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Sample records for nonparametric methods cart

  1. Nonparametric methods for volatility density estimation

    NARCIS (Netherlands)

    Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.

    2009-01-01

    Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the density of the volatility process. Both models based on

  2. portfolio optimization based on nonparametric estimation methods

    Directory of Open Access Journals (Sweden)

    mahsa ghandehari

    2017-03-01

    Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.

  3. Nonparametric methods in actigraphy: An update

    Directory of Open Access Journals (Sweden)

    Bruno S.B. Gonçalves

    2014-09-01

    Full Text Available Circadian rhythmicity in humans has been well studied using actigraphy, a method of measuring gross motor movement. As actigraphic technology continues to evolve, it is important for data analysis to keep pace with new variables and features. Our objective is to study the behavior of two variables, interdaily stability and intradaily variability, to describe rest activity rhythm. Simulated data and actigraphy data of humans, rats, and marmosets were used in this study. We modified the method of calculation for IV and IS by modifying the time intervals of analysis. For each variable, we calculated the average value (IVm and ISm results for each time interval. Simulated data showed that (1 synchronization analysis depends on sample size, and (2 fragmentation is independent of the amplitude of the generated noise. We were able to obtain a significant difference in the fragmentation patterns of stroke patients using an IVm variable, while the variable IV60 was not identified. Rhythmic synchronization of activity and rest was significantly higher in young than adults with Parkinson׳s when using the ISM variable; however, this difference was not seen using IS60. We propose an updated format to calculate rhythmic fragmentation, including two additional optional variables. These alternative methods of nonparametric analysis aim to more precisely detect sleep–wake cycle fragmentation and synchronization.

  4. Speaker Linking and Applications using Non-Parametric Hashing Methods

    Science.gov (United States)

    2016-09-08

    nonparametric estimate of a multivariate density function,” The Annals of Math- ematical Statistics , vol. 36, no. 3, pp. 1049–1051, 1965. [9] E. A. Patrick...Speaker Linking and Applications using Non-Parametric Hashing Methods† Douglas Sturim and William M. Campbell MIT Lincoln Laboratory, Lexington, MA...with many approaches [1, 2]. For this paper, we focus on using i-vectors [2], but the methods apply to any embedding. For the task of speaker QBE and

  5. Application of nonparametric statistic method for DNBR limit calculation

    International Nuclear Information System (INIS)

    Dong Bo; Kuang Bo; Zhu Xuenong

    2013-01-01

    Background: Nonparametric statistical method is a kind of statistical inference method not depending on a certain distribution; it calculates the tolerance limits under certain probability level and confidence through sampling methods. The DNBR margin is one important parameter of NPP design, which presents the safety level of NPP. Purpose and Methods: This paper uses nonparametric statistical method basing on Wilks formula and VIPER-01 subchannel analysis code to calculate the DNBR design limits (DL) of 300 MW NPP (Nuclear Power Plant) during the complete loss of flow accident, simultaneously compared with the DL of DNBR through means of ITDP to get certain DNBR margin. Results: The results indicate that this method can gain 2.96% DNBR margin more than that obtained by ITDP methodology. Conclusions: Because of the reduction of the conservation during analysis process, the nonparametric statistical method can provide greater DNBR margin and the increase of DNBR margin is benefited for the upgrading of core refuel scheme. (authors)

  6. Comparing parametric and nonparametric regression methods for panel data

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

  7. 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.

  8. Investigation of MLE in nonparametric estimation methods of reliability function

    International Nuclear Information System (INIS)

    Ahn, Kwang Won; Kim, Yoon Ik; Chung, Chang Hyun; Kim, Kil Yoo

    2001-01-01

    There have been lots of trials to estimate a reliability function. In the ESReDA 20 th seminar, a new method in nonparametric way was proposed. The major point of that paper is how to use censored data efficiently. Generally there are three kinds of approach to estimate a reliability function in nonparametric way, i.e., Reduced Sample Method, Actuarial Method and Product-Limit (PL) Method. The above three methods have some limits. So we suggest an advanced method that reflects censored information more efficiently. In many instances there will be a unique maximum likelihood estimator (MLE) of an unknown parameter, and often it may be obtained by the process of differentiation. It is well known that the three methods generally used to estimate a reliability function in nonparametric way have maximum likelihood estimators that are uniquely exist. So, MLE of the new method is derived in this study. The procedure to calculate a MLE is similar just like that of PL-estimator. The difference of the two is that in the new method, the mass (or weight) of each has an influence of the others but the mass in PL-estimator not

  9. International Conference on Robust Rank-Based and Nonparametric Methods

    CERN Document Server

    McKean, Joseph

    2016-01-01

    The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with r...

  10. Using non-parametric methods in econometric production analysis

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    2012-01-01

    by investigating the relationship between the elasticity of scale and the farm size. We use a balanced panel data set of 371~specialised crop farms for the years 2004-2007. A non-parametric specification test shows that neither the Cobb-Douglas function nor the Translog function are consistent with the "true......Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify a functional form of the production function of which the Cobb...... parameter estimates, but also in biased measures which are derived from the parameters, such as elasticities. Therefore, we propose to use non-parametric econometric methods. First, these can be applied to verify the functional form used in parametric production analysis. Second, they can be directly used...

  11. Using non-parametric methods in econometric production analysis

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify the functional form of the production function. Most often, the Cobb...... results—including measures that are of interest of applied economists, such as elasticities. Therefore, we propose to use nonparametric econometric methods. First, they can be applied to verify the functional form used in parametric estimations of production functions. Second, they can be directly used...

  12. Digital spectral analysis parametric, non-parametric and advanced methods

    CERN Document Server

    Castanié, Francis

    2013-01-01

    Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods a

  13. A robust nonparametric method for quantifying undetected extinctions.

    Science.gov (United States)

    Chisholm, Ryan A; Giam, Xingli; Sadanandan, Keren R; Fung, Tak; Rheindt, Frank E

    2016-06-01

    How many species have gone extinct in modern times before being described by science? To answer this question, and thereby get a full assessment of humanity's impact on biodiversity, statistical methods that quantify undetected extinctions are required. Such methods have been developed recently, but they are limited by their reliance on parametric assumptions; specifically, they assume the pools of extant and undetected species decay exponentially, whereas real detection rates vary temporally with survey effort and real extinction rates vary with the waxing and waning of threatening processes. We devised a new, nonparametric method for estimating undetected extinctions. As inputs, the method requires only the first and last date at which each species in an ensemble was recorded. As outputs, the method provides estimates of the proportion of species that have gone extinct, detected, or undetected and, in the special case where the number of undetected extant species in the present day is assumed close to zero, of the absolute number of undetected extinct species. The main assumption of the method is that the per-species extinction rate is independent of whether a species has been detected or not. We applied the method to the resident native bird fauna of Singapore. Of 195 recorded species, 58 (29.7%) have gone extinct in the last 200 years. Our method projected that an additional 9.6 species (95% CI 3.4, 19.8) have gone extinct without first being recorded, implying a true extinction rate of 33.0% (95% CI 31.0%, 36.2%). We provide R code for implementing our method. Because our method does not depend on strong assumptions, we expect it to be broadly useful for quantifying undetected extinctions. © 2016 Society for Conservation Biology.

  14. Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method.

    Science.gov (United States)

    Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A

    2017-06-30

    Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  15. The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard

    and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...

  16. Nonparametric Change Point Diagnosis Method of Concrete Dam Crack Behavior Abnormality

    Directory of Open Access Journals (Sweden)

    Zhanchao Li

    2013-01-01

    Full Text Available The study on diagnosis method of concrete crack behavior abnormality has always been a hot spot and difficulty in the safety monitoring field of hydraulic structure. Based on the performance of concrete dam crack behavior abnormality in parametric statistical model and nonparametric statistical model, the internal relation between concrete dam crack behavior abnormality and statistical change point theory is deeply analyzed from the model structure instability of parametric statistical model and change of sequence distribution law of nonparametric statistical model. On this basis, through the reduction of change point problem, the establishment of basic nonparametric change point model, and asymptotic analysis on test method of basic change point problem, the nonparametric change point diagnosis method of concrete dam crack behavior abnormality is created in consideration of the situation that in practice concrete dam crack behavior may have more abnormality points. And the nonparametric change point diagnosis method of concrete dam crack behavior abnormality is used in the actual project, demonstrating the effectiveness and scientific reasonableness of the method established. Meanwhile, the nonparametric change point diagnosis method of concrete dam crack behavior abnormality has a complete theoretical basis and strong practicality with a broad application prospect in actual project.

  17. Transition redshift: new constraints from parametric and nonparametric methods

    Energy Technology Data Exchange (ETDEWEB)

    Rani, Nisha; Mahajan, Shobhit; Mukherjee, Amitabha [Department of Physics and Astrophysics, University of Delhi, New Delhi 110007 (India); Jain, Deepak [Deen Dayal Upadhyaya College, University of Delhi, New Delhi 110015 (India); Pires, Nilza, E-mail: nrani@physics.du.ac.in, E-mail: djain@ddu.du.ac.in, E-mail: shobhit.mahajan@gmail.com, E-mail: amimukh@gmail.com, E-mail: npires@dfte.ufrn.br [Departamento de Física Teórica e Experimental, UFRN, Campus Universitário, Natal, RN 59072-970 (Brazil)

    2015-12-01

    In this paper, we use the cosmokinematics approach to study the accelerated expansion of the Universe. This is a model independent approach and depends only on the assumption that the Universe is homogeneous and isotropic and is described by the FRW metric. We parametrize the deceleration parameter, q(z), to constrain the transition redshift (z{sub t}) at which the expansion of the Universe goes from a decelerating to an accelerating phase. We use three different parametrizations of q(z) namely, q{sub I}(z)=q{sub 1}+q{sub 2}z, q{sub II} (z) = q{sub 3} + q{sub 4} ln (1 + z) and q{sub III} (z)=½+q{sub 5}/(1+z){sup 2}. A joint analysis of the age of galaxies, strong lensing and supernovae Ia data indicates that the transition redshift is less than unity i.e. z{sub t} < 1. We also use a nonparametric approach (LOESS+SIMEX) to constrain z{sub t}. This too gives z{sub t} < 1 which is consistent with the value obtained by the parametric approach.

  18. Modern nonparametric, robust and multivariate methods festschrift in honour of Hannu Oja

    CERN Document Server

    Taskinen, Sara

    2015-01-01

    Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.

  19. Nonparametric method for failures diagnosis in the actuating subsystem of aircraft control system

    Science.gov (United States)

    Terentev, M. N.; Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

    2018-02-01

    In this paper we design a nonparametric method for failures diagnosis in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on analytical nonparametric one-step-ahead state prediction approach. This makes it possible to predict the behavior of unidentified and failure dynamic systems, to weaken the requirements to control signals, and to reduce the diagnostic time and problem complexity.

  20. A non-parametric method for correction of global radiation observations

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Perers, Bengt

    2013-01-01

    in the observations are corrected. These are errors such as: tilt in the leveling of the sensor, shadowing from surrounding objects, clipping and saturation in the signal processing, and errors from dirt and wear. The method is based on a statistical non-parametric clear-sky model which is applied to both...

  1. Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods - A comparison

    NARCIS (Netherlands)

    Verrelst, Jochem; Rivera, Juan Pablo; Veroustraete, Frank; Muñoz-Marí, Jordi; Clevers, J.G.P.W.; Camps-Valls, Gustau; Moreno, José

    2015-01-01

    Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC),

  2. Hadron Energy Reconstruction for ATLAS Barrel Combined Calorimeter Using Non-Parametrical Method

    CERN Document Server

    Kulchitskii, Yu A

    2000-01-01

    Hadron energy reconstruction for the ATLAS barrel prototype combined calorimeter in the framework of the non-parametrical method is discussed. The non-parametrical method utilizes only the known e/h ratios and the electron calibration constants and does not require the determination of any parameters by a minimization technique. Thus, this technique lends itself to fast energy reconstruction in a first level trigger. The reconstructed mean values of the hadron energies are within \\pm1% of the true values and the fractional energy resolution is [(58\\pm 3)%{\\sqrt{GeV}}/\\sqrt{E}+(2.5\\pm0.3)%]\\bigoplus(1.7\\pm0.2) GeV/E. The value of the e/h ratio obtained for the electromagnetic compartment of the combined calorimeter is 1.74\\pm0.04. Results of a study of the longitudinal hadronic shower development are also presented.

  3. The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables

    OpenAIRE

    Ambrogioni, Luca; Güçlü, Umut; van Gerven, Marcel A. J.; Maris, Eric

    2017-01-01

    This paper introduces the kernel mixture network, a new method for nonparametric estimation of conditional probability densities using neural networks. We model arbitrarily complex conditional densities as linear combinations of a family of kernel functions centered at a subset of training points. The weights are determined by the outer layer of a deep neural network, trained by minimizing the negative log likelihood. This generalizes the popular quantized softmax approach, which can be seen ...

  4. Nonparametric Change Point Diagnosis Method of Concrete Dam Crack Behavior Abnormality

    OpenAIRE

    Li, Zhanchao; Gu, Chongshi; Wu, Zhongru

    2013-01-01

    The study on diagnosis method of concrete crack behavior abnormality has always been a hot spot and difficulty in the safety monitoring field of hydraulic structure. Based on the performance of concrete dam crack behavior abnormality in parametric statistical model and nonparametric statistical model, the internal relation between concrete dam crack behavior abnormality and statistical change point theory is deeply analyzed from the model structure instability of parametric statistical model ...

  5. Bootstrapping the economy -- a non-parametric method of generating consistent future scenarios

    OpenAIRE

    Müller, Ulrich A; Bürgi, Roland; Dacorogna, Michel M

    2004-01-01

    The fortune and the risk of a business venture depends on the future course of the economy. There is a strong demand for economic forecasts and scenarios that can be applied to planning and modeling. While there is an ongoing debate on modeling economic scenarios, the bootstrapping (or resampling) approach presented here has several advantages. As a non-parametric method, it directly relies on past market behaviors rather than debatable assumptions on models and parameters. Simultaneous dep...

  6. A nonparametric approach to calculate critical micelle concentrations: the local polynomial regression method

    Energy Technology Data Exchange (ETDEWEB)

    Lopez Fontan, J.L.; Costa, J.; Ruso, J.M.; Prieto, G. [Dept. of Applied Physics, Univ. of Santiago de Compostela, Santiago de Compostela (Spain); Sarmiento, F. [Dept. of Mathematics, Faculty of Informatics, Univ. of A Coruna, A Coruna (Spain)

    2004-02-01

    The application of a statistical method, the local polynomial regression method, (LPRM), based on a nonparametric estimation of the regression function to determine the critical micelle concentration (cmc) is presented. The method is extremely flexible because it does not impose any parametric model on the subjacent structure of the data but rather allows the data to speak for themselves. Good concordance of cmc values with those obtained by other methods was found for systems in which the variation of a measured physical property with concentration showed an abrupt change. When this variation was slow, discrepancies between the values obtained by LPRM and others methods were found. (orig.)

  7. Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

    Science.gov (United States)

    Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

    2016-01-01

    In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration

  8. 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.

  9. Impulse response identification with deterministic inputs using non-parametric methods

    International Nuclear Information System (INIS)

    Bhargava, U.K.; Kashyap, R.L.; Goodman, D.M.

    1985-01-01

    This paper addresses the problem of impulse response identification using non-parametric methods. Although the techniques developed herein apply to the truncated, untruncated, and the circulant models, we focus on the truncated model which is useful in certain applications. Two methods of impulse response identification will be presented. The first is based on the minimization of the C/sub L/ Statistic, which is an estimate of the mean-square prediction error; the second is a Bayesian approach. For both of these methods, we consider the effects of using both the identity matrix and the Laplacian matrix as weights on the energy in the impulse response. In addition, we present a method for estimating the effective length of the impulse response. Estimating the length is particularly important in the truncated case. Finally, we develop a method for estimating the noise variance at the output. Often, prior information on the noise variance is not available, and a good estimate is crucial to the success of estimating the impulse response with a nonparametric technique

  10. Nonparametric method for failures detection and localization in the actuating subsystem of aircraft control system

    Science.gov (United States)

    Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

    2018-02-01

    In this paper we design a nonparametric method for failures detection and localization in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on algebraic solvability conditions for the aircraft model identification problem. This makes it possible to significantly increase the efficiency of detection and localization problem solution by completely eliminating errors, associated with aircraft model uncertainties.

  11. Comparison of Parametric and Nonparametric Methods for Analyzing the Bias of a Numerical Model

    Directory of Open Access Journals (Sweden)

    Isaac Mugume

    2016-01-01

    Full Text Available Numerical models are presently applied in many fields for simulation and prediction, operation, or research. The output from these models normally has both systematic and random errors. The study compared January 2015 temperature data for Uganda as simulated using the Weather Research and Forecast model with actual observed station temperature data to analyze the bias using parametric (the root mean square error (RMSE, the mean absolute error (MAE, mean error (ME, skewness, and the bias easy estimate (BES and nonparametric (the sign test, STM methods. The RMSE normally overestimates the error compared to MAE. The RMSE and MAE are not sensitive to direction of bias. The ME gives both direction and magnitude of bias but can be distorted by extreme values while the BES is insensitive to extreme values. The STM is robust for giving the direction of bias; it is not sensitive to extreme values but it does not give the magnitude of bias. The graphical tools (such as time series and cumulative curves show the performance of the model with time. It is recommended to integrate parametric and nonparametric methods along with graphical methods for a comprehensive analysis of bias of a numerical model.

  12. Hadron energy reconstruction for the ATLAS calorimetry in the framework of the nonparametrical method

    CERN Document Server

    Akhmadaliev, S Z; Ambrosini, G; Amorim, A; Anderson, K; Andrieux, M L; Aubert, Bernard; Augé, E; Badaud, F; Baisin, L; Barreiro, F; Battistoni, G; Bazan, A; Bazizi, K; Belymam, A; Benchekroun, D; Berglund, S R; Berset, J C; Blanchot, G; Bogush, A A; Bohm, C; Boldea, V; Bonivento, W; Bosman, M; Bouhemaid, N; Breton, D; Brette, P; Bromberg, C; Budagov, Yu A; Burdin, S V; Calôba, L P; Camarena, F; Camin, D V; Canton, B; Caprini, M; Carvalho, J; Casado, M P; Castillo, M V; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Chadelas, R; Chalifour, M; Chekhtman, A; Chevalley, J L; Chirikov-Zorin, I E; Chlachidze, G; Citterio, M; Cleland, W E; Clément, C; Cobal, M; Cogswell, F; Colas, Jacques; Collot, J; Cologna, S; Constantinescu, S; Costa, G; Costanzo, D; Crouau, M; Daudon, F; David, J; David, M; Davidek, T; Dawson, J; De, K; de La Taille, C; Del Peso, J; Del Prete, T; de Saintignon, P; Di Girolamo, B; Dinkespiler, B; Dita, S; Dodd, J; Dolejsi, J; Dolezal, Z; Downing, R; Dugne, J J; Dzahini, D; Efthymiopoulos, I; Errede, D; Errede, S; Evans, H; Eynard, G; Fassi, F; Fassnacht, P; Ferrari, A; Ferrer, A; Flaminio, Vincenzo; Fournier, D; Fumagalli, G; Gallas, E; Gaspar, M; Giakoumopoulou, V; Gianotti, F; Gildemeister, O; Giokaris, N; Glagolev, V; Glebov, V Yu; Gomes, A; González, V; González de la Hoz, S; Grabskii, V; Graugès-Pous, E; Grenier, P; Hakopian, H H; Haney, M; Hébrard, C; Henriques, A; Hervás, L; Higón, E; Holmgren, Sven Olof; Hostachy, J Y; Hoummada, A; Huston, J; Imbault, D; Ivanyushenkov, Yu M; Jézéquel, S; Johansson, E K; Jon-And, K; Jones, R; Juste, A; Kakurin, S; Karyukhin, A N; Khokhlov, Yu A; Khubua, J I; Klioukhine, V I; Kolachev, G M; Kopikov, S V; Kostrikov, M E; Kozlov, V; Krivkova, P; Kukhtin, V V; Kulagin, M; Kulchitskii, Yu A; Kuzmin, M V; Labarga, L; Laborie, G; Lacour, D; Laforge, B; Lami, S; Lapin, V; Le Dortz, O; Lefebvre, M; Le Flour, T; Leitner, R; Leltchouk, M; Li, J; Liablin, M V; Linossier, O; Lissauer, D; Lobkowicz, F; Lokajícek, M; Lomakin, Yu F; López-Amengual, J M; Lund-Jensen, B; Maio, A; Makowiecki, D S; Malyukov, S N; Mandelli, L; Mansoulié, B; Mapelli, Livio P; Marin, C P; Marrocchesi, P S; Marroquim, F; Martin, P; Maslennikov, A L; Massol, N; Mataix, L; Mazzanti, M; Mazzoni, E; Merritt, F S; Michel, B; Miller, R; Minashvili, I A; Miralles, L; Mnatzakanian, E A; Monnier, E; Montarou, G; Mornacchi, Giuseppe; Moynot, M; Muanza, G S; Nayman, P; Némécek, S; Nessi, Marzio; Nicoleau, S; Niculescu, M; Noppe, J M; Onofre, A; Pallin, D; Pantea, D; Paoletti, R; Park, I C; Parrour, G; Parsons, J; Pereira, A; Perini, L; Perlas, J A; Perrodo, P; Pilcher, J E; Pinhão, J; Plothow-Besch, Hartmute; Poggioli, Luc; Poirot, S; Price, L; Protopopov, Yu; Proudfoot, J; Puzo, P; Radeka, V; Rahm, David Charles; Reinmuth, G; Renzoni, G; Rescia, S; Resconi, S; Richards, R; Richer, J P; Roda, C; Rodier, S; Roldán, J; Romance, J B; Romanov, V; Romero, P; Rossel, F; Rusakovitch, N A; Sala, P; Sanchis, E; Sanders, H; Santoni, C; Santos, J; Sauvage, D; Sauvage, G; Sawyer, L; Says, L P; Schaffer, A C; Schwemling, P; Schwindling, J; Seguin-Moreau, N; Seidl, W; Seixas, J M; Selldén, B; Seman, M; Semenov, A; Serin, L; Shaldaev, E; Shochet, M J; Sidorov, V; Silva, J; Simaitis, V J; Simion, S; Sissakian, A N; Snopkov, R; Söderqvist, J; Solodkov, A A; Soloviev, A; Soloviev, I V; Sonderegger, P; Soustruznik, K; Spanó, F; Spiwoks, R; Stanek, R; Starchenko, E A; Stavina, P; Stephens, R; Suk, M; Surkov, A; Sykora, I; Takai, H; Tang, F; Tardell, S; Tartarelli, F; Tas, P; Teiger, J; Thaler, J; Thion, J; Tikhonov, Yu A; Tisserant, S; Tokar, S; Topilin, N D; Trka, Z; Turcotte, M; Valkár, S; Varanda, M J; Vartapetian, A H; Vazeille, F; Vichou, I; Vinogradov, V; Vorozhtsov, S B; Vuillemin, V; White, A; Wielers, M; Wingerter-Seez, I; Wolters, H; Yamdagni, N; Yosef, C; Zaitsev, A; Zitoun, R; Zolnierowski, Y

    2002-01-01

    This paper discusses hadron energy reconstruction for the ATLAS barrel prototype combined calorimeter (consisting of a lead-liquid argon electromagnetic part and an iron-scintillator hadronic part) in the framework of the nonparametrical method. The nonparametrical method utilizes only the known e/h ratios and the electron calibration constants and does not require the determination of any parameters by a minimization technique. Thus, this technique lends itself to an easy use in a first level trigger. The reconstructed mean values of the hadron energies are within +or-1% of the true values and the fractional energy resolution is [(58+or-3)%/ square root E+(2.5+or-0.3)%](+)(1.7+or-0.2)/E. The value of the e/h ratio obtained for the electromagnetic compartment of the combined calorimeter is 1.74+or-0.04 and agrees with the prediction that e/h >1.66 for this electromagnetic calorimeter. Results of a study of the longitudinal hadronic shower development are also presented. The data have been taken in the H8 beam...

  13. Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method.

    Science.gov (United States)

    Zhang, Tingting; Kou, S C

    2010-01-01

    Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.

  14. The application of non-parametric statistical method for an ALARA implementation

    International Nuclear Information System (INIS)

    Cho, Young Ho; Herr, Young Hoi

    2003-01-01

    The cost-effective reduction of Occupational Radiation Dose (ORD) at a nuclear power plant could not be achieved without going through an extensive analysis of accumulated ORD data of existing plants. Through the data analysis, it is required to identify what are the jobs of repetitive high ORD at the nuclear power plant. In this study, Percentile Rank Sum Method (PRSM) is proposed to identify repetitive high ORD jobs, which is based on non-parametric statistical theory. As a case study, the method is applied to ORD data of maintenance and repair jobs at Kori units 3 and 4 that are pressurized water reactors with 950 MWe capacity and have been operated since 1986 and 1987, respectively in Korea. The results was verified and validated, and PRSM has been demonstrated to be an efficient method of analyzing the data

  15. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang

    2017-02-16

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  16. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang; Cheng, James; Xiao, Xiaokui; Fujimaki, Ryohei; Muraoka, Yusuke

    2017-01-01

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  17. Nonparametric Methods in Astronomy: Think, Regress, Observe—Pick Any Three

    Science.gov (United States)

    Steinhardt, Charles L.; Jermyn, Adam S.

    2018-02-01

    Telescopes are much more expensive than astronomers, so it is essential to minimize required sample sizes by using the most data-efficient statistical methods possible. However, the most commonly used model-independent techniques for finding the relationship between two variables in astronomy are flawed. In the worst case they can lead without warning to subtly yet catastrophically wrong results, and even in the best case they require more data than necessary. Unfortunately, there is no single best technique for nonparametric regression. Instead, we provide a guide for how astronomers can choose the best method for their specific problem and provide a python library with both wrappers for the most useful existing algorithms and implementations of two new algorithms developed here.

  18. Statistical analysis using the Bayesian nonparametric method for irradiation embrittlement of reactor pressure vessels

    Energy Technology Data Exchange (ETDEWEB)

    Takamizawa, Hisashi, E-mail: takamizawa.hisashi@jaea.go.jp; Itoh, Hiroto, E-mail: ito.hiroto@jaea.go.jp; Nishiyama, Yutaka, E-mail: nishiyama.yutaka93@jaea.go.jp

    2016-10-15

    In order to understand neutron irradiation embrittlement in high fluence regions, statistical analysis using the Bayesian nonparametric (BNP) method was performed for the Japanese surveillance and material test reactor irradiation database. The BNP method is essentially expressed as an infinite summation of normal distributions, with input data being subdivided into clusters with identical statistical parameters, such as mean and standard deviation, for each cluster to estimate shifts in ductile-to-brittle transition temperature (DBTT). The clusters typically depend on chemical compositions, irradiation conditions, and the irradiation embrittlement. Specific variables contributing to the irradiation embrittlement include the content of Cu, Ni, P, Si, and Mn in the pressure vessel steels, neutron flux, neutron fluence, and irradiation temperatures. It was found that the measured shifts of DBTT correlated well with the calculated ones. Data associated with the same materials were subdivided into the same clusters even if neutron fluences were increased.

  19. A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets

    Science.gov (United States)

    Carrig, Madeline M.; Manrique-Vallier, Daniel; Ranby, Krista W.; Reiter, Jerome P.; Hoyle, Rick H.

    2015-01-01

    Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches. PMID:26257437

  20. Nonparametric identification of nonlinear dynamic systems using a synchronisation-based method

    Science.gov (United States)

    Kenderi, Gábor; Fidlin, Alexander

    2014-12-01

    The present study proposes an identification method for highly nonlinear mechanical systems that does not require a priori knowledge of the underlying nonlinearities to reconstruct arbitrary restoring force surfaces between degrees of freedom. This approach is based on the master-slave synchronisation between a dynamic model of the system as the slave and the real system as the master using measurements of the latter. As the model synchronises to the measurements, it becomes an observer of the real system. The optimal observer algorithm in a least-squares sense is given by the Kalman filter. Using the well-known state augmentation technique, the Kalman filter can be turned into a dual state and parameter estimator to identify parameters of a priori characterised nonlinearities. The paper proposes an extension of this technique towards nonparametric identification. A general system model is introduced by describing the restoring forces as bilateral spring-dampers with time-variant coefficients, which are estimated as augmented states. The estimation procedure is followed by an a posteriori statistical analysis to reconstruct noise-free restoring force characteristics using the estimated states and their estimated variances. Observability is provided using only one measured mechanical quantity per degree of freedom, which makes this approach less demanding in the number of necessary measurement signals compared with truly nonparametric solutions, which typically require displacement, velocity and acceleration signals. Additionally, due to the statistical rigour of the procedure, it successfully addresses signals corrupted by significant measurement noise. In the present paper, the method is described in detail, which is followed by numerical examples of one degree of freedom (1DoF) and 2DoF mechanical systems with strong nonlinearities of vibro-impact type to demonstrate the effectiveness of the proposed technique.

  1. 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%.

  2. Two non-parametric methods for derivation of constraints from radiotherapy dose–histogram data

    International Nuclear Information System (INIS)

    Ebert, M A; Kennedy, A; Joseph, D J; Gulliford, S L; Buettner, F; Foo, K; Haworth, A; Denham, J W

    2014-01-01

    Dose constraints based on histograms provide a convenient and widely-used method for informing and guiding radiotherapy treatment planning. Methods of derivation of such constraints are often poorly described. Two non-parametric methods for derivation of constraints are described and investigated in the context of determination of dose-specific cut-points—values of the free parameter (e.g., percentage volume of the irradiated organ) which best reflect resulting changes in complication incidence. A method based on receiver operating characteristic (ROC) analysis and one based on a maximally-selected standardized rank sum are described and compared using rectal toxicity data from a prostate radiotherapy trial. Multiple test corrections are applied using a free step-down resampling algorithm, which accounts for the large number of tests undertaken to search for optimal cut-points and the inherent correlation between dose–histogram points. Both methods provide consistent significant cut-point values, with the rank sum method displaying some sensitivity to the underlying data. The ROC method is simple to implement and can utilize a complication atlas, though an advantage of the rank sum method is the ability to incorporate all complication grades without the need for grade dichotomization. (note)

  3. [Nonparametric method of estimating survival functions containing right-censored and interval-censored data].

    Science.gov (United States)

    Xu, Yonghong; Gao, Xiaohuan; Wang, Zhengxi

    2014-04-01

    Missing data represent a general problem in many scientific fields, especially in medical survival analysis. Dealing with censored data, interpolation method is one of important methods. However, most of the interpolation methods replace the censored data with the exact data, which will distort the real distribution of the censored data and reduce the probability of the real data falling into the interpolation data. In order to solve this problem, we in this paper propose a nonparametric method of estimating the survival function of right-censored and interval-censored data and compare its performance to SC (self-consistent) algorithm. Comparing to the average interpolation and the nearest neighbor interpolation method, the proposed method in this paper replaces the right-censored data with the interval-censored data, and greatly improves the probability of the real data falling into imputation interval. Then it bases on the empirical distribution theory to estimate the survival function of right-censored and interval-censored data. The results of numerical examples and a real breast cancer data set demonstrated that the proposed method had higher accuracy and better robustness for the different proportion of the censored data. This paper provides a good method to compare the clinical treatments performance with estimation of the survival data of the patients. This pro vides some help to the medical survival data analysis.

  4. The impact of type of manual medication cart filling method on the frequency of medication administration errors : A prospective before and after study

    NARCIS (Netherlands)

    Schimmel, Anneliene M.; Becker, Matthijs L.; van den Bout, Tilly; Taxis, Katja; van den Bemt, Patricia M. L. A.

    Background: The medication cart can be filled using an automated system or a manual method and when using a manual method the medication can be arranged either by round time or by medication name. For the manual methods, it is hypothesized that the latter method would result in a lower frequency of

  5. On the use of permutation in and the performance of a class of nonparametric methods to detect differential gene expression.

    Science.gov (United States)

    Pan, Wei

    2003-07-22

    Recently a class of nonparametric statistical methods, including the empirical Bayes (EB) method, the significance analysis of microarray (SAM) method and the mixture model method (MMM), have been proposed to detect differential gene expression for replicated microarray experiments conducted under two conditions. All the methods depend on constructing a test statistic Z and a so-called null statistic z. The null statistic z is used to provide some reference distribution for Z such that statistical inference can be accomplished. A common way of constructing z is to apply Z to randomly permuted data. Here we point our that the distribution of z may not approximate the null distribution of Z well, leading to possibly too conservative inference. This observation may apply to other permutation-based nonparametric methods. We propose a new method of constructing a null statistic that aims to estimate the null distribution of a test statistic directly. Using simulated data and real data, we assess and compare the performance of the existing method and our new method when applied in EB, SAM and MMM. Some interesting findings on operating characteristics of EB, SAM and MMM are also reported. Finally, by combining the idea of SAM and MMM, we outline a simple nonparametric method based on the direct use of a test statistic and a null statistic.

  6. A nonparametric statistical method for determination of a confidence interval for the mean of a set of results obtained in a laboratory intercomparison

    International Nuclear Information System (INIS)

    Veglia, A.

    1981-08-01

    In cases where sets of data are obviously not normally distributed, the application of a nonparametric method for the estimation of a confidence interval for the mean seems to be more suitable than some other methods because such a method requires few assumptions about the population of data. A two-step statistical method is proposed which can be applied to any set of analytical results: elimination of outliers by a nonparametric method based on Tchebycheff's inequality, and determination of a confidence interval for the mean by a non-parametric method based on binominal distribution. The method is appropriate only for samples of size n>=10

  7. Non-parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods

    DEFF Research Database (Denmark)

    Høg, Esben

    In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean-reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...

  8. Non-Parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods

    DEFF Research Database (Denmark)

    Høg, Esben

    2003-01-01

    In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean--reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...

  9. Trends in three decades of HIV/AIDS epidemic in Thailand by nonparametric backcalculation method.

    Science.gov (United States)

    Punyacharoensin, Narat; Viwatwongkasem, Chukiat

    2009-06-01

    To reconstruct the past HIV incidence and prevalence in Thailand from 1980 to 2008 and predict the country's AIDS incidence from 2009 to 2011. Nonparametric backcalculation was adopted utilizing 100 quarterly observed new AIDS counts excluding pediatric cases. The accuracy of data was enhanced through a series of data adjustments using the weight method to account for several surveillance reporting issues. The mixture of time-dependent distributions allowed the effects of age at seroconversion and antiretroviral therapy to be incorporated simultaneously. Sensitivity analyses were conducted to assess model variations that were subject to major uncertainties. Future AIDS incidence was projected for various predetermined HIV incidence patterns. HIV incidence in Thailand reached its peak in 1992 with approximately 115,000 cases. A steep decline thereafter discontinued in 1997 and was followed by another strike of 42,000 cases in 1999. The second surge, which happened concurrently with the major economic crisis, brought on 60,000 new infections. As of December 2008, more than 1 million individuals had been infected and around 430,000 adults were living with HIV corresponding to a prevalence rate of 1.2%. The incidence rate had become less than 0.1% since 2002. The backcalculated estimates were dominated by postulated median AIDS progression time and adjustments to surveillance data. Our analysis indicated that, thus far, the 1990s was the most severe era of HIV/AIDS epidemic in Thailand with two HIV incidence peaks. A drop in new infections led to a decrease in recent AIDS incidence, and this tendency is likely to remain unchanged until 2011, if not further.

  10. Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

    Science.gov (United States)

    Lu, Tao

    2016-01-01

    The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

  11. Parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method of ledre profile attributes

    Science.gov (United States)

    Hastuti, S.; Harijono; Murtini, E. S.; Fibrianto, K.

    2018-03-01

    This current study is aimed to investigate the use of parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method. Ledre as Bojonegoro unique local food product was used as point of interest, in which 319 panelists were involved in the study. The result showed that ledre is characterized as easy-crushed texture, sticky in mouth, stingy sensation and easy to swallow. It has also strong banana flavour with brown in colour. Compared to eggroll and semprong, ledre has more variances in terms of taste as well the roll length. As RATA questionnaire is designed to collect categorical data, non-parametric approach is the common statistical procedure. However, similar results were also obtained as parametric approach, regardless the fact of non-normal distributed data. Thus, it suggests that parametric approach can be applicable for consumer study with large number of respondents, even though it may not satisfy the assumption of ANOVA (Analysis of Variances).

  12. Bayesian nonparametric data analysis

    CERN Document Server

    Müller, Peter; Jara, Alejandro; Hanson, Tim

    2015-01-01

    This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.

  13. Non-parametric order statistics method applied to uncertainty propagation in fuel rod calculations

    International Nuclear Information System (INIS)

    Arimescu, V.E.; Heins, L.

    2001-01-01

    Advances in modeling fuel rod behavior and accumulations of adequate experimental data have made possible the introduction of quantitative methods to estimate the uncertainty of predictions made with best-estimate fuel rod codes. The uncertainty range of the input variables is characterized by a truncated distribution which is typically a normal, lognormal, or uniform distribution. While the distribution for fabrication parameters is defined to cover the design or fabrication tolerances, the distribution of modeling parameters is inferred from the experimental database consisting of separate effects tests and global tests. The final step of the methodology uses a Monte Carlo type of random sampling of all relevant input variables and performs best-estimate code calculations to propagate these uncertainties in order to evaluate the uncertainty range of outputs of interest for design analysis, such as internal rod pressure and fuel centerline temperature. The statistical method underlying this Monte Carlo sampling is non-parametric order statistics, which is perfectly suited to evaluate quantiles of populations with unknown distribution. The application of this method is straightforward in the case of one single fuel rod, when a 95/95 statement is applicable: 'with a probability of 95% and confidence level of 95% the values of output of interest are below a certain value'. Therefore, the 0.95-quantile is estimated for the distribution of all possible values of one fuel rod with a statistical confidence of 95%. On the other hand, a more elaborate procedure is required if all the fuel rods in the core are being analyzed. In this case, the aim is to evaluate the following global statement: with 95% confidence level, the expected number of fuel rods which are not exceeding a certain value is all the fuel rods in the core except only a few fuel rods. In both cases, the thresholds determined by the analysis should be below the safety acceptable design limit. An indirect

  14. Parametric methods outperformed non-parametric methods in comparisons of discrete numerical variables

    Directory of Open Access Journals (Sweden)

    Sandvik Leiv

    2011-04-01

    Full Text Available Abstract Background The number of events per individual is a widely reported variable in medical research papers. Such variables are the most common representation of the general variable type called discrete numerical. There is currently no consensus on how to compare and present such variables, and recommendations are lacking. The objective of this paper is to present recommendations for analysis and presentation of results for discrete numerical variables. Methods Two simulation studies were used to investigate the performance of hypothesis tests and confidence interval methods for variables with outcomes {0, 1, 2}, {0, 1, 2, 3}, {0, 1, 2, 3, 4}, and {0, 1, 2, 3, 4, 5}, using the difference between the means as an effect measure. Results The Welch U test (the T test with adjustment for unequal variances and its associated confidence interval performed well for almost all situations considered. The Brunner-Munzel test also performed well, except for small sample sizes (10 in each group. The ordinary T test, the Wilcoxon-Mann-Whitney test, the percentile bootstrap interval, and the bootstrap-t interval did not perform satisfactorily. Conclusions The difference between the means is an appropriate effect measure for comparing two independent discrete numerical variables that has both lower and upper bounds. To analyze this problem, we encourage more frequent use of parametric hypothesis tests and confidence intervals.

  15. A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

    Science.gov (United States)

    Hu, Pingsha; Maiti, Tapabrata

    2011-01-01

    Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

  16. Nonparametric method for genomics-based prediction of performance of quantitative traits involving epistasis in plant breeding.

    Directory of Open Access Journals (Sweden)

    Xiaochun Sun

    Full Text Available Genomic selection (GS procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA and reproducing kernel Hilbert spaces (RKHS regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.

  17. Nonparametric method for genomics-based prediction of performance of quantitative traits involving epistasis in plant breeding.

    Science.gov (United States)

    Sun, Xiaochun; Ma, Ping; Mumm, Rita H

    2012-01-01

    Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.

  18. Theory of nonparametric tests

    CERN Document Server

    Dickhaus, Thorsten

    2018-01-01

    This textbook provides a self-contained presentation of the main concepts and methods of nonparametric statistical testing, with a particular focus on the theoretical foundations of goodness-of-fit tests, rank tests, resampling tests, and projection tests. The substitution principle is employed as a unified approach to the nonparametric test problems discussed. In addition to mathematical theory, it also includes numerous examples and computer implementations. The book is intended for advanced undergraduate, graduate, and postdoc students as well as young researchers. Readers should be familiar with the basic concepts of mathematical statistics typically covered in introductory statistics courses.

  19. 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.

  20. A comparison of parametric and nonparametric methods for normalising cDNA microarray data.

    Science.gov (United States)

    Khondoker, Mizanur R; Glasbey, Chris A; Worton, Bruce J

    2007-12-01

    Normalisation is an essential first step in the analysis of most cDNA microarray data, to correct for effects arising from imperfections in the technology. Loess smoothing is commonly used to correct for trends in log-ratio data. However, parametric models, such as the additive plus multiplicative variance model, have been preferred for scale normalisation, though the variance structure of microarray data may be of a more complex nature than can be accommodated by a parametric model. We propose a new nonparametric approach that incorporates location and scale normalisation simultaneously using a Generalised Additive Model for Location, Scale and Shape (GAMLSS, Rigby and Stasinopoulos, 2005, Applied Statistics, 54, 507-554). We compare its performance in inferring differential expression with Huber et al.'s (2002, Bioinformatics, 18, 96-104) arsinh variance stabilising transformation (AVST) using real and simulated data. We show GAMLSS to be as powerful as AVST when the parametric model is correct, and more powerful when the model is wrong. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

  1. High-Throughput Flow Cytometric Method for the Simultaneous Measurement of CAR-T Cell Characterization and Cytotoxicity against Solid Tumor Cell Lines.

    Science.gov (United States)

    Martinez, Emily M; Klebanoff, Samuel D; Secrest, Stephanie; Romain, Gabrielle; Haile, Samuel T; Emtage, Peter C R; Gilbert, Amy E

    2018-04-01

    High-throughput flow cytometry is an attractive platform for the analysis of adoptive cellular therapies such as chimeric antigen receptor T cell therapy (CAR-T) because it allows for the concurrent measurement of T cell-dependent cellular cytotoxicity (TDCC) and the functional characterization of engineered T cells with respect to percentage of CAR transduction, T cell phenotype, and measurement of T cell function such as activation in a single assay. The use of adherent tumor cell lines can be challenging in these flow-based assays. Here, we present the development of a high-throughput flow-based assay to measure TDCC for a CAR-T construct co-cultured with multiple adherent tumor cell lines. We describe optimal assay conditions (such as adherent cell dissociation techniques to minimize impact on cell viability) that result in robust cytotoxicity assays. In addition, we report on the concurrent use of T cell transduction and activation antibody panels (CD25) that provide further dissection of engineered T cell function. In conclusion, we present the development of a high-throughput flow cytometry method allowing for in vitro interrogation of solid tumor, targeting CAR-T cell-mediated cytotoxicity, CAR transduction, and engineered T cell characterization in a single assay.

  2. Bayesian nonparametric hierarchical modeling.

    Science.gov (United States)

    Dunson, David B

    2009-04-01

    In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.

  3. Uncertainty in decision models analyzing cost-effectiveness : The joint distribution of incremental costs and effectiveness evaluated with a nonparametric bootstrap method

    NARCIS (Netherlands)

    Hunink, Maria; Bult, J.R.; De Vries, J; Weinstein, MC

    1998-01-01

    Purpose. To illustrate the use of a nonparametric bootstrap method in the evaluation of uncertainty in decision models analyzing cost-effectiveness. Methods. The authors reevaluated a previously published cost-effectiveness analysis that used a Markov model comparing initial percutaneous

  4. 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.

  5. Non-parametric method for separating domestic hot water heating spikes and space heating

    DEFF Research Database (Denmark)

    Bacher, Peder; de Saint-Aubain, Philip Anton; Christiansen, Lasse Engbo

    2016-01-01

    In this paper a method for separating spikes from a noisy data series, where the data change and evolve over time, is presented. The method is applied on measurements of the total heat load for a single family house. It relies on the fact that the domestic hot water heating is a process generating...

  6. A powerful nonparametric method for detecting differentially co-expressed genes: distance correlation screening and edge-count test.

    Science.gov (United States)

    Zhang, Qingyang

    2018-05-16

    Differential co-expression analysis, as a complement of differential expression analysis, offers significant insights into the changes in molecular mechanism of different phenotypes. A prevailing approach to detecting differentially co-expressed genes is to compare Pearson's correlation coefficients in two phenotypes. However, due to the limitations of Pearson's correlation measure, this approach lacks the power to detect nonlinear changes in gene co-expression which is common in gene regulatory networks. In this work, a new nonparametric procedure is proposed to search differentially co-expressed gene pairs in different phenotypes from large-scale data. Our computational pipeline consisted of two main steps, a screening step and a testing step. The screening step is to reduce the search space by filtering out all the independent gene pairs using distance correlation measure. In the testing step, we compare the gene co-expression patterns in different phenotypes by a recently developed edge-count test. Both steps are distribution-free and targeting nonlinear relations. We illustrate the promise of the new approach by analyzing the Cancer Genome Atlas data and the METABRIC data for breast cancer subtypes. Compared with some existing methods, the new method is more powerful in detecting nonlinear type of differential co-expressions. The distance correlation screening can greatly improve computational efficiency, facilitating its application to large data sets.

  7. Nonparametric statistical inference

    CERN Document Server

    Gibbons, Jean Dickinson

    2014-01-01

    Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.

  8. Comparison of non-parametric methods for ungrouping coarsely aggregated data

    DEFF Research Database (Denmark)

    Rizzi, Silvia; Thinggaard, Mikael; Engholm, Gerda

    2016-01-01

    group at the highest ages. When histogram intervals are too coarse, information is lost and comparison between histograms with different boundaries is arduous. In these cases it is useful to estimate detailed distributions from grouped data. Methods From an extensive literature search we identify five...

  9. A Non-parametric Method for Calculating Conditional Stressed Value at Risk

    Directory of Open Access Journals (Sweden)

    Kohei Marumo

    2017-01-01

    Full Text Available We consider the Value at Risk (VaR of a portfolio under stressed conditions. In practice, the stressed VaR (sVaR is commonly calculated using the data set that includes the stressed period. It tells us how much the risk amount increases if we use the stressed data set. In this paper, we consider the VaR under stress scenarios. Technically, this can be done by deriving the distribution of profit or loss conditioned on the value of risk factors. We use two methods; the one that uses the linear model and the one that uses the Hermite expansion discussed by Marumo and Wolff (2013, 2016. Numerical examples shows that the method using the Hermite expansion is capable of capturing the non-linear effects such as correlation collapse and volatility clustering, which are often observed in the markets.

  10. Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model

    International Nuclear Information System (INIS)

    Kuosmanen, Timo

    2012-01-01

    Electricity distribution network is a prime example of a natural local monopoly. In many countries, electricity distribution is regulated by the government. Many regulators apply frontier estimation techniques such as data envelopment analysis (DEA) or stochastic frontier analysis (SFA) as an integral part of their regulatory framework. While more advanced methods that combine nonparametric frontier with stochastic error term are known in the literature, in practice, regulators continue to apply simplistic methods. This paper reports the main results of the project commissioned by the Finnish regulator for further development of the cost frontier estimation in their regulatory framework. The key objectives of the project were to integrate a stochastic SFA-style noise term to the nonparametric, axiomatic DEA-style cost frontier, and to take the heterogeneity of firms and their operating environments better into account. To achieve these objectives, a new method called stochastic nonparametric envelopment of data (StoNED) was examined. Based on the insights and experiences gained in the empirical analysis using the real data of the regulated networks, the Finnish regulator adopted the StoNED method in use from 2012 onwards.

  11. 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.

  12. 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.

  13. Nonparametric statistics for social and behavioral sciences

    CERN Document Server

    Kraska-MIller, M

    2013-01-01

    Introduction to Research in Social and Behavioral SciencesBasic Principles of ResearchPlanning for ResearchTypes of Research Designs Sampling ProceduresValidity and Reliability of Measurement InstrumentsSteps of the Research Process Introduction to Nonparametric StatisticsData AnalysisOverview of Nonparametric Statistics and Parametric Statistics Overview of Parametric Statistics Overview of Nonparametric StatisticsImportance of Nonparametric MethodsMeasurement InstrumentsAnalysis of Data to Determine Association and Agreement Pearson Chi-Square Test of Association and IndependenceContingency

  14. Nonparametric statistical inference

    CERN Document Server

    Gibbons, Jean Dickinson

    2010-01-01

    Overall, this remains a very fine book suitable for a graduate-level course in nonparametric statistics. I recommend it for all people interested in learning the basic ideas of nonparametric statistical inference.-Eugenia Stoimenova, Journal of Applied Statistics, June 2012… one of the best books available for a graduate (or advanced undergraduate) text for a theory course on nonparametric statistics. … a very well-written and organized book on nonparametric statistics, especially useful and recommended for teachers and graduate students.-Biometrics, 67, September 2011This excellently presente

  15. Decision support using nonparametric statistics

    CERN Document Server

    Beatty, Warren

    2018-01-01

    This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.

  16. Estimation from PET data of transient changes in dopamine concentration induced by alcohol: support for a non-parametric signal estimation method

    Energy Technology Data Exchange (ETDEWEB)

    Constantinescu, C C; Yoder, K K; Normandin, M D; Morris, E D [Department of Radiology, Indiana University School of Medicine, Indianapolis, IN (United States); Kareken, D A [Department of Neurology, Indiana University School of Medicine, Indianapolis, IN (United States); Bouman, C A [Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN (United States); O' Connor, S J [Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN (United States)], E-mail: emorris@iupui.edu

    2008-03-07

    We previously developed a model-independent technique (non-parametric ntPET) for extracting the transient changes in neurotransmitter concentration from paired (rest and activation) PET studies with a receptor ligand. To provide support for our method, we introduced three hypotheses of validation based on work by Endres and Carson (1998 J. Cereb. Blood Flow Metab. 18 1196-210) and Yoder et al (2004 J. Nucl. Med. 45 903-11), and tested them on experimental data. All three hypotheses describe relationships between the estimated free (synaptic) dopamine curves (F{sup DA}(t)) and the change in binding potential ({delta}BP). The veracity of the F{sup DA}(t) curves recovered by nonparametric ntPET is supported when the data adhere to the following hypothesized behaviors: (1) {delta}BP should decline with increasing DA peak time, (2) {delta}BP should increase as the strength of the temporal correlation between F{sup DA}(t) and the free raclopride (F{sup RAC}(t)) curve increases, (3) {delta}BP should decline linearly with the effective weighted availability of the receptor sites. We analyzed regional brain data from 8 healthy subjects who received two [{sup 11}C]raclopride scans: one at rest, and one during which unanticipated IV alcohol was administered to stimulate dopamine release. For several striatal regions, nonparametric ntPET was applied to recover F{sup DA}(t), and binding potential values were determined. Kendall rank-correlation analysis confirmed that the F{sup DA}(t) data followed the expected trends for all three validation hypotheses. Our findings lend credence to our model-independent estimates of F{sup DA}(t). Application of nonparametric ntPET may yield important insights into how alterations in timing of dopaminergic neurotransmission are involved in the pathologies of addiction and other psychiatric disorders.

  17. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin

    2017-01-19

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

  18. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

    2017-01-01

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

  19. Nonparametric combinatorial sequence models.

    Science.gov (United States)

    Wauthier, Fabian L; Jordan, Michael I; Jojic, Nebojsa

    2011-11-01

    This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This article presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three biological sequence families which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution over sequence representations induced by the prior. By integrating out the posterior, our method compares favorably to leading binding predictors.

  20. On Cooper's Nonparametric Test.

    Science.gov (United States)

    Schmeidler, James

    1978-01-01

    The basic assumption of Cooper's nonparametric test for trend (EJ 125 069) is questioned. It is contended that the proper assumption alters the distribution of the statistic and reduces its usefulness. (JKS)

  1. 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

  2. On Rigorous Drought Assessment Using Daily Time Scale: Non-Stationary Frequency Analyses, Revisited Concepts, and a New Method to Yield Non-Parametric Indices

    Directory of Open Access Journals (Sweden)

    Charles Onyutha

    2017-10-01

    Full Text Available Some of the problems in drought assessments are that: analyses tend to focus on coarse temporal scales, many of the methods yield skewed indices, a few terminologies are ambiguously used, and analyses comprise an implicit assumption that the observations come from a stationary process. To solve these problems, this paper introduces non-stationary frequency analyses of quantiles. How to use non-parametric rescaling to obtain robust indices that are not (or minimally skewed is also introduced. To avoid ambiguity, some concepts on, e.g., incidence, extremity, etc., were revisited through shift from monthly to daily time scale. Demonstrations on the introduced methods were made using daily flow and precipitation insufficiency (precipitation minus potential evapotranspiration from the Blue Nile basin in Africa. Results show that, when a significant trend exists in extreme events, stationarity-based quantiles can be far different from those when non-stationarity is considered. The introduced non-parametric indices were found to closely agree with the well-known standardized precipitation evapotranspiration indices in many aspects but skewness. Apart from revisiting some concepts, the advantages of the use of fine instead of coarse time scales in drought assessment were given. The links for obtaining freely downloadable tools on how to implement the introduced methods were provided.

  3. 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…

  4. Nonparametric Inference for Periodic Sequences

    KAUST Repository

    Sun, Ying

    2012-02-01

    This article proposes a nonparametric method for estimating the period and values of a periodic sequence when the data are evenly spaced in time. The period is estimated by a "leave-out-one-cycle" version of cross-validation (CV) and complements the periodogram, a widely used tool for period estimation. The CV method is computationally simple and implicitly penalizes multiples of the smallest period, leading to a "virtually" consistent estimator of integer periods. This estimator is investigated both theoretically and by simulation.We also propose a nonparametric test of the null hypothesis that the data have constantmean against the alternative that the sequence of means is periodic. Finally, our methodology is demonstrated on three well-known time series: the sunspots and lynx trapping data, and the El Niño series of sea surface temperatures. © 2012 American Statistical Association and the American Society for Quality.

  5. Application of nonparametric regression methods to study the relationship between NO2 concentrations and local wind direction and speed at background sites.

    Science.gov (United States)

    Donnelly, Aoife; Misstear, Bruce; Broderick, Brian

    2011-02-15

    Background concentrations of nitrogen dioxide (NO(2)) are not constant but vary temporally and spatially. The current paper presents a powerful tool for the quantification of the effects of wind direction and wind speed on background NO(2) concentrations, particularly in cases where monitoring data are limited. In contrast to previous studies which applied similar methods to sites directly affected by local pollution sources, the current study focuses on background sites with the aim of improving methods for predicting background concentrations adopted in air quality modelling studies. The relationship between measured NO(2) concentration in air at three such sites in Ireland and locally measured wind direction has been quantified using nonparametric regression methods. The major aim was to analyse a method for quantifying the effects of local wind direction on background levels of NO(2) in Ireland. The method was expanded to include wind speed as an added predictor variable. A Gaussian kernel function is used in the analysis and circular statistics employed for the wind direction variable. Wind direction and wind speed were both found to have a statistically significant effect on background levels of NO(2) at all three sites. Frequently environmental impact assessments are based on short term baseline monitoring producing a limited dataset. The presented non-parametric regression methods, in contrast to the frequently used methods such as binning of the data, allow concentrations for missing data pairs to be estimated and distinction between spurious and true peaks in concentrations to be made. The methods were found to provide a realistic estimation of long term concentration variation with wind direction and speed, even for cases where the data set is limited. Accurate identification of the actual variation at each location and causative factors could be made, thus supporting the improved definition of background concentrations for use in air quality modelling

  6. 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...

  7. 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

  8. 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 ...

  9. Nonparametric Transfer Function Models

    Science.gov (United States)

    Liu, Jun M.; Chen, Rong; Yao, Qiwei

    2009-01-01

    In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584

  10. 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.

  11. Quantal Response: Nonparametric Modeling

    Science.gov (United States)

    2017-01-01

    capture the behavior of observed phenomena. Higher-order polynomial and finite-dimensional spline basis models allow for more complicated responses as the...flexibility as these are nonparametric (not constrained to any particular functional form). These should be useful in identifying nonstandard behavior via... deviance ∆ = −2 log(Lreduced/Lfull) is defined in terms of the likelihood function L. For normal error, Lfull = 1, and based on Eq. A-2, we have log

  12. Nonparametric identification of copula structures

    KAUST Repository

    Li, Bo

    2013-06-01

    We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric and based on the asymptotic distribution of the empirical copula process.We perform simulation experiments to evaluate our test and conclude that our method is reliable and powerful for assessing common assumptions on the structure of copulas, particularly when the sample size is moderately large. We illustrate our testing approach on two datasets. © 2013 American Statistical Association.

  13. Benchmark of the non-parametric Bayesian deconvolution method implemented in the SINBAD code for X/γ rays spectra processing

    Energy Technology Data Exchange (ETDEWEB)

    Rohée, E. [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif-sur-Yvette (France); Coulon, R., E-mail: romain.coulon@cea.fr [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif-sur-Yvette (France); Carrel, F. [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif-sur-Yvette (France); Dautremer, T.; Barat, E.; Montagu, T. [CEA, LIST, Laboratoire de Modélisation et Simulation des Systèmes, F-91191 Gif-sur-Yvette (France); Normand, S. [CEA, DAM, Le Ponant, DPN/STXN, F-75015 Paris (France); Jammes, C. [CEA, DEN, Cadarache, DER/SPEx/LDCI, F-13108 Saint-Paul-lez-Durance (France)

    2016-11-11

    Radionuclide identification and quantification are a serious concern for many applications as for in situ monitoring at nuclear facilities, laboratory analysis, special nuclear materials detection, environmental monitoring, and waste measurements. High resolution gamma-ray spectrometry based on high purity germanium diode detectors is the best solution available for isotopic identification. Over the last decades, methods have been developed to improve gamma spectra analysis. However, some difficulties remain in the analysis when full energy peaks are folded together with high ratio between their amplitudes, and when the Compton background is much larger compared to the signal of a single peak. In this context, this study deals with the comparison between a conventional analysis based on “iterative peak fitting deconvolution” method and a “nonparametric Bayesian deconvolution” approach developed by the CEA LIST and implemented into the SINBAD code. The iterative peak fit deconvolution is used in this study as a reference method largely validated by industrial standards to unfold complex spectra from HPGe detectors. Complex cases of spectra are studied from IAEA benchmark protocol tests and with measured spectra. The SINBAD code shows promising deconvolution capabilities compared to the conventional method without any expert parameter fine tuning.

  14. A comparison of selected parametric and non-parametric imputation methods for estimating forest biomass and basal area

    Science.gov (United States)

    Donald Gagliasso; Susan Hummel; Hailemariam. Temesgen

    2014-01-01

    Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future...

  15. Empirical Methods for Detecting Regional Trends and Other Spatial Expressions in Antrim Shale Gas Productivity, with Implications for Improving Resource Projections Using Local Nonparametric Estimation Techniques

    Science.gov (United States)

    Coburn, T.C.; Freeman, P.A.; Attanasi, E.D.

    2012-01-01

    The primary objectives of this research were to (1) investigate empirical methods for establishing regional trends in unconventional gas resources as exhibited by historical production data and (2) determine whether or not incorporating additional knowledge of a regional trend in a suite of previously established local nonparametric resource prediction algorithms influences assessment results. Three different trend detection methods were applied to publicly available production data (well EUR aggregated to 80-acre cells) from the Devonian Antrim Shale gas play in the Michigan Basin. This effort led to the identification of a southeast-northwest trend in cell EUR values across the play that, in a very general sense, conforms to the primary fracture and structural orientations of the province. However, including this trend in the resource prediction algorithms did not lead to improved results. Further analysis indicated the existence of clustering among cell EUR values that likely dampens the contribution of the regional trend. The reason for the clustering, a somewhat unexpected result, is not completely understood, although the geological literature provides some possible explanations. With appropriate data, a better understanding of this clustering phenomenon may lead to important information about the factors and their interactions that control Antrim Shale gas production, which may, in turn, help establish a more general protocol for better estimating resources in this and other shale gas plays. ?? 2011 International Association for Mathematical Geology (outside the USA).

  16. Recent Advances and Trends in Nonparametric Statistics

    CERN Document Server

    Akritas, MG

    2003-01-01

    The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection o

  17. Non-Parametric Estimation of Correlation Functions

    DEFF Research Database (Denmark)

    Brincker, Rune; Rytter, Anders; Krenk, Steen

    In this paper three methods of non-parametric correlation function estimation are reviewed and evaluated: the direct method, estimation by the Fast Fourier Transform and finally estimation by the Random Decrement technique. The basic ideas of the techniques are reviewed, sources of bias are point...

  18. A simple method for optimising transformation of non-parametric data: an illustration by reference to cortisol assays.

    Science.gov (United States)

    Clark, James E; Osborne, Jason W; Gallagher, Peter; Watson, Stuart

    2016-07-01

    Neuroendocrine data are typically positively skewed and rarely conform to the expectations of a Gaussian distribution. This can be a problem when attempting to analyse results within the framework of the general linear model, which relies on assumptions that residuals in the data are normally distributed. One frequently used method for handling violations of this assumption is to transform variables to bring residuals into closer alignment with assumptions (as residuals are not directly manipulated). This is often attempted through ad hoc traditional transformations such as square root, log and inverse. However, Box and Cox (Box & Cox, ) observed that these are all special cases of power transformations and proposed a more flexible method of transformation for researchers to optimise alignment with assumptions. The goal of this paper is to demonstrate the benefits of the infinitely flexible Box-Cox transformation on neuroendocrine data using syntax in spss. When applied to positively skewed data typical of neuroendocrine data, the majority (~2/3) of cases were brought into strict alignment with Gaussian distribution (i.e. a non-significant Shapiro-Wilks test). Those unable to meet this challenge showed substantial improvement in distributional properties. The biggest challenge was distributions with a high ratio of kurtosis to skewness. We discuss how these cases might be handled, and we highlight some of the broader issues associated with transformation. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  19. Nonparametric statistics with applications to science and engineering

    CERN Document Server

    Kvam, Paul H

    2007-01-01

    A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provide...

  20. 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.

  1. BIOMETRIC AUTHENTICATION USING NONPARAMETRIC METHODS

    OpenAIRE

    S V Sheela; K R Radhika

    2010-01-01

    The physiological and behavioral trait is employed to develop biometric authentication systems. The proposed work deals with the authentication of iris and signature based on minimum variance criteria. The iris patterns are preprocessed based on area of the connected components. The segmented image used for authentication consists of the region with large variations in the gray level values. The image region is split into quadtree components. The components with minimum variance are determine...

  2. Nonparametric predictive inference in statistical process control

    NARCIS (Netherlands)

    Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

    2000-01-01

    New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on

  3. A Bayesian Nonparametric Approach to Factor Analysis

    DEFF Research Database (Denmark)

    Piatek, Rémi; Papaspiliopoulos, Omiros

    2018-01-01

    This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does no...

  4. A NONPARAMETRIC HYPOTHESIS TEST VIA THE BOOTSTRAP RESAMPLING

    OpenAIRE

    Temel, Tugrul T.

    2001-01-01

    This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test. The paper also develops a Mathematica Code for the test algorithm.

  5. Nonparametric tests for censored data

    CERN Document Server

    Bagdonavicus, Vilijandas; Nikulin, Mikhail

    2013-01-01

    This book concerns testing hypotheses in non-parametric models. Generalizations of many non-parametric tests to the case of censored and truncated data are considered. Most of the test results are proved and real applications are illustrated using examples. Theories and exercises are provided. The incorrect use of many tests applying most statistical software is highlighted and discussed.

  6. 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.

  7. Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers

    Directory of Open Access Journals (Sweden)

    Stochl Jan

    2012-06-01

    Full Text Available Abstract Background Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires. Methods Scalability of data from 1 a cross-sectional health survey (the Scottish Health Education Population Survey and 2 a general population birth cohort study (the National Child Development Study illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale. Results and conclusions After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items we show that all items from the 12-item General Health Questionnaire (GHQ-12 – when binary scored – were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech’s “well-being” and “distress” clinical scales. An illustration of ordinal item analysis

  8. Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers.

    Science.gov (United States)

    Stochl, Jan; Jones, Peter B; Croudace, Tim J

    2012-06-11

    Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related) Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires. Scalability of data from 1) a cross-sectional health survey (the Scottish Health Education Population Survey) and 2) a general population birth cohort study (the National Child Development Study) illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale. After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items) we show that all items from the 12-item General Health Questionnaire (GHQ-12)--when binary scored--were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech's "well-being" and "distress" clinical scales). An illustration of ordinal item analysis confirmed that all 14 positively worded items of the Warwick-Edinburgh Mental

  9. Nonparametric identification of copula structures

    KAUST Repository

    Li, Bo; Genton, Marc G.

    2013-01-01

    We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric

  10. 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…

  11. Bayesian Nonparametric Longitudinal Data Analysis.

    Science.gov (United States)

    Quintana, Fernando A; Johnson, Wesley O; Waetjen, Elaine; Gold, Ellen

    2016-01-01

    Practical Bayesian nonparametric methods have been developed across a wide variety of contexts. Here, we develop a novel statistical model that generalizes standard mixed models for longitudinal data that include flexible mean functions as well as combined compound symmetry (CS) and autoregressive (AR) covariance structures. AR structure is often specified through the use of a Gaussian process (GP) with covariance functions that allow longitudinal data to be more correlated if they are observed closer in time than if they are observed farther apart. We allow for AR structure by considering a broader class of models that incorporates a Dirichlet Process Mixture (DPM) over the covariance parameters of the GP. We are able to take advantage of modern Bayesian statistical methods in making full predictive inferences and about characteristics of longitudinal profiles and their differences across covariate combinations. We also take advantage of the generality of our model, which provides for estimation of a variety of covariance structures. We observe that models that fail to incorporate CS or AR structure can result in very poor estimation of a covariance or correlation matrix. In our illustration using hormone data observed on women through the menopausal transition, biology dictates the use of a generalized family of sigmoid functions as a model for time trends across subpopulation categories.

  12. Parametric and Non-Parametric System Modelling

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg

    1999-01-01

    the focus is on combinations of parametric and non-parametric methods of regression. This combination can be in terms of additive models where e.g. one or more non-parametric term is added to a linear regression model. It can also be in terms of conditional parametric models where the coefficients...... considered. It is shown that adaptive estimation in conditional parametric models can be performed by combining the well known methods of local polynomial regression and recursive least squares with exponential forgetting. The approach used for estimation in conditional parametric models also highlights how...... networks is included. In this paper, neural networks are used for predicting the electricity production of a wind farm. The results are compared with results obtained using an adaptively estimated ARX-model. Finally, two papers on stochastic differential equations are included. In the first paper, among...

  13. Nonparametric Bayes Modeling of Multivariate Categorical Data.

    Science.gov (United States)

    Dunson, David B; Xing, Chuanhua

    2012-01-01

    Modeling of multivariate unordered categorical (nominal) data is a challenging problem, particularly in high dimensions and cases in which one wishes to avoid strong assumptions about the dependence structure. Commonly used approaches rely on the incorporation of latent Gaussian random variables or parametric latent class models. The goal of this article is to develop a nonparametric Bayes approach, which defines a prior with full support on the space of distributions for multiple unordered categorical variables. This support condition ensures that we are not restricting the dependence structure a priori. We show this can be accomplished through a Dirichlet process mixture of product multinomial distributions, which is also a convenient form for posterior computation. Methods for nonparametric testing of violations of independence are proposed, and the methods are applied to model positional dependence within transcription factor binding motifs.

  14. 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

  15. 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…

  16. 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.

  17. A nonparametric mixture model for cure rate estimation.

    Science.gov (United States)

    Peng, Y; Dear, K B

    2000-03-01

    Nonparametric methods have attracted less attention than their parametric counterparts for cure rate analysis. In this paper, we study a general nonparametric mixture model. The proportional hazards assumption is employed in modeling the effect of covariates on the failure time of patients who are not cured. The EM algorithm, the marginal likelihood approach, and multiple imputations are employed to estimate parameters of interest in the model. This model extends models and improves estimation methods proposed by other researchers. It also extends Cox's proportional hazards regression model by allowing a proportion of event-free patients and investigating covariate effects on that proportion. The model and its estimation method are investigated by simulations. An application to breast cancer data, including comparisons with previous analyses using a parametric model and an existing nonparametric model by other researchers, confirms the conclusions from the parametric model but not those from the existing nonparametric model.

  18. 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).

  19. Network structure exploration via Bayesian nonparametric models

    International Nuclear Information System (INIS)

    Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z

    2015-01-01

    Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)

  20. Nonparametric Mixture Models for Supervised Image Parcellation.

    Science.gov (United States)

    Sabuncu, Mert R; Yeo, B T Thomas; Van Leemput, Koen; Fischl, Bruce; Golland, Polina

    2009-09-01

    We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various settings of a model parameter yield algorithms that use image intensity information differently in determining the weight of a training subject during fusion. One particular setting computes a single, global weight per training subject, whereas another setting uses locally varying weights when fusing the training data. The proposed nonparametric parcellation approach capitalizes on recently developed fast and robust pairwise image alignment tools. The use of multiple registrations allows the algorithm to be robust to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with expert manual labels for the white matter, cerebral cortex, ventricles and subcortical structures. The results demonstrate that the proposed nonparametric segmentation framework yields significantly better segmentation than state-of-the-art algorithms.

  1. Statistical methods for ranking data

    CERN Document Server

    Alvo, Mayer

    2014-01-01

    This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

  2. Glaucoma Monitoring in a Clinical Setting Glaucoma Progression Analysis vs Nonparametric Progression Analysis in the Groningen Longitudinal Glaucoma Study

    NARCIS (Netherlands)

    Wesselink, Christiaan; Heeg, Govert P.; Jansonius, Nomdo M.

    Objective: To compare prospectively 2 perimetric progression detection algorithms for glaucoma, the Early Manifest Glaucoma Trial algorithm (glaucoma progression analysis [GPA]) and a nonparametric algorithm applied to the mean deviation (MD) (nonparametric progression analysis [NPA]). Methods:

  3. Nonparametric factor analysis of time series

    OpenAIRE

    Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

    1998-01-01

    We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

  4. 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.

  5. Nonparametric predictive inference in reliability

    International Nuclear Information System (INIS)

    Coolen, F.P.A.; Coolen-Schrijner, P.; Yan, K.J.

    2002-01-01

    We introduce a recently developed statistical approach, called nonparametric predictive inference (NPI), to reliability. Bounds for the survival function for a future observation are presented. We illustrate how NPI can deal with right-censored data, and discuss aspects of competing risks. We present possible applications of NPI for Bernoulli data, and we briefly outline applications of NPI for replacement decisions. The emphasis is on introduction and illustration of NPI in reliability contexts, detailed mathematical justifications are presented elsewhere

  6. Non-parametric smoothing of experimental data

    International Nuclear Information System (INIS)

    Kuketayev, A.T.; Pen'kov, F.M.

    2007-01-01

    Full text: Rapid processing of experimental data samples in nuclear physics often requires differentiation in order to find extrema. Therefore, even at the preliminary stage of data analysis, a range of noise reduction methods are used to smooth experimental data. There are many non-parametric smoothing techniques: interval averages, moving averages, exponential smoothing, etc. Nevertheless, it is more common to use a priori information about the behavior of the experimental curve in order to construct smoothing schemes based on the least squares techniques. The latter methodology's advantage is that the area under the curve can be preserved, which is equivalent to conservation of total speed of counting. The disadvantages of this approach include the lack of a priori information. For example, very often the sums of undifferentiated (by a detector) peaks are replaced with one peak during the processing of data, introducing uncontrolled errors in the determination of the physical quantities. The problem is solvable only by having experienced personnel, whose skills are much greater than the challenge. We propose a set of non-parametric techniques, which allows the use of any additional information on the nature of experimental dependence. The method is based on a construction of a functional, which includes both experimental data and a priori information. Minimum of this functional is reached on a non-parametric smoothed curve. Euler (Lagrange) differential equations are constructed for these curves; then their solutions are obtained analytically or numerically. The proposed approach allows for automated processing of nuclear physics data, eliminating the need for highly skilled laboratory personnel. Pursuant to the proposed approach is the possibility to obtain smoothing curves in a given confidence interval, e.g. according to the χ 2 distribution. This approach is applicable when constructing smooth solutions of ill-posed problems, in particular when solving

  7. Convergence in energy consumption per capita across the US states, 1970–2013: An exploration through selected parametric and non-parametric methods

    International Nuclear Information System (INIS)

    Mohammadi, Hassan; Ram, Rati

    2017-01-01

    Noting the paucity of studies of convergence in energy consumption across the US states, and the usefulness of a study that shares the spirit of the enormous research on convergence in energy-related variables in cross-country contexts, this paper explores convergence in per-capita energy consumption across the US states over the 44-year period 1970–2013. Several well-known parametric and non-parametric approaches are explored partly to shed light on the substantive question and partly to provide a comparative methodological perspective on these approaches. Several statements summarize the outcome of our explorations. First, the widely-used Barro-type regressions do not indicate beta-convergence during the entire period or any of several sub-periods. Second, lack of sigma-convergence is also noted in terms of standard deviation of logarithms and coefficient of variation which do not show a decline between 1970 and 2013, but show slight upward trends. Third, kernel density function plots indicate some flattening of the distribution which is consistent with the results from sigma-convergence scenario. Fourth, intra-distribution mobility (“gamma convergence”) in terms of an index of rank concordance suggests a slow decline in the index. Fifth, the general impression from several types of panel and time-series unit-root tests is that of non-stationarity of the series and thus the lack of stochastic convergence during the period. Sixth, therefore, the overall impression seems to be that of the lack of convergence across states in per-capita energy consumption. The present interstate inequality in per-capita energy consumption may, therefore, reflect variations in structural factors and might not be expected to diminish.

  8. Nonparametric Mixture of Regression Models.

    Science.gov (United States)

    Huang, Mian; Li, Runze; Wang, Shaoli

    2013-07-01

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

  9. Nonparametric regression using the concept of minimum energy

    International Nuclear Information System (INIS)

    Williams, Mike

    2011-01-01

    It has recently been shown that an unbinned distance-based statistic, the energy, can be used to construct an extremely powerful nonparametric multivariate two sample goodness-of-fit test. An extension to this method that makes it possible to perform nonparametric regression using multiple multivariate data sets is presented in this paper. The technique, which is based on the concept of minimizing the energy of the system, permits determination of parameters of interest without the need for parametric expressions of the parent distributions of the data sets. The application and performance of this new method is discussed in the context of some simple example analyses.

  10. A nonparametric spatial scan statistic for continuous data.

    Science.gov (United States)

    Jung, Inkyung; Cho, Ho Jin

    2015-10-20

    Spatial scan statistics are widely used for spatial cluster detection, and several parametric models exist. For continuous data, a normal-based scan statistic can be used. However, the performance of the model has not been fully evaluated for non-normal data. We propose a nonparametric spatial scan statistic based on the Wilcoxon rank-sum test statistic and compared the performance of the method with parametric models via a simulation study under various scenarios. The nonparametric method outperforms the normal-based scan statistic in terms of power and accuracy in almost all cases under consideration in the simulation study. The proposed nonparametric spatial scan statistic is therefore an excellent alternative to the normal model for continuous data and is especially useful for data following skewed or heavy-tailed distributions.

  11. 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.

  12. A ¤nonparametric dynamic additive regression model for longitudinal data

    DEFF Research Database (Denmark)

    Martinussen, T.; Scheike, T. H.

    2000-01-01

    dynamic linear models, estimating equations, least squares, longitudinal data, nonparametric methods, partly conditional mean models, time-varying-coefficient models......dynamic linear models, estimating equations, least squares, longitudinal data, nonparametric methods, partly conditional mean models, time-varying-coefficient models...

  13. 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.

  14. 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.

  15. 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.

  16. Nonparametric correlation models for portfolio allocation

    DEFF Research Database (Denmark)

    Aslanidis, Nektarios; Casas, Isabel

    2013-01-01

    This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural ...... currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis....

  17. A contingency table approach to nonparametric testing

    CERN Document Server

    Rayner, JCW

    2000-01-01

    Most texts on nonparametric techniques concentrate on location and linear-linear (correlation) tests, with less emphasis on dispersion effects and linear-quadratic tests. Tests for higher moment effects are virtually ignored. Using a fresh approach, A Contingency Table Approach to Nonparametric Testing unifies and extends the popular, standard tests by linking them to tests based on models for data that can be presented in contingency tables.This approach unifies popular nonparametric statistical inference and makes the traditional, most commonly performed nonparametric analyses much more comp

  18. Nonparametric Bayesian inference in biostatistics

    CERN Document Server

    Müller, Peter

    2015-01-01

    As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...

  19. Nonparametric e-Mixture Estimation.

    Science.gov (United States)

    Takano, Ken; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru

    2016-12-01

    This study considers the common situation in data analysis when there are few observations of the distribution of interest or the target distribution, while abundant observations are available from auxiliary distributions. In this situation, it is natural to compensate for the lack of data from the target distribution by using data sets from these auxiliary distributions-in other words, approximating the target distribution in a subspace spanned by a set of auxiliary distributions. Mixture modeling is one of the simplest ways to integrate information from the target and auxiliary distributions in order to express the target distribution as accurately as possible. There are two typical mixtures in the context of information geometry: the [Formula: see text]- and [Formula: see text]-mixtures. The [Formula: see text]-mixture is applied in a variety of research fields because of the presence of the well-known expectation-maximazation algorithm for parameter estimation, whereas the [Formula: see text]-mixture is rarely used because of its difficulty of estimation, particularly for nonparametric models. The [Formula: see text]-mixture, however, is a well-tempered distribution that satisfies the principle of maximum entropy. To model a target distribution with scarce observations accurately, this letter proposes a novel framework for a nonparametric modeling of the [Formula: see text]-mixture and a geometrically inspired estimation algorithm. As numerical examples of the proposed framework, a transfer learning setup is considered. The experimental results show that this framework works well for three types of synthetic data sets, as well as an EEG real-world data set.

  20. Nonparametric inference of network structure and dynamics

    Science.gov (United States)

    Peixoto, Tiago P.

    The network structure of complex systems determine their function and serve as evidence for the evolutionary mechanisms that lie behind them. Despite considerable effort in recent years, it remains an open challenge to formulate general descriptions of the large-scale structure of network systems, and how to reliably extract such information from data. Although many approaches have been proposed, few methods attempt to gauge the statistical significance of the uncovered structures, and hence the majority cannot reliably separate actual structure from stochastic fluctuations. Due to the sheer size and high-dimensionality of many networks, this represents a major limitation that prevents meaningful interpretations of the results obtained with such nonstatistical methods. In this talk, I will show how these issues can be tackled in a principled and efficient fashion by formulating appropriate generative models of network structure that can have their parameters inferred from data. By employing a Bayesian description of such models, the inference can be performed in a nonparametric fashion, that does not require any a priori knowledge or ad hoc assumptions about the data. I will show how this approach can be used to perform model comparison, and how hierarchical models yield the most appropriate trade-off between model complexity and quality of fit based on the statistical evidence present in the data. I will also show how this general approach can be elegantly extended to networks with edge attributes, that are embedded in latent spaces, and that change in time. The latter is obtained via a fully dynamic generative network model, based on arbitrary-order Markov chains, that can also be inferred in a nonparametric fashion. Throughout the talk I will illustrate the application of the methods with many empirical networks such as the internet at the autonomous systems level, the global airport network, the network of actors and films, social networks, citations among

  1. A general approach to posterior contraction in nonparametric inverse problems

    NARCIS (Netherlands)

    Knapik, Bartek; Salomond, Jean Bernard

    In this paper, we propose a general method to derive an upper bound for the contraction rate of the posterior distribution for nonparametric inverse problems. We present a general theorem that allows us to derive contraction rates for the parameter of interest from contraction rates of the related

  2. Nonparametric estimation of location and scale parameters

    KAUST Repository

    Potgieter, C.J.

    2012-12-01

    Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal assumptions regarding the form of the distribution functions of X and Y. We discuss an approach to the estimation problem that is based on asymptotic likelihood considerations. Our results enable us to provide a methodology that can be implemented easily and which yields estimators that are often near optimal when compared to fully parametric methods. We evaluate the performance of the estimators in a series of Monte Carlo simulations. © 2012 Elsevier B.V. All rights reserved.

  3. 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.

  4. A Normalization-Free and Nonparametric Method Sharpens Large-Scale Transcriptome Analysis and Reveals Common Gene Alteration Patterns in Cancers.

    Science.gov (United States)

    Li, Qi-Gang; He, Yong-Han; Wu, Huan; Yang, Cui-Ping; Pu, Shao-Yan; Fan, Song-Qing; Jiang, Li-Ping; Shen, Qiu-Shuo; Wang, Xiao-Xiong; Chen, Xiao-Qiong; Yu, Qin; Li, Ying; Sun, Chang; Wang, Xiangting; Zhou, Jumin; Li, Hai-Peng; Chen, Yong-Bin; Kong, Qing-Peng

    2017-01-01

    Heterogeneity in transcriptional data hampers the identification of differentially expressed genes (DEGs) and understanding of cancer, essentially because current methods rely on cross-sample normalization and/or distribution assumption-both sensitive to heterogeneous values. Here, we developed a new method, Cross-Value Association Analysis (CVAA), which overcomes the limitation and is more robust to heterogeneous data than the other methods. Applying CVAA to a more complex pan-cancer dataset containing 5,540 transcriptomes discovered numerous new DEGs and many previously rarely explored pathways/processes; some of them were validated, both in vitro and in vivo , to be crucial in tumorigenesis, e.g., alcohol metabolism ( ADH1B ), chromosome remodeling ( NCAPH ) and complement system ( Adipsin ). Together, we present a sharper tool to navigate large-scale expression data and gain new mechanistic insights into tumorigenesis.

  5. 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.

  6. 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)

  7. Surface Estimation, Variable Selection, and the Nonparametric Oracle Property.

    Science.gov (United States)

    Storlie, Curtis B; Bondell, Howard D; Reich, Brian J; Zhang, Hao Helen

    2011-04-01

    Variable selection for multivariate nonparametric regression is an important, yet challenging, problem due, in part, to the infinite dimensionality of the function space. An ideal selection procedure should be automatic, stable, easy to use, and have desirable asymptotic properties. In particular, we define a selection procedure to be nonparametric oracle (np-oracle) if it consistently selects the correct subset of predictors and at the same time estimates the smooth surface at the optimal nonparametric rate, as the sample size goes to infinity. In this paper, we propose a model selection procedure for nonparametric models, and explore the conditions under which the new method enjoys the aforementioned properties. Developed in the framework of smoothing spline ANOVA, our estimator is obtained via solving a regularization problem with a novel adaptive penalty on the sum of functional component norms. Theoretical properties of the new estimator are established. Additionally, numerous simulated and real examples further demonstrate that the new approach substantially outperforms other existing methods in the finite sample setting.

  8. Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

    2013-04-01

    In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

  9. Nonparametric Bayesian Modeling of Complex Networks

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Mørup, Morten

    2013-01-01

    an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...

  10. Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering

    Directory of Open Access Journals (Sweden)

    Xin Tian

    2017-06-01

    Full Text Available We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online. Clustering is introduced for dictionary learning. A set of dictionaries could be generated, and each dictionary is used for one cluster’s sparse coding. In this way, the signals in one cluster could be well represented by their corresponding dictionaries. A nonparametric Bayesian dictionary learning method is used to learn the dictionaries, which naturally infers an appropriate dictionary size for each cluster. A uniform quantizer and an adaptive arithmetic coding algorithm are adopted to code the sparse coefficients. With comparisons to other state-of-the art approaches, the effectiveness of the proposed method could be validated in the experiments.

  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)

    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

  12. Nonparametric functional mapping of quantitative trait loci.

    Science.gov (United States)

    Yang, Jie; Wu, Rongling; Casella, George

    2009-03-01

    Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples.

  13. Essays on nonparametric econometrics of stochastic volatility

    NARCIS (Netherlands)

    Zu, Y.

    2012-01-01

    Volatility is a concept that describes the variation of financial returns. Measuring and modelling volatility dynamics is an important aspect of financial econometrics. This thesis is concerned with nonparametric approaches to volatility measurement and volatility model validation.

  14. Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data

    OpenAIRE

    CORNELIS A. LOS

    2004-01-01

    The efficiency of speculative markets, as represented by Fama's 1970 fair game model, is tested on weekly price index data of six Asian stock markets - Hong Kong, Indonesia, Malaysia, Singapore, Taiwan and Thailand - using Sherry's (1992) non-parametric methods. These scientific testing methods were originally developed to analyze the information processing efficiency of nervous systems. In particular, the stationarity and independence of the price innovations are tested over ten years, from ...

  15. 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...

  16. Car sharing à la carte

    CERN Multimedia

    Anaïs Schaeffer

    2012-01-01

    Do you want to make your commute to CERN easier, while saving money at the same time? Would you prefer not to spend a quarter of an hour crawling round the CERN car parks looking for a space? If so, read on: this article might well be of great interest to you.   We would like to draw your attention to a well established, albeit sadly under-used, method of transport: car sharing. To promote car-sharing, the GS Department has stepped in to call on the services of the Swiss firm Green Monkeys which specialises in this user-friendly and intelligent transport scheme. The company’s slogan is:  “Car-sharing as you want, when you want and as much as you want”. The principle is very straightforward. To use this car-sharing facility, you simply complete your free online registration with Green Monkeys, providing the following details: your journey, departure time, arrival time and days of the week, and indicating whether you are a passenger or driver or both. &a...

  17. 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

  18. Bayesian nonparametric adaptive control using Gaussian processes.

    Science.gov (United States)

    Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A

    2015-03-01

    Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.

  19. 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.

  20. 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...

  1. Nonparametric Regression Estimation for Multivariate Null Recurrent Processes

    Directory of Open Access Journals (Sweden)

    Biqing Cai

    2015-04-01

    Full Text Available This paper discusses nonparametric kernel regression with the regressor being a \\(d\\-dimensional \\(\\beta\\-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate \\(\\sqrt{n(Th^{d}}\\, where \\(n(T\\ is the number of regenerations for a \\(\\beta\\-null recurrent process and the limiting distribution (with proper normalization is normal. Furthermore, we show that the two-step estimator for the volatility function is consistent. The finite sample performance of the estimate is quite reasonable when the leave-one-out cross validation method is used for bandwidth selection. We apply the proposed method to study the relationship of Federal funds rate with 3-month and 5-year T-bill rates and discover the existence of nonlinearity of the relationship. Furthermore, the in-sample and out-of-sample performance of the nonparametric model is far better than the linear model.

  2. Comparing nonparametric Bayesian tree priors for clonal reconstruction of tumors.

    Science.gov (United States)

    Deshwar, Amit G; Vembu, Shankar; Morris, Quaid

    2015-01-01

    Statistical machine learning methods, especially nonparametric Bayesian methods, have become increasingly popular to infer clonal population structure of tumors. Here we describe the treeCRP, an extension of the Chinese restaurant process (CRP), a popular construction used in nonparametric mixture models, to infer the phylogeny and genotype of major subclonal lineages represented in the population of cancer cells. We also propose new split-merge updates tailored to the subclonal reconstruction problem that improve the mixing time of Markov chains. In comparisons with the tree-structured stick breaking prior used in PhyloSub, we demonstrate superior mixing and running time using the treeCRP with our new split-merge procedures. We also show that given the same number of samples, TSSB and treeCRP have similar ability to recover the subclonal structure of a tumor…

  3. Non-parametric estimation of the individual's utility map

    OpenAIRE

    Noguchi, Takao; Sanborn, Adam N.; Stewart, Neil

    2013-01-01

    Models of risky choice have attracted much attention in behavioural economics. Previous research has repeatedly demonstrated that individuals' choices are not well explained by expected utility theory, and a number of alternative models have been examined using carefully selected sets of choice alternatives. The model performance however, can depend on which choice alternatives are being tested. Here we develop a non-parametric method for estimating the utility map over the wide range of choi...

  4. 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.

  5. 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...

  6. 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…

  7. 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.

  8. Single versus mixture Weibull distributions for nonparametric satellite reliability

    International Nuclear Information System (INIS)

    Castet, Jean-Francois; Saleh, Joseph H.

    2010-01-01

    Long recognized as a critical design attribute for space systems, satellite reliability has not yet received the proper attention as limited on-orbit failure data and statistical analyses can be found in the technical literature. To fill this gap, we recently conducted a nonparametric analysis of satellite reliability for 1584 Earth-orbiting satellites launched between January 1990 and October 2008. In this paper, we provide an advanced parametric fit, based on mixture of Weibull distributions, and compare it with the single Weibull distribution model obtained with the Maximum Likelihood Estimation (MLE) method. We demonstrate that both parametric fits are good approximations of the nonparametric satellite reliability, but that the mixture Weibull distribution provides significant accuracy in capturing all the failure trends in the failure data, as evidenced by the analysis of the residuals and their quasi-normal dispersion.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. STATCAT, Statistical Analysis of Parametric and Non-Parametric Data

    International Nuclear Information System (INIS)

    David, Hugh

    1990-01-01

    1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required

  15. Teaching Nonparametric Statistics Using Student Instrumental Values.

    Science.gov (United States)

    Anderson, Jonathan W.; Diddams, Margaret

    Nonparametric statistics are often difficult to teach in introduction to statistics courses because of the lack of real-world examples. This study demonstrated how teachers can use differences in the rankings and ratings of undergraduate and graduate values to discuss: (1) ipsative and normative scaling; (2) uses of the Mann-Whitney U-test; and…

  16. Nonparametric conditional predictive regions for time series

    NARCIS (Netherlands)

    de Gooijer, J.G.; Zerom Godefay, D.

    2000-01-01

    Several nonparametric predictors based on the Nadaraya-Watson kernel regression estimator have been proposed in the literature. They include the conditional mean, the conditional median, and the conditional mode. In this paper, we consider three types of predictive regions for these predictors — the

  17. Nonparametric predictive inference in statistical process control

    NARCIS (Netherlands)

    Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

    2004-01-01

    Statistical process control (SPC) is used to decide when to stop a process as confidence in the quality of the next item(s) is low. Information to specify a parametric model is not always available, and as SPC is of a predictive nature, we present a control chart developed using nonparametric

  18. Nonparametric estimation in models for unobservable heterogeneity

    OpenAIRE

    Hohmann, Daniel

    2014-01-01

    Nonparametric models which allow for data with unobservable heterogeneity are studied. The first publication introduces new estimators and their asymptotic properties for conditional mixture models. The second publication considers estimation of a function from noisy observations of its Radon transform in a Gaussian white noise model.

  19. Nonparametric estimation of location and scale parameters

    KAUST Repository

    Potgieter, C.J.; Lombard, F.

    2012-01-01

    Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal

  20. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

  1. Nonparametric Inference for Periodic Sequences

    KAUST Repository

    Sun, Ying; Hart, Jeffrey D.; Genton, Marc G.

    2012-01-01

    the periodogram, a widely used tool for period estimation. The CV method is computationally simple and implicitly penalizes multiples of the smallest period, leading to a "virtually" consistent estimator of integer periods. This estimator is investigated both

  2. 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...

  3. Evaluation of Nonparametric Probabilistic Forecasts of Wind Power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg, orlov 31.07.2008

    Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the most...... likely outcome for each look-ahead time, but also with uncertainty estimates given by probabilistic forecasts. In order to avoid assumptions on the shape of predictive distributions, these probabilistic predictions are produced from nonparametric methods, and then take the form of a single or a set...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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)

  12. 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.

  13. Robustifying Bayesian nonparametric mixtures for count data.

    Science.gov (United States)

    Canale, Antonio; Prünster, Igor

    2017-03-01

    Our motivating application stems from surveys of natural populations and is characterized by large spatial heterogeneity in the counts, which makes parametric approaches to modeling local animal abundance too restrictive. We adopt a Bayesian nonparametric approach based on mixture models and innovate with respect to popular Dirichlet process mixture of Poisson kernels by increasing the model flexibility at the level both of the kernel and the nonparametric mixing measure. This allows to derive accurate and robust estimates of the distribution of local animal abundance and of the corresponding clusters. The application and a simulation study for different scenarios yield also some general methodological implications. Adding flexibility solely at the level of the mixing measure does not improve inferences, since its impact is severely limited by the rigidity of the Poisson kernel with considerable consequences in terms of bias. However, once a kernel more flexible than the Poisson is chosen, inferences can be robustified by choosing a prior more general than the Dirichlet process. Therefore, to improve the performance of Bayesian nonparametric mixtures for count data one has to enrich the model simultaneously at both levels, the kernel and the mixing measure. © 2016, The International Biometric Society.

  14. A Bayesian nonparametric estimation of distributions and quantiles

    International Nuclear Information System (INIS)

    Poern, K.

    1988-11-01

    The report describes a Bayesian, nonparametric method for the estimation of a distribution function and its quantiles. The method, presupposing random sampling, is nonparametric, so the user has to specify a prior distribution on a space of distributions (and not on a parameter space). In the current application, where the method is used to estimate the uncertainty of a parametric calculational model, the Dirichlet prior distribution is to a large extent determined by the first batch of Monte Carlo-realizations. In this case the results of the estimation technique is very similar to the conventional empirical distribution function. The resulting posterior distribution is also Dirichlet, and thus facilitates the determination of probability (confidence) intervals at any given point in the space of interest. Another advantage is that also the posterior distribution of a specified quantitle can be derived and utilized to determine a probability interval for that quantile. The method was devised for use in the PROPER code package for uncertainty and sensitivity analysis. (orig.)

  15. A non-parametric framework for estimating threshold limit values

    Directory of Open Access Journals (Sweden)

    Ulm Kurt

    2005-11-01

    Full Text Available Abstract Background To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. Methods We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss two algorithms to select the threshold among them: the reduced isotonic regression and an algorithm considering the closed family of hypotheses. We assess the performance of these two alternative approaches under different scenarios in a simulation study. We illustrate the framework by analysing the data from a study conducted by the German Research Foundation aiming to set a threshold limit value in the exposure to total dust at workplace, as a causal agent for developing chronic bronchitis. Results In the paper we demonstrate the use and the properties of the proposed methodology along with the results from an application. The method appears to detect the threshold with satisfactory success. However, its performance can be compromised by the low power to reject the constant risk assumption when the true dose-response relationship is weak. Conclusion The estimation of thresholds based on isotonic framework is conceptually simple and sufficiently powerful. Given that in threshold value estimation context there is not a gold standard method, the proposed model provides a useful non-parametric alternative to the standard approaches and can corroborate or challenge their findings.

  16. Single-cell multiplexed cytokine profiling of CD19 CAR-T cells reveals a diverse landscape of polyfunctional antigen-specific response.

    Science.gov (United States)

    Xue, Qiong; Bettini, Emily; Paczkowski, Patrick; Ng, Colin; Kaiser, Alaina; McConnell, Timothy; Kodrasi, Olja; Quigley, Máire F; Heath, James; Fan, Rong; Mackay, Sean; Dudley, Mark E; Kassim, Sadik H; Zhou, Jing

    2017-11-21

    It remains challenging to characterize the functional attributes of chimeric antigen receptor (CAR)-engineered T cell product targeting CD19 related to potency and immunotoxicity ex vivo, despite promising in vivo efficacy in patients with B cell malignancies. We employed a single-cell, 16-plex cytokine microfluidics device and new analysis techniques to evaluate the functional profile of CD19 CAR-T cells upon antigen-specific stimulation. CAR-T cells were manufactured from human PBMCs transfected with the lentivirus encoding the CD19-BB-z transgene and expanded with anti-CD3/anti-CD28 coated beads. The enriched CAR-T cells were stimulated with anti-CAR or control IgG beads, stained with anti-CD4 RPE and anti-CD8 Alexa Fluor 647 antibodies, and incubated for 16 h in a single-cell barcode chip (SCBC). Each SCBC contains ~12,000 microchambers, covered with a glass slide that was pre-patterned with a complete copy of a 16-plex antibody array. Protein secretions from single CAR-T cells were captured and subsequently analyzed using proprietary software and new visualization methods. We demonstrate a new method for single-cell profiling of CD19 CAR-T pre-infusion products prepared from 4 healthy donors. CAR-T single cells exhibited a marked heterogeneity of cytokine secretions and polyfunctional (2+ cytokine) subsets specific to anti-CAR bead stimulation. The breadth of responses includes anti-tumor effector (Granzyme B, IFN-γ, MIP-1α, TNF-α), stimulatory (GM-CSF, IL-2, IL-8), regulatory (IL-4, IL-13, IL-22), and inflammatory (IL-6, IL-17A) functions. Furthermore, we developed two new bioinformatics tools for more effective polyfunctional subset visualization and comparison between donors. Single-cell, multiplexed, proteomic profiling of CD19 CAR-T product reveals a diverse landscape of immune effector response of CD19 CAR-T cells to antigen-specific challenge, providing a new platform for capturing CAR-T product data for correlative analysis. Additionally, such high

  17. Introduction to nonparametric statistics for the biological sciences using R

    CERN Document Server

    MacFarland, Thomas W

    2016-01-01

    This book contains a rich set of tools for nonparametric analyses, and the purpose of this supplemental text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriate To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses a...

  18. 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.

  19. Nonparametric Bayesian density estimation on manifolds with applications to planar shapes.

    Science.gov (United States)

    Bhattacharya, Abhishek; Dunson, David B

    2010-12-01

    Statistical analysis on landmark-based shape spaces has diverse applications in morphometrics, medical diagnostics, machine vision and other areas. These shape spaces are non-Euclidean quotient manifolds. To conduct nonparametric inferences, one may define notions of centre and spread on this manifold and work with their estimates. However, it is useful to consider full likelihood-based methods, which allow nonparametric estimation of the probability density. This article proposes a broad class of mixture models constructed using suitable kernels on a general compact metric space and then on the planar shape space in particular. Following a Bayesian approach with a nonparametric prior on the mixing distribution, conditions are obtained under which the Kullback-Leibler property holds, implying large support and weak posterior consistency. Gibbs sampling methods are developed for posterior computation, and the methods are applied to problems in density estimation and classification with shape-based predictors. Simulation studies show improved estimation performance relative to existing approaches.

  20. Bayesian nonparametric dictionary learning for compressed sensing MRI.

    Science.gov (United States)

    Huang, Yue; Paisley, John; Lin, Qin; Ding, Xinghao; Fu, Xueyang; Zhang, Xiao-Ping

    2014-12-01

    We develop a Bayesian nonparametric model for reconstructing magnetic resonance images (MRIs) from highly undersampled k -space data. We perform dictionary learning as part of the image reconstruction process. To this end, we use the beta process as a nonparametric dictionary learning prior for representing an image patch as a sparse combination of dictionary elements. The size of the dictionary and patch-specific sparsity pattern are inferred from the data, in addition to other dictionary learning variables. Dictionary learning is performed directly on the compressed image, and so is tailored to the MRI being considered. In addition, we investigate a total variation penalty term in combination with the dictionary learning model, and show how the denoising property of dictionary learning removes dependence on regularization parameters in the noisy setting. We derive a stochastic optimization algorithm based on Markov chain Monte Carlo for the Bayesian model, and use the alternating direction method of multipliers for efficiently performing total variation minimization. We present empirical results on several MRI, which show that the proposed regularization framework can improve reconstruction accuracy over other methods.

  1. Bioprocess iterative batch-to-batch optimization based on hybrid parametric/nonparametric models.

    Science.gov (United States)

    Teixeira, Ana P; Clemente, João J; Cunha, António E; Carrondo, Manuel J T; Oliveira, Rui

    2006-01-01

    This paper presents a novel method for iterative batch-to-batch dynamic optimization of bioprocesses. The relationship between process performance and control inputs is established by means of hybrid grey-box models combining parametric and nonparametric structures. The bioreactor dynamics are defined by material balance equations, whereas the cell population subsystem is represented by an adjustable mixture of nonparametric and parametric models. Thus optimizations are possible without detailed mechanistic knowledge concerning the biological system. A clustering technique is used to supervise the reliability of the nonparametric subsystem during the optimization. Whenever the nonparametric outputs are unreliable, the objective function is penalized. The technique was evaluated with three simulation case studies. The overall results suggest that the convergence to the optimal process performance may be achieved after a small number of batches. The model unreliability risk constraint along with sampling scheduling are crucial to minimize the experimental effort required to attain a given process performance. In general terms, it may be concluded that the proposed method broadens the application of the hybrid parametric/nonparametric modeling technique to "newer" processes with higher potential for optimization.

  2. 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.

  3. 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

  4. 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

  5. Decompounding random sums: A nonparametric approach

    DEFF Research Database (Denmark)

    Hansen, Martin Bøgsted; Pitts, Susan M.

    Observations from sums of random variables with a random number of summands, known as random, compound or stopped sums arise within many areas of engineering and science. Quite often it is desirable to infer properties of the distribution of the terms in the random sum. In the present paper we...... review a number of applications and consider the nonlinear inverse problem of inferring the cumulative distribution function of the components in the random sum. We review the existing literature on non-parametric approaches to the problem. The models amenable to the analysis are generalized considerably...

  6. A Nonparametric Test for Seasonal Unit Roots

    OpenAIRE

    Kunst, Robert M.

    2009-01-01

    Abstract: We consider a nonparametric test for the null of seasonal unit roots in quarterly time series that builds on the RUR (records unit root) test by Aparicio, Escribano, and Sipols. We find that the test concept is more promising than a formalization of visual aids such as plots by quarter. In order to cope with the sensitivity of the original RUR test to autocorrelation under its null of a unit root, we suggest an augmentation step by autoregression. We present some evidence on the siz...

  7. 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.

  8. 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.

  9. 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

  10. Multivariate nonparametric regression and visualization with R and applications to finance

    CERN Document Server

    Klemelä, Jussi

    2014-01-01

    A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generatingmechanisms, the book begins with an overview of classification and regression. The book then introduces and examines various tested and proven visualization techniques for learning samples and functio

  11. Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

    Science.gov (United States)

    Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

    2018-03-01

    We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

  12. Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

    Directory of Open Access Journals (Sweden)

    Jinchao Feng

    2018-03-01

    Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

  13. 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.

  14. Nonparametric Analyses of Log-Periodic Precursors to Financial Crashes

    Science.gov (United States)

    Zhou, Wei-Xing; Sornette, Didier

    We apply two nonparametric methods to further test the hypothesis that log-periodicity characterizes the detrended price trajectory of large financial indices prior to financial crashes or strong corrections. The term "parametric" refers here to the use of the log-periodic power law formula to fit the data; in contrast, "nonparametric" refers to the use of general tools such as Fourier transform, and in the present case the Hilbert transform and the so-called (H, q)-analysis. The analysis using the (H, q)-derivative is applied to seven time series ending with the October 1987 crash, the October 1997 correction and the April 2000 crash of the Dow Jones Industrial Average (DJIA), the Standard & Poor 500 and Nasdaq indices. The Hilbert transform is applied to two detrended price time series in terms of the ln(tc-t) variable, where tc is the time of the crash. Taking all results together, we find strong evidence for a universal fundamental log-frequency f=1.02±0.05 corresponding to the scaling ratio λ=2.67±0.12. These values are in very good agreement with those obtained in earlier works with different parametric techniques. This note is extracted from a long unpublished report with 58 figures available at , which extensively describes the evidence we have accumulated on these seven time series, in particular by presenting all relevant details so that the reader can judge for himself or herself the validity and robustness of the results.

  15. Genomic breeding value estimation using nonparametric additive regression models

    Directory of Open Access Journals (Sweden)

    Solberg Trygve

    2009-01-01

    Full Text Available Abstract Genomic selection refers to the use of genomewide dense markers for breeding value estimation and subsequently for selection. The main challenge of genomic breeding value estimation is the estimation of many effects from a limited number of observations. Bayesian methods have been proposed to successfully cope with these challenges. As an alternative class of models, non- and semiparametric models were recently introduced. The present study investigated the ability of nonparametric additive regression models to predict genomic breeding values. The genotypes were modelled for each marker or pair of flanking markers (i.e. the predictors separately. The nonparametric functions for the predictors were estimated simultaneously using additive model theory, applying a binomial kernel. The optimal degree of smoothing was determined by bootstrapping. A mutation-drift-balance simulation was carried out. The breeding values of the last generation (genotyped was predicted using data from the next last generation (genotyped and phenotyped. The results show moderate to high accuracies of the predicted breeding values. A determination of predictor specific degree of smoothing increased the accuracy.

  16. Application of nonparametric statistics to material strength/reliability assessment

    International Nuclear Information System (INIS)

    Arai, Taketoshi

    1992-01-01

    An advanced material technology requires data base on a wide variety of material behavior which need to be established experimentally. It may often happen that experiments are practically limited in terms of reproducibility or a range of test parameters. Statistical methods can be applied to understanding uncertainties in such a quantitative manner as required from the reliability point of view. Statistical assessment involves determinations of a most probable value and the maximum and/or minimum value as one-sided or two-sided confidence limit. A scatter of test data can be approximated by a theoretical distribution only if the goodness of fit satisfies a test criterion. Alternatively, nonparametric statistics (NPS) or distribution-free statistics can be applied. Mathematical procedures by NPS are well established for dealing with most reliability problems. They handle only order statistics of a sample. Mathematical formulas and some applications to engineering assessments are described. They include confidence limits of median, population coverage of sample, required minimum number of a sample, and confidence limits of fracture probability. These applications demonstrate that a nonparametric statistical estimation is useful in logical decision making in the case a large uncertainty exists. (author)

  17. A comparative study of non-parametric models for identification of ...

    African Journals Online (AJOL)

    However, the frequency response method using random binary signals was good for unpredicted white noise characteristics and considered the best method for non-parametric system identifica-tion. The autoregressive external input (ARX) model was very useful for system identification, but on applicati-on, few input ...

  18. Bayesian Nonparametric Clustering for Positive Definite Matrices.

    Science.gov (United States)

    Cherian, Anoop; Morellas, Vassilios; Papanikolopoulos, Nikolaos

    2016-05-01

    Symmetric Positive Definite (SPD) matrices emerge as data descriptors in several applications of computer vision such as object tracking, texture recognition, and diffusion tensor imaging. Clustering these data matrices forms an integral part of these applications, for which soft-clustering algorithms (K-Means, expectation maximization, etc.) are generally used. As is well-known, these algorithms need the number of clusters to be specified, which is difficult when the dataset scales. To address this issue, we resort to the classical nonparametric Bayesian framework by modeling the data as a mixture model using the Dirichlet process (DP) prior. Since these matrices do not conform to the Euclidean geometry, rather belongs to a curved Riemannian manifold,existing DP models cannot be directly applied. Thus, in this paper, we propose a novel DP mixture model framework for SPD matrices. Using the log-determinant divergence as the underlying dissimilarity measure to compare these matrices, and further using the connection between this measure and the Wishart distribution, we derive a novel DPM model based on the Wishart-Inverse-Wishart conjugate pair. We apply this model to several applications in computer vision. Our experiments demonstrate that our model is scalable to the dataset size and at the same time achieves superior accuracy compared to several state-of-the-art parametric and nonparametric clustering algorithms.

  19. Nonparametric estimation of stochastic differential equations with sparse Gaussian processes.

    Science.gov (United States)

    García, Constantino A; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G

    2017-08-01

    The application of stochastic differential equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a nonparametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudosamples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behavior of complex systems.

  20. Indoor Positioning Using Nonparametric Belief Propagation Based on Spanning Trees

    Directory of Open Access Journals (Sweden)

    Savic Vladimir

    2010-01-01

    Full Text Available Nonparametric belief propagation (NBP is one of the best-known methods for cooperative localization in sensor networks. It is capable of providing information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance measurement errors. However, the accuracy of NBP is questionable in loopy networks. Therefore, in this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST created by breadth first search (BFS method. In addition, we propose a reliable indoor model based on obtained measurements in our lab. According to our simulation results, NBP-ST performs better than NBP in terms of accuracy and communication cost in the networks with high connectivity (i.e., highly loopy networks. Furthermore, the computational and communication costs are nearly constant with respect to the transmission radius. However, the drawbacks of proposed method are a little bit higher computational cost and poor performance in low-connected networks.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Generative Temporal Modelling of Neuroimaging - Decomposition and Nonparametric Testing

    DEFF Research Database (Denmark)

    Hald, Ditte Høvenhoff

    The goal of this thesis is to explore two improvements for functional magnetic resonance imaging (fMRI) analysis; namely our proposed decomposition method and an extension to the non-parametric testing framework. Analysis of fMRI allows researchers to investigate the functional processes...... of the brain, and provides insight into neuronal coupling during mental processes or tasks. The decomposition method is a Gaussian process-based independent components analysis (GPICA), which incorporates a temporal dependency in the sources. A hierarchical model specification is used, featuring both...... instantaneous and convolutive mixing, and the inferred temporal patterns. Spatial maps are seen to capture smooth and localized stimuli-related components, and often identifiable noise components. The implementation is freely available as a GUI/SPM plugin, and we recommend using GPICA as an additional tool when...

  9. Nonparametric autocovariance estimation from censored time series by Gaussian imputation.

    Science.gov (United States)

    Park, Jung Wook; Genton, Marc G; Ghosh, Sujit K

    2009-02-01

    One of the most frequently used methods to model the autocovariance function of a second-order stationary time series is to use the parametric framework of autoregressive and moving average models developed by Box and Jenkins. However, such parametric models, though very flexible, may not always be adequate to model autocovariance functions with sharp changes. Furthermore, if the data do not follow the parametric model and are censored at a certain value, the estimation results may not be reliable. We develop a Gaussian imputation method to estimate an autocovariance structure via nonparametric estimation of the autocovariance function in order to address both censoring and incorrect model specification. We demonstrate the effectiveness of the technique in terms of bias and efficiency with simulations under various rates of censoring and underlying models. We describe its application to a time series of silicon concentrations in the Arctic.

  10. 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

  11. On Parametric (and Non-Parametric Variation

    Directory of Open Access Journals (Sweden)

    Neil Smith

    2009-11-01

    Full Text Available This article raises the issue of the correct characterization of ‘Parametric Variation’ in syntax and phonology. After specifying their theoretical commitments, the authors outline the relevant parts of the Principles–and–Parameters framework, and draw a three-way distinction among Universal Principles, Parameters, and Accidents. The core of the contribution then consists of an attempt to provide identity criteria for parametric, as opposed to non-parametric, variation. Parametric choices must be antecedently known, and it is suggested that they must also satisfy seven individually necessary and jointly sufficient criteria. These are that they be cognitively represented, systematic, dependent on the input, deterministic, discrete, mutually exclusive, and irreversible.

  12. Nonparametric predictive pairwise comparison with competing risks

    International Nuclear Information System (INIS)

    Coolen-Maturi, Tahani

    2014-01-01

    In reliability, failure data often correspond to competing risks, where several failure modes can cause a unit to fail. This paper presents nonparametric predictive inference (NPI) for pairwise comparison with competing risks data, assuming that the failure modes are independent. These failure modes could be the same or different among the two groups, and these can be both observed and unobserved failure modes. NPI is a statistical approach based on few assumptions, with inferences strongly based on data and with uncertainty quantified via lower and upper probabilities. The focus is on the lower and upper probabilities for the event that the lifetime of a future unit from one group, say Y, is greater than the lifetime of a future unit from the second group, say X. The paper also shows how the two groups can be compared based on particular failure mode(s), and the comparison of the two groups when some of the competing risks are combined is discussed

  13. 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

    rate was 0.342 for the training sample and 0.346 for the validation sample. The CART model was easier to interpret and discovered target populations that possess clinical significance. This study suggests that the non-parametric CART model is parsimonious, potentially easier to interpret, and provides additional information in identifying the subgroups at high risk of ATP use among cigarette smokers.

  14. Exact nonparametric confidence bands for the survivor function.

    Science.gov (United States)

    Matthews, David

    2013-10-12

    A method to produce exact simultaneous confidence bands for the empirical cumulative distribution function that was first described by Owen, and subsequently corrected by Jager and Wellner, is the starting point for deriving exact nonparametric confidence bands for the survivor function of any positive random variable. We invert a nonparametric likelihood test of uniformity, constructed from the Kaplan-Meier estimator of the survivor function, to obtain simultaneous lower and upper bands for the function of interest with specified global confidence level. The method involves calculating a null distribution and associated critical value for each observed sample configuration. However, Noe recursions and the Van Wijngaarden-Decker-Brent root-finding algorithm provide the necessary tools for efficient computation of these exact bounds. Various aspects of the effect of right censoring on these exact bands are investigated, using as illustrations two observational studies of survival experience among non-Hodgkin's lymphoma patients and a much larger group of subjects with advanced lung cancer enrolled in trials within the North Central Cancer Treatment Group. Monte Carlo simulations confirm the merits of the proposed method of deriving simultaneous interval estimates of the survivor function across the entire range of the observed sample. This research was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada. It was begun while the author was visiting the Department of Statistics, University of Auckland, and completed during a subsequent sojourn at the Medical Research Council Biostatistics Unit in Cambridge. The support of both institutions, in addition to that of NSERC and the University of Waterloo, is greatly appreciated.

  15. Hyperspectral image segmentation using a cooperative nonparametric approach

    Science.gov (United States)

    Taher, Akar; Chehdi, Kacem; Cariou, Claude

    2013-10-01

    In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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.

  1. Supremum Norm Posterior Contraction and Credible Sets for Nonparametric Multivariate Regression

    NARCIS (Netherlands)

    Yoo, W.W.; Ghosal, S

    2016-01-01

    In the setting of nonparametric multivariate regression with unknown error variance, we study asymptotic properties of a Bayesian method for estimating a regression function f and its mixed partial derivatives. We use a random series of tensor product of B-splines with normal basis coefficients as a

  2. Does Private Tutoring Work? The Effectiveness of Private Tutoring: A Nonparametric Bounds Analysis

    Science.gov (United States)

    Hof, Stefanie

    2014-01-01

    Private tutoring has become popular throughout the world. However, evidence for the effect of private tutoring on students' academic outcome is inconclusive; therefore, this paper presents an alternative framework: a nonparametric bounds method. The present examination uses, for the first time, a large representative data-set in a European setting…

  3. Assessing pupil and school performance by non-parametric and parametric techniques

    NARCIS (Netherlands)

    de Witte, K.; Thanassoulis, E.; Simpson, G.; Battisti, G.; Charlesworth-May, A.

    2010-01-01

    This paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall

  4. Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

    Science.gov (United States)

    Mittag, Kathleen Cage

    Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

  5. Nonparametric estimation of the stationary M/G/1 workload distribution function

    DEFF Research Database (Denmark)

    Hansen, Martin Bøgsted

    2005-01-01

    In this paper it is demonstrated how a nonparametric estimator of the stationary workload distribution function of the M/G/1-queue can be obtained by systematic sampling the workload process. Weak convergence results and bootstrap methods for empirical distribution functions for stationary associ...

  6. Debt and growth: A non-parametric approach

    Science.gov (United States)

    Brida, Juan Gabriel; Gómez, David Matesanz; Seijas, Maria Nela

    2017-11-01

    In this study, we explore the dynamic relationship between public debt and economic growth by using a non-parametric approach based on data symbolization and clustering methods. The study uses annual data of general government consolidated gross debt-to-GDP ratio and gross domestic product for sixteen countries between 1977 and 2015. Using symbolic sequences, we introduce a notion of distance between the dynamical paths of different countries. Then, a Minimal Spanning Tree and a Hierarchical Tree are constructed from time series to help detecting the existence of groups of countries sharing similar economic performance. The main finding of the study appears for the period 2008-2016 when several countries surpassed the 90% debt-to-GDP threshold. During this period, three groups (clubs) of countries are obtained: high, mid and low indebted countries, suggesting that the employed debt-to-GDP threshold drives economic dynamics for the selected countries.

  7. Nonparametric estimation of benchmark doses in environmental risk assessment

    Science.gov (United States)

    Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen

    2013-01-01

    Summary An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a pre-specified benchmark response in a dose-response experiment. In such settings, representations of the risk are traditionally based on a parametric dose-response model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007). We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits’ small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations. PMID:23914133

  8. Simple nonparametric checks for model data fit in CAT

    NARCIS (Netherlands)

    Meijer, R.R.

    2005-01-01

    In this paper, the usefulness of several nonparametric checks is discussed in a computerized adaptive testing (CAT) context. Although there is no tradition of nonparametric scalability in CAT, it can be argued that scalability checks can be useful to investigate, for example, the quality of item

  9. Nonparametric Bayesian inference for multidimensional compound Poisson processes

    NARCIS (Netherlands)

    Gugushvili, S.; van der Meulen, F.; Spreij, P.

    2015-01-01

    Given a sample from a discretely observed multidimensional compound Poisson process, we study the problem of nonparametric estimation of its jump size density r0 and intensity λ0. We take a nonparametric Bayesian approach to the problem and determine posterior contraction rates in this context,

  10. Nonparametric analysis of blocked ordered categories data: some examples revisited

    Directory of Open Access Journals (Sweden)

    O. Thas

    2006-08-01

    Full Text Available Nonparametric analysis for general block designs can be given by using the Cochran-Mantel-Haenszel (CMH statistics. We demonstrate this with four examples and note that several well-known nonparametric statistics are special cases of CMH statistics.

  11. A Structural Labor Supply Model with Nonparametric Preferences

    NARCIS (Netherlands)

    van Soest, A.H.O.; Das, J.W.M.; Gong, X.

    2000-01-01

    Nonparametric techniques are usually seen as a statistic device for data description and exploration, and not as a tool for estimating models with a richer economic structure, which are often required for policy analysis.This paper presents an example where nonparametric flexibility can be attained

  12. 2nd Conference of the International Society for Nonparametric Statistics

    CERN Document Server

    Manteiga, Wenceslao; Romo, Juan

    2016-01-01

    This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cádiz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid. The 15 articles are a representative sample of the 336 contributed papers presented at the conference. They cover topics such as high-dimensional data modelling, inference for stochastic processes and for dependent data, nonparametric and goodness-of-fit testing, nonparametric curve estimation, object-oriented data analysis, and semiparametric inference. The aim of the ISNPS 2014 conference was to bring together recent advances and trends in several areas of nonparametric statistics in order to facilitate the exchange of research ideas, promote collaboration among researchers...

  13. 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.

  14. 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.

  15. Testing for constant nonparametric effects in general semiparametric regression models with interactions

    KAUST Repository

    Wei, Jiawei

    2011-07-01

    We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work was originally motivated by a unique testing problem in genetic epidemiology (Chatterjee, et al., 2006) that involved a typical generalized linear model but with an additional term reminiscent of the Tukey one-degree-of-freedom formulation, and their interest was in testing for main effects of the genetic variables, while gaining statistical power by allowing for a possible interaction between genes and the environment. Later work (Maity, et al., 2009) involved the possibility of modeling the environmental variable nonparametrically, but they focused on whether there was a parametric main effect for the genetic variables. In this paper, we consider the complementary problem, where the interest is in testing for the main effect of the nonparametrically modeled environmental variable. We derive a generalized likelihood ratio test for this hypothesis, show how to implement it, and provide evidence that our method can improve statistical power when compared to standard partially linear models with main effects only. We use the method for the primary purpose of analyzing data from a case-control study of colorectal adenoma.

  16. 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

  17. 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.

  18. 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

  19. Nonparametric tests for equality of psychometric functions.

    Science.gov (United States)

    García-Pérez, Miguel A; Núñez-Antón, Vicente

    2017-12-07

    Many empirical studies measure psychometric functions (curves describing how observers' performance varies with stimulus magnitude) because these functions capture the effects of experimental conditions. To assess these effects, parametric curves are often fitted to the data and comparisons are carried out by testing for equality of mean parameter estimates across conditions. This approach is parametric and, thus, vulnerable to violations of the implied assumptions. Furthermore, testing for equality of means of parameters may be misleading: Psychometric functions may vary meaningfully across conditions on an observer-by-observer basis with no effect on the mean values of the estimated parameters. Alternative approaches to assess equality of psychometric functions per se are thus needed. This paper compares three nonparametric tests that are applicable in all situations of interest: The existing generalized Mantel-Haenszel test, a generalization of the Berry-Mielke test that was developed here, and a split variant of the generalized Mantel-Haenszel test also developed here. Their statistical properties (accuracy and power) are studied via simulation and the results show that all tests are indistinguishable as to accuracy but they differ non-uniformly as to power. Empirical use of the tests is illustrated via analyses of published data sets and practical recommendations are given. The computer code in MATLAB and R to conduct these tests is available as Electronic Supplemental Material.

  20. Non-parametric Tuning of PID Controllers A Modified Relay-Feedback-Test Approach

    CERN Document Server

    Boiko, Igor

    2013-01-01

    The relay feedback test (RFT) has become a popular and efficient  tool used in process identification and automatic controller tuning. Non-parametric Tuning of PID Controllers couples new modifications of classical RFT with application-specific optimal tuning rules to form a non-parametric method of test-and-tuning. Test and tuning are coordinated through a set of common parameters so that a PID controller can obtain the desired gain or phase margins in a system exactly, even with unknown process dynamics. The concept of process-specific optimal tuning rules in the nonparametric setup, with corresponding tuning rules for flow, level pressure, and temperature control loops is presented in the text.   Common problems of tuning accuracy based on parametric and non-parametric approaches are addressed. In addition, the text treats the parametric approach to tuning based on the modified RFT approach and the exact model of oscillations in the system under test using the locus of a perturbedrelay system (LPRS) meth...

  1. 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.

  2. 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.

  3. 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.

  4. Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

    Science.gov (United States)

    Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.

    2011-01-01

    Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433

  5. Nonparametric Bayes Classification and Hypothesis Testing on Manifolds

    Science.gov (United States)

    Bhattacharya, Abhishek; Dunson, David

    2012-01-01

    Our first focus is prediction of a categorical response variable using features that lie on a general manifold. For example, the manifold may correspond to the surface of a hypersphere. We propose a general kernel mixture model for the joint distribution of the response and predictors, with the kernel expressed in product form and dependence induced through the unknown mixing measure. We provide simple sufficient conditions for large support and weak and strong posterior consistency in estimating both the joint distribution of the response and predictors and the conditional distribution of the response. Focusing on a Dirichlet process prior for the mixing measure, these conditions hold using von Mises-Fisher kernels when the manifold is the unit hypersphere. In this case, Bayesian methods are developed for efficient posterior computation using slice sampling. Next we develop Bayesian nonparametric methods for testing whether there is a difference in distributions between groups of observations on the manifold having unknown densities. We prove consistency of the Bayes factor and develop efficient computational methods for its calculation. The proposed classification and testing methods are evaluated using simulation examples and applied to spherical data applications. PMID:22754028

  6. 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.

  7. Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs

    NARCIS (Netherlands)

    Kuosmanen, T.K.

    2005-01-01

    Environmental Economics and Natural Resources Group at Wageningen University in The Netherlands Weak disposability of outputs means that firms can abate harmful emissions by decreasing the activity level. Modeling weak disposability in nonparametric production analysis has caused some confusion.

  8. Multi-sample nonparametric treatments comparison in medical ...

    African Journals Online (AJOL)

    Multi-sample nonparametric treatments comparison in medical follow-up study with unequal observation processes through simulation and bladder tumour case study. P. L. Tan, N.A. Ibrahim, M.B. Adam, J. Arasan ...

  9. 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

  10. A Car Transportation System in Cooperation by Multiple Mobile Robots for Each Wheel: iCART II

    Science.gov (United States)

    Kashiwazaki, Koshi; Yonezawa, Naoaki; Kosuge, Kazuhiro; Sugahara, Yusuke; Hirata, Yasuhisa; Endo, Mitsuru; Kanbayashi, Takashi; Shinozuka, Hiroyuki; Suzuki, Koki; Ono, Yuki

    The authors proposed a car transportation system, iCART (intelligent Cooperative Autonomous Robot Transporters), for automation of mechanical parking systems by two mobile robots. However, it was difficult to downsize the mobile robot because the length of it requires at least the wheelbase of a car. This paper proposes a new car transportation system, iCART II (iCART - type II), based on “a-robot-for-a-wheel” concept. A prototype system, MRWheel (a Mobile Robot for a Wheel), is designed and downsized less than half the conventional robot. First, a method for lifting up a wheel by MRWheel is described. In general, it is very difficult for mobile robots such as MRWheel to move to desired positions without motion errors caused by slipping, etc. Therefore, we propose a follower's motion error estimation algorithm based on the internal force applied to each follower by extending a conventional leader-follower type decentralized control algorithm for cooperative object transportation. The proposed algorithm enables followers to estimate their motion errors and enables the robots to transport a car to a desired position. In addition, we analyze and prove the stability and convergence of the resultant system with the proposed algorithm. In order to extract only the internal force from the force applied to each robot, we also propose a model-based external force compensation method. Finally, proposed methods are applied to the car transportation system, the experimental results confirm their validity.

  11. Nonparametric predictive inference for combining diagnostic tests with parametric copula

    Science.gov (United States)

    Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.

    2017-09-01

    Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.

  12. Bayesian nonparametric clustering in phylogenetics: modeling antigenic evolution in influenza.

    Science.gov (United States)

    Cybis, Gabriela B; Sinsheimer, Janet S; Bedford, Trevor; Rambaut, Andrew; Lemey, Philippe; Suchard, Marc A

    2018-01-30

    Influenza is responsible for up to 500,000 deaths every year, and antigenic variability represents much of its epidemiological burden. To visualize antigenic differences across many viral strains, antigenic cartography methods use multidimensional scaling on binding assay data to map influenza antigenicity onto a low-dimensional space. Analysis of such assay data ideally leads to natural clustering of influenza strains of similar antigenicity that correlate with sequence evolution. To understand the dynamics of these antigenic groups, we present a framework that jointly models genetic and antigenic evolution by combining multidimensional scaling of binding assay data, Bayesian phylogenetic machinery and nonparametric clustering methods. We propose a phylogenetic Chinese restaurant process that extends the current process to incorporate the phylogenetic dependency structure between strains in the modeling of antigenic clusters. With this method, we are able to use the genetic information to better understand the evolution of antigenicity throughout epidemics, as shown in applications of this model to H1N1 influenza. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  13. On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests

    Directory of Open Access Journals (Sweden)

    Aaditya Ramdas

    2017-01-01

    Full Text Available Nonparametric two-sample or homogeneity testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. The literature is old and rich, with a wide variety of statistics having being designed and analyzed, both for the unidimensional and the multivariate setting. Inthisshortsurvey,wefocusonteststatisticsthatinvolvetheWassersteindistance. Usingan entropic smoothing of the Wasserstein distance, we connect these to very different tests including multivariate methods involving energy statistics and kernel based maximum mean discrepancy and univariate methods like the Kolmogorov–Smirnov test, probability or quantile (PP/QQ plots and receiver operating characteristic or ordinal dominance (ROC/ODC curves. Some observations are implicit in the literature, while others seem to have not been noticed thus far. Given nonparametric two-sample testing’s classical and continued importance, we aim to provide useful connections for theorists and practitioners familiar with one subset of methods but not others.

  14. Multinomial Response Models, for Modeling and Determining Important Factors in Different Contraceptive Methods in Women

    Directory of Open Access Journals (Sweden)

    E Haji Nejad

    2001-06-01

    Full Text Available Difference aspects of multinomial statistical modelings and its classifications has been studied so far. In these type of problems Y is the qualitative random variable with T possible states which are considered as classifications. The goal is prediction of Y based on a random Vector X ? IR^m. Many methods for analyzing these problems were considered. One of the modern and general method of classification is Classification and Regression Trees (CART. Another method is recursive partitioning techniques which has a strange relationship with nonparametric regression. Classical discriminant analysis is a standard method for analyzing these type of data. Flexible discriminant analysis method which is a combination of nonparametric regression and discriminant analysis and classification using spline that includes least square regression and additive cubic splines. Neural network is an advanced statistical method for analyzing these types of data. In this paper properties of multinomial logistics regression were investigated and this method was used for modeling effective factors in selecting contraceptive methods in Ghom province for married women age 15-49. The response variable has a tetranomial distibution. The levels of this variable are: nothing, pills, traditional and a collection of other contraceptive methods. A collection of significant independent variables were: place, age of women, education, history of pregnancy and family size. Menstruation age and age at marriage were not statistically significant.

  15. 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.

  16. Non-parametric Bayesian networks: Improving theory and reviewing applications

    International Nuclear Information System (INIS)

    Hanea, Anca; Morales Napoles, Oswaldo; Ababei, Dan

    2015-01-01

    Applications in various domains often lead to high dimensional dependence modelling. A Bayesian network (BN) is a probabilistic graphical model that provides an elegant way of expressing the joint distribution of a large number of interrelated variables. BNs have been successfully used to represent uncertain knowledge in a variety of fields. The majority of applications use discrete BNs, i.e. BNs whose nodes represent discrete variables. Integrating continuous variables in BNs is an area fraught with difficulty. Several methods that handle discrete-continuous BNs have been proposed in the literature. This paper concentrates only on one method called non-parametric BNs (NPBNs). NPBNs were introduced in 2004 and they have been or are currently being used in at least twelve professional applications. This paper provides a short introduction to NPBNs, a couple of theoretical advances, and an overview of applications. The aim of the paper is twofold: one is to present the latest improvements of the theory underlying NPBNs, and the other is to complement the existing overviews of BNs applications with the NPNBs applications. The latter opens the opportunity to discuss some difficulties that applications pose to the theoretical framework and in this way offers some NPBN modelling guidance to practitioners. - Highlights: • The paper gives an overview of the current NPBNs methodology. • We extend the NPBN methodology by relaxing the conditions of one of its fundamental theorems. • We propose improvements of the data mining algorithm for the NPBNs. • We review the professional applications of the NPBNs.

  17. 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.

  18. 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.

  19. Bootstrap Prediction Intervals in Non-Parametric Regression with Applications to Anomaly Detection

    Science.gov (United States)

    Kumar, Sricharan; Srivistava, Ashok N.

    2012-01-01

    Prediction intervals provide a measure of the probable interval in which the outputs of a regression model can be expected to occur. Subsequently, these prediction intervals can be used to determine if the observed output is anomalous or not, conditioned on the input. In this paper, a procedure for determining prediction intervals for outputs of nonparametric regression models using bootstrap methods is proposed. Bootstrap methods allow for a non-parametric approach to computing prediction intervals with no specific assumptions about the sampling distribution of the noise or the data. The asymptotic fidelity of the proposed prediction intervals is theoretically proved. Subsequently, the validity of the bootstrap based prediction intervals is illustrated via simulations. Finally, the bootstrap prediction intervals are applied to the problem of anomaly detection on aviation data.

  20. A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems

    Science.gov (United States)

    Merkatas, Christos; Kaloudis, Konstantinos; Hatjispyros, Spyridon J.

    2017-06-01

    We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods. Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of an arbitrary degree and when a Geometric Stick Breaking mixture process prior over the space of densities, is applied to the additive errors. Our method is parsimonious compared to Bayesian nonparametric techniques based on Dirichlet process mixtures, flexible and general. Simulations based on synthetic time series are presented.

  1. A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems.

    Science.gov (United States)

    Merkatas, Christos; Kaloudis, Konstantinos; Hatjispyros, Spyridon J

    2017-06-01

    We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods. Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of an arbitrary degree and when a Geometric Stick Breaking mixture process prior over the space of densities, is applied to the additive errors. Our method is parsimonious compared to Bayesian nonparametric techniques based on Dirichlet process mixtures, flexible and general. Simulations based on synthetic time series are presented.

  2. 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.

  3. Driving Style Analysis Using Primitive Driving Patterns With Bayesian Nonparametric Approaches

    OpenAIRE

    Wang, Wenshuo; Xi, Junqiang; Zhao, Ding

    2017-01-01

    Analysis and recognition of driving styles are profoundly important to intelligent transportation and vehicle calibration. This paper presents a novel driving style analysis framework using the primitive driving patterns learned from naturalistic driving data. In order to achieve this, first, a Bayesian nonparametric learning method based on a hidden semi-Markov model (HSMM) is introduced to extract primitive driving patterns from time series driving data without prior knowledge of the number...

  4. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

    DEFF Research Database (Denmark)

    Tan, Qihua; Thomassen, Mads; Burton, Mark

    2017-01-01

    the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

  5. A local non-parametric model for trade sign inference

    Science.gov (United States)

    Blazejewski, Adam; Coggins, Richard

    2005-03-01

    We investigate a regularity in market order submission strategies for 12 stocks with large market capitalization on the Australian Stock Exchange. The regularity is evidenced by a predictable relationship between the trade sign (trade initiator), size of the trade, and the contents of the limit order book before the trade. We demonstrate this predictability by developing an empirical inference model to classify trades into buyer-initiated and seller-initiated. The model employs a local non-parametric method, k-nearest neighbor, which in the past was used successfully for chaotic time series prediction. The k-nearest neighbor with three predictor variables achieves an average out-of-sample classification accuracy of 71.40%, compared to 63.32% for the linear logistic regression with seven predictor variables. The result suggests that a non-linear approach may produce a more parsimonious trade sign inference model with a higher out-of-sample classification accuracy. Furthermore, for most of our stocks the observed regularity in market order submissions seems to have a memory of at least 30 trading days.

  6. Bayesian nonparametric meta-analysis using Polya tree mixture models.

    Science.gov (United States)

    Branscum, Adam J; Hanson, Timothy E

    2008-09-01

    Summary. A common goal in meta-analysis is estimation of a single effect measure using data from several studies that are each designed to address the same scientific inquiry. Because studies are typically conducted in geographically disperse locations, recent developments in the statistical analysis of meta-analytic data involve the use of random effects models that account for study-to-study variability attributable to differences in environments, demographics, genetics, and other sources that lead to heterogeneity in populations. Stemming from asymptotic theory, study-specific summary statistics are modeled according to normal distributions with means representing latent true effect measures. A parametric approach subsequently models these latent measures using a normal distribution, which is strictly a convenient modeling assumption absent of theoretical justification. To eliminate the influence of overly restrictive parametric models on inferences, we consider a broader class of random effects distributions. We develop a novel hierarchical Bayesian nonparametric Polya tree mixture (PTM) model. We present methodology for testing the PTM versus a normal random effects model. These methods provide researchers a straightforward approach for conducting a sensitivity analysis of the normality assumption for random effects. An application involving meta-analysis of epidemiologic studies designed to characterize the association between alcohol consumption and breast cancer is presented, which together with results from simulated data highlight the performance of PTMs in the presence of nonnormality of effect measures in the source population.

  7. DPpackage: Bayesian Semi- and Nonparametric Modeling in R

    Directory of Open Access Journals (Sweden)

    Alejandro Jara

    2011-04-01

    Full Text Available Data analysis sometimes requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against mis-specification of the probability model. In the Bayesian context, this is accomplished by placing a prior distribution on a function space, such as the space of all probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function spaces are highly complex and hence sampling methods play a key role. This paper provides an introduction to a simple, yet comprehensive, set of programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently, DPpackage includes models for marginal and conditional density estimation, receiver operating characteristic curve analysis, interval-censored data, binary regression data, item response data, longitudinal and clustered data using generalized linear mixed models, and regression data using generalized additive models. The package also contains functions to compute pseudo-Bayes factors for model comparison and for eliciting the precision parameter of the Dirichlet process prior, and a general purpose Metropolis sampling algorithm. To maximize computational efficiency, the actual sampling for each model is carried out using compiled C, C++ or Fortran code.

  8. 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.

  9. Bayesian nonparametric estimation of continuous monotone functions with applications to dose-response analysis.

    Science.gov (United States)

    Bornkamp, Björn; Ickstadt, Katja

    2009-03-01

    In this article, we consider monotone nonparametric regression in a Bayesian framework. The monotone function is modeled as a mixture of shifted and scaled parametric probability distribution functions, and a general random probability measure is assumed as the prior for the mixing distribution. We investigate the choice of the underlying parametric distribution function and find that the two-sided power distribution function is well suited both from a computational and mathematical point of view. The model is motivated by traditional nonlinear models for dose-response analysis, and provides possibilities to elicitate informative prior distributions on different aspects of the curve. The method is compared with other recent approaches to monotone nonparametric regression in a simulation study and is illustrated on a data set from dose-response analysis.

  10. Promotion time cure rate model with nonparametric form of covariate effects.

    Science.gov (United States)

    Chen, Tianlei; Du, Pang

    2018-05-10

    Survival data with a cured portion are commonly seen in clinical trials. Motivated from a biological interpretation of cancer metastasis, promotion time cure model is a popular alternative to the mixture cure rate model for analyzing such data. The existing promotion cure models all assume a restrictive parametric form of covariate effects, which can be incorrectly specified especially at the exploratory stage. In this paper, we propose a nonparametric approach to modeling the covariate effects under the framework of promotion time cure model. The covariate effect function is estimated by smoothing splines via the optimization of a penalized profile likelihood. Point-wise interval estimates are also derived from the Bayesian interpretation of the penalized profile likelihood. Asymptotic convergence rates are established for the proposed estimates. Simulations show excellent performance of the proposed nonparametric method, which is then applied to a melanoma study. Copyright © 2018 John Wiley & Sons, Ltd.

  11. Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures.

    Science.gov (United States)

    Filippi, Sarah; Holmes, Chris C; Nieto-Barajas, Luis E

    2016-11-16

    In this article we propose novel Bayesian nonparametric methods using Dirichlet Process Mixture (DPM) models for detecting pairwise dependence between random variables while accounting for uncertainty in the form of the underlying distributions. A key criteria is that the procedures should scale to large data sets. In this regard we find that the formal calculation of the Bayes factor for a dependent-vs.-independent DPM joint probability measure is not feasible computationally. To address this we present Bayesian diagnostic measures for characterising evidence against a "null model" of pairwise independence. In simulation studies, as well as for a real data analysis, we show that our approach provides a useful tool for the exploratory nonparametric Bayesian analysis of large multivariate data sets.

  12. A multitemporal and non-parametric approach for assessing the impacts of drought on vegetation greenness

    DEFF Research Database (Denmark)

    Carrao, Hugo; Sepulcre, Guadalupe; Horion, Stéphanie Marie Anne F

    2013-01-01

    This study evaluates the relationship between the frequency and duration of meteorological droughts and the subsequent temporal changes on the quantity of actively photosynthesizing biomass (greenness) estimated from satellite imagery on rainfed croplands in Latin America. An innovative non-parametric...... and non-supervised approach, based on the Fisher-Jenks optimal classification algorithm, is used to identify multi-scale meteorological droughts on the basis of empirical cumulative distributions of 1, 3, 6, and 12-monthly precipitation totals. As input data for the classifier, we use the gridded GPCC...... for the period between 1998 and 2010. The time-series analysis of vegetation greenness is performed during the growing season with a non-parametric method, namely the seasonal Relative Greenness (RG) of spatially accumulated fAPAR. The Global Land Cover map of 2000 and the GlobCover maps of 2005/2006 and 2009...

  13. Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

    Science.gov (United States)

    Schiemann, R.; Erdin, R.; Willi, M.; Frei, C.; Berenguer, M.; Sempere-Torres, D.

    2011-05-01

    Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation

  14. On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

    KAUST Repository

    Dai, Wenlin; Tong, Tiejun; Zhu, Lixing

    2017-01-01

    Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

  15. On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

    KAUST Repository

    Dai, Wenlin

    2017-09-01

    Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

  16. Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

    Directory of Open Access Journals (Sweden)

    Saerom Park

    Full Text Available Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

  17. Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

    Science.gov (United States)

    Park, Saerom; Lee, Jaewook; Son, Youngdoo

    2016-01-01

    Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

  18. 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

  19. 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

  20. 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…

  1. 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.

  2. 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…

  3. 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)

  4. 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.

  5. [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.

  6. 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.

  7. Smooth semi-nonparametric (SNP) estimation of the cumulative incidence function.

    Science.gov (United States)

    Duc, Anh Nguyen; Wolbers, Marcel

    2017-08-15

    This paper presents a novel approach to estimation of the cumulative incidence function in the presence of competing risks. The underlying statistical model is specified via a mixture factorization of the joint distribution of the event type and the time to the event. The time to event distributions conditional on the event type are modeled using smooth semi-nonparametric densities. One strength of this approach is that it can handle arbitrary censoring and truncation while relying on mild parametric assumptions. A stepwise forward algorithm for model estimation and adaptive selection of smooth semi-nonparametric polynomial degrees is presented, implemented in the statistical software R, evaluated in a sequence of simulation studies, and applied to data from a clinical trial in cryptococcal meningitis. The simulations demonstrate that the proposed method frequently outperforms both parametric and nonparametric alternatives. They also support the use of 'ad hoc' asymptotic inference to derive confidence intervals. An extension to regression modeling is also presented, and its potential and challenges are discussed. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

  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. 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

  10. Nonparametric estimation of the heterogeneity of a random medium using compound Poisson process modeling of wave multiple scattering.

    Science.gov (United States)

    Le Bihan, Nicolas; Margerin, Ludovic

    2009-07-01

    In this paper, we present a nonparametric method to estimate the heterogeneity of a random medium from the angular distribution of intensity of waves transmitted through a slab of random material. Our approach is based on the modeling of forward multiple scattering using compound Poisson processes on compact Lie groups. The estimation technique is validated through numerical simulations based on radiative transfer theory.

  11. 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 ...

  12. 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.

  13. Adaptive nonparametric Bayesian inference using location-scale mixture priors

    NARCIS (Netherlands)

    Jonge, de R.; Zanten, van J.H.

    2010-01-01

    We study location-scale mixture priors for nonparametric statistical problems, including multivariate regression, density estimation and classification. We show that a rate-adaptive procedure can be obtained if the prior is properly constructed. In particular, we show that adaptation is achieved if

  14. The nonparametric bootstrap for the current status model

    NARCIS (Netherlands)

    Groeneboom, P.; Hendrickx, K.

    2017-01-01

    It has been proved that direct bootstrapping of the nonparametric maximum likelihood estimator (MLE) of the distribution function in the current status model leads to inconsistent confidence intervals. We show that bootstrapping of functionals of the MLE can however be used to produce valid

  15. Non-Parametric Analysis of Rating Transition and Default Data

    DEFF Research Database (Denmark)

    Fledelius, Peter; Lando, David; Perch Nielsen, Jens

    2004-01-01

    We demonstrate the use of non-parametric intensity estimation - including construction of pointwise confidence sets - for analyzing rating transition data. We find that transition intensities away from the class studied here for illustration strongly depend on the direction of the previous move b...

  16. Bayesian nonparametric system reliability using sets of priors

    NARCIS (Netherlands)

    Walter, G.M.; Aslett, L.J.M.; Coolen, F.P.A.

    2016-01-01

    An imprecise Bayesian nonparametric approach to system reliability with multiple types of components is developed. This allows modelling partial or imperfect prior knowledge on component failure distributions in a flexible way through bounds on the functioning probability. Given component level test

  17. Nonparametric modeling of dynamic functional connectivity in fmri data

    DEFF Research Database (Denmark)

    Nielsen, Søren Føns Vind; Madsen, Kristoffer H.; Røge, Rasmus

    2015-01-01

    dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a nonparametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted...

  18. Parametric vs. Nonparametric Regression Modelling within Clinical Decision Support

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    2017-01-01

    Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability

  19. On the robust nonparametric regression estimation for a functional regressor

    OpenAIRE

    Azzedine , Nadjia; Laksaci , Ali; Ould-Saïd , Elias

    2009-01-01

    On the robust nonparametric regression estimation for a functional regressor correspondance: Corresponding author. (Ould-Said, Elias) (Azzedine, Nadjia) (Laksaci, Ali) (Ould-Said, Elias) Departement de Mathematiques--> , Univ. Djillali Liabes--> , BP 89--> , 22000 Sidi Bel Abbes--> - ALGERIA (Azzedine, Nadjia) Departement de Mathema...

  20. Non-parametric analysis of production efficiency of poultry egg ...

    African Journals Online (AJOL)

    Non-parametric analysis of production efficiency of poultry egg farmers in Delta ... analysis of factors affecting the output of poultry farmers showed that stock ... should be put in place for farmers to learn the best farm practices carried out on the ...

  1. Nonparametric, Coupled ,Bayesian ,Dictionary ,and Classifier Learning for Hyperspectral Classification.

    Science.gov (United States)

    Akhtar, Naveed; Mian, Ajmal

    2017-10-03

    We present a principled approach to learn a discriminative dictionary along a linear classifier for hyperspectral classification. Our approach places Gaussian Process priors over the dictionary to account for the relative smoothness of the natural spectra, whereas the classifier parameters are sampled from multivariate Gaussians. We employ two Beta-Bernoulli processes to jointly infer the dictionary and the classifier. These processes are coupled under the same sets of Bernoulli distributions. In our approach, these distributions signify the frequency of the dictionary atom usage in representing class-specific training spectra, which also makes the dictionary discriminative. Due to the coupling between the dictionary and the classifier, the popularity of the atoms for representing different classes gets encoded into the classifier. This helps in predicting the class labels of test spectra that are first represented over the dictionary by solving a simultaneous sparse optimization problem. The labels of the spectra are predicted by feeding the resulting representations to the classifier. Our approach exploits the nonparametric Bayesian framework to automatically infer the dictionary size--the key parameter in discriminative dictionary learning. Moreover, it also has the desirable property of adaptively learning the association between the dictionary atoms and the class labels by itself. We use Gibbs sampling to infer the posterior probability distributions over the dictionary and the classifier under the proposed model, for which, we derive analytical expressions. To establish the effectiveness of our approach, we test it on benchmark hyperspectral images. The classification performance is compared with the state-of-the-art dictionary learning-based classification methods.

  2. Nonhomogeneous Poisson process with nonparametric frailty

    International Nuclear Information System (INIS)

    Slimacek, Vaclav; Lindqvist, Bo Henry

    2016-01-01

    The failure processes of heterogeneous repairable systems are often modeled by non-homogeneous Poisson processes. The common way to describe an unobserved heterogeneity between systems is to multiply the basic rate of occurrence of failures by a random variable (a so-called frailty) having a specified parametric distribution. Since the frailty is unobservable, the choice of its distribution is a problematic part of using these models, as are often the numerical computations needed in the estimation of these models. The main purpose of this paper is to develop a method for estimation of the parameters of a nonhomogeneous Poisson process with unobserved heterogeneity which does not require parametric assumptions about the heterogeneity and which avoids the frequently encountered numerical problems associated with the standard models for unobserved heterogeneity. The introduced method is illustrated on an example involving the power law process, and is compared to the standard gamma frailty model and to the classical model without unobserved heterogeneity. The derived results are confirmed in a simulation study which also reveals several not commonly known properties of the gamma frailty model and the classical model, and on a real life example. - Highlights: • A new method for estimation of a NHPP with frailty is introduced. • Introduced method does not require parametric assumptions about frailty. • The approach is illustrated on an example with the power law process. • The method is compared to the gamma frailty model and to the model without frailty.

  3. 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.

  4. Transformation-invariant and nonparametric monotone smooth estimation of ROC curves.

    Science.gov (United States)

    Du, Pang; Tang, Liansheng

    2009-01-30

    When a new diagnostic test is developed, it is of interest to evaluate its accuracy in distinguishing diseased subjects from non-diseased subjects. The accuracy of the test is often evaluated by receiver operating characteristic (ROC) curves. Smooth ROC estimates are often preferable for continuous test results when the underlying ROC curves are in fact continuous. Nonparametric and parametric methods have been proposed by various authors to obtain smooth ROC curve estimates. However, there are certain drawbacks with the existing methods. Parametric methods need specific model assumptions. Nonparametric methods do not always satisfy the inherent properties of the ROC curves, such as monotonicity and transformation invariance. In this paper we propose a monotone spline approach to obtain smooth monotone ROC curves. Our method ensures important inherent properties of the underlying ROC curves, which include monotonicity, transformation invariance, and boundary constraints. We compare the finite sample performance of the newly proposed ROC method with other ROC smoothing methods in large-scale simulation studies. We illustrate our method through a real life example. Copyright (c) 2008 John Wiley & Sons, Ltd.

  5. 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.

  6. 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.

  7. Non-parametric system identification from non-linear stochastic response

    DEFF Research Database (Denmark)

    Rüdinger, Finn; Krenk, Steen

    2001-01-01

    An estimation method is proposed for identification of non-linear stiffness and damping of single-degree-of-freedom systems under stationary white noise excitation. Non-parametric estimates of the stiffness and damping along with an estimate of the white noise intensity are obtained by suitable...... of the energy at mean-level crossings, which yields the damping relative to white noise intensity. Finally, an estimate of the noise intensity is extracted by estimating the absolute damping from the autocovariance functions of a set of modified phase plane variables at different energy levels. The method...

  8. Efficient nonparametric estimation of causal mediation effects

    OpenAIRE

    Chan, K. C. G.; Imai, K.; Yam, S. C. P.; Zhang, Z.

    2016-01-01

    An essential goal of program evaluation and scientific research is the investigation of causal mechanisms. Over the past several decades, causal mediation analysis has been used in medical and social sciences to decompose the treatment effect into the natural direct and indirect effects. However, all of the existing mediation analysis methods rely on parametric modeling assumptions in one way or another, typically requiring researchers to specify multiple regression models involving the treat...

  9. A nonparametric approach to forecasting realized volatility

    OpenAIRE

    Adam Clements; Ralf Becker

    2009-01-01

    A well developed literature exists in relation to modeling and forecasting asset return volatility. Much of this relate to the development of time series models of volatility. This paper proposes an alternative method for forecasting volatility that does not involve such a model. Under this approach a forecast is a weighted average of historical volatility. The greatest weight is given to periods that exhibit the most similar market conditions to the time at which the forecast is being formed...

  10. 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.

  11. 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.

  12. Testing for constant nonparametric effects in general semiparametric regression models with interactions

    KAUST Repository

    Wei, Jiawei; Carroll, Raymond J.; Maity, Arnab

    2011-01-01

    We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work

  13. High throughput nonparametric probability density estimation.

    Science.gov (United States)

    Farmer, Jenny; Jacobs, Donald

    2018-01-01

    In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.

  14. 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

  15. Nonparametric Collective Spectral Density Estimation and Clustering

    KAUST Repository

    Maadooliat, Mehdi

    2017-04-12

    In this paper, we develop a method for the simultaneous estimation of spectral density functions (SDFs) for a collection of stationary time series that share some common features. Due to the similarities among the SDFs, the log-SDF can be represented using a common set of basis functions. The basis shared by the collection of the log-SDFs is estimated as a low-dimensional manifold of a large space spanned by a pre-specified rich basis. A collective estimation approach pools information and borrows strength across the SDFs to achieve better estimation efficiency. Also, each estimated spectral density has a concise representation using the coefficients of the basis expansion, and these coefficients can be used for visualization, clustering, and classification purposes. The Whittle pseudo-maximum likelihood approach is used to fit the model and an alternating blockwise Newton-type algorithm is developed for the computation. A web-based shiny App found at

  16. Nonparametric Collective Spectral Density Estimation and Clustering

    KAUST Repository

    Maadooliat, Mehdi; Sun, Ying; Chen, Tianbo

    2017-01-01

    In this paper, we develop a method for the simultaneous estimation of spectral density functions (SDFs) for a collection of stationary time series that share some common features. Due to the similarities among the SDFs, the log-SDF can be represented using a common set of basis functions. The basis shared by the collection of the log-SDFs is estimated as a low-dimensional manifold of a large space spanned by a pre-specified rich basis. A collective estimation approach pools information and borrows strength across the SDFs to achieve better estimation efficiency. Also, each estimated spectral density has a concise representation using the coefficients of the basis expansion, and these coefficients can be used for visualization, clustering, and classification purposes. The Whittle pseudo-maximum likelihood approach is used to fit the model and an alternating blockwise Newton-type algorithm is developed for the computation. A web-based shiny App found at

  17. Nonparametric additive regression for repeatedly measured data

    KAUST Repository

    Carroll, R. J.

    2009-05-20

    We develop an easily computed smooth backfitting algorithm for additive model fitting in repeated measures problems. Our methodology easily copes with various settings, such as when some covariates are the same over repeated response measurements. We allow for a working covariance matrix for the regression errors, showing that our method is most efficient when the correct covariance matrix is used. The component functions achieve the known asymptotic variance lower bound for the scalar argument case. Smooth backfitting also leads directly to design-independent biases in the local linear case. Simulations show our estimator has smaller variance than the usual kernel estimator. This is also illustrated by an example from nutritional epidemiology. © 2009 Biometrika Trust.

  18. Nonparametric Bayesian models for a spatial covariance.

    Science.gov (United States)

    Reich, Brian J; Fuentes, Montserrat

    2012-01-01

    A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.

  19. Nonparametric instrumental regression with non-convex constraints

    International Nuclear Information System (INIS)

    Grasmair, M; Scherzer, O; Vanhems, A

    2013-01-01

    This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition. (paper)

  20. Nonparametric instrumental regression with non-convex constraints

    Science.gov (United States)

    Grasmair, M.; Scherzer, O.; Vanhems, A.

    2013-03-01

    This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition.

  1. Nonparametric Bayesian models through probit stick-breaking processes.

    Science.gov (United States)

    Rodríguez, Abel; Dunson, David B

    2011-03-01

    We describe a novel class of Bayesian nonparametric priors based on stick-breaking constructions where the weights of the process are constructed as probit transformations of normal random variables. We show that these priors are extremely flexible, allowing us to generate a great variety of models while preserving computational simplicity. Particular emphasis is placed on the construction of rich temporal and spatial processes, which are applied to two problems in finance and ecology.

  2. Exact nonparametric inference for detection of nonlinear determinism

    OpenAIRE

    Luo, Xiaodong; Zhang, Jie; Small, Michael; Moroz, Irene

    2005-01-01

    We propose an exact nonparametric inference scheme for the detection of nonlinear determinism. The essential fact utilized in our scheme is that, for a linear stochastic process with jointly symmetric innovations, its ordinary least square (OLS) linear prediction error is symmetric about zero. Based on this viewpoint, a class of linear signed rank statistics, e.g. the Wilcoxon signed rank statistic, can be derived with the known null distributions from the prediction error. Thus one of the ad...

  3. Nonparametric bootstrap analysis with applications to demographic effects in demand functions.

    Science.gov (United States)

    Gozalo, P L

    1997-12-01

    "A new bootstrap proposal, labeled smooth conditional moment (SCM) bootstrap, is introduced for independent but not necessarily identically distributed data, where the classical bootstrap procedure fails.... A good example of the benefits of using nonparametric and bootstrap methods is the area of empirical demand analysis. In particular, we will be concerned with their application to the study of two important topics: what are the most relevant effects of household demographic variables on demand behavior, and to what extent present parametric specifications capture these effects." excerpt

  4. CATDAT - A program for parametric and nonparametric categorical data analysis user's manual, Version 1.0

    International Nuclear Information System (INIS)

    Peterson, James R.; Haas, Timothy C.; Lee, Danny C.

    2000-01-01

    Natural resource professionals are increasingly required to develop rigorous statistical models that relate environmental data to categorical responses data. Recent advances in the statistical and computing sciences have led to the development of sophisticated methods for parametric and nonparametric analysis of data with categorical responses. The statistical software package CATDAT was designed to make some of these relatively new and powerful techniques available to scientists. The CATDAT statistical package includes 4 analytical techniques: generalized logit modeling; binary classification tree; extended K-nearest neighbor classification; and modular neural network

  5. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

    Science.gov (United States)

    Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

    2017-06-06

    Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. An adaptive distance measure for use with nonparametric models

    International Nuclear Information System (INIS)

    Garvey, D. R.; Hines, J. W.

    2006-01-01

    Distance measures perform a critical task in nonparametric, locally weighted regression. Locally weighted regression (LWR) models are a form of 'lazy learning' which construct a local model 'on the fly' by comparing a query vector to historical, exemplar vectors according to a three step process. First, the distance of the query vector to each of the exemplar vectors is calculated. Next, these distances are passed to a kernel function, which converts the distances to similarities or weights. Finally, the model output or response is calculated by performing locally weighted polynomial regression. To date, traditional distance measures, such as the Euclidean, weighted Euclidean, and L1-norm have been used as the first step in the prediction process. Since these measures do not take into consideration sensor failures and drift, they are inherently ill-suited for application to 'real world' systems. This paper describes one such LWR model, namely auto associative kernel regression (AAKR), and describes a new, Adaptive Euclidean distance measure that can be used to dynamically compensate for faulty sensor inputs. In this new distance measure, the query observations that lie outside of the training range (i.e. outside the minimum and maximum input exemplars) are dropped from the distance calculation. This allows for the distance calculation to be robust to sensor drifts and failures, in addition to providing a method for managing inputs that exceed the training range. In this paper, AAKR models using the standard and Adaptive Euclidean distance are developed and compared for the pressure system of an operating nuclear power plant. It is shown that using the standard Euclidean distance for data with failed inputs, significant errors in the AAKR predictions can result. By using the Adaptive Euclidean distance it is shown that high fidelity predictions are possible, in spite of the input failure. In fact, it is shown that with the Adaptive Euclidean distance prediction

  11. Nonparametric estimation for censored mixture data with application to the Cooperative Huntington's Observational Research Trial.

    Science.gov (United States)

    Wang, Yuanjia; Garcia, Tanya P; Ma, Yanyuan

    2012-01-01

    This work presents methods for estimating genotype-specific distributions from genetic epidemiology studies where the event times are subject to right censoring, the genotypes are not directly observed, and the data arise from a mixture of scientifically meaningful subpopulations. Examples of such studies include kin-cohort studies and quantitative trait locus (QTL) studies. Current methods for analyzing censored mixture data include two types of nonparametric maximum likelihood estimators (NPMLEs) which do not make parametric assumptions on the genotype-specific density functions. Although both NPMLEs are commonly used, we show that one is inefficient and the other inconsistent. To overcome these deficiencies, we propose three classes of consistent nonparametric estimators which do not assume parametric density models and are easy to implement. They are based on the inverse probability weighting (IPW), augmented IPW (AIPW), and nonparametric imputation (IMP). The AIPW achieves the efficiency bound without additional modeling assumptions. Extensive simulation experiments demonstrate satisfactory performance of these estimators even when the data are heavily censored. We apply these estimators to the Cooperative Huntington's Observational Research Trial (COHORT), and provide age-specific estimates of the effect of mutation in the Huntington gene on mortality using a sample of family members. The close approximation of the estimated non-carrier survival rates to that of the U.S. population indicates small ascertainment bias in the COHORT family sample. Our analyses underscore an elevated risk of death in Huntington gene mutation carriers compared to non-carriers for a wide age range, and suggest that the mutation equally affects survival rates in both genders. The estimated survival rates are useful in genetic counseling for providing guidelines on interpreting the risk of death associated with a positive genetic testing, and in facilitating future subjects at risk

  12. Comparative analysis of automotive paints by laser induced breakdown spectroscopy and nonparametric permutation tests

    International Nuclear Information System (INIS)

    McIntee, Erin; Viglino, Emilie; Rinke, Caitlin; Kumor, Stephanie; Ni Liqiang; Sigman, Michael E.

    2010-01-01

    Laser-induced breakdown spectroscopy (LIBS) has been investigated for the discrimination of automobile paint samples. Paint samples from automobiles of different makes, models, and years were collected and separated into sets based on the color, presence or absence of effect pigments and the number of paint layers. Twelve LIBS spectra were obtained for each paint sample, each an average of a five single shot 'drill down' spectra from consecutive laser ablations in the same spot on the sample. Analyses by a nonparametric permutation test and a parametric Wald test were performed to determine the extent of discrimination within each set of paint samples. The discrimination power and Type I error were assessed for each data analysis method. Conversion of the spectral intensity to a log-scale (base 10) resulted in a higher overall discrimination power while observing the same significance level. Working on the log-scale, the nonparametric permutation tests gave an overall 89.83% discrimination power with a size of Type I error being 4.44% at the nominal significance level of 5%. White paint samples, as a group, were the most difficult to differentiate with the power being only 86.56% followed by 95.83% for black paint samples. Parametric analysis of the data set produced lower discrimination (85.17%) with 3.33% Type I errors, which is not recommended for both theoretical and practical considerations. The nonparametric testing method is applicable across many analytical comparisons, with the specific application described here being the pairwise comparison of automotive paint samples.

  13. 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.

  14. 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...

  15. 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

  16. 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

  17. 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.

  18. 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)

  19. 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.

  20. 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.

  1. 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?

  2. Nonparametric estimation of age-specific reference percentile curves with radial smoothing.

    Science.gov (United States)

    Wan, Xiaohai; Qu, Yongming; Huang, Yao; Zhang, Xiao; Song, Hanping; Jiang, Honghua

    2012-01-01

    Reference percentile curves represent the covariate-dependent distribution of a quantitative measurement and are often used to summarize and monitor dynamic processes such as human growth. We propose a new nonparametric method based on a radial smoothing (RS) technique to estimate age-specific reference percentile curves assuming the underlying distribution is relatively close to normal. We compared the RS method with both the LMS and the generalized additive models for location, scale and shape (GAMLSS) methods using simulated data and found that our method has smaller estimation error than the two existing methods. We also applied the new method to analyze height growth data from children being followed in a clinical observational study of growth hormone treatment, and compared the growth curves between those with growth disorders and the general population. Copyright © 2011 Elsevier Inc. All rights reserved.

  3. Injerto columelar extendido angulado. Método para prevenir la rotación cefálica y lateral de los injertos de cartílago en la punta nasal Angulated extended collumelar graft. A method to prevent the cephalic and lateral rotation of the cartilage graft in the nasal tip

    Directory of Open Access Journals (Sweden)

    Y. Castro Govea

    2011-06-01

    Full Text Available El paciente mestizo generalmente posee una nariz pequeña, de base ancha, con fosas nasales redondas y dorso convexo. Los cartílagos alares son débiles, delgados y cortos, proporcionando un soporte estructural deficiente y pobre definición de la punta nasal. Los injertos de cartílago de la punta nasal se usan frecuentemente para corregir esta condición; sin embargo un problema común es la rotación cefálica, caudal y lateral de estos cartílagos. Empleamos un injerto columelar extendido angulado (ICEA para proporcionar elongación y soporte columelar; la extensión angulada nos brinda a su vez un mejor control y predicción de la posición de los injertos de la punta nasal al prevenir su desplazamiento cefálico y lateral. El protocolo quirúrgico empleado incluyó historia clínica completa, desarrollo de un plan quirúrgico mediante análisis de la deformidad y fotografías pre y postoperatorias para el control de los pacientes a medio y largo plazo. Tratamos 95 pacientes usando este procedimiento; 75 con rinoplastia abierta y 20 con técnica cerrada. El rango del periodo de seguimiento fue de 6 meses a 4 años. Los resultados obtenidos fueron satisfactorios, mostrando mejor control y predicción de la forma de la punta nasal. En conclusión, creemos que el injerto columelar extendido angulado proporciona un mejor control de la proyección y angularidad de los injertos colocados en la punta nasal.The mestizo patient usually has a small nose, with wide base, round nostrils and convex dorsum. The alar cartilages are weak, thin and short, providing a deficient structural support and poor definition of the nasal tip. Cartilage graft in the nasal tip are very often used to correct this condition, but a commun problem of this procedure is the cephalic or lateral rotation of these grafts. We used an angulated extended collumalar graft to give collumelar support and elongation. The angulated extension of the graft provides a better control and

  4. 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.

  5. A semi-nonparametric mixture model for selecting functionally consistent proteins.

    Science.gov (United States)

    Yu, Lianbo; Doerge, Rw

    2010-09-28

    High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

  6. Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

    Science.gov (United States)

    Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

    We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

  7. Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

    Science.gov (United States)

    Curceac, S.; Ternynck, C.; Ouarda, T.

    2015-12-01

    Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

  8. Does less frequent routine monitoring of patients on a stable, fully suppressed cART regimen lead to an increased risk of treatment failure?

    DEFF Research Database (Denmark)

    Reekie, Joanne; Mocroft, Amanda; Sambatakou, Helen

    2008-01-01

    SIDA study who maintained a stable and fully suppressed cART regimen for 1 year were included in the analysis. METHODS: Risk of treatment failure, defined by viral rebound, fall in CD4 cell count, development of new AIDS-defining illness, serious opportunistic infection or death, in the 12 months following...... interval (CI) 0.1-0.5], 2.2% (95% CI 1.6-2.8) and 6.0% (95% CI 5.0-7.0) risk of treatment failure, respectively. Patients who spent more than 80% of their time on cART with fully suppressed viraemia prior to baseline had a 38% reduced risk of treatment failure, hazard ratio 0.62 (95% CI 0.42-0.90, P = 0...

  9. 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

  10. kruX: matrix-based non-parametric eQTL discovery.

    Science.gov (United States)

    Qi, Jianlong; Asl, Hassan Foroughi; Björkegren, Johan; Michoel, Tom

    2014-01-14

    The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com.

  11. Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements

    KAUST Repository

    Ryu, Duchwan

    2010-09-28

    We consider nonparametric regression analysis in a generalized linear model (GLM) framework for data with covariates that are the subject-specific random effects of longitudinal measurements. The usual assumption that the effects of the longitudinal covariate processes are linear in the GLM may be unrealistic and if this happens it can cast doubt on the inference of observed covariate effects. Allowing the regression functions to be unknown, we propose to apply Bayesian nonparametric methods including cubic smoothing splines or P-splines for the possible nonlinearity and use an additive model in this complex setting. To improve computational efficiency, we propose the use of data-augmentation schemes. The approach allows flexible covariance structures for the random effects and within-subject measurement errors of the longitudinal processes. The posterior model space is explored through a Markov chain Monte Carlo (MCMC) sampler. The proposed methods are illustrated and compared to other approaches, the "naive" approach and the regression calibration, via simulations and by an application that investigates the relationship between obesity in adulthood and childhood growth curves. © 2010, The International Biometric Society.

  12. 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.

  13. A Nonparametric Bayesian Approach For Emission Tomography Reconstruction

    International Nuclear Information System (INIS)

    Barat, Eric; Dautremer, Thomas

    2007-01-01

    We introduce a PET reconstruction algorithm following a nonparametric Bayesian (NPB) approach. In contrast with Expectation Maximization (EM), the proposed technique does not rely on any space discretization. Namely, the activity distribution--normalized emission intensity of the spatial poisson process--is considered as a spatial probability density and observations are the projections of random emissions whose distribution has to be estimated. This approach is nonparametric in the sense that the quantity of interest belongs to the set of probability measures on R k (for reconstruction in k-dimensions) and it is Bayesian in the sense that we define a prior directly on this spatial measure. In this context, we propose to model the nonparametric probability density as an infinite mixture of multivariate normal distributions. As a prior for this mixture we consider a Dirichlet Process Mixture (DPM) with a Normal-Inverse Wishart (NIW) model as base distribution of the Dirichlet Process. As in EM-family reconstruction, we use a data augmentation scheme where the set of hidden variables are the emission locations for each observed line of response in the continuous object space. Thanks to the data augmentation, we propose a Markov Chain Monte Carlo (MCMC) algorithm (Gibbs sampler) which is able to generate draws from the posterior distribution of the spatial intensity. A difference with EM is that one step of the Gibbs sampler corresponds to the generation of emission locations while only the expected number of emissions per pixel/voxel is used in EM. Another key difference is that the estimated spatial intensity is a continuous function such that there is no need to compute a projection matrix. Finally, draws from the intensity posterior distribution allow the estimation of posterior functionnals like the variance or confidence intervals. Results are presented for simulated data based on a 2D brain phantom and compared to Bayesian MAP-EM

  14. Panel data nonparametric estimation of production risk and risk preferences

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    approaches for obtaining firm-specific measures of risk attitudes. We found that Polish dairy farmers are risk averse regarding production risk and price uncertainty. According to our results, Polish dairy farmers perceive the production risk as being more significant than the risk related to output price......We apply nonparametric panel data kernel regression to investigate production risk, out-put price uncertainty, and risk attitudes of Polish dairy farms based on a firm-level unbalanced panel data set that covers the period 2004–2010. We compare different model specifications and different...

  15. A Bayesian nonparametric approach to causal inference on quantiles.

    Science.gov (United States)

    Xu, Dandan; Daniels, Michael J; Winterstein, Almut G

    2018-02-25

    We propose a Bayesian nonparametric approach (BNP) for causal inference on quantiles in the presence of many confounders. In particular, we define relevant causal quantities and specify BNP models to avoid bias from restrictive parametric assumptions. We first use Bayesian additive regression trees (BART) to model the propensity score and then construct the distribution of potential outcomes given the propensity score using a Dirichlet process mixture (DPM) of normals model. We thoroughly evaluate the operating characteristics of our approach and compare it to Bayesian and frequentist competitors. We use our approach to answer an important clinical question involving acute kidney injury using electronic health records. © 2018, The International Biometric Society.

  16. Categorical and nonparametric data analysis choosing the best statistical technique

    CERN Document Server

    Nussbaum, E Michael

    2014-01-01

    Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain

  17. Nonparametric statistics a step-by-step approach

    CERN Document Server

    Corder, Gregory W

    2014-01-01

    "…a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory.  It also deserves a place in libraries of all institutions where introductory statistics courses are taught."" -CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical powerSPSS® (Version 21) software and updated screen ca

  18. Estimation of Stochastic Volatility Models by Nonparametric Filtering

    DEFF Research Database (Denmark)

    Kanaya, Shin; Kristensen, Dennis

    2016-01-01

    /estimated volatility process replacing the latent process. Our estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps and market microstructure noise. The resulting estimators of the stochastic volatility model will carry additional biases...... and variances due to the first-step estimation, but under regularity conditions we show that these vanish asymptotically and our estimators inherit the asymptotic properties of the infeasible estimators based on observations of the volatility process. A simulation study examines the finite-sample properties...

  19. 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

  20. 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

  1. Nonparametric Identification of Glucose-Insulin Process in IDDM Patient with Multi-meal Disturbance

    Science.gov (United States)

    Bhattacharjee, A.; Sutradhar, A.

    2012-12-01

    Modern close loop control for blood glucose level in a diabetic patient necessarily uses an explicit model of the process. A fixed parameter full order or reduced order model does not characterize the inter-patient and intra-patient parameter variability. This paper deals with a frequency domain nonparametric identification of the nonlinear glucose-insulin process in an insulin dependent diabetes mellitus patient that captures the process dynamics in presence of uncertainties and parameter variations. An online frequency domain kernel estimation method has been proposed that uses the input-output data from the 19th order first principle model of the patient in intravenous route. Volterra equations up to second order kernels with extended input vector for a Hammerstein model are solved online by adaptive recursive least square (ARLS) algorithm. The frequency domain kernels are estimated using the harmonic excitation input data sequence from the virtual patient model. A short filter memory length of M = 2 was found sufficient to yield acceptable accuracy with lesser computation time. The nonparametric models are useful for closed loop control, where the frequency domain kernels can be directly used as the transfer function. The validation results show good fit both in frequency and time domain responses with nominal patient as well as with parameter variations.

  2. Non-parametric transformation for data correlation and integration: From theory to practice

    Energy Technology Data Exchange (ETDEWEB)

    Datta-Gupta, A.; Xue, Guoping; Lee, Sang Heon [Texas A& M Univ., College Station, TX (United States)

    1997-08-01

    The purpose of this paper is two-fold. First, we introduce the use of non-parametric transformations for correlating petrophysical data during reservoir characterization. Such transformations are completely data driven and do not require a priori functional relationship between response and predictor variables which is the case with traditional multiple regression. The transformations are very general, computationally efficient and can easily handle mixed data types for example, continuous variables such as porosity, permeability and categorical variables such as rock type, lithofacies. The power of the non-parametric transformation techniques for data correlation has been illustrated through synthetic and field examples. Second, we utilize these transformations to propose a two-stage approach for data integration during heterogeneity characterization. The principal advantages of our approach over traditional cokriging or cosimulation methods are: (1) it does not require a linear relationship between primary and secondary data, (2) it exploits the secondary information to its fullest potential by maximizing the correlation between the primary and secondary data, (3) it can be easily applied to cases where several types of secondary or soft data are involved, and (4) it significantly reduces variance function calculations and thus, greatly facilitates non-Gaussian cosimulation. We demonstrate the data integration procedure using synthetic and field examples. The field example involves estimation of pore-footage distribution using well data and multiple seismic attributes.

  3. Bayesian Nonparametric Measurement of Factor Betas and Clustering with Application to Hedge Fund Returns

    Directory of Open Access Journals (Sweden)

    Urbi Garay

    2016-03-01

    Full Text Available We define a dynamic and self-adjusting mixture of Gaussian Graphical Models to cluster financial returns, and provide a new method for extraction of nonparametric estimates of dynamic alphas (excess return and betas (to a choice set of explanatory factors in a multivariate setting. This approach, as well as the outputs, has a dynamic, nonstationary and nonparametric form, which circumvents the problem of model risk and parametric assumptions that the Kalman filter and other widely used approaches rely on. The by-product of clusters, used for shrinkage and information borrowing, can be of use to determine relationships around specific events. This approach exhibits a smaller Root Mean Squared Error than traditionally used benchmarks in financial settings, which we illustrate through simulation. As an illustration, we use hedge fund index data, and find that our estimated alphas are, on average, 0.13% per month higher (1.6% per year than alphas estimated through Ordinary Least Squares. The approach exhibits fast adaptation to abrupt changes in the parameters, as seen in our estimated alphas and betas, which exhibit high volatility, especially in periods which can be identified as times of stressful market events, a reflection of the dynamic positioning of hedge fund portfolio managers.

  4. Bayesian nonparametric inference on quantile residual life function: Application to breast cancer data.

    Science.gov (United States)

    Park, Taeyoung; Jeong, Jong-Hyeon; Lee, Jae Won

    2012-08-15

    There is often an interest in estimating a residual life function as a summary measure of survival data. For ease in presentation of the potential therapeutic effect of a new drug, investigators may summarize survival data in terms of the remaining life years of patients. Under heavy right censoring, however, some reasonably high quantiles (e.g., median) of a residual lifetime distribution cannot be always estimated via a popular nonparametric approach on the basis of the Kaplan-Meier estimator. To overcome the difficulties in dealing with heavily censored survival data, this paper develops a Bayesian nonparametric approach that takes advantage of a fully model-based but highly flexible probabilistic framework. We use a Dirichlet process mixture of Weibull distributions to avoid strong parametric assumptions on the unknown failure time distribution, making it possible to estimate any quantile residual life function under heavy censoring. Posterior computation through Markov chain Monte Carlo is straightforward and efficient because of conjugacy properties and partial collapse. We illustrate the proposed methods by using both simulated data and heavily censored survival data from a recent breast cancer clinical trial conducted by the National Surgical Adjuvant Breast and Bowel Project. Copyright © 2012 John Wiley & Sons, Ltd.

  5. Non-parametric PSF estimation from celestial transit solar images using blind deconvolution

    Directory of Open Access Journals (Sweden)

    González Adriana

    2016-01-01

    Full Text Available Context: Characterization of instrumental effects in astronomical imaging is important in order to extract accurate physical information from the observations. The measured image in a real optical instrument is usually represented by the convolution of an ideal image with a Point Spread Function (PSF. Additionally, the image acquisition process is also contaminated by other sources of noise (read-out, photon-counting. The problem of estimating both the PSF and a denoised image is called blind deconvolution and is ill-posed. Aims: We propose a blind deconvolution scheme that relies on image regularization. Contrarily to most methods presented in the literature, our method does not assume a parametric model of the PSF and can thus be applied to any telescope. Methods: Our scheme uses a wavelet analysis prior model on the image and weak assumptions on the PSF. We use observations from a celestial transit, where the occulting body can be assumed to be a black disk. These constraints allow us to retain meaningful solutions for the filter and the image, eliminating trivial, translated, and interchanged solutions. Under an additive Gaussian noise assumption, they also enforce noise canceling and avoid reconstruction artifacts by promoting the whiteness of the residual between the blurred observations and the cleaned data. Results: Our method is applied to synthetic and experimental data. The PSF is estimated for the SECCHI/EUVI instrument using the 2007 Lunar transit, and for SDO/AIA using the 2012 Venus transit. Results show that the proposed non-parametric blind deconvolution method is able to estimate the core of the PSF with a similar quality to parametric methods proposed in the literature. We also show that, if these parametric estimations are incorporated in the acquisition model, the resulting PSF outperforms both the parametric and non-parametric methods.

  6. 1st Conference of the International Society for Nonparametric Statistics

    CERN Document Server

    Lahiri, S; Politis, Dimitris

    2014-01-01

    This volume is composed of peer-reviewed papers that have developed from the First Conference of the International Society for NonParametric Statistics (ISNPS). This inaugural conference took place in Chalkidiki, Greece, June 15-19, 2012. It was organized with the co-sponsorship of the IMS, the ISI, and other organizations. M.G. Akritas, S.N. Lahiri, and D.N. Politis are the first executive committee members of ISNPS, and the editors of this volume. ISNPS has a distinguished Advisory Committee that includes Professors R.Beran, P.Bickel, R. Carroll, D. Cook, P. Hall, R. Johnson, B. Lindsay, E. Parzen, P. Robinson, M. Rosenblatt, G. Roussas, T. SubbaRao, and G. Wahba. The Charting Committee of ISNPS consists of more than 50 prominent researchers from all over the world.   The chapters in this volume bring forth recent advances and trends in several areas of nonparametric statistics. In this way, the volume facilitates the exchange of research ideas, promotes collaboration among researchers from all over the wo...

  7. 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.

  8. Development of a Childhood Attachment and Relational Trauma Screen (CARTS: a relational-socioecological framework for surveying attachment security and childhood trauma history

    Directory of Open Access Journals (Sweden)

    Paul A. Frewen

    2013-04-01

    Full Text Available Background : Current psychometric measures of childhood trauma history generally fail to assess the relational-socioecological context within which childhood maltreatment occurs, including the relationship of abusers to abused persons, the emotional availability of caregivers, and the respondent's own thoughts, feelings, and actions in response to maltreatment. Objective : To evaluate a computerized approach to measuring the relational-socioecological context within which childhood maltreatment occurs. Method : The psychometric properties of a Childhood Attachment and Relational Trauma Screen (CARTS were evaluated as a retrospective survey of childhood maltreatment history designed to be appropriate for completion by adults. Participants were undergraduates (n=222, an internet sample (n=123, and psychiatric outpatients (n=30. Results : The internal reliability, convergent, and concurrent validity of the CARTS were supported across samples. Paired differences in means and correlations between rated item-descriptiveness to self, mothers, and fathers also accorded with findings of prior attachment and maltreatment research, illustrating the utility of assessing the occurrence and effects of maltreatment within a relational-socioecological framework. Conclusions : Results preliminarily support a new survey methodology for assessing childhood maltreatment within a relational-socioecological framework. Further psychometric evaluation of the CARTS is warranted.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Bacterial Contamination and Disinfection Status of Laryngoscopes Stored in Emergency Crash Carts

    Science.gov (United States)

    Lee, Jung Won; Shin, Hee Bong; Lee, In Kyung

    2017-01-01

    Objectives To identify bacterial contamination rates of laryngoscope blades and handles stored in emergency crash carts by hospital and area according to the frequency of intubation attempts. Methods One hundred forty-eight handles and 71 blades deemed ready for patient use from two tertiary hospitals were sampled with sterile swabs using a standardized rolling technique. Samples were considered negative (not contaminated) if no colonies were present on the blood agar plate after an 18-hour incubation period. Samples were stratified by hospital and according to the frequency of intubation attempts (10 attempts per year) using the χ2-test and Fisher exact test. Results One or more species of bacteria were isolated from 4 (5.6%) handle tops, 20 (28.2%) handles with knurled surfaces, and 27 (18.2%) blades. No significant differences were found in microbial contamination levels on the handle tops and blades between the two hospitals and two areas according to the frequency of intubation attempts. However, significant differences were found between the two hospitals and two areas in the level of microbial contamination on the handles with knurled surfaces (pdisinfect laryngoscope blades and handles; handles should be re-designed to eliminate points of contact with the blade; and single-use, one-piece laryngoscopes should be introduced. PMID:28605891

  16. CADDIS Volume 4. Data Analysis: PECBO Appendix - R Scripts for Non-Parametric Regressions

    Science.gov (United States)

    Script for computing nonparametric regression analysis. Overview of using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, statistical scripts.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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).

  3. 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.

  4. A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS.

    Science.gov (United States)

    Zhao, Yize; Kang, Jian; Yu, Tianwei

    2014-06-01

    It is very challenging to select informative features from tens of thousands of measured features in high-throughput data analysis. Recently, several parametric/regression models have been developed utilizing the gene network information to select genes or pathways strongly associated with a clinical/biological outcome. Alternatively, in this paper, we propose a nonparametric Bayesian model for gene selection incorporating network information. In addition to identifying genes that have a strong association with a clinical outcome, our model can select genes with particular expressional behavior, in which case the regression models are not directly applicable. We show that our proposed model is equivalent to an infinity mixture model for which we develop a posterior computation algorithm based on Markov chain Monte Carlo (MCMC) methods. We also propose two fast computing algorithms that approximate the posterior simulation with good accuracy but relatively low computational cost. We illustrate our methods on simulation studies and the analysis of Spellman yeast cell cycle microarray data.

  5. Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

    Science.gov (United States)

    Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

    2018-03-01

    Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

  6. Gaussian process-based Bayesian nonparametric inference of population size trajectories from gene genealogies.

    Science.gov (United States)

    Palacios, Julia A; Minin, Vladimir N

    2013-03-01

    Changes in population size influence genetic diversity of the population and, as a result, leave a signature of these changes in individual genomes in the population. We are interested in the inverse problem of reconstructing past population dynamics from genomic data. We start with a standard framework based on the coalescent, a stochastic process that generates genealogies connecting randomly sampled individuals from the population of interest. These genealogies serve as a glue between the population demographic history and genomic sequences. It turns out that only the times of genealogical lineage coalescences contain information about population size dynamics. Viewing these coalescent times as a point process, estimating population size trajectories is equivalent to estimating a conditional intensity of this point process. Therefore, our inverse problem is similar to estimating an inhomogeneous Poisson process intensity function. We demonstrate how recent advances in Gaussian process-based nonparametric inference for Poisson processes can be extended to Bayesian nonparametric estimation of population size dynamics under the coalescent. We compare our Gaussian process (GP) approach to one of the state-of-the-art Gaussian Markov random field (GMRF) methods for estimating population trajectories. Using simulated data, we demonstrate that our method has better accuracy and precision. Next, we analyze two genealogies reconstructed from real sequences of hepatitis C and human Influenza A viruses. In both cases, we recover more believed aspects of the viral demographic histories than the GMRF approach. We also find that our GP method produces more reasonable uncertainty estimates than the GMRF method. Copyright © 2013, The International Biometric Society.

  7. Testing and Estimating Shape-Constrained Nonparametric Density and Regression in the Presence of Measurement Error

    KAUST Repository

    Carroll, Raymond J.

    2011-03-01

    In many applications we can expect that, or are interested to know if, a density function or a regression curve satisfies some specific shape constraints. For example, when the explanatory variable, X, represents the value taken by a treatment or dosage, the conditional mean of the response, Y , is often anticipated to be a monotone function of X. Indeed, if this regression mean is not monotone (in the appropriate direction) then the medical or commercial value of the treatment is likely to be significantly curtailed, at least for values of X that lie beyond the point at which monotonicity fails. In the case of a density, common shape constraints include log-concavity and unimodality. If we can correctly guess the shape of a curve, then nonparametric estimators can be improved by taking this information into account. Addressing such problems requires a method for testing the hypothesis that the curve of interest satisfies a shape constraint, and, if the conclusion of the test is positive, a technique for estimating the curve subject to the constraint. Nonparametric methodology for solving these problems already exists, but only in cases where the covariates are observed precisely. However in many problems, data can only be observed with measurement errors, and the methods employed in the error-free case typically do not carry over to this error context. In this paper we develop a novel approach to hypothesis testing and function estimation under shape constraints, which is valid in the context of measurement errors. Our method is based on tilting an estimator of the density or the regression mean until it satisfies the shape constraint, and we take as our test statistic the distance through which it is tilted. Bootstrap methods are used to calibrate the test. The constrained curve estimators that we develop are also based on tilting, and in that context our work has points of contact with methodology in the error-free case.

  8. 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.

  9. 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.

  10. 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.

  11. Nonparametric Estimation of Distributions in Random Effects Models

    KAUST Repository

    Hart, Jeffrey D.

    2011-01-01

    We propose using minimum distance to obtain nonparametric estimates of the distributions of components in random effects models. A main setting considered is equivalent to having a large number of small datasets whose locations, and perhaps scales, vary randomly, but which otherwise have a common distribution. Interest focuses on estimating the distribution that is common to all datasets, knowledge of which is crucial in multiple testing problems where a location/scale invariant test is applied to every small dataset. A detailed algorithm for computing minimum distance estimates is proposed, and the usefulness of our methodology is illustrated by a simulation study and an analysis of microarray data. Supplemental materials for the article, including R-code and a dataset, are available online. © 2011 American Statistical Association.

  12. Prior processes and their applications nonparametric Bayesian estimation

    CERN Document Server

    Phadia, Eswar G

    2016-01-01

    This book presents a systematic and comprehensive treatment of various prior processes that have been developed over the past four decades for dealing with Bayesian approach to solving selected nonparametric inference problems. This revised edition has been substantially expanded to reflect the current interest in this area. After an overview of different prior processes, it examines the now pre-eminent Dirichlet process and its variants including hierarchical processes, then addresses new processes such as dependent Dirichlet, local Dirichlet, time-varying and spatial processes, all of which exploit the countable mixture representation of the Dirichlet process. It subsequently discusses various neutral to right type processes, including gamma and extended gamma, beta and beta-Stacy processes, and then describes the Chinese Restaurant, Indian Buffet and infinite gamma-Poisson processes, which prove to be very useful in areas such as machine learning, information retrieval and featural modeling. Tailfree and P...

  13. Spurious Seasonality Detection: A Non-Parametric Test Proposal

    Directory of Open Access Journals (Sweden)

    Aurelio F. Bariviera

    2018-01-01

    Full Text Available This paper offers a general and comprehensive definition of the day-of-the-week effect. Using symbolic dynamics, we develop a unique test based on ordinal patterns in order to detect it. This test uncovers the fact that the so-called “day-of-the-week” effect is partly an artifact of the hidden correlation structure of the data. We present simulations based on artificial time series as well. While time series generated with long memory are prone to exhibit daily seasonality, pure white noise signals exhibit no pattern preference. Since ours is a non-parametric test, it requires no assumptions about the distribution of returns, so that it could be a practical alternative to conventional econometric tests. We also made an exhaustive application of the here-proposed technique to 83 stock indexes around the world. Finally, the paper highlights the relevance of symbolic analysis in economic time series studies.

  14. Multi-Directional Non-Parametric Analysis of Agricultural Efficiency

    DEFF Research Database (Denmark)

    Balezentis, Tomas

    This thesis seeks to develop methodologies for assessment of agricultural efficiency and employ them to Lithuanian family farms. In particular, we focus on three particular objectives throughout the research: (i) to perform a fully non-parametric analysis of efficiency effects, (ii) to extend...... to the Multi-Directional Efficiency Analysis approach when the proposed models were employed to analyse empirical data of Lithuanian family farm performance, we saw substantial differences in efficiencies associated with different inputs. In particular, assets appeared to be the least efficiently used input...... relative to labour, intermediate consumption and land (in some cases land was not treated as a discretionary input). These findings call for further research on relationships among financial structure, investment decisions, and efficiency in Lithuanian family farms. Application of different techniques...

  15. Evolution of drug resistance in HIV infected patients remaining on a virologically failing cART regimen

    DEFF Research Database (Denmark)

    Cozzi-Lepri, A; Phillips, AN; Ruiz, L

    2007-01-01

    OBJECTIVE: To estimate the extent of drug resistance accumulation in patients kept on a virologically failing regimen and its determinants in the clinical setting. DESIGN: The study focused on 110 patients of EuroSIDA on an unchanged regimen who had two genotypic tests performed at two time points...... (t0 and t1) when viral load was > 400 copies/ml. METHODS: Accumulation of resistance between t0 and t1 was measured using genotypic susceptibility scores (GSS) obtained by counting the total number of active drugs (according to the Rega system v6.4.1) among all licensed antiretrovirals as of 1...... January 2006. Patients were grouped according to the number of active drugs in the failing regimen at t0 (GSS_f-t0). RESULTS: At t0, patients had been on the failing combination antiretroviral therapy (cART) for a median of 11 months (range, 6-50 months). Even patients with extensive resistance...

  16. 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.

  17. A Nonparametric Shape Prior Constrained Active Contour Model for Segmentation of Coronaries in CTA Images

    Directory of Open Access Journals (Sweden)

    Yin Wang

    2014-01-01

    Full Text Available We present a nonparametric shape constrained algorithm for segmentation of coronary arteries in computed tomography images within the framework of active contours. An adaptive scale selection scheme, based on the global histogram information of the image data, is employed to determine the appropriate window size for each point on the active contour, which improves the performance of the active contour model in the low contrast local image regions. The possible leakage, which cannot be identified by using intensity features alone, is reduced through the application of the proposed shape constraint, where the shape of circular sampled intensity profile is used to evaluate the likelihood of current segmentation being considered vascular structures. Experiments on both synthetic and clinical datasets have demonstrated the efficiency and robustness of the proposed method. The results on clinical datasets have shown that the proposed approach is capable of extracting more detailed coronary vessels with subvoxel accuracy.

  18. A non-parametric consistency test of the ΛCDM model with Planck CMB data

    Energy Technology Data Exchange (ETDEWEB)

    Aghamousa, Amir; Shafieloo, Arman [Korea Astronomy and Space Science Institute, Daejeon 305-348 (Korea, Republic of); Hamann, Jan, E-mail: amir@aghamousa.com, E-mail: jan.hamann@unsw.edu.au, E-mail: shafieloo@kasi.re.kr [School of Physics, The University of New South Wales, Sydney NSW 2052 (Australia)

    2017-09-01

    Non-parametric reconstruction methods, such as Gaussian process (GP) regression, provide a model-independent way of estimating an underlying function and its uncertainty from noisy data. We demonstrate how GP-reconstruction can be used as a consistency test between a given data set and a specific model by looking for structures in the residuals of the data with respect to the model's best-fit. Applying this formalism to the Planck temperature and polarisation power spectrum measurements, we test their global consistency with the predictions of the base ΛCDM model. Our results do not show any serious inconsistencies, lending further support to the interpretation of the base ΛCDM model as cosmology's gold standard.

  19. Semi-nonparametric estimates of interfuel substitution in US energy demand

    Energy Technology Data Exchange (ETDEWEB)

    Serletis, A.; Shahmoradi, A. [University of Calgary, Calgary, AB (Canada). Dept. of Economics

    2008-09-15

    This paper focuses on the demand for crude oil, natural gas, and coal in the United States in the context of two globally flexible functional forms - the Fourier and the Asymptotically Ideal Model (AIM) - estimated subject to full regularity, using methods suggested over 20 years ago by Gallant and Golub (Gallant, A. Ronald and Golub, Gene H. Imposing Curvature Restrictions on Flexible Functional Forms. Journal of Econometrics 26 (1984), 295-321) and recently used by Serletis and Shahmoradi (Serletis, A., Shahmoradi, A., 2005. Semi-nonparametric estimates of the demand for money in the United States. Macroeconomic Dynamics 9, 542-559) in the monetary demand systems literature. We provide a comparison in terms of a full set of elasticities and also a policy perspective, using (for the first time) parameter estimates that are consistent with global regularity.

  20. Semi-nonparametric estimates of interfuel substitution in U.S. energy demand

    Energy Technology Data Exchange (ETDEWEB)

    Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada); Shahmoradi, Asghar [Faculty of Economics, University of Tehran, Tehran (Iran)

    2008-09-15

    This paper focuses on the demand for crude oil, natural gas, and coal in the United States in the context of two globally flexible functional forms - the Fourier and the Asymptotically Ideal Model (AIM) - estimated subject to full regularity, using methods suggested over 20 years ago by Gallant and Golub [Gallant, A. Ronald and Golub, Gene H. Imposing Curvature Restrictions on Flexible Functional Forms. Journal of Econometrics 26 (1984), 295-321] and recently used by Serletis and Shahmoradi [Serletis, A., Shahmoradi, A., 2005. Semi-nonparametric estimates of the demand for money in the United States. Macroeconomic Dynamics 9, 542-559] in the monetary demand systems literature. We provide a comparison in terms of a full set of elasticities and also a policy perspective, using (for the first time) parameter estimates that are consistent with global regularity. (author)

  1. Non-parametric adaptive importance sampling for the probability estimation of a launcher impact position

    International Nuclear Information System (INIS)

    Morio, Jerome

    2011-01-01

    Importance sampling (IS) is a useful simulation technique to estimate critical probability with a better accuracy than Monte Carlo methods. It consists in generating random weighted samples from an auxiliary distribution rather than the distribution of interest. The crucial part of this algorithm is the choice of an efficient auxiliary PDF that has to be able to simulate more rare random events. The optimisation of this auxiliary distribution is often in practice very difficult. In this article, we propose to approach the IS optimal auxiliary density with non-parametric adaptive importance sampling (NAIS). We apply this technique for the probability estimation of spatial launcher impact position since it has currently become a more and more important issue in the field of aeronautics.

  2. Extending the linear model with R generalized linear, mixed effects and nonparametric regression models

    CERN Document Server

    Faraway, Julian J

    2005-01-01

    Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway''s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author''s treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the ...

  3. Bayesian nonparametric modeling for comparison of single-neuron firing intensities.

    Science.gov (United States)

    Kottas, Athanasios; Behseta, Sam

    2010-03-01

    We propose a fully inferential model-based approach to the problem of comparing the firing patterns of a neuron recorded under two distinct experimental conditions. The methodology is based on nonhomogeneous Poisson process models for the firing times of each condition with flexible nonparametric mixture prior models for the corresponding intensity functions. We demonstrate posterior inferences from a global analysis, which may be used to compare the two conditions over the entire experimental time window, as well as from a pointwise analysis at selected time points to detect local deviations of firing patterns from one condition to another. We apply our method on two neurons recorded from the primary motor cortex area of a monkey's brain while performing a sequence of reaching tasks.

  4. REGRES: A FORTRAN-77 program to calculate nonparametric and ``structural'' parametric solutions to bivariate regression equations

    Science.gov (United States)

    Rock, N. M. S.; Duffy, T. R.

    REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.

  5. Using nonparametrics to specify a model to measure the value of travel time

    DEFF Research Database (Denmark)

    Fosgerau, Mogens

    2007-01-01

    Using a range of nonparametric methods, the paper examines the specification of a model to evaluate the willingness-to-pay (WTP) for travel time changes from binomial choice data from a simple time-cost trading experiment. The analysis favours a model with random WTP as the only source...... of randomness over a model with fixed WTP which is linear in time and cost and has an additive random error term. Results further indicate that the distribution of log WTP can be described as a sum of a linear index fixing the location of the log WTP distribution and an independent random variable representing...... unobserved heterogeneity. This formulation is useful for parametric modelling. The index indicates that the WTP varies systematically with income and other individual characteristics. The WTP varies also with the time difference presented in the experiment which is in contradiction of standard utility theory....

  6. Nonparametric Estimation of Cumulative Incidence Functions for Competing Risks Data with Missing Cause of Failure

    DEFF Research Database (Denmark)

    Effraimidis, Georgios; Dahl, Christian Møller

    In this paper, we develop a fully nonparametric approach for the estimation of the cumulative incidence function with Missing At Random right-censored competing risks data. We obtain results on the pointwise asymptotic normality as well as the uniform convergence rate of the proposed nonparametric...

  7. Non-parametric tests of productive efficiency with errors-in-variables

    NARCIS (Netherlands)

    Kuosmanen, T.K.; Post, T.; Scholtes, S.

    2007-01-01

    We develop a non-parametric test of productive efficiency that accounts for errors-in-variables, following the approach of Varian. [1985. Nonparametric analysis of optimizing behavior with measurement error. Journal of Econometrics 30(1/2), 445-458]. The test is based on the general Pareto-Koopmans

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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...

  14. 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 ...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Science.gov (United States)

    Tokuda, Tomoki; Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  20. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Directory of Open Access Journals (Sweden)

    Tomoki Tokuda

    Full Text Available We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  1. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

    Science.gov (United States)

    Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

  2. 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

  3. 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.

  4. 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.

  5. Assessing the family dynamics of childhood maltreatment history with the Childhood Attachment and Relational Trauma Screen (CARTS

    Directory of Open Access Journals (Sweden)

    Paul Frewen

    2015-08-01

    Full Text Available Background: Existing survey measures of childhood trauma history generally fail to take into account the relational-socioecological environment in which childhood maltreatment occurs. Variables such as the relationship between the perpetrator and the victim, the emotional availability of caregivers, witnessing the abuse of others, and the respondent's own thoughts, feelings, and actions in response to maltreatment are rarely assessed by current measures. Methods: To address these concerns, the current study further investigated the family dynamics of childhood maltreatment using the Childhood Attachment and Relational Trauma Screen (CARTS in 1,782 persons assessed online. Results: Paired differences in means between item-rated descriptiveness of self, mothers, and fathers suggested that respondents’ relationship with their biological fathers was less positive and secure than their relationship with their biological mothers, and that biological fathers were more often the perpetrator of emotional, physical, and sexual abuse than biological mothers. However, results further suggested that ratings between self, mothers, and fathers were positively correlated such that, for example, reports of a mother's or a respondent's own abusive behavior were more likely in the presence of reports of a father's abusive behavior. In addition, analyses evaluating witnessing violence demonstrated that fathers were rated as more often violent toward mothers than the reverse, although intimate partner violence was also frequently bidirectional. Analyses of sibling ratings further demonstrated that older brothers were either as or more frequently abusive when compared with parents. Finally, results suggested that childhood emotional, physical, and sexual abuse were much more often perpetrated by family members than extra-familial and non-family members. Conclusions: In so far as these findings are consistent with the prior childhood trauma and attachment literature

  6. In Vivo Expansion and Antitumor Activity of Coinfused CD28- and 4-1BB-Engineered CAR-T Cells in Patients with B Cell Leukemia.

    Science.gov (United States)

    Cheng, Zhi; Wei, Runhong; Ma, Qiuling; Shi, Lin; He, Feng; Shi, Zixiao; Jin, Tao; Xie, Ronglin; Wei, Baofeng; Chen, Jing; Fang, Hongliang; Han, Xiaolu; Rohrs, Jennifer A; Bryson, Paul; Liu, Yarong; Li, Qi-Jing; Zhu, Bo; Wang, Pin

    2018-04-04

    Several recent clinical trials have successfully incorporated a costimulatory domain derived from either CD28 or 4-1BB with the original CD3ζ T cell activating domain to form second-generation chimeric antigen receptors (CARs) that can increase the responsiveness and survival of CAR-engineered T (CAR-T) cells. However, a rigorous assessment of the individual benefits of these costimulatory components relative to the in vivo performance of infused T cells in patients is still lacking. Therefore, we have designed a study that allows us to investigate and compare the impact of different costimulatory signal domains on CAR-T cells in vivo. Patients with B cell leukemia were infused with a mixture of two types of CD19-specific CAR-T cells, individually bearing CD28 (28ζ) and 4-1BB (BBζ) costimulatory signaling domains. We found that such a clinical procedure was feasible and safe. Complete remission (CR) was observed in five of seven enrolled patients, with two patients exhibiting durable CR lasting more than 15 months. The in vivo expansion pattern of 28ζ and BBζ CAR-T cells varied significantly among individual patients. These results confirm a feasible method of comparing different CAR designs within individual patients, potentially offering objective insights that may facilitate the development of optimal CAR-T cell-based immunotherapies. Copyright © 2018 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

  7. Nonparametric test of consistency between cosmological models and multiband CMB measurements

    Energy Technology Data Exchange (ETDEWEB)

    Aghamousa, Amir [Asia Pacific Center for Theoretical Physics, Pohang, Gyeongbuk 790-784 (Korea, Republic of); Shafieloo, Arman, E-mail: amir@apctp.org, E-mail: shafieloo@kasi.re.kr [Korea Astronomy and Space Science Institute, Daejeon 305-348 (Korea, Republic of)

    2015-06-01

    We present a novel approach to test the consistency of the cosmological models with multiband CMB data using a nonparametric approach. In our analysis we calibrate the REACT (Risk Estimation and Adaptation after Coordinate Transformation) confidence levels associated with distances in function space (confidence distances) based on the Monte Carlo simulations in order to test the consistency of an assumed cosmological model with observation. To show the applicability of our algorithm, we confront Planck 2013 temperature data with concordance model of cosmology considering two different Planck spectra combination. In order to have an accurate quantitative statistical measure to compare between the data and the theoretical expectations, we calibrate REACT confidence distances and perform a bias control using many realizations of the data. Our results in this work using Planck 2013 temperature data put the best fit ΛCDM model at 95% (∼ 2σ) confidence distance from the center of the nonparametric confidence set while repeating the analysis excluding the Planck 217 × 217 GHz spectrum data, the best fit ΛCDM model shifts to 70% (∼ 1σ) confidence distance. The most prominent features in the data deviating from the best fit ΛCDM model seems to be at low multipoles  18 < ℓ < 26 at greater than 2σ, ℓ ∼ 750 at ∼1 to 2σ and ℓ ∼ 1800 at greater than 2σ level. Excluding the 217×217 GHz spectrum the feature at ℓ ∼ 1800 becomes substantially less significance at ∼1 to 2σ confidence level. Results of our analysis based on the new approach we propose in this work are in agreement with other analysis done using alternative methods.

  8. 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

  9. 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

  10. 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.

  11. Efficient nonparametric n -body force fields from machine learning

    Science.gov (United States)

    Glielmo, Aldo; Zeni, Claudio; De Vita, Alessandro

    2018-05-01

    We provide a definition and explicit expressions for n -body Gaussian process (GP) kernels, which can learn any interatomic interaction occurring in a physical system, up to n -body contributions, for any value of n . The series is complete, as it can be shown that the "universal approximator" squared exponential kernel can be written as a sum of n -body kernels. These recipes enable the choice of optimally efficient force models for each target system, as confirmed by extensive testing on various materials. We furthermore describe how the n -body kernels can be "mapped" on equivalent representations that provide database-size-independent predictions and are thus crucially more efficient. We explicitly carry out this mapping procedure for the first nontrivial (three-body) kernel of the series, and we show that this reproduces the GP-predicted forces with meV /Å accuracy while being orders of magnitude faster. These results pave the way to using novel force models (here named "M-FFs") that are computationally as fast as their corresponding standard parametrized n -body force fields, while retaining the nonparametric character, the ease of training and validation, and the accuracy of the best recently proposed machine-learning potentials.

  12. Nonparametric predictive inference for combined competing risks data

    International Nuclear Information System (INIS)

    Coolen-Maturi, Tahani; Coolen, Frank P.A.

    2014-01-01

    The nonparametric predictive inference (NPI) approach for competing risks data has recently been presented, in particular addressing the question due to which of the competing risks the next unit will fail, and also considering the effects of unobserved, re-defined, unknown or removed competing risks. In this paper, we introduce how the NPI approach can be used to deal with situations where units are not all at risk from all competing risks. This may typically occur if one combines information from multiple samples, which can, e.g. be related to further aspects of units that define the samples or groups to which the units belong or to different applications where the circumstances under which the units operate can vary. We study the effect of combining the additional information from these multiple samples, so effectively borrowing information on specific competing risks from other units, on the inferences. Such combination of information can be relevant to competing risks scenarios in a variety of application areas, including engineering and medical studies

  13. Discrete non-parametric kernel estimation for global sensitivity analysis

    International Nuclear Information System (INIS)

    Senga Kiessé, Tristan; Ventura, Anne

    2016-01-01

    This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

  14. Nonparametric Integrated Agrometeorological Drought Monitoring: Model Development and Application

    Science.gov (United States)

    Zhang, Qiang; Li, Qin; Singh, Vijay P.; Shi, Peijun; Huang, Qingzhong; Sun, Peng

    2018-01-01

    Drought is a major natural hazard that has massive impacts on the society. How to monitor drought is critical for its mitigation and early warning. This study proposed a modified version of the multivariate standardized drought index (MSDI) based on precipitation, evapotranspiration, and soil moisture, i.e., modified multivariate standardized drought index (MMSDI). This study also used nonparametric joint probability distribution analysis. Comparisons were done between standardized precipitation evapotranspiration index (SPEI), standardized soil moisture index (SSMI), MSDI, and MMSDI, and real-world observed drought regimes. Results indicated that MMSDI detected droughts that SPEI and/or SSMI failed to do. Also, MMSDI detected almost all droughts that were identified by SPEI and SSMI. Further, droughts detected by MMSDI were similar to real-world observed droughts in terms of drought intensity and drought-affected area. When compared to MMSDI, MSDI has the potential to overestimate drought intensity and drought-affected area across China, which should be attributed to exclusion of the evapotranspiration components from estimation of drought intensity. Therefore, MMSDI is proposed for drought monitoring that can detect agrometeorological droughts. Results of this study provide a framework for integrated drought monitoring in other regions of the world and can help to develop drought mitigation.

  15. Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

    Science.gov (United States)

    Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

    2015-02-01

    We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

  16. Nonparametric adaptive age replacement with a one-cycle criterion

    International Nuclear Information System (INIS)

    Coolen-Schrijner, P.; Coolen, F.P.A.

    2007-01-01

    Age replacement of technical units has received much attention in the reliability literature over the last four decades. Mostly, the failure time distribution for the units is assumed to be known, and minimal costs per unit of time is used as optimality criterion, where renewal reward theory simplifies the mathematics involved but requires the assumption that the same process and replacement strategy continues over a very large ('infinite') period of time. Recently, there has been increasing attention to adaptive strategies for age replacement, taking into account the information from the process. Although renewal reward theory can still be used to provide an intuitively and mathematically attractive optimality criterion, it is more logical to use minimal costs per unit of time over a single cycle as optimality criterion for adaptive age replacement. In this paper, we first show that in the classical age replacement setting, with known failure time distribution with increasing hazard rate, the one-cycle criterion leads to earlier replacement than the renewal reward criterion. Thereafter, we present adaptive age replacement with a one-cycle criterion within the nonparametric predictive inferential framework. We study the performance of this approach via simulations, which are also used for comparisons with the use of the renewal reward criterion within the same statistical framework

  17. Bayesian Nonparametric Model for Estimating Multistate Travel Time Distribution

    Directory of Open Access Journals (Sweden)

    Emmanuel Kidando

    2017-01-01

    Full Text Available Multistate models, that is, models with more than two distributions, are preferred over single-state probability models in modeling the distribution of travel time. Literature review indicated that the finite multistate modeling of travel time using lognormal distribution is superior to other probability functions. In this study, we extend the finite multistate lognormal model of estimating the travel time distribution to unbounded lognormal distribution. In particular, a nonparametric Dirichlet Process Mixture Model (DPMM with stick-breaking process representation was used. The strength of the DPMM is that it can choose the number of components dynamically as part of the algorithm during parameter estimation. To reduce computational complexity, the modeling process was limited to a maximum of six components. Then, the Markov Chain Monte Carlo (MCMC sampling technique was employed to estimate the parameters’ posterior distribution. Speed data from nine links of a freeway corridor, aggregated on a 5-minute basis, were used to calculate the corridor travel time. The results demonstrated that this model offers significant flexibility in modeling to account for complex mixture distributions of the travel time without specifying the number of components. The DPMM modeling further revealed that freeway travel time is characterized by multistate or single-state models depending on the inclusion of onset and offset of congestion periods.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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....

  4. 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

  5. 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...

  6. 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

  7. Separating environmental efficiency into production and abatement efficiency. A nonparametric model with application to U.S. power plants

    Energy Technology Data Exchange (ETDEWEB)

    Hampf, Benjamin

    2011-08-15

    In this paper we present a new approach to evaluate the environmental efficiency of decision making units. We propose a model that describes a two-stage process consisting of a production and an end-of-pipe abatement stage with the environmental efficiency being determined by the efficiency of both stages. Taking the dependencies between the two stages into account, we show how nonparametric methods can be used to measure environmental efficiency and to decompose it into production and abatement efficiency. For an empirical illustration we apply our model to an analysis of U.S. power plants.

  8. Economic decision making and the application of nonparametric prediction models

    Science.gov (United States)

    Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

    2008-01-01

    Sustained increases in energy prices have focused attention on gas resources in low-permeability shale or in coals that were previously considered economically marginal. Daily well deliverability is often relatively small, although the estimates of the total volumes of recoverable resources in these settings are often large. Planning and development decisions for extraction of such resources must be areawide because profitable extraction requires optimization of scale economies to minimize costs and reduce risk. For an individual firm, the decision to enter such plays depends on reconnaissance-level estimates of regional recoverable resources and on cost estimates to develop untested areas. This paper shows how simple nonparametric local regression models, used to predict technically recoverable resources at untested sites, can be combined with economic models to compute regional-scale cost functions. The context of the worked example is the Devonian Antrim-shale gas play in the Michigan basin. One finding relates to selection of the resource prediction model to be used with economic models. Models chosen because they can best predict aggregate volume over larger areas (many hundreds of sites) smooth out granularity in the distribution of predicted volumes at individual sites. This loss of detail affects the representation of economic cost functions and may affect economic decisions. Second, because some analysts consider unconventional resources to be ubiquitous, the selection and order of specific drilling sites may, in practice, be determined arbitrarily by extraneous factors. The analysis shows a 15-20% gain in gas volume when these simple models are applied to order drilling prospects strategically rather than to choose drilling locations randomly. Copyright ?? 2008 Society of Petroleum Engineers.

  9. A parametric interpretation of Bayesian Nonparametric Inference from Gene Genealogies: Linking ecological, population genetics and evolutionary processes.

    Science.gov (United States)

    Ponciano, José Miguel

    2017-11-22

    Using a nonparametric Bayesian approach Palacios and Minin (2013) dramatically improved the accuracy, precision of Bayesian inference of population size trajectories from gene genealogies. These authors proposed an extension of a Gaussian Process (GP) nonparametric inferential method for the intensity function of non-homogeneous Poisson processes. They found that not only the statistical properties of the estimators were improved with their method, but also, that key aspects of the demographic histories were recovered. The authors' work represents the first Bayesian nonparametric solution to this inferential problem because they specify a convenient prior belief without a particular functional form on the population trajectory. Their approach works so well and provides such a profound understanding of the biological process, that the question arises as to how truly "biology-free" their approach really is. Using well-known concepts of stochastic population dynamics, here I demonstrate that in fact, Palacios and Minin's GP model can be cast as a parametric population growth model with density dependence and environmental stochasticity. Making this link between population genetics and stochastic population dynamics modeling provides novel insights into eliciting biologically meaningful priors for the trajectory of the effective population size. The results presented here also bring novel understanding of GP as models for the evolution of a trait. Thus, the ecological principles foundation of Palacios and Minin (2013)'s prior adds to the conceptual and scientific value of these authors' inferential approach. I conclude this note by listing a series of insights brought about by this connection with Ecology. Copyright © 2017 The Author. Published by Elsevier Inc. All rights reserved.

  10. Nonparametric estimation for censored mixture data with application to the Cooperative Huntington’s Observational Research Trial

    Science.gov (United States)

    Wang, Yuanjia; Garcia, Tanya P.; Ma, Yanyuan

    2012-01-01

    This work presents methods for estimating genotype-specific distributions from genetic epidemiology studies where the event times are subject to right censoring, the genotypes are not directly observed, and the data arise from a mixture of scientifically meaningful subpopulations. Examples of such studies include kin-cohort studies and quantitative trait locus (QTL) studies. Current methods for analyzing censored mixture data include two types of nonparametric maximum likelihood estimators (NPMLEs) which do not make parametric assumptions on the genotype-specific density functions. Although both NPMLEs are commonly used, we show that one is inefficient and the other inconsistent. To overcome these deficiencies, we propose three classes of consistent nonparametric estimators which do not assume parametric density models and are easy to implement. They are based on the inverse probability weighting (IPW), augmented IPW (AIPW), and nonparametric imputation (IMP). The AIPW achieves the efficiency bound without additional modeling assumptions. Extensive simulation experiments demonstrate satisfactory performance of these estimators even when the data are heavily censored. We apply these estimators to the Cooperative Huntington’s Observational Research Trial (COHORT), and provide age-specific estimates of the effect of mutation in the Huntington gene on mortality using a sample of family members. The close approximation of the estimated non-carrier survival rates to that of the U.S. population indicates small ascertainment bias in the COHORT family sample. Our analyses underscore an elevated risk of death in Huntington gene mutation carriers compared to non-carriers for a wide age range, and suggest that the mutation equally affects survival rates in both genders. The estimated survival rates are useful in genetic counseling for providing guidelines on interpreting the risk of death associated with a positive genetic testing, and in facilitating future subjects at risk

  11. Enjeux juridiques du contrôle des émissions personnelles de gaz à effet de serre par un dispositif de carte carbone

    Directory of Open Access Journals (Sweden)

    Sandrine Rousseaux

    2011-02-01

    Full Text Available La carte carbone individuelle est un dispositif innovant, qui permet d’impliquer les particuliers dans la lutte face au changement climatique. Ce dispositif consiste à limiter leurs émissions de gaz à effet de serre, ce qui suppose de suivre leur consommation de certains produits et services. Ce mode de contrôle des émissions personnelles soulève parfois des controverses, la carte carbone pouvant être perçue comme un instrument de rationnement potentiellement liberticide. Ces deux aspects sont discutés sur la base d’une analyse comparative de la conception et des modalités de mise en œuvre des différents dispositifs de carte carbone, établis ou envisagés en Europe et aux États-Unis. Il en ressort que les controverses ne sont pas réellement fondées.The individual carbon card is an innovative mechanism that helps involve individuals in the fight against climate change. It consists in limiting their greenhouse gas emissions, which requires monitoring a part of their goods and services consumption. This method of personal emissions control is much debated since the carbon card may be perceived as a rationing tool and raises civil liberty issues. Both of these controversial aspects are discussed on the basis of a comparative analysis of how the various carbon card programs, established or contemplated in Europe and in the USA, are designed and implemented. The findings are these controversies are somewhat groundless.

  12. Nonparametric Monitoring for Geotechnical Structures Subject to Long-Term Environmental Change

    Directory of Open Access Journals (Sweden)

    Hae-Bum Yun

    2011-01-01

    Full Text Available A nonparametric, data-driven methodology of monitoring for geotechnical structures subject to long-term environmental change is discussed. Avoiding physical assumptions or excessive simplification of the monitored structures, the nonparametric monitoring methodology presented in this paper provides reliable performance-related information particularly when the collection of sensor data is limited. For the validation of the nonparametric methodology, a field case study was performed using a full-scale retaining wall, which had been monitored for three years using three tilt gauges. Using the very limited sensor data, it is demonstrated that important performance-related information, such as drainage performance and sensor damage, could be disentangled from significant daily, seasonal and multiyear environmental variations. Extensive literature review on recent developments of parametric and nonparametric data processing techniques for geotechnical applications is also presented.

  13. Kernel bandwidth estimation for non-parametric density estimation: a comparative study

    CSIR Research Space (South Africa)

    Van der Walt, CM

    2013-12-01

    Full Text Available We investigate the performance of conventional bandwidth estimators for non-parametric kernel density estimation on a number of representative pattern-recognition tasks, to gain a better understanding of the behaviour of these estimators in high...

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

    Science.gov (United States)

    Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

    2015-05-01

    Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. A multi-instrument non-parametric reconstruction of the electron pressure profile in the galaxy cluster CLJ1226.9+3332

    Science.gov (United States)

    Romero, C.; McWilliam, M.; Macías-Pérez, J.-F.; Adam, R.; Ade, P.; André, P.; Aussel, H.; Beelen, A.; Benoît, A.; Bideaud, A.; Billot, N.; Bourrion, O.; Calvo, M.; Catalano, A.; Coiffard, G.; Comis, B.; de Petris, M.; Désert, F.-X.; Doyle, S.; Goupy, J.; Kramer, C.; Lagache, G.; Leclercq, S.; Lestrade, J.-F.; Mauskopf, P.; Mayet, F.; Monfardini, A.; Pascale, E.; Perotto, L.; Pisano, G.; Ponthieu, N.; Revéret, V.; Ritacco, A.; Roussel, H.; Ruppin, F.; Schuster, K.; Sievers, A.; Triqueneaux, S.; Tucker, C.; Zylka, R.

    2018-04-01

    Context. In the past decade, sensitive, resolved Sunyaev-Zel'dovich (SZ) studies of galaxy clusters have become common. Whereas many previous SZ studies have parameterized the pressure profiles of galaxy clusters, non-parametric reconstructions will provide insights into the thermodynamic state of the intracluster medium. Aim. We seek to recover the non-parametric pressure profiles of the high redshift (z = 0.89) galaxy cluster CLJ 1226.9+3332 as inferred from SZ data from the MUSTANG, NIKA, Bolocam, and Planck instruments, which all probe different angular scales. Methods: Our non-parametric algorithm makes use of logarithmic interpolation, which under the assumption of ellipsoidal symmetry is analytically integrable. For MUSTANG, NIKA, and Bolocam we derive a non-parametric pressure profile independently and find good agreement among the instruments. In particular, we find that the non-parametric profiles are consistent with a fitted generalized Navaro-Frenk-White (gNFW) profile. Given the ability of Planck to constrain the total signal, we include a prior on the integrated Compton Y parameter as determined by Planck. Results: For a given instrument, constraints on the pressure profile diminish rapidly beyond the field of view. The overlap in spatial scales probed by these four datasets is therefore critical in checking for consistency between instruments. By using multiple instruments, our analysis of CLJ 1226.9+3332 covers a large radial range, from the central regions to the cluster outskirts: 0.05 R500 generation of SZ instruments such as NIKA2 and MUSTANG2.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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...

  6. 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...

  7. Examples of the Application of Nonparametric Information Geometry to Statistical Physics

    Directory of Open Access Journals (Sweden)

    Giovanni Pistone

    2013-09-01

    Full Text Available We review a nonparametric version of Amari’s information geometry in which the set of positive probability densities on a given sample space is endowed with an atlas of charts to form a differentiable manifold modeled on Orlicz Banach spaces. This nonparametric setting is used to discuss the setting of typical problems in machine learning and statistical physics, such as black-box optimization, Kullback-Leibler divergence, Boltzmann-Gibbs entropy and the Boltzmann equation.

  8. Screen Wars, Star Wars, and Sequels: Nonparametric Reanalysis of Movie Profitability

    OpenAIRE

    W. D. Walls

    2012-01-01

    In this paper we use nonparametric statistical tools to quantify motion-picture profit. We quantify the unconditional distribution of profit, the distribution of profit conditional on stars and sequels, and we also model the conditional expectation of movie profits using a non- parametric data-driven regression model. The flexibility of the non-parametric approach accommodates the full range of possible relationships among the variables without prior specification of a functional form, thereb...

  9. Developing an immigration policy for Germany on the basis of a nonparametric labor market classification

    OpenAIRE

    Froelich, Markus; Puhani, Patrick

    2004-01-01

    Based on a nonparametrically estimated model of labor market classifications, this paper makes suggestions for immigration policy using data from western Germany in the 1990s. It is demonstrated that nonparametric regression is feasible in higher dimensions with only a few thousand observations. In sum, labor markets able to absorb immigrants are characterized by above average age and by professional occupations. On the other hand, labor markets for young workers in service occupations are id...

  10. Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices

    OpenAIRE

    Hiroyuki Kasahara; Katsumi Shimotsu

    2006-01-01

    In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in appli...

  11. 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

  12. Rank-based permutation approaches for non-parametric factorial designs.

    Science.gov (United States)

    Umlauft, Maria; Konietschke, Frank; Pauly, Markus

    2017-11-01

    Inference methods for null hypotheses formulated in terms of distribution functions in general non-parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set-up Wald-type statistics and ANOVA-type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal-Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability. © 2017 The British Psychological Society.

  13. Notes on the Implementation of Non-Parametric Statistics within the Westinghouse Realistic Large Break LOCA Evaluation Model (ASTRUM)

    International Nuclear Information System (INIS)

    Frepoli, Cesare; Oriani, Luca

    2006-01-01

    In recent years, non-parametric or order statistics methods have been widely used to assess the impact of the uncertainties within Best-Estimate LOCA evaluation models. The bounding of the uncertainties is achieved with a direct Monte Carlo sampling of the uncertainty attributes, with the minimum trial number selected to 'stabilize' the estimation of the critical output values (peak cladding temperature (PCT), local maximum oxidation (LMO), and core-wide oxidation (CWO A non-parametric order statistics uncertainty analysis was recently implemented within the Westinghouse Realistic Large Break LOCA evaluation model, also referred to as 'Automated Statistical Treatment of Uncertainty Method' (ASTRUM). The implementation or interpretation of order statistics in safety analysis is not fully consistent within the industry. This has led to an extensive public debate among regulators and researchers which can be found in the open literature. The USNRC-approved Westinghouse method follows a rigorous implementation of the order statistics theory, which leads to the execution of 124 simulations within a Large Break LOCA analysis. This is a solid approach which guarantees that a bounding value (at 95% probability) of the 95 th percentile for each of the three 10 CFR 50.46 ECCS design acceptance criteria (PCT, LMO and CWO) is obtained. The objective of this paper is to provide additional insights on the ASTRUM statistical approach, with a more in-depth analysis of pros and cons of the order statistics and of the Westinghouse approach in the implementation of this statistical methodology. (authors)

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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.