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Sample records for regression tree cart

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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...

  11. 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.

  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. 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

  14. 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%,…

  15. 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...

  16. An application in identifying high-risk populations in alternative tobacco product use utilizing logistic regression and CART: a heuristic comparison.

    Science.gov (United States)

    Lei, Yang; Nollen, Nikki; Ahluwahlia, Jasjit S; Yu, Qing; Mayo, Matthew S

    2015-04-09

    Other forms of tobacco use are increasing in prevalence, yet most tobacco control efforts are aimed at cigarettes. In light of this, it is important to identify individuals who are using both cigarettes and alternative tobacco products (ATPs). Most previous studies have used regression models. We conducted a traditional logistic regression model and a classification and regression tree (CART) model to illustrate and discuss the added advantages of using CART in the setting of identifying high-risk subgroups of ATP users among cigarettes smokers. The data were collected from an online cross-sectional survey administered by Survey Sampling International between July 5, 2012 and August 15, 2012. Eligible participants self-identified as current smokers, African American, White, or Latino (of any race), were English-speaking, and were at least 25 years old. The study sample included 2,376 participants and was divided into independent training and validation samples for a hold out validation. Logistic regression and CART models were used to examine the important predictors of cigarettes + ATP users. The logistic regression model identified nine important factors: gender, age, race, nicotine dependence, buying cigarettes or borrowing, whether the price of cigarettes influences the brand purchased, whether the participants set limits on cigarettes per day, alcohol use scores, and discrimination frequencies. The C-index of the logistic regression model was 0.74, indicating good discriminatory capability. The model performed well in the validation cohort also with good discrimination (c-index = 0.73) and excellent calibration (R-square = 0.96 in the calibration regression). The parsimonious CART model identified gender, age, alcohol use score, race, and discrimination frequencies to be the most important factors. It also revealed interesting partial interactions. The c-index is 0.70 for the training sample and 0.69 for the validation sample. The misclassification

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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)

  4. 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

  5. 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.

  6. 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.

  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. 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.

  9. 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.

  10. 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.

  11. Efficient tumor regression by adoptively transferred CEA-specific CAR-T cells associated with symptoms of mild cytokine release syndrome.

    Science.gov (United States)

    Wang, Linan; Ma, Ning; Okamoto, Sachiko; Amaishi, Yasunori; Sato, Eiichi; Seo, Naohiro; Mineno, Junichi; Takesako, Kazutoh; Kato, Takuma; Shiku, Hiroshi

    2016-01-01

    Carcinoembryonic antigen (CEA) is a cell surface antigen highly expressed in various cancer cell types and in healthy tissues. It has the potential to be a target for chimeric antigen receptor (CAR)-modified T-cell therapy; however, the safety of this approach in terms of on-target/off-tumor effects needs to be determined. To address this issue in a clinically relevant model, we used a mouse model in which the T cells expressing CEA-specific CAR were transferred into tumor-bearing CEA-transgenic (Tg) mice that physiologically expressed CEA as a self-antigen. The adoptive transfer in conjunction with lymphodepleting and myeloablative preconditioning mediated significant tumor regression but caused weight loss in CEA-Tg, but not in wild-type mice. The weight loss was not associated with overt inflammation in the CEA-expressing gastrointestinal tract but was associated with malnutrition, reflected in elevated systemic levels of cytokines linked to anorexia, which could be controlled by the administration of an anti-IL-6 receptor monoclonal antibody without compromising efficacy. The apparent relationship between lymphodepleting and myeloablative preconditioning, efficacy, and off-tumor toxicity of CAR-T cells would necessitate the development of CEA-specific CAR-T cells with improved signaling domains that require less stringent preconditioning for their efficacy. Taken together, these results suggest that CEA-specific CAR-based adoptive T-cell therapy may be effective for patients with CEA + solid tumors. Distinguishing the fine line between therapeutic efficacy and off-tumor toxicity would involve further modifications of CAR-T cells and preconditioning regimens.

  12. 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.

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

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    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

  14. 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

  15. 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...

  16. 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.

  17. 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...

  18. Using CART to segment road images

    Science.gov (United States)

    Davies, Bob; Lienhart, Rainer

    2006-01-01

    The 2005 DARPA Grand Challenge is a 132 mile race through the desert with autonomous robotic vehicles. Lasers mounted on the car roof provide a map of the road up to 20 meters ahead of the car but the car needs to see further in order to go fast enough to win the race. Computer vision can extend that map of the road ahead but desert road is notoriously similar to the surrounding desert. The CART algorithm (Classification and Regression Trees) provided a machine learning boost to find road while at the same time measuring when that road could not be distinguished from surrounding desert.

  19. 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.

  20. 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

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  3. Using Evidence-Based Decision Trees Instead of Formulas to Identify At-Risk Readers. REL 2014-036

    Science.gov (United States)

    Koon, Sharon; Petscher, Yaacov; Foorman, Barbara R.

    2014-01-01

    This study examines whether the classification and regression tree (CART) model improves the early identification of students at risk for reading comprehension difficulties compared with the more difficult to interpret logistic regression model. CART is a type of predictive modeling that relies on nonparametric techniques. It presents results in…

  4. 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....

  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. 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%.

  8. 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%.

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

    Directory of Open Access Journals (Sweden)

    Wisoedhanie Widi Anugrahanti

    2017-06-01

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

  10. 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.

  11. 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.

  12. 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.

  13. 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.…

  14. 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…

  15. 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)....

  16. 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.

  17. 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.

  18. The use of ZIP and CART to model cryptosporidiosis in relation to climatic variables.

    Science.gov (United States)

    Hu, Wenbiao; Mengersen, Kerrie; Fu, Shiu-Yun; Tong, Shilu

    2010-07-01

    This research assesses the potential impact of weekly weather variability on the incidence of cryptosporidiosis disease using time series zero-inflated Poisson (ZIP) and classification and regression tree (CART) models. Data on weather variables, notified cryptosporidiosis cases and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Both time series ZIP and CART models show a clear association between weather variables (maximum temperature, relative humidity, rainfall and wind speed) and cryptosporidiosis disease. The time series CART models indicated that, when weekly maximum temperature exceeded 31 degrees C and relative humidity was less than 63%, the relative risk of cryptosporidiosis rose by 13.64 (expected morbidity: 39.4; 95% confidence interval: 30.9-47.9). These findings may have applications as a decision support tool in planning disease control and risk-management programs for cryptosporidiosis disease.

  19. 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...

  20. Simulation of land use change in the three gorges reservoir area based on CART-CA

    Science.gov (United States)

    Yuan, Min

    2018-05-01

    This study proposes a new method to simulate spatiotemporal complex multiple land uses by using classification and regression tree algorithm (CART) based CA model. In this model, we use classification and regression tree algorithm to calculate land class conversion probability, and combine neighborhood factor, random factor to extract cellular transformation rules. The overall Kappa coefficient is 0.8014 and the overall accuracy is 0.8821 in the land dynamic simulation results of the three gorges reservoir area from 2000 to 2010, and the simulation results are satisfactory.

  1. 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.

  2. 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 ...

  3. 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)

  4. [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.

  5. 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

  6. 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

  7. 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.

  8. Service Cart For Engines

    Science.gov (United States)

    Ng, Gim Shek

    1995-01-01

    Cart supports rear-mounted air-cooled engine from Volkswagen or Porsche automobile. One person removes, repairs, tests, and reinstalls engine of car, van, or home-built airplane. Consists of framework of wood, steel, and aluminum components supported by four wheels. Engine lifted from vehicle by hydraulic jack and gently lowered onto waiting cart. Jack removed from under engine. Rear of vehicle raised just enough that engine can be rolled out from under it. Cart easily supports 200-lb engine. Also used to hold transmission. With removable sheet-metal top, cart used as portable seat.

  9. 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....

  10. 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

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. [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

  19. State of the cart.

    Science.gov (United States)

    Bernstein, C; Weiss, S; Lorenzini, B

    1994-03-15

    Food on wheels: it's here, there and everywhere. But while some operations rev up cart expansion plans, others have shifted into low gear. Here's an update on that '90s phenomenon: mobile merchandising.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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'.

  9. 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,…

  10. 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...

  11. 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…

  12. 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.

  13. 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

  14. 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,...

  15. 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.

  16. 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....

  17. Jeux de cartes

    Directory of Open Access Journals (Sweden)

    Priscilla DE ROO

    1988-03-01

    Full Text Available Le dessinateur Cabu illustre par la carte deux étapes récentes de l'État de la France: les rapports entre eux (État et institutions et nous (les Français et leur territoire avant et après la cohabitation.

  18. Jeux de cartes

    Directory of Open Access Journals (Sweden)

    Pierre GENTELLE

    1986-09-01

    Full Text Available Dans la grande tradition de la science-fiction et des lieux imaginaires traduits ici en «jeux» de cartes, l'auteur bouleverse quelques localisations au prix de mouvements tectoniques imprévus et en prévoit quelques conséquences.

  19. 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

  20. 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

  1. 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...

  2. [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.

  3. IL-7 and CCL19 expression in CAR-T cells improves immune cell infiltration and CAR-T cell survival in the tumor.

    Science.gov (United States)

    Adachi, Keishi; Kano, Yosuke; Nagai, Tomohiko; Okuyama, Namiko; Sakoda, Yukimi; Tamada, Koji

    2018-04-01

    Infiltration, accumulation, and survival of chimeric antigen receptor T (CAR-T) cells in solid tumors is crucial for tumor clearance. We engineered CAR-T cells to express interleukin (IL)-7 and CCL19 (7 × 19 CAR-T cells), as these factors are essential for the maintenance of T-cell zones in lymphoid organs. In mice, 7 × 19 CAR-T cells achieved complete regression of pre-established solid tumors and prolonged mouse survival, with superior anti-tumor activity compared to conventional CAR-T cells. Histopathological analyses showed increased infiltration of dendritic cells (DC) and T cells into tumor tissues following 7 × 19 CAR-T cell therapy. Depletion of recipient T cells before 7 × 19 CAR-T cell administration dampened the therapeutic effects of 7 × 19 CAR-T cell treatment, suggesting that CAR-T cells and recipient immune cells collaborated to exert anti-tumor activity. Following treatment of mice with 7 × 19 CAR-T cells, both recipient conventional T cells and administered CAR-T cells generated memory responses against tumors.

  4. Evaluation of the New York City Green Carts program

    Directory of Open Access Journals (Sweden)

    Shannon M Farley

    2015-12-01

    Full Text Available Access to fresh fruits and vegetables is a concern, particularly among low-income populations. Mobile vending is one strategy to expand produce availability and access to increase consumption. In 2008, New York City launched a mobile vending initiative, Green Carts. We report on the evaluation. Three waves of cross-sectional observational surveys of produce availability, variety, and quality were conducted during the summers of 2008, 2009, and 2011 in a stratified random sample of stores and carts comparing establishments in Green Cart neighborhoods (n = 13 with comparison neighborhoods (n = 3. Bivariate analyses for availability, variety, and quality comparing Green Cart and comparison neighborhoods were presented across years, and logistic and negative binomial regressions were used to test whether fruit and vegetable availability, variety, and quality increased in Green Cart compared with comparison neighborhoods, adjusting for clustering and neighborhood demographics. Establishments selling fruits and vegetables in Green Cart neighborhoods increased between 2008 and 2011 (50% to 69%, p <0.0001; there was no comparable increase in comparison neighborhoods. Establishments selling more than 10 fruits and vegetables types increased from 31% to 38% (p = 0.0414 in Green Cart neighborhoods; there was no change in comparison neighborhoods. Produce quality was high among comparison establishments, with 95% and 94% meeting the quality threshold in 2008 and 2011, while declining in Green Cart neighborhood establishments from 96% to 88% (p < 0.0001. Sustained produce availability was found in Green Cart neighborhoods between 2008–2011. Green Carts are one strategy contributing to improving produce access among New Yorkers.

  5. 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...

  6. 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

  7. 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

  8. 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

  9. 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…

  10. Controlling errors in unidosis carts

    Directory of Open Access Journals (Sweden)

    Inmaculada Díaz Fernández

    2010-01-01

    Full Text Available Objective: To identify errors in the unidosis system carts. Method: For two months, the Pharmacy Service controlled medication either returned or missing from the unidosis carts both in the pharmacy and in the wards. Results: Uncorrected unidosis carts show a 0.9% of medication errors (264 versus 0.6% (154 which appeared in unidosis carts previously revised. In carts not revised, the error is 70.83% and mainly caused when setting up unidosis carts. The rest are due to a lack of stock or unavailability (21.6%, errors in the transcription of medical orders (6.81% or that the boxes had not been emptied previously (0.76%. The errors found in the units correspond to errors in the transcription of the treatment (3.46%, non-receipt of the unidosis copy (23.14%, the patient did not take the medication (14.36%or was discharged without medication (12.77%, was not provided by nurses (14.09%, was withdrawn from the stocks of the unit (14.62%, and errors of the pharmacy service (17.56% . Conclusions: It is concluded the need to redress unidosis carts and a computerized prescription system to avoid errors in transcription.Discussion: A high percentage of medication errors is caused by human error. If unidosis carts are overlooked before sent to hospitalization units, the error diminishes to 0.3%.

  11. Fan Cart: The Next Generation

    Science.gov (United States)

    Lamore, Brian

    2016-01-01

    For years the fan cart has provided physics students with an excellent resource for exploring fundamental mechanics concepts such as acceleration, Newton's laws, impulse, momentum, work-energy, and energy conversions. "The Physics Teacher" has even seen some excellent do-it-yourself (DIY) fan carts and activities. If you are interested…

  12. Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models

    Directory of Open Access Journals (Sweden)

    Paccaud Fred

    2004-04-01

    Full Text Available Abstract Background We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. Methods Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i linear regression; (ii logistic classification; (iii regression trees; (iv classification trees (iii and iv are collectively known as "CART". Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. Results Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60–80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. Conclusions There were no striking differences between either the algebraic (i, ii vs. non-algebraic (iii, iv, or the regression (i, iii vs. classification (ii, iv modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

  13. 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.

  14. 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...

  15. 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.

  16. A la Carte Community

    DEFF Research Database (Denmark)

    Gundelach, Peter; Brincker, Benedikte

    2010-01-01

    and shows that there are high levels of virtual as well as face-to-face interaction among the members. The participants feel that they belong to the community and many also feel that they are recognised as part of the community. However, the members do not share common values neither in relation to software......The exchange of open source software is a phenomenon that is becoming in- creasingly significant to IT users. This article presents the results of a study of the TYPO3 community, a community related to an open source CMS software. The article explores the community, identity and values of TYPO3...... pro- duction nor generally. Instead, they stress that you are free to choose your own values. Against this background, the authors introduce the notion of an ‘a la carte community', i.e. a community where individuals pick and choose their degree of participation and integra- tion into the community...

  17. FMIT alignment cart

    International Nuclear Information System (INIS)

    Potter, R.C.; Dauelsberg, L.B.; Clark, D.C.; Grieggs, R.J.

    1981-01-01

    The Fusion Materials Irradiation Test (FMIT) Facility alignment cart must perform several functions. It must serve as a fixture to receive the drift-tube girder assembly when it is removed from the linac tank. It must transport the girder assembly from the linac vault to the area where alignment or disassembly is to take place. It must serve as a disassembly fixture to hold the girder while individual drift tubes are removed for repair. It must align the drift tube bores in a straight line parallel to the girder, using an optical system. These functions must be performed without violating any clearances found within the building. The bore tubes of the drift tubes will be irradiated, and shielding will be included in the system for easier maintenance

  18. La redistribution des cartes.

    Directory of Open Access Journals (Sweden)

    Muriel Berthou Crestey

    2009-11-01

    Full Text Available Redessinée par Jacques Rancière, la carte du sensible acquiert une dimension interactive, formant un réseau de connexions organisé sans hiérarchie préétablie. Fondée sur le principe de l’horizontalité et de l’égalité, elle déplace les limites pour offrir un terrain propice à l’émancipation, permettant un cadrage inédit, un regard neuf. Chaque place assignée est désormais ouverte et vacante. Il n’y a plus de chemin tracé. Toute nouvelle configuration est possible et ...

  19. 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.

  20. Engineering CAR-T cells.

    Science.gov (United States)

    Zhang, Cheng; Liu, Jun; Zhong, Jiang F; Zhang, Xi

    2017-01-01

    Chimeric antigen receptor redirected T cells (CAR-T cells) have achieved inspiring outcomes in patients with B cell malignancies, and are now being investigated in other hematologic malignancies and solid tumors. CAR-T cells are generated by the T cells from patients' or donors' blood. After the T cells are expanded and genetically modified, they are reinfused into the patients. However, many challenges still need to be resolved in order for this technology to gain widespread adoption. In this review, we first discuss the structure and evolution of chimeric antigen receptors. We then report on the tools used for production of CAR-T cells. Finally, we address the challenges posed by CAR-T cells.

  1. Exploring the social determinants of mental health service use using intersectionality theory and CART analysis.

    Science.gov (United States)

    Cairney, John; Veldhuizen, Scott; Vigod, Simone; Streiner, David L; Wade, Terrance J; Kurdyak, Paul

    2014-02-01

    Fewer than half of individuals with a mental disorder seek formal care in a given year. Much research has been conducted on the factors that influence service use in this population, but the methods generally used cannot easily identify the complex interactions that are thought to exist. In this paper, we examine predictors of subsequent service use among respondents to a population health survey who met criteria for a past-year mood, anxiety or substance-related disorder. To determine service use, we use an administrative database including all physician consultations in the period of interest. To identify predictors, we use classification tree (CART) analysis, a data mining technique with the ability to identify unsuspected interactions. We compare results to those from logistic regression models. We identify 1213 individuals with past-year disorder. In the year after the survey, 24% (n=312) of these had a mental health-related physician consultation. Logistic regression revealed that age, sex and marital status predicted service use. CART analysis yielded a set of rules based on age, sex, marital status and income adequacy, with marital status playing a role among men and by income adequacy important among women. CART analysis proved moderately effective overall, with agreement of 60%, sensitivity of 82% and specificity of 53%. Results highlight the potential of data-mining techniques to uncover complex interactions, and offer support to the view that the intersection of multiple statuses influence health and behaviour in ways that are difficult to identify with conventional statistics. The disadvantages of these methods are also discussed.

  2. Analysis of stable states in global savannas: is the CART pulling the horse?

    Science.gov (United States)

    Hanan, Niall P; Tredennick, Andrew T; Prihodko, Lara; Bucini, Gabriela; Dohn, Justin

    2014-03-01

    Multiple stable states, bifurcations and thresholds are fashionable concepts in the ecological literature, a recognition that complex ecosystems may at times exhibit the interesting dynamic behaviours predicted by relatively simple biomathematical models. Recently, several papers in Global Ecology and Biogeography , Proceedings of the National Academy of Sciences USA, Science and elsewhere have attempted to quantify the prevalence of alternate stable states in the savannas of Africa, Australia and South America, and the tundra-taiga-grassland transitions of the circum-boreal region using satellite-derived woody canopy cover. While we agree with the logic that basins of attraction can be inferred from the relative frequencies of ecosystem states observed in space and time, we caution that the statistical methodologies underlying the satellite product used in these studies may confound our ability to infer the presence of multiple stable states. We demonstrate this point using a uniformly distributed 'pseudo-tree cover' database for Africa that we use to retrace the steps involved in creation of the satellite tree-cover product and subsequent analysis. We show how classification and regression tree (CART)-based products may impose discontinuities in satellite tree-cover estimates even when such discontinuities are not present in reality. As regional and global remote sensing and geospatial data become more easily accessible for ecological studies, we recommend careful consideration of how error distributions in remote sensing products may interact with the data needs and theoretical expectations of the ecological process under study.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Fernando Sánchez Lasheras

    2015-03-01

    Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. Classification decision tree in CT imaging: application to the differential diagnosis of solitary pulmonary nodules

    International Nuclear Information System (INIS)

    Ma Hongxia; Guo Yulin; Wang Qiuping; Qiang Yongqian; Liu Min; Guo Xiaojuan; Guo Youmin; Chen Qihang

    2008-01-01

    Objective: To establish classification and regression tree (CART) for differentiating benign from malignant solitary pulmonary nudules (SPN). Methods: One hundred and sixteen consecutive cases with 116 solitary pulmonary nodules, which finally were pathologically proven 54 malignant nodules and 62 benign nodules, were prospectively registered in this research. Twelve clinical presentations and 22 CT findings were collected as predictors. A classification tree was established to distinguish benign SPNs from malignant ones. In the observer test, two groups (one made of junior radiologists and one of senior radiologists) were independently presented with clinical information and CT images without knowing the pathologic and machine-learning results. Performance of observers and CART were compared by receiver operating characteristic analysis. Results: Receiver operating characteristic analysis showed areas under the curve of CART, senior radiologists and junior radiologists respectively were 0.910±0.029, 0.827±0.038, 0.612±0.052. Difference between areas(DBF) between CART and junior radiologists was 0.297(P<0.01). DBF between CART and senior radiologists was 0.083 (P<0.05). DBF between senior and junior radiologists was 0.214 (P<0.01). CART showed a best diagnostic efficiency, followed by junior radiologists, and then senior radiologists. Conclusion: Our data mining techniques using CART prove a high accuracy in differentiating benign from malignant pulmonary nodules based on clinical variables and CT findings. It will be a potentially useful tool in further application of artificial intelligence in the imaging diagnosis. (authors)

  14. 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

  15. 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.

  16. 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

  17. 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

  18. Toward dialysis "a la carte".

    Science.gov (United States)

    Funck-Brentano, J L

    1987-12-01

    From the very beginning, the artificial kidney postponed the death of patients with end-stage renal failure. For years, owing to the performance of the machine, the patient was obliged to follow a severe diet in order to maintain good humoral and circulatory status. Now technological improvements allow "dialysis à la carte," whereby each individual achieves a better clinical status. The next step will be automation of the procedure to improve its security, mainly for dialysis performed at home.

  19. 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).

  20. Revisión de los Árboles de Clasificación y Regresión (CART

    Directory of Open Access Journals (Sweden)

    Juan Felipe Díaz Sepúlveda

    2011-07-01

    Full Text Available ResumenDependiendo del problema, el propósito básico de un estudio de clasificación puede ser producir una correcta clasificación o descubrir la estructura predictiva del problema. Si nuestro objetivo es lo último, entonces estamos tratando de entender qué variables o interacciones de variables describen el fenómeno, esto es, dar caracterizaciones simples de las condiciones que determinan cuándo un objeto está en una clase más que en otra. Los Árboles de Clasificación y Regresión, en inglés Classification and Regression Trees (CART, deben su desarrollo a L. Breiman, J. Friedman, R. Olshen y C. Stone, autores del libro del mismo nombre, publicado en 1984 [Breiman y otros, 1984]. El objetivo de este artículo es dar a conocer desde el punto de vista teórico en qué consiste esta técnica de clasificación.Palabras claves:Clasificador, partición, árbol de clasificación, árbol de regresión, nodo, hoja, impureza, validación cruzada.AbstractDepending on the problem, the basic purpose of a classification study may be to produce a correct classification or predictive discovering the structure of the problem If our goal is the latter, then we are trying to understand what variables or interactions of variables describing the phenomenon, that is, give simple characterizations of the conditions that determine when an object is In a class more than another. The Classification and Regression Trees, Classification and Regression English Trees (CART, owes its development to L Breiman, J. Friedman, R. Olshen and C Stone, who wrote the book of the same name, published in 1984 [Breiman et al, 1984]. The aim of this paper is to report from the theoretical point of view it is this classification technique.Key words:Sorter, partition, classification tree, regression tree, node, leaf, impurity, cross validation.

  1. Des cartes dans la classe…

    Directory of Open Access Journals (Sweden)

    R. Gimeno

    1990-09-01

    Full Text Available La majorité des enseignants qui veulent faire des cartes — et les faire réaliser aux élèves — pour répondre aux exigences des instructions officielles, doivent surmonter leur manque de compétences en cartographie et en didactique ainsi que les difficultés propres aux logiciels de cartographie encore peu performants. Ces compétences et la réflexion qui les accompagne sont pourtant accessibles aux enfants de l’école élémentaire…

  2. Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling

    Science.gov (United States)

    Galelli, S.; Castelletti, A.

    2013-07-01

    Combining randomization methods with ensemble prediction is emerging as an effective option to balance accuracy and computational efficiency in data-driven modelling. In this paper, we investigate the prediction capability of extremely randomized trees (Extra-Trees), in terms of accuracy, explanation ability and computational efficiency, in a streamflow modelling exercise. Extra-Trees are a totally randomized tree-based ensemble method that (i) alleviates the poor generalisation property and tendency to overfitting of traditional standalone decision trees (e.g. CART); (ii) is computationally efficient; and, (iii) allows to infer the relative importance of the input variables, which might help in the ex-post physical interpretation of the model. The Extra-Trees potential is analysed on two real-world case studies - Marina catchment (Singapore) and Canning River (Western Australia) - representing two different morphoclimatic contexts. The evaluation is performed against other tree-based methods (CART and M5) and parametric data-driven approaches (ANNs and multiple linear regression). Results show that Extra-Trees perform comparatively well to the best of the benchmarks (i.e. M5) in both the watersheds, while outperforming the other approaches in terms of computational requirement when adopted on large datasets. In addition, the ranking of the input variable provided can be given a physically meaningful interpretation.

  3. Rolling Friction on a Wheeled Laboratory Cart

    Science.gov (United States)

    Mungan, Carl E.

    2012-01-01

    A simple model is developed that predicts the coefficient of rolling friction for an undriven laboratory cart on a track that is approximately independent of the mass loaded onto the cart and of the angle of inclination of the track. The model includes both deformation of the wheels/track and frictional torque at the axles/bearings. The concept of…

  4. Shopping cart injuries, entrapment, and childhood fatality.

    Science.gov (United States)

    Jensen, Lisbeth; Charlwood, Cheryl; Byard, Roger W

    2008-09-01

    Shopping carts may be associated with a variety of injuries, particularly in toddlers and young children. These usually relate to falls from carts or to tip-overs. Injuries that are sustained include hematomas/contusions, abrasions, lacerations, fractures, and fingertip amputations. Fatal episodes are uncommon and are usually due to blunt craniocerebral trauma from falls. A case involving a 19-month-old girl is reported who became entrapped when she inserted her head through the side frame of a cart that had been removed from a supermarket and left at her home address. Death was caused by neck compression. Although rare, the potential for lethal entrapment during unsupervised play means that the presence of stray shopping carts at private residences and in public places, including playgrounds and parks, is of concern. Strategies, such as coin deposits, should be encouraged to assist in the return of such carts to supermarkets.

  5. 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…

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. Getting started with OpenCart module development

    CERN Document Server

    Nepali, Rupak

    2013-01-01

    Written as a step-by-step guide, Getting Started with OpenCart Module Development will teach you all you need to know about OpenCart, from custom extensions to module development.This book is for developers who want to develop OpenCart extensions and for those who want to learn more about the code workflow of OpenCart. Basic knowledge of OpenCart would be an added advantage.

  11. 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...

  12. 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.

  13. 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.

  14. 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

  15. tgp: An R Package for Bayesian Nonstationary, Semiparametric Nonlinear Regression and Design by Treed Gaussian Process Models

    Directory of Open Access Journals (Sweden)

    Robert B. Gramacy

    2007-06-01

    Full Text Available The tgp package for R is a tool for fully Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes with jumps to the limiting linear model. Special cases also implemented include Bayesian linear models, linear CART, stationary separable and isotropic Gaussian processes. In addition to inference and posterior prediction, the package supports the (sequential design of experiments under these models paired with several objective criteria. 1-d and 2-d plotting, with higher dimension projection and slice capabilities, and tree drawing functions (requiring maptree and combinat packages, are also provided for visualization of tgp objects.

  16. GLYCAN-DIRECTED CAR-T CELLS.

    Science.gov (United States)

    Steentoft, Catharina; Migliorini, Denis; King, Tiffany R; Mandel, Ulla; June, Carl H; Posey, Avery D

    2018-01-23

    Cancer immunotherapy is rapidly advancing in the treatment of a variety of hematopoietic cancers, including pediatric acute lymphoblastic leukemia and diffuse large B cell lymphoma, with chimeric antigen receptor (CAR)-T cells. CARs are genetically encoded artificial T cell receptors that combine the antigen specificity of an antibody with the machinery of T cell activation. However, implementation of CAR technology in the treatment of solid tumors has been progressing much slower. Solid tumors are characterized by a number of challenges that need to be overcome, including cellular heterogeneity, immunosuppressive tumor microenvironment (TME), and, in particular, few known cancer-specific targets. Post-translational modifications that differentially occur in malignant cells generate valid cell surface, cancer-specific targets for CAR-T cells. We previously demonstrated that CAR-T cells targeting an aberrant O-glycosylation of MUC1, a common cancer marker associated with changes in cell adhesion, tumor growth, and poor prognosis, could control malignant growth in mouse models. Here, we discuss the field of glycan-directed CAR-T cells and review the different classes of antibodies specific for glycan-targeting, including the generation of high affinity O-glycopeptide antibodies. Finally, we discuss historic and recently investigated glycan targets for CAR-T cells and provide our perspective on how targeting the tumor glycoproteome and/or glycome will improve CAR-T immunotherapy. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. A novel dendrochronological approach reveals drivers of carbon sequestration in tree species of riparian forests across spatiotemporal scales.

    Science.gov (United States)

    Rieger, Isaak; Kowarik, Ingo; Cherubini, Paolo; Cierjacks, Arne

    2017-01-01

    Aboveground carbon (C) sequestration in trees is important in global C dynamics, but reliable techniques for its modeling in highly productive and heterogeneous ecosystems are limited. We applied an extended dendrochronological approach to disentangle the functioning of drivers from the atmosphere (temperature, precipitation), the lithosphere (sedimentation rate), the hydrosphere (groundwater table, river water level fluctuation), the biosphere (tree characteristics), and the anthroposphere (dike construction). Carbon sequestration in aboveground biomass of riparian Quercus robur L. and Fraxinus excelsior L. was modeled (1) over time using boosted regression tree analysis (BRT) on cross-datable trees characterized by equal annual growth ring patterns and (2) across space using a subsequent classification and regression tree analysis (CART) on cross-datable and not cross-datable trees. While C sequestration of cross-datable Q. robur responded to precipitation and temperature, cross-datable F. excelsior also responded to a low Danube river water level. However, CART revealed that C sequestration over time is governed by tree height and parameters that vary over space (magnitude of fluctuation in the groundwater table, vertical distance to mean river water level, and longitudinal distance to upstream end of the study area). Thus, a uniform response to climatic drivers of aboveground C sequestration in Q. robur was only detectable in trees of an intermediate height class and in taller trees (>21.8m) on sites where the groundwater table fluctuated little (≤0.9m). The detection of climatic drivers and the river water level in F. excelsior depended on sites at lower altitudes above the mean river water level (≤2.7m) and along a less dynamic downstream section of the study area. Our approach indicates unexploited opportunities of understanding the interplay of different environmental drivers in aboveground C sequestration. Results may support species-specific and

  18. 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).

  19. 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

  20. Clinical trials of CAR-T cells in China

    Directory of Open Access Journals (Sweden)

    Bingshan Liu

    2017-10-01

    Full Text Available Abstract Novel immunotherapeutic agents targeting tumor-site microenvironment are revolutionizing cancer therapy. Chimeric antigen receptor (CAR-engineered T cells are widely studied for cancer immunotherapy. CD19-specific CAR-T cells, tisagenlecleucel, have been recently approved for clinical application. Ongoing clinical trials are testing CAR designs directed at novel targets involved in hematological and solid malignancies. In addition to trials of single-target CAR-T cells, simultaneous and sequential CAR-T cells are being studied for clinical applications. Multi-target CAR-engineered T cells are also entering clinical trials. T cell receptor-engineered CAR-T and universal CAR-T cells represent new frontiers in CAR-T cell development. In this study, we analyzed the characteristics of CAR constructs and registered clinical trials of CAR-T cells in China and provided a quick glimpse of the landscape of CAR-T studies in China.

  1. Clinical trials of CAR-T cells in China.

    Science.gov (United States)

    Liu, Bingshan; Song, Yongping; Liu, Delong

    2017-10-23

    Novel immunotherapeutic agents targeting tumor-site microenvironment are revolutionizing cancer therapy. Chimeric antigen receptor (CAR)-engineered T cells are widely studied for cancer immunotherapy. CD19-specific CAR-T cells, tisagenlecleucel, have been recently approved for clinical application. Ongoing clinical trials are testing CAR designs directed at novel targets involved in hematological and solid malignancies. In addition to trials of single-target CAR-T cells, simultaneous and sequential CAR-T cells are being studied for clinical applications. Multi-target CAR-engineered T cells are also entering clinical trials. T cell receptor-engineered CAR-T and universal CAR-T cells represent new frontiers in CAR-T cell development. In this study, we analyzed the characteristics of CAR constructs and registered clinical trials of CAR-T cells in China and provided a quick glimpse of the landscape of CAR-T studies in China.

  2. 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

  3. Preconception use of cART by HIV-positive pregnant women increases the risk of infants being born small for gestational age

    Science.gov (United States)

    Smit, Colette; Godfried, Mieke H.; Bakker, Rachel; Nellen, Jeannine F. J. B.; Jaddoe, Vincent W. V.; van Leeuwen, Elisabeth; Reiss, Peter; Steegers, Eric A. P.; van der Ende, Marchina E.

    2018-01-01

    Background The benefits of combination anti-retroviral therapy (cART) in HIV-positive pregnant women (improved maternal health and prevention of mother to child transmission [pMTCT]) currently outweigh the adverse effects due to cART. As the variety of cART increases, however, the question arises as to which type of cART is safest for pregnant women and women of childbearing age. We studied the effect of timing and exposure to different classes of cART on adverse birth outcomes in a large HIV cohort in the Netherlands. Materials and methods We included singleton HEU infants registered in the ATHENA cohort from 1997 to 2015. Multivariate logistic regression analysis for single and multiple pregnancies was used to evaluate predictors of small for gestational age (SGA, birth weight Women starting cART before conception had an increased risk of having a SGA infant compared to women starting cART after conception (OR 1.35, 95% CI 1.03−1.77, p = 0.03). The risk for SGA was highest in women who started a protease inhibitor-(PI) based regimen prior to pregnancy, compared with women who initiated PI-based cART during pregnancy. While the association of preterm delivery and preconception cART was significant in univariate analysis, on multivariate analysis only a non-significant trend was observed (OR 1.39, 95% CI 0.94−1.92, p = 0.06) in women who had started cART before compared to after conception. In multivariate analysis, the risk of low birth weight (OR 1.34, 95% CI 0.94−1.92, p = 0.11) was not significantly increased in women who had started cART prior to conception compared to after conception. Conclusion In our cohort of pregnant HIV-positive women, the use of cART prior to conception, most notably a PI-based regimen, was associated with intrauterine growth restriction resulting in SGA. Data showed a non-significant trend in the risk of PTD associated with preconception use of cART compared to its use after conception. More studies are needed with regard to the

  4. Assessing the HIV Care Continuum in Latin America: progress in clinical retention, cART use and viral suppression

    Science.gov (United States)

    Rebeiro, Peter F; Cesar, Carina; Shepherd, Bryan E; De Boni, Raquel B; Cortés, Claudia P; Rodriguez, Fernanda; Belaunzarán-Zamudio, Pablo; Pape, Jean W; Padgett, Denis; Hoces, Daniel; McGowan, Catherine C; Cahn, Pedro

    2016-01-01

    Introduction We assessed trends in HIV Care Continuum outcomes associated with delayed disease progression and reduced transmission within a large Latin American cohort over a decade: clinical retention, combination antiretroviral therapy (cART) use and viral suppression (VS). Methods Adults from Caribbean, Central and South America network for HIV epidemiology clinical cohorts in seven countries contributed data between 2003 and 2012. Retention was defined as two or more HIV care visits annually, >90 days apart. cART was defined as prescription of three or more antiretroviral agents annually. VS was defined as HIV-1 RNA <200 copies/mL at last measurement annually. cART and VS denominators were subjects with at least one visit annually. Multivariable modified Poisson regression was used to assess temporal trends and examine associations between age, sex, HIV transmission mode, cohort, calendar year and time in care. Results Among 18,799 individuals in retention analyses, 14,380 in cART analyses and 13,330 in VS analyses, differences existed between those meeting indicator definitions versus those not by most characteristics. Retention, cART and VS significantly improved from 2003 to 2012 (63 to 77%, 74 to 91% and 53 to 82%, respectively; p<0.05, each). Female sex (risk ratio (RR)=0.97 vs. males) and injection drug use as HIV transmission mode (RR=0.83 vs. male sexual contact with males (MSM)) were significantly associated with lower retention, but unrelated with cART or VS. MSM (RR=0.96) significantly decreased the probability of cART compared with heterosexual transmission. Conclusions HIV Care Continuum outcomes improved over time in Latin America, though disparities for vulnerable groups remain. Efforts must be made to increase retention, cART and VS, while engaging in additional research to sustain progress in these settings. PMID:27065108

  5. Hypothalamic CART is a new anorectic peptide regulated by leptin.

    Science.gov (United States)

    Kristensen, P; Judge, M E; Thim, L; Ribel, U; Christjansen, K N; Wulff, B S; Clausen, J T; Jensen, P B; Madsen, O D; Vrang, N; Larsen, P J; Hastrup, S

    1998-05-07

    The mammalian hypothalamus strongly influences ingestive behaviour through several different signalling molecules and receptor systems. Here we show that CART (cocaine- and amphetamine-regulated transcript), a brain-located peptide, is a satiety factor and is closely associated with the actions of two important regulators of food intake, leptin and neuropeptide Y. Food-deprived animals show a pronounced decrease in expression of CART messenger RNA in the arcuate nucleus. In animal models of obesity with disrupted leptin signalling, CART mRNA is almost absent from the arcuate nucleus. Peripheral administration of leptin to obese mice stimulates CART mRNA expression. When injected intracerebroventricularly into rats, recombinant CART peptide inhibits both normal and starvation-induced feeding, and completely blocks the feeding response induced by neuropeptide Y. An antiserum against CART increases feeding in normal rats, indicating that CART may be an endogenous inhibitor of food intake in normal animals.

  6. Establishing Decision Trees for Predicting Successful Postpyloric Nasoenteric Tube Placement in Critically Ill Patients.

    Science.gov (United States)

    Chen, Weisheng; Sun, Cheng; Wei, Ru; Zhang, Yanlin; Ye, Heng; Chi, Ruibin; Zhang, Yichen; Hu, Bei; Lv, Bo; Chen, Lifang; Zhang, Xiunong; Lan, Huilan; Chen, Chunbo

    2018-01-01

    Despite the use of prokinetic agents, the overall success rate for postpyloric placement via a self-propelled spiral nasoenteric tube is quite low. This retrospective study was conducted in the intensive care units of 11 university hospitals from 2006 to 2016 among adult patients who underwent self-propelled spiral nasoenteric tube insertion. Success was defined as postpyloric nasoenteric tube placement confirmed by abdominal x-ray scan 24 hours after tube insertion. Chi-square automatic interaction detection (CHAID), simple classification and regression trees (SimpleCart), and J48 methodologies were used to develop decision tree models, and multiple logistic regression (LR) methodology was used to develop an LR model for predicting successful postpyloric nasoenteric tube placement. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of these models. Successful postpyloric nasoenteric tube placement was confirmed in 427 of 939 patients enrolled. For predicting successful postpyloric nasoenteric tube placement, the performance of the 3 decision trees was similar in terms of the AUCs: 0.715 for the CHAID model, 0.682 for the SimpleCart model, and 0.671 for the J48 model. The AUC of the LR model was 0.729, which outperformed the J48 model. Both the CHAID and LR models achieved an acceptable discrimination for predicting successful postpyloric nasoenteric tube placement and were useful for intensivists in the setting of self-propelled spiral nasoenteric tube insertion. © 2016 American Society for Parenteral and Enteral Nutrition.

  7. [RS estimation of inventory parameters and carbon storage of moso bamboo forest based on synergistic use of object-based image analysis and decision tree].

    Science.gov (United States)

    Du, Hua Qiang; Sun, Xiao Yan; Han, Ning; Mao, Fang Jie

    2017-10-01

    By synergistically using the object-based image analysis (OBIA) and the classification and regression tree (CART) methods, the distribution information, the indexes (including diameter at breast, tree height, and crown closure), and the aboveground carbon storage (AGC) of moso bamboo forest in Shanchuan Town, Anji County, Zhejiang Province were investigated. The results showed that the moso bamboo forest could be accurately delineated by integrating the multi-scale ima ge segmentation in OBIA technique and CART, which connected the image objects at various scales, with a pretty good producer's accuracy of 89.1%. The investigation of indexes estimated by regression tree model that was constructed based on the features extracted from the image objects reached normal or better accuracy, in which the crown closure model archived the best estimating accuracy of 67.9%. The estimating accuracy of diameter at breast and tree height was relatively low, which was consistent with conclusion that estimating diameter at breast and tree height using optical remote sensing could not achieve satisfactory results. Estimation of AGC reached relatively high accuracy, and accuracy of the region of high value achieved above 80%.

  8. Comparison of single and boosted protease inhibitor versus nonnucleoside reverse transcriptase inhibitor-containing cART regimens in antiretroviral-naïve patients starting cART after January 1, 2000

    DEFF Research Database (Denmark)

    Mocroft, A; Horban, A; Clumeck, N

    2006-01-01

    increase) response in antiretroviral-naïve patients starting either a single protease inhibitor (PI; n = 183), a ritonavir-boosted PI regimen (n = 197), or a nonnucleoside reverse transcriptase inhibitor (NNRTI)-based cART regimen (n = 447) after January 1, 2000, and the odds of lack of virologic...... or immunologic response at 3 years after starting cART. METHOD: Cox proportional hazards models and logistic regression. RESULTS: After adjustment, compared to patients taking an NNRTI-regimen, patients taking a single-PI regimen were significantly less likely to achieve a viral load (VL)

  9. La carte scolaire et son assouplissement

    OpenAIRE

    Merle, Pierre

    2014-01-01

    Cet article a pour objet l'étude de la politique d’assouplissement de la carte scolaire mise en œuvre à partir de la rentrée scolaire 2007. Cette politique poursuit officiellement deux objectifs : apporter une plus grande liberté de choix de l’établissement aux parents ; favoriser la mixité sociale. L’étude de cette politique repose, dans un premier temps, sur l’analyse de la réalisation formelle des objectifs poursuivis (notamment la comparaison des anciens et nouveaux critères de dérogation...

  10. Substance use and adherence among people living with HIV/AIDS receiving cART in Latin America

    Science.gov (United States)

    De Boni, Raquel B.; Shepherd, Bryan E.; Grinsztejn, Beatriz; Cesar, Carina; Cortés, Claudia; Padgett, Denis; Gotuzzo, Eduardo; Belaunzarán-Zamudio, Pablo F.; Rebeiro, Peter F.; Duda, Stephany N.; McGowan, Catherine C.

    2016-01-01

    This cross-sectional study describes substance use prevalence and its association with cART adherence among 3343 individuals receiving care at HIV clinics in Argentina, Brazil, Chile, Honduras, Mexico, and Peru. A rapid screening tool evaluated self-reported 7-day recall of alcohol, marijuana, cocaine, heroin, and methamphetamine use, and missed cART doses. Overall, 29.3% individuals reported having ≥ 1 alcoholic drinks, 5.0% reported any illicit drug use and 17.0% reported missed cART doses. In the logistic regression model, compared to no substance use, alcohol use (adjusted odds ratio (AOR)=2.46, 95% confidence interval (CI): 1.99–3.05), illicit drug use (AOR=3.57, 95% CI: 2.02–6.30), and using both alcohol and illicit drugs (AOR=4.98, 95% CI: 3.19–7.79) were associated with missed cART doses. The associations between substance use and likelihood of missing cART doses point to the need of targeting alcohol and illicit drug use to improve adherence among people living with HIV in Latin America. PMID:27091028

  11. Preconception use of cART by HIV-positive pregnant women increases the risk of infants being born small for gestational age.

    Science.gov (United States)

    Snijdewind, Ingrid J M; Smit, Colette; Godfried, Mieke H; Bakker, Rachel; Nellen, Jeannine F J B; Jaddoe, Vincent W V; van Leeuwen, Elisabeth; Reiss, Peter; Steegers, Eric A P; van der Ende, Marchina E

    2018-01-01

    The benefits of combination anti-retroviral therapy (cART) in HIV-positive pregnant women (improved maternal health and prevention of mother to child transmission [pMTCT]) currently outweigh the adverse effects due to cART. As the variety of cART increases, however, the question arises as to which type of cART is safest for pregnant women and women of childbearing age. We studied the effect of timing and exposure to different classes of cART on adverse birth outcomes in a large HIV cohort in the Netherlands. We included singleton HEU infants registered in the ATHENA cohort from 1997 to 2015. Multivariate logistic regression analysis for single and multiple pregnancies was used to evaluate predictors of small for gestational age (SGA, birth weight pregnant HIV-positive women, the use of cART prior to conception, most notably a PI-based regimen, was associated with intrauterine growth restriction resulting in SGA. Data showed a non-significant trend in the risk of PTD associated with preconception use of cART compared to its use after conception. More studies are needed with regard to the mechanisms taking place in the placenta during fetal growth in pregnant HIV-positive women using cART. It will only be with this knowledge that we can begin to understand the potential impact of HIV and cART on the fetus, in order to be able to determine the optimal individualised drug regimen for HIV-infected women of childbearing age.

  12. Prediksi Kerawanan Wilayah Terhadap Tindak Pencurian Sepeda Motor Menggunakan Metode (SARIMA Dan CART

    Directory of Open Access Journals (Sweden)

    Pradita Eko Prasetyo Utomo

    2017-07-01

    Full Text Available Motor vehicle theft is a crime that is most common in Indonesia. Growth of vehicle motorcycle significant in each year accompanied by the increasing theft of motorcycles in each year, we need a system that is able to forecast the development and the theft of the motorcycle. This research proposes the development of forecasting models vulnerability criminal offense of theft of motorcycles with ARIMA forecasting method. This method not only forecast from variable of theft but also residents, vehicles and unemployment. The study also determined the classification level of vulnerability to the crime of theft of a motorcycle using a method based on the Decision Tree CART ARIMA forecasting method. Forecasting time series data with ARIMA method performed by each of the variables to produce the best ARIMA forecasting model which varies based on the data pattern of each of those variables. The results of classification by CART method to get the value of accuracy of 92% for the city of Yogyakarta and 85% for DIY. Based on the above, the results of ARIMA forecasting and classification CART can be used in determining the level of vulnerability to the crime of theft of motorcycles.

  13. Resonance treatment methodology in DeCART

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kang Seog; Joo, Han Gyu; Lee, Chung Chan; Chang, Moon Hee

    2003-12-01

    The typical nuclear design procedure consists of two steps which are the transport lattice calculation for the fuel assembly and the nodal diffusion calculation for the reactor core. DeCART (Deterministic Core Analysis based on Ray Tracing) code has been developed to perform the 3-dimensional whole-core transport calculation removing some of the approximations in the 2-step procedure. This code employs the synthesis of 1- and 2-dimensional characteristics methods in the framework of the 3-dimensional CMFD (Coarse Mesh Finite Difference) formulation. The subgroup method is used for the resonance treatment. HELIOS library is used for the multi-group neutron cross section and the resonance data without any modification. This report includes the methodology of the resonance treatment in DeCART. And this report also includes the Monte Carlo resonance treatment under development for the generation of the resonance integral table and the subgroup data. The interpolation method of the equivalence cross section is reviewed for the efficient resonance transport calculation with thermal-hydraulic feedback, and the new method to consider the temperature distribution explicitly in the subgroup method is also introduced.

  14. Professor: A motorized field-based phenotyping cart

    Science.gov (United States)

    An easy-to-customize, low-cost, low disturbance, motorized proximal sensing cart for field-based high-throughput phenotyping is described. General dimensions, motor specifications, and a remote operation application are given. The cart, named Professor, supports mounting multiple proximal sensors an...

  15. The Retarding Force on a Fan-Cart Reversing Direction

    Science.gov (United States)

    Aurora, Tarlok S.; Brunner, Bernard J.

    2011-01-01

    In introductory physics, students learn that an object tossed upward has a constant downward acceleration while going up, at the highest point and while falling down. To demonstrate this concept, a self-propelled fan cart system is used on a frictionless track. A quick push is given to the fan cart and it is allowed to move away on a track under…

  16. Shoulder joint loading and posture during medicine cart pushing task.

    Science.gov (United States)

    Xu, Xu; Lin, Jia-Hua; Boyer, Jon

    2013-01-01

    Excessive physical loads and awkward shoulder postures during pushing and pulling are risk factors for shoulder pain. Pushing a medicine cart is a major component of a work shift for nurses and medical assistants in hospitals and other health care facilities. A laboratory experiment was conducted to examine the effects of common factors (e.g., lane congestion, cart load stability, floor surface friction) on shoulder joint moment and shoulder elevation angle of participants during cart pushing. Participants pushed a medicine cart on straight tracks and turning around right-angle corners. Peak shoulder joint moments reached 25.1 Nm, 20.3 Nm, and 26.8 Nm for initial, transition, and turning phases of the pushing tasks, indicating that shoulder joint loading while pushing a medical cart is comparable to levels previously reported from heavy manual activities encountered in industry (e.g., garbage collection). Also, except for user experience, all other main study factors, including congestion level, cart load stability, location of transition strip, shoulder tendency, surface friction, and handedness, significantly influenced shoulder joint moment and shoulder elevation angle. The findings provide a better understanding of shoulder exposures associated with medicine cart operations and may be helpful in designing and optimizing the physical environment where medicine carts are used.

  17. CART in the Regulation of Appetite and Energy Homeostasis

    Directory of Open Access Journals (Sweden)

    Jackie eLau

    2014-10-01

    Full Text Available The cocaine- and amphetamine-regulated transcript (CART has been the subject of significant interest for over a decade. Work to decipher the detailed mechanism of CART function has been hampered by the lack of specific pharmacological tools like antagonists and the absence of a specific CART receptor(s. However, extensive research has been devoted to elucidate the role of the CART peptide and it is now evident that CART is a key neurotransmitter and hormone involved in the regulation of diverse biological processes, including food intake, maintenance of body weight, reward and addiction, stress response, psychostimulant effects and endocrine functions1,2. In this review, we focus on knowledge gained on CART’s role in controlling appetite and energy homeostasis, and also address certain species differences between rodents and humans.

  18. Establishing guidelines for CAR-T cells: challenges and considerations.

    Science.gov (United States)

    Wang, Wei; Qin, Di-Yuan; Zhang, Bing-Lan; Wei, Wei; Wang, Yong-Sheng; Wei, Yu-Quan

    2016-04-01

    T cells, genetically modified by chimeric antigen receptors (CAR-T), are endowed with specificity to a desired antigen and are cytotoxic to cells expressing the targeted antigen. CAR-T-based cancer immunotherapy is a promising therapy for curing hematological malignancy, such as acute lymphoid leukemia, and is promising for extending their efficacy to defeat solid tumors. To date, dozens of different CAR-T cells have been evaluated in clinical trials to treat tumors; this necessitates the establishment of guidelines for the production and application of CAR-T cells. However, it is challenging to standardize CAR-T cancer therapy because it involves a combination of gene therapy and cell therapy. In this review, we compare the existing guidelines for CAR-T cells and discuss the challenges and considerations for establishing guidance for CAR-T-based cancer immunotherapy.

  19. Involvement of CART in estradiol-induced anorexia.

    Science.gov (United States)

    Dandekar, Manoj P; Nakhate, Kartik T; Kokare, Dadasaheb M; Subhedar, Nishikant K

    2012-01-18

    Since estradiol exercises inhibitory effect on food intake, we wanted to find out if this influence of estradiol is mediated by cocaine- and amphetamine-regulated transcript peptide (CART), a well established anorectic agent in the brain. Ovariectomized (OVX) rats, replaced with estradiol to produce estrous-phase like conditions, showed a significant decrease in food intake as compared with that in OVX controls. Intracerebroventricular (icv) administration of CART (0.5-1 μg/rat) to OVX rats, resulted in a dose-dependent reduction in the food intake. The lower dose (0.25 μg) had no effect, and was considered subeffective. In estradiol replaced OVX rats, CART at subeffective dose, further reduced food intake. However, CART failed to reduce food intake in estradiol replaced OVX rats pretreated with anti-estrogenic agent tamoxifen (3 mg/kg, subcutaneous). Administration of CART antibody (1:500 dilution/rat, i.c.v.) significantly attenuated estradiol-induced anorexia in the OVX rats. While estradiol replacement significantly increased CART-immunoreactivity in the cells/fibers of paraventricular nucleus (PVN) of OVX rats, fibers in the anteroventral periventricular nucleus (AVPV), and cells/fibers in the arcuate nucleus (ARC) showed considerable reduction. These changes were attenuated following concurrent injection of tamoxifen to the estradiol replaced OVX rats. However, CART-immunoreactive cells/fibers in the periventricular area did not respond to any of the treatments. We suggest that estradiol treatment might influence the hypothalamic CART system in a site specific manner. While increased CART activity in the PVN might produce anorexia, reduction of CART in ARC and AVPV might represent a compensatory homeostatic response. Copyright © 2011 Elsevier Inc. All rights reserved.

  20. 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...

  1. 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.

  2. La carte des 36 000 communes

    Directory of Open Access Journals (Sweden)

    Aliette DELAMARRE

    1989-12-01

    Full Text Available La carte généralisée du maillage communal français, obtenue à partir d'un sondage spatial au quart, met en évidence des modèles régionaux caractérisés par des mailles inégalement fines. Cette division du territoire, héritée de la trame paroissiale, a été mise en mémoire par la création, en 1789, de l'institution communale. Seuls les travaux de géographie historique permettront de découvrir les mécanismes de sa mise en place à dater des Xe-XIe, voire des VIe et VIIe siècles.

  3. Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

    Science.gov (United States)

    Sankari, E Siva; Manimegalai, D

    2017-12-21

    Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Classication of Status of the Region on Java Island using C4.5, CHAID, and CART Methods

    Science.gov (United States)

    Syaraswati, R. A.; Slamet, I.; Winarno, B.

    2017-06-01

    The indicator of region economic success can be measured by economic growth, presented by value of Gross Regional Domestic Product (GRDP). Java island has the biggest GDP contribution toward the Indonesian government, but not all of the region gives equality contribution. The C4.5, CHAID, and CART methods can be used for classifying the status of the region with nonparametric approach. The C4.5 and CHAID methods are non-binary decision tree, meanwhile the CART methods is binary decision tree. The purposes of this paper are to know how the classification and to determine the factors that influence on classification of the region. The dependent variable is status of the region which is divided into four categories based on Klassen typology. The result shows factors that have the biggest contribution on classification of status of the region on Java island based on C4.5 method are economic growth rate, electricity, gas, and water sector, and area. The factors that have the biggest contribution based on CHAID method are growth rate, manufacturing sector, and electricity, gas, and water sector, while based on CART method are growth rate, manufacturing sector, and electricity, gas, and water sector.

  5. CAR-T Cell Therapies From the Transfusion Medicine Perspective.

    Science.gov (United States)

    Fesnak, Andrew; Lin, ChieYu; Siegel, Don L; Maus, Marcela V

    2016-07-01

    The use of chimeric antigen receptor (CAR)-T cell therapy for the treatment of hematologic malignancies has generated significant excitement over the last several years. From a transfusion medicine perspective, the implementation of CAR-T therapy as a potential mainstay treatment for not only hematologic but also solid-organ malignancies represents a significant opportunity for growth and expansion. In this review, we will describe the rationale for the development of genetically redirected T cells as a cancer therapeutic, the different elements that are required to engineer these cells, as well as an overview of the process by which patient cells are harvested and processed to create and subsequently validate CAR-T cells. Finally, we will briefly describe some of the toxicities and clinical efficacy of CAR-T cells in the setting of patients with advanced malignancy. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Ejection of a rear facing, golf cart passenger.

    Science.gov (United States)

    Schau, Kyle; Masory, Oren

    2013-10-01

    The following report details the findings of a series of experiments and simulations performed on a commercially available, shuttle style golf cart during several maneuvers involving rapid accelerations of the vehicle. It is determined that the current set of passive restraints on these types of golf carts are not adequate in preventing ejection of a rear facing passenger during rapid accelerations in the forward and lateral directions. Experimental data and simulations show that a hip restraint must be a minimum of 13 in. above the seat in order to secure a rear facing passenger during sharp turns, compared to the current restraint height of 5 in. Furthermore, it is determined that a restraint directly in front of the rear facing passenger is necessary to prevent ejection. In addressing these issues, golf cart manufacturers could greatly reduce the likelihood of injury due to ejection of a rear facing, golf cart passenger. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Modelling modulus of elasticity of Pinus pinaster Ait. in northwestern Spain with standing tree acoustic measurements, tree, stand and site variables

    Directory of Open Access Journals (Sweden)

    Esther Merlo

    2014-04-01

    Full Text Available Aim of study: Modelling the structural quality of Pinus pinaster Ait. wood on the basis of measurements made on standing trees is essential because of the importance of the species in the Galician forestry and timber industries and the good mechanical properties of its wood. In this study, we investigated how timber stiffness is affected by tree and stand properties, climatic and edaphic characteristics and competition. Area of study: The study was performed in Galicia, north-western Spain.Material and methods: Ten pure and even-aged P. pinaster stands were selected and tree and stand variables and the stress wave velocity of 410 standing trees were measured. A sub-sample of 73 trees, representing the variability in acoustic velocity, were felled and sawed into structural timber pieces (224 which were subjected to a bending test to determine the modulus of elasticity (MOE. Main results: Linear models including wood properties explained more than 97%, 73% and 60% of the observed MOE variability at site, tree and board level, respectively, with acoustic velocity and wood density as the main regressors. Other linear models, which did not include wood density, explained more than 88%, 69% and 55% of the observed MOE variability at site, tree and board level, respectively, with acoustic velocity as the main regressor. Moreover, a classification tree for estimating the visual grade according to standard UNE 56544:2011 was developed. Research highlights: The results have demonstrated the usefulness of acoustic velocity for predicting MOE in standing trees. The use of the fitted equations together with existing dynamic growth models will enable preliminary assessment of timber stiffness in relation to different silvicultural alternatives used with this species.Keywords: stress wave velocity, modulus of elasticity, site index, competition index, stepwise regression, CART.

  8. Clinical trials of CAR-T cells in China

    OpenAIRE

    Bingshan Liu; Yongping Song; Delong Liu

    2017-01-01

    Abstract Novel immunotherapeutic agents targeting tumor-site microenvironment are revolutionizing cancer therapy. Chimeric antigen receptor (CAR)-engineered T cells are widely studied for cancer immunotherapy. CD19-specific CAR-T cells, tisagenlecleucel, have been recently approved for clinical application. Ongoing clinical trials are testing CAR designs directed at novel targets involved in hematological and solid malignancies. In addition to trials of single-target CAR-T cells, simultaneous...

  9. La Carte de Localisation Probable des Avalanches (CPLA

    Directory of Open Access Journals (Sweden)

    Gilles BORREL

    1994-12-01

    Full Text Available La Carte de Localisation Probable des Avalanches (CPLA indique l’enveloppe des limites extrêmes connues atteintes par les avalanches, ainsi que les travaux de protection associés. Il s’agit d’un document informatif et non d’une carte de risque. Depuis 1990, les données thématiques sont numérisées.

  10. Modeling flash floods in ungauged mountain catchments of China: A decision tree learning approach for parameter regionalization

    Science.gov (United States)

    Ragettli, S.; Zhou, J.; Wang, H.; Liu, C.; Guo, L.

    2017-12-01

    Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. One of the main challenges of setting up such a system is finding appropriate model parameter values for ungauged catchments. Previous studies have shown that the transfer of parameter sets from hydrologically similar gauged catchments is one of the best performing regionalization methods. However, a remaining key issue is the identification of suitable descriptors of similarity. In this study, we use decision tree learning to explore parameter set transferability in the full space of catchment descriptors. For this purpose, a semi-distributed rainfall-runoff model is set up for 35 catchments in ten Chinese provinces. Hourly runoff data from in total 858 storm events are used to calibrate the model and to evaluate the performance of parameter set transfers between catchments. We then present a novel technique that uses the splitting rules of classification and regression trees (CART) for finding suitable donor catchments for ungauged target catchments. The ability of the model to detect flood events in assumed ungauged catchments is evaluated in series of leave-one-out tests. We show that CART analysis increases the probability of detection of 10-year flood events in comparison to a conventional measure of physiographic-climatic similarity by up to 20%. Decision tree learning can outperform other regionalization approaches because it generates rules that optimally consider spatial proximity and physical similarity. Spatial proximity can be used as a selection criteria but is skipped in the case where no similar gauged catchments are in the vicinity. We conclude that the CART regionalization concept is particularly suitable for implementation in sparsely gauged and topographically complex environments where a proximity

  11. Genetic Regulation of Hypothalamic Cocaine and Amphetamine-Regulated Transcript (CART) in BxD Inbred Mice

    Science.gov (United States)

    Hawks, Brian W.; Li, Wei; Garlow, Steven J.

    2009-01-01

    Cocaine-Amphetamine Regulated Transcript (CART) peptides are implicated in a wide range of behaviors including in the reinforcing properties of psychostimulants, feeding and energy balance and stress and anxiety responses. We conducted a complex trait analysis to examine natural variation in the regulation of CART transcript abundance (CARTta) in the hypothalamus. CART transcript abundance was measured in total hypothalamic RNA from 26 BxD recombinant inbred (RI) mouse strains and in the C57BL/6 (B6) and DBA/2J (D2) progenitor strains. The strain distribution pattern for CARTta was continuous across the RI panel, which is consistent with this being a quantitative trait. Marker regression and interval mapping revealed significant quantitative trait loci (QTL) on mouse chromosome 4 (around 58.2cM) and chromosome 11 (between 20–36cM) that influence CARTta and account for 31% of the between strain variance in this phenotype. There are numerous candidate genes and QTL in these chromosomal regions that may indicate shared genetic regulation between CART expression and other neurobiological processes referable to known actions of this neuropeptide. PMID:18199428

  12. Preconception use of cART by HIV-positive pregnant women increases the risk of infants being born small for gestational age.

    Directory of Open Access Journals (Sweden)

    Ingrid J M Snijdewind

    Full Text Available The benefits of combination anti-retroviral therapy (cART in HIV-positive pregnant women (improved maternal health and prevention of mother to child transmission [pMTCT] currently outweigh the adverse effects due to cART. As the variety of cART increases, however, the question arises as to which type of cART is safest for pregnant women and women of childbearing age. We studied the effect of timing and exposure to different classes of cART on adverse birth outcomes in a large HIV cohort in the Netherlands.We included singleton HEU infants registered in the ATHENA cohort from 1997 to 2015. Multivariate logistic regression analysis for single and multiple pregnancies was used to evaluate predictors of small for gestational age (SGA, birth weight <10th percentile for gestational age, low birth weight and preterm delivery.A total of 1392 children born to 1022 mothers were included. Of these, 331 (23.8% children were SGA. Women starting cART before conception had an increased risk of having a SGA infant compared to women starting cART after conception (OR 1.35, 95% CI 1.03-1.77, p = 0.03. The risk for SGA was highest in women who started a protease inhibitor-(PI based regimen prior to pregnancy, compared with women who initiated PI-based cART during pregnancy. While the association of preterm delivery and preconception cART was significant in univariate analysis, on multivariate analysis only a non-significant trend was observed (OR 1.39, 95% CI 0.94-1.92, p = 0.06 in women who had started cART before compared to after conception. In multivariate analysis, the risk of low birth weight (OR 1.34, 95% CI 0.94-1.92, p = 0.11 was not significantly increased in women who had started cART prior to conception compared to after conception.In our cohort of pregnant HIV-positive women, the use of cART prior to conception, most notably a PI-based regimen, was associated with intrauterine growth restriction resulting in SGA. Data showed a non-significant trend in

  13. Prediction of strontium bromide laser efficiency using cluster and decision tree analysis

    Directory of Open Access Journals (Sweden)

    Iliev Iliycho

    2018-01-01

    Full Text Available Subject of investigation is a new high-powered strontium bromide (SrBr2 vapor laser emitting in multiline region of wavelengths. The laser is an alternative to the atom strontium lasers and electron free lasers, especially at the line 6.45 μm which line is used in surgery for medical processing of biological tissues and bones with minimal damage. In this paper the experimental data from measurements of operational and output characteristics of the laser are statistically processed by means of cluster analysis and tree-based regression techniques. The aim is to extract the more important relationships and dependences from the available data which influence the increase of the overall laser efficiency. There are constructed and analyzed a set of cluster models. It is shown by using different cluster methods that the seven investigated operational characteristics (laser tube diameter, length, supplied electrical power, and others and laser efficiency are combined in 2 clusters. By the built regression tree models using Classification and Regression Trees (CART technique there are obtained dependences to predict the values of efficiency, and especially the maximum efficiency with over 95% accuracy.

  14. 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...

  15. Parallelization characteristics of the DeCART code

    International Nuclear Information System (INIS)

    Cho, J. Y.; Joo, H. G.; Kim, H. Y.; Lee, C. C.; Chang, M. H.; Zee, S. Q.

    2003-12-01

    This report is to describe the parallelization characteristics of the DeCART code and also examine its parallel performance. Parallel computing algorithms are implemented to DeCART to reduce the tremendous computational burden and memory requirement involved in the three-dimensional whole core transport calculation. In the parallelization of the DeCART code, the axial domain decomposition is first realized by using MPI (Message Passing Interface), and then the azimuthal angle domain decomposition by using either MPI or OpenMP. When using the MPI for both the axial and the angle domain decomposition, the concept of MPI grouping is employed for convenient communication in each communication world. For the parallel computation, most of all the computing modules except for the thermal hydraulic module are parallelized. These parallelized computing modules include the MOC ray tracing, CMFD, NEM, region-wise cross section preparation and cell homogenization modules. For the distributed allocation, most of all the MOC and CMFD/NEM variables are allocated only for the assigned planes, which reduces the required memory by a ratio of the number of the assigned planes to the number of all planes. The parallel performance of the DeCART code is evaluated by solving two problems, a rodded variation of the C5G7 MOX three-dimensional benchmark problem and a simplified three-dimensional SMART PWR core problem. In the aspect of parallel performance, the DeCART code shows a good speedup of about 40.1 and 22.4 in the ray tracing module and about 37.3 and 20.2 in the total computing time when using 48 CPUs on the IBM Regatta and 24 CPUs on the LINUX cluster, respectively. In the comparison between the MPI and OpenMP, OpenMP shows a somewhat better performance than MPI. Therefore, it is concluded that the first priority in the parallel computation of the DeCART code is in the axial domain decomposition by using MPI, and then in the angular domain using OpenMP, and finally the angular

  16. Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

    Science.gov (United States)

    Pashaei, Elnaz; Ozen, Mustafa; Aydin, Nizamettin

    2015-08-01

    Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classifier by applying Boosted C5.0 decision tree as the fitness function. To evaluate the effectiveness of our proposed method, it is implemented on 1 microarray dataset and 5 different medical data sets obtained from UCI machine learning databases. Moreover, the results of PSO + Boosted C5.0 implementation are compared to eight well-known benchmark classification methods (PSO+C4.5, support vector machine under the kernel of Radial Basis Function, Classification And Regression Tree (CART), C4.5 decision tree, C5.0 decision tree, Boosted C5.0 decision tree, Naive Bayes and Weighted K-Nearest neighbor). Repeated five-fold cross-validation method was used to justify the performance of classifiers. Experimental results show that our proposed method not only improve the performance of PSO+C4.5 but also obtains higher classification accuracy compared to the other classification methods.

  17. CAR-T therapy for leukemia: progress and challenges.

    Science.gov (United States)

    Wang, Xin; Xiao, Qing; Wang, Zhe; Feng, Wen-Li

    2017-04-01

    Despite the rapid development of therapeutic strategies, leukemia remains a type of difficult-to-treat hematopoietic malignancy that necessitates introduction of more effective treatment options to improve life expectancy and quality of patients. Genetic engineering in adoptively transferred T cells to express antigen-specific chimeric antigen receptors (CARs) has proved highly powerful and efficacious in inducing sustained responses in patients with refractory malignancies, as exemplified by the success of CD19-targeting CAR-T treatment in patients with relapsed acute lymphoblastic leukemia. Recent strategies, including manipulating intracellular activating domains and transducing viral vectors, have resulted in better designed and optimized CAR-T cells. This is further facilitated by the rapid identification of an accumulating number of potential leukemic antigens that may serve as therapeutic targets for CAR-T cells. This review will provide a comprehensive background and scrutinize recent important breakthrough studies on anti-leukemia CAR-T cells, with focus on recently identified antigens for CAR-T therapy design and approaches to overcome critical challenges. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Implementation of Generalized Adjoint Equation Solver for DeCART

    International Nuclear Information System (INIS)

    Han, Tae Young; Cho, Jin Young; Lee, Hyun Chul; Noh, Jae Man

    2013-01-01

    In this paper, the generalized adjoint solver based on the generalized perturbation theory is implemented on DeCART and the verification calculations were carried out. As the results, the adjoint flux for the general response coincides with the reference solution and it is expected that the solver could produce the parameters for the sensitivity and uncertainty analysis. Recently, MUSAD (Modules of Uncertainty and Sensitivity Analysis for DeCART) was developed for the uncertainty analysis of PMR200 core and the fundamental adjoint solver was implemented into DeCART. However, the application of the code was limited to the uncertainty to the multiplication factor, k eff , because it was based on the classical perturbation theory. For the uncertainty analysis to the general response as like the power density, it is necessary to develop the analysis module based on the generalized perturbation theory and it needs the generalized adjoint solutions from DeCART. In this paper, the generalized adjoint solver is implemented on DeCART and the calculation results are compared with the results by TSUNAMI of SCALE 6.1

  19. Simulation and Test of a Fuel Cell Hybrid Golf Cart

    Directory of Open Access Journals (Sweden)

    Jingming Liang

    2014-01-01

    Full Text Available This paper establishes the simulation model of fuel cell hybrid golf cart (FCHGC, which applies the non-GUI mode of the Advanced Vehicle Simulator (ADVISOR and the genetic algorithm (GA to optimize it. Simulation of the objective function is composed of fuel consumption and vehicle dynamic performance; the variables are the fuel cell stack power sizes and the battery numbers. By means of simulation, the optimal parameters of vehicle power unit, fuel cell stack, and battery pack are worked out. On this basis, GUI mode of ADVISOR is used to select the rated power of vehicle motor. In line with simulation parameters, an electrical golf cart is refitted by adding a 2 kW hydrogen air proton exchange membrane fuel cell (PEMFC stack system and test the FCHGC. The result shows that the simulation data is effective but it needs improving compared with that of the real cart test.

  20. New development in CAR-T cell therapy.

    Science.gov (United States)

    Wang, Zhenguang; Wu, Zhiqiang; Liu, Yang; Han, Weidong

    2017-02-21

    Chimeric antigen receptor (CAR)-engineered T cells (CAR-T cells) have yielded unprecedented efficacy in B cell malignancies, most remarkably in anti-CD19 CAR-T cells for B cell acute lymphoblastic leukemia (B-ALL) with up to a 90% complete remission rate. However, tumor antigen escape has emerged as a main challenge for the long-term disease control of this promising immunotherapy in B cell malignancies. In addition, this success has encountered significant hurdles in translation to solid tumors, and the safety of the on-target/off-tumor recognition of normal tissues is one of the main reasons. In this mini-review, we characterize some of the mechanisms for antigen loss relapse and new strategies to address this issue. In addition, we discuss some novel CAR designs that are being considered to enhance the safety of CAR-T cell therapy in solid tumors.

  1. Improving Odometric Accuracy for an Autonomous Electric Cart

    Directory of Open Access Journals (Sweden)

    Jonay Toledo

    2018-01-01

    Full Text Available In this paper, a study of the odometric system for the autonomous cart Verdino, which is an electric vehicle based on a golf cart, is presented. A mathematical model of the odometric system is derived from cart movement equations, and is used to compute the vehicle position and orientation. The inputs of the system are the odometry encoders, and the model uses the wheels diameter and distance between wheels as parameters. With this model, a least square minimization is made in order to get the nominal best parameters. This model is updated, including a real time wheel diameter measurement improving the accuracy of the results. A neural network model is used in order to learn the odometric model from data. Tests are made using this neural network in several configurations and the results are compared to the mathematical model, showing that the neural network can outperform the first proposed model.

  2. Improving Odometric Accuracy for an Autonomous Electric Cart.

    Science.gov (United States)

    Toledo, Jonay; Piñeiro, Jose D; Arnay, Rafael; Acosta, Daniel; Acosta, Leopoldo

    2018-01-12

    In this paper, a study of the odometric system for the autonomous cart Verdino, which is an electric vehicle based on a golf cart, is presented. A mathematical model of the odometric system is derived from cart movement equations, and is used to compute the vehicle position and orientation. The inputs of the system are the odometry encoders, and the model uses the wheels diameter and distance between wheels as parameters. With this model, a least square minimization is made in order to get the nominal best parameters. This model is updated, including a real time wheel diameter measurement improving the accuracy of the results. A neural network model is used in order to learn the odometric model from data. Tests are made using this neural network in several configurations and the results are compared to the mathematical model, showing that the neural network can outperform the first proposed model.

  3. New development in CAR-T cell therapy

    Directory of Open Access Journals (Sweden)

    Zhenguang Wang

    2017-02-01

    Full Text Available Abstract Chimeric antigen receptor (CAR-engineered T cells (CAR-T cells have yielded unprecedented efficacy in B cell malignancies, most remarkably in anti-CD19 CAR-T cells for B cell acute lymphoblastic leukemia (B-ALL with up to a 90% complete remission rate. However, tumor antigen escape has emerged as a main challenge for the long-term disease control of this promising immunotherapy in B cell malignancies. In addition, this success has encountered significant hurdles in translation to solid tumors, and the safety of the on-target/off-tumor recognition of normal tissues is one of the main reasons. In this mini-review, we characterize some of the mechanisms for antigen loss relapse and new strategies to address this issue. In addition, we discuss some novel CAR designs that are being considered to enhance the safety of CAR-T cell therapy in solid tumors.

  4. An rf communications system for the West Valley transfer cart

    International Nuclear Information System (INIS)

    Crutcher, R.I.; Moore, M.R.

    1993-01-01

    A prototype radio frequency communications system for digital data was designed and built by Oak Ridge National Laboratory for use in controlling the vitrification facility transfer cart at the West Valley Nuclear Services facility in New York. The communications system provides bidirectional wireless data transfer between the operator control station and the material transfer cart. The system was designed to operate in radiation fields of 10 4 R/h while withstanding a total integrated dose of 10 7 R of gamma radiation. Implementation of antenna spatial diversity, automatic gain control, and spectral processing improves operation in the reflective environment of the metal-lined reprocessing cells

  5. Vermeer et les cartes de géographie.

    Directory of Open Access Journals (Sweden)

    Jean MARTINON

    1987-09-01

    Full Text Available De nombreux tableaux de Vermeer sont «tapissés» de cartes de géographie. Objets scientifiques, elles témoignent de l'importance des découvertes au XVIIe siècle en Europe et de l'ouverture des Pays-Bas sur le monde. Objets de décoration, les cartes tendent à se confondre avec des représentations paysagères. Objets romanesques, elles introduisent le lointain et le rêve dans les intérieurs confinés de la bourgeoisie d'Amsterdam.

  6. Which countries pay more or less for their long term debt? A CART approach || ¿Qué países pagan más o menos por su deuda a largo plazo? Una aproximación a través de la metodología CART

    Directory of Open Access Journals (Sweden)

    González-Fernández, Marcos

    2016-06-01

    Full Text Available The objective of this paper is to classify a group of EMU countries according to the main determinants of long-term sovereign bond yields. We apply the Classification and Regression Tree method (CART. According to the findings, countries with lower inflation, a lower debt to GDP ratio, a lower average income tax rate, higher public debt maturity and higher IPI growth are placed in classification groups that have lower bond yields. These results confirm the hypothesis that countries with better macroeconomic and fiscal indicators have lower sovereign bond yields.|| El objetivo de este artículo es clasificar un grupo de países de la UME teniendo en cuenta los principales determinantes de los tipos a largo plazo de la deuda soberana. Se aplica la metodología basada en árboles de decisión. Según los resultados, los grupos de países que tienen menor inflación, deuda pública, tipo impositivo medio y mayor vencimiento de la deuda pública y crecimiento económico pagan menos por su deuda soberana a largo plazo. Se confirma la hipótesis de que los países que tienen los mejores indicadores macroeconómicos y fiscales son los que presentan menores costes en su deuda soberana.

  7. CART neurons in the arcuate nucleus and lateral hypothalamic area exert differential controls on energy homeostasis

    Directory of Open Access Journals (Sweden)

    Jackie Lau

    2018-01-01

    Full Text Available Objective: The cocaine- and amphetamine-regulated transcript (CART codes for a pivotal neuropeptide important in the control of appetite and energy homeostasis. However, limited understanding exists for the defined effector sites underlying CART function, as discrepant effects of central CART administration have been reported. Methods: By combining Cart-cre knock-in mice with a Cart adeno-associated viral vector designed using the flip-excision switch (AAV-FLEX technology, specific reintroduction or overexpression of CART selectively in CART neurons in the arcuate nucleus (Arc and lateral hypothalamic area (LHA, respectively, was achieved. The effects on energy homeostasis control were investigated. Results: Here we show that CART neuron-specific reintroduction of CART into the Arc and LHA leads to distinct effects on energy homeostasis control. Specifically, CART reintroduction into the Arc of otherwise CART-deficient Cartcre/cre mice markedly decreased fat mass and body weight, whereas CART reintroduction into the LHA caused significant fat mass gain and lean mass loss, but overall unaltered body weight. The reduced adiposity in ArcCART;Cartcre/cre mice was associated with an increase in both energy expenditure and physical activity, along with significantly decreased Npy mRNA levels in the Arc but with no change in food consumption. Distinctively, the elevated fat mass in LHACART;Cartcre/cre mice was accompanied by diminished insulin responsiveness and glucose tolerance, greater spontaneous food intake, and reduced energy expenditure, which is consistent with the observed decrease of brown adipose tissue temperature. This is also in line with significantly reduced tyrosine hydroxylase (Th and notably increased corticotropin-releasing hormone (Crh mRNA expressions in the paraventricular nucleus (PVN. Conclusions: Taken together, these results identify catabolic and anabolic effects of CART in the Arc and LHA, respectively, demonstrating for

  8. Overview of the West Valley Vitrification Facility transfer cart control system

    International Nuclear Information System (INIS)

    Bradley, E.C.; Rupple, F.R.

    1993-01-01

    Oak Ridge National Laboratory (ORNL) has designed the control system for the West Valley Demonstration Project Vitrification Facility transfer cart. The transfer cart will transfer canisters of vitrified high-level waste remotely within the Vitrification Facility. The control system will operate the cart under battery power by wireless control. The equipment includes cart mounted control electronics, battery charger, control pendants, engineer's console, and facility antennas

  9. 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…

  10. Smart Shopping Carts: How Real-Time Feedback Influences Spending

    NARCIS (Netherlands)

    Ittersum, van K.; Wansink, B.; Pennings, J.M.E.; Sheehan, D.

    2013-01-01

    Although interest in smart shopping carts is increasing, both retailers and consumer groups have concerns about how real-time spending feedback will influence shopping behavior. Building on budgeting and spending theories, the authors conduct three lab and grocery store experiments that robustly

  11. Smart shopping carts : How real-time feedback influences spending

    NARCIS (Netherlands)

    van Ittersum, Koert; Wansink, B.; Pennings, J.M.E.; Sheehan, D.

    Although interest in smart shopping carts is increasing, both retailers and consumer groups have concerns about how real-time spending feedback will influence shopping behavior. Building on budgeting and spending theories, the authors conduct three lab and grocery store experiments that robustly

  12. Smart shopping carts : How real-time feedback influences spending

    NARCIS (Netherlands)

    van Ittersum, Koert; Wansink, B.; Pennings, J.M.E.; Sheehan, D.

    2013-01-01

    Although interest in smart shopping carts is increasing, both retailers and consumer groups have concerns about how real-time spending feedback will influence shopping behavior. Building on budgeting and spending theories, the authors conduct three lab and grocery store experiments that robustly

  13. Acceptance Test Report for Gamma Carts A and B

    International Nuclear Information System (INIS)

    FULLER, P.J.

    2000-01-01

    Report of Shop Test of the Gamma Cart System to be used in the AZ-101 Mixer Pump Demonstration Test. Reports of the hardware and software tests. The objective of the testing was to verify in the shop that the hardware and software operated according to design specifications before field-testing and installation

  14. TEST OF AN ANIMAL DRAWN FIELD IMPLEMENT CART

    Directory of Open Access Journals (Sweden)

    Paolo Spugnoli

    2008-06-01

    Full Text Available The field performance of a horse-drawn hitch cart equipped with a PTO system powered by the two cart ground wheels have been investigated. For this purpose field tests on clay and turf soil, with varying ballast and PTO torque, have been carried out pulling the cart by a tractor. Preliminary tests were aimed at assessing the traction capability of horse breed. These tests showed that the mean draught force given by two of these horses was 173daN, average working speed was about 1m*s-1, resulting a mean draught power developed by each horse of about 0.86kW. The PTO cart system performance has shown that the torque has not exceeded 2.4daN*m, maximum draught or PTO power was 1.15kW, rotation speed just higher than 400min-1, with mean efficiency of about 50%. These values are consistent with horse performance and small haymaking, fertilizing, seeding and chemical application machine requirements.

  15. 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...

  16. HIV-associated cognitive performance and psychomotor impairment in a Thai cohort on long-term cART.

    Science.gov (United States)

    Do, Tanya C; Kerr, Stephen J; Avihingsanon, Anchalee; Suksawek, Saowaluk; Klungkang, Supalak; Channgam, Taweesak; Odermatt, Christoph C; Maek-A-Nantawat, Wirach; Ruxtungtham, Kiat; Ananworanich, Jintanat; Valcour, Victor; Reiss, Peter; Wit, Ferdinand W

    2018-01-01

    To assess cognitive performance and psychomotor impairment in an HIV-positive cohort, well-suppressed on combination antiretroviral therapy (cART), in an Asian resource-limited setting. Cross-sectional sociodemographic and cognitive data were collected in 329 HIV-positive and 510 HIV-negative participants. Cognitive performance was assessed using the International HIV Dementia Scale (IHDS), Montreal Cognitive Assessment (MoCA), WAIS-III Digit Symbol, Trail Making A, and Grooved Pegboard (both hands). Psychomotor test scores in the HIV-positive participants were converted to Z-scores using scores of the HIV-negative participants as normative data. Psychomotor impairment was defined as performance on two tests more than 1 standard deviation (SD) from controls or more than 2 SD on one test. Multivariate linear and logistic regression analyses were used to investigate associations between HIV and non-HIV-related covariates and poorer cognitive performance and psychomotor impairment. HIV-positive participants, mean age 45 (SD 7.69) years received cART for a median of 12.1 years (interquartile range [IQR] 9.1-14.4). Median CD4 cell count was 563 cells/mm 3 (IQR 435-725), and 92.77% had plasma HIV RNA performance (tests all P 90% on long-term cART, we found that inferior cognitive performance and psychomotor impairment were primarily associated with non-HIV-related factors.

  17. Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines

    International Nuclear Information System (INIS)

    Li, Yanting; He, Yong; Su, Yan; Shu, Lianjie

    2016-01-01

    Highlights: • Suggests a nonparametric model based on MARS for output power prediction. • Compare the MARS model with a wide variety of prediction models. • Show that the MARS model is able to provide an overall good performance in both the training and testing stages. - Abstract: Both linear and nonlinear models have been proposed for forecasting the power output of photovoltaic systems. Linear models are simple to implement but less flexible. Due to the stochastic nature of the power output of PV systems, nonlinear models tend to provide better forecast than linear models. Motivated by this, this paper suggests a fairly simple nonlinear regression model known as multivariate adaptive regression splines (MARS), as an alternative to forecasting of solar power output. The MARS model is a data-driven modeling approach without any assumption about the relationship between the power output and predictors. It maintains simplicity of the classical multiple linear regression (MLR) model while possessing the capability of handling nonlinearity. It is simpler in format than other nonlinear models such as ANN, k-nearest neighbors (KNN), classification and regression tree (CART), and support vector machine (SVM). The MARS model was applied on the daily output of a grid-connected 2.1 kW PV system to provide the 1-day-ahead mean daily forecast of the power output. The comparisons with a wide variety of forecast models show that the MARS model is able to provide reliable forecast performance.

  18. Testing of the West Valley Vitrification Facility transfer cart control system

    International Nuclear Information System (INIS)

    Halliwell, J.W.; Bradley, E.C.

    1995-01-01

    Oak Ridge National Laboratory (ORNL) has designed and tested the control system for the West Valley Demonstration Project Vitrification Facility transfer cart. The transfer cart will transfer canisters of vitrified high-level waste remotely within the Vitrification Facility. The control system operates the cart under battery power by wireless control. The equipment includes cart-mounted control electronics, battery charger, control pendants, engineer's console, and facility antennas. Testing was performed in several phases of development: (1) prototype equipment was built and tested during design, (2) board-level testing was then performed at ORNL during fabrication, and (3) system-level testing was then performed by ORNL at the fabrication subcontractor's facility for the completed cart system. These tests verified (1) the performance of the cart relative to design requirements and (2) operation of various built-in cart features. The final phase of testing is planned to be conducted during installation at the West Valley Vitrification Facility

  19. Finding and applying evidence during clinical rounds: the "evidence cart".

    Science.gov (United States)

    Sackett, D L; Straus, S E

    1998-10-21

    Physicians need easy access to evidence for clinical decisions while they care for patients but, to our knowledge, no investigators have assessed use of evidence during rounds with house staff. To determine if it was feasible to find and apply evidence during clinical rounds, using an "evidence cart" that contains multiple sources of evidence and the means for projecting and printing them. Descriptive feasibility study of use of evidence during 1 month (April 1997) and anonymous questionnaire (May 1997). General medicine inpatient service. Medical students, house staff, fellows, and attending consultant. Evidence cart that included 2 secondary sources developed by the department (critically appraised topics [CATs] and Redbook), Best Evidence, JAMA Rational Clinical Examination series, the Cochrane Library, MEDLINE, a physical examination textbook, a radiology anatomy textbook, and a Simulscope, which allows several people to listen simultaneously to the same signs on physical examination. Number of times sources were used, type of sources searched and success of searches, time needed to search, and whether the search affected patient care. The evidence cart was used 98 times, but could not be taken on bedside rounds because of its bulk; hard copies of several sources were taken instead. When the evidence cart was used during team rounds and student rounds, some sources could be accessed quickly enough (10.2-25.4 seconds) to be practical on our service. Of 98 searches, 79 (81%) sought evidence that could affect diagnostic and/or treatment decisions. Seventy-one (90%) of 79 searches regarding patient management were successful, and when assessed from the perspective of the most junior team members responsible for each patient's evaluation and management, 37 (52%) of the 71 successful searches confirmed their current or tentative diagnostic or treatment plans, 18 (25%) led to a new diagnostic skill, an additional test, or a new management decision, and 16 (23

  20. A School Experiment in Kinematics: Shooting from a Ballistic Cart

    Science.gov (United States)

    Kranjc, T.; Razpet, N.

    2011-10-01

    Many physics textbooks start with kinematics. In the lab, students observe the motions, describe and make predictions, and get acquainted with basic kinematics quantities and their meaning. Then they can perform calculations and compare the results with experimental findings. In this paper we describe an experiment that is not often done, but is interesting and attractive to students—the ballistic cart, i.e., the shooting of a ball from a cart moving along a slope. For that, one has to be familiar with one-dimensional uniform motion and one-dimensional motion with constant acceleration, as well as curvilinear motion that is a combination of such motions.1,2 The experimental results confirm theoretical predictions.

  1. Pushing, pulling and manoeuvring an industrial cart: a psychophysiological study.

    Science.gov (United States)

    Giagloglou, Evanthia; Radenkovic, Milan; Brankovic, Sasa; Antoniou, Panagiotis; Zivanovic-Macuzic, Ivana

    2017-09-18

    One of the most frequent manual occupational tasks involves the pushing and pulling of a cart. Although several studies have associated health risks with pushing and pulling, the effects are not clear since occupational tasks have social, cognitive and physical components. The present work investigates a real case of a pushing and pulling occupational task from a manufacturing company. The study initially characterizes the case in accordance with Standard No. ISO 11228-2:2007 as low risk. An experiment with 14 individuals during three modalities of pushing and pulling was performed in order to further investigate the task with the application of electrophysiology. At the end, a simple questionnaire was given. The results show electrophysiological differences among the three modalities of pushing and pulling, with a major difference between action with no load and fully loaded with a full range of motions on the cart to handle.

  2. A cloud climatology of the Southern Great Plains ARM CART

    Energy Technology Data Exchange (ETDEWEB)

    Lazarus, S.M.; Krueger, S.K.; Mace, G.G.

    2000-05-15

    Cloud amount statistics from three different sources were processed and compared. Surface observations from a National Centers for Environmental Prediction dataset were used. The data (Edited Cloud Report; ECR) consist of synoptic weather reports that have been edited to facilitate cloud analysis. Two stations near the Southern Great Plains (SGP) Cloud and Radiation Test Bed (CART) in north-central Oklahoma (Oklahoma City, Oklahoma and Wichita, Kansas) were selected. The ECR data span a 10-yr period from December 1981 to November 1991. The International Satellite Cloud Climatology Project (ISCCP) provided cloud amounts over the SGP CART for an 8-yr period (1983--91). Cloud amounts were also obtained from Micro Pulse Lidar (MPL) and Belfort Ceilometer (BLC) cloud-base height measurements made at the SGP CART over a 1-yr period. The annual and diurnal cycles of cloud amount as a function of cloud height and type were analyzed. The three datasets closely agree for total cloud amount. Good agreement was found in the ECR and MPL-BLC monthly low cloud amounts. With the exception of summer and midday in other seasons, the ISCCP low cloud amount estimates are generally 5%--10% less than the others. The ECR high cloud amount estimates are typically 10%--15% greater than those obtained from either the ISCCP or MPL-BLC datasets. The observed diurnal variations of altocumulus support the authors' model results of radiatively induced circulations.

  3. Regional CAR-T cell infusions for peritoneal carcinomatosis are superior to systemic delivery.

    Science.gov (United States)

    Katz, S C; Point, G R; Cunetta, M; Thorn, M; Guha, P; Espat, N J; Boutros, C; Hanna, N; Junghans, R P

    2016-05-01

    Metastatic spread of colorectal cancer (CRC) to the peritoneal cavity is common and difficult to treat, with many patients dying from malignant bowel obstruction. Chimeric antigen receptor T cell (CAR-T) immunotherapy has shown great promise, and we previously reported murine and phase I clinical studies on regional intrahepatic CAR-T infusion for CRC liver metastases. We are now studying intraperitoneal (IP) delivery of CAR-Ts for peritoneal carcinomatosis. Regional IP infusion of CAR-T resulted in superior protection against carcinoembryonic antigen (CEA+) peritoneal tumors, when compared with systemically infused CAR-Ts. IP CAR-Ts also provided prolonged protection against IP tumor re-challenges and demonstrated an increase in effector memory phenotype over time. IP CAR-Ts provided protection against tumor growth at distant subcutaneous (SC) sites in association with increases in serum IFNγ levels. Given the challenges posed by immunoinhibitory pathways in solid tumors, we combined IP CAR-T treatment with suppressor cell targeting. High frequencies of myeloid-derived suppressor cells (MDSC) and regulatory T cells (Treg) were found within the IP tumors, with MDSC expressing high levels of immunosuppressive PD-L1. Combinatorial IP CAR-T treatment with depleting antibodies against MDSC and Treg further improved efficacy against peritoneal metastases. Our data support further development of combinatorial IP CAR-T immunotherapy for peritoneal malignancies.

  4. CryoCart Restoration and Vacuum Pipe Construction

    Science.gov (United States)

    Chaidez, Mariana

    2016-01-01

    first completed at the component level. During this process, the igniter of the main engine and the RCS thrusters will be tested under a vacuum. To complete the testing of the components, the test setup first needed to be finalized. The CryoCart is being used to feed the propellants to the test article. The CryoCart is a movable test set-up that was developed in 2009 to provide a mobile platform for testing oxygen/methane systems with hot-fire capability up to 100 lbf. The CryoCart consists of three different systems: Oxygen, Methane, and liquid Nitrogen. The Oxygen and Methane systems are placed into two different carts while the liquid nitrogen system is mainly located in the methane cart. Over the years, the CryoCart has been utilized for different projects and has undergone deterioration. For this reason, a new phase has been developed to rebuild it to working conditions once again. During my internship, I was aiding in the construction and restoration of the CryoCart. In the initial stages of the process, I updated the fluid and electrical schematics for the oxygen, methane, and test article systems. The original CryoCart consisted of an electrical panel that utilized electromechanical relays and a terminal to drive the igniter power and signal, as well as the main fuel and oxygen valves. This electrical panel connected to the CryoCart through various wire harnesses that could be found exiting from the CryoCart. First, it was determined how these harnesses connected to the electromechanical relays so that they worked correctly. Once the electrical system was understood, an alternative for the electromechanical relays and the Molex connectors used throughout the system was sought since these components can often prove to be unreliable. Solid State relays and MIL connectors were purchased to serve as replacements. Upon arrival of the parts, crimping and wiring was completed to install the new solid state relays and MIL connectors. During the replacement of the relays

  5. How to differentiate acute pelvic inflammatory disease from acute appendicitis? A decision tree based on CT findings

    Energy Technology Data Exchange (ETDEWEB)

    El Hentour, Kim; Millet, Ingrid; Pages-Bouic, Emmanuelle; Curros-Doyon, Fernanda; Taourel, Patrice [Lapeyronie Hospital, Department of Medical Imaging, Montpellier (France); Molinari, Nicolas [UMR 5149 IMAG, CHU, Department of Medical Information and Statistics, Montpellier (France)

    2018-02-15

    To construct a decision tree based on CT findings to differentiate acute pelvic inflammatory disease (PID) from acute appendicitis (AA) in women with lower abdominal pain and inflammatory syndrome. This retrospective study was approved by our institutional review board and informed consent was waived. Contrast-enhanced CT studies of 109 women with acute PID and 218 age-matched women with AA were retrospectively and independently reviewed by two radiologists to identify CT findings predictive of PID or AA. Surgical and laboratory data were used for the PID and AA reference standard. Appropriate tests were performed to compare PID and AA and a CT decision tree using the classification and regression tree (CART) algorithm was generated. The median patient age was 28 years (interquartile range, 22-39 years). According to the decision tree, an appendiceal diameter ≥ 7 mm was the most discriminating criterion for differentiating acute PID and AA, followed by a left tubal diameter ≥ 10 mm, with a global accuracy of 98.2 % (95 % CI: 96-99.4). Appendiceal diameter and left tubal thickening are the most discriminating CT criteria for differentiating acute PID from AA. (orig.)

  6. How to differentiate acute pelvic inflammatory disease from acute appendicitis? A decision tree based on CT findings

    International Nuclear Information System (INIS)

    El Hentour, Kim; Millet, Ingrid; Pages-Bouic, Emmanuelle; Curros-Doyon, Fernanda; Taourel, Patrice; Molinari, Nicolas

    2018-01-01

    To construct a decision tree based on CT findings to differentiate acute pelvic inflammatory disease (PID) from acute appendicitis (AA) in women with lower abdominal pain and inflammatory syndrome. This retrospective study was approved by our institutional review board and informed consent was waived. Contrast-enhanced CT studies of 109 women with acute PID and 218 age-matched women with AA were retrospectively and independently reviewed by two radiologists to identify CT findings predictive of PID or AA. Surgical and laboratory data were used for the PID and AA reference standard. Appropriate tests were performed to compare PID and AA and a CT decision tree using the classification and regression tree (CART) algorithm was generated. The median patient age was 28 years (interquartile range, 22-39 years). According to the decision tree, an appendiceal diameter ≥ 7 mm was the most discriminating criterion for differentiating acute PID and AA, followed by a left tubal diameter ≥ 10 mm, with a global accuracy of 98.2 % (95 % CI: 96-99.4). Appendiceal diameter and left tubal thickening are the most discriminating CT criteria for differentiating acute PID from AA. (orig.)

  7. In silico prediction of toxicity of phenols to Tetrahymena pyriformis by using genetic algorithm and decision tree-based modeling approach.

    Science.gov (United States)

    Abbasitabar, Fatemeh; Zare-Shahabadi, Vahid

    2017-04-01

    Risk assessment of chemicals is an important issue in environmental protection; however, there is a huge lack of experimental data for a large number of end-points. The experimental determination of toxicity of chemicals involves high costs and time-consuming process. In silico tools such as quantitative structure-toxicity relationship (QSTR) models, which are constructed on the basis of computational molecular descriptors, can predict missing data for toxic end-points for existing or even not yet synthesized chemicals. Phenol derivatives are known to be aquatic pollutants. With this background, we aimed to develop an accurate and reliable QSTR model for the prediction of toxicity of 206 phenols to Tetrahymena pyriformis. A multiple linear regression (MLR)-based QSTR was obtained using a powerful descriptor selection tool named Memorized_ACO algorithm. Statistical parameters of the model were 0.72 and 0.68 for R training 2 and R test 2 , respectively. To develop a high-quality QSTR model, classification and regression tree (CART) was employed. Two approaches were considered: (1) phenols were classified into different modes of action using CART and (2) the phenols in the training set were partitioned to several subsets by a tree in such a manner that in each subset, a high-quality MLR could be developed. For the first approach, the statistical parameters of the resultant QSTR model were improved to 0.83 and 0.75 for R training 2 and R test 2 , respectively. Genetic algorithm was employed in the second approach to obtain an optimal tree, and it was shown that the final QSTR model provided excellent prediction accuracy for the training and test sets (R training 2 and R test 2 were 0.91 and 0.93, respectively). The mean absolute error for the test set was computed as 0.1615. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. The PASCO Wireless Smart Cart: A Game Changer in the Undergraduate Physics Laboratory

    Science.gov (United States)

    Shakur, Asif; Connor, Rainor

    2018-03-01

    With the introduction of the Wireless Smart Cart by PASCO scientific in April 2016, we expect a paradigm shift in undergraduate physics laboratory instruction. We have evaluated the feasibility of using the smart cart by carrying out experiments that are usually performed using traditional PASCO equipment. The simplicity, convenience, and cost-saving achieved by replacing a plethora of traditional laboratory sensors, wires, and equipment clutter with the smart cart are reported here.

  9. Differential expression of CART in feeding and reward circuits in binge eating rat model.

    Science.gov (United States)

    Bharne, Ashish P; Borkar, Chandrashekhar D; Subhedar, Nishikant K; Kokare, Dadasaheb M

    2015-09-15

    Binge eating (BE) disrupts feeding and subverts reward mechanism. Since cocaine- and amphetamine-regulated transcript peptide (CART) mediates satiety as well as reward, its role in BE justifies investigation. To induce BE, rats were provided restricted access to high fat sweet palatable diet (HFSPD) for a period of 4 weeks. Immunoreactivity profile of the CART elements, and accompanying neuroplastic changes were studied in satiety- and reward-regulating brain nuclei. Further, we investigated the effects of CART, CART-antibody or rimonabant on the intake of normal chow or HFSPD. Rats fed on HFSPD showed development of BE-like phenotype as reflected by significant consumption of HFSPD in short time frame, suggestive of dysregulated satiety mechanisms. At the mid-point during BE, CART-immunoreactivity was significantly increased in hypothalamic arcuate (ARC), lateral (LH), nucleus accumbens shell (AcbSh) and paraventricular nucleus of thalamus (PVT). However, for next 22-h post-binge time-period, the animals showed no interest in food, and low CART expression. Pre-binge treatment with rimonabant, a drug recommended for the treatment of BE, produced anorexia, increased CART expression in ARC and LH, but not in AcbSh and PVT. Higher dose of CART was required to produce anorexia in binged rats. While neuronal tracing studies confirmed CART fiber connectivity from ARC and LH to AcbSh, increase in CART and synaptophysin immunostaining in this pathway in BE rats suggested strengthening of the CART connectivity. We conclude that CART bearing ARC-LH-PVT-AcbSh reward circuit may override the satiety signaling in ARC-PVN pathway in BE rats. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Data acquisition in modeling using neural networks and decision trees

    Directory of Open Access Journals (Sweden)

    R. Sika

    2011-04-01

    Full Text Available The paper presents a comparison of selected models from area of artificial neural networks and decision trees in relation with actualconditions of foundry processes. The work contains short descriptions of used algorithms, their destination and method of data preparation,which is a domain of work of Data Mining systems. First part concerns data acquisition realized in selected iron foundry, indicating problems to solve in aspect of casting process modeling. Second part is a comparison of selected algorithms: a decision tree and artificial neural network, that is CART (Classification And Regression Trees and BP (Backpropagation in MLP (Multilayer Perceptron networks algorithms.Aim of the paper is to show an aspect of selecting data for modeling, cleaning it and reducing, for example due to too strong correlationbetween some of recorded process parameters. Also, it has been shown what results can be obtained using two different approaches:first when modeling using available commercial software, for example Statistica, second when modeling step by step using Excel spreadsheetbasing on the same algorithm, like BP-MLP. Discrepancy of results obtained from these two approaches originates from a priorimade assumptions. Mentioned earlier Statistica universal software package, when used without awareness of relations of technologicalparameters, i.e. without user having experience in foundry and without scheduling ranks of particular parameters basing on acquisition, can not give credible basis to predict the quality of the castings. Also, a decisive influence of data acquisition method has been clearly indicated, the acquisition should be conducted according to repetitive measurement and control procedures. This paper is based on about 250 records of actual data, for one assortment for 6 month period, where only 12 data sets were complete (including two that were used for validation of neural network and useful for creating a model. It is definitely too

  11. Characterisation of CART-containing neurons and cells in the porcine pancreas, gastro-intestinal tract, adrenal and thyroid glands

    Directory of Open Access Journals (Sweden)

    Gunnarsdóttir Anna

    2007-07-01

    Full Text Available Abstract Background The peptide CART is widely expressed in central and peripheral neurons, as well as in endocrine cells. Known peripheral sites of expression include the gastrointestinal (GI tract, the pancreas, and the adrenal glands. In rodent pancreas CART is expressed both in islet endocrine cells and in nerve fibers, some of which innervate the islets. Recent data show that CART is a regulator of islet hormone secretion, and that CART null mutant mice have islet dysfunction. CART also effects GI motility, mainly via central routes. In addition, CART participates in the regulation of the hypothalamus-pituitary-adrenal-axis. We investigated CART expression in porcine pancreas, GI-tract, adrenal glands, and thyroid gland using immunocytochemistry. Results CART immunoreactive (IR nerve cell bodies and fibers were numerous in pancreatic and enteric ganglia. The majority of these were also VIP IR. The finding of intrinsic CART containing neurons indicates that pancreatic and GI CART IR nerve fibers have an intrinsic origin. No CART IR endocrine cells were detected in the pancreas or in the GI tract. The adrenal medulla harboured numerous CART IR endocrine cells, most of which were adrenaline producing. In addition CART IR fibers were frequently seen in the adrenal cortex and capsule. The capsule also contained CART IR nerve cell bodies. The majority of the adrenal CART IR neuronal elements were also VIP IR. CART IR was also seen in a substantial proportion of the C-cells in the thyroid gland. The majority of these cells were also somatostatin IR, and/or 5-HT IR, and/or VIP IR. Conclusion CART is a major neuropeptide in intrinsic neurons of the porcine GI-tract and pancreas, a major constituent of adrenaline producing adrenomedullary cells, and a novel peptide of the thyroid C-cells. CART is suggested to be a regulatory peptide in the porcine pancreas, GI-tract, adrenal gland and thyroid.

  12. E-Commerce Performance. Shopping Cart Key Performance Indicators

    Directory of Open Access Journals (Sweden)

    Mihaela I. MUNTEAN

    2016-01-01

    Full Text Available In an e-commerce performance framework is important to identify the key performance indicators that measure success and together provide the greatest context into the business perfor-mance. Shopping carts are an essential part of ecommerce, a minimal set of key performance indicators being the subject of our debate. The theoretical approach is sustained by a case study, an e-shop implemented using PHP and MySQL, for simulating main business processes within the considered performance framework. Our approach opens a perspective for future research using additional indicators in order to properly evaluate the global performance of any e-shop.

  13. DeCART v1.2 User's Manual

    International Nuclear Information System (INIS)

    Cho, J. Y.; Kim, K. S.; Kim, H. Y.; Lee, C. C.; Zee, S. Q; Joo, H. G.

    2007-07-01

    DeCART (Deterministic Core Analysis based on Ray Tracing) is a whole core neutron transport code capable of direct subpin level flux calculation at power generating conditions. It does not require a priori homogenization nor group condensation needed in conventional reactor physics calculations. The depletion and transient calculation capabilities are also available. This manual serves as a self-sufficient guide to use the code. First of all, the various features of the code are explained which encompass various modeling options as well as the basic calculation functionalities. The instructions for running the code are also given with a description of the output files generated. Next, the underlying concepts and principles of preparing a DeCART model for a problem under consideration are presented. Each part of the input needed to specify the geometry, material composition, thermal operating condition, program execution control parameters are explained with examples. The descriptions of all the input cards are then followed. Finally, various sample model inputs ranging from a simple 2D pin cell to a realistic 3D core problem, steady-state to transient problems, and from rectangular to hexagonal core problems are presented

  14. DeCART v1.1 user's manual

    International Nuclear Information System (INIS)

    Cho, J. Y.; Kim, K. S.; Kim, H. Y.; Lee, C. C.; Zee, S. Q.; Joo, H. G.

    2005-03-01

    DeCART (Deterministic Core Analysis based on Ray Tracing) is a whole core neutron transport code capable of direct subpin level flux calculation at power generating conditions. It does not require a priori homogenization nor group condensation needed in conventional reactor physics calculations. The depletion and transient calculation capabilities are also available. This manual serves as a self-sufficient guide to use the code. First of all, the various features of the code are explained which encompass various modeling options as well as the basic calculation functionalities. The instructions for running the code are also given with a description of the output files generated. Next, the underlying concepts and principles of preparing a DeCART model for a problem under consideration are presented. Each part of the input needed to specify the geometry, material composition, thermal operating condition, program execution control parameters are explained with examples. The descriptions of all the input cards are then followed. Finally, various sample model inputs ranging from a simple 2D pin cell to a realistic 3D core problem, steady-state to transient problems, are presented

  15. Genetic polymorphisms associated with fatty liver disease and fibrosis in HIV positive patients receiving combined antiretroviral therapy (cART)

    Science.gov (United States)

    Luda, Carolin; Schwarze-Zander, Carolynne; Boesecke, Christoph; Hansel, Cordula; Nischalke, Hans-Dieter; Lutz, Philipp; Mohr, Raphael; Wasmuth, Jan-Christian; Strassburg, Christian P.; Trebicka, Jonel; Rockstroh, Jürgen Kurt; Spengler, Ulrich

    2017-01-01

    Hepatic steatosis can occur with any antiretroviral therapy (cART). Although single nucleotide polymorphisms (SNPs) have been identified to predispose to alcoholic and non-alcoholic fatty liver disease, their role for treatment-associated steatosis in HIV-positive patients remains unclear. We determined the frequency of PNPLA3 (rs738409), CSPG3/NCAN (rs2228603), GCKR (rs780094), PPP1R3B (rs4240624), TM6SF (rs8542926), LYPLAL1 (rs12137855) and MBOAT7 (rs626283) by RT-PCR in 117 HIV-positive patients on cART and stratified participants based on their “controlled attenuation parameter” (CAP) into probable (CAP: 215–300 dB/m) and definite (CAP >300 dB/m) hepatic steatosis. We analyzed CAP values and routine metabolic parameters according to the allele frequencies. Sixty-five (55.6%) and 13 (11.1%) patients were allocated to probable and definite steatosis. CAP values (p = 0.012) and serum triglycerides (p = 0.043) were increased in carriers of the GCKR (rs780094) A allele. Cox logistic regression identified triglycerides (p = 0.006), bilirubin (p = 0.021) and BMI (p = 0.068), but not the genetic parameters as risk factors for the occurrence of hepatic steatosis. Taken together, according to the limited sample size, this exploratory study generates the hypothesis that genetic polymorphisms seem to exert minor effects on the risk for fatty liver disease in HIV-positive patients on cART. Nevertheless, SNPs may modify metabolic complications once metabolic abnormalities have developed. Hence, subsequent analysis of a larger cohort is needed. PMID:28594920

  16. The PASCO Wireless Smart Cart: A Game Changer in the Undergraduate Physics Laboratory

    Science.gov (United States)

    Shakur, Asif; Connor, Rainor

    2018-01-01

    With the introduction of the Wireless Smart Cart by PASCO scientific in April 2016, we expect a paradigm shift in undergraduate physics laboratory instruction. We have evaluated the feasibility of using the smart cart by carrying out experiments that are usually performed using traditional PASCO equipment. The simplicity, convenience, and…

  17. CART peptide is a potential endogenous antioxidant and preferentially localized in mitochondria.

    Directory of Open Access Journals (Sweden)

    Peizhong Mao

    Full Text Available The multifunctional neuropeptide Cocaine and Amphetamine Regulated Transcript (CART is secreted from hypothalamus, pituitary, adrenal gland and pancreas. It also can be found in circulatory system. This feature suggests a general role for CART in different cells. In the present study, we demonstrate that CART protects mitochondrial DNA (mtDNA, cellular proteins and lipids against the oxidative action of hydrogen peroxide, a widely used oxidant. Using cis-parinaric acid as a sensitive reporting probe for peroxidation in membranes, and a lipid-soluble azo initiator of peroxyl radicals, 2,2'-azobis(2,4-dimethylvaleronitrile we found that CART is an antioxidant. Furthermore, we found that CART localized to mitochondria in cultured cells and mouse brain neuronal cells. More importantly, pretreatment with CART by systemic injection protects against a mouse oxidative stress model, which mimics the main features of Parkinson's disease. Given the unique molecular structure and biological features of CART, we conclude that CART is an antioxidant peptide (or antioxidant hormone. We further propose that it may have strong therapeutic properties for human diseases in which oxidative stress is strongly involved such as Parkinson's disease.

  18. Schoolchildren's Consumption of Competitive Foods and Beverages, Excluding a la Carte

    Science.gov (United States)

    Kakarala, Madhuri; Keast, Debra R.; Hoerr, Sharon

    2010-01-01

    Background: Competitive foods/beverages are those in school vending machines, school stores, snack bars, special sales, and items sold a la carte in the school cafeteria that compete with United States Department of Agriculture (USDA) meal program offerings. Grouping a la carte items with less nutritious items allowed in less regulated venues may…

  19. AZ-101 Mixer Pump Demonstration Data Acquisition System and Gamma Cart Data Acquisition Control System Software Configuration Management Plan

    International Nuclear Information System (INIS)

    WHITE, D.A.

    1999-01-01

    This Software Configuration Management Plan (SCMP) provides the instructions for change control of the AZ1101 Mixer Pump Demonstration Data Acquisition System (DAS) and the Sludge Mobilization Cart (Gamma Cart) Data Acquisition and Control System (DACS)

  20. CRISPR-Cas9 mediated LAG-3 disruption in CAR-T cells.

    Science.gov (United States)

    Zhang, Yongping; Zhang, Xingying; Cheng, Chen; Mu, Wei; Liu, Xiaojuan; Li, Na; Wei, Xiaofei; Liu, Xiang; Xia, Changqing; Wang, Haoyi

    2017-12-01

    T cells engineered with chimeric antigen receptor (CAR) have been successfully applied to treat advanced refractory B cell malignancy. However, many challenges remain in extending its application toward the treatment of solid tumors. The immunosuppressive nature of tumor microenvironment is considered one of the key factors limiting CAR-T efficacy. One negative regulator of Tcell activity is lymphocyte activation gene-3 (LAG-3). We successfully generated LAG-3 knockout Tand CAR-T cells with high efficiency using CRISPR-Cas9 mediated gene editing and found that the viability and immune phenotype were not dramatically changed during in vitro culture. LAG-3 knockout CAR-T cells displayed robust antigen-specific antitumor activity in cell culture and in murine xenograft model, which is comparable to standard CAR-T cells. Our study demonstrates an efficient approach to silence immune checkpoint in CAR-T cells via gene editing.

  1. [Current Status and Challenges of CAR-T Immunotherapy in Hematologic Malignancies -Review].

    Science.gov (United States)

    Cheng, Xin; Wang, Ya-Jie; Feng, Shuai; Wu, Ya-Yun; Yang, Tong-Hua; Lai, Xun

    2018-04-01

    The chimeric antigen receptor (CAR) T cell therapy has gradually became a new trend in the treatment of refractory and relapsed hematologic malignancies by developing for 30 years. With the exciting development of genetic engineering, CAR-T technology has subjected to 4 generations of innovation. Structure of CAR-T started from a single signal molecule to 2 or more than 2 co-stimulatory molecules, and then coding the CAR gene or promoter. CAR-T can specifically recognize tumor antigens, and does not be restricted by major histocompatibility complex (MHC), thus making a breakthrough in clinical treatment. In this review, the history, structure and mechanism of action of CAR-T, as well as the current status and challenges of CAR-T immunotherapy in acute lymphoblastic leukemia, acute myeloid leukemia, chronic myeloid leukemia and multiple myeloma are summarized.

  2. Insights into cytokine release syndrome and neurotoxicity after CD19-specific CAR-T cell therapy.

    Science.gov (United States)

    Gauthier, Jordan; Turtle, Cameron J

    2018-04-03

    T-cells engineered to express CD19-specific chimeric antigen receptors (CD19 CAR-T cells) can achieve high response rates in patients with refractory/relapsed (R/R) CD19+ hematologic malignancies. Nonetheless, the efficacy of CD19-specific CAR-T cell therapy can be offset by significant toxicities, such as cytokine release syndrome (CRS) and neurotoxicity. In this report of our presentation at the 2018 Second French International Symposium on CAR-T cells (CAR-T day), we describe the clinical presentations of CRS and neurotoxicity in a cohort of 133 adults treated with CD19 CAR-T cells at the Fred Hutchinson Cancer Research Center, and provide insights into the mechanisms contributing to these toxicities. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

  3. Decision tree methods: applications for classification and prediction.

    Science.gov (United States)

    Song, Yan-Yan; Lu, Ying

    2015-04-25

    Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. This method classifies a population into branch-like segments that construct an inverted tree with a root node, internal nodes, and leaf nodes. The algorithm is non-parametric and can efficiently deal with large, complicated datasets without imposing a complicated parametric structure. When the sample size is large enough, study data can be divided into training and validation datasets. Using the training dataset to build a decision tree model and a validation dataset to decide on the appropriate tree size needed to achieve the optimal final model. This paper introduces frequently used algorithms used to develop decision trees (including CART, C4.5, CHAID, and QUEST) and describes the SPSS and SAS programs that can be used to visualize tree structure.

  4. Italian translation and cross-cultural comparison with the Childhood Attachment and Relational Trauma Screen (CARTS).

    Science.gov (United States)

    Simonelli, A; Sacchi, C; Cantoni, L; Brown, M; Frewen, P

    2017-01-01

    Background : The Childhood Attachment and Relational Trauma Screen (CARTS) is a computer-administered survey designed to assess retrospectively the socio-ecological context in which instances of child abuse may have occurred. To date, studies supporting the validity of the CARTS have only been undertaken in English-speaking North American populations. Validation projects in other countries and cross-cultural comparisons are therefore warranted. Objective : Develop and preliminarily evaluate the psychometric properties of an Italian version of the CARTS on college students and compare such observations to data acquired from Canadian students. Method : Seventy-nine undergraduate students from the University of Padua (Italy) completed an Italian translation of the CARTS as well as measures of childhood experiences, mental health and attachment, responses to which were compared to those obtained in 288 Canadian students who completed the CARTS in English. Results : Internal consistency and convergent validity with the Childhood Trauma Questionnaire and Parental Bonding Instrument were found to be acceptable for the Italian translation. Within the Italian sample, correlation analyses suggested that CARTS Mother ratings referring to attachment and abuse were associated with romantic attachment, whereas CARTS Father ratings were significantly correlated to PTSD symptoms and other symptoms of psychopathology-distress. Significant differences between Italian and Canadian students across the relationship types for the CARTS abuse and attachment scales were found, indicating that Italian students rated their mothers and fathers as simultaneously less abusive, but also less as a source of secure attachment. Conclusions : The results of this preliminary study seem to suggest convergent validity of the Italian CARTS and the association between childhood attachment-related experiences and romantic attachment. Cultural variations were identified between Canadian and Italian

  5. Association of Cocaine- and Amphetamine-Regulated Transcript (CART) Messenger RNA Level, Food Intake, and Growth in Channel Catfish

    Science.gov (United States)

    Cocaine-and Amphetamine-Regulated Transcript (CART) is a potent hypothalamic anorectic peptide in mammals and fish. We hypothesized that increased food intake is associated with changes in expression of CART mRNA within the brain of channel catfish. Objectives were to clone the CART gene, examine ...

  6. Purification and characterisation of a new hypothalamic satiety peptide, cocaine and amphetamine regulated transcript (CART), produced in yeast.

    Science.gov (United States)

    Thim, L; Nielsen, P F; Judge, M E; Andersen, A S; Diers, I; Egel-Mitani, M; Hastrup, S

    1998-05-29

    Cocaine and amphetamine regulated transcript (CART) is a newly discovered hypothalamic peptide with a potent appetite suppressing activity following intracerebroventricular administration. When the mature rat CART sequence encoding CART(1-102) was inserted in the yeast expression plasmid three CART peptides could be purified from the fermentation broth reflecting processing at dibasic sequences. None of these corresponded to the naturally occurring CART(55-102). In order to obtain CART(55-102) the precursor Glu-Glu-Ile-Asp-CART(55-102) has been produced and CART(55-102) was generated by digestion of the precursor with dipeptidylaminopeptidase-1. All four generated CART peptides have been characterised by N-terminal amino acid sequencing and mass spectrometry. The CART peptides contain six cysteine residues and using the yeast expressed CART(62-102) the disulphide bond configuration was found to be I-III, II-V and IV-VI. When the four CART peptides were intracerebroventricularly injected in fasted mice (0.1 to 2.0 microg) they all produced a dose dependent inhibition of food intake.

  7. 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…

  8. Differential expression of CART in ewes with differing ovulation rates.

    Science.gov (United States)

    Juengel, Jennifer L; French, Michelle C; Quirke, Laurel D; Kauff, Alexia; Smith, George W; Johnstone, Peter D

    2017-04-01

    We hypothesised that cocaine- and amphetamine-regulated transcript ( CARTPT ) would be differentially expressed in ewes with differing ovulation rates. Expression of mRNA for CARTPT , as well as LHCGR , FSHR , CYP19A1 and CYP17A1 was determined in antral follicles ≥1 mm in diameter collected during the follicular phase in ewes heterozygous for the Booroola and Inverdale genes (I+B+; average ovulation rate 4) and ++ contemporaries (++; average ovulation rate 1.8). In ++ ewes ( n  = 6), CARTPT was expressed in small follicles (1 to ewes. In I+B+ ewes, 5/6 ewes did not have any follicles that expressed CARTPT , and no CART peptide was detected in any follicle examined. Expression pattern of CYP19A1 differed between I+B+ and ++ ewes with an increased percentage of small and medium follicles (3 to ewes. Many of the large follicles from the I+B+ ewes appeared non-functional and expression of LHCGR , FSHR , CYP17A1 and CYP19A1 was less than that observed in ++ ewes. Expression of FSHR and CYP17A1 was not different between groups in small and medium follicles, but LHCGR expression was approximately double in I+B+ ewes compared to that in ++ ewes. Thus, ewes with high ovulation rates had a distinct pattern of expression of CARTPT mRNA and protein compared to ewes with normal ovulation rates, providing evidence for CART being important in the regulation of ovulation rate. © 2017 Society for Reproduction and Fertility.

  9. 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.

  10. Different Subsets of T Cells, Memory, Effector Functions, and CAR-T Immunotherapy.

    Science.gov (United States)

    Golubovskaya, Vita; Wu, Lijun

    2016-03-15

    This review is focused on different subsets of T cells: CD4 and CD8, memory and effector functions, and their role in CAR-T therapy--a cellular adoptive immunotherapy with T cells expressing chimeric antigen receptor. The CAR-T cells recognize tumor antigens and induce cytotoxic activities against tumor cells. Recently, differences in T cell functions and the role of memory and effector T cells were shown to be important in CAR-T cell immunotherapy. The CD4⁺ subsets (Th1, Th2, Th9, Th17, Th22, Treg, and Tfh) and CD8⁺ memory and effector subsets differ in extra-cellular (CD25, CD45RO, CD45RA, CCR-7, L-Selectin [CD62L], etc.); intracellular markers (FOXP3); epigenetic and genetic programs; and metabolic pathways (catabolic or anabolic); and these differences can be modulated to improve CAR-T therapy. In addition, CD4⁺ Treg cells suppress the efficacy of CAR-T cell therapy, and different approaches to overcome this suppression are discussed in this review. Thus, next-generation CAR-T immunotherapy can be improved, based on our knowledge of T cell subsets functions, differentiation, proliferation, and signaling pathways to generate more active CAR-T cells against tumors.

  11. Different Subsets of T Cells, Memory, Effector Functions, and CAR-T Immunotherapy

    Directory of Open Access Journals (Sweden)

    Vita Golubovskaya

    2016-03-01

    Full Text Available This review is focused on different subsets of T cells: CD4 and CD8, memory and effector functions, and their role in CAR-T therapy––a cellular adoptive immunotherapy with T cells expressing chimeric antigen receptor. The CAR-T cells recognize tumor antigens and induce cytotoxic activities against tumor cells. Recently, differences in T cell functions and the role of memory and effector T cells were shown to be important in CAR-T cell immunotherapy. The CD4+ subsets (Th1, Th2, Th9, Th17, Th22, Treg, and Tfh and CD8+ memory and effector subsets differ in extra-cellular (CD25, CD45RO, CD45RA, CCR-7, L-Selectin [CD62L], etc.; intracellular markers (FOXP3; epigenetic and genetic programs; and metabolic pathways (catabolic or anabolic; and these differences can be modulated to improve CAR-T therapy. In addition, CD4+ Treg cells suppress the efficacy of CAR-T cell therapy, and different approaches to overcome this suppression are discussed in this review. Thus, next-generation CAR-T immunotherapy can be improved, based on our knowledge of T cell subsets functions, differentiation, proliferation, and signaling pathways to generate more active CAR-T cells against tumors.

  12. New analogs of the CART peptide with anorexigenic potency: the importance of individual disulfide bridges.

    Science.gov (United States)

    Blechová, Miroslava; Nagelová, Veronika; Záková, Lenka; Demianová, Zuzana; Zelezná, Blanka; Maletínská, Lenka

    2013-01-01

    The CART (cocaine- and amphetamine-regulated transcript) peptide is an anorexigenic neuropeptide that acts in the hypothalamus. The receptor and the mechanism of action of this peptide are still unknown. In our previous study, we showed that the CART peptide binds specifically to PC12 rat pheochromocytoma cells in both the native and differentiated into neuronal phenotype. Two biologically active forms, CART(55-102) and CART(61-102), with equal biological activity, contain three disulfide bridges. To clarify the importance of each of these disulfide bridges in maintaining the biological activity of CART(61-102), an Ala scan at particular S-S bridges forming cysteines was performed, and analogs with only one or two disulfide bridges were synthesized. In this study, a stabilized CART(61-102) analog with norleucine instead of methionine at position 67 was also prepared and was found to bind to PC12 cells with an anorexigenic potency similar to that of CART(61-102). The binding study revealed that out of all analogs tested, [Ala(68,86)]CART(61-102), which contains two disulfide bridges (positions 74-94 and 88-101), preserved a high affinity to both native PC12 cells and those that had been differentiated into neurons. In food intake and behavioral tests with mice after intracerebroventricular administration, this analog showed strong and long-lasting anorexigenic potency. Therefore, the disulfide bridge between cysteines 68 and 86 in CART(61-102) can be omitted without a loss of biological activity, but the preservation of two other disulfide bridges and the full-length peptide are essential for biological activity. Copyright © 2012 Elsevier Inc. All rights reserved.

  13. Myeloid Conditioning with c-kit-Targeted CAR-T Cells Enables Donor Stem Cell Engraftment.

    Science.gov (United States)

    Arai, Yasuyuki; Choi, Uimook; Corsino, Cristina I; Koontz, Sherry M; Tajima, Masaki; Sweeney, Colin L; Black, Mary A; Feldman, Steven A; Dinauer, Mary C; Malech, Harry L

    2018-05-02

    We report a novel approach to bone marrow (BM) conditioning using c-kit-targeted chimeric antigen receptor T (c-kit CAR-T) cells in mice. Previous reports using anti-c-kit or anti-CD45 antibody linked to a toxin such as saporin have been promising. We developed a distinctly different approach using c-kit CAR-T cells. Initial studies demonstrated in vitro killing of hematopoietic stem cells by c-kit CAR-T cells but poor expansion in vivo and poor migration of CAR-T cells into BM. Pre-treatment of recipient mice with low-dose cyclophosphamide (125 mg/kg) together with CXCR4 transduction in the CAR-T cells enhanced trafficking to and expansion in BM (c-kit + population (9.0%-0.1%). Because congenic Thy1.1 CAR-T cells were used in the Thy1.2-recipient mice, anti-Thy1.1 antibody could be used to deplete CAR-T cells in vivo before donor BM transplant. This achieved 20%-40% multilineage engraftment. We applied this conditioning to achieve an average of 28% correction of chronic granulomatous disease mice by wild-type BM transplant. Our findings provide a proof of concept that c-kit CAR-T cells can achieve effective BM conditioning without chemo-/radiotherapy. Our work also demonstrates that co-expression of a trafficking receptor can enhance targeting of CAR-T cells to a designated tissue. Published by Elsevier Inc.

  14. Decision Tree Technique for Particle Identification

    International Nuclear Information System (INIS)

    Quiller, Ryan

    2003-01-01

    Particle identification based on measurements such as the Cerenkov angle, momentum, and the rate of energy loss per unit distance (-dE/dx) is fundamental to the BaBar detector for particle physics experiments. It is particularly important to separate the charged forms of kaons and pions. Currently, the Neural Net, an algorithm based on mapping input variables to an output variable using hidden variables as intermediaries, is one of the primary tools used for identification. In this study, a decision tree classification technique implemented in the computer program, CART, was investigated and compared to the Neural Net over the range of momenta, 0.25 GeV/c to 5.0 GeV/c. For a given subinterval of momentum, three decision trees were made using different sets of input variables. The sensitivity and specificity were calculated for varying kaon acceptance thresholds. This data was used to plot Receiver Operating Characteristic curves (ROC curves) to compare the performance of the classification methods. Also, input variables used in constructing the decision trees were analyzed. It was found that the Neural Net was a significant contributor to decision trees using dE/dx and the Cerenkov angle as inputs. Furthermore, the Neural Net had poorer performance than the decision tree technique, but tended to improve decision tree performance when used as an input variable. These results suggest that the decision tree technique using Neural Net input may possibly increase accuracy of particle identification in BaBar

  15. Stochastic search, optimization and regression with energy applications

    Science.gov (United States)

    Hannah, Lauren A.

    models. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression like CART, Bayesian trees and Gaussian processes. Compared to existing techniques, the DP-GLM provides a single model (and corresponding inference algorithms) that performs well in many regression settings. Finally, we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whose behavior depends on an exogenous state variable which affects the shape of the objective function. Currently, there is no general purpose algorithm to solve this class of problems. We use nonparametric density estimation to take observations from the joint state-outcome distribution and use them to infer the optimal decision for a given query state. We propose two solution methods that depend on the problem characteristics: function-based and gradient-based optimization. We examine two weighting schemes, kernel-based weights and Dirichlet process-based weights, for use with the solution methods. The weights and solution methods are tested on a synthetic multi-product newsvendor problem and the hour-ahead wind commitment problem. Our results show that in some cases Dirichlet process weights offer substantial benefits over kernel based weights and more generally that nonparametric estimation methods provide good solutions to otherwise intractable problems.

  16. Quantitative evaluation of CART-containing cells in urinary bladder of rats with renovascular hypertension

    Directory of Open Access Journals (Sweden)

    I. Janiuk

    2015-04-01

    Full Text Available Recent biological advances make it possible to discover new peptides associated with hypertension. The cocaine- and amphetamine-regulated transcript (CART is a known factor in appetite and feeding behaviour. Various lines of evidence suggest that this peptide participates not only in control of feeding behaviour but also in the regulation of the cardiovascular and sympathetic systems and blood pressure. The role of CART in blood pressure regulation led us to undertake a study aimed at analysing quantitative changes in CART-containing cells in urinary bladders (UB of rats with renovascular hypertension. We used the Goldblatt model of arterial hypertension (two-kidney, one clip to evaluate quantitative changes. This model provides researchers with a commonly used tool to analyse the renin-angiotensin system of blood pressure control and, eventually, to develop drugs for the treatment of chronic hypertension. The study was performed on sections of urinary bladders of rats after 3-, 14-, 28-, 42 and 91 days from hypertension induction. Immunohistochemical identification of CART cells was performed on paraffin for the UBs of all the study animals. CART was detected in the endocrine cells, especially numerous in the submucosa and muscularis layers, with a few found in the transitional epithelium and only occasionally in serosa. Hypertension significantly increased the number of CART-positive cells in the rat UBs. After 3 and 42 days following the procedure, statistically significantly higher numbers of CART-positive cells were identified in comparison with the control animals. The differences between the hypertensive rats and the control animals concerned not only the number density of CART-immunoreactive cells but also their localization. After a 6-week period, each of the rats subjected to the renal artery clipping procedure developed stable hypertension. CART appeared in numerous transitional epithelium cells. As this study provides novel findings

  17. STS-37 crewmembers test CETA hand cart during training session in JSC's WETF

    Science.gov (United States)

    1989-01-01

    STS-37 Atlantis, Orbiter Vehicle (OV) 104, Mission Specialist (MS) Jerry L. Ross and MS Jerome Apt test crew and equipment translation aid (CETA) manual hand over hand cart during underwater session in JSC's Weightless Environment Training Facility (WETF) Bldg 29. Wearing an extravehicular mobility unit (EMU), Ross pulls the CETA manual cart along the rail while Apt holds onto the back of the cart. The test will determine how difficult it is to maneuver cargo in such a manner when it is done in space on STS-37. The goal is to find the best method for astronauts to move around the exterior of Space Station Freedom (SSF).

  18. 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.…

  19. Circulating serovars of Leptospira in cart horses of central and southern Ethiopia and associated risk factors.

    Science.gov (United States)

    Tsegay, K; Potts, A D; Aklilu, N; Lötter, C; Gummow, B

    2016-03-01

    Little work has been done on diseases of horses in Ethiopia or tropical regions of the world. Yet, Ethiopia has the largest horse population in Africa and their horses play a pivotal role in their economy as traction animals. A serological and questionnaire survey was therefore conducted to determine the circulating serovars of Leptospira and their association with potential risk factors in the cart horse population of Central and Southern Ethiopia. A total of 184 out of 418 cart horses from 13 districts had antibody titres of 1:100 or greater to at least one of 16 serovars of Leptospira species in Central and Southern Ethiopian horses. A significantly higher seropositivity (62.1%) was noted in horses from the highland agroecology followed by midland (44.4%) and lowland (39.8%). Serovar Bratislava (34.5%) was the predominant serovar followed by serovars Djasiman (9.8%), Topaz (5.98%) and Pomona (5.3%). Age and location proved to be associated with seropositive horses with older horses being more commonly affected and the districts of Ziway (Batu) (Apparent Prevalence (AP)=65.5%), Shashemene (AP=48.3%) and Sebeta (AP=41.4%) having the highest prevalence. Multivariable logistic regression found risk factors significantly associated with Leptospira seropositive horses were drinking river water (OR=2.8) and horses 7-12 years old (OR=5) and risk factors specifically associated with serovar Bratislava seropositive horses were drinking river water (OR=2.5), horses ≥13 years (OR=3.5) and the presence of dogs in adjacent neighbouring properties (OR=0.3). Dogs had a protective effect against seropositivity to serovars Bratislava and Djasiman, which may be due to their ability to control rodents. The high seroprevalence confirm that leptospirosis is endemic among horses of Central and Southern Ethiopia. The predominance of serovar Bratislava supports the idea that serovar Bratislava may be adapted to and maintained by the horse population of Central and Southern Ethiopia

  20. 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 ...

  1. 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.

  2. 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.

  3. 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.

  4. The Communities Advancing Resilience Toolkit (CART): an intervention to build community resilience to disasters.

    Science.gov (United States)

    Pfefferbaum, Rose L; Pfefferbaum, Betty; Van Horn, Richard L; Klomp, Richard W; Norris, Fran H; Reissman, Dori B

    2013-01-01

    Community resilience has emerged as a construct to support and foster healthy individual, family, and community adaptation to mass casualty incidents. The Communities Advancing Resilience Toolkit (CART) is a publicly available theory-based and evidence-informed community intervention designed to enhance community resilience by bringing stakeholders together to address community issues in a process that includes assessment, feedback, planning, and action. Tools include a field-tested community resilience survey and other assessment and analytical instruments. The CART process encourages public engagement in problem solving and the development and use of local assets to address community needs. CART recognizes 4 interrelated domains that contribute to community resilience: connection and caring, resources, transformative potential, and disaster management. The primary value of CART is its contribution to community participation, communication, self-awareness, cooperation, and critical reflection and its ability to stimulate analysis, collaboration, skill building, resource sharing, and purposeful action.

  5. Shopper marketing nutrition interventions: Social norms on grocery carts increase produce spending without increasing shopper budgets

    Directory of Open Access Journals (Sweden)

    Collin R. Payne

    2015-01-01

    Conclusions: Descriptive and provincial social norm messages (i.e., on grocery cart placards may be an overlooked tool to increase produce demand without decreasing store profitability and increasing shopper budgets.

  6. Strategies from a nationwide health information technology implementation: the VA CART story.

    Science.gov (United States)

    Box, Tamára L; McDonell, Mary; Helfrich, Christian D; Jesse, Robert L; Fihn, Stephan D; Rumsfeld, John S

    2010-01-01

    The VA Cardiovascular Assessment, Reporting, and Tracking (CART) system is a customized electronic medical record system which provides standardized report generation for cardiac catheterization procedures, serves as a national data repository, and is the centerpiece of a national quality improvement program. Like many health information technology projects, CART implementation did not proceed without some barriers and resistance. We describe the nationwide implementation of CART at the 77 VA hospitals which perform cardiac catheterizations in three phases: (1) strategic collaborations; (2) installation; and (3) adoption. Throughout implementation, success required a careful balance of technical, clinical, and organizational factors. We offer strategies developed through CART implementation which are broadly applicable to technology projects aimed at improving the quality, reliability, and efficiency of health care.

  7. Parallelization characteristics of a three-dimensional whole-core code DeCART

    International Nuclear Information System (INIS)

    Cho, J. Y.; Joo, H.K.; Kim, H. Y.; Lee, J. C.; Jang, M. H.

    2003-01-01

    Neutron transport calculation for three-dimensional amount of computing time but also huge memory. Therefore, whole-core codes such as DeCART need both also parallel computation and distributed memory capabilities. This paper is to implement such parallel capabilities based on MPI grouping and memory distribution on the DeCART code, and then to evaluate the performance by solving the C5G7 three-dimensional benchmark and a simplified three-dimensional SMART core problem. In C5G7 problem with 24 CPUs, a speedup of maximum 22 is obtained on IBM regatta machine and 21 on a LINUX cluster for the MOC kernel, which indicates good parallel performance of the DeCART code. The simplified SMART problem which need about 11 GBytes memory with one processors requires about 940 MBytes, which means that the DeCART code can now solve large core problems on affordable LINUX clusters

  8. Phase I Escalating-Dose Trial of CAR-T Therapy Targeting CEA+ Metastatic Colorectal Cancers.

    Science.gov (United States)

    Zhang, Chengcheng; Wang, Zhe; Yang, Zhi; Wang, Meiling; Li, Shiqi; Li, Yunyan; Zhang, Rui; Xiong, Zhouxing; Wei, Zhihao; Shen, Junjie; Luo, Yongli; Zhang, Qianzhen; Liu, Limei; Qin, Hong; Liu, Wei; Wu, Feng; Chen, Wei; Pan, Feng; Zhang, Xianquan; Bie, Ping; Liang, Houjie; Pecher, Gabriele; Qian, Cheng

    2017-05-03

    Chimeric antigen receptor T (CAR-T) cells have shown promising efficacy in treatment of hematological malignancies, but its applications in solid tumors need further exploration. In this study, we investigated CAR-T therapy targeting carcino-embryonic antigen (CEA)-positive colorectal cancer (CRC) patients with metastases to evaluate its safety and efficacy. Five escalating dose levels (DLs) (1 × 10 5 to 1 × 10 8 /CAR + /kg cells) of CAR-T were applied in 10 CRC patients. Our data showed that severe adverse events related to CAR-T therapy were not observed. Of the 10 patients, 7 patients who experienced progressive disease (PD) in previous treatments had stable disease after CAR-T therapy. Two patients remained with stable disease for more than 30 weeks, and two patients showed tumor shrinkage by positron emission tomography (PET)/computed tomography (CT) and MRI analysis, respectively. Decline of serum CEA level was apparent in most patients even in long-term observation. Furthermore, we observed persistence of CAR-T cells in peripheral blood of patients receiving high doses of CAR-T therapy. Importantly, we observed CAR-T cell proliferation especially in patients after a second CAR-T therapy. Taken together, we demonstrated that CEA CAR-T cell therapy was well tolerated in CEA + CRC patients even in high doses, and some efficacy was observed in most of the treated patients. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

  9. Anthelmintic Resistance of Strongyle Nematodes to Ivermectin and Fenbendazole on Cart Horses in Gondar, Northwest Ethiopia

    OpenAIRE

    Seyoum, Zewdu; Zewdu, Alemu; Dagnachew, Shimelis; Bogale, Basazinew

    2017-01-01

    A study was conducted from November 2015 to April 2016 to determine fenbendazole and ivermectin resistance status of intestinal nematodes of cart horses in Gondar, Northwest Ethiopia. Forty-five strongyle infected animals were used for this study. The animals were randomly allocated into three groups (15 horses per group). Group I was treated with fenbendazole and Group II with ivermectin and Group III was left untreated. Faecal samples were collected from each cart horse before and after tre...

  10. 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...

  11. 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...

  12. Evaluation of solar-assisted, electric and gas golf carts, Bathurst Glen golf course, Richmond Hill, Ontario

    International Nuclear Information System (INIS)

    2010-08-01

    Municipalities try to limit air pollution resulting from the use of small gasoline engines. Indeed, these engines participate in the smog and greenhouse gas (GHG) emissions and they present operating costs more important than electric equivalents. The potential positive impacts of the use of electric or solar electric golf carts instead of gasoline carts are analyzed through a study that compares two solar-assisted electric golf carts, two standard electric golf carts and two gas-powered golf carts. The energy use and related Co2 emissions, the dependability, and the relative costs were evaluated and Golfer preference was also considered thanks to a feedback survey. The comparison between the solar-assisted and the standard electric carts was made on the basis of electricity measures at three points: alternating current (AC) electricity taken from the grid, direct current (DC) electricity flowing into and out of the batteries, and DC electricity generated by the solar panels. The data collected during this study suggested that other factors associated with cart condition or driver behaviours can be more important than the solar panels in determining overall energy consumption. Choosing an area with full sun exposure to install the solar panel and connecting directly to the grid would also maximize generation potential. The comparison of performance between electric carts and gas carts showed the most considerable positive findings. Indeed, fuel costs and emissions are significantly lower in the case of the electric carts, which also present a better fuel efficiency. Switching the 20 percent of gas-powered carts counted within a 100 km radius of Toronto with electric carts could be comparable to removing 155 mid-sized gasoline cars of the road. The electric golf carts present many important financial and environmental benefits when compared to gas carts. The performance is marginally enhanced with the use of solar panels on electric carts and the date collected from

  13. CAR-T Cells: A Systematic Review and Mixed Methods Analysis of the Clinical Trial Landscape.

    Science.gov (United States)

    Pettitt, David; Arshad, Zeeshaan; Smith, James; Stanic, Tijana; Holländer, Georg; Brindley, David

    2018-02-07

    CAR-T cells are a promising new therapy that offer significant advantages compared with conventional immunotherapies. This systematic review and clinical trial landscape identifies and critiques published CAR-T cell clinical trials and examines the critical factors required to enable CAR-T cells to become a standard therapy. A review of the literature was conducted to identify suitable studies from the MEDLINE and Ovid bibliographic databases. The literature and database searches identified 20 studies for inclusion. The average number of participants per clinical trial examined was 11 patients. All studies included in this systematic review investigated CAR-T cells and were prospective, uncontrolled clinical studies. Leukemia is the most common cancer subtype and accounts for 57.4% (n = 120) of disease indications. The majority of studies used an autologous cell source (85%, n = 17) rather than an allogeneic cell source. Translational challenges encompass technical considerations relating to CAR-T cell development, manufacturing practicability, clinical trial approaches, CAR-T cell quality and persistence, and patient management. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

  14. Cocaine-and Amphetamine Regulated Transcript (CART) Peptide Is Expressed in Precursor Cells and Somatotropes of the Mouse Pituitary Gland

    Science.gov (United States)

    Mortensen, Amanda H.

    2016-01-01

    Cocaine-and Amphetamine Regulated Transcript (CART) peptide is expressed in the brain, endocrine and neuroendocrine systems and secreted into the serum. It is thought to play a role in regulation of hypothalamic pituitary functions. Here we report a spatial and temporal analysis of Cart expression in the pituitaries of adult and developing normal and mutant mice with hypopituitarism. We found that Prop1 is not necessary for initiation of Cart expression in the fetal pituitary at e14.5, but it is required indirectly for maintenance of Cart expression in the postnatal anterior pituitary gland. Pou1f1 deficiency has no effect on Cart expression before or after birth. There is no 1:1 correspondence between CART and any particular cell type. In neonates, CART is detected primarily in non-proliferating, POU1F1-positive cells. CART is also found in some cells that express TSH and GH suggesting a correspondence with committed progenitors of the POU1F1 lineage. In summary, we have characterized the normal temporal and cell specific expression of CART in mouse development and demonstrate that postnatal CART expression in the pituitary gland requires PROP1. PMID:27685990

  15. Cocaine-and Amphetamine Regulated Transcript (CART Peptide Is Expressed in Precursor Cells and Somatotropes of the Mouse Pituitary Gland.

    Directory of Open Access Journals (Sweden)

    Amanda H Mortensen

    Full Text Available Cocaine-and Amphetamine Regulated Transcript (CART peptide is expressed in the brain, endocrine and neuroendocrine systems and secreted into the serum. It is thought to play a role in regulation of hypothalamic pituitary functions. Here we report a spatial and temporal analysis of Cart expression in the pituitaries of adult and developing normal and mutant mice with hypopituitarism. We found that Prop1 is not necessary for initiation of Cart expression in the fetal pituitary at e14.5, but it is required indirectly for maintenance of Cart expression in the postnatal anterior pituitary gland. Pou1f1 deficiency has no effect on Cart expression before or after birth. There is no 1:1 correspondence between CART and any particular cell type. In neonates, CART is detected primarily in non-proliferating, POU1F1-positive cells. CART is also found in some cells that express TSH and GH suggesting a correspondence with committed progenitors of the POU1F1 lineage. In summary, we have characterized the normal temporal and cell specific expression of CART in mouse development and demonstrate that postnatal CART expression in the pituitary gland requires PROP1.

  16. Intermediate transport in Southeast Asia. [Carts, cycles, mini-buses

    Energy Technology Data Exchange (ETDEWEB)

    Meier, A.K.

    1977-06-01

    Traffic flows through the streets of Southeast Asian countries even though they are used for almost all aspects of human and animal existence. The carts, bicycles, tricycles, and motorcycles, motorized three-wheelers, mini-buses are the so-called intermediate-transport vehicles. It is upon this group of vehicles that a culture--constrained by its own unique economic, environmental, and technological factors--exerts its influence most directly toward the solution of the transport problem. Transportation fills more service roles in Southeast Asian cities than in Western cities. Communication facilities such as telephones and postal services are notoriously unreliable. The personal encounter is all important in social and business interactions in Southeast Asia. Each of the transport modes is examined in view of design and use in a number of specific cultural settings for the countries in Southeast Asia. Present use of intermediate transport in developed countries is discussed briefly, and its further development predicted--pointing out the health and conservation advantages. (MCW)

  17. Motion sickness in ancient China: Seasickness and cart-sickness.

    Science.gov (United States)

    Brandt, Thomas; Bauer, Matthias; Benson, Judy; Huppert, Doreen

    2016-07-19

    To find and analyze descriptions of motion sickness in Chinese historical sources. Databases and dictionaries were searched for various terms for seasickness and travel sickness, which were then entered into databases of full texts allowing selection of relevant passages from about the third to the 19th century ad. Already in 300 ad the Chinese differentiated cart-sickness, particularly experienced by persons from the arid north of China, from a ship-illness experienced by persons from the south, where rivers were important for transportation and travel. In the Middle Ages, a third form of motion sickness was called litter-influence experienced by persons transported in a bed suspended between 2 long poles. The ancient Chinese recognized the particular susceptibility of children to motion sickness. Therapeutic recommendations include drinking the urine of young boys, swallowing white sand-syrup, collecting water drops from a bamboo stick, or hiding some earth from the middle of the kitchen hearth under the hair. The Chinese medical classics distinguished several forms of travel sickness, all of which had their own written characters. The pathophysiologic mechanism was explained by the medicine of correspondences, which was based on malfunctions within the body, its invasion by external pathogens like wind, or the deficit or surfeit of certain bodily substances such as the life force Qi. The concept of motion as the trigger of sickness initially appeared in a chapter on warding off the influence of demons and corpses, e.g., ancient magic and beliefs. © 2016 American Academy of Neurology.

  18. Multidisciplinary approach to converting power chair into motorized prone cart.

    Science.gov (United States)

    Brose, Steven W; Wali, Eisha

    2014-01-01

    Pressure ulcers remain a major source of morbidity and mortality in veterans with neurologic impairment. Management of pressure ulcers typically involves pressure relief over skin regions containing wounds, but this can lead to loss of mobility and independence when the wounds are located in regions that receive pressure from sitting. An innovative, low-cost, multidisciplinary effort was undertaken to maximize quality of life in a veteran with a thoracic-4 level complete spinal cord injury and a stage 4 ischial wound. The person's power wheelchair was converted into a motorized prone cart, allowing navigation of the Department of Veterans Affairs spinal cord injury hospital ward and improved socialization while relieving pressure on the wound. Physical and occupational therapy assisted with the reconfiguration of the power chair and verified safe transfers into the chair and driving of the device. Psychology verified positive psychosocial benefit, while nursing and physician services verified an absence of unwanted pain or skin injury resulting from use of the device. Further investigation of ways to apply this technique is warranted to improve the quality of life of persons with pressure ulcers.

  19. To Love—To Live: Barrow and Cart

    Directory of Open Access Journals (Sweden)

    Lisa McDonald

    2013-02-01

    Full Text Available From the residue of meaning, an ensemble of shadows. From the glint of souvenir, pliable impressions. In this paper, we work a poetics of encounter, of being, keeping, homage, of paying homage to fragility, to object and to interspecies—ways are found to engage motion from within and around co-extensive bodies. With the consolation of images, we follow the terse rhythms of routine and street where dwelling is a case of affective dissent. Zones of departure appear through testimony as well as chance, taking their own form. A footfall brings us as observers into quiet spaces which refuse self-estrangement as we travel by way of an unquiet ground. Breath, respiration, aspiration. Precipitation. Sculptures of mist are also the language of lives, of kinship between object, footfall and air. A language of brackets, questions, ellipses. There may be a man, a dog, a barrow. There may be a woman, a cart. Air. How shall this image be made?

  20. Demographic and financial characteristics of school districts with low and high à la Carte sales in rural Kansas Public Schools.

    Science.gov (United States)

    Nollen, Nicole L; Kimminau, Kim S; Nazir, Niaman

    2011-06-01

    Reducing à la carte items in schools-foods and beverages sold outside the reimbursable meals program-can have important implications for childhood obesity. However, schools are reluctant to reduce à la carte offerings because of the impact these changes could have on revenue. Some foodservice programs operate with limited à la carte sales, but little is known about these programs. This secondary data analysis compared rural and urban/suburban school districts with low and high à la carte sales. Foodservice financial records (2007-2008) were obtained from the Kansas State Department of Education for all public K-12 school districts (n=302). χ² and t tests were used to examine the independent association of variables to à la carte sales. A multivariate model was then constructed of the factors most strongly associated with low à la carte sales. In rural districts with low à la carte sales, lunch prices and participation were higher, lunch costs and à la carte quality were lower, and fewer free/reduced price lunches were served compared to rural districts with high à la carte sales. Lunch price (odds ratio=1.2; 95% confidence interval, 1.1 to 1.4) and free/reduced price lunch participation (odds ratio=3.0; 95% confidence interval, 1.0 to 9.8) remained in the multivariate model predicting low à la carte sales. No differences were found between urban/suburban districts with low and high à la carte sales. Findings highlight important factors to maintaining low à la carte sales. Schools should consider raising lunch prices and increasing meal participation rates as two potential strategies for reducing the sale of à la carte items without compromising foodservice revenue. Copyright © 2011 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

  1. CART (cocaine- and amphetamine-regulated transcript) peptide specific binding sites in PC12 cells have characteristics of CART peptide receptors

    Czech Academy of Sciences Publication Activity Database

    Nagelová, Veronika; Pirnik, Z.; Železná, Blanka; Maletínská, Lenka

    2014-01-01

    Roč. 1547, Feb 14 (2014), s. 16-24 ISSN 0006-8993 R&D Projects: GA ČR GAP303/10/1368 Institutional support: RVO:61388963 Keywords : CART peptide * PC12 cell * differentiation * binding * signaling * c-Jun Subject RIV: CE - Biochemistry Impact factor: 2.843, year: 2014

  2. CAR-T cells and allogeneic hematopoietic stem cell transplantation for relapsed/refractory B-cell acute lymphoblastic leukemia.

    Science.gov (United States)

    Liu, Jun; Zhang, Xi; Zhong, Jiang F; Zhang, Cheng

    2017-10-01

    Relapsed/refractory acute lymphoblastic leukemia (ALL) has a low remission rate after chemotherapy, a high relapse rate and poor long-term survival even when allogeneic hematopoietic stem cell transplantation (allo-HSCT) is performed. Chimeric antigen receptors redirected T cells (CAR-T cells) can enhance disease remission with a favorable outcome for relapsed/refractory ALL, though some cases quickly relapsed after CAR-T cell treatment. Thus, treatment with CAR-T cells followed by allo-HSCT may be the best way to treat relapsed/refractory ALL. In this review, we first discuss the different types of CAR-T cells. We then discuss the treatment of relapsed/refractory ALL using only CAR-T cells. Finally, we discuss the use of CAR-T cells, followed by allo-HSCT, for the treatment of relapsed/refractory ALL.

  3. 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...

  4. 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 ...

  5. 241-AZ-101 Mixer Pump Demonstration Test Gamma Cart Acceptance Test Procedure and Quality Test Plan (ATP and QTP)

    International Nuclear Information System (INIS)

    WHITE, D.A.

    2000-01-01

    Shop test of the sludge mobilization cart system to be used in the AZ-101 Mixer Pump Demonstration Test Tests hardware and software. This procedure involves testing the Instrumentation involved with the Gamma Cart System, local and remote, including depth indicators, speed controls, interface to data acquisition software and the raising and lowering functions. This Procedure will be performed twice, once for each Gamma Cart System. This procedure does not test the accuracy of the data acquisition software

  6. 241-AZ-101 Mixer Pump Demonstration Test Gamma Cart Acceptance Test Procedure and Quality Test Plan (ATP and QTP)

    International Nuclear Information System (INIS)

    WHITE, D.A.

    2000-01-01

    Shop Test of the Gamma Cart System to be used in the AZ-101 Mixer Pump Demonstration Test. Tests hardware and software. This procedure involves testing the Instrumentation involved with the Gamma Cart System, local and remote, including: depth indicators, speed controls, interface to data acquisition software and the raising and lowering functions. This Procedure will be performed twice, once for each Gamma Cart System. This procedure does not test the accuracy of the data acquisition software

  7. A Novel Clinical Prediction Model for Prognosis in Malignant Pleural Mesothelioma Using Decision Tree Analysis.

    Science.gov (United States)

    Brims, Fraser J H; Meniawy, Tarek M; Duffus, Ian; de Fonseka, Duneesha; Segal, Amanda; Creaney, Jenette; Maskell, Nicholas; Lake, Richard A; de Klerk, Nick; Nowak, Anna K

    2016-04-01

    Malignant pleural mesothelioma (MPM) is a rare cancer with a heterogeneous prognosis. Prognostic models are not widely utilized clinically. Classification and regression tree (CART) analysis examines the interaction of multiple variables with a given outcome. Between 2005 and 2014, all cases with pathologically confirmed MPM had routinely available histological, clinical, and laboratory characteristics recorded. Classification and regression tree analysis was performed using 29 variables with 18-month survival as the dependent variable. Risk groups were refined according to survival and clinical characteristics. The model was then tested on an external international cohort. A total of 482 cases were included in the derivation cohort; the median survival was 12.6 months, and the median age was 69 years. The model defined four risk groups with clear survival differences (p loss. The group with the best survival at 18 months (86.7% alive, median survival 34.0 months, termed risk group 1) had no weight loss, a hemoglobin level greater than 153 g/L, and a serum albumin level greater than 43 g/L. The group with the worst survival (0% alive, median survival 7.5 months, termed risk group 4d) had weight loss, a performance score of 0 or 1, and sarcomatoid histological characteristics. The C-statistic for the model was 0.761, and the sensitivity was 94.5%. Validation on 174 external cases confirmed the model's ability to discriminate between risk groups in an alternative data set with fair performance (C-statistic 0.68). We have developed and validated a simple, clinically relevant model to reliably discriminate patients at high and lower risk of death using routinely available variables from the time of diagnosis in unselected populations of patients with MPM. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  8. 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 ...

  9. 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 ...

  10. 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 ...

  11. 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.

  12. 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.

  13. 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…

  14. 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...

  15. 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.

  16. Parallelization of a three-dimensional whole core transport code DeCART

    Energy Technology Data Exchange (ETDEWEB)

    Jin Young, Cho; Han Gyu, Joo; Ha Yong, Kim; Moon-Hee, Chang [Korea Atomic Energy Research Institute, Yuseong-gu, Daejon (Korea, Republic of)

    2003-07-01

    Parallelization of the DeCART (deterministic core analysis based on ray tracing) code is presented that reduces the computational burden of the tremendous computing time and memory required in three-dimensional whole core transport calculations. The parallelization employs the concept of MPI grouping and the MPI/OpenMP mixed scheme as well. Since most of the computing time and memory are used in MOC (method of characteristics) and the multi-group CMFD (coarse mesh finite difference) calculation in DeCART, variables and subroutines related to these two modules are the primary targets for parallelization. Specifically, the ray tracing module was parallelized using a planar domain decomposition scheme and an angular domain decomposition scheme. The parallel performance of the DeCART code is evaluated by solving a rodded variation of the C5G7MOX three dimensional benchmark problem and a simplified three-dimensional SMART PWR core problem. In C5G7MOX problem with 24 CPUs, a speedup of maximum 21 is obtained on an IBM Regatta machine and 22 on a LINUX Cluster in the MOC kernel, which indicates good parallel performance of the DeCART code. In the simplified SMART problem, the memory requirement of about 11 GBytes in the single processor cases reduces to 940 Mbytes with 24 processors, which means that the DeCART code can now solve large core problems with affordable LINUX clusters. (authors)

  17. CAR-T cell therapy in gastrointestinal tumors and hepatic carcinoma: From bench to bedside.

    Science.gov (United States)

    Zhang, Qi; Zhang, Zimu; Peng, Meiyu; Fu, Shuyu; Xue, Zhenyi; Zhang, Rongxin

    2016-01-01

    The chimeric antigen receptor (CAR) is a genetically engineered receptor that combines a scFv domain, which specifically recognizes the tumor-specific antigen, with T cell activation domains. CAR-T cell therapies have demonstrated tremendous efficacy against hematologic malignancies in many clinical trials. Recent studies have extended these efforts to the treatment of solid tumors. However, the outcomes of CAR-T cell therapy for solid tumors are not as remarkable as the outcomes have been for hematologic malignancies. A series of hurdles has arisen with respect to CAR-T cell-based immunotherapy, which needs to be overcome to target solid tumors. The major challenge for CAR-T cell therapy in solid tumors is the selection of the appropriate specific antigen to demarcate the tumor from normal tissue. In this review, we discuss the application of CAR-T cells to gastrointestinal and hepatic carcinomas in preclinical and clinical research. Furthermore, we analyze the usefulness of several specific markers in the study of gastrointestinal tumors and hepatic carcinoma.

  18. Cancer Immunotherapy Using CAR-T Cells: From the Research Bench to the Assembly Line.

    Science.gov (United States)

    Gomes-Silva, Diogo; Ramos, Carlos A

    2018-02-01

    The focus of cancer treatment has recently shifted toward targeted therapies, including immunotherapy, which allow better individualization of care and are hoped to increase the probability of success for patients. Specifically, T cells genetically modified to express chimeric antigen receptors (CARs; CAR-T cells) have generated exciting results. Recent clinical successes with this cutting-edge therapy have helped to push CAR-T cells toward approval for wider use. However, several limitations need to be addressed before the widespread use of CAR-T cells as a standard treatment. Here, a succinct background on adoptive T-cell therapy (ATCT)is given. A brief overview of the structure of CARs, how they are introduced into T cells, and how CAR-T cell expansion and selection is achieved in vitro is then presented. Some of the challenges in CAR design are discussed, as well as the difficulties that arise in large-scale CAR-T cell manufacture that will need to be addressed to achieve successful commercialization of this type of cell therapy. Finally, developments already on the horizon are discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. The development of CAR design for tumor CAR-T cell therapy.

    Science.gov (United States)

    Xu, Dandan; Jin, Guoliang; Chai, Dafei; Zhou, Xiaowan; Gu, Weiyu; Chong, Yanyun; Song, Jingyuan; Zheng, Junnian

    2018-03-02

    In recent years, the chimeric antigen receptor modified T cells (Chimeric antigen receptor T cells, CAR-T) immunotherapy has developed rapidly, which has been considered the most promising therapy. Efforts to enhance the efficacy of CAR-based anti-tumor therapy have been made, such as the improvement of structures of CAR-T cells, including the development of extracellular antigen recognition receptors, intracellular co-stimulatory molecules and the combination application of CARs and synthetic small molecules. In addition, effects on the function of the CAR-T cells that the space distance between the antigen binding domains and tumor targets and the length of the spacer domains have are also being investigated. Given the fast-moving nature of this field, it is necessary to make a summary of the development of CAR-T cells. In this review, we mainly focus on the present design strategies of CAR-T cells with the hope that they can provide insights to increase the anti-tumor efficacy and safety.

  20. CD47-CAR-T Cells Effectively Kill Target Cancer Cells and Block Pancreatic Tumor Growth.

    Science.gov (United States)

    Golubovskaya, Vita; Berahovich, Robert; Zhou, Hua; Xu, Shirley; Harto, Hizkia; Li, Le; Chao, Cheng-Chi; Mao, Mike Ming; Wu, Lijun

    2017-10-21

    CD47 is a glycoprotein of the immunoglobulin superfamily that is often overexpressed in different types of hematological and solid cancer tumors and plays important role in blocking phagocytosis, increased tumor survival, metastasis and angiogenesis. In the present report, we designed CAR (chimeric antigen receptor)-T cells that bind CD47 antigen. We used ScFv (single chain variable fragment) from mouse CD47 antibody to generate CD47-CAR-T cells for targeting different cancer cell lines. CD47-CAR-T cells effectively killed ovarian, pancreatic and other cancer cells and produced high level of cytokines that correlated with expression of CD47 antigen. In addition, CD47-CAR-T cells significantly blocked BxPC3 pancreatic xenograft tumor growth after intratumoral injection into NSG mice. Moreover, we humanized mouse CD47 ScFv and showed that it effectively bound CD47 antigen. The humanized CD47-CAR-T cells also specifically killed ovarian, pancreatic, and cervical cancer cell lines and produced IL-2 that correlated with expression of CD47. Thus, CD47-CAR-T cells can be used as a novel cellular therapeutic agent for treating different types of cancer.

  1. Active-passive vibration absorber of beam-cart-seesaw system with piezoelectric transducers

    Science.gov (United States)

    Lin, J.; Huang, C. J.; Chang, Julian; Wang, S.-W.

    2010-09-01

    In contrast with fully controllable systems, a super articulated mechanical system (SAMS) is a controlled underactuated mechanical system in which the dimensions of the configuration space exceed the dimensions of the control input space. The objectives of the research are to develop a novel SAMS model which is called beam-cart-seesaw system, and renovate a novel approach for achieving a high performance active-passive piezoelectric vibration absorber for such system. The system consists of two mobile carts, which are coupled via rack and pinion mechanics to two parallel tracks mounted on pneumatic rodless cylinders. One cart carries an elastic beam, and the other cart acts as a counterbalance. One adjustable counterweight mass is also installed underneath the seesaw to serve as a passive damping mechanism to absorb impact and shock energy. The motion and control of a Bernoulli-Euler beam subjected to the modified cart/seesaw system are analyzed first. Moreover, gray relational grade is utilized to investigate the sensitivity of tuning the active proportional-integral-derivative (PID) controller to achieve desired vibration suppression performance. Consequently, it is shown that the active-passive vibration absorber can not only provide passive damping, but can also enhance the active action authority. The proposed software/hardware platform can also be profitable for the standardization of laboratory equipment, as well as for the development of entertainment tools.

  2. Otolaryngology Consult Carts: Maximizing Patient Care, Surgeon Efficiency, and Cost Containment.

    Science.gov (United States)

    Royer, Mark C; Royer, Allison K

    2015-11-01

    The objective of this study was to develop an otolaryngology consult cart system to ensure prompt delivery to the bedside of all the unique equipment and medications required for emergent and urgent otolaryngology consults. An otolaryngology practice responsible for emergency room and hospital consult coverage sought to create a cart containing all equipment, medications, and supplies for otolaryngology consults. Meetings with hospital administration and emergency room, nursing, pharmacy, central processing, and operating room staff were held to develop a system for the emergent delivery of the cart to the needed location, sterilization and restocking of equipment between uses, and appropriate billing of supplies. Two months were required from conception to implementation. All equipment was purchased new, including flexible scopes and headlights. The cart is sterilized, restocked, and maintained by central processing after each use. The equipment is available to handle all airway emergencies as well as all common otolaryngology consults and is delivered bedside in less than 5 minutes. The development of a self-contained otolaryngology consult cart requires coordination with a wide variety of hospital departments. This system, while requiring initial monetary and time investment, has resulted in improved patient care, cost containment, and surgeon convenience. © The Author(s) 2015.

  3. 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

  4. Golf cart prototype development and navigation simulation using ROS and Gazebo

    Directory of Open Access Journals (Sweden)

    Shimchik Ilya

    2016-01-01

    Full Text Available This paper presents our approach to development of an autonomous golf cart, which will navigate in inaccessible by regular vehicles private areas. For this purpose, we have built a virtual golf course terrain and golf cart model in Gazebo, selected and modernized ROS-based packages in order to use them with Ackermann steering vehicle simulation. To verify our simulation and algorithms, we navigated the golf cart model from one golf hole to another within a virtual 3D golf course. For the real world algorithms’ verification, we developed a small-size vehicle prototype based on Traxxas radio-controlled car model, which is equipped with an on-board controller and sensors. The autonomous navigation of Traxxas-based vehicle prototype has been tested in indoor environment, where it utilized sensory data about environment and vehicle states, and performed localization, optimal trajectory computation and dynamic obstacles’ recognition with adjusting the route in real time.

  5. Hurdles of CAR-T cell-based cancer immunotherapy directed against solid tumors.

    Science.gov (United States)

    Zhang, Bing-Lan; Qin, Di-Yuan; Mo, Ze-Ming; Li, Yi; Wei, Wei; Wang, Yong-Sheng; Wang, Wei; Wei, Yu-Quan

    2016-04-01

    Recent reports on the impressive efficacy of chimeric antigen receptor (CAR)-modified T cells against hematologic malignancies have inspired oncologists to extend these efforts for the treatment of solid tumors. Clinical trials of CAR-T-based cancer immunotherapy for solid tumors showed that the efficacies are not as remarkable as in the case of hematologic malignancies. There are several challenges that researchers must face when treating solid cancers with CAR-T cells, these include choosing an ideal target, promoting efficient trafficking and infiltration, overcoming the immunosuppressive microenvironment, and avoiding associated toxicity. In this review, we discuss the obstacles imposed by solid tumors on CAR-T cell-based immunotherapy and strategies adopted to improve the therapeutic potential of this approach. Continued investigations are necessary to improve therapeutic outcomes and decrease the adverse effects of CAR-T cell therapy in patients with solid malignancies in the future.

  6. New Approaches in CAR-T Cell Immunotherapy for Breast Cancer.

    Science.gov (United States)

    Wang, Jinghua; Zhou, Penghui

    2017-01-01

    Despite significant advances in surgery, chemotherapy, radiotherapy, endocrine therapy, and molecular-targeted therapy, breast cancer remains the leading cause of death from malignant tumors among women. Immunotherapy has recently become a critical component of breast cancer treatment with encouraging activity and mild safety profiles. CAR-T therapy using genetically modifying T cells with chimeric antigen receptors (CAR) is the most commonly used approach to generate tumor-specific T cells. It has shown good curative effect for a variety of malignant diseases, especially for hematological malignancies. In this review, we briefly introduce the history and the present state of CAR research. Then we discuss the barriers of solid tumors for CARs application and possible strategies to improve therapeutic response with a focus on breast cancer. At last, we outlook the future directions of CAR-T therapy including managing toxicities and developing universal CAR-T cells.

  7. Chimeric-antigen receptor T (CAR-T) cell therapy for solid tumors: challenges and opportunities.

    Science.gov (United States)

    Xia, An-Liang; Wang, Xiao-Chen; Lu, Yi-Jun; Lu, Xiao-Jie; Sun, Beicheng

    2017-10-27

    Chimeric antigen receptor (CAR)-engineered T cells (CAR-T cells) have been shown to have unprecedented efficacy in B cell malignancies, most notably in B cell acute lymphoblastic leukemia (B-ALL) with up to a 90% complete remission rate using anti-CD19 CAR-T cells. However, CAR T-cell therapy for solid tumors currently is faced with numerous challenges such as physical barriers, the immunosuppressive tumor microenvironment and the specificity and safety. The clinical results in solid tumors have been much less encouraging, with multiple cases of toxicity and a lack of therapeutic response. In this review, we will discuss the current stats and challenges of CAR-T cell therapy for solid tumors, and propose possibl e solutions and future perspectives.

  8. The Coach-Athlete Relationship Questionnaire (CART-Q): development and initial validation.

    Science.gov (United States)

    Jowett, Sophia; Ntoumanis, Nikos

    2004-08-01

    The purpose of the present study was to develop and validate a self-report instrument that measures the nature of the coach-athlete relationship. Jowett et al.'s (Jowett & Meek, 2000; Jowett, in press) qualitative case studies and relevant literature were used to generate items for an instrument that measures affective, cognitive, and behavioral aspects of the coach-athlete relationship. Two studies were carried out in an attempt to assess content, predictive, and construct validity, as well as internal consistency, of the Coach-Athlete Relationship Questionnaire (CART-Q), using two independent British samples. Principal component analysis and confirmatory factor analysis were used to reduce the number of items, identify principal components, and confirm the latent structure of the CART-Q. Results supported the multidimensional nature of the coach-athlete relationship. The latent structure of the CART-Q was underlined by the latent variables of coaches' and athletes' Closeness (emotions), Commitment (cognitions), and Complementarity (behaviors).

  9. Depletion methodology in the 3-D whole core transport code DeCART

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kang Seog; Cho, Jin Young; Zee, Sung Quun

    2005-02-01

    Three dimensional whole-core transport code DeCART has been developed to include a characteristics of the numerical reactor to replace partly the experiment. This code adopts the deterministic method in simulating the neutron behavior with the least assumption and approximation. This neutronic code is also coupled with the thermal hydraulic code CFD and the thermo mechanical code to simulate the combined effects. Depletion module has been implemented in DeCART code to predict the depleted composition in the fuel. The exponential matrix method of ORIGEN-2 has been used for the depletion calculation. The library of including decay constants, yield matrix and others has been used and greatly simplified for the calculation efficiency. This report summarizes the theoretical backgrounds and includes the verification of the depletion module in DeCART by performing the benchmark calculations.

  10. 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.

  11. Cart'Eaux: an automatic mapping procedure for wastewater networks using machine learning and data mining

    Science.gov (United States)

    Bailly, J. S.; Delenne, C.; Chahinian, N.; Bringay, S.; Commandré, B.; Chaumont, M.; Derras, M.; Deruelle, L.; Roche, M.; Rodriguez, F.; Subsol, G.; Teisseire, M.

    2017-12-01

    In France, local government institutions must establish a detailed description of wastewater networks. The information should be available, but it remains fragmented (different formats held by different stakeholders) and incomplete. In the "Cart'Eaux" project, a multidisciplinary team, including an industrial partner, develops a global methodology using Machine Learning and Data Mining approaches applied to various types of large data to recover information in the aim of mapping urban sewage systems for hydraulic modelling. Deep-learning is first applied using a Convolution Neural Network to localize manhole covers on 5 cm resolution aerial RGB images. The detected manhole covers are then automatically connected using a tree-shaped graph constrained by industry rules. Based on a Delaunay triangulation, connections are chosen to minimize a cost function depending on pipe length, slope and possible intersection with roads or buildings. A stochastic version of this algorithm is currently being developed to account for positional uncertainty and detection errors, and generate sets of probable networks. As more information is required for hydraulic modeling (slopes, diameters, materials, etc.), text data mining is used to extract network characteristics from data posted on the Web or available through governmental or specific databases. Using an appropriate list of keywords, the web is scoured for documents which are saved in text format. The thematic entities are identified and linked to the surrounding spatial and temporal entities. The methodology is developed and tested on two towns in southern France. The primary results are encouraging: 54% of manhole covers are detected with few false detections, enabling the reconstruction of probable networks. The data mining results are still being investigated. It is clear at this stage that getting numerical values on specific pipes will be challenging. Thus, when no information is found, decision rules will be used to

  12. CAR-T cells: the long and winding road to solid tumors.

    Science.gov (United States)

    D'Aloia, Maria Michela; Zizzari, Ilaria Grazia; Sacchetti, Benedetto; Pierelli, Luca; Alimandi, Maurizio

    2018-02-15

    Adoptive cell therapy of solid tumors with reprogrammed T cells can be considered the "next generation" of cancer hallmarks. CAR-T cells fail to be as effective as in liquid tumors for the inability to reach and survive in the microenvironment surrounding the neoplastic foci. The intricate net of cross-interactions occurring between tumor components, stromal and immune cells leads to an ineffective anergic status favoring the evasion from the host's defenses. Our goal is hereby to trace the road imposed by solid tumors to CAR-T cells, highlighting pitfalls and strategies to be developed and refined to possibly overcome these hurdles.

  13. Incorporation of Immune Checkpoint Blockade into Chimeric Antigen Receptor T Cells (CAR-Ts): Combination or Built-In CAR-T.

    Science.gov (United States)

    Yoon, Dok Hyun; Osborn, Mark J; Tolar, Jakub; Kim, Chong Jai

    2018-01-24

    Chimeric antigen receptor (CAR) T cell therapy represents the first U.S. Food and Drug Administration approved gene therapy and these engineered cells function with unprecedented efficacy in the treatment of refractory CD19 positive hematologic malignancies. CAR translation to solid tumors is also being actively investigated; however, efficacy to date has been variable due to tumor-evolved mechanisms that inhibit local immune cell activity. To bolster the potency of CAR-T cells, modulation of the immunosuppressive tumor microenvironment with immune-checkpoint blockade is a promising strategy. The impact of this approach on hematological malignancies is in its infancy, and in this review we discuss CAR-T cells and their synergy with immune-checkpoint blockade.

  14. Incorporation of Immune Checkpoint Blockade into Chimeric Antigen Receptor T Cells (CAR-Ts: Combination or Built-In CAR-T

    Directory of Open Access Journals (Sweden)

    Dok Hyun Yoon

    2018-01-01

    Full Text Available Chimeric antigen receptor (CAR T cell therapy represents the first U.S. Food and Drug Administration approved gene therapy and these engineered cells function with unprecedented efficacy in the treatment of refractory CD19 positive hematologic malignancies. CAR translation to solid tumors is also being actively investigated; however, efficacy to date has been variable due to tumor-evolved mechanisms that inhibit local immune cell activity. To bolster the potency of CAR-T cells, modulation of the immunosuppressive tumor microenvironment with immune-checkpoint blockade is a promising strategy. The impact of this approach on hematological malignancies is in its infancy, and in this review we discuss CAR-T cells and their synergy with immune-checkpoint blockade.

  15. 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...

  16. 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....

  17. 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.

  18. Risk Factors for Non-Adherence to cART in Immigrants with HIV Living in the Netherlands: Results from the ROtterdam ADherence (ROAD Project.

    Directory of Open Access Journals (Sweden)

    Sabrina K Been

    Full Text Available In the Netherlands, immigrant people living with HIV (PLWH have poorer psychological and treatment outcomes than Dutch PLWH. This cross-sectional field study examined risk factors for non-adherence to combination Antiretroviral Therapy (cART among immigrant PLWH. First and second generation immigrant PLWH attending outpatient clinics at two HIV-treatment centers in Rotterdam were selected for this study. Socio-demographic and clinical characteristics for all eligible participants were collected from an existing database. Trained interviewers subsequently completed questionnaires together with consenting participants (n = 352 to gather additional data on socio-demographic characteristics, psychosocial variables, and self-reported adherence to cART. Univariable and multivariable logistic regression analyses were conducted among 301 participants who had used cART ≥6 months prior to inclusion. Independent risk factors for self-reported non-adherence were (I not having attended formal education or only primary school (OR = 3.25; 95% CI: 1.28-8.26, versus University, (II experiencing low levels of social support (OR = 2.56; 95% CI: 1.37-4.82, and (III reporting low treatment adherence self-efficacy (OR = 2.99; 95% CI: 1.59-5.64. Additionally, HIV-RNA >50 copies/ml and internalized HIV-related stigma were marginally associated (P<0.10 with non-adherence (OR = 2.53; 95% CI: 0.91-7.06 and OR = 1.82; 95% CI: 0.97-3.43. The findings that low educational attainment, lack of social support, and low treatment adherence self-efficacy are associated with non-adherence point to the need for tailored supportive interventions. Establishing contact with peer immigrant PLWH who serve as role models might be a successful intervention for this specific population.

  19. Changes in RANKL during the first two years after cART initiation in HIV-infected cART naïve adults

    DEFF Research Database (Denmark)

    Mathiesen, Inger Hee Mabuza; Salem, Mohammad; Gerstoft, Jan

    2017-01-01

    accelerated bone loss could be mediated by increased soluble RANKL (sRANKL) levels associated with CD4+ T cell recovery. METHODS: We used multiplex immunoassays to determine sRANKL and OPG concentrations in plasma from 48 HIV patients at baseline and 12, 24, 48 and 96 weeks after cART initiation. RESULTS......: Soluble RANKL changed significantly over time (overall p = 0.02) with 25% decrease (95% CI: -42 to -5) at week 24 compared to baseline and stabilized at a lower level thereafter. We found no correlation between CD4+ T cell count increment and changes in sRANKL or between percentage change in BMD...... and changes in sRANKL. CONCLUSION: In this study there was no indication that the accelerated bone loss after cART initiation was mediated by early changes in sRANKL due to CD4+ T cell recovery. Future studies should focus on the initial weeks after initiation of cART. TRIAL REGISTRATION: Clinical...

  20. CD19 CAR-T cells of defined CD4+:CD8+ composition in adult B cell ALL patients.

    Science.gov (United States)

    Turtle, Cameron J; Hanafi, Laïla-Aïcha; Berger, Carolina; Gooley, Theodore A; Cherian, Sindhu; Hudecek, Michael; Sommermeyer, Daniel; Melville, Katherine; Pender, Barbara; Budiarto, Tanya M; Robinson, Emily; Steevens, Natalia N; Chaney, Colette; Soma, Lorinda; Chen, Xueyan; Yeung, Cecilia; Wood, Brent; Li, Daniel; Cao, Jianhong; Heimfeld, Shelly; Jensen, Michael C; Riddell, Stanley R; Maloney, David G

    2016-06-01

    T cells that have been modified to express a CD19-specific chimeric antigen receptor (CAR) have antitumor activity in B cell malignancies; however, identification of the factors that determine toxicity and efficacy of these T cells has been challenging in prior studies in which phenotypically heterogeneous CAR-T cell products were prepared from unselected T cells. We conducted a clinical trial to evaluate CD19 CAR-T cells that were manufactured from defined CD4+ and CD8+ T cell subsets and administered in a defined CD4+:CD8+ composition to adults with B cell acute lymphoblastic leukemia after lymphodepletion chemotherapy. The defined composition product was remarkably potent, as 27 of 29 patients (93%) achieved BM remission, as determined by flow cytometry. We established that high CAR-T cell doses and tumor burden increase the risks of severe cytokine release syndrome and neurotoxicity. Moreover, we identified serum biomarkers that allow testing of early intervention strategies in patients at the highest risk of toxicity. Risk-stratified CAR-T cell dosing based on BM disease burden decreased toxicity. CD8+ T cell-mediated anti-CAR transgene product immune responses developed after CAR-T cell infusion in some patients, limited CAR-T cell persistence, and increased relapse risk. Addition of fludarabine to the lymphodepletion regimen improved CAR-T cell persistence and disease-free survival. Immunotherapy with a CAR-T cell product of defined composition enabled identification of factors that correlated with CAR-T cell expansion, persistence, and toxicity and facilitated design of lymphodepletion and CAR-T cell dosing strategies that mitigated toxicity and improved disease-free survival. ClinicalTrials.gov NCT01865617. R01-CA136551; Life Science Development Fund; Juno Therapeutics; Bezos Family Foundation.

  1. 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...

  2. Preconception use of cART by HIV-positive pregnant women increases the risk of infants being born small for gestational age

    NARCIS (Netherlands)

    Snijdewind, Ingrid J. M.; Smit, Colette; Godfried, Mieke H.; Bakker, Rachel; Nellen, Jeannine F. J. B.; Jaddoe, Vincent W. V.; van Leeuwen, Elisabeth; Reiss, Peter; Steegers, Eric A. P.; van der Ende, Marchina E.

    2018-01-01

    Background The benefits of combination anti-retroviral therapy (cART) in HIV-positive pregnant women (improved maternal health and prevention of mother to child transmission [pMTCT]) currently outweigh the adverse effects due to cART. As the variety of cART increases, however, the question arises as

  3. 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

  4. 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

  5. Causes of Death among AIDS Patients after Introduction of Free Combination Antiretroviral Therapy (cART in Three Chinese Provinces, 2010-2011.

    Directory of Open Access Journals (Sweden)

    Liyan Wang

    Full Text Available Although AIDS-related deaths have had significant economic and social impact following an increased disease burden internationally, few studies have evaluated the cause of AIDS-related deaths among patients with AIDS on combination anti-retroviral therapy (cART in China. This study examines the causes of death among AIDS-patients in China and uses a methodology to increase data accuracy compared to the previous studies on AIDS-related mortality in China, that have taken the reported cause of death in the National HIV Registry at face-value.Death certificates/medical records were examined and a cross-sectional survey was conducted in three provinces to verify the causes of death among AIDS patients who died between January 1, 2010 and June 30, 2011. Chi-square analysis was conducted to examine the categorical variables by causes of death and by ART status. Univariate and multivariate logistic regression were used to evaluate factors associated with AIDS-related death versus non-AIDS related death.This study used a sample of 1,109 subjects. The average age at death was 44.5 years. AIDS-related deaths were significantly higher than non-AIDS and injury-related deaths. In the sample, 41.9% (465/1109 were deceased within a year of HIV diagnosis and 52.7% (584/1109 of the deceased AIDS patients were not on cART. For AIDS-related deaths (n = 798, statistically significant factors included CD4 count <200 cells/mm3 at the time of cART initiation (AOR 1.94, 95%CI 1.24-3.05, ART naïve (AOR 1.69, 95%CI 1.09-2.61; p = 0.019 and age <39 years (AOR 2.96, 95%CI 1.77-4.96.For the AIDS patients that were deceased, only those who initiated cART while at a CD4 count ≥200 cells/mm3 were less likely to die from AIDS-related causes compared to those who didn't initiate ART at all.

  6. Anorexigenní neuropeptid CART v regulaci příjmu potravy

    Czech Academy of Sciences Publication Activity Database

    Nagelová, Veronika; Železná, Blanka; Maletínská, Lenka

    2014-01-01

    Roč. 108, č. 4 (2014), s. 354-357 ISSN 0009-2770 R&D Projects: GA ČR GAP303/10/1368 Institutional support: RVO:61388963 Keywords : CART * cocaine and amphetamine regulated transcript * anorexigenic neuropeptide Subject RIV: CE - Biochemistry Impact factor: 0.272, year: 2014

  7. Structure-activity relationship of CART (cocaine- and amphetamine-regulated transcript) peptide fragments

    Czech Academy of Sciences Publication Activity Database

    Maixnerová, Jana; Hlaváček, Jan; Blokešová, Darja; Kowalczyk, W.; Elbert, Tomáš; Šanda, Miloslav; Blechová, Miroslava; Železná, Blanka; Slaninová, Jiřina; Maletínská, Lenka

    2007-01-01

    Roč. 28, č. 10 (2007), s. 1945-1953 ISSN 0196-9781 R&D Projects: GA ČR GA303/05/0614 Institutional research plan: CEZ:AV0Z40550506 Keywords : CART peptide * fragments * binding * PC12 cells Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.368, year: 2007

  8. Robust Takagi-Sugeno Fuzzy Dynamic Regulator for Trajectory Tracking of a Pendulum-Cart System

    Directory of Open Access Journals (Sweden)

    Miguel A. Llama

    2015-01-01

    Full Text Available Starting from a nonlinear model for a pendulum-cart system, on which viscous friction is considered, a Takagi-Sugeno (T-S fuzzy augmented model (TSFAM as well as a TSFAM with uncertainty (TSFAMwU is proposed. Since the design of a T-S fuzzy controller is based on the T-S fuzzy model of the nonlinear system, then, to address the trajectory tracking problem of the pendulum-cart system, three T-S fuzzy controllers are proposed via parallel distributed compensation: (1 a T-S fuzzy servo controller (TSFSC designed from the TSFAM; (2 a robust TSFSC (RTSFSC designed from the TSFAMwU; and (3 a robust T-S fuzzy dynamic regulator (RTSFDR designed from the RTSFSC with the addition of a T-S fuzzy observer, which estimates cart and pendulum velocities. Both TSFAM and TSFAMwU are comprised of two fuzzy rules and designed via local approximation in fuzzy partition spaces technique. Feedback gains for the three fuzzy controllers are obtained via linear matrix inequalities approach. A swing-up controller is developed to swing the pendulum up from its pendant position to its upright position. Real-time experiments validate the effectiveness of the proposed schemes, keeping the pendulum in its upright position while the cart follows a reference signal, standing out the RTSFDR.

  9. Fire behavior of e-tablets stored in aircraft galley carts.

    Science.gov (United States)

    2015-04-01

    The use of electronic-tablets (e-tablets) as replacements for conventional in-flight entertainment systems has gained popularity : among airlines globally. Innovative methods of storing and charging e-tablets in galley carts have been suggested or ar...

  10. New analogs of the CART peptide with anorexigenic potency: The importance of individual disulfide bridges

    Czech Academy of Sciences Publication Activity Database

    Blechová, Miroslava; Nagelová, Veronika; Žáková, Lenka; Demianova, Zuzana; Železná, Blanka; Maletínská, Lenka

    2013-01-01

    Roč. 39, January (2013), s. 138-144 ISSN 0196-9781 R&D Projects: GA ČR GAP303/10/1368 Institutional support: RVO:61388963 Keywords : CART peptide analogs * sulfitolysis * PC12 cells * binding * food intake Subject RIV: CE - Biochemistry Impact factor: 2.614, year: 2013

  11. Automated cart with VIS/NIR hyperspectral reflectance and fluorescence imaging capabilities

    Science.gov (United States)

    A system to take high-resolution VIS/NIR hyperspectral reflectance and fluorescence images in outdoor fields using ambient lighting or a pulsed laser (355 nm), respectively, for illumination was designed, built, and tested. Components of the system include a semi-autonomous cart, a gated-intensified...

  12. Health constraints of Cart Horses in the Dry warm, Sub-moist tepid ...

    African Journals Online (AJOL)

    The objectives of this study were to identify the major health and welfare constraints of cart horses in the dry warm, sub-moist tepid and moist cool climatic zones of Ethiopia. The study was cross sectional and a total of 837 horses were examined. Five major health problems and welfare issues were identified. Lymphangitis ...

  13. CAR-T cells and combination therapies: What's next in the immunotherapy revolution?

    Science.gov (United States)

    Ramello, Maria C; Haura, Eric B; Abate-Daga, Daniel

    2018-03-01

    Cancer immunotherapies are dramatically reshaping the clinical management of oncologic patients. For many of these therapies, the guidelines for administration, monitoring, and management of associated toxicities are still being established. This is especially relevant for adoptively transferred, genetically-modified T cells, which have unique pharmacokinetic properties, due to their ability to replicate and persist long-term, following a single administration. Furthermore, in the case of CAR-T cells, the use of synthetic immune receptors may impact signaling pathways involved in T cell function and survival in unexpected ways. We, herein, comment on the most salient aspects of CAR-T cell design and clinical experience in the treatment of solid tumors. In addition, we discuss different possible scenarios for combinations of CAR-T cells and other treatment modalities, with a special emphasis on kinase inhibitors, elaborating on the strategies to maximize synergism. Finally, we discuss some of the technologies that are available to explore the molecular events governing the success of these therapies. The young fields of synthetic and systems biology are likely to be major players in the advancement of CAR-T cell therapies, providing the tools and the knowledge to engineer patients' T lymphocytes into intelligent cancer-fighting micromachines. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Biomarkers of cytokine release syndrome and neurotoxicity related to CAR-T cell therapy.

    Science.gov (United States)

    Wang, Zhenguang; Han, Weidong

    2018-01-01

    Severe cytokine release syndrome (CRS) and neurotoxicity following chimeric antigen receptor T cell (CAR-T) therapy can be life-threatening in some cases, and management of those toxicities is still a great challenge for physicians. Researchers hope to understand the pathophysiology of CRS and neurotoxicity, and identify predictive biomarkers that can forecast those toxicities in advance. Some risk factors for severe CRS and/or neurotoxicity including patient and treatment characteristics have been identified in multiple clinical trials of CAR-T cell therapy. Moreover, several groups have identified some predictive biomarkers that are able to determine beforehand which patients may suffer severe CRS and/or neurotoxicity during CAR-T cell therapy, facilitating testing of early intervention strategies for those toxicities. However, further studies are needed to better understand the biology and related risk factors for CRS and/or neurotoxicity, and determine if those identified predictors can be extrapolated to other series. Herein, we review the pathophysiology of CRS and neurotoxicity, and summarize the progress of predictive biomarkers to improve CAR-T cell therapy in cancer.

  15. A Rapid Cell Expansion Process for Production of Engineered Autologous CAR-T Cell Therapies.

    Science.gov (United States)

    Lu, Tangying Lily; Pugach, Omar; Somerville, Robert; Rosenberg, Steven A; Kochenderfer, James N; Better, Marc; Feldman, Steven A

    2016-12-01

    The treatment of B-cell malignancies by adoptive cell transfer (ACT) of anti-CD19 chimeric antigen receptor T cells (CD19 CAR-T) has proven to be a highly successful therapeutic modality in several clinical trials. 1-6 The anti-CD19 CAR-T cell production method used to support initial trials relied on numerous manual, open process steps, human serum, and 10 days of cell culture to achieve a clinical dose. 7 This approach limited the ability to support large multicenter clinical trials, as well as scale up for commercial cell production. Therefore, studies were completed to streamline and optimize the original National Cancer Institute production process by removing human serum from the process in order to minimize the risk of viral contamination, moving process steps from an open system to functionally closed system operations in order to minimize the risk of microbial contamination, and standardizing additional process steps in order to maximize process consistency. This study reports a procedure for generating CD19 CAR-T cells in 6 days, using a functionally closed manufacturing process and defined, serum-free medium. This method is able to produce CD19 CAR-T cells that are phenotypically and functionally indistinguishable from cells produced for clinical trials by the previously described production process.

  16. Control of trunk motion following sudden stop perturbations during cart pushing.

    Science.gov (United States)

    Lee, Yun-Ju; Hoozemans, Marco J M; van Dieën, Jaap H

    2011-01-04

    External perturbations during pushing tasks have been suggested to be a risk factor for low-back symptoms. An experiment was designed to investigate whether self-induced and externally induced sudden stops while pushing a high inertia cart influence trunk motions, and how flexor and extensor muscles counteract these perturbations. Twelve healthy male participants pushed a 200 kg cart at shoulder height and hip height. Pushing while walking was compared to situations in which participants had to stop the cart suddenly (self-induced stop) or in which the wheels of the cart were unexpectedly blocked (externally induced stop). For the perturbed conditions, the peak values and the maximum changes from the reference condition (pushing while walking) of the external moment at L5/S1, trunk inclination and electromyographic amplitudes of trunk muscles were determined. In the self-induced stop, a voluntary trunk extension occurred. Initial responses in both stops consisted of flexor and extensor muscle cocontraction. In self-induced stops this was followed by sustained extensor activity. In the externally induced stops, an external extension moment caused a decrease in trunk inclination. The opposite directions of the internal moment and trunk motion in the externally induced stop while pushing at shoulder height may indicate insufficient active control of trunk posture. Consequently, sudden blocking of the wheels in pushing at shoulder height may put the low back at risk of mechanical injury. Copyright © 2010 Elsevier Ltd. All rights reserved.

  17. Penerapan Algoritma Decision Tree C4.5 Untuk Penilaian Rumah Tinggal

    OpenAIRE

    Setiadi, Budi

    2015-01-01

    There is still a possibility of assessment error homes as a reference value of credit, which will open opportunities for NPL. So we need a way of assessment (predictive value) is quite proportional, credible and accurate. Inaccurate predictions led to the planning of improper credit management. Prediction value of collateral house has attracted the interest of many researchers because of its importance both in theoretical andempirical.Namely C4.5 decision tree algorithm, CART and CHAID that c...

  18. The nucleus accumbens 5-HTR4-CART pathway ties anorexia to hyperactivity

    Science.gov (United States)

    Jean, A; Laurent, L; Bockaert, J; Charnay, Y; Dusticier, N; Nieoullon, A; Barrot, M; Neve, R; Compan, V

    2012-01-01

    In mental diseases, the brain does not systematically adjust motor activity to feeding. Probably, the most outlined example is the association between hyperactivity and anorexia in Anorexia nervosa. The neural underpinnings of this ‘paradox', however, are poorly elucidated. Although anorexia and hyperactivity prevail over self-preservation, both symptoms rarely exist independently, suggesting commonalities in neural pathways, most likely in the reward system. We previously discovered an addictive molecular facet of anorexia, involving production, in the nucleus accumbens (NAc), of the same transcripts stimulated in response to cocaine and amphetamine (CART) upon stimulation of the 5-HT4 receptors (5-HTR4) or MDMA (ecstasy). Here, we tested whether this pathway predisposes not only to anorexia but also to hyperactivity. Following food restriction, mice are expected to overeat. However, selecting hyperactive and addiction-related animal models, we observed that mice lacking 5-HTR1B self-imposed food restriction after deprivation and still displayed anorexia and hyperactivity after ecstasy. Decryption of the mechanisms showed a gain-of-function of 5-HTR4 in the absence of 5-HTR1B, associated with CART surplus in the NAc and not in other brain areas. NAc-5-HTR4 overexpression upregulated NAc-CART, provoked anorexia and hyperactivity. NAc-5-HTR4 knockdown or blockade reduced ecstasy-induced hyperactivity. Finally, NAc-CART knockdown suppressed hyperactivity upon stimulation of the NAc-5-HTR4. Additionally, inactivating NAc-5-HTR4 suppressed ecstasy's preference, strengthening the rewarding facet of anorexia. In conclusion, the NAc-5-HTR4/CART pathway establishes a ‘tight-junction' between anorexia and hyperactivity, suggesting the existence of a primary functional unit susceptible to limit overeating associated with resting following homeostasis rules. PMID:23233022

  19. Simulation at the point of care: reduced-cost, in situ training via a mobile cart.

    Science.gov (United States)

    Weinstock, Peter H; Kappus, Liana J; Garden, Alexander; Burns, Jeffrey P

    2009-03-01

    The rapid growth of simulation in health care has challenged traditional paradigms of hospital-based education and training. Simulation addresses patient safety through deliberative practice of high-risk low-frequency events within a safe, structured environment. Despite its inherent appeal, widespread adoption of simulation is prohibited by high cost, limited space, interruptions to clinical duties, and the inability to replicate important nuances of clinical environments. We therefore sought to develop a reduced-cost low-space mobile cart to provide realistic simulation experiences to a range of providers within the clinical environment and to serve as a model for transportable, cost-effective, widespread simulation-based training of bona-fide workplace teams. Descriptive study. A tertiary care pediatric teaching hospital. A self-contained mobile simulation cart was constructed at a cost of $8054 (mannequin not included). The cart is compatible with any mannequin and contains all equipment needed to produce a high quality simulation experience equivalent to that of our on-site center--including didactics and debriefing with videotaped recordings complete with vital sign overlay. Over a 3-year period the cart delivered 57 courses to 425 participants from five pediatric departments. All individuals were trained among their native teams and within their own clinical environment. By bringing all pedagogical elements to the actual clinical environment, a mobile cart can provide simulation to hospital teams that might not otherwise benefit from the educational tool. By reducing the setup cost and the need for dedicated space, the mobile approach provides a mechanism to increase the number of institutions capable of harnessing the power of simulation-based education internationally.

  20. The nucleus accumbens 5-HTR₄-CART pathway ties anorexia to hyperactivity.

    Science.gov (United States)

    Jean, A; Laurent, L; Bockaert, J; Charnay, Y; Dusticier, N; Nieoullon, A; Barrot, M; Neve, R; Compan, V

    2012-12-11

    In mental diseases, the brain does not systematically adjust motor activity to feeding. Probably, the most outlined example is the association between hyperactivity and anorexia in Anorexia nervosa. The neural underpinnings of this 'paradox', however, are poorly elucidated. Although anorexia and hyperactivity prevail over self-preservation, both symptoms rarely exist independently, suggesting commonalities in neural pathways, most likely in the reward system. We previously discovered an addictive molecular facet of anorexia, involving production, in the nucleus accumbens (NAc), of the same transcripts stimulated in response to cocaine and amphetamine (CART) upon stimulation of the 5-HT(4) receptors (5-HTR(4)) or MDMA (ecstasy). Here, we tested whether this pathway predisposes not only to anorexia but also to hyperactivity. Following food restriction, mice are expected to overeat. However, selecting hyperactive and addiction-related animal models, we observed that mice lacking 5-HTR(1B) self-imposed food restriction after deprivation and still displayed anorexia and hyperactivity after ecstasy. Decryption of the mechanisms showed a gain-of-function of 5-HTR(4) in the absence of 5-HTR(1B), associated with CART surplus in the NAc and not in other brain areas. NAc-5-HTR(4) overexpression upregulated NAc-CART, provoked anorexia and hyperactivity. NAc-5-HTR(4) knockdown or blockade reduced ecstasy-induced hyperactivity. Finally, NAc-CART knockdown suppressed hyperactivity upon stimulation of the NAc-5-HTR(4). Additionally, inactivating NAc-5-HTR(4) suppressed ecstasy's preference, strengthening the rewarding facet of anorexia. In conclusion, the NAc-5-HTR(4)/CART pathway establishes a 'tight-junction' between anorexia and hyperactivity, suggesting the existence of a primary functional unit susceptible to limit overeating associated with resting following homeostasis rules.

  1. The costs and calorie content of à la carte food items purchased by students during school lunch

    Directory of Open Access Journals (Sweden)

    Betsey Ramirez

    2018-06-01

    Full Text Available School environments influence student food choices. À la carte foods and beverages are often low nutrient and energy dense. This study assessed how much money students spent for these foods, and the total kilocalories purchased per student during the 2012–2013 school year. Six elementary and four intermediate schools in the Houston area provided daily food purchase transaction data, and the cost and the calories for each item. Chi-square analysis assessed differences in the number of students purchasing à la carte items by grade level and school free/reduced-price meal (FRP eligibility. Analysis of covariance assessed grade level differences in cost and calories of weekly purchases, controlling for FRP eligibility. Intermediate grade students spent significantly more on à la carte food purchases and purchased more calories (both p < 0.001 than elementary school students. Lower socioeconomic status (SES elementary and intermediate school students purchased fewer à la carte foods compared to those in higher SES schools (p < 0.001. Intermediate school students purchased more à la carte foods and calories from à la carte foods than elementary students. Whether the new competitive food rules in schools improve student food selection and purchase, and dietary intake habits across all grade levels remains unknown. Keywords: National School Lunch Program, Elementary schools, Intermediate schools, À la carte foods, Competitive foods, Costs, Calories

  2. Chimeric antigen receptor T cell (CAR-T) immunotherapy for solid tumors: lessons learned and strategies for moving forward.

    Science.gov (United States)

    Li, Jian; Li, Wenwen; Huang, Kejia; Zhang, Yang; Kupfer, Gary; Zhao, Qi

    2018-02-13

    Recently, the US Food and Drug Administration (FDA) approved the first chimeric antigen receptor T cell (CAR-T) therapy for the treatment CD19-positive B cell acute lymphoblastic leukemia. While CAR-T has achieved remarkable success in the treatment of hematopoietic malignancies, whether it can benefit solid tumor patients to the same extent is still uncertain. Even though hundreds of clinical trials are undergoing exploring a variety of tumor-associated antigens (TAA), no such antigen with comparable properties like CD19 has yet been identified regarding solid tumors CAR-T immunotherapy. Inefficient T cell trafficking, immunosuppressive tumor microenvironment, suboptimal antigen recognition specificity, and lack of safety control are currently considered as the main obstacles in solid tumor CAR-T therapy. Here, we reviewed the solid tumor CAR-T clinical trials, emphasizing the studies with published results. We further discussed the challenges that CAR-T is facing for solid tumor treatment and proposed potential strategies to improve the efficacy of CAR-T as promising immunotherapy.

  3. 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.

  4. Cocaine- and amphetamine-regulated transcript (CART signaling within the paraventricular thalamus modulates cocaine-seeking behaviour.

    Directory of Open Access Journals (Sweden)

    Morgan H James

    Full Text Available BACKGROUND: Cocaine- and amphetamine-regulated transcript (CART has been demonstrated to play a role in regulating the rewarding and reinforcing effects of various drugs of abuse. A recent study demonstrated that i.c.v. administration of CART negatively modulates reinstatement of alcohol seeking, however, the site(s of action remains unclear. We investigated the paraventricular thalamus (PVT as a potential site of relapse-relevant CART signaling, as this region is known to receive dense innervation from CART-containing hypothalamic cells and to project to a number of regions known to be involved in mediating reinstatement, including the nucleus accumbens (NAC, medial prefrontal cortex (mPFC and basolateral amygdala (BLA. METHODOLOGY/PRINCIPAL FINDINGS: Male rats were trained to self-administer cocaine before being extinguished to a set criterion. One day following extinction, animals received intra-PVT infusions of saline, tetrodotoxin (TTX; 2.5 ng, CART (0.625 µg or 2.5 µg or no injection, followed by a cocaine prime (10 mg/kg, i.p.. Animals were then tested under extinction conditions for one hour. Treatment with either TTX or CART resulted in a significant attenuation of drug-seeking behaviour following cocaine-prime, with the 2.5 µg dose of CART having the greatest effect. This effect was specific to the PVT region, as misplaced injections of both TTX and CART resulted in responding that was identical to controls. CONCLUSIONS/SIGNIFICANCE: We show for the first time that CART signaling within the PVT acts to inhibit drug-primed reinstatement of cocaine seeking behaviour, presumably by negatively modulating PVT efferents that are important for drug seeking, including the NAC, mPFC and BLA. In this way, we identify a possible target for future pharmacological interventions designed to suppress drug seeking.

  5. Evaluation of CART peptide level in rat plasma and CSF: Possible role as a biomarker in opioid addiction.

    Science.gov (United States)

    Bakhtazad, Atefeh; Vousooghi, Nasim; Garmabi, Behzad; Zarrindast, Mohammad Reza

    2016-10-01

    It has been shown previously that cocaine- and amphetamine-regulated transcript (CART) peptide has a modulatory role and homeostatic regulatory effect in motivation to and reward of the drugs of abuse specially psychostimulants. Recent data also showed that in addition to psychostimulants, CART is critically involved in the different stages of opioid addiction. Here we have evaluated the fluctuations in the level of CART peptide in plasma and CSF in different phases of opioid addiction to find out whether CART can serve as a suitable marker in opioid addiction studies. Male rats were randomly distributed in groups of control, acute low-dose (10mg/kg) morphine, acute high-dose morphine (80mg/kg), chronic escalating doses of morphine, withdrawal syndrome precipitated by administration of naloxone (1mg/kg), and abstinent after long-term drug-free maintenance of addicted animals. The level of CART peptide in CSF and plasma samples was measured by enzyme immunoassay. CART peptide concentration in the CSF and plasma was significantly elevated in acute high-dose morphine and withdrawal state animals and down-regulated in addicted rats. In abstinent group, CART peptide level was up-regulated in plasma but not in CSF samples. As the observed results are in agreement with data regarding the CART mRNA and protein expression in the brain reward pathway in opioid addiction phases, it may be suggested that evaluation of CART peptide level in CSF or plasma could be a suitable marker which reflects the rises and falls of the peptide concentration in brain in the development of opioid addiction. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Increase in cocaine- and amphetamine-regulated transcript (CART) in specific areas of the mouse brain by acute caffeine administration.

    Science.gov (United States)

    Cho, Jin Hee; Cho, Yun Ha; Kim, Hyo Young; Cha, Seung Ha; Ryu, Hyun; Jang, Wooyoung; Shin, Kyung Ho

    2015-04-01

    Caffeine produces a variety of behavioral effects including increased alertness, reduced food intake, anxiogenic effects, and dependence upon repeated exposure. Although many of the effects of caffeine are mediated by its ability to block adenosine receptors, it is possible that other neural substrates, such as cocaine- and amphetamine-regulated transcript (CART), may be involved in the effects of caffeine. Indeed, a recent study demonstrated that repeated caffeine administration increases CART in the mouse striatum. However, it is not clear whether acute caffeine administration alters CART in other areas of the brain. To explore this possibility, we investigated the dose- and time-dependent changes in CART immunoreactivity (CART-IR) after a single dose of caffeine in mice. We found that a high dose of caffeine (100 mg/kg) significantly increased CART-IR 2 h after administration in the nucleus accumbens shell (AcbSh), dorsal bed nucleus of the stria terminalis (dBNST), central nucleus of the amygdala (CeA), paraventricular hypothalamic nucleus (PVN), arcuate hypothalamic nucleus (Arc), and locus coeruleus (LC), and returned to control levels after 8 h. But this increase was not observed in other brain areas. In addition, caffeine administration at doses of 25 and 50 mg/kg appears to produce dose-dependent increases in CART-IR in these brain areas; however, the magnitude of increase in CART-IR observed at a dose of 50 mg/kg was similar or greater than that observed at a dose of 100 mg/kg. This result suggests that CART-IR in AcbSh, dBNST, CeA, PVN, Arc, and LC is selectively affected by caffeine administration. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Chromatin immunoprecipitation assays revealed CREB and serine 133 phospho-CREB binding to the CART gene proximal promoter.

    Science.gov (United States)

    Rogge, George A; Shen, Li-Ling; Kuhar, Michael J

    2010-07-16

    Both over expression of cyclic AMP response element binding protein (CREB) in the nucleus accumbens (NAc), and intra-accumbal injection of cocaine- and amphetamine-regulated transcript (CART) peptides, have been shown to decrease cocaine reward. Also, over expression of CREB in the rat NAc increased CART mRNA and peptide levels, but it is not known if this was due to a direct action of P-CREB on the CART gene promoter. The goal of this study was to test if CREB and P-CREB bound directly to the CRE site in the CART promoter, using chromatin immunoprecipitation (ChIP) assays. ChIP assay with anti-CREB antibodies showed an enrichment of the CART promoter fragment containing the CRE region over IgG precipitated material, a non-specific control. Forskolin, which was known to increase CART mRNA levels in GH3 cells, was utilized to show that the drug increased levels of P-CREB protein and P-CREB binding to the CART promoter CRE-containing region. A region of the c-Fos promoter containing a CRE cis-regulatory element was previously shown to bind P-CREB, and it was used here as a positive control. These data suggest that the effects of CREB over expression on blunting cocaine reward could be, at least in part, attributed to the increased expression of the CART gene by direct interaction of P-CREB with the CART promoter CRE site, rather than by some indirect action. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  8. 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.

  9. 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.

  10. 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

  11. 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-

  12. 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.

  13. 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 ...

  14. 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 ...

  15. 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.

  16. 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 ...

  17. 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 ...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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 ...

  3. ~{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.

  4. 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....

  5. 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.

  6. Safety, tumor trafficking and immunogenicity of chimeric antigen receptor (CAR)-T cells specific for TAG-72 in colorectal cancer.

    Science.gov (United States)

    Hege, Kristen M; Bergsland, Emily K; Fisher, George A; Nemunaitis, John J; Warren, Robert S; McArthur, James G; Lin, Andy A; Schlom, Jeffrey; June, Carl H; Sherwin, Stephen A

    2017-01-01

    T cells engineered to express chimeric antigen receptors (CARs) have established efficacy in the treatment of B-cell malignancies, but their relevance in solid tumors remains undefined. Here we report results of the first human trials of CAR-T cells in the treatment of solid tumors performed in the 1990s. Patients with metastatic colorectal cancer (CRC) were treated in two phase 1 trials with first-generation retroviral transduced CAR-T cells targeting tumor-associated glycoprotein (TAG)-72 and including a CD3-zeta intracellular signaling domain (CART72 cells). In trial C-9701 and C-9702, CART72 cells were administered in escalating doses up to 10 10 total cells; in trial C-9701 CART72 cells were administered by intravenous infusion. In trial C-9702, CART72 cells were administered via direct hepatic artery infusion in patients with colorectal liver metastases. In both trials, a brief course of interferon-alpha (IFN-α) was given with each CART72 infusion to upregulate expression of TAG-72. Fourteen patients were enrolled in C-9701 and nine in C-9702. CART72 manufacturing success rate was 100% with an average transduction efficiency of 38%. Ten patients were treated in CC-9701 and 6 in CC-9702. Symptoms consistent with low-grade, cytokine release syndrome were observed in both trials without clear evidence of on target/off tumor toxicity. Detectable, but mostly short-term (≤14 weeks), persistence of CART72 cells was observed in blood; one patient had CART72 cells detectable at 48 weeks. Trafficking to tumor tissues was confirmed in a tumor biopsy from one of three patients. A subset of patients had 111 Indium-labeled CART72 cells injected, and trafficking could be detected to liver, but T cells appeared largely excluded from large metastatic deposits. Tumor biomarkers carcinoembryonic antigen (CEA) and TAG-72 were measured in serum; there was a precipitous decline of TAG-72, but not CEA, in some patients due to induction of an interfering antibody to the TAG-72

  7. Substance use and adherence among people living with HIV/AIDS receiving cART in Latin America

    OpenAIRE

    De Boni, Raquel B.; Shepherd, Bryan E.; Grinsztejn, Beatriz; Cesar, Carina; Cortés, Claudia; Padgett, Denis; Gotuzzo, Eduardo; Belaunzarán-Zamudio, Pablo F.; Rebeiro, Peter F.; Duda, Stephany N.; McGowan, Catherine C.

    2016-01-01

    This cross-sectional study describes substance use prevalence and its association with cART adherence among 3343 individuals receiving care at HIV clinics in Argentina, Brazil, Chile, Honduras, Mexico, and Peru. A rapid screening tool evaluated self-reported 7-day recall of alcohol, marijuana, cocaine, heroin, and methamphetamine use, and missed cART doses. Overall, 29.3% individuals reported having ≥ 1 alcoholic drinks, 5.0% reported any illicit drug use and 17.0% reported missed cART doses....

  8. Etiologies of pediatric craniofacial injuries: a comparison of injuries involving all-terrain vehicles and golf carts.

    Science.gov (United States)

    White, Lauren C; McKinnon, Brian J; Hughes, C Anthony

    2013-03-01

    To determine incidence and etiologies of craniofacial injuries in the pediatric population through comparison of injuries caused by all-terrain vehicles and golf cart trauma. Case series with chart review. Level 1 trauma center. Retrospective review of pediatric traumas at a tertiary academic medical center from 2003 to 2012 identified 196 patients whose injuries resulted from accidents involving either all-terrain vehicles or golf carts. Data was collected and variables such as age, gender, driver vs. passenger, location of accident, Glasgow coma scale, Injury severity scale, Abbreviated injury scale, and presence or absence of helmet use were examined. 196 pediatric patients were identified: 68 patients had injuries resulting from golf cart accidents, and 128 patients from ATV accidents. 66.4% of ATV-related traumas were male, compared to 52.9% of golf cart-related traumas. Ages of injured patients were similar between the two modalities with average age of ATV traumas 10.8 (±4.0) years and golf cart traumas 10.0 (±4.6) years. Caucasians were most commonly involved in both ATV (79.7%) and golf cart traumas (85.3%). 58.6% of all ATV related trauma and 69.1% of all golf cart trauma resulted in craniofacial injuries. The most common craniofacial injury was a closed head injury with brief loss of consciousness, occurring in 46.1% of the ATV traumas and 54.4% of the golf cart traumas. Temporal bone fractures were the second most common type of craniofacial injury, occurring in 5.5% of ATV accidents and 7.4% of the golf cart traumas. Length of hospital stay and, cases requiring surgery and severity scores were similar between both populations. Intensive care admissions and injury severity scores approached but not reach statistical significance (0.096 and 0.083, respectively). The only statistically significant differences between the two modalities were helmet use (P=0.00018%) and days requiring ventilator assistance (P=0.025). ATVs and golf carts are often exempt

  9. EL PRECURSOR DEL NEUROPEPTIDO CART POSEE UNA SEÑAL DE DESTINACION A LAS VESICULAS DE SECRECION REGULADA

    OpenAIRE

    BLANCO NAHUELQUEO, ELIAS HUMBERTO; BLANCO NAHUELQUEO, ELIAS HUMBERTO

    2011-01-01

    CART (Cocaine- Amphetamine Regulated Transcript} fue descubierto como un RNAm que es inducido por una dosis aguda de cocaína y también de anfetamina en el estriado de cerebro de rata. A partir de su descubrimiento el neuropéptido CART fue vinculado a drogas de abuso, sin embargo existe mayor evidencia que lo vincula al control del apetito. El neuropéptido CART inhibe potentemente el apetito (efecto anorexigénico} cuando es administrado intra-cerebralmente a roedores. Una subregión de...

  10. 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.

  11. 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

  12. Emerging immunotherapeutics in adenocarcinomas: A focus on CAR-T cells.

    Science.gov (United States)

    Yazdanifar, Mahboubeh; Zhou, Ru; Mukherjee, Pinku

    2016-01-01

    More than 80% of all cancers arise from epithelial cells referred to as carcinomas. Adenocarcinomas are the most common type of carcinomas arising from the specialized epithelial cells that line the ducts of our major organs. Despite many advances in cancer therapies, metastatic and treatment-refractory cancers remain the 2 nd leading cause of death. Immunotherapy has offered potential opportunities with specific targeting of tumor cells and inducing remission in many cancer patients. Numerous therapies using antibodies as antagonists or checkpoint inhibitors/immune modulators, peptide or cell vaccines, cytokines, and adoptive T cell therapies have been developed. The most innovative immunotherapy approach so far has been the use of engineered T cell, also referred to as chimeric antigen receptor T cells (CAR-T cells). CAR-T cells are genetically modified naïve T cells that express a chimeric molecule which comprises of the antigen-recognition domains (scFv) of an anti-tumor antibody and one, two, or three intracellular signaling domains of the T cell receptor (TCR). When these engineered T cells recognize and bind to the tumor antigen target via the scFv fragment, a signal is sent to the intracellular TCR domains of the CAR, leading to activation of the T cells to become cytolytic against the tumor cells. CAR-T cell therapy has shown tremendous success for certain hematopoietic malignancies, but this success has not been extrapolated to adenocarcinomas. This is due to multiple factors associated with adenocarcinoma that are different from hematopoietic tumors. Although many advances have been made in targeting multiple cancers by CAR-T cells, clinical trials have shown adverse effects and toxicity related to this treatment. New strategies are yet to be devised to manage side effects associated with CAR-T cell therapies. In this review, we report some of the promising immunotherapeutic strategies being developed for treatment of most common adenocarcinomas with

  13. Lamivudine monotherapy-based cART is efficacious for HBV treatment in HIV/HBV co-infection when baseline HBV DNA<20,000IU/ml

    Science.gov (United States)

    LI, Yijia; XIE, Jing; HAN, Yang; WANG, Huanling; ZHU, Ting; WANG, Nidan; LV, Wei; GUO, Fuping; QIU, Zhifeng; LI, Yanling; DU, Shanshan; SONG, Xiaojing; THIO, Chloe L; LI, Taisheng

    2016-01-01

    Background Although combination antiretroviral therapy (cART) including tenofovir (TDF)+lamivudine (3TC) or emtricitabine (FTC) is recommended for treatment of HIV/HBV co-infected patients, TDF is unavailable in some resource-limited areas. Some data suggest that 3TC monotherapy-based cART may be effective in patients with low pre-treatment HBV DNA. Methods Prospective study of 151 Chinese HIV/HBV co-infected subjects of whom 60 received 3TC-based cART and 91 received TDF+3TC-based cART. Factors associated with HBV DNA suppression at 24 and 48 weeks, including anti-HBV drugs, baseline HBV DNA, and baseline CD4 cell count, were evaluated overall and stratified by baseline HBV DNA using Poisson regression with a robust error variance. Results Baseline HBV DNA≥20,000 IU/ml was present in 48.3% and 44.0% of subjects in the 3TC and TDF groups, respectively (P=0.60). After 48 weeks of treatment, HBV DNA suppression rates were similar between these two groups (96.8% vs. 98.0% for 3TC and TDF+3TC, P>0.999) in subjects with baseline HBV DNAHBV DNA ≥20,000 IU/ml, TDF+3TC was associated with higher suppression rates (34.5% vs. 72.5% in 3TC and TDF+3TC groups, respectively, P=0.002). In stratified multivariate regression, TDF use (RR 1.98, P=0.010) and baseline HBV DNA (per 1 log increase in IU/ml, RR 0.74, PHBV DNA suppression only when baseline HBV DNA≥20,000IU/ml. Conclusion This study suggests that 3TC monotherapy-based cART is efficacious for HBV treatment through 48 weeks in HIV/HBV co-infection when baseline HBV DNA<20,000IU/ml. Studies with long-term follow-up are warranted to determine if this finding persists. PMID:26745828

  14. Rapid Erosion Modeling in a Western Kenya Watershed using Visible Near Infrared Reflectance, Classification Tree Analysis and 137Cesium.

    Science.gov (United States)

    deGraffenried, Jeff B; Shepherd, Keith D

    2009-12-15

    Human induced soil erosion has severe economic and environmental impacts throughout the world. It is more severe in the tropics than elsewhere and results in diminished food production and security. Kenya has limited arable land and 30 percent of the country experiences severe to very severe human induced soil degradation. The purpose of this research was to test visible near infrared diffuse reflectance spectroscopy (VNIR) as a tool for rapid assessment and benchmarking of soil condition and erosion severity class. The study was conducted in the Saiwa River watershed in the northern Rift Valley Province of western Kenya, a tropical highland area. Soil 137 Cs concentration was measured to validate spectrally derived erosion classes and establish the background levels for difference land use types. Results indicate VNIR could be used to accurately evaluate a large and diverse soil data set and predict soil erosion characteristics. Soil condition was spectrally assessed and modeled. Analysis of mean raw spectra indicated significant reflectance differences between soil erosion classes. The largest differences occurred between 1,350 and 1,950 nm with the largest separation occurring at 1,920 nm. Classification and Regression Tree (CART) analysis indicated that the spectral model had practical predictive success (72%) with Receiver Operating Characteristic (ROC) of 0.74. The change in 137 Cs concentrations supported the premise that VNIR is an effective tool for rapid screening of soil erosion condition.

  15. 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.

  16. 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.

  17. Clinical pharmacology of CAR-T cells: Linking cellular pharmacodynamics to pharmacokinetics and antitumor effects.

    Science.gov (United States)

    Norelli, M; Casucci, M; Bonini, C; Bondanza, A

    2016-01-01

    Adoptive cell transfer of T cells genetically modified with tumor-reactive chimeric antigen receptors (CARs) is a rapidly emerging field in oncology, which in preliminary clinical trials has already shown striking antitumor efficacy. Despite these premises, there are still a number of open issues related to CAR-T cells, spanning from their exact mechanism of action (pharmacodynamics), to the factors associated with their in vivo persistence (pharmacokinetics), and, finally, to the relative contribution of each of the two in determining the antitumor effects and accompanying toxicities. In light of the unprecedented curative potential of CAR-T cells and of their predicted wide availability in the next few years, in this review we will summarize the current knowledge on the clinical pharmacology aspects of what is anticipated to be a brand new class of biopharmaceuticals to join the therapeutic armamentarium of cancer doctors. Copyright © 2015. Published by Elsevier B.V.

  18. Investigation on Superior Performance by Fractional Controller for Cart-Servo Laboratory Set-Up

    Directory of Open Access Journals (Sweden)

    Ameya Anil Kesarkar

    2014-01-01

    Full Text Available In this paper, an investigation is made on the superiority of fractional PID controller (PI^alpha D^beta over conventional PID for the cart-servo laboratory set-up. The designed controllers are optimum in the sense of Integral Absolute Error (IAE and Integral Square Error (ISE. The paper contributes in three aspects: 1 Acquiring nonlinear mathematical model for the cart-servo laboratory set-up, 2 Designing fractional and integer order PID for minimizing IAE, ISE, 3 Analyzing the performance of designed controllers for simulated plant model as well as real plant. The results show a significantly superior performance by PI^alpha D^beta as compared to the conventional PID controller.

  19. Penser et activer les relations entre cartes et récits

    Directory of Open Access Journals (Sweden)

    SÉBASTIEN CAQUARD

    2015-03-01

    Full Text Available De prime abord, récit et carte semblent en opposition directe. Le récit offre un point de vue partiel et personnel, souvent chronologique et intimement associé à une trame narrative structurée autour d’évènements vécus, imaginés ou remémorés par un sujet concret engagé dans un cheminement. La carte s’ingénie à présenter de manière synthétique et abstraite des données quantifiables à partir d’un point distant, figé dans le temps, dépersonnalisé et aérien.

  20. 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.

  1. 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....

  2. 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....

  3. Inventaire des cartes climatiques conservées à la cartothèque de l' IGN

    Directory of Open Access Journals (Sweden)

    Bernadette Joseph

    2010-12-01

    Full Text Available Cet inventaire présente la liste des cartes climatiques étrangères, conservées à la cartothèque de l' IGN. Ce fonds très riche en cartes thématiques n'est actuellement pas répertorié dans les catalogues SUDOC ou OPALE. Il n'est accessible qu'en interne sur fichiers papier.

  4. Synergistic effect of CART (cocaine- and amphetamine-regulated transcript peptide and cholecystokinin on food intake regulation in lean mice

    Directory of Open Access Journals (Sweden)

    Kiss Alexander

    2008-10-01

    Full Text Available Abstract Background CART (cocaine- and amphetamine-regulated transcript peptide and cholecystokinin (CCK are neuromodulators involved in feeding behavior. This study is based on previously found synergistic effect of leptin and CCK on food intake and our hypothesis on a co-operation of the CART peptide and CCK in food intake regulation and Fos activation in their common targets, the nucleus tractus solitarii of the brainstem (NTS, the paraventricular nucleus (PVN, and the dorsomedial nucleus (DMH of the hypothalamus. Results In fasted C57BL/6 mice, the anorexigenic effect of CART(61-102 in the doses of 0.1 or 0.5 μg/mouse was significantly enhanced by low doses of CCK-8 of 0.4 or 4 μg/kg, while 1 mg/kg dose of CCK-A receptor antagonist devazepide blocked the effect of CART(61-102 on food intake. After simultaneous administration of 0.1 μg/mouse CART(61-102 and of 4 μg/kg of CCK-8, the number of Fos-positive neurons in NTS, PVN, and DMH was significantly higher than after administration of each particular peptide. Besides, CART(61-102 and CCK-8 showed an additive effect on inhibition of the locomotor activity of mice in an open field test. Conclusion The synergistic and long-lasting effect of the CART peptide and CCK on food intake and their additive effect on Fos immunoreactivity in their common targets suggest a co-operative action of CART peptide and CCK which could be related to synergistic effect of leptin on CCK satiety.

  5. Cocaine- and amphetamine-regulated transcript (CART) peptide specific binding in pheochromocytoma cells PC12

    Czech Academy of Sciences Publication Activity Database

    Maletínská, Lenka; Maixnerová, Jana; Matyšková, Resha; Haugvicová, Renata; Šloncová, Eva; Elbert, Tomáš; Slaninová, Jiřina; Železná, Blanka

    2007-01-01

    Roč. 559, 2/3 (2007), s. 109-114 ISSN 0014-2999 R&D Projects: GA ČR GA303/05/0614 Institutional research plan: CEZ:AV0Z40550506; CEZ:AV0Z50520514; CEZ:AV0Z50200510 Keywords : radioligand binding * CART * PC12 cells * food intake Subject RIV: CE - Biochemistry Impact factor: 2.376, year: 2007

  6. Peptid CART (cocaine- and amphetamine- regulated transcript) v signalizaci buněk PC12

    Czech Academy of Sciences Publication Activity Database

    Nagelová, Veronika; Železná, Blanka; Maletínská, Lenka

    2014-01-01

    Roč. 108, č. 5 (2014), s. 543 ISSN 0009-2770. [Mezioborové setkání mladých biologů, biochemiků a chemiků /14./. 13.05.2014-16.05.2014, Milovy] R&D Projects: GA ČR GAP303/10/1368 Institutional support: RVO:61388963 Keywords : peptide CART * PC12 * c-Jun * SAPK/JNK Subject RIV: CE - Biochemistry

  7. VERA Pin and Fuel Assembly Depletion Benchmark Calculations by McCARD and DeCART

    Energy Technology Data Exchange (ETDEWEB)

    Park, Ho Jin; Cho, Jin Young [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    Monte Carlo (MC) codes have been developed and used to simulate a neutron transport since MC method was devised in the Manhattan project. Solving the neutron transport problem with the MC method is simple and straightforward to understand. Because there are few essential approximations for the 6- dimension phase of a neutron such as the location, energy, and direction in MC calculations, highly accurate solutions can be obtained through such calculations. In this work, the VERA pin and fuel assembly (FA) depletion benchmark calculations are performed to examine the depletion capability of the newly generated DeCART multi-group cross section library. To obtain the reference solutions, MC depletion calculations are conducted using McCARD. Moreover, to scrutinize the effect by stochastic uncertainty propagation, uncertainty propagation analyses are performed using a sensitivity and uncertainty (S/U) analysis method and stochastic sampling (S.S) method. It is still expensive and challenging to perform a depletion analysis by a MC code. Nevertheless, many studies and works for a MC depletion analysis have been conducted to utilize the benefits of the MC method. In this study, McCARD MC and DeCART MOC transport calculations are performed for the VERA pin and FA depletion benchmarks. The DeCART depletion calculations are conducted to examine the depletion capability of the newly generated multi-group cross section library. The DeCART depletion calculations give excellent agreement with the McCARD reference one. From the McCARD results, it is observed that the MC depletion results depend on how to split the burnup interval. First, only to quantify the effect of the stochastic uncertainty propagation at 40 DTS, the uncertainty propagation analyses are performed using the S/U and S.S. method.

  8. Registro de los cartógrafos medievales activos en el puerto de Mallorca

    Directory of Open Access Journals (Sweden)

    Llompart, Gabriel

    1997-12-01

    Full Text Available In medieval times, with the opening of the Atlantic trading routes at the beginning of the 14th century, the port of the Ciutat de Mallorques became important as the base of a gathering of both cartographers and copiers of maps. Today these maps are dispersed in museums throughout the world. Until the present day, these early map makers were known only through their works. Presented here is the first register of the "maestros" of navigational charts who worked in the "port of Mallorca". The documentation is taken from local notarial and administrative sources, all of which help the better clarification of their names, birthplaces, their Sitz im Leben and their methods of production, which were later surpassed and improved by the advent of the modern printing press.[fr] Le port de Ciutat de Mallorques fût très important pour l'histoire de la cartographie médiévale, parce-qu'un certain nombre de dessinateurs et copistes de cartes s'établirent là au commencement du XIV siècle, en raison de l'ouverture de la route atlantique. Maintenant, ces cartes se trouvent dispersées en diferents musées par tout le monde. Les auteurs de ces cartes étaient connus et datés jusqu'aujourd'hui à travers ses ouvrages. Dans cet article nous est donné un premier registre des maîtres de cartes de naviguer que travaillèrent au port de Majorque, provenant de sources locales, notariales et administratives, que nous permettent d'eclircir leurs noms, leur date de naissance leur Sitz im Leben et leurs méthodes de travail, peu après débordés et dépassés par la presse moderne.

  9. CAR-T cells targeting CLL-1 as an approach to treat acute myeloid leukemia.

    Science.gov (United States)

    Wang, Jinghua; Chen, Siyu; Xiao, Wei; Li, Wende; Wang, Liang; Yang, Shuo; Wang, Weida; Xu, Liping; Liao, Shuangye; Liu, Wenjian; Wang, Yang; Liu, Nawei; Zhang, Jianeng; Xia, Xiaojun; Kang, Tiebang; Chen, Gong; Cai, Xiuyu; Yang, Han; Zhang, Xing; Lu, Yue; Zhou, Penghui

    2018-01-10

    Acute myeloid leukemia (AML) is one of the most common types of adult acute leukemia. Standard chemotherapies can induce complete remission in selected patients; however, a majority of patients eventually relapse and succumb to the disease. Thus, the development of novel therapeutics for AML is urgently needed. Human C-type lectin-like molecule-1 (CLL-1) is a type II transmembrane glycoprotein, and its expression is restricted to myeloid cells and the majority of AML blasts. Moreover, CLL-1 is expressed in leukemia stem cells (LSCs), but absent in hematopoietic stem cells (HSCs), which may provide a potential therapeutic target for AML treatment. We tested the expression of CLL-1 antigen on peripheral blood cells and bone marrow cells in healthy donor and AML patients. Then, we developed a chimeric antigen receptor (CAR) containing a CLL1-specific single-chain variable fragment, in combination with CD28, 4-1BB costimulatory domains, and CD3-ζ signaling domain. We further investigate the function of CLL-1 CAR-T cells. The CLL-1 CAR-T cells specifically lysed CLL-1 + cell lines as well as primary AML patient samples in vitro. Strong anti-leukemic activity was observed in vivo by using a xenograft model of disseminated AML. Importantly, CLL-1 + myeloid progenitor cells and mature myeloid cells were specifically eliminated by CLL-1 CAR-T cells, while normal HSCs were not targeted due to the lack of CLL-1 expression. CLL-1 CAR-T represents a promising immunotherapy for the treatment of AML.

  10. The vending and à la carte policy intervention in Maine public high schools.

    Science.gov (United States)

    Davee, Anne-Marie; Blum, Janet E Whatley; Devore, Rachel L; Beaudoin, Christina M; Kaley, Lori A; Leiter, Janet L; Wigand, Debra A

    2005-11-01

    A healthy school nutrition environment may be important for decreasing childhood overweight. This article describes a project to make healthier snacks and beverages available in vending machines and à la carte programs in Maine public high schools. Seven public high schools in Maine volunteered to participate in this project. Four schools made changes to the nutrition environment, and three schools that served as controls did not. The nutrition guidelines were to offer only low-fat (not more than 30% of total calories from fat) and low-sugar (not more than 35% by weight of sugar) items in vending machines and à la carte programs. Strategies to implement the project included early communications with school officials, monetary stipends for participation, identification of a school liaison, and a committee at each school to promote the healthy changes. Baseline nutrient content and sales of all competitive foods and beverages were assessed to develop the guidelines for changes in the four schools. Student volunteers at all seven schools were measured for height, weight, diet quality, and physical activity level to assess the impact of the change to the nutrition environment. Baseline measures were taken in the spring semester of 2004. Nutrition changes were made to the à la carte programs and vending machines in the four intervention schools at the start of the fall semester of 2004. Follow-up nutrition assessment and student data collection occurred in the spring semester of 2005. Healthy changes in vending machines were more easily achieved than those made in the à la carte programs. Technical assistance and ongoing support were essential for successful implementation of this intervention. It is possible to improve the nutrition environment of Maine public high schools. Stakeholder support is essential to sustain healthy changes.

  11. Pendekatan Cart untuk Mendapatkan Faktor yang Mempengaruhi Terjangkitnya Penyakit Demam Tifoid di Aceh Utara

    Directory of Open Access Journals (Sweden)

    Dina Yuanita

    2010-05-01

    research conducted to find factors that influence the outbreak of typhoid fever in NAD. research using the CART Method. The results of the analysis indicate that the main factor causing typhoid fever was drinking water reservoirs. The other factors are waste water reservoirs, the physical quality of drinking water, a habit washing hands with soap before eating, the bowel, the dump, gender, socioeconomic status, habits of washing hands with soap after defecation and health education.

  12. Penyusunan Dan Penyelenggaran A La Carte Menu Pada Hotel Sinabung Dan Resort

    OpenAIRE

    Nasution, Rahmawaty

    2011-01-01

    Dalam operasional hotel, hotel memiliki beberapa departemen yang mempunyai peranan yang sangat penting dalam penjualan jasa dan pelayanan, dan salah satunya adalah departemen Food & Beverage. Food & Beverage mempunyai peran yang sangat besar dalam sebuah hotel, karena pendapatan sebuah hotel yang terbesar ada pada Food & Beverage terutama pada restoran. Adapun salah satu nama jenis restoran yang ada di Hotel Sinabung. Hotel Sinabung menyediakan jenis menu antara lain A La Carte Menu. M...

  13. Shopper marketing nutrition interventions: Social norms on grocery carts increase produce spending without increasing shopper budgets☆

    Science.gov (United States)

    Payne, Collin R.; Niculescu, Mihai; Just, David R.; Kelly, Michael P.

    2015-01-01

    Objectives We assessed the efficacy of an easy-to-implement shopper marketing nutrition intervention in a pilot and two additional studies to increase produce demand without decreasing store profitability or increasing shopper budgets. Methods We created grocery cart placards that detailed the number of produce items purchased (i.e., descriptive norm) at particular stores (i.e., provincial norm). The effect of these placards on produce spending was assessed across 971,706 individual person grocery store transactions aggregated by day. The pilot study designated a baseline period (in both control and intervention store) followed by installation of grocery cart placards (in the intervention store) for two weeks. The pilot study was conducted in Texas in 2012. In two additional stores, we designated baseline periods followed by 28 days of the same grocery cart placard intervention as in the pilot. Additional interventions were conducted in New Mexico in 2013. Results The pilot study resulted in a significant difference between average produce spending per day per person across treatment periods (i.e., intervention versus same time period in control) (16%) and the difference between average produce spending per day per person across stores in the control periods (4%); Furthermore, the same intervention in two additional stores resulted in significant produce spending increases of 12.4% and 7.5% per day per person respectively. In all stores, total spending did not change. Conclusions Descriptive and provincial social norm messages (i.e., on grocery cart placards) may be an overlooked tool to increase produce demand without decreasing store profitability and increasing shopper budgets. PMID:26844084

  14. Le CO.C.A.O: le commentaire de carte assisté par ordinateur

    Directory of Open Access Journals (Sweden)

    Joël CHARRE

    1991-12-01

    Full Text Available Le contenu d’une carte topographique peut être enregistré informatiquement sous forme d’un Système d’Information Géographique (SIG raster. En changeant de support, l’information change de nature: de fixe, elle devient manipulable, adaptable, vivante. L’analyse spatiale peut alors reposer sur des mesures de superficies, des fréquences de co-occurrences, des proximités...

  15. P300/CBP acts as a coactivator to cartilage homeoprotein-1 (Cart1), paired-like homeoprotein, through acetylation of the conserved lysine residue adjacent to the homeodomain.

    Science.gov (United States)

    Iioka, Takashi; Furukawa, Keizo; Yamaguchi, Akira; Shindo, Hiroyuki; Yamashita, Shunichi; Tsukazaki, Tomoo

    2003-08-01

    The paired-like homeoprotein, Cart1, is involved in skeletal development. We describe here that the general coactivator p300/CBP controls the transcription activity of Cart1 through acetylation of a lysine residue that is highly conserved in other homeoproteins. Acetylation of this residue increases the interaction between p300/CBP and Cart1 and enhances its transcriptional activation. Cart1 encodes a paired-like homeoprotein expressed selectively in chondrocyte lineage during embryonic development. Although its target gene remains unknown, gene disruption studies have revealed that Cart1 plays an important role for craniofacial bone formation as well as limb development by cooperating with another homeoprotein, Alx4. In this report, we study the functional involvement of p300/CBP, coactivators with intrinsic histone acetyltransferase (HAT) activity, in the transcriptional control of Cart1. To study the transcription activity of Cart1, a reporter construct containing a putative Cart1 binding site was transiently transfected with the expression vectors of each protein. The interaction between p300/CBP and Cart1 was investigated by glutathione S-transferase (GST) pull-down, yeast two-hybrid, and immunoprecipitation assays. In vitro acetylation assay was performed with the recombinant p300-HAT domain and Cart1 in the presence of acetyl-CoA. p300 and CBP stimulate Cart1-dependent transcription activity, and this transactivation is inhibited by E1A and Tax, oncoproteins that suppress the activity of p300/CBP. Cart1 binds to p300 in vivo and in vitro, and this requires the homeodomain of Cart 1 and N-terminal 139 amino acids of p300. Confocal microscopy analysis shows that Cart1 recruits overexpressed and endogenous p300 to a Cart1-specific subnuclear compartment. Cart1 is acetylated in vivo and sodium butyrate and trichostatin A, histone deacetylase inhibitors, markedly enhance the transcription activity of Cart1. Deletion and mutagenesis analysis identifies the 131st

  16. 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.

  17. Anthelmintic Resistance of Strongyle Nematodes to Ivermectin and Fenbendazole on Cart Horses in Gondar, Northwest Ethiopia

    Directory of Open Access Journals (Sweden)

    Zewdu Seyoum

    2017-01-01

    Full Text Available A study was conducted from November 2015 to April 2016 to determine fenbendazole and ivermectin resistance status of intestinal nematodes of cart horses in Gondar, Northwest Ethiopia. Forty-five strongyle infected animals were used for this study. The animals were randomly allocated into three groups (15 horses per group. Group I was treated with fenbendazole and Group II with ivermectin and Group III was left untreated. Faecal samples were collected from each cart horse before and after treatment. Accordingly, the reduction in the mean fecal egg count at fourteen days of treatment for ivermectin and fenbendazole was 97.25% and 79.4%, respectively. It was significantly different in net egg count between treatment and control groups after treatment. From the study, resistance level was determined for fenbendazole and suspected for ivermectin. In addition, a questionnaire survey was also conducted on 90 selected cart owners to assess their perception on anthelmintics. In the survey, the most available drugs in the study area used by the owners were fenbendazole and ivermectin. Most respondents have no knowledge about drug management techniques. Hence, animal health extension services to create awareness regarding anthelmintic management that plays a key role in reducing the anthelmintic resistance parasites.

  18. Anthelmintic Resistance of Strongyle Nematodes to Ivermectin and Fenbendazole on Cart Horses in Gondar, Northwest Ethiopia.

    Science.gov (United States)

    Seyoum, Zewdu; Zewdu, Alemu; Dagnachew, Shimelis; Bogale, Basazinew

    2017-01-01

    A study was conducted from November 2015 to April 2016 to determine fenbendazole and ivermectin resistance status of intestinal nematodes of cart horses in Gondar, Northwest Ethiopia. Forty-five strongyle infected animals were used for this study. The animals were randomly allocated into three groups (15 horses per group). Group I was treated with fenbendazole and Group II with ivermectin and Group III was left untreated. Faecal samples were collected from each cart horse before and after treatment. Accordingly, the reduction in the mean fecal egg count at fourteen days of treatment for ivermectin and fenbendazole was 97.25% and 79.4%, respectively. It was significantly different in net egg count between treatment and control groups after treatment. From the study, resistance level was determined for fenbendazole and suspected for ivermectin. In addition, a questionnaire survey was also conducted on 90 selected cart owners to assess their perception on anthelmintics. In the survey, the most available drugs in the study area used by the owners were fenbendazole and ivermectin. Most respondents have no knowledge about drug management techniques. Hence, animal health extension services to create awareness regarding anthelmintic management that plays a key role in reducing the anthelmintic resistance parasites.

  19. An application of CART algorithm in genetics: IGFs and cGH polymorphisms in Japanese quail

    Science.gov (United States)

    Kaplan, Selçuk

    2017-04-01

    The avian insulin-like growth factor-1 (IGFs) and avian growth hormone (cGH) genes are the most important genes that can affect bird performance traits because of its important function in growth and metabolism. Understanding the molecular genetic basis of variation in growth-related traits is of importance for continued improvement and increased rates of genetic gain. The objective of the present study was to identify polymorphisms of cGH and IGFs genes in Japanese quail using conventional least square method (LSM) and CART algorithm. Therefore, this study was aimed to demonstrate at determining the polymorphisms of two genes related growth characteristics via CART algorithm. A simulated data set was generated to analyze by adhering the results of some poultry genetic studies which it includes live weights at 5 weeks of age, 3 alleles and 6 genotypes of cGH and 2 alleles and 3 genotypes of IGFs. As a result, it has been determined that the CART algorithm has some advantages as for that LSM.

  20. Automated Cart with VIS/NIR Hyperspectral Reflectance and Fluorescence Imaging Capabilities

    Directory of Open Access Journals (Sweden)

    Alan M. Lefcourt

    2016-12-01

    Full Text Available A system to take high-resolution Visible/Near Infra-Red (VIS/NIR hyperspectral reflectance and fluorescence images in outdoor fields using ambient lighting or a pulsed laser (355 nm, respectively, for illumination purposes was designed, built, and tested. Components of the system include a semi-autonomous cart, a gated-intensified camera, a spectral adapter, a frequency-triple Nd:YAG (Neodymium-doped Yttrium Aluminium Garnet laser, and optics to convert the Gaussian laser beam into a line-illumination source. The front wheels of the cart are independently powered by stepper motors that support stepping or continuous motion. When stepping, a spreadsheet is used to program parameters of image sets to be acquired at each step. For example, the spreadsheet can be used to set delays before the start of image acquisitions, acquisition times, and laser attenuation. One possible use of this functionality would be to establish acquisition parameters to facilitate the measurement of fluorescence decay-curve characteristics. The laser and camera are mounted on an aluminum plate that allows the optics to be calibrated in a laboratory setting and then moved to the cart. The system was validated by acquiring images of fluorescence responses of spinach leaves and dairy manure.

  1. Design of the CART data system for the US Department of Energy's ARM Program

    International Nuclear Information System (INIS)

    Melton, R.B.; Campbell, A.P.; Edwards, D.M.; Kanciruk, P.; Tichler, J.L.

    1991-01-01

    The Department of Energy (DOE) has initiated a major atmospheric research effort to reduce the uncertainties found in general circulation and other models due to the effects of clouds and radiation. The objective of the Atmospheric Radiation Measurement Program (ARM) is to provide an experimental testbed for the study of important atmospheric effects, particularly cloud and radiative processes, and testing parameterizations of the processes for use in atmospheric models. This experimental testbed, known as the Clouds and Radiation Testbed (CART), will include a complex data system, the CART Data Environment (CDE). The major functions of the CDE will be to: acquire environments from instruments and external data sources; perform quality assessments of the data streams; create data streams of known quality to be used as model input compared to model output; execute the models and capture their predictions; and make data streams associated with model tests available to ARM investigators in near real-time. The CDE will also be expected to capture ancillary information (''meta-data'') associated with the data streams, provide data management facilities for design of ARM experiments, and provide for archival data storage. The first section of this paper presents background information on CART. Next the process for the functional design of the system is described, the functional requirements summarized, and the conceptual architecture of the CDE is presented. Finally, the status of the CDE design activities is summarized, and major technical challenges are discussed

  2. CAR-T cell therapy in ovarian cancer: from the bench to the bedside.

    Science.gov (United States)

    Zhu, Xinxin; Cai, Han; Zhao, Ling; Ning, Li; Lang, Jinghe

    2017-09-08

    Ovarian cancer (OC) is the most lethal gynecological malignancy and is responsible for most gynecological cancer deaths. Apart from conventional surgery, chemotherapy, and radiotherapy, chimeric antigen receptor-modified T (CAR-T) cells as a representative of adoptive cellular immunotherapy have received considerable attention in the research field of cancer treatment. CARs combine antigen specificity and T-cell-activating properties in a single fusion molecule. Several preclinical experiments and clinical trials have confirmed that adoptive cell immunotherapy using typical CAR-engineered T cells for OC is a promising treatment approach with striking clinical efficacy; moreover, the emerging CAR-Ts targeting various antigens also exert great potential. However, such therapies have side effects and toxicities, such as cytokine-associated and "on-target, off-tumor" toxicities. In this review, we systematically detail and highlight the present knowledge of CAR-Ts including the constructions, vectors, clinical applications, development challenges, and solutions of CAR-T-cell therapy for OC. We hope to provide new insight into OC treatment for the future.

  3. New Strategies for the Treatment of Solid Tumors with CAR-T Cells.

    Science.gov (United States)

    Zhang, Hao; Ye, Zhen-Long; Yuan, Zhen-Gang; Luo, Zheng-Qiang; Jin, Hua-Jun; Qian, Qi-Jun

    2016-01-01

    Recent years, we have witnessed significant progresses in both basic and clinical studies regarding novel therapeutic strategies with genetically engineered T cells. Modification with chimeric antigen receptors (CARs) endows T cells with tumor specific cytotoxicity and thus induce anti-tumor immunity against malignancies. However, targeting solid tumors is more challenging than targeting B-cell malignancies with CAR-T cells because of the histopathological structure features, specific antigens shortage and strong immunosuppressive environment of solid tumors. Meanwhile, the on-target/off-tumor toxicity caused by relative expression of target on normal tissues is another issue that should be reckoned. Optimization of the design of CAR vectors, exploration of new targets, addition of safe switches and combination with other treatments bring new vitality to the CAR-T cell based immunotherapy against solid tumors. In this review, we focus on the major obstacles limiting the application of CAR-T cell therapy toward solid tumors and summarize the measures to refine this new cancer therapeutic modality.

  4. Paralleled comparison of vectors for the generation of CAR-T cells.

    Science.gov (United States)

    Qin, Di-Yuan; Huang, Yong; Li, Dan; Wang, Yong-Sheng; Wang, Wei; Wei, Yu-Quan

    2016-09-01

    T-lymphocytes genetically engineered with the chimeric antigen receptor (CAR-T) have shown great therapeutic potential in cancer treatment. A variety of preclinical researches and clinical trials of CAR-T therapy have been carried out to lay the foundation for future clinical application. In these researches, several gene-transfer methods were used to deliver CARs or other genes into T-lymphocytes, equipping CAR-modified T cells with a property of recognizing and attacking antigen-expressing tumor cells in a major histocompatibility complex-independent manner. Here, we summarize the gene-transfer vectors commonly used in the generation of CAR-T cell, including retrovirus vectors, lentivirus vectors, the transposon/transposase system, the plasmid-based system, and the messenger RNA electroporation system. The following aspects were compared in parallel: efficiency of gene transfer, the integration methods in the modified T cells, foreground of scale-up production, and application and development in clinical trials. These aspects should be taken into account to generate the optimal CAR-gene vector that may be suitable for future clinical application.

  5. A Novel Biped Pattern Generator Based on Extended ZMP and Extended Cart-Table Model

    Directory of Open Access Journals (Sweden)

    Guangbin Sun

    2015-07-01

    Full Text Available This paper focuses on planning patterns for biped walking on complex terrains. Two problems are solved: ZMP (zero moment point cannot be used on uneven terrain, and the conventional cart-table model does not allow vertical CM (centre of mass motion. For the ZMP definition problem, we propose the extended ZMP (EZMP concept as an extension of ZMP to uneven terrains. It can be used to judge dynamic balance on universal terrains. We achieve a deeper insight into the connection and difference between ZMP and EZMP by adding different constraints. For the model problem, we extend the cart-table model by using a dynamic constraint instead of constant height constraint, which results in a mathematically symmetric set of three equations. In this way, the vertical motion is enabled and the resultant equations are still linear. Based on the extended ZMP concept and extended cart-table model, a biped pattern generator using triple preview controllers is constructed and implemented simultaneously to three dimensions. Using the proposed pattern generator, the Atlas robot is simulated. The simulation results show the robot can walk stably on rather complex terrains by accurately tracking extended ZMP.

  6. Analysis of performance measures to handle medical E-commerce shopping cart abandonment in cloud

    Directory of Open Access Journals (Sweden)

    Vedhanayagam Priya

    Full Text Available The E-commerce zone is crowded with many Internet users. Medical E-commerce has had significant growth in part because of a great deal of growth in the Indian E-commerce field. Medical E-commerce sites use cloud computing to guarantee a high quality of service anywhere and anytime in the world. For online access, the customer's expectations are very high. Medical E-commerce retailers are directed towards cloud service providers based on their quality of service. During online shopping, impatient customers may abandon a specific medical E-commerce shopping cart due to slow response. This is quite difficult to endure for a medical E-commerce firm. The research described herein observed the effect of shopping cart abandonment on medical E-commerce websites deployed in cloud computing. The impact of the idle virtual machine on customer impatience during medical E-commerce shopping was also studied. The ultimate aim of this study was to propose a stochastic queueing model and to yield results through probability generating functions. The results of the model may be highly useful for a medical E-commerce firm facing customer impatience, so as to design its service system to offer satisfactory quality of service. Keywords: Cloud computing, Queueing, Virtual machine, E-commerce, Cart abandonment, Quality of Service

  7. Developmental status of preschool children receiving cART: a descriptive cohort study.

    Science.gov (United States)

    Potterton, J; Hilburn, N; Strehlau, R

    2016-05-01

    HIV is known to cause neurodevelopmental problems in infants and young children. The impact of HIV on the development of preschool-age children has been less well described. The study was conducted at an urban paediatric HIV clinic in Johannesburg, South Africa. A sample of convenience was used. Sixty-eight medically stable children between the ages of 3 and 5 years were assessed with the Griffiths Scales of Mental Development. Children were excluded from the study if they had severe HIV encephalopathy, which made it impossible for them to participate in the items on the Griffiths Scales of Mental Development. The children had started combination antiretroviral treatment (cART) at a mean age of 8.1 months. The majority of the children were virologically suppressed and did not present with wasting or stunting. Severe overall developmental delay (z-scores perception were the most severely affected. Personal-social development was the least affected with only 13.4% of the children demonstrating severe delay. Despite having early access to cART, children infected with HIV are still at risk for severe developmental delay across a number of facets. Very early initiation of cART may help alleviate this problem. All preschool children infected with HIV should have routine developmental screening. © 2016 John Wiley & Sons Ltd.

  8. Nursing perception of the impact of medication carts on patient safety and ergonomics in a teaching health care center.

    Science.gov (United States)

    Rochais, Élise; Atkinson, Suzanne; Bussières, Jean-François

    2013-04-01

    In our Quebec (Canada) University Hospital Center, 68 medication carts have been implemented as part of a nationally funded project on drug distribution technologies. There are limited data published about the impact of medication carts in point-of-care units. Our main objective was to assess nursing staff's perception and satisfaction of medication carts on patient safety and ergonomics. Quantitative and qualitative cross-sectional study. Data were gathered from a printed questionnaire administered to nurses and an organized focus group composed of nurses and pharmacists. A total of 195 nurses completed the questionnaire. Eighty percent of the nurses agreed that medication carts made health care staff's work easier and 64% agreed that it helped to reduce medication incidents/accidents. Only 27% and 43% agreed that carts' location reduces the risk of patients' interruptions and colleagues' interruptions, respectively. A total of 17 suggestions were extracted from the focus group (n = 7 nurses; n = 3 pharmacist) and will be implemented in the next year. This descriptive study confirms the positive perception and satisfaction of nurses exposed to medication carts. However, interruptions are a major concern and source of dissatisfaction. The focus group has revealed many issues which will be improved.

  9. Allogeneic CD19-CAR-T cell infusion after allogeneic hematopoietic stem cell transplantation in B cell malignancies.

    Science.gov (United States)

    Liu, Jun; Zhong, Jiang F; Zhang, Xi; Zhang, Cheng

    2017-01-31

    Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is considered the cornerstone in treatment of hematological malignancies. However, relapse of the hematological disease after allo-HSCT remains a challenge and is associated with poor long-term survival. Chimeric antigen receptor redirected T cells (CAR-T cells) can lead to disease remission in patients with relapsed/refractory hematological malignancies. However, the therapeutic window for infusion of CAR-T cells post allo-HSCT and its efficacy are debatable. In this review, we first discuss the use of CAR-T cells for relapsed cases after allo-HSCT. We then review the toxicities and the occurrence of graft-versus-host disease in relapsed patients who received CAR-T cells post allo-HSCT. Finally, we review clinical trial registrations and the therapeutic time window for infusion of CAR-T cells post allo-HSCT. The treatment of allogeneic CAR-T cells is beneficial for patients with relapsed B cell malignancies after allo-HSCT with low toxicities and complications. However, multicenter clinical trials with larger sample sizes should be performed to select the optimal therapeutic window and confirm its efficacy.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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....

  16. 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).

  17. 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

  18. 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...

  19. 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...

  20. 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.

  1. 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...

  2. 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.

  3. 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.

  4. 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...

  5. 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...

  6. 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...

  7. Survival in HIV-infected patients after a cancer diagnosis in the cART Era: results of an italian multicenter study.

    Science.gov (United States)

    Gotti, Daria; Raffetti, Elena; Albini, Laura; Sighinolfi, Laura; Maggiolo, Franco; Di Filippo, Elisa; Ladisa, Nicoletta; Angarano, Gioacchino; Lapadula, Giuseppe; Pan, Angelo; Esposti, Anna Degli; Fabbiani, Massimiliano; Focà, Emanuele; Scalzini, Alfredo; Donato, Francesco; Quiros-Roldan, Eugenia

    2014-01-01

    We studied survival and associated risk factors in an Italian nationwide cohort of HIV-infected individuals after an AIDS-defining cancer (ADC) or non-AIDS-defining cancer (NADC) diagnosis in the modern cART era. Multi-center, retrospective, observational study of HIV patients included in the MASTER Italian Cohort with a cancer diagnosis from January 1998 to September 2012. Malignancies were divided into ADC or NADC on the basis of the Centre for Disease Control-1993 classification. Recurrence of cancer and metastases were excluded. Survivals were estimated according to the Kaplan-Meier method and compared according to the log-rank test. Statistically significant variables at univariate analysis were entered in a multivariate Cox regression model. Eight hundred and sixty-six cancer diagnoses were recorded among 13,388 subjects in the MASTER Database after 1998: 435 (51%) were ADCs and 431 (49%) were NADCs. Survival was more favorable after an ADC diagnosis than a NADC diagnosis (10-year survival: 62.7%±2.9% vs. 46%±4.2%; p = 0.017). Non-Hodgkin lymphoma had lower survival rates than patients with Kaposi sarcoma or cervical cancer (10-year survival: 48.2%±4.3% vs. 72.8%±4.0% vs. 78.5%±9.9%; pcancer showed better survival (10-year survival: 65.1%±14%) than lung cancer (1-year survival: 28%±8.7%), liver cancer (5-year survival: 31.9%±6.4%) or Hodgkin lymphoma (10-year survival: 24.8%±11.2%). Lower CD4+ count and intravenous drug use were significantly associated with decreased survival after ADCs or NADCs diagnosis. Exposure to cART was found to be associated with prolonged survival only in the case of ADCs. cART has improved survival in patients with an ADC diagnosis, whereas the prognosis after a diagnosis of NADCs is poor. Low CD4+ counts and intravenous drug use are risk factors for survival following a diagnosis of ADCs and Hodgkin lymphoma in the NADC group.

  8. Survival in HIV-infected patients after a cancer diagnosis in the cART Era: results of an italian multicenter study.

    Directory of Open Access Journals (Sweden)

    Daria Gotti

    Full Text Available OBJECTIVES: We studied survival and associated risk factors in an Italian nationwide cohort of HIV-infected individuals after an AIDS-defining cancer (ADC or non-AIDS-defining cancer (NADC diagnosis in the modern cART era. METHODS: Multi-center, retrospective, observational study of HIV patients included in the MASTER Italian Cohort with a cancer diagnosis from January 1998 to September 2012. Malignancies were divided into ADC or NADC on the basis of the Centre for Disease Control-1993 classification. Recurrence of cancer and metastases were excluded. Survivals were estimated according to the Kaplan-Meier method and compared according to the log-rank test. Statistically significant variables at univariate analysis were entered in a multivariate Cox regression model. RESULTS: Eight hundred and sixty-six cancer diagnoses were recorded among 13,388 subjects in the MASTER Database after 1998: 435 (51% were ADCs and 431 (49% were NADCs. Survival was more favorable after an ADC diagnosis than a NADC diagnosis (10-year survival: 62.7%±2.9% vs. 46%±4.2%; p = 0.017. Non-Hodgkin lymphoma had lower survival rates than patients with Kaposi sarcoma or cervical cancer (10-year survival: 48.2%±4.3% vs. 72.8%±4.0% vs. 78.5%±9.9%; p<0.001. Regarding NADCs, breast cancer showed better survival (10-year survival: 65.1%±14% than lung cancer (1-year survival: 28%±8.7%, liver cancer (5-year survival: 31.9%±6.4% or Hodgkin lymphoma (10-year survival: 24.8%±11.2%. Lower CD4+ count and intravenous drug use were significantly associated with decreased survival after ADCs or NADCs diagnosis. Exposure to cART was found to be associated with prolonged survival only in the case of ADCs. CONCLUSIONS: cART has improved survival in patients with an ADC diagnosis, whereas the prognosis after a diagnosis of NADCs is poor. Low CD4+ counts and intravenous drug use are risk factors for survival following a diagnosis of ADCs and Hodgkin lymphoma in the NADC group.

  9. 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.

  10. 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.

  11. 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...

  12. 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...

  13. 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...

  14. The hypothalamic satiety peptide CART is expressed in anorectic and non-anorectic pancreatic islet tumors and in the normal islet of Langerhans.

    Science.gov (United States)

    Jensen, P B; Kristensen, P; Clausen, J T; Judge, M E; Hastrup, S; Thim, L; Wulff, B S; Foged, C; Jensen, J; Holst, J J; Madsen, O D

    1999-03-26

    The hypothalamic satiety peptide CART (cocaine and amphetamine regulated transcript) is expressed at high levels in anorectic rat glucagonomas but not in hypoglycemic insulinomas. However, a non-anorectic metastasis derived from the glucagonoma retained high CART expression levels and produced circulating CART levels comparable to that of the anorectic tumors. Moreover, distinct glucagonoma lines derived by stable HES-1 transfection of the insulinoma caused severe anorexia but retained low circulating levels of CART comparable to that of insulinoma bearing or control rats. Islet tumor associated anorexia and circulating CART levels are thus not correlated, and in line with this peripheral administration of CART (5-50 mg/kg) produced no effect on feeding behavior. In the rat two alternatively spliced forms of CART mRNA exist and quantitative PCR revealed expression of both forms in the hypothalamus, in the different islet tumors, and in the islets of Langerhans. Immunocytochemistry as well as in situ hybridization localized CART expression to the somatostatin producing islet D cell. A potential endocrine/paracrine role of islet CART remains to be clarified.

  15. Causes of Death among AIDS Patients after Introduction of Free Combination Antiretroviral Therapy (cART) in Three Chinese Provinces, 2010-2011.

    Science.gov (United States)

    Wang, Liyan; Ge, Lin; Wang, Lu; Morano, Jamie P; Guo, Wei; Khoshnood, Kaveh; Qin, Qianqian; Ding, Zhengwei; Sun, Dingyong; Liu, Xiaoyan; Luo, Hongbing; Tillman, Jonas; Cui, Yan

    2015-01-01

    Although AIDS-related deaths have had significant economic and social impact following an increased disease burden internationally, few studies have evaluated the cause of AIDS-related deaths among patients with AIDS on combination anti-retroviral therapy (cART) in China. This study examines the causes of death among AIDS-patients in China and uses a methodology to increase data accuracy compared to the previous studies on AIDS-related mortality in China, that have taken the reported cause of death in the National HIV Registry at face-value. Death certificates/medical records were examined and a cross-sectional survey was conducted in three provinces to verify the causes of death among AIDS patients who died between January 1, 2010 and June 30, 2011. Chi-square analysis was conducted to examine the categorical variables by causes of death and by ART status. Univariate and multivariate logistic regression were used to evaluate factors associated with AIDS-related death versus non-AIDS related death. This study used a sample of 1,109 subjects. The average age at death was 44.5 years. AIDS-related deaths were significantly higher than non-AIDS and injury-related deaths. In the sample, 41.9% (465/1109) were deceased within a year of HIV diagnosis and 52.7% (584/1109) of the deceased AIDS patients were not on cART. For AIDS-related deaths (n = 798), statistically significant factors included CD4 count causes compared to those who didn't initiate ART at all.

  16. 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...

  17. GUCY2C-directed CAR-T cells oppose colorectal cancer metastases without autoimmunity.

    Science.gov (United States)

    Magee, Michael S; Kraft, Crystal L; Abraham, Tara S; Baybutt, Trevor R; Marszalowicz, Glen P; Li, Peng; Waldman, Scott A; Snook, Adam E

    2016-01-01

    Adoptive T-cell therapy (ACT) is an emerging paradigm in which T cells are genetically modified to target cancer-associated antigens and eradicate tumors. However, challenges treating epithelial cancers with ACT reflect antigen targets that are not tumor-specific, permitting immune damage to normal tissues, and preclinical testing in artificial xenogeneic models, preventing prediction of toxicities in patients. In that context, mucosa-restricted antigens expressed by cancers exploit anatomical compartmentalization which shields mucosae from systemic antitumor immunity. This shielding may be amplified with ACT platforms employing antibody-based chimeric antigen receptors (CARs), which mediate MHC-independent recog-nition of antigens. GUCY2C is a cancer mucosa antigen expressed on the luminal surfaces of the intestinal mucosa in mice and humans, and universally overexpressed by colorectal tumors, suggesting its unique utility as an ACT target. T cells expressing CARs directed by a GUCY2C-specific antibody fragment recognized GUCY2C, quantified by expression of activation markers and cytokines. Further, GUCY2C CAR-T cells lysed GUCY2C-expressing, but not GUCY2C-deficient, mouse colorectal cancer cells. Moreover, GUCY2C CAR-T cells reduced tumor number and morbidity and improved survival in mice harboring GUCY2C-expressing colorectal cancer metastases. GUCY2C-directed T cell efficacy reflected CAR affinity and surface expression and was achieved without immune-mediated damage to normal tissues in syngeneic mice. These observations highlight the potential for therapeutic translation of GUCY2C-directed CAR-T cells to treat metastatic tumors, without collateral autoimmunity, in patients with metastatic colorectal cancer.

  18. Identitat, ideologia i argumentació en les cartes al director del diari Levante EMV

    OpenAIRE

    Portalés Llop, Enric

    2017-01-01

    El nostre estudi es basa en l’anàlisi de l’autopresentació dels escriptors de cartes al director del diari Levante EMV. N’hem seleccionat 127 i hem dividit el treball en la identificació dels autors per la informació que ells mateixos aporten (nom, sexe) i aquella que es pot inferir de les tries pragmaestilístiques que han fet. Concloem que els indicis textuals triats (persones gramaticals, possessius, etc.) transmeten tot d’informacions rellevants sobre la identitat dels autors, la defensa d...

  19. Putting the horse before the cart: a pragmatist analysis of knowledge

    Directory of Open Access Journals (Sweden)

    Luís M. Augusto

    2011-01-01

    Full Text Available The definition of knowledge as justified true belief is the best we presently have. However, the canonical tripartite analysis of knowledge does not do justice to it due to a Platonic conception of a priori truth that puts the cart before the horse. Within a pragmatic approach, I argue that by doing away with a priori truth, namely by submitting truth to justification, and by accordingly altering the canonical analysis of knowledge, this is a fruitful definition. So fruitful indeed that it renders the Gettier counterexamples vacuous, allowing positive work in epistemology and related disciplines.

  20. New developments of the CARTE thermochemical code: A two-phase equation of state for nanocarbons

    Energy Technology Data Exchange (ETDEWEB)

    Dubois, Vincent, E-mail: vincent-jp.dubois@cea.fr; Pineau, Nicolas [CEA, DAM, DIF, F-91297 Arpajon (France)

    2016-01-07

    We developed a new equation of state (EOS) for nanocarbons in the thermodynamic range of high explosives detonation products (up to 50 GPa and 4000 K). This EOS was fitted to an extensive database of thermodynamic properties computed by molecular dynamics simulations of nanodiamonds and nano-onions with the LCBOPII potential. We reproduced the detonation properties of a variety of high explosives with the CARTE thermochemical code, including carbon-poor and carbon-rich explosives, with excellent accuracy.

  1. Analysis of effects of manhole covers on motorcycle driver maneuvers: a nonparametric classification tree approach.

    Science.gov (United States)

    Chang, Li-Yen

    2014-01-01

    A manhole cover is a removable plate forming the lid over the opening of a manhole to allow traffic to pass over the manhole and to prevent people from falling in. Because most manhole covers are placed in roadway traffic lanes, if these manhole covers are not appropriately installed or maintained, they can represent unexpected hazards on the road, especially for motorcycle drivers. The objective of this study is to identify the effects of manhole cover characteristics as well as driver factors and traffic and roadway conditions on motorcycle driver maneuvers. A video camera was used to record motorcycle drivers' maneuvers when they encountered an inappropriately installed or maintained manhole cover. Information on 3059 drivers' maneuver decisions was recorded. Classification and regression tree (CART) models were applied to explore factors that can significantly affect motorcycle driver maneuvers when passing a manhole cover. Nearly 50 percent of the motorcycle drivers decelerated or changed their driving path to reduce the effects of the manhole cover. The manhole cover characteristics including the level difference between manhole cover and pavement, the pavement condition over the manhole cover, and the size of the manhole cover can significantly affect motorcycle driver maneuvers. Other factors, including traffic conditions, lane width, motorcycle speed, and loading conditions, also have significant effects on motorcycle driver maneuvers. To reduce the effects and potential risks from the manhole covers, highway authorities not only need to make sure that any newly installed manhole covers are as level as possible but also need to regularly maintain all the manhole covers to ensure that they are in good condition. In the long run, the size of manhole covers should be kept as small as possible so that the impact of manhole covers on motorcycle drivers can be effectively reduced. Supplemental materials are available for this article. Go to the publisher

  2. 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...

  3. A History of Regression and Related Model-Fitting in the Earth Sciences (1636?-2000)

    International Nuclear Information System (INIS)

    Howarth, Richard J.

    2001-01-01

    roots in meeting the evident need for improved estimators in spatial interpolation. Technical advances in regression analysis during the 1970s embraced the development of regression diagnostics and consequent attention to outliers; the recognition of problems caused by correlated predictors, and the subsequent introduction of ridge regression to overcome them; and techniques for fitting errors-in-variables and mixture models. Improvements in computational power have enabled ever more computer-intensive methods to be applied. These include algorithms which are robust in the presence of outliers, for example Rousseeuw's 1984 Least Median Squares; nonparametric smoothing methods, such as kernel-functions, splines and Cleveland's 1979 LOcally WEighted Scatterplot Smoother (LOWESS); and the Classification and Regression Tree (CART) technique of Breiman and others in 1984. Despite a continuing improvement in the rate of technology-transfer from the statistical to the earth-science community, despite an abrupt drop to a time-lag of about 10 years following the introduction of digital computers, these more recent developments are only just beginning to penetrate beyond the research community of earth scientists. Examples of applications to problem-solving in the earth sciences are given

  4. Liver myeloid-derived suppressor cells expand in response to liver metastases in mice and inhibit the anti-tumor efficacy of anti-CEA CAR-T

    Science.gov (United States)

    Burga, Rachel A.; Thorn, Mitchell; Point, Gary R.; Guha, Prajna; Nguyen, Cang T.; Licata, Lauren A.; DeMatteo, Ronald P.; Ayala, Alfred; Espat, N. Joseph; Junghans, Richard P.; Katz, Steven C.

    2015-01-01

    Chimeric antigen receptor modified T cell (CAR-T) technology, a promising immunotherapeutic tool, has not been applied specifically to treat liver metastases (LM). While CAR-T delivery to LM can be optimized by regional intrahepatic infusion, we propose that liver CD11b+Gr-1+ myeloid-derived suppressor cells (L-MDSC) will inhibit the efficacy of CAR-T in the intrahepatic space. We studied anti-CEA CAR-T in a murine model of CEA+ LM and identified mechanisms through which L-MDSC expand and inhibit CAR-T function. We established CEA+ LM in mice and studied purified L-MDSC and responses to treatment with intrahepatic anti-CEA CAR-T infusions. L-MDSC expanded three-fold in response to LM and their expansion was dependent on GM-CSF, which was produced by tumor cells. L-MDSC utilized PD-L1 to suppress anti-tumor responses through engagement of PD-1 on CAR-T. GM-CSF, in cooperation with STAT3, promoted L-MDSC PD-L1 expression. CAR-T efficacy was rescued when mice received CAR-T in combination with MDSC depletion, GM-CSF neutralization to prevent MDSC expansion, or PD-L1 blockade. As L-MDSC suppressed anti-CEA CAR-T, infusion of anti-CEA CAR-T in tandem with agents targeting L-MDSC is a rational strategy for future clinical trials. PMID:25850344

  5. Potent anti-leukemia activities of humanized CD19-targeted CAR-T cells in patients with relapsed/refractory acute lymphoblastic leukemia.

    Science.gov (United States)

    Cao, Jiang; Wang, Gang; Cheng, Hai; Wei, Chen; Qi, Kunming; Sang, Wei; Zhenyu, Li; Shi, Ming; Li, Huizhong; Qiao, Jianlin; Pan, Bin; Zhao, Jing; Wu, Qingyun; Zeng, Lingyu; Niu, Mingshan; Jing, Guangjun; Zheng, Junnian; Xu, Kailin

    2018-04-10

    Chimeric antigen receptor T (CAR-T) cell therapy has shown promising results for relapsed/refractory (R/R) acute lymphoblastic leukemia (ALL). The immune response induced by murine single-chain variable fragment (scFv) of the CAR may limit CAR-T cell persistence and thus increases the risk of leukemia relapse. In this study, we developed a novel humanized scFv from the murine FMC63 antibody. A total of 18 R/R ALL patients with or without prior murine CD19 CAR-T therapy were treated with humanized CD19-targeted CAR-T cells (hCART19s). After lymphodepletion chemotherapy with cyclophosphamide and fludarabine, the patients received a single dose (1 × 10 6 /kg) of autologous hCART19s infusion. Among the 14 patients without previous CAR-T therapy, 13 (92.9%) achieved complete remission (CR) or CR with incomplete count recovery (CRi) on day 30, whereas 1 of the 3 patients who failed a second murine CAR-T infusion achieved CR after hCART19s infusion. At day 180, the overall and leukemia-free survival rates were 65.8% and 71.4%, respectively. The cumulative incidence of relapse was 22.6%, and the non-relapse mortality rate was 7.1%. During treatment, 13 patients developed grade 1-2 cytokine release syndrome (CRS), 4 patients developed grade 3-5 CRS, and 1 patient experienced reversible neurotoxicity. These results indicated that hCART19s could induce remission in patients with R/R B-ALL, especially in patients who received a reinfusion of murine CAR-T. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

  6. 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).

  7. Design of an automated cart and mount for a hyperspectral imaging system to be used in produce fields

    Science.gov (United States)

    Lefcourt, Alan M.; Kistler, Ross; Gadsden, S. Andrew

    2016-05-01

    The goal of this project was to construct a cart and a mounting system that would allow a hyperspectral laser-induced fluorescence imaging system (HLIFIS) to be used to detect fecal material in produce fields. Fecal contaminated produce is a recognized food safety risk. Previous research demonstrated the HLIFIS could detect fecal contamination in a laboratory setting. A cart was designed and built, and then tested to demonstrate that the cart was capable of moving at constant speeds or at precise intervals. A mounting system was designed and built to facilitate the critical alignment of the camera's imaging and the laser's illumination fields, and to allow the HLIFIS to be used in both field and laboratory settings without changing alignments. A hardened mount for the Powell lens that is used to produce the appropriate illumination profile was also designed, built, and tested.

  8. 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.

  9. Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping

    Directory of Open Access Journals (Sweden)

    Alison L. Thompson

    2018-04-01

    Full Text Available Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L. entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1 alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI, canopy height, normalized difference vegetative index (NDVI, and leaf area index (LAI differed among entries and showed an interaction with the water regime (p < 0.05. Broad-sense heritability (H2 estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033. Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions.

  10. Short-Term High-Fat Diet Increases Leptin Activation of CART Neurons and Advances Puberty in Female Mice.

    Science.gov (United States)

    Venancio, Jade Cabestre; Margatho, Lisandra Oliveira; Rorato, Rodrigo; Rosales, Roberta Ribeiro Costa; Debarba, Lucas Kniess; Coletti, Ricardo; Antunes-Rodrigues, Jose; Elias, Carol F; Elias, Lucila Leico K

    2017-11-01

    Leptin is a permissive factor for puberty initiation, participating as a metabolic cue in the activation of the kisspeptin (Kiss1)-gonadotropin-releasing hormone neuronal circuitry; however, it has no direct effect on Kiss1 neurons. Leptin acts on hypothalamic cocaine- and amphetamine-regulated transcript (CART) neurons, participating in the regulation of energy homeostasis. We investigated the influence of a short-term high-fat diet (HFD) on the effect of leptin on puberty timing. Kiss1-hrGFP female mice received a HFD or regular diet (RD) after weaning at postnatal day (PN)21 and were studied at PN28 and PN32. The HFD increased body weight and plasma leptin concentrations and decreased the age at vaginal opening (HFD, 32 ± 0.53 days; RD, 38 ± 0.67 days). Similar colocalization of neurokinin B and dynorphin in Kiss1-hrGFP neurons of the arcuate nucleus (ARC) was observed between the HFD and RD groups. The HFD increased CART expression in the ARC and Kiss1 messenger RNA expression in the anteroventral periventricular (AVPV)/anterior periventricular (Pe). The HFD also increased the number of ARC CART neurons expressing leptin-induced phosphorylated STAT3 (signal transducer and activator of transcription 3) at PN32. Close apposition of CART fibers to Kiss1-hrGFP neurons was observed in the ARC of both RD- and HFD-fed mice. In conclusion, these data reinforce the notion that a HFD increases kisspeptin expression in the AVPV/Pe and advances puberty initiation. Furthermore, we have demonstrated that the HFD-induced earlier puberty is associated with an increase in CART expression in the ARC. Therefore, these data indicate that CART neurons in the ARC can mediate the effect of leptin on Kiss1 neurons in early puberty induced by a HFD. Copyright © 2017 Endocrine Society.

  11. 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.

  12. A boundary-layer cloud study using Southern Great Plains Cloud and radiation testbed (CART) data

    Energy Technology Data Exchange (ETDEWEB)

    Albrecht, B.; Mace, G.; Dong, X.; Syrett, W. [Pennsylvania State Univ., University Park, PA (United States)] [and others

    1996-04-01

    Boundary layer clouds-stratus and fairweather cumulus - are closely coupled involves the radiative impact of the clouds on the surface energy budget and the strong dependence of cloud formation and maintenance on the turbulent fluxes of heat and moisture in the boundary layer. The continuous data collection at the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site provides a unique opportunity to study components of the coupling processes associated with boundary layer clouds and to provide descriptions of cloud and boundary layer structure that can be used to test parameterizations used in climate models. But before the CART data can be used for process studies and parameterization testing, it is necessary to evaluate and validate data and to develop techniques for effectively combining the data to provide meaningful descriptions of cloud and boundary layer characteristics. In this study we use measurements made during an intensive observing period we consider a case where low-level stratus were observed at the site for about 18 hours. This case is being used to examine the temporal evolution of cloud base, cloud top, cloud liquid water content, surface radiative fluxes, and boundary layer structure. A method for inferring cloud microphysics from these parameters is currently being evaluated.

  13. DeCART v1.2 User's Manual

    Energy Technology Data Exchange (ETDEWEB)

    Cho, J. Y.; Kim, K. S.; Kim, H. Y.; Lee, C. C.; Zee, S. Q; Joo, H. G

    2007-07-15

    DeCART (Deterministic Core Analysis based on Ray Tracing) is a whole core neutron transport code capable of direct subpin level flux calculation at power generating conditions. It does not require a priori homogenization nor group condensation needed in conventional reactor physics calculations. The depletion and transient calculation capabilities are also available. This manual serves as a self-sufficient guide to use the code. First of all, the various features of the code are explained which encompass various modeling options as well as the basic calculation functionalities. The instructions for running the code are also given with a description of the output files generated. Next, the underlying concepts and principles of preparing a DeCART model for a problem under consideration are presented. Each part of the input needed to specify the geometry, material composition, thermal operating condition, program execution control parameters are explained with examples. The descriptions of all the input cards are then followed. Finally, various sample model inputs ranging from a simple 2D pin cell to a realistic 3D core problem, steady-state to transient problems, and from rectangular to hexagonal core problems are presented.

  14. DeCART v1.1 user's manual

    Energy Technology Data Exchange (ETDEWEB)

    Cho, J. Y.; Kim, K. S.; Kim, H. Y.; Lee, C. C.; Zee, S. Q.; Joo, H. G

    2005-03-15

    DeCART (Deterministic Core Analysis based on Ray Tracing) is a whole core neutron transport code capable of direct subpin level flux calculation at power generating conditions. It does not require a priori homogenization nor group condensation needed in conventional reactor physics calculations. The depletion and transient calculation capabilities are also available. This manual serves as a self-sufficient guide to use the code. First of all, the various features of the code are explained which encompass various modeling options as well as the basic calculation functionalities. The instructions for running the code are also given with a description of the output files generated. Next, the underlying concepts and principles of preparing a DeCART model for a problem under consideration are presented. Each part of the input needed to specify the geometry, material composition, thermal operating condition, program execution control parameters are explained with examples. The descriptions of all the input cards are then followed. Finally, various sample model inputs ranging from a simple 2D pin cell to a realistic 3D core problem, steady-state to transient problems, are presented.

  15. It’s all change for the "carte de légitimation"

    CERN Multimedia

    2009-01-01

    From now on, the Swiss carte de légitimation will be issued to associates and users as well as staff members, and applications will be handled electronically, thus facilitating various procedures. In collaboration with the GS-AIS Group, the HR Department is continuing its modernisation of administrative procedures. Now that MARS forms and applications to participate in the saved leave scheme have been computerised and employment certificates and change of home address forms have been made available on line on a self-service basis, it’s the turn of the carte de légitimation to enter the digital era. In future, when a new card needs to be produced, the member of the personnel’s data will be forwarded electronically from CERN’s database to the database of the Swiss Federal Department of Foreign Affairs (DFAE), eliminating the need for a paper form. Similarly, paper ID photos will no longer be needed as the digital photo taken for ...

  16. Error quantification of the axial nodal diffusion kernel of the DeCART code

    International Nuclear Information System (INIS)

    Cho, J. Y.; Kim, K. S.; Lee, C. C.

    2006-01-01

    This paper is to quantify the transport effects involved in the axial nodal diffusion kernel of the DeCART code. The transport effects are itemized into three effects, the homogenization, the diffusion, and the nodal effects. A five pin model consisting of four fuel pins and one non-fuel pin is demonstrated to quantify the transport effects. The transport effects are analyzed for three problems, the single pin (SP), guide tube (GT) and control rod (CR) problems by replacing the non-fuel pin with the fuel pin, a guide-tube and a control rod pins, respectively. The homogenization and diffusion effects are estimated to be about -4 and -50 pcm for the eigenvalue, and less than 2 % for the node power. The nodal effect on the eigenvalue is evaluated to be about -50 pcm in the SP and GT problems, and +350 pcm in the CR problem. Regarding the node power, this effect induces about a 3 % error in the SP and GT problems, and about a 20 % error in the CR problem. The large power error in the CR problem is due to the plane thickness, and it can be decreased by using the adaptive plane size. From the error quantification, it is concluded that the homogenization and the diffusion effects are not controllable if DeCART maintains the diffusion kernel for the axial solution, but the nodal effect is controllable by introducing the adaptive plane size scheme. (authors)

  17. Loss of the HVEM Tumor Suppressor in Lymphoma and Restoration by Modified CAR-T Cells.

    Science.gov (United States)

    Boice, Michael; Salloum, Darin; Mourcin, Frederic; Sanghvi, Viraj; Amin, Rada; Oricchio, Elisa; Jiang, Man; Mottok, Anja; Denis-Lagache, Nicolas; Ciriello, Giovanni; Tam, Wayne; Teruya-Feldstein, Julie; de Stanchina, Elisa; Chan, Wing C; Malek, Sami N; Ennishi, Daisuke; Brentjens, Renier J; Gascoyne, Randy D; Cogné, Michel; Tarte, Karin; Wendel, Hans-Guido

    2016-10-06

    The HVEM (TNFRSF14) receptor gene is among the most frequently mutated genes in germinal center lymphomas. We report that loss of HVEM leads to cell-autonomous activation of B cell proliferation and drives the development of GC lymphomas in vivo. HVEM-deficient lymphoma B cells also induce a tumor-supportive microenvironment marked by exacerbated lymphoid stroma activation and increased recruitment of T follicular helper (T FH ) cells. These changes result from the disruption of inhibitory cell-cell interactions between the HVEM and BTLA (B and T lymphocyte attenuator) receptors. Accordingly, administration of the HVEM ectodomain protein (solHVEM (P37-V202) ) binds BTLA and restores tumor suppression. To deliver solHVEM to lymphomas in vivo, we engineered CD19-targeted chimeric antigen receptor (CAR) T cells that produce solHVEM locally and continuously. These modified CAR-T cells show enhanced therapeutic activity against xenografted lymphomas. Hence, the HVEM-BTLA axis opposes lymphoma development, and our study illustrates the use of CAR-T cells as "micro-pharmacies" able to deliver an anti-cancer protein. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Heterogeneous surface fluxes and their effects on the SGP CART site

    International Nuclear Information System (INIS)

    Doran, J.C.; Hu, Q.; Hubbe, J.M.; Liljegren, J.C.; Shaw, W.J.; Zhong, S.; Collatz, G.J.

    1995-03-01

    The treatment of subgrid-scale variations of surface properties and the resultant spatial variations of sensible and latent heat fluxes has received increasing attention in recent years. Mesoscale numerical simulations of highly idealized conditions, in which strong flux contrasts exist between adjacent surfaces, have shown that under some circumstances the secondary circulations induced by land-use differences can significantly affect the properties of the planetary boundary layer (PBL) and the region of the atmosphere above the PBL. At the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site, the fluxes from different land-surface types are not expected to differ as dramatically as those found in idealized simulations. Although the corresponding effects on the atmosphere should thus be less dramatic, they are still potentially important. From an ARM perspective, in tests of single column models (SCMs) it would be useful to understand the effects of the lower boundary conditions on model performance. We describe here our initial efforts to characterize the variable surface fluxes over the CART site and to assess their effects on the PBL that are important for the performance of SCMs

  19. 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...

  20. 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,...

  1. Reparación del cartílago articular con injerto libre de pericondrio estudio experimental

    OpenAIRE

    Ballesteros Vazquez, P.; Carranza Bencano, Andrés; Armas Padrón, J. R.; Saenz López de Rueda, F.

    1994-01-01

    Ante la incapacidad de regeneración espontánea de lesiones profundas y amplias del cartílago articular, estudiamos la reparación cartilaginosa con plastias de pericondrio tomadas de la región condro-costal e implantándolas con su cara condrogénica sobre una lesión osteocondral realizada en la superficie articular rotuliana. Macroscópica e histológicamente, a la octava semana, el neocartílago formado tenía igual apariencia que el cartílago hialino normal, no existiendo separació...

  2. HRB, Hydrostatically Regenerative Brake system for dust-carts and buses; HRB, ein hydraulischer Hybrid fuer Muellfahrzeuge und Busse

    Energy Technology Data Exchange (ETDEWEB)

    Ehret, Christine; Kliffken, Markus G.; Bracht, Detlef van [Bosch Rexroth AG (Germany)

    2009-07-01

    The HRB, Hydrostatically Regenerative Brake System by Rexroth, saves up to 25 percent diesel in heavy-duty industrial vehicles and also reduces exhaust emissions. Practical tests and field tests with a dust-cart of Haller Umweltsysteme GmbH and Co. KG in the city of Berlin proved this. The dust-cart has been in operation since July 2008. Measurements in practical operation have proved the savings calculated in simulations. Detailed economic efficiency calculations are possible in advance with a software also developed by Rexroth.

  3. Multi-pruning of decision trees for knowledge representation and classification

    KAUST Repository

    Azad, Mohammad

    2016-06-09

    We consider two important questions related to decision trees: first how to construct a decision tree with reasonable number of nodes and reasonable number of misclassification, and second how to improve the prediction accuracy of decision trees when they are used as classifiers. We have created a dynamic programming based approach for bi-criteria optimization of decision trees relative to the number of nodes and the number of misclassification. This approach allows us to construct the set of all Pareto optimal points and to derive, for each such point, decision trees with parameters corresponding to that point. Experiments on datasets from UCI ML Repository show that, very often, we can find a suitable Pareto optimal point and derive a decision tree with small number of nodes at the expense of small increment in number of misclassification. Based on the created approach we have proposed a multi-pruning procedure which constructs decision trees that, as classifiers, often outperform decision trees constructed by CART. © 2015 IEEE.

  4. Multi-pruning of decision trees for knowledge representation and classification

    KAUST Repository

    Azad, Mohammad; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

    2016-01-01

    We consider two important questions related to decision trees: first how to construct a decision tree with reasonable number of nodes and reasonable number of misclassification, and second how to improve the prediction accuracy of decision trees when they are used as classifiers. We have created a dynamic programming based approach for bi-criteria optimization of decision trees relative to the number of nodes and the number of misclassification. This approach allows us to construct the set of all Pareto optimal points and to derive, for each such point, decision trees with parameters corresponding to that point. Experiments on datasets from UCI ML Repository show that, very often, we can find a suitable Pareto optimal point and derive a decision tree with small number of nodes at the expense of small increment in number of misclassification. Based on the created approach we have proposed a multi-pruning procedure which constructs decision trees that, as classifiers, often outperform decision trees constructed by CART. © 2015 IEEE.

  5. Impact of Portion-Size Control for School a la Carte Items: Changes in Kilocalories and Macronutrients Purchased by Middle School Students

    Science.gov (United States)

    We assessed the impact of a pilot middle school a la carte intervention on food and beverage purchases, kilocalories, fat, carbohydrate, and protein sold per student, and nutrient density of the foods sold. A la carte sales were obtained from six middle schools in three states for 1 baseline week an...

  6. New Splitting Criteria for Decision Trees in Stationary Data Streams.

    Science.gov (United States)

    Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Rutkowski, Leszek; Duda, Piotr; Jaworski, Maciej

    2018-06-01

    The most popular tools for stream data mining are based on decision trees. In previous 15 years, all designed methods, headed by the very fast decision tree algorithm, relayed on Hoeffding's inequality and hundreds of researchers followed this scheme. Recently, we have demonstrated that although the Hoeffding decision trees are an effective tool for dealing with stream data, they are a purely heuristic procedure; for example, classical decision trees such as ID3 or CART cannot be adopted to data stream mining using Hoeffding's inequality. Therefore, there is an urgent need to develop new algorithms, which are both mathematically justified and characterized by good performance. In this paper, we address this problem by developing a family of new splitting criteria for classification in stationary data streams and investigating their probabilistic properties. The new criteria, derived using appropriate statistical tools, are based on the misclassification error and the Gini index impurity measures. The general division of splitting criteria into two types is proposed. Attributes chosen based on type- splitting criteria guarantee, with high probability, the highest expected value of split measure. Type- criteria ensure that the chosen attribute is the same, with high probability, as it would be chosen based on the whole infinite data stream. Moreover, in this paper, two hybrid splitting criteria are proposed, which are the combinations of single criteria based on the misclassification error and Gini index.

  7. 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)

  8. 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.

  9. 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 (...

  10. 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

  11. Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System.

    Science.gov (United States)

    Rau, Cheng-Shyuan; Wu, Shao-Chun; Chien, Peng-Chen; Kuo, Pao-Jen; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

    2017-11-22

    Background: In contrast to patients with traumatic subarachnoid hemorrhage (tSAH) in the presence of other types of intracranial hemorrhage, the prognosis of patients with isolated tSAH is good. The incidence of mortality in these patients ranges from 0-2.5%. However, few data or predictive models are available for the identification of patients with a high mortality risk. In this study, we aimed to construct a model for mortality prediction using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry, in a Level 1 trauma center. Methods: Five hundred and forty-five patients with isolated tSAH, including 533 patients who survived and 12 who died, between January 2009 and December 2016, were allocated to training ( n = 377) or test ( n = 168) sets. Using the data on demographics and injury characteristics, as well as laboratory data of the patients, classification and regression tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. Results: In this established DT model, three nodes (head Abbreviated Injury Scale (AIS) score ≤4, creatinine (Cr) 4 died, as did the 57% of those with an AIS score ≤4, but Cr ≥1.4 and age ≥76 years. All patients who did not meet the above-mentioned criteria survived. With all the variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 90.9% and specificity of 98.1%) and 97.7% (sensitivity of 100% and specificity of 97.7%), for the training set and test set, respectively. Conclusions: The study established a DT model with three nodes (head AIS score ≤4, Cr decision-making algorithm may help identify patients with a high risk of mortality.

  12. 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...

  13. Feeding-related effects of cart (cocaine and amphetamine regulated transcript) peptides and cholecystokinin in mouse obese models

    Czech Academy of Sciences Publication Activity Database

    Maletínská, Lenka; Maixnerová, Jana; Toma, Resha Shamas; Haugvicová, Renata; Slaninová, Jiřina; Železná, Blanka

    2006-01-01

    Roč. 12, Supplement (2006), s. 178 ISSN 1075-2617. [European Peptide Symposium /29./. 03.09.2006-08.09.2006, Gdansk] Institutional research plan: CEZ:AV0Z40550506 Keywords : CART peptides * food intake * mouse obesity * CCK Subject RIV: CC - Organic Chemistry

  14. Structure-activity relationship of cocaine- and amphetamine-regulated transcript (CART) by peptide analogs: Importance of disulfide bridges

    Czech Academy of Sciences Publication Activity Database

    Blechová, Miroslava; Nagelová, Veronika; Demianova, Zuzana; Železná, Blanka; Maletínská, Lenka

    2012-01-01

    Roč. 18, S1 (2012), S89-S90 ISSN 1075-2617. [European Peptide Symposium /32./. 02.09.2012-07.09.2012, Athens] Institutional research plan: CEZ:AV0Z40550506 Keywords : CART * neuropeptides * cell line PC12 * anorexigenic effect Subject RIV: CE - Biochemistry

  15. Turning a Common Lab Exercise into a Challenging Lab Experiment: Revisiting the Cart on an Inclined Track

    Science.gov (United States)

    Amato, Joseph C.; Williams, Roger E.

    2010-01-01

    A common lab exercise in the introductory college physics course employs a low-friction cart and associated track to study the validity of Newton's second law. Yet for college students, especially those who have already encountered a good high school physics course, the exercise must seem a little pointless. These students have already learned to…

  16. An "off-the-shelf" fratricide-resistant CAR-T for the treatment of T cell hematologic malignancies.

    Science.gov (United States)

    Cooper, Matthew L; Choi, Jaebok; Staser, Karl; Ritchey, Julie K; Devenport, Jessica M; Eckardt, Kayla; Rettig, Michael P; Wang, Bing; Eissenberg, Linda G; Ghobadi, Armin; Gehrs, Leah N; Prior, Julie L; Achilefu, Samuel; Miller, Christopher A; Fronick, Catrina C; O'Neal, Julie; Gao, Feng; Weinstock, David M; Gutierrez, Alejandro; Fulton, Robert S; DiPersio, John F

    2018-02-20

    T cell malignancies represent a group of hematologic cancers with high rates of relapse and mortality in patients for whom no effective targeted therapies exist. The shared expression of target antigens between chimeric antigen receptor (CAR) T cells and malignant T cells has limited the development of CAR-T because of unintended CAR-T fratricide and an inability to harvest sufficient autologous T cells. Here, we describe a fratricide-resistant "off-the-shelf" CAR-T (or UCART7) that targets CD7+ T cell malignancies and, through CRISPR/Cas9 gene editing, lacks both CD7 and T cell receptor alpha chain (TRAC) expression. UCART7 demonstrates efficacy against human T cell acute lymphoblastic leukemia (T-ALL) cell lines and primary T-ALL in vitro and in vivo without the induction of xenogeneic GvHD. Fratricide-resistant, allo-tolerant "off-the-shelf" CAR-T represents a strategy for treatment of relapsed and refractory T-ALL and non-Hodgkin's T cell lymphoma without a requirement for autologous T cells.

  17. Resting-state subcortical functional connectivity in HIV-infected patients on long-term cART

    NARCIS (Netherlands)

    Janssen, M.A.M.; Hinne, M.; Janssen, R.J.; Gerven, M.A.J. van; Steens, S.C.; Góraj, B.M.; Koopmans, P.P.; Kessels, R.P.C.

    2017-01-01

    Despite long-term successful treatment with cART, impairments in cognitive functioning are still being reported in HIV-infected patients. Since changes in cognitive function may be preceded by subtle changes in brain function, neuroimaging techniques, such as resting-state functional magnetic

  18. Synergistic effect of CART (cocaine- and amphetamine-regulated transcript) peptide and cholecystokinin on food intake regulation in lean mice

    Czech Academy of Sciences Publication Activity Database

    Maletínská, Lenka; Maixnerová, Jana; Matyšková, Resha; Haugvicová, Renata; Pirnik, Z.; Kiss, A.; Železná, Blanka

    2008-01-01

    Roč. 9, č. 101 (2008), s. 1-10 ISSN 1471-2202 R&D Projects: GA ČR GA303/05/0614 Institutional research plan: CEZ:AV0Z40550506; CEZ:AV0Z50200510 Keywords : mice * food intake * CART peptide Subject RIV: CE - Biochemistry Impact factor: 2.850, year: 2008

  19. Wagging the Dog, Carting the Horse: Testing and Improving Schools. Summary of Conference Proceedings. Research into Practice Project.

    Science.gov (United States)

    Herman, Joan; And Others

    The purpose of the conference, "Wagging the Dog, Carting the Horse: Testing vs. Improving California Schools," was to discuss alternative perspectives on testing and evaluation in education and their role in improving teaching and learning. Four papers were presented: (1) "Using Educational Evaluation for the Improvement of California Schools," by…

  20. 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...

  1. 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...

  2. 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.

  3. 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.

  4. The Effects of Direction of Exertion, Path, and Load Placement in Nursing Cart Pushing and Pulling Tasks: An Electromyographical Study.

    Science.gov (United States)

    Kao, Huei Chu; Lin, Chiuhsiang Joe; Lee, Yung Hui; Chen, Su Huang

    2015-01-01

    The purpose of this study was to explore the effects of direction of exertion (DOE) (pushing, pulling), path (walking in a straight line, turning left, walking uphill), and load placement (LP) (the 18 blocks were indicated by X, Y and Z axis; there were 3 levels on the X axis, 2 levels on the Y axis, and 3 levels on the Z axis) on muscle activity and ratings of perceived exertion in nursing cart pushing and pulling tasks. Ten participants who were female students and not experienced nurses were recruited to participate in the experiment. Each participant performed 108 experimental trials in the study, consisting of 2 directions of exertion (push and pull), 3 paths, and 18 load placements (indicated by X, Y and Z axes). A 23kg load was placed into one load placement. The dependent variables were electromyographic (EMG) data of four muscles collected bilaterally as follows: Left (L) and right (R) trapezius (TR), flexor digitorum superficialis (FDS), extensor digitorum (ED), and erector spinae (ES) and subjective ratings of perceived exertion (RPE). Split-split-plot ANOVA was conducted to analyze significant differences between DOE, path, and LP in the EMG and RPE data. Pulling cart tasks produced a significantly higher activation of the muscles (RTR:54.4%, LTR:50.3%, LFDS:57.0%, LED:63.4%, RES:40.7%, LES:36.7%) than pushing cart tasks (RTR:42.4%, LTR:35.1%, LFDS:32.3%, LED:55.1%, RES:33.3%, LES:32.1%). A significantly greater perceived exertion was found in pulling cart tasks than pushing cart tasks. Significantly higher activation of all muscles and perceived exertion were observed for walking uphill than walking in a straight line and turning left. Significantly lower muscle activity of all muscles and subject ratings were observed for the central position on the X axis, the bottom position on the Y axis, and the posterior position on the Z axis. These findings suggest that nursing staff should adopt forward pushing when moving a nursing cart, instead of backward

  5. 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...

  6. 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.

  7. Feeding a sustainable chemical industry: do we have the bioproducts cart before the feedstocks horse?

    Science.gov (United States)

    Dale, Bruce E

    2017-09-21

    A sustainable chemical industry cannot exist at scale without both sustainable feedstocks and feedstock supply chains to provide the raw materials. However, most current research focus is on producing the sustainable chemicals and materials. Little attention is given to how and by whom sustainable feedstocks will be supplied. In effect, we have put the bioproducts cart before the sustainable feedstocks horse. For example, bulky, unstable, non-commodity feedstocks such as crop residues probably cannot supply a large-scale sustainable industry. Likewise, those who manage land to produce feedstocks must benefit significantly from feedstock production, otherwise they will not participate in this industry and it will never grow. However, given real markets that properly reward farmers, demand for sustainable bioproducts and bioenergy can drive the adoption of more sustainable agricultural and forestry practices, providing many societal "win-win" opportunities. Three case studies are presented to show how this "win-win" process might unfold.

  8. Food Environment in Secondary Schools: À La Carte, Vending Machines, and Food Policies and Practices

    Science.gov (United States)

    French, Simone A.; Story, Mary; Fulkerson, Jayne A.; Gerlach, Anne Faricy

    2003-01-01

    Objectives. This study described the food environment in 20 Minnesota secondary schools. Methods. Data were collected on school food policies and the availability and nutritional content of foods in school à la carte (ALC) areas and vending machines (VMs). Results. Approximately 36% and 35% of foods in ALC areas and in VMs, respectively, met the lower-fat criterion (≤ 5.5 fat grams/serving). The chips/crackers category constituted the largest share of ALC foods (11.5%). The median number of VMs per school was 12 (4 soft drink, 2 snack, 5 other). Few school food policies were reported. Conclusions. The availability of healthful foods and beverages in schools as well as school food policies that foster healthful food choices among students needs greater attention. PMID:12835203

  9. The Impact of Groupement des Cartes Bancaires on Competition Law Enforcement

    Directory of Open Access Journals (Sweden)

    Piero Fattori

    2015-10-01

    Full Text Available The Groupement des Cartes bancaires represents a key judgment for competition enforcement, as it provides helpful clarification on the notion of “restriction by object” and on the judicial standard of review of Commission decisions. As of the first aspect, the ruling limited the restrictions by object to those which by their very nature and on the basis of the experience reveal a sufficient degree of harm to competition. On the standard required to the Court in reviewing competition decisions, the ECJ underlines the necessity of carrying out a full review, specifying that the presence of economic issues should not dispense the Court with an in-depth review of the law and the facts. The principles expressed in the judgment could have a great impact also at national level, where it could provide useful guidance both to Italian competition authority and to the Administrative Courts.

  10. Latin American Integration: Regionalism à la Carte in a Multipolar World?

    Directory of Open Access Journals (Sweden)

    Cintia Quiliconi

    2017-10-01

    Full Text Available This article presents an analysis of the different approaches proposed by authors who have done research on Latin American integration and regionalism, and suggests that there are three competing initiatives of integration and regionalism in the third wave of Latin American integration: Post-Liberal Regionalism contained within UNASUR and ALBA, Open Regionalism Reloaded in the region through the Pacific Alliance, and Multilateralism or Diplomatic Regionalism with a Latin American flavor envisaged in the recently created CELAC. The study concludes that these new developments of a regionalism à la carte are a product of dislocation of the economic agenda of regionalism towards a set of diverse issues. Hence it demands a rethinking of the theorization of Latin American Regionalism.

  11. 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.

  12. Site scientific mission plan for the southern great plains CART site January-June 2000.; TOPICAL

    International Nuclear Information System (INIS)

    Peppler, R. A.; Sisterson, D. L.; Lamb, P.

    2001-01-01

    The Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site was designed to help satisfy the data needs of the Atmospheric Radiation Measurement (ARM) Program Science Team. This Site Scientific Mission Plan defines the scientific priorities for site activities during the six months beginning on January 1, 2000, and looks forward in less detail to subsequent six-month periods. The primary purpose of this document is to provide scientific guidance for the development of plans for site operations. It also provides information on current plans to the ARM functional teams (Management Team, Data and Science Integration Team[DSIT], Operations Team, and Instrument Team[IT]) and serves to disseminate the plans more generally within the ARM Program and among the members of the Science Team. This document includes a description of the operational status of the site and the primary site activities envisioned, together with information concerning approved and proposed intensive observation periods (IOPs). The primary users of this document are the site operator, the site program manager, the Site Scientist Team (SST), the Science Team through the ARM Program science director, the ARM Program Experiment Center, and the aforementioned ARM Program functional teams. This plan is a living document that is updated and reissued every six months as the observational facilities are developed, tested, and augmented and as priorities are adjusted in response to developments in scientific planning and understanding. With this issue, many aspects of earlier Site Scientific Mission Plan reports have been moved to ARM sites on the World Wide Web. This report and all previous reports are available on the SGP CART web site

  13. Decision and Inhibitory Trees for Decision Tables with Many-Valued Decisions

    KAUST Repository

    Azad, Mohammad

    2018-06-06

    Decision trees are one of the most commonly used tools in decision analysis, knowledge representation, machine learning, etc., for its simplicity and interpretability. We consider an extension of dynamic programming approach to process the whole set of decision trees for the given decision table which was previously only attainable by brute-force algorithms. We study decision tables with many-valued decisions (each row may contain multiple decisions) because they are more reasonable models of data in many cases. To address this problem in a broad sense, we consider not only decision trees but also inhibitory trees where terminal nodes are labeled with “̸= decision”. Inhibitory trees can sometimes describe more knowledge from datasets than decision trees. As for cost functions, we consider depth or average depth to minimize time complexity of trees, and the number of nodes or the number of the terminal, or nonterminal nodes to minimize the space complexity of trees. We investigate the multi-stage optimization of trees relative to some cost functions, and also the possibility to describe the whole set of strictly optimal trees. Furthermore, we study the bi-criteria optimization cost vs. cost and cost vs. uncertainty for decision trees, and cost vs. cost and cost vs. completeness for inhibitory trees. The most interesting application of the developed technique is the creation of multi-pruning and restricted multi-pruning approaches which are useful for knowledge representation and prediction. The experimental results show that decision trees constructed by these approaches can often outperform the decision trees constructed by the CART algorithm. Another application includes the comparison of 12 greedy heuristics for single- and bi-criteria optimization (cost vs. cost) of trees. We also study the three approaches (decision tables with many-valued decisions, decision tables with most common decisions, and decision tables with generalized decisions) to handle

  14. Treatment of acute lymphoblastic leukaemia with the second generation of CD19 CAR-T containing either CD28 or 4-1BB.

    Science.gov (United States)

    Li, Shiqi; Zhang, Jiasi; Wang, Meiling; Fu, Gang; Li, Yunyan; Pei, Li; Xiong, Zhouxing; Qin, Dabing; Zhang, Rui; Tian, Xiaobo; Wei, Zhihao; Chen, Run; Chen, Xuejiao; Wan, Jia; Chen, Jun; Wei, Xia; Xu, Yanmin; Zhang, Pei; Wang, Ping; Peng, Xi; Yang, Sainan; Shen, Junjie; Yang, Zhi; Chen, Jieping; Qian, Cheng

    2018-04-10

    T cells modified with anti-CD19 chimeric antigen receptor (CAR) containing either CD28 or 4-1BB (also termed TNFRSF9, CD137) costimulatory signalling have shown great potential in the treatment of acute lymphoblastic leukaemia (ALL). However, the difference between CD28 and 4-1BB costimulatory signalling in CAR-T treatment has not been well elucidated in clinical trials. In this study, we treated 10 relapsed or refractory ALL patients with the second generation CD19 CAR-T. The first 5 patients were treated with CD28-CAR and the other 5 patients were treated with 4-1BB CAR-T. All the 10 patients were response-evaluable. Three patients achieved complete remission and 1 patient with extramedullary disease achieved partial response after CD28-CAR-T treatment. In the 4-1BB CAR-T treatment group, 3 patients achieved complete remission. Furthermore, FLT-3 ligand (FLT3LG) was highly correlated with response time and may serve as a prognosis factor. No severe adverse events were observed in these 10 treated patients. Our study showed that both CD28 CAR-T and 4-1BB CAR-T both worked for response but they differed in response pattern (peak reaction time, reaction lasting time and reaction degree), adverse events, cytokine secretion and immune-suppressive factor level. © 2018 John Wiley & Sons Ltd.

  15. FLAG-tagged CD19-specific CAR-T cells eliminate CD19-bearing solid tumor cells in vitro and in vivo.

    Science.gov (United States)

    Berahovich, Robert; Xu, Shirley; Zhou, Hua; Harto, Hizkia; Xu, Qumiao; Garcia, Andres; Liu, Fenyong; Golubovskaya, Vita M; Wu, Lijun

    2017-06-01

    Autologous T cells expressing chimeric antigen receptors (CARs) specific for CD19 have demonstrated remarkable efficacy as therapeutics for B cell malignancies. In the present study, we generated FLAG-tagged CD19-specific CAR-T cells (CD19-FLAG) and compared them to their non-tagged counterparts for their effects on solid and hematological cancer cells in vitro and in vivo . For solid tumors, we used HeLa cervical carcinoma cells engineered to overexpress CD19 (HeLa-CD19), and for hematological cancer we used Raji Burkitt's lymphoma cells, which endogenously express CD19. Like non-tagged CD19 CAR-T cells, CD19-FLAG CAR-T cells expanded in culture >100-fold and exhibited potent cytolytic activity against both HeLa-CD19 and Raji cells in vitro . CD19-FLAG CAR-T cells also secreted significantly more IFN-gamma and IL-2 than the control T cells. In vivo , CD19-FLAG CAR-T cells significantly blocked the growth of HeLa-CD19 solid tumors, increased tumor cleaved caspase-3 levels, and expanded systemically. CD19-FLAG CAR-T cells also significantly reduced Raji tumor burden and extended mouse survival. These results demonstrate the strong efficacy of FLAG-tagged CD19 CAR-T cells in solid and hematological cancer models.

  16. 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...

  17. 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.

  18. Effect of desipramine and citalopram treatment on forced swimming test-induced changes in cocaine- and amphetamine-regulated transcript (CART) immunoreactivity in mice.

    Science.gov (United States)

    Chung, Sung; Kim, Hee Jeong; Kim, Hyun Ju; Choi, Sun Hye; Kim, Jin Wook; Kim, Jeong Min; Shin, Kyung Ho

    2014-05-01

    Recent study demonstrates antidepressant-like effect of cocaine- and amphetamine-regulated transcript (CART) in the forced swimming test (FST), but less is known about whether antidepressant treatments alter levels of CART immunoreactivity (CART-IR) in the FST. To explore this possibility, we assessed the treatment effects of desipramine and citalopram, which inhibit the reuptake of norepinephrine and serotonin into the presynaptic terminals, respectively, on changes in levels of CART-IR before and after the test swim in mouse brain. Levels of CART-IR in the nucleus accumbens shell (AcbSh), dorsal bed nucleus of the stria terminalis (dBNST), and hypothalamic paraventricular nucleus (PVN) were significantly increased before the test swim by desipramine and citalopram treatments. This increase in CART-IR in the AcbSh, dBNST, and PVN before the test swim remained elevated by desipramine treatment after the test swim, but this increase in these brain areas returned to near control levels after test swim by citalopram treatment. Citalopram, but not desipramine, treatment increased levels of CART-IR in the central nucleus of the amygdala (CeA) and the locus ceruleus (LC) before the test swim, and this increase was returned to control levels after the test swim in the CeA, but not in the LC. These results suggest common and distinct regulation of CART by desipramine and citalopram treatments in the FST and raise the possibility that CART in the AcbSh, dBNST, and CeA may be involved in antidepressant-like effect in the FST.

  19. Actual use of and satisfaction associated with rollators and "shopping carts" among frail elderly Japanese people using day-service facilities.

    Science.gov (United States)

    Kitajima, Eiji; Moriuchi, Takefumi; Iso, Naoki; Sagari, Akira; Kikuchi, Yasuyuki; Higashi, Toshio

    2017-07-01

    Purpose This study aimed at clarifying the actual use of and satisfaction with rollators and "shopping carts" (wheeled walkers with storage) among frail elderly people, who were certified by a long-term care insurance system as users of facilities that provide day-service nursing care and rehabilitation. Methods We identified 1247 frail elderly people who used day-service facilities, and evaluated their actual use of, and satisfaction with, rollators and shopping carts. Results Forty-four (3.5%) individuals used rollators, and 53 (4.3%) used shopping carts. The shopping cart group contained more individuals who were certified as care level 1 (26.4%), than the rollator group (20.5%), and 52.8% of the shopping cart group was certified as care levels 1-3. The scores for "repairs and services" and "follow-up" from the Quebec User Evaluation of Satisfaction with assistive Technology second version (QUEST 2.0) survey were significantly higher in the rollator group than in the shopping cart group. Conclusions The QUEST 2.0 scores revealed that shopping cart users exhibit insufficient "repairs and services" and "follow-up" scores. As frail elderly people with poor care status accounted for >50% of the shopping cart group, these individuals urgently need walking aids that are tailored to their care status. Implications for Rehabilitation We conclude that walking aid fitting must be tailored to each persons care status, and suggest that a system should be established to allow occupational or physical therapists to provide this fitting Moreover, our analysis of the QUEST2.0 service scores revealed that repairs, services, and follow-up are insufficient to meet the needs of shopping cart users.

  20. Improving CART-Cell Therapy of Solid Tumors with Oncolytic Virus-Driven Production of a Bispecific T-cell Engager.

    Science.gov (United States)

    Wing, Anna; Fajardo, Carlos Alberto; Posey, Avery D; Shaw, Carolyn; Da, Tong; Young, Regina M; Alemany, Ramon; June, Carl H; Guedan, Sonia

    2018-05-01

    T cells expressing chimeric antigen receptors (CART) have shown significant promise in clinical trials to treat hematologic malignancies, but their efficacy in solid tumors has been limited. Oncolytic viruses have the potential to act in synergy with immunotherapies due to their immunogenic oncolytic properties and the opportunity of incorporating therapeutic transgenes in their genomes. Here, we hypothesized that an oncolytic adenovirus armed with an EGFR-targeting, bispecific T-cell engager (OAd-BiTE) would improve the outcome of CART-cell therapy in solid tumors. We report that CART cells targeting the folate receptor alpha (FR-α) successfully infiltrated preestablished xenograft tumors but failed to induce complete responses, presumably due to the presence of antigen-negative cancer cells. We demonstrated that OAd-BiTE-mediated oncolysis significantly improved CART-cell activation and proliferation, while increasing cytokine production and cytotoxicity, and showed an in vitro favorable safety profile compared with EGFR-targeting CARTs. BiTEs secreted from infected cells redirected CART cells toward EGFR in the absence of FR-α, thereby addressing tumor heterogeneity. BiTE secretion also redirected CAR-negative, nonspecific T cells found in CART-cell preparations toward tumor cells. The combinatorial approach improved antitumor efficacy and prolonged survival in mouse models of cancer when compared with the monotherapies, and this was the result of an increased BiTE-mediated T-cell activation in tumors. Overall, these results demonstrated that the combination of a BiTE-expressing oncolytic virus with adoptive CART-cell therapy overcomes key limitations of CART cells and BiTEs as monotherapies in solid tumors and encourage its further evaluation in human trials. Cancer Immunol Res; 6(5); 605-16. ©2018 AACR . ©2018 American Association for Cancer Research.