of each other the way parasites do. Reiteration means the birth of an entire tree, with trunk, branches and roots. A young RT grows vertically; then, with the help of wood plasticity and a lever, it inclines and turns horizontal, thus becoming more efficient in light capturing. It has been a relevant discovery to find, within a single tree crown, genetic variations from one RT to another: in several species, a tree is a colony of genomes.

  10. Multiscale singularity trees

    DEFF Research Database (Denmark)

    Somchaipeng, Kerawit; Sporring, Jon; Johansen, Peter

    2007-01-01

    We propose MultiScale Singularity Trees (MSSTs) as a structure to represent images, and we propose an algorithm for image comparison based on comparing MSSTs. The algorithm is tested on 3 public image databases and compared to 2 state-of-theart methods. We conclude that the computational complexity...... of our algorithm only allows for the comparison of small trees, and that the results of our method are comparable with state-of-the-art using much fewer parameters for image representation....

  11. Type extension trees

    DEFF Research Database (Denmark)

    Jaeger, Manfred

    2006-01-01

    We introduce type extension trees as a formal representation language for complex combinatorial features of relational data. Based on a very simple syntax this language provides a unified framework for expressing features as diverse as embedded subgraphs on the one hand, and marginal counts...... of attribute values on the other. We show by various examples how many existing relational data mining techniques can be expressed as the problem of constructing a type extension tree and a discriminant function....

  12. Tree felling 2014

    CERN Multimedia

    2014-01-01

    With a view to creating new landscapes and making its population of trees safer and healthier, this winter CERN will complete the tree-felling campaign started in 2010.   Tree felling will take place between 15 and 22 November on the Swiss part of the Meyrin site. This work is being carried out above all for safety reasons. The trees to be cut down are at risk of falling as they are too old and too tall to withstand the wind. In addition, the roots of poplar trees are very powerful and spread widely, potentially damaging underground networks, pavements and roadways. Compensatory tree planting campaigns will take place in the future, subject to the availability of funding, with the aim of creating coherent landscapes while also respecting the functional constraints of the site. These matters are being considered in close collaboration with the Geneva nature and countryside directorate (Direction générale de la nature et du paysage, DGNP). GS-SE Group

  13. Laguna Verde simulator: A new TRAC-RT based application

    International Nuclear Information System (INIS)

    Munoz Cases, J.J.; Tanarro Onrubia, A.

    2006-01-01

    In a partnership with GSE Systems, TECNATOM is developing a full scope training simulator for Laguna Verde Unit 2 (LV2). The simulator design is based upon the current 'state-of-the art technology' regarding the simulation platform, instructor station, visualization tools, advanced thermalhydraulics and neutronics models, I/O systems and automated model building technology. When completed, LV2 simulator will achieve a remarkable level of modeling fidelity by using TECNATOM's TRAC-RT advanced thermalhydraulic code for the reactor coolant and main steam systems, and NEMO neutronic model for the reactor core calculations. These models have been utilized up to date for the development or upgrading of nine NPP simulators in Spain and abroad, with more than 8000 hours of training sessions, and have developed an excellent reputation for its robustness and high fidelity. (author)

  14. Benefit-based tree valuation

    Science.gov (United States)

    E.G. McPherson

    2007-01-01

    Benefit-based tree valuation provides alternative estimates of the fair and reasonable value of trees while illustrating the relative contribution of different benefit types. This study compared estimates of tree value obtained using cost- and benefit-based approaches. The cost-based approach used the Council of Landscape and Tree Appraisers trunk formula method, and...

  15. Attack Trees with Sequential Conjunction

    NARCIS (Netherlands)

    Jhawar, Ravi; Kordy, Barbara; Mauw, Sjouke; Radomirović, Sasa; Trujillo-Rasua, Rolando

    2015-01-01

    We provide the first formal foundation of SAND attack trees which are a popular extension of the well-known attack trees. The SAND at- tack tree formalism increases the expressivity of attack trees by intro- ducing the sequential conjunctive operator SAND. This operator enables the modeling of

  16. [Luuletused] / William Wordsworth ; tlk. Märt Väljataga

    Index Scriptorium Estoniae

    Wordsworth, William

    2004-01-01

    Sisu: Värsid, mis kirjutatud mõned miilid Tintern Abbeyst ülalpool... ; "Mõnd kirevahku kummalist..." ; "Käis vaikselt ojakalda peal..." ; "Kolm aastat sirguda ta võis..." ; "Mu hinge piiras unesulg..." ; "Kui mere taha viia ma..." ; Jugapuud. Saatesõna lk. 24. Orig.: Lines composed a few miles above Tintern Abbey... ; "Strange fits of passion have I known..." ; "She dwelt among the untrodden ways..." ; "Three years she grew..." ; "A slumber did my spirit seal..." ; "I traveled among unknown men..." ; Yew trees

  17. Tree manipulation experiment

    Science.gov (United States)

    Nishina, K.; Takenaka, C.; Ishizuka, S.; Hashimoto, S.; Yagai, Y.

    2012-12-01

    Some forest operations such as thinning and harvesting management could cause changes in N cycling and N2O emission from soils, since thinning and harvesting managements are accompanied with changes in aboveground environments such as an increase of slash falling and solar radiation on the forest floor. However, a considerable uncertainty exists in effects of thinning and harvesting on N2O fluxes regarding changes in belowground environments by cutting trees. To focus on the effect of changes in belowground environments on the N2O emissions from soils, we conducted a tree manipulation experiment in Japanese cedar (Cryptomeria japonica) stand without soil compaction and slash falling near the chambers and measured N2O flux at 50 cm and 150 cm distances from the tree trunk (stump) before and after cutting. We targeted 5 trees for the manipulation and established the measurement chambers to the 4 directions around each targeted tree relative to upper slope (upper, left, right, lower positions). We evaluated the effect of logging on the emission by using hierarchical Bayesian model. HB model can evaluate the variability in observed data and their uncertainties in the estimation with various probability distributions. Moreover, the HB model can easily accommodate the non-linear relationship among the N2O emissions and the environmental factors, and explicitly take non-independent data (nested structure of data) for the estimation into account by using random effects in the model. Our results showed tree cutting stimulated N2O emission from soils, and also that the increase of N2O flux depended on the distance from the trunk (stump): the increase of N2O flux at 50 cm from the trunk (stump) was greater than that of 150 cm from the trunk. The posterior simulation of the HB model indicated that the stimulation of N2O emission by tree cut- ting could reach up to 200 cm in our experimental plot. By tree cutting, the estimated N2O emission at 0-40 cm from the trunk doubled

  18. Tantsuime: märjaks nutetud Märt Agu saab 8000 uut sõpra / Märt Agu ; intervjueerinud Rein Sikk

    Index Scriptorium Estoniae

    Agu, Märt, 1980-

    2011-01-01

    11. Noorte tantsupeo "Maa ja ilm" üldjuht ja Tallinna Tantsuakadeemia kunstiline juht Märt Agu Tallinna lauluväljakul toimuvast tantsupeost, ülevaatustest, eesti meeste rahvatantsust, oma isast Mait Agust, tema tantsust "Põhjamaa", tantsuõpetaja elukutsest, eesti tantsust, Tallinna Tantsuakadeemiast. Andmeid Märt Agu loomingu kohta

  19. Spontaneous regression of pulmonary bullae

    International Nuclear Information System (INIS)

    Satoh, H.; Ishikawa, H.; Ohtsuka, M.; Sekizawa, K.

    2002-01-01

    The natural history of pulmonary bullae is often characterized by gradual, progressive enlargement. Spontaneous regression of bullae is, however, very rare. We report a case in which complete resolution of pulmonary bullae in the left upper lung occurred spontaneously. The management of pulmonary bullae is occasionally made difficult because of gradual progressive enlargement associated with abnormal pulmonary function. Some patients have multiple bulla in both lungs and/or have a history of pulmonary emphysema. Others have a giant bulla without emphysematous change in the lungs. Our present case had treated lung cancer with no evidence of local recurrence. He had no emphysematous change in lung function test and had no complaints, although the high resolution CT scan shows evidence of underlying minimal changes of emphysema. Ortin and Gurney presented three cases of spontaneous reduction in size of bulla. Interestingly, one of them had a marked decrease in the size of a bulla in association with thickening of the wall of the bulla, which was observed in our patient. This case we describe is of interest, not only because of the rarity with which regression of pulmonary bulla has been reported in the literature, but also because of the spontaneous improvements in the radiological picture in the absence of overt infection or tumor. Copyright (2002) Blackwell Science Pty Ltd

  20. Quantum algorithm for linear regression

    Science.gov (United States)

    Wang, Guoming

    2017-07-01

    We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

  1. Interpretation of commonly used statistical regression models.

    Science.gov (United States)

    Kasza, Jessica; Wolfe, Rory

    2014-01-01

    A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

  2. Increased spruce tree growth in Central Europe since 1960s.

    Science.gov (United States)

    Cienciala, Emil; Altman, Jan; Doležal, Jiří; Kopáček, Jiří; Štěpánek, Petr; Ståhl, Göran; Tumajer, Jan

    2018-04-01

    Tree growth response to recent environmental changes is of key interest for forest ecology. This study addressed the following questions with respect to Norway spruce (Picea abies, L. Karst.) in Central Europe: Has tree growth accelerated during the last five decades? What are the main environmental drivers of the observed tree radial stem growth and how much variability can be explained by them? Using a nationwide dendrochronological sampling of Norway spruce in the Czech Republic (1246 trees, 266 plots), novel regional tree-ring width chronologies for 40(±10)- and 60(±10)-year old trees were assembled, averaged across three elevation zones (break points at 500 and 700m). Correspondingly averaged drivers, including temperature, precipitation, nitrogen (N) deposition and ambient CO 2 concentration, were used in a general linear model (GLM) to analyze the contribution of these in explaining tree ring width variability for the period from 1961 to 2013. Spruce tree radial stem growth responded strongly to the changing environment in Central Europe during the period, with a mean tree ring width increase of 24 and 32% for the 40- and 60-year old trees, respectively. The indicative General Linear Model analysis identified CO 2 , precipitation during the vegetation season, spring air temperature (March-May) and N-deposition as the significant covariates of growth, with the latter including interactions with elevation zones. The regression models explained 57% and 55% of the variability in the two tree ring width chronologies, respectively. Growth response to N-deposition showed the highest variability along the elevation gradient with growth stimulation/limitation at sites below/above 700m. A strong sensitivity of stem growth to CO 2 was also indicated, suggesting that the effect of rising ambient CO 2 concentration (direct or indirect by increased water use efficiency) should be considered in analyses of long-term growth together with climatic factors and N

  3. Clinical application of RT-nested PCR integrated with RFLP in Hantavirus detection and genotyping: a prospective study in Shandong Province, PR China.

    Science.gov (United States)

    Liu, Yun-Xi; Zhao, Zhong-Tang; Cao, Wu-Chun; Xu, Xiao-Qun; Suo, Ji-Jiang; Xing, Yu-Bin; Jia, Ning; Du, Ming-Mei; Liu, Bo-Wei; Yao, Yuan

    2013-01-01

    The aim of the present study was to evaluate the clinical usefulness of applying RT-nested PCR along with RFLP as a method for diagnosis and genotypic differentiation of Hantavirus in the acute-stage sera of HFRS patients as compared to the ELISA technique. A prospective study of patients with suspected HFRS patients was carried out. Sera were collected for serological evaluation by ELISA and RT-nested PCR testing. Primers were selected from the published sequence of the S segment of HTNV strain 76-118 and SEOV strain SR-11, which made it possible to obtain an amplicon of 403 bp by RT-nested PCR. The genotypic differentiations of the RT-nested PCR amplicons were carried out by RFLP. Sequence analyses of the amplicons were used to confirm the accuracy of the results obtained by RFLP. Of the 48 acute-stage sera from suspected HFRS patients, 35 were ELISA-positive while 41 were positive by RT-nested PCR. With Hind III and Hinf I, RFLP profiles of the RT-nested PCR amplicons of the 41 positive sera exhibited two patterns. 33 had RFLP profiles similar to the reference strain R22, and thus belonged to the SEOV type. The other 8 samples which were collected during October-December had RFLP profiles similar to the reference strain 76-118, and thus belonged to the HTNV type. Sequence phylogenetic analysis of RT-nested PCR amplicons revealed sdp1, sdp2 YXL-2008, and sdp3 as close relatives of HTNV strain 76-118, while sdp22 and sdp37 as close relatives of SEOV strain Z37 and strain R22 located in two separate clusters in the phylogenetic tree. These results were identical to those acquired by RFLP. RT-nested PCR integrated with RFLP was a rapid, simple, accurate method for detecting and differentiating the genotypes of Hantavirus in the acute-stage sera of suspected HFRS patients. In Shandong province, the main genotypes of Hantavirus belonged to the SEOV types, while the HTNV types were observed during the autumn-winter season.

  4. Tree growth and competition in an old-growth Picea abies forest of boreal Sweden: influence of tree spatial patterning

    Science.gov (United States)

    Fraver, Shawn; D'Amato, Anthony W.; Bradford, John B.; Jonsson, Bengt Gunnar; Jönsson, Mari; Esseen, Per-Anders

    2013-01-01

    Question: What factors best characterize tree competitive environments in this structurally diverse old-growth forest, and do these factors vary spatially within and among stands? Location: Old-growth Picea abies forest of boreal Sweden. Methods: Using long-term, mapped permanent plot data augmented with dendrochronological analyses, we evaluated the effect of neighbourhood competition on focal tree growth by means of standard competition indices, each modified to include various metrics of trees size, neighbour mortality weighting (for neighbours that died during the inventory period), and within-neighbourhood tree clustering. Candidate models were evaluated using mixed-model linear regression analyses, with mean basal area increment as the response variable. We then analysed stand-level spatial patterns of competition indices and growth rates (via kriging) to determine if the relationship between these patterns could further elucidate factors influencing tree growth. Results: Inter-tree competition clearly affected growth rates, with crown volume being the size metric most strongly influencing the neighbourhood competitive environment. Including neighbour tree mortality weightings in models only slightly improved descriptions of competitive interactions. Although the within-neighbourhood clustering index did not improve model predictions, competition intensity was influenced by the underlying stand-level tree spatial arrangement: stand-level clustering locally intensified competition and reduced tree growth, whereas in the absence of such clustering, inter-tree competition played a lesser role in constraining tree growth. Conclusions: Our findings demonstrate that competition continues to influence forest processes and structures in an old-growth system that has not experienced major disturbances for at least two centuries. The finding that the underlying tree spatial pattern influenced the competitive environment suggests caution in interpreting traditional tree

  5. Steiner trees in industry

    CERN Document Server

    Du, Ding-Zhu

    2001-01-01

    This book is a collection of articles studying various Steiner tree prob­ lems with applications in industries, such as the design of electronic cir­ cuits, computer networking, telecommunication, and perfect phylogeny. The Steiner tree problem was initiated in the Euclidean plane. Given a set of points in the Euclidean plane, the shortest network interconnect­ ing the points in the set is called the Steiner minimum tree. The Steiner minimum tree may contain some vertices which are not the given points. Those vertices are called Steiner points while the given points are called terminals. The shortest network for three terminals was first studied by Fermat (1601-1665). Fermat proposed the problem of finding a point to minimize the total distance from it to three terminals in the Euclidean plane. The direct generalization is to find a point to minimize the total distance from it to n terminals, which is still called the Fermat problem today. The Steiner minimum tree problem is an indirect generalization. Sch...

  6. Translating Response During Therapy into Ultimate Treatment Outcome: A Personalized 4-Dimensional MRI Tumor Volumetric Regression Approach in Cervical Cancer

    International Nuclear Information System (INIS)

    Mayr, Nina A.; Wang, Jian Z.; Lo, Simon S.; Zhang Dongqing; Grecula, John C.; Lu Lanchun; Montebello, Joseph F.; Fowler, Jeffrey M.; Yuh, William T.C.

    2010-01-01

    Purpose: To assess individual volumetric tumor regression pattern in cervical cancer during therapy using serial four-dimensional MRI and to define the regression parameters' prognostic value validated with local control and survival correlation. Methods and Materials: One hundred and fifteen patients with Stage IB 2 -IVA cervical cancer treated with radiation therapy (RT) underwent serial MRI before (MRI 1) and during RT, at 2-2.5 weeks (MRI 2, at 20-25 Gy), and at 4-5 weeks (MRI 3, at 40-50 Gy). Eighty patients had a fourth MRI 1-2 months post-RT. Mean follow-up was 5.3 years. Tumor volume was measured by MRI-based three-dimensional volumetry, and plotted as dose(time)/volume regression curves. Volume regression parameters were correlated with local control, disease-specific, and overall survival. Results: Residual tumor volume, slope, and area under the regression curve correlated significantly with local control and survival. Residual volumes ≥20% at 40-50 Gy were independently associated with inferior 5-year local control (53% vs. 97%, p <0.001) and disease-specific survival rates (50% vs. 72%, p = 0.009) than smaller volumes. Patients with post-RT residual volumes ≥10% had 0% local control and 17% disease-specific survival, compared with 91% and 72% for <10% volume (p <0.001). Conclusion: Using more accurate four-dimensional volumetric regression analysis, tumor response can now be directly translated into individual patients' outcome for clinical application. Our results define two temporal thresholds critically influencing local control and survival. In patients with ≥20% residual volume at 40-50 Gy and ≥10% post-RT, the risk for local failure and death are so high that aggressive intervention may be warranted.

  7. Prediction, Regression and Critical Realism

    DEFF Research Database (Denmark)

    Næss, Petter

    2004-01-01

    This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

  8. On Weighted Support Vector Regression

    DEFF Research Database (Denmark)

    Han, Xixuan; Clemmensen, Line Katrine Harder

    2014-01-01

    We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...... shrinks the coefficient of each observation in the estimated functions; thus, it is widely used for minimizing influence of outliers. We propose to additionally add weights to the slack variables in the constraints (CF‐weights) and call the combination of weights the doubly weighted SVR. We illustrate...... the differences and similarities of the two types of weights by demonstrating the connection between the Least Absolute Shrinkage and Selection Operator (LASSO) and the SVR. We show that an SVR problem can be transformed to a LASSO problem plus a linear constraint and a box constraint. We demonstrate...

  9. Visualization of Uncertain Contour Trees

    DEFF Research Database (Denmark)

    Kraus, Martin

    2010-01-01

    Contour trees can represent the topology of large volume data sets in a relatively compact, discrete data structure. However, the resulting trees often contain many thousands of nodes; thus, many graph drawing techniques fail to produce satisfactory results. Therefore, several visualization methods...... were proposed recently for the visualization of contour trees. Unfortunately, none of these techniques is able to handle uncertain contour trees although any uncertainty of the volume data inevitably results in partially uncertain contour trees. In this work, we visualize uncertain contour trees...... by combining the contour trees of two morphologically filtered versions of a volume data set, which represent the range of uncertainty. These two contour trees are combined and visualized within a single image such that a range of potential contour trees is represented by the resulting visualization. Thus...

  10. Generic Ising trees

    DEFF Research Database (Denmark)

    Durhuus, Bergfinnur Jøgvan; Napolitano, George Maria

    2012-01-01

    The Ising model on a class of infinite random trees is defined as a thermodynamiclimit of finite systems. A detailed description of the corresponding distribution of infinite spin configurations is given. As an application, we study the magnetization properties of such systems and prove that they......The Ising model on a class of infinite random trees is defined as a thermodynamiclimit of finite systems. A detailed description of the corresponding distribution of infinite spin configurations is given. As an application, we study the magnetization properties of such systems and prove...... that they exhibit no spontaneous magnetization. Furthermore, the values of the Hausdorff and spectral dimensions of the underlying trees are calculated and found to be, respectively,¯dh =2 and¯ds = 4/3....

  11. Random Forest as a Predictive Analytics Alternative to Regression in Institutional Research

    Science.gov (United States)

    He, Lingjun; Levine, Richard A.; Fan, Juanjuan; Beemer, Joshua; Stronach, Jeanne

    2018-01-01

    In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…

  12. Weighted linear regression using D2H and D2 as the independent variables

    Science.gov (United States)

    Hans T. Schreuder; Michael S. Williams

    1998-01-01

    Several error structures for weighted regression equations used for predicting volume were examined for 2 large data sets of felled and standing loblolly pine trees (Pinus taeda L.). The generally accepted model with variance of error proportional to the value of the covariate squared ( D2H = diameter squared times height or D...

  13. Hierarchical Matching and Regression with Application to Photometric Redshift Estimation

    Science.gov (United States)

    Murtagh, Fionn

    2017-06-01

    This work emphasizes that heterogeneity, diversity, discontinuity, and discreteness in data is to be exploited in classification and regression problems. A global a priori model may not be desirable. For data analytics in cosmology, this is motivated by the variety of cosmological objects such as elliptical, spiral, active, and merging galaxies at a wide range of redshifts. Our aim is matching and similarity-based analytics that takes account of discrete relationships in the data. The information structure of the data is represented by a hierarchy or tree where the branch structure, rather than just the proximity, is important. The representation is related to p-adic number theory. The clustering or binning of the data values, related to the precision of the measurements, has a central role in this methodology. If used for regression, our approach is a method of cluster-wise regression, generalizing nearest neighbour regression. Both to exemplify this analytics approach, and to demonstrate computational benefits, we address the well-known photometric redshift or `photo-z' problem, seeking to match Sloan Digital Sky Survey (SDSS) spectroscopic and photometric redshifts.

  14. ColorTree: a batch customization tool for phylogenic trees.

    Science.gov (United States)

    Chen, Wei-Hua; Lercher, Martin J

    2009-07-31

    Genome sequencing projects and comparative genomics studies typically aim to trace the evolutionary history of large gene sets, often requiring human inspection of hundreds of phylogenetic trees. If trees are checked for compatibility with an explicit null hypothesis (e.g., the monophyly of certain groups), this daunting task is greatly facilitated by an appropriate coloring scheme. In this note, we introduce ColorTree, a simple yet powerful batch customization tool for phylogenic trees. Based on pattern matching rules, ColorTree applies a set of customizations to an input tree file, e.g., coloring labels or branches. The customized trees are saved to an output file, which can then be viewed and further edited by Dendroscope (a freely available tree viewer). ColorTree runs on any Perl installation as a stand-alone command line tool, and its application can thus be easily automated. This way, hundreds of phylogenic trees can be customized for easy visual inspection in a matter of minutes. ColorTree allows efficient and flexible visual customization of large tree sets through the application of a user-supplied configuration file to multiple tree files.

  15. Gold nanoparticle-based RT-PCR and real-time quantitative RT-PCR assays for detection of Japanese encephalitis virus

    International Nuclear Information System (INIS)

    Huang, S-H; Tsai, M-H; Lin, C-W; Yang, T-C; Chuang, P-H; Tsai, I-S; Lu, H-C; Wan Lei; Lin, Y-J; Lai, C-H

    2008-01-01

    Virus isolation and antibody detection are routinely used for diagnosis of Japanese encephalitis virus (JEV) infection, but the low level of transient viremia in some JE patients makes JEV isolation from clinical and surveillance samples very difficult. We describe the use of gold nanoparticle-based RT-PCR and real-time quantitative RT-PCR assays for detection of JEV from its RNA genome. We tested the effect of gold nanoparticles on four different PCR systems, including conventional PCR, reverse-transcription PCR (RT-PCR), and SYBR green real-time PCR and RT-PCR assays for diagnosis in the acute phase of JEV infection. Gold nanoparticles increased the amplification yield of the PCR product and shortened the PCR time compared to the conventional reaction. In addition, nanogold-based real-time RT-PCR showed a linear relationship between Ct and template amount using ten-fold dilutions of JEV. The nanogold-based RT-PCR and real-time quantitative RT-PCR assays were able to detect low levels (1-10 000 copies) of the JEV RNA genomes extracted from culture medium or whole blood, providing early diagnostic tools for the detection of low-level viremia in the acute-phase infection. The assays described here were simple, sensitive, and rapid approaches for detection and quantitation of JEV in tissue cultured samples as well as clinical samples

  16. A Branch-and-Price approach to find optimal decision trees

    NARCIS (Netherlands)

    Firat, M.; Crognier, Guillaume; Gabor, Adriana; Zhang, Y.

    2018-01-01

    In Artificial Intelligence (AI) field, decision trees have gained certain importance due to their effectiveness in solving classification and regression problems. Recently, in the literature we see finding optimal decision trees are formulated as Mixed Integer Linear Programming (MILP) models. This

  17. Factors influencing the use of RT in NSW: a qualitative study exploring consumer and health professional practices

    International Nuclear Information System (INIS)

    Sundaresan, Puma; Milross, Christopher G.; Stockler, Martin R.; Smith, Andrea; Evans, Alison; King, Madeleine T.

    2014-01-01

    Radiotherapy (RT) is an essential and cost-effective cancer treatment. It is underutilised in Australia. Bridging the gap between actual and optimal RT utilisation requires not only provision of adequate RT infrastructure but also an understanding of the factors that influence the extent to which this opportunity for RT is utilised. This study explored factors perceived to affect RT-related decision making by consumers and health professionals (HPs). Six semi-structured focus groups (FGs) and 13 interviews were conducted at three geographical locations in NSW, Australia (n=26 consumers and 30 HPs). Audio recordings of FGs and interviews were transcribed verbatim and analysed thematically. An exhaustive list of issues perceived to affect consumer and HP RT decisions was identified. There were common themes across participant groups and locations. Perceptions of RT and its benefits, as well as accurate communication of the expected benefits and risks of RT, were highlighted as important to decision making. Perceived factors relating to 'inconvenience' of RT were multifaceted and included travel, relocation, accommodation, time away from work and financial challenges. Perceived potential barriers to RT referral included knowledge of RT and RT services, availability of a local or visiting RT service, referrer bias, and the low profile of RT. Important drivers during RT decisions appear to include the perceived benefit, risks and inconvenience of RT. Underutilisation of RT may also result from multiple barriers at the referrer level. Further research into whether these factors influence actual RT decisions is needed.

  18. Kuidas sünnib pealkiri? / Pärt Lias

    Index Scriptorium Estoniae

    Lias, Pärt

    2002-01-01

    Pealkiri, pühendus, moto, joonealune märge, ees- ja järelsõna on teose teksti manused, mis ei kuulu otse teksti, kuid selgitavad, täiendavad ja täpsustavad seda. Gerard Genette on need teksti lisandid koondanud üldnimetuse paratekstid alla. Eesti kirjanikud vastavad Pärt Liase küsimusele oma teoste pealkirjade saamisloo kohta: Aimee Beekman, Henn-Kaarel Hellat, Joel Sang ja Arvo Mägi (4); Lennart Meri, Heino Kiik ja Fanny de Sivers (5); Helga Nõu, Ülle Kauksi, Maie Kalda ja Cornelius Hasselblatt (6); Debora Vaarandi, Vaino Vahing, Arved Viirlaid ja Wimberg (7); Vahur Afanasjev, Matt Barker, Andrus Kivirähk, Jürgen Rooste ja Contra (8); Elin Toona, Jaak Rähesoo, Enn Soosaar, Juhan Peegel ja Toomas Kall (9); Kerttu Rakke, Aare Pilv, Aarne Ruben, Indrek Hargla, Jan Kaus ja Karen Orlau (10); Ene Mihkelson, Mats Traat ja Boriss Baljasnõi (11); Maimu Berg, Ain Kaalep, Enn Nõu ja Madis Kõiv (12)

  19. A parallel buffer tree

    DEFF Research Database (Denmark)

    Sitchinava, Nodar; Zeh, Norbert

    2012-01-01

    We present the parallel buffer tree, a parallel external memory (PEM) data structure for batched search problems. This data structure is a non-trivial extension of Arge's sequential buffer tree to a private-cache multiprocessor environment and reduces the number of I/O operations by the number of...... in the optimal OhOf(psortN + K/PB) parallel I/O complexity, where K is the size of the output reported in the process and psortN is the parallel I/O complexity of sorting N elements using P processors....

  20. Credit Scoring Problem Based on Regression Analysis

    OpenAIRE

    Khassawneh, Bashar Suhil Jad Allah

    2014-01-01

    ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....

  1. Comparative evaluation of conventional RT-PCR and real-time RT-PCR (RRT-PCR) for detection of avian metapneumovirus subtype A

    OpenAIRE

    Ferreira, HL; Spilki, FR; dos Santos, MMAB; de Almeida, RS; Arns, CW

    2009-01-01

    Avian metapneumovirus (AMPV) belongs to Metapneumovirus genus of Paramyxoviridae family. Virus isolation, serology, and detection of genomic RNA are used as diagnostic methods for AMPV. The aim of the present study was to compare the detection of six subgroup A AMPV isolates (AMPV/A) viral RNA by using different conventional and real time RT-PCR methods. Two new RT-PCR tests and two real time RT-PCR tests, both detecting fusion (F) gene and nucleocapsid (N) gene were compared with an establis...

  2. Regularized Label Relaxation Linear Regression.

    Science.gov (United States)

    Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung; Fang, Bingwu

    2018-04-01

    Linear regression (LR) and some of its variants have been widely used for classification problems. Most of these methods assume that during the learning phase, the training samples can be exactly transformed into a strict binary label matrix, which has too little freedom to fit the labels adequately. To address this problem, in this paper, we propose a novel regularized label relaxation LR method, which has the following notable characteristics. First, the proposed method relaxes the strict binary label matrix into a slack variable matrix by introducing a nonnegative label relaxation matrix into LR, which provides more freedom to fit the labels and simultaneously enlarges the margins between different classes as much as possible. Second, the proposed method constructs the class compactness graph based on manifold learning and uses it as the regularization item to avoid the problem of overfitting. The class compactness graph is used to ensure that the samples sharing the same labels can be kept close after they are transformed. Two different algorithms, which are, respectively, based on -norm and -norm loss functions are devised. These two algorithms have compact closed-form solutions in each iteration so that they are easily implemented. Extensive experiments show that these two algorithms outperform the state-of-the-art algorithms in terms of the classification accuracy and running time.

  3. Socio-economic determinants of growing trees on farms in the middle hills of Nepal

    DEFF Research Database (Denmark)

    Oli, B.N.; Treue, Thorsten; Larsen, Helle Overgaard

    2015-01-01

    were found. The Shannon–Wiener index was 2.46 and Simpson’s Dominance index was 0.15. Trees on farmland contributed on average 43 % of households’ firewood and fodder consumption. Apparent determinants of tree growing were identified through OLS regression; they included size of land and livestock......On-farm tree growing is potentially important for livelihood strategies and forest conservation, and varies greatly according to local contexts. A detailed knowledge base is therefore needed, requiring, inter alia, the documentation of factors associated with growing trees on farms. The present...... study surveyed 304 randomly sampled households in ten community forestry user groups in Nepal, eliciting data on demographics, income and consumption of tree products. All trees on households’ farm land were registered by species. Farmers had on average 65 trees per hectare and a total of 92 species...

  4. Runtime Optimizations for Tree-Based Machine Learning Models

    NARCIS (Netherlands)

    N. Asadi; J.J.P. Lin (Jimmy); A.P. de Vries (Arjen)

    2014-01-01

    htmlabstractTree-based models have proven to be an effective solution for web ranking as well as other machine learning problems in diverse domains. This paper focuses on optimizing the runtime performance of applying such models to make predictions, specifically using gradient-boosted regression

  5. Modelling dimensional growth of three street tree species in the ...

    African Journals Online (AJOL)

    The results could also be used in the process of modelling energy use reduction, air pollution uptake, rainfall interception, carbon sequestration and microclimate modification of urban forests such as those found in the City of Tshwane. Keywords: allometry; regression; size relationships; tree growth; urban forests. Southern ...

  6. Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

    Science.gov (United States)

    Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

    2017-12-01

    The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

  7. Effect of low frequency ultrasound on combined rt-PA and eptifibatide thrombolysis in human clots.

    Science.gov (United States)

    Meunier, Jason M; Holland, Christy K; Pancioli, Arthur M; Lindsell, Christopher J; Shaw, George J

    2009-01-01

    Fibrinolytics such as recombinant tissue plasminogen activator (rt-PA) are used to treat thrombotic disease such as acute myocardial infarction (AMI) and ischemic stroke. Interest in increasing efficacy and reducing side effects has led to the study of adjuncts such as GP IIb-IIIa inhibitors and ultrasound (US) enhanced thrombolysis. Currently, GP IIb-IIIa inhibitor and fibrinolytic treatment are often used in AMI, and are under investigation for stroke treatment. However, little is known of the efficacy of combined GP IIb-IIIa inhibitor, fibrinolytic and ultrasound treatment. We measure the lytic efficacy of rt-PA, eptifibatide (Epf) and 120 kHz ultrasound treatment in an in-vitro human clot model. Blood was drawn from 15 subjects after IRB approval. Clots were made in 20 microL pipettes, and placed in a water tank for microscopic visualization during lytic treatment. Clots were exposed to control, rt-PA (rt-PA), eptifibatide (Epf), or rt-PA+eptifibatide (rt-PA + Epf), with (+US) or without (-US) ultrasound for 30 minutes at 37 degrees C in human plasma. Clot lysis was measured over time, using a microscopic imaging technique. The fractional clot loss (FCL) and initial lytic rate (LR) were used to quantify lytic efficacy. LR values for (- US) treated clots were 0.8+/-0.1(control), 1.8+/-0.3 (Epf), 1.5+/-0.2 (rt-PA), and 1.3+/-0.4 (rt-PA + Epf) (% clot width/minute) respectively. In comparison, the (+ US) group exhibited LR values of 1.6+/-0.2 (control), 4.3+/-0.4 (Epf), 6.3+/-0.4 (rt-PA), and 4.6+/-0.6 (rt-PA + Epf). For (- US) treated clots, FCL was 6.0+/-0.8 (control), 9.2+/-2.5 (Epf), 15.6+/-1.7 (rt-PA), and 28.0+/-2.2% (rt-PA + Epf) respectively. FCL for (+ US) clots was 13.5+/-2.4 (control), 20.7+/-6.4 (Epf), 44.4+/-3.6 (rt-PA) and 30.3+/-3.6% (rt-PA + Epf) respectively. Although the addition of eptifibatide enhances the in-vitro lytic efficacy of rt-PA in the absence of ultrasound, the efficacy of ultrasound and rt-PA is greater than that of combined

  8. Measuring urban tree loss dynamics across residential landscapes.

    Science.gov (United States)

    Ossola, Alessandro; Hopton, Matthew E

    2018-01-15

    The spatial arrangement of urban vegetation depends on urban morphology and socio-economic settings. Urban vegetation changes over time because of human management. Urban trees are removed due to hazard prevention or aesthetic preferences. Previous research attributed tree loss to decreases in canopy cover. However, this provides little information about location and structural characteristics of trees lost, as well as environmental and social factors affecting tree loss dynamics. This is particularly relevant in residential landscapes where access to residential parcels for field surveys is limited. We tested whether multi-temporal airborne LiDAR and multi-spectral imagery collected at a 5-year interval can be used to investigate urban tree loss dynamics across residential landscapes in Denver, CO and Milwaukee, WI, covering 400,705 residential parcels in 444 census tracts. Position and stem height of trees lost were extracted from canopy height models calculated as the difference between final (year 5) and initial (year 0) vegetation height derived from LiDAR. Multivariate regression models were used to predict number and height of tree stems lost in residential parcels in each census tract based on urban morphological and socio-economic variables. A total of 28,427 stems were lost from residential parcels in Denver and Milwaukee over 5years. Overall, 7% of residential parcels lost one stem, averaging 90.87 stems per km 2 . Average stem height was 10.16m, though trees lost in Denver were taller compared to Milwaukee. The number of stems lost was higher in neighborhoods with higher canopy cover and developed before the 1970s. However, socio-economic characteristics had little effect on tree loss dynamics. The study provides a simple method for measuring urban tree loss dynamics within and across entire cities, and represents a further step toward high resolution assessments of the three-dimensional change of urban vegetation at large spatial scales. Published by

  9. Embedding complete ternary tree in hypercubes using AVL trees

    NARCIS (Netherlands)

    S.A. Choudum; I. Raman (Indhumathi)

    2008-01-01

    htmlabstractA complete ternary tree is a tree in which every non-leaf vertex has exactly three children. We prove that a complete ternary tree of height h, TTh, is embeddable in a hypercube of dimension . This result coincides with the result of [2]. However, in this paper, the embedding utilizes

  10. Portraits of Tree Families

    NARCIS (Netherlands)

    Balgooy, van M.M.J.

    1998-01-01

    With the publication of the second volume of the series ‘Malesian Seed Plants’, entitled ‘Portraits of Tree Families’, I would like to refer to the Introduction of the first volume, ‘Spot-characters’ for a historical background and an explanation of the aims of this series. The present book treats

  11. P{owering 'Trees

    Indian Academy of Sciences (India)

    Melia dubia Cav. of Meliaceae is a large deciduous tree. Leaves are compound with toothed leaflets. Flowers are small, greenish-yellow in much-branched inflorescences. Fruits are green, ellipsoidal with a single seed covered by hard portion ( as in a mango fruit) and surrounded by fleshy pulp outside. The bark is bitter ...

  12. Programming macro tree transducers

    DEFF Research Database (Denmark)

    Bahr, Patrick; Day, Laurence E.

    2013-01-01

    transducers can be concisely represented in Haskell, and demonstrate the benefits of utilising such an approach with a number of examples. In particular, tree transducers afford a modular programming style as they can be easily composed and manipulated. Our Haskell representation generalises the original...

  13. Chapter 5 - Tree Mortality

    Science.gov (United States)

    Mark J. Ambrose

    2014-01-01

    Tree mortality is a natural process in all forest ecosystems. Extremely high mortality, however, can also be an indicator of forest health issues. On a regional scale, high mortality levels may indicate widespread insect or disease problems. High mortality may also occur if a large proportion of the forest in a particular region is made up of older, senescent stands....

  14. A Universal Phylogenetic Tree.

    Science.gov (United States)

    Offner, Susan

    2001-01-01

    Presents a universal phylogenetic tree suitable for use in high school and college-level biology classrooms. Illustrates the antiquity of life and that all life is related, even if it dates back 3.5 billion years. Reflects important evolutionary relationships and provides an exciting way to learn about the history of life. (SAH)

  15. Base tree property

    Czech Academy of Sciences Publication Activity Database

    Balcar, B.; Doucha, Michal; Hrušák, M.

    2015-01-01

    Roč. 32, č. 1 (2015), s. 69-81 ISSN 0167-8094 R&D Projects: GA AV ČR IAA100190902 Institutional support: RVO:67985840 Keywords : forcing * Boolean algebras * base tree Subject RIV: BA - General Mathematics Impact factor: 0.614, year: 2015 http://link.springer.com/article/10.1007/s11083-013-9316-2

  16. Multiquarks and Steiner trees

    International Nuclear Information System (INIS)

    Richard, Jean-Marc

    2010-01-01

    A brief review review is presented of models tentatively leading to stable multiquarks. A new attempt is presented, based on a Steiner-tree model of confinement, which is inspired by by QCD. It leads to more attraction than the empirical colour-additive model used in earlier multiquark calculations, and predict several multiquark states in configurations with different flavours.

  17. Meteorological Factors and Tree Characteristics Influencing the Initiation and Rate of Stemflow from Deciduous Trees in an Urban Park

    Science.gov (United States)

    Schooling, J. T.; Carlyle-Moses, D. E.

    2013-12-01

    Stemflow, SF, represents that portion of precipitation that is intercepted by a tree's canopy and diverted to the ground at the tree base by flowing along branches and down the bole. The focused input of water and nutrients associated with SF have been shown to be of hydrological and biogeochemical importance in a number of plant communities and forest environments. Although the concentrated water volume and the nutrient / pollutant fluxes associated with SF in urban areas may be highly relevant for stormwater quantity and quality management, they have received only minor study in built environments. In an urban park in Kamloops, British Columbia, Canada, SF volumes generated from 40 deciduous trees representing 22 species were sampled on a precipitation event basis over a period of 16 months. Using this data, we derived the threshold rainfall depth required for SF initiation from each tree by taking the absolute value of the y-intercept of the linear regression of SF volume versus rainfall depth divided by the slope of that regression. The SF discharge rate once the threshold rainfall depth had been reached was taken as the slope of the linear regression equation. Thus, a simplified SF equation was developed: SFv = QSF x (Pg = Pg''), where SFv is stemflow volume (litres), QSF is the discharge rate (litres / mm), and Pg and Pg' represent the precipitation depth and the threshold precipitation depth, respectively. We then examined the influence of meteorological factors (precipitation type [rain / snow / rain + snow], precipitation depth, rainfall intensity, wind speed and direction, and vapour pressure deficit), and tree characteristics (tree diameter at breast height, tree height, leaf size and orientation, bark roughness, crown projection area, leaf area index, canopy cover fraction, branching angle, the proportion of the crown that was comprised of branches, and overlap with other tree canopies) on QSF and Pg' in order to expand on the simplified model and

  18. Tree Transduction Tools for Cdec

    Directory of Open Access Journals (Sweden)

    Austin Matthews

    2014-09-01

    Full Text Available We describe a collection of open source tools for learning tree-to-string and tree-to-tree transducers and the extensions to the cdec decoder that enable translation with these. Our modular, easy-to-extend tools extract rules from trees or forests aligned to strings and trees subject to different structural constraints. A fast, multithreaded implementation of the Cohn and Blunsom (2009 model for extracting compact tree-to-string rules is also included. The implementation of the tree composition algorithm used by cdec is described, and translation quality and decoding time results are presented. Our experimental results add to the body of evidence suggesting that tree transducers are a compelling option for translation, particularly when decoding speed and translation model size are important.

  19. Selecting Landscape Plants: Shade Trees

    OpenAIRE

    Relf, Diane; Appleton, Bonnie Lee, 1948-2012; Close, David

    2015-01-01

    Because of the permanency of trees and their importance in the landscape, care must be taken to select the best species for each situation. This publication goes over how to choose landscape trees that are shade tolerant.

  20. DeepRT: deep learning for peptide retention time prediction in proteomics

    OpenAIRE

    Ma, Chunwei; Zhu, Zhiyong; Ye, Jun; Yang, Jiarui; Pei, Jianguo; Xu, Shaohang; Zhou, Ruo; Yu, Chang; Mo, Fan; Wen, Bo; Liu, Siqi

    2017-01-01

    Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Herein, we present DeepRT, a deep learning based software for peptide retention time prediction. DeepRT automatically learns features directly from the peptide sequences using the deep convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) model, which eliminates the need to use hand-crafted features or rules. After the feature learning, pr...

  1. Adjustable chain trees for proteins

    DEFF Research Database (Denmark)

    Winter, Pawel; Fonseca, Rasmus

    2012-01-01

    A chain tree is a data structure for changing protein conformations. It enables very fast detection of clashes and free energy potential calculations. A modified version of chain trees that adjust themselves to the changing conformations of folding proteins is introduced. This results in much...... tighter bounding volume hierarchies and therefore fewer intersection checks. Computational results indicate that the efficiency of the adjustable chain trees is significantly improved compared to the traditional chain trees....

  2. Introduction to fault tree analysis

    International Nuclear Information System (INIS)

    Barlow, R.E.; Lambert, H.E.

    1975-01-01

    An elementary, engineering oriented introduction to fault tree analysis is presented. The basic concepts, techniques and applications of fault tree analysis, FTA, are described. The two major steps of FTA are identified as (1) the construction of the fault tree and (2) its evaluation. The evaluation of the fault tree can be qualitative or quantitative depending upon the scope, extensiveness and use of the analysis. The advantages, limitations and usefulness of FTA are discussed

  3. Endogenous reverse transcriptase (RT) activity and Chromatin remodeling in normal and transformed cells and early embryos

    International Nuclear Information System (INIS)

    Spadafora, C.; Sciamanna, I.; Misteli, T.

    2009-01-01

    Endogenous Reverse Transcriptase (RT) is an enzyme encoded by two classes of genomic retro-elements: retro-transposons and endogenous retroviruses. Basal levels of RT are expressed in all non pathological, differentiated tissues while high RT expression levels characterize tumorigenic cells, germ cells and embryonic tissues. Preliminary studies carried out in our laboratory have shown that RT inhibition using pharmacological inhibitors (nevirapine and efavirenz, two drugs currently used in AIDS therapy) drastically reduces cell proliferation, promotes differentiation of tumorigenic cells in vitro, induces a reprogrammed gene expression and antagonizes tumor progression in nude mice inoculated with tumorigenic human cell lines, including melanoma, prostate and colon carcinoma and microcitoma

  4. Principal component regression analysis with SPSS.

    Science.gov (United States)

    Liu, R X; Kuang, J; Gong, Q; Hou, X L

    2003-06-01

    The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

  5. The Re-Think Tree.

    Science.gov (United States)

    Gear, Jim

    1993-01-01

    The Re-Think Tree is a simple framework to help individuals assess and improve their behaviors related to environmental issues. The branches of the tree in order of priority are refuse, reduce, re-use, and recycle. Roots of the tree include such things as public opinion, education, and watchdog groups. (KS)

  6. The Hopi Fruit Tree Book.

    Science.gov (United States)

    Nyhuis, Jane

    Referring as often as possible to traditional Hopi practices and to materials readily available on the reservation, the illustrated booklet provides information on the care and maintenance of young fruit trees. An introduction to fruit trees explains the special characteristics of new trees, e.g., grafting, planting pits, and watering. The…

  7. Rectilinear Full Steiner Tree Generation

    DEFF Research Database (Denmark)

    Zachariasen, Martin

    1999-01-01

    The fastest exact algorithm (in practice) for the rectilinear Steiner tree problem in the plane uses a two-phase scheme: First, a small but sufficient set of full Steiner trees (FSTs) is generated and then a Steiner minimum tree is constructed from this set by using simple backtrack search, dynamic...

  8. Inferences from growing trees backwards

    Science.gov (United States)

    David W. Green; Kent A. McDonald

    1997-01-01

    The objective of this paper is to illustrate how longitudinal stress wave techniques can be useful in tracking the future quality of a growing tree. Monitoring the quality of selected trees in a plantation forest could provide early input to decisions on the effectiveness of management practices, or future utilization options, for trees in a plantation. There will...

  9. Genetic transformation of forest trees

    African Journals Online (AJOL)

    Admin

    In this review, the recent progress on genetic transformation of forest trees were discussed. Its described also, different applications of genetic engineering for improving forest trees or understanding the mechanisms governing genes expression in woody plants. Key words: Genetic transformation, transgenic forest trees, ...

  10. Comparison of RT-PCR-Dot blot hybridization based on radioisotope 32P with conventional RT-PCR and commercial ELISA Assays for blood screening of HIV-1

    International Nuclear Information System (INIS)

    Maria Lina R; Andi Yasmon

    2011-01-01

    There are many commercial ELISA and rapid test kits that have been used for blood screening; however, the kits can give false positive and negative results. Therefore, RT-PCR (Reverse Transcription Polymerase Chain Reaction) - Dot Blot Hybridization based on radioisotope 32 P (RDBR) method was developed in this research, to compare the method with the conventional RT-PCR and commercial ELISA Enzyme-Linked lmmunosorbent Assay) kit. This method is efficient for screening of large blood specimens and surveillance study. Eighty seven samples were used and serum of the samples were tested by ELISA to detect HIV-1. The HIV-l RNA genome was extracted from plasma samples and tested using the RT-PCR and RDBR methods. Of 87 samples that were tested, the rates of positive testing of the RT-PCR, the RDBR, and the ELISA were 71.26%, 74.71%, and 80.46%, respectively. The RDBR (a combination of RTPCR and dot blot hybridization) was more sensitive than conventional RT-PCR by showing 3.45% in increase number of positive specimens. The results showed that of 9 samples (10.34%) were negative RDBR and positive ELISA, while 4 samples (4.60%) were negative ELISA and positive RDBR. The two methods showed slightly difference in the results but further validation is still needed. However, RDBR has high potential as an alternative method for screening of blood in large quantities when compared to method of conventional RT-PCR and ELISA. (author)

  11. Tree biomass in the Swiss landscape: nationwide modelling for improved accounting for forest and non-forest trees.

    Science.gov (United States)

    Price, B; Gomez, A; Mathys, L; Gardi, O; Schellenberger, A; Ginzler, C; Thürig, E

    2017-03-01

    Trees outside forest (TOF) can perform a variety of social, economic and ecological functions including carbon sequestration. However, detailed quantification of tree biomass is usually limited to forest areas. Taking advantage of structural information available from stereo aerial imagery and airborne laser scanning (ALS), this research models tree biomass using national forest inventory data and linear least-square regression and applies the model both inside and outside of forest to create a nationwide model for tree biomass (above ground and below ground). Validation of the tree biomass model against TOF data within settlement areas shows relatively low model performance (R 2 of 0.44) but still a considerable improvement on current biomass estimates used for greenhouse gas inventory and carbon accounting. We demonstrate an efficient and easily implementable approach to modelling tree biomass across a large heterogeneous nationwide area. The model offers significant opportunity for improved estimates on land use combination categories (CC) where tree biomass has either not been included or only roughly estimated until now. The ALS biomass model also offers the advantage of providing greater spatial resolution and greater within CC spatial variability compared to the current nationwide estimates.

  12. Risk factors of regression and undercorrection in photorefractive keratectomy:a case-control study

    Directory of Open Access Journals (Sweden)

    Seyed-Farzad Mohammadi

    2015-10-01

    Full Text Available AIM:To determine risk factors of regression and undercorrection following photorefractive keratectomy (PRK in myopia or myopic astigmatism.METHODS: A case-control study was designed in which eyes with an indication for re-treatment (RT were defined as cases; primary criteria for RT indication, as assessed at least 9mo postoperatively, included an uncorrected distance visual acuity (UDVA of 20/30 or worse and a stable refraction for more than 3mo. Additional considerations included optical quality symptoms and significant higher order aberrations (HOAs. Controls were chosen from the same cohort of operated eyes which had complete post-operative follow up data beyond 9mo and did not need RT. The cohort included patients who had undergone PRK by the Tissue-Saving (TS ablation profile of Technolas 217z100 excimer laser (Bausch & Lomb, Rochester, NY, USA. Mitomycin C had been used in all of the primary procedures.RESULTS:We had 70 case eyes and 158 control eyes, and they were comparable in terms of age, sex and follow-up time (P values:0.58, 1.00 and 0.89, respectively. Pre-operative spherical equivalent of more than -5.00 diopter (D, intended optical zone (OZ diameter of less than 6.00 mm and ocular fixation instability during laser ablation were associated with RT indications (all P values <0.001. These factors maintained their significance in the multiple logistic regression model with odd ratios of 6.12, 6.71 and 7.89, respectively.CONCLUSION:Higher refractive correction (>-5.00 D, smaller OZ (<6.00 mm and unstable fixation during laser ablation of PRK for myopia and myopic astigmatism were found to be strong predictors of undercorrection and regression.

  13. Survey of Cherry necrotic rusty mottle virus and Cherry green ring mottle virus incidence in Korea by Duplex RT-PCR

    Directory of Open Access Journals (Sweden)

    Seung-Yeol Lee

    2014-12-01

    Full Text Available The incidence of Cherry necrotic rusty mottle virus (CNRMV and Cherry green ring mottle virus (CGRMV have recently been occurred in Korea, posing a problem for sweet cherry cultivation. Since infected trees have symptomless leaves or ring-like spots on the pericarp, it is difficult to identify a viral infection. In this study, the incidence of CNRMV and CGRMV in sweet cherry in Gyeongbuk province was surveyed using a newly developed duplex reverse transcriptase polymerase chain reaction (RT-PCR method that can detect both viruses in a single reaction. CNRMV and CGRMV co-infection rates were 29.6%, 53.6%, and 17.6%, respectively, in samples collected from three different sites (Daegu, Gyeongju and Gyeongsan in Gyeongbuk province during 2012 and 2013. This duplex RT-PCR method offers a simple, rapid, and effective way of identifying CNRMV and CGRMV simultaneously in sweet cherry trees, which can aid in the management of viral infections that could undermine yield.

  14. TREE SELECTING AND TREE RING MEASURING IN DENDROCHRONOLOGICAL INVESTIGATIONS

    Directory of Open Access Journals (Sweden)

    Sefa Akbulut

    2004-04-01

    Full Text Available Dendrochronology is a method of dating which makes use of the annual nature of tree growth. Dendrochronology may be divided into a number of subfields, each of which covers one or more aspects of the use of tree ring data: dendroclimatology, dendrogeomorphology, dendrohydrology, dendroecology, dendroarchaelogy, and dendrogylaciology. Basic of all form the analysis of the tree rings. The wood or tree rings can aid to dating past events about climatology, ecology, geology, hydrology. Dendrochronological studies are conducted either on increment cores or on discs. It may be seen abnormalities on tree rings during the measurement like that false rings, missing rings, reaction wood. Like that situation, increment cores must be extracted from four different sides of each tree and be studied as more as on tree.

  15. Tree Colors: Color Schemes for Tree-Structured Data.

    Science.gov (United States)

    Tennekes, Martijn; de Jonge, Edwin

    2014-12-01

    We present a method to map tree structures to colors from the Hue-Chroma-Luminance color model, which is known for its well balanced perceptual properties. The Tree Colors method can be tuned with several parameters, whose effect on the resulting color schemes is discussed in detail. We provide a free and open source implementation with sensible parameter defaults. Categorical data are very common in statistical graphics, and often these categories form a classification tree. We evaluate applying Tree Colors to tree structured data with a survey on a large group of users from a national statistical institute. Our user study suggests that Tree Colors are useful, not only for improving node-link diagrams, but also for unveiling tree structure in non-hierarchical visualizations.

  16. DaRT: A CALL System to Help Students Practice and Develop Reasoning Skills in Choosing English Articles.

    Science.gov (United States)

    Yoshii, Rika; Milne, Alastair

    1998-01-01

    Describes DaRT, a computer assisted language-learning system for helping English-as-a-Second-Language students master English articles. DaRT uses a diagrammatic reasoning tool to present communicative contexts for exercises in choosing appropriate articles. This paper describes the development of DaRT and DaRT's system components and concludes…

  17. Rate of tree carbon accumulation increases continuously with tree size.

    Science.gov (United States)

    Stephenson, N L; Das, A J; Condit, R; Russo, S E; Baker, P J; Beckman, N G; Coomes, D A; Lines, E R; Morris, W K; Rüger, N; Alvarez, E; Blundo, C; Bunyavejchewin, S; Chuyong, G; Davies, S J; Duque, A; Ewango, C N; Flores, O; Franklin, J F; Grau, H R; Hao, Z; Harmon, M E; Hubbell, S P; Kenfack, D; Lin, Y; Makana, J-R; Malizia, A; Malizia, L R; Pabst, R J; Pongpattananurak, N; Su, S-H; Sun, I-F; Tan, S; Thomas, D; van Mantgem, P J; Wang, X; Wiser, S K; Zavala, M A

    2014-03-06

    Forests are major components of the global carbon cycle, providing substantial feedback to atmospheric greenhouse gas concentrations. Our ability to understand and predict changes in the forest carbon cycle--particularly net primary productivity and carbon storage--increasingly relies on models that represent biological processes across several scales of biological organization, from tree leaves to forest stands. Yet, despite advances in our understanding of productivity at the scales of leaves and stands, no consensus exists about the nature of productivity at the scale of the individual tree, in part because we lack a broad empirical assessment of whether rates of absolute tree mass growth (and thus carbon accumulation) decrease, remain constant, or increase as trees increase in size and age. Here we present a global analysis of 403 tropical and temperate tree species, showing that for most species mass growth rate increases continuously with tree size. Thus, large, old trees do not act simply as senescent carbon reservoirs but actively fix large amounts of carbon compared to smaller trees; at the extreme, a single big tree can add the same amount of carbon to the forest within a year as is contained in an entire mid-sized tree. The apparent paradoxes of individual tree growth increasing with tree size despite declining leaf-level and stand-level productivity can be explained, respectively, by increases in a tree's total leaf area that outpace declines in productivity per unit of leaf area and, among other factors, age-related reductions in population density. Our results resolve conflicting assumptions about the nature of tree growth, inform efforts to undertand and model forest carbon dynamics, and have additional implications for theories of resource allocation and plant senescence.

  18. A Rapid Protocol of Crude RNA/DNA Extraction for RT-qPCR Detection and Quantification of 'Candidatus Phytoplasma prunorum'.

    Science.gov (United States)

    Minguzzi, Stefano; Terlizzi, Federica; Lanzoni, Chiara; Poggi Pollini, Carlo; Ratti, Claudio

    2016-01-01

    Many efforts have been made to develop a rapid and sensitive method for phytoplasma and virus detection. Taking our cue from previous works, different rapid sample preparation methods have been tested and applied to Candidatus Phytoplasma prunorum ('Ca. P. prunorum') detection by RT-qPCR. A duplex RT-qPCR has been optimized using the crude sap as a template to simultaneously amplify a fragment of 16S rRNA of the pathogen and 18S rRNA of the host plant. The specific plant 18S rRNA internal control allows comparison and relative quantification of samples. A comparison between DNA and RNA contribution to qPCR detection is provided, showing higher contribution of the latter. The method presented here has been validated on more than a hundred samples of apricot, plum and peach trees. Since 2013, this method has been successfully applied to monitor 'Ca. P. prunorum' infections in field and nursery. A triplex RT-qPCR assay has also been optimized to simultaneously detect 'Ca. P. prunorum' and Plum pox virus (PPV) in Prunus.

  19. The incidence and functional consequences of RT-associated cardiac perfusion defects

    International Nuclear Information System (INIS)

    Marks, Lawrence B.; Yu Xiaoli; Prosnitz, Robert G.; Zhou Sumin; Hardenbergh, Patricia H.; Blazing, Michael; Hollis, Donna; Lind, Pehr; Tisch, Andrea; Wong, Terence Z.; Borges-Neto, Salvador

    2005-01-01

    Purpose: Radiation therapy (RT) for left-sided breast cancer has been associated with cardiac dysfunction. We herein assess the temporal nature and volume dependence of RT-induced left ventricular perfusion defects and whether these perfusion defects are related to changes in cardiac wall motion or alterations in ejection fraction. Methods: From 1998 to 2001, 114 patients were enrolled onto an IRB-approved prospective clinical study to assess changes in regional and global cardiac function after RT for left-sided breast cancer. Patients were imaged 30 to 60 minutes after injection of technetium 99m sestamibi or tetrofosmin. Post-RT perfusion scans were compared with the pre-RT studies to assess for RT-induced perfusion defects as well as functional changes in wall motion and ejection fraction. Two-tailed Fisher's exact test and the Cochran-Armitage test for linear trends were used for statistical analysis. Results: The incidence of new perfusion defects 6, 12, 18, and 24 months after RT was 27%, 29%, 38%, and 42%, respectively. New defects occurred in approximately 10% to 20% and 50% to 60% of patients with less than 5%, and greater than 5%, of their left ventricle included within the RT fields, respectively (p = 0.33 to 0.00008). The rates of wall motion abnormalities in patients with and without perfusion defects were 12% to 40% versus 0% to 9%, respectively; p values were 0.007 to 0.16, depending on the post-RT interval. Conclusions: Radiation therapy causes volume-dependent perfusion defects in approximately 40% of patients within 2 years of RT. These perfusion defects are associated with corresponding wall-motion abnormalities. Additional study is necessary to better define the long-term functional consequences of RT-induced perfusion defects

  20. Contaminant Gradients in Trees: Directional Tree Coring Reveals Boundaries of Soil and Soil-Gas Contamination with Potential Applications in Vapor Intrusion Assessment.

    Science.gov (United States)

    Wilson, Jordan L; Samaranayake, V A; Limmer, Matthew A; Schumacher, John G; Burken, Joel G

    2017-12-19

    Contaminated sites pose ecological and human-health risks through exposure to contaminated soil and groundwater. Whereas we can readily locate, monitor, and track contaminants in groundwater, it is harder to perform these tasks in the vadose zone. In this study, tree-core samples were collected at a Superfund site to determine if the sample-collection location around a particular tree could reveal the subsurface location, or direction, of soil and soil-gas contaminant plumes. Contaminant-centroid vectors were calculated from tree-core data to reveal contaminant distributions in directional tree samples at a higher resolution, and vectors were correlated with soil-gas characterization collected using conventional methods. Results clearly demonstrated that directional tree coring around tree trunks can indicate gradients in soil and soil-gas contaminant plumes, and the strength of the correlations were directly proportionate to the magnitude of tree-core concentration gradients (spearman's coefficient of -0.61 and -0.55 in soil and tree-core gradients, respectively). Linear regression indicates agreement between the concentration-centroid vectors is significantly affected by in planta and soil concentration gradients and when concentration centroids in soil are closer to trees. Given the existing link between soil-gas and vapor intrusion, this study also indicates that directional tree coring might be applicable in vapor intrusion assessment.

  1. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...

  2. Semiparametric regression during 2003–2007

    KAUST Repository

    Ruppert, David; Wand, M.P.; Carroll, Raymond J.

    2009-01-01

    Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

  3. Gaussian process regression analysis for functional data

    CERN Document Server

    Shi, Jian Qing

    2011-01-01

    Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime

  4. Regression Analysis by Example. 5th Edition

    Science.gov (United States)

    Chatterjee, Samprit; Hadi, Ali S.

    2012-01-01

    Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

  5. Standards for Standardized Logistic Regression Coefficients

    Science.gov (United States)

    Menard, Scott

    2011-01-01

    Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

  6. A Seemingly Unrelated Poisson Regression Model

    OpenAIRE

    King, Gary

    1989-01-01

    This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.

  7. Fault tree analysis

    International Nuclear Information System (INIS)

    1981-09-01

    Suggestion are made concerning the method of the fault tree analysis, the use of certain symbols in the examination of system failures. This purpose of the fault free analysis is to find logical connections of component or subsystem failures leading to undesirable occurrances. The results of these examinations are part of the system assessment concerning operation and safety. The objectives of the analysis are: systematical identification of all possible failure combinations (causes) leading to a specific undesirable occurrance, finding of reliability parameters such as frequency of failure combinations, frequency of the undesirable occurrance or non-availability of the system when required. The fault tree analysis provides a near and reconstructable documentation of the examination. (orig./HP) [de

  8. Tree-level formalism

    International Nuclear Information System (INIS)

    Brandhuber, Andreas; Spence, Bill; Travaglini, Gabriele

    2011-01-01

    We review two novel techniques used to calculate tree-level scattering amplitudes efficiently: MHV diagrams, and on-shell recursion relations. For the MHV diagrams, we consider applications to tree-level amplitudes and focus in particular on the N=4 supersymmetric formulation. We also briefly describe the derivation of loop amplitudes using MHV diagrams. For the recursion relations, after presenting their general proof, we discuss several applications to massless theories with and without supersymmetry, to theories with massive particles, and to graviton amplitudes in general relativity. This article is an invited review for a special issue of Journal of Physics A: Mathematical and Theoretical devoted to 'Scattering amplitudes in gauge theories'. (review)

  9. Tree Rings: Timekeepers of the Past.

    Science.gov (United States)

    Phipps, R. L.; McGowan, J.

    One of a series of general interest publications on science issues, this booklet describes the uses of tree rings in historical and biological recordkeeping. Separate sections cover the following topics: dating of tree rings, dating with tree rings, tree ring formation, tree ring identification, sample collections, tree ring cross dating, tree…

  10. Wood for the trees

    Directory of Open Access Journals (Sweden)

    Rob Garbutt

    2013-10-01

    Full Text Available Our paper focuses on the materiality, cultural history and cultural relations of selected artworks in the exhibition Wood for the trees (Lismore Regional Gallery, New South Wales, Australia, 10 June – 17 July 2011. The title of the exhibition, intentionally misreading the aphorism “Can’t see the wood for the trees”, by reading the wood for the resource rather than the collective wood[s], implies conservation, preservation, and the need for sustaining the originating resource. These ideas have particular resonance on the NSW far north coast, a region once rich in rainforest. While the Indigenous population had sustainable practices of forest and land management, the colonists deployed felling and harvesting in order to convert the value of the local, abundant rainforest trees into high-value timber. By the late twentieth century, however, a new wave of settlers launched a protest movements against the proposed logging of remnant rainforest at Terania Creek and elsewhere in the region. Wood for the trees, curated by Gallery Director Brett Adlington, plays on this dynamic relationship between wood, trees and people. We discuss the way selected artworks give expression to the themes or concepts of productive labour, nature and culture, conservation and sustainability, and memory. The artworks include Watjinbuy Marrawilil’s (1980 Carved ancestral figure ceremonial pole, Elizabeth Stops’ (2009/10 Explorations into colonisation, Hossein Valamanesh’s (2008 Memory stick, and AñA Wojak’s (2008 Unread book (in a forgotten language. Our art writing on the works, a practice informed by Bal (2002, Muecke (2008 and Papastergiadis (2004, becomes a conversation between the works and the themes or concepts. As a form of material excess of the most productive kind (Grosz, 2008, p. 7, art seeds a response to that which is in the air waiting to be said of the past, present and future.

  11. Productivity of the supply system based on whole-tree bundling

    Energy Technology Data Exchange (ETDEWEB)

    Laitila, J. (Finnish Forest Research Inst., Joensuu (Finland)), Email: juha.laitila@metla.fi; Jylhae, P. (Finnish Forest Research Inst., Kannus (Finland)), Email: paula.jylha@metla.fi; Kaerhae, K. (Metsaeteho Oy, Helsinki (Finland)), Email: kalle.karha@metsateho.fi

    2009-07-01

    In the present study, time consumption models for bundle harvesting and forwarding were created by applying regression analyses. The time studies related to on-road transportation were created by applying regression analyses. The time studies related to on-road transportation were focused on comparing the terminal times spent on handling of whole-tree bundles and conventional 5-m pulpwood. The number of whole-tree bundles per truck load and the weights of the payloads were also recorded. The forwarding productivity of whole-tree bundles was about double compared to conventional pulpwood and whole-trees. In on-road transportation, the mean loading and unloading time of whole-tree bundles per truck load was 46 % higher compared to that of conventional 5-m pulpwood. The second prototype of the bundle harvester is under construction, and the time studies are to be continued after accomplishing the machine in the autumn 2009. (orig.)

  12. Recursive Trees for Practical ORAM

    Directory of Open Access Journals (Sweden)

    Moataz Tarik

    2015-06-01

    Full Text Available We present a new, general data structure that reduces the communication cost of recent tree-based ORAMs. Contrary to ORAM trees with constant height and path lengths, our new construction r-ORAM allows for trees with varying shorter path length. Accessing an element in the ORAM tree results in different communication costs depending on the location of the element. The main idea behind r-ORAM is a recursive ORAM tree structure, where nodes in the tree are roots of other trees. While this approach results in a worst-case access cost (tree height at most as any recent tree-based ORAM, we show that the average cost saving is around 35% for recent binary tree ORAMs. Besides reducing communication cost, r-ORAM also reduces storage overhead on the server by 4% to 20% depending on the ORAM’s client memory type. To prove r-ORAM’s soundness, we conduct a detailed overflow analysis. r-ORAM’s recursive approach is general in that it can be applied to all recent tree ORAMs, both constant and poly-log client memory ORAMs. Finally, we implement and benchmark r-ORAM in a practical setting to back up our theoretical claims.

  13. Mathematical foundations of event trees

    International Nuclear Information System (INIS)

    Papazoglou, Ioannis A.

    1998-01-01

    A mathematical foundation from first principles of event trees is presented. The main objective of this formulation is to offer a formal basis for developing automated computer assisted construction techniques for event trees. The mathematical theory of event trees is based on the correspondence between the paths of the tree and the elements of the outcome space of a joint event. The concept of a basic cylinder set is introduced to describe joint event outcomes conditional on specific outcomes of basic events or unconditional on the outcome of basic events. The concept of outcome space partition is used to describe the minimum amount of information intended to be preserved by the event tree representation. These concepts form the basis for an algorithm for systematic search for and generation of the most compact (reduced) form of an event tree consistent with the minimum amount of information the tree should preserve. This mathematical foundation allows for the development of techniques for automated generation of event trees corresponding to joint events which are formally described through other types of graphical models. Such a technique has been developed for complex systems described by functional blocks and it is reported elsewhere. On the quantification issue of event trees, a formal definition of a probability space corresponding to the event tree outcomes is provided. Finally, a short discussion is offered on the relationship of the presented mathematical theory with the more general use of event trees in reliability analysis of dynamic systems

  14. Making CSB + -Trees Processor Conscious

    DEFF Research Database (Denmark)

    Samuel, Michael; Pedersen, Anders Uhl; Bonnet, Philippe

    2005-01-01

    of the CSB+-tree. We argue that it is necessary to consider a larger group of parameters in order to adapt CSB+-tree to processor architectures as different as Pentium and Itanium. We identify this group of parameters and study how it impacts the performance of CSB+-tree on Itanium 2. Finally, we propose......Cache-conscious indexes, such as CSB+-tree, are sensitive to the underlying processor architecture. In this paper, we focus on how to adapt the CSB+-tree so that it performs well on a range of different processor architectures. Previous work has focused on the impact of node size on the performance...... a systematic method for adapting CSB+-tree to new platforms. This work is a first step towards integrating CSB+-tree in MySQL’s heap storage manager....

  15. Submodular unsplittable flow on trees

    DEFF Research Database (Denmark)

    Adamaszek, Anna Maria; Chalermsook, Parinya; Ene, Alina

    2016-01-01

    We study the Unsplittable Flow problem (UFP) on trees with a submodular objective function. The input to this problem is a tree with edge capacities and a collection of tasks, each characterized by a source node, a sink node, and a demand. A subset of the tasks is feasible if the tasks can...... simultaneously send their demands from the source to the sink without violating the edge capacities. The goal is to select a feasible subset of the tasks that maximizes a submodular objective function. Our main result is an O(k log n)-approximation algorithm for Submodular UFP on trees where k denotes...... the pathwidth of the given tree. Since every tree has pathwidth O(log n), we obtain an O(log2 n) approximation for arbitrary trees. This is the first non-trivial approximation guarantee for the problem and it matches the best approximation known for UFP on trees with a linear objective function. Our main...

  16. (Almost) practical tree codes

    KAUST Repository

    Khina, Anatoly

    2016-08-15

    We consider the problem of stabilizing an unstable plant driven by bounded noise over a digital noisy communication link, a scenario at the heart of networked control. To stabilize such a plant, one needs real-time encoding and decoding with an error probability profile that decays exponentially with the decoding delay. The works of Schulman and Sahai over the past two decades have developed the notions of tree codes and anytime capacity, and provided the theoretical framework for studying such problems. Nonetheless, there has been little practical progress in this area due to the absence of explicit constructions of tree codes with efficient encoding and decoding algorithms. Recently, linear time-invariant tree codes were proposed to achieve the desired result under maximum-likelihood decoding. In this work, we take one more step towards practicality, by showing that these codes can be efficiently decoded using sequential decoding algorithms, up to some loss in performance (and with some practical complexity caveats). We supplement our theoretical results with numerical simulations that demonstrate the effectiveness of the decoder in a control system setting.

  17. Table 1. Primer sequences used for real-time qRT-PCR analysis of ...

    Indian Academy of Sciences (India)

    User

    TGTCCCAGTAAACCGCTC. GAATCCAGCACGATACCAGT. Figure 1. Expression analysis of candidate CsActin and CsFbox genes by qRT-PCR in response to 4°C treatment. The y-axis indicates Cq values, and error bars represent standard deviations of the mean values of four replicates. Rt, roots; St, stems; Le, leaves; Fl ...

  18. School Psychologists' Willingness to Implement RtI: The Role of Philosophical and Practical Readiness

    Science.gov (United States)

    Fan, Chung-Hau; Denner, Peter R.; Bocanegra, Joel O.; Ding, Yi

    2016-01-01

    After the change in IDEIA, different models of response to intervention (RtI) have been practiced widely in American school systems. School psychologists are in an important position to facilitate RtI practice and provide professional development in order to help their school systems successfully undergo this transformation. However, there is a…

  19. Simultaneous detection of three lily viruses using Triplex IC-RT-PCR.

    Science.gov (United States)

    Zhang, Yubao; Wang, Yajun; Xie, Zhongkui; Yang, Guo; Guo, Zhihong; Wang, Le

    2017-11-01

    Viruses commonly infecting lily (Lilium spp.) include: Lily symptomless virus (LSV), Cucumber mosaic virus (CMV) and Lily mottle virus (LMoV). These viruses usually co-infect lilies causing severe economic losses in terms of quantity and quality of flower and bulb production around the world. Reliable and precise detection systems need to be developed for virus identification. We describe the development of a triplex immunocapture (IC) reverse transcription (RT) polymerase chain reaction (PCR) assay for the simultaneous detection of LSV, CMV and LMoV. The triplex IC-RT-PCR was compared with a quadruplex RT-PCR assay. Relative to the quadruplex RT-PCR, the specificity of the triplex IC-RT-PCR system for LSV, CMV and LMoV was 100% for field samples. The sensitivity of the triplex IC-RT-PCR system was 99.4%, 81.4% and 98.7% for LSV, CMV and LMoV, respectively. Agreement (κ) between the results obtained from the two tests was 0.968, 0.844 and 0.984 for LSV, CMV and LMoV, respectively. This is the first report of the simultaneous detection of LSV, CMV and LMoV in a triplex IC-RT-PCR assay. In particular we believe this convenient and reliable triplex IC-RT-PCR method could be used routinely for large-scale field surveys or crop health monitoring of lily. Copyright © 2017. Published by Elsevier B.V.

  20. Quantitative real-time RT-PCR and chromogenic in situ hybridization

    DEFF Research Database (Denmark)

    Rosa, Fabíola E; Silveira, Sara M; Silveira, Cássia G T

    2009-01-01

    . METHODS: To elucidate the molecular profile of HER-2 status, mRNA and protein expression in 75 invasive breast carcinomas were analyzed by real time quantitative RT-PCR (qRT-PCR) and IHC, respectively. Amplifications were evaluated in 43 of these cases by CISH and in 11 by FISH. RESULTS: The concordance...

  1. Propidium monoazide reverse transcription PCR and RT-qPCR for detecting infectious enterovirus and norovirus

    Science.gov (United States)

    Presently there is no established cell line or small animal model that allows for the detection of infectious human norovirus. Current methods based on RT-PCR and RT-qPCR detect both infectious and non-infectious virus and thus the conclusions that may be drawn regarding the publ...

  2. L. Harrison: Mass (to St. Anthony); A. Pärt: Berliner Messe / Robert Cowan

    Index Scriptorium Estoniae

    Cowan, Robert

    1994-01-01

    Uuest heliplaadist "L. Harrison: Mass (to St. Anthony); A. Pärt: Berliner Messe. Oregon Repertory Singers / Gilbert Seeley. Koch International Classics CD 37 177-2; Pärt - comparative version: Estonian Phil. Chbr. Ch., Tallinn CO / Kaljuste" (11/93)(ECM) 439 162-2

  3. Teekond Kirjasõna Vabariigis / Märt Väljataga ; intervjueerinud Marek Tamm

    Index Scriptorium Estoniae

    Väljataga, Märt, 1965-

    2015-01-01

    rt Väljataga tõlgitud R. Rorty artiklist "Pragmatism ja filosoofia", mis ilmus Akadeemia 1992, nr. 2, lk. 281-282, 285, tema filosoofiast ja Märt Väljataga tööst ajakirja "Vikerkaar" toimetajana ning tõlkijana

  4. Rate of tree carbon accumulation increases continuously with tree size

    Science.gov (United States)

    Stephenson, N.L.; Das, A.J.; Condit, R.; Russo, S.E.; Baker, P.J.; Beckman, N.G.; Coomes, D.A.; Lines, E.R.; Morris, W.K.; Rüger, N.; Álvarez, E.; Blundo, C.; Bunyavejchewin, S.; Chuyong, G.; Davies, S.J.; Duque, Á.; Ewango, C.N.; Flores, O.; Franklin, J.F.; Grau, H.R.; Hao, Z.; Harmon, M.E.; Hubbell, S.P.; Kenfack, D.; Lin, Y.; Makana, J.-R.; Malizia, A.; Malizia, L.R.; Pabst, R.J.; Pongpattananurak, N.; Su, S.-H.; Sun, I-F.; Tan, S.; Thomas, D.; van Mantgem, P.J.; Wang, X.; Wiser, S.K.; Zavala, M.A.

    2014-01-01

    Forests are major components of the global carbon cycle, providing substantial feedback to atmospheric greenhouse gas concentrations. Our ability to understand and predict changes in the forest carbon cycle—particularly net primary productivity and carbon storage - increasingly relies on models that represent biological processes across several scales of biological organization, from tree leaves to forest stands. Yet, despite advances in our understanding of productivity at the scales of leaves and stands, no consensus exists about the nature of productivity at the scale of the individual tree, in part because we lack a broad empirical assessment of whether rates of absolute tree mass growth (and thus carbon accumulation) decrease, remain constant, or increase as trees increase in size and age. Here we present a global analysis of 403 tropical and temperate tree species, showing that for most species mass growth rate increases continuously with tree size. Thus, large, old trees do not act simply as senescent carbon reservoirs but actively fix large amounts of carbon compared to smaller trees; at the extreme, a single big tree can add the same amount of carbon to the forest within a year as is contained in an entire mid-sized tree. The apparent paradoxes of individual tree growth increasing with tree size despite declining leaf-level and stand-level productivity can be explained, respectively, by increases in a tree’s total leaf area that outpace declines in productivity per unit of leaf area and, among other factors, age-related reductions in population density. Our results resolve conflicting assumptions about the nature of tree growth, inform efforts to understand and model forest carbon dynamics, and have additional implications for theories of resource allocation and plant senescence.

  5. Regression with Sparse Approximations of Data

    DEFF Research Database (Denmark)

    Noorzad, Pardis; Sturm, Bob L.

    2012-01-01

    We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...

  6. Spontaneous regression of a congenital melanocytic nevus

    Directory of Open Access Journals (Sweden)

    Amiya Kumar Nath

    2011-01-01

    Full Text Available Congenital melanocytic nevus (CMN may rarely regress which may also be associated with a halo or vitiligo. We describe a 10-year-old girl who presented with CMN on the left leg since birth, which recently started to regress spontaneously with associated depigmentation in the lesion and at a distant site. Dermoscopy performed at different sites of the regressing lesion demonstrated loss of epidermal pigments first followed by loss of dermal pigments. Histopathology and Masson-Fontana stain demonstrated lymphocytic infiltration and loss of pigment production in the regressing area. Immunohistochemistry staining (S100 and HMB-45, however, showed that nevus cells were present in the regressing areas.

  7. Pesticides in Urban Multiunit Dwellings: Hazard IdentificationUsing Classification and Regression Tree (CART) Analysis

    Science.gov (United States)

    Many units in public housing or other low-income urban dwellings may have elevated pesticide residues, given recurring infestation, but it would be logistically and economically infeasible to sample a large number of units to identify highly exposed households to design interven...

  8. Predicting forest attributes from climate data using a recursive partitioning and regression tree algorithm

    Science.gov (United States)

    Greg C. Liknes; Christopher W. Woodall; Charles H. Perry

    2009-01-01

    Climate information frequently is included in geospatial modeling efforts to improve the predictive capability of other data sources. The selection of an appropriate climate data source requires consideration given the number of choices available. With regard to climate data, there are a variety of parameters (e.g., temperature, humidity, precipitation), time intervals...

  9. A Multi-industry Default Prediction Model using Logistic Regression and Decision Tree

    OpenAIRE

    Suresh Ramakrishnan; Maryam Mirzaei; Mahmoud Bekri

    2015-01-01

    The accurate prediction of corporate bankruptcy for the firms in different industries is of a great concern to investors and creditors, as the reduction of creditors’ risk and a considerable amount of saving for an industry economy can be possible. Financial statements vary between industries. Therefore, economic intuition suggests that industry effects should be an important component in bankruptcy prediction. This study attempts to detail the characteristics of each industry using sector in...

  10. Multi-site solar power forecasting using gradient boosted regression trees

    DEFF Research Database (Denmark)

    Persson, Caroline Stougård; Bacher, Peder; Shiga, Takahiro

    2017-01-01

    The challenges to optimally utilize weather dependent renewable energy sources call for powerful tools for forecasting. This paper presents a non-parametric machine learning approach used for multi-site prediction of solar power generation on a forecast horizon of one to six hours. Historical pow...

  11. Implementing GIS regression trees for generating the spatial distribution of copper in Mediterranean environments

    DEFF Research Database (Denmark)

    Bou Kheir, Rania; Greve, Mogens Humlekrog; Deroin, Jean-Paul

    2013-01-01

    Soil contamination by heavy metals has become a widespread dangerous problem in many parts of the world, including the Mediterranean environments. This is closely related to the increase irrigation by waste waters, to the uncontrolled application of sewage sludge, industrial effluents, pesticides...... and fertilizers, to the rapid urbanization, to the atmospheric deposition of dust and aerosols, to the vehicular emissions and to many other negative human activities. In this context, this paper predicts the spatial distribution and concentration level of copper (Cu) in the 195km2 of Nahr el-Jawz watershed......H, hydraulical conductivity, organic matter, stoniness ratio, soil depth, slope gradient, slope aspect, slope curvature, land cover/use, distance to drainage line, proximity to roads, nearness to cities, and surroundings to waste areas) were generated from satellite imageries, Digital Elevation Models (DEMs...

  12. Decision Tree of Occupational Lung Cancer Using Classification and Regression Analysis

    Directory of Open Access Journals (Sweden)

    Tae-Woo Kim

    2010-12-01

    Conclusion: We found that exposure to lung carcinogens, latency and smoking history were predictive factors of approval for occupational lung cancer. Further studies for work-relatedness of occupational disease are needed.

  13. Integrating classification trees with local logistic regression in Intensive Care prognosis

    NARCIS (Netherlands)

    Abu-Hanna, Ameen; de Keizer, Nicolette

    2003-01-01

    Health care effectiveness and efficiency are under constant scrutiny especially when treatment is quite costly as in the Intensive Care (IC). Currently there are various international quality of care programs for the evaluation of IC. At the heart of such quality of care programs lie prognostic

  14. Simultaneous detection and identification of four cherry viruses by two step multiplex RT-PCR with an internal control of plant nad5 mRNA.

    Science.gov (United States)

    Noorani, Md Salik; Awasthi, Prachi; Sharma, Maheshwar Prasad; Ram, Raja; Zaidi, Aijaz Asgar; Hallan, Vipin

    2013-10-01

    A multiplex reverse transcription-polymerase chain reaction (mRT-PCR) was developed and standardized for the simultaneous detection of four cherry viruses: Cherry virus A (CVA, Genus; Capillovirus), Cherry necrotic rusty mottle virus (CNRMV, unassigned species of the Betaflexiviridae), Little cherry virus 1 (LChV-1, Genus; Closterovirus) and Prunus necrotic ringspot virus (PNRSV, Genus; Ilarvirus) with nad5 as plant internal control. A reliable and quick method for total plant RNA extraction from pome and stone fruit trees was also developed. To minimize primer dimer formation, a single antisense primer for CVA and CNRMV was used. A mixture of random hexamer and oligo (dT) primer was used for cDNA synthesis, which was highly suited and economic for multiplexing. All four viruses were detected successfully by mRT-PCR in artificially created viral RNA mixture and field samples of sweet cherry. The identity of the viruses was confirmed by sequencing. The assay could detect above viruses in diluted cDNA (10(-4)) and RNA (10(-3), except PNRSV which was detected only till ten times lesser dilution). The developed mRT-PCR will not only be useful for the detection of viruses from single or multiple infections of sweet cherry plants but also for other stone and pome fruits. The developed method will be therefore quite helpful for virus indexing, plant quarantine and certification programs. This is the first report for the simultaneous detection of four cherry viruses by mRT-PCR. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Behavior of cesium-134 in the tea tree

    International Nuclear Information System (INIS)

    Xu Yinliang; Chen Kaixuan; Chen Chuangqun

    1996-01-01

    The radioactivity changes of 134 Cs in the aged and the young leaves followed an exponential regression function after spraying 134 Cs in the tea trees. Contamination by spraying 134 Cs greatly harmed tea tree and by irrigating or mixing 134 Cs with soil resulted in a potential endangerment. The concentrating ability of tea leaves for 134 CS was very low and K value was 0.02. After the fresh tea leaves were processed to dry tea, the content of 134 Cs decreased by about 13.3%. When the tea leaves were soaked in hot water, the extraction ratio was around 83.6%

  16. Pre-treatment ASPECTS-DWI score has a relation with functional outcome at 3 months following intravenous rt-PA therapy

    International Nuclear Information System (INIS)

    Nezu, Tomohisa; Koga, Masatoshi; Naganuma, Masaki

    2009-01-01

    The clinical importance of early ischemic changes (EIC) on diffusion-weighted imaging (DWI) before recombinant tissue-plasminogen activator (rt-PA) thrombolysis has not been elucidated well. The present study aimed evaluating whether Alberta Stroke Programme Early CT Score (ASPECTS)-DWI before rt-PA therapy could predict chronic independent outcome. Consecutive stroke patients treated with rt-PA from October 2005 through July 2008 were registered from 10 major stroke centers located without regional imbalance in Japan. Before rt-PA IV infusion, we assessed EIC on DWI by using ASPECTS-DWI (11 points). Independent outcome was defined by modified Rankin Scale score (mRS) 0-2 at 3 months after stroke onset. A total of 420 patients (280 men, 71±11 years in age) were studied, and 221 (52.6%) of them were independent (mRS 0-2) at 3 months. The independent patients were younger, had less hypertension and atrial fibrillation, lower baseline National Institutes of Health Stroke Scale (NIHSS) score, higher ASPECTS-DWI, less internal carotid artery occlusion than dependent patients (mRS 3-6, P<0.05 for all). The optimal cutoff score of ASPECTS-DWI to predict independent outcome was ≥7 with a sensitivity of 92% and specificity of 31%, and the area under the receiver-operating characteristic curve was 0.622. After multivariate logistic regression analysis, ASPECTS-DWI ≥7 was independently predictive of an independent outcome at 3 months (odds ratio (OR) 2.78, 95% confidence interval (CI) 1.45-5.49). ASPECTS-DWI before rt-PA therapy is useful to predict patients' chronic functional outcome. (author)

  17. Early fibrinogen degradation coagulopathy: a predictive factor of parenchymal hematomas in cerebral rt-PA thrombolysis.

    Science.gov (United States)

    Sun, Xuhong; Berthiller, Julien; Trouillas, Paul; Derex, Laurent; Diallo, Laho; Hanss, Michel

    2015-04-15

    The purpose of this study was to systematically determine the correlations between the post-thrombolytic changes of hemostasis parameters and the occurrence of early intracerebral hemorrhage (ICH). In 72 consecutive patients with cerebral infarcts treated with rt-PA, plasma levels of fibrinogen, plasminogen, alpha2-antiplasmin, factor XIII, fibrin(ogen) degradation products (FDPs) and d-Dimers were measured at baseline, 2 and 24h after thrombolysis. Correlations were studied between the hemostasis events and early (less than 24h) hemorrhagic infarcts (HIs) or parenchymatous hematomas (PH). Of 72 patients, 6 patients (8.3%) had early PHs, 11 (15.3%) had early HIs, and 55 (76.4%) had no bleeding. Early HIs were not linked to any hemostasis parameter at any time. Univariate comparison of patients having early PHs with non-bleeding patients showed hemostasis abnormalities at 2h: high FDP (p=0.01), high Log FDP (p=0.01), low fibrinogen (p=0.01), and low Log fibrinogen (p=0.01). Logistic regression adjusted for age, NIHSS and diabetes confirmed these 2hour predictors: Log FDP (OR: 7.50; CI: 1.26 to 44.61, p=0.03), and Log fibrinogen (OR: 19.32; CI: 1.81 to 205.98, p=0.01). The decrease in fibrinogen less than 2g/L multiplies the odds of early PH by a factor 12.82. An early fibrinogen degradation coagulopathy involving an increase of FDP and a massive consumption of circulating fibrinogen is predictive of early parenchymal hematomas, indicating the occurrence of a particularly intense lysis of circulating fibrinogen. These results, if confirmed by future studies, suggest that early assays of fibrinogen and FDP may be useful in predicting the risk of post-thrombolytic intracerebral hematoma. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. On Determining if Tree-based Networks Contain Fixed Trees.

    Science.gov (United States)

    Anaya, Maria; Anipchenko-Ulaj, Olga; Ashfaq, Aisha; Chiu, Joyce; Kaiser, Mahedi; Ohsawa, Max Shoji; Owen, Megan; Pavlechko, Ella; St John, Katherine; Suleria, Shivam; Thompson, Keith; Yap, Corrine

    2016-05-01

    We address an open question of Francis and Steel about phylogenetic networks and trees. They give a polynomial time algorithm to decide if a phylogenetic network, N, is tree-based and pose the problem: given a fixed tree T and network N, is N based on T? We show that it is [Formula: see text]-hard to decide, by reduction from 3-Dimensional Matching (3DM) and further that the problem is fixed-parameter tractable.

  19. Trees in the city: valuing street trees in Portland, Oregon

    Science.gov (United States)

    G.H. Donovan; D.T. Butry

    2010-01-01

    We use a hedonic price model to simultaneously estimate the effects of street trees on the sales price and the time-on-market (TOM) of houses in Portland. Oregon. On average, street trees add $8,870 to sales price and reduce TOM by 1.7 days. In addition, we found that the benefits of street trees spill over to neighboring houses. Because the provision and maintenance...

  20. Systolic trees and systolic language recognition by tree automata

    Energy Technology Data Exchange (ETDEWEB)

    Steinby, M

    1983-01-01

    K. Culik II, J. Gruska, A. Salomaa and D. Wood have studied the language recognition capabilities of certain types of systolically operating networks of processors (see research reports Cs-81-32, Cs-81-36 and Cs-82-01, Univ. of Waterloo, Ontario, Canada). In this paper, their model for systolic VLSI trees is formalised in terms of standard tree automaton theory, and the way in which some known facts about recognisable forests and tree transductions can be applied in VLSI tree theory is demonstrated. 13 references.