Drawing a Regression Line between Spaghetti & Basketball
Ozgun-Koca, S. Asli; Edwards, Thomas G.
2010-01-01
"I liked to grab things on the graphics and see it first hand, see what we were doing on the problem. It makes more sense." These words were from a student who completed a series of lessons on lines of best fit. She made this comment after comparing a hands-on approach using a strand of spaghetti with a high-tech approach using a calculator. To…
Alternate Double Single Track Lines
Energy Technology Data Exchange (ETDEWEB)
Moraga Contreras, P.; Grande Andrade, Z.; Castillo Ron, E.
2016-07-01
The paper discusses the advantages and shortcomings of alternate double single track (ADST) lines with respect to double track lines for high speed lines. ADST lines consists of sequences of double and single track segments optimally selected in order to reduce the construction and maintenance costs of railway lines and to optimize the timetables used to satisfy a given demand. The single tracks are selected to coincide with expensive segments (tunnels and viaducts) and the double tracks are chosen to coincide with flat areas and only where they are necessary. At the same time, departure times are adjusted for trains to cross at the cheap double track segments. This alternative can be used for new lines and also for existing conventional lines where some new tracks are to be constructed to reduce travel time (increase speed). The ADST proposal is illustrated with some examples of both types (new lines and where conventional lines exist), including the Palencia-Santander, the Santiago-Valparaíso-Viña del Mar and the Dublin-Belfast lines, where very important reductions (90 %) are obtained, especially where a railway infrastructure already exist. (Author)
Testing hypotheses for differences between linear regression lines
Stanley J. Zarnoch
2009-01-01
Five hypotheses are identified for testing differences between simple linear regression lines. The distinctions between these hypotheses are based on a priori assumptions and illustrated with full and reduced models. The contrast approach is presented as an easy and complete method for testing for overall differences between the regressions and for making pairwise...
On-line mixture-based alternative to logistic regression
Czech Academy of Sciences Publication Activity Database
Nagy, Ivan; Suzdaleva, Evgenia
2016-01-01
Roč. 26, č. 5 (2016), s. 417-437 ISSN 1210-0552 R&D Projects: GA ČR GA15-03564S Institutional support: RVO:67985556 Keywords : on-line modeling * on-line logistic regression * recursive mixture estimation * data dependent pointer Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.394, year: 2016 http://library.utia.cas.cz/separaty/2016/ZS/suzdaleva-0464463.pdf
Mixture of Regression Models with Single-Index
Xiang, Sijia; Yao, Weixin
2016-01-01
In this article, we propose a class of semiparametric mixture regression models with single-index. We argue that many recently proposed semiparametric/nonparametric mixture regression models can be considered special cases of the proposed model. However, unlike existing semiparametric mixture regression models, the new pro- posed model can easily incorporate multivariate predictors into the nonparametric components. Backfitting estimates and the corresponding algorithms have been proposed for...
Generalized single-hidden layer feedforward networks for regression problems.
Wang, Ning; Er, Meng Joo; Han, Min
2015-06-01
In this paper, traditional single-hidden layer feedforward network (SLFN) is extended to novel generalized SLFN (GSLFN) by employing polynomial functions of inputs as output weights connecting randomly generated hidden units with corresponding output nodes. The significant contributions of this paper are as follows: 1) a primal GSLFN (P-GSLFN) is implemented using randomly generated hidden nodes and polynomial output weights whereby the regression matrix is augmented by full or partial input variables and only polynomial coefficients are to be estimated; 2) a simplified GSLFN (S-GSLFN) is realized by decomposing the polynomial output weights of the P-GSLFN into randomly generated polynomial nodes and tunable output weights; 3) both P- and S-GSLFN are able to achieve universal approximation if the output weights are tuned by ridge regression estimators; and 4) by virtue of the developed batch and online sequential ridge ELM (BR-ELM and OSR-ELM) learning algorithms, high performance of the proposed GSLFNs in terms of generalization and learning speed is guaranteed. Comprehensive simulation studies and comparisons with standard SLFNs are carried out on real-world regression benchmark data sets. Simulation results demonstrate that the innovative GSLFNs using BR-ELM and OSR-ELM are superior to standard SLFNs in terms of accuracy, training speed, and structure compactness.
A regression-based Kansei engineering system based on form feature lines for product form design
Directory of Open Access Journals (Sweden)
Yan Xiong
2016-06-01
Full Text Available When developing new products, it is important for a designer to understand users’ perceptions and develop product form with the corresponding perceptions. In order to establish the mapping between users’ perceptions and product design features effectively, in this study, we presented a regression-based Kansei engineering system based on form feature lines for product form design. First according to the characteristics of design concept representation, product form features–product form feature lines were defined. Second, Kansei words were chosen to describe image perceptions toward product samples. Then, multiple linear regression and support vector regression were used to construct the models, respectively, that predicted users’ image perceptions. Using mobile phones as experimental samples, Kansei prediction models were established based on the front view form feature lines of the samples. From the experimental results, these two predict models were of good adaptability. But in contrast to multiple linear regression, the predict performance of support vector regression model was better, and support vector regression is more suitable for form regression prediction. The results of the case showed that the proposed method provided an effective means for designers to manipulate product features as a whole, and it can optimize Kansei model and improve practical values.
Genomic prediction based on data from three layer lines using non-linear regression models
Huang, H.; Windig, J.J.; Vereijken, A.; Calus, M.P.L.
2014-01-01
Background - Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. Methods - In an attempt to alleviate
Semiparametric Mixtures of Regressions with Single-index for Model Based Clustering
Xiang, Sijia; Yao, Weixin
2017-01-01
In this article, we propose two classes of semiparametric mixture regression models with single-index for model based clustering. Unlike many semiparametric/nonparametric mixture regression models that can only be applied to low dimensional predictors, the new semiparametric models can easily incorporate high dimensional predictors into the nonparametric components. The proposed models are very general, and many of the recently proposed semiparametric/nonparametric mixture regression models a...
FMEF Electrical single line diagram and panel schedule verification process
International Nuclear Information System (INIS)
Fong, S.K.
1998-01-01
Since the FMEF did not have a mission, a formal drawing verification program was not developed, however, a verification process on essential electrical single line drawings and panel schedules was established to benefit the operations lock and tag program and to enhance the electrical safety culture of the facility. The purpose of this document is to provide a basis by which future landlords and cognizant personnel can understand the degree of verification performed on the electrical single lines and panel schedules. It is the intent that this document be revised or replaced by a more formal requirements document if a mission is identified for the FMEF
Linear Regression on Sparse Features for Single-Channel Speech Separation
DEFF Research Database (Denmark)
Schmidt, Mikkel N.; Olsson, Rasmus Kongsgaard
2007-01-01
In this work we address the problem of separating multiple speakers from a single microphone recording. We formulate a linear regression model for estimating each speaker based on features derived from the mixture. The employed feature representation is a sparse, non-negative encoding of the speech...... compared to linear regression on spectral features and compared to separation based directly on the non-negative sparse features....... mixture in terms of pre-learned speaker-dependent dictionaries. Previous work has shown that this feature representation by itself provides some degree of separation. We show that the performance is significantly improved when regression analysis is performed on the sparse, non-negative features, both...
Single channel in-line multimodal digital holography.
Rivenson, Yair; Katz, Barak; Kelner, Roy; Rosen, Joseph
2013-11-15
We present a new single channel in-line setup for holographic recording that can properly record various objects that cannot be recorded by the Gabor holographic method. This configuration allows the recording of holograms based on several modalities while addressing important issues of the original Gabor setup, including the well-known twin-image problem and the weak scattering condition.
Bertrand, Julie; Balding, David J
2013-03-01
Studies on the influence of single nucleotide polymorphisms (SNPs) on drug pharmacokinetics (PK) have usually been limited to the analysis of observed drug concentration or area under the concentration versus time curve. Nonlinear mixed effects models enable analysis of the entire curve, even for sparse data, but until recently, there has been no systematic method to examine the effects of multiple SNPs on the model parameters. The aim of this study was to assess different penalized regression methods for including SNPs in PK analyses. A total of 200 data sets were simulated under both the null and an alternative hypothesis. In each data set for each of the 300 participants, a PK profile at six sampling times was simulated and 1227 genotypes were generated through haplotypes. After modelling the PK profiles using an expectation maximization algorithm, genetic association with individual parameters was investigated using the following approaches: (i) a classical stepwise approach, (ii) ridge regression modified to include a test, (iii) Lasso and (iv) a generalization of Lasso, the HyperLasso. Penalized regression approaches are often much faster than the stepwise approach. There are significantly fewer true positives for ridge regression than for the stepwise procedure and HyperLasso. The higher number of true positives in the stepwise procedure was accompanied by a higher count of false positives (not significant). We find that all approaches except ridge regression show similar power, but penalized regression can be much less computationally demanding. We conclude that penalized regression should be preferred over stepwise procedures for PK analyses with a large panel of genetic covariates.
Hu, L; Zhang, Z G; Mouraux, A; Iannetti, G D
2015-05-01
Transient sensory, motor or cognitive event elicit not only phase-locked event-related potentials (ERPs) in the ongoing electroencephalogram (EEG), but also induce non-phase-locked modulations of ongoing EEG oscillations. These modulations can be detected when single-trial waveforms are analysed in the time-frequency domain, and consist in stimulus-induced decreases (event-related desynchronization, ERD) or increases (event-related synchronization, ERS) of synchrony in the activity of the underlying neuronal populations. ERD and ERS reflect changes in the parameters that control oscillations in neuronal networks and, depending on the frequency at which they occur, represent neuronal mechanisms involved in cortical activation, inhibition and binding. ERD and ERS are commonly estimated by averaging the time-frequency decomposition of single trials. However, their trial-to-trial variability that can reflect physiologically-important information is lost by across-trial averaging. Here, we aim to (1) develop novel approaches to explore single-trial parameters (including latency, frequency and magnitude) of ERP/ERD/ERS; (2) disclose the relationship between estimated single-trial parameters and other experimental factors (e.g., perceived intensity). We found that (1) stimulus-elicited ERP/ERD/ERS can be correctly separated using principal component analysis (PCA) decomposition with Varimax rotation on the single-trial time-frequency distributions; (2) time-frequency multiple linear regression with dispersion term (TF-MLRd) enhances the signal-to-noise ratio of ERP/ERD/ERS in single trials, and provides an unbiased estimation of their latency, frequency, and magnitude at single-trial level; (3) these estimates can be meaningfully correlated with each other and with other experimental factors at single-trial level (e.g., perceived stimulus intensity and ERP magnitude). The methods described in this article allow exploring fully non-phase-locked stimulus-induced cortical
Walking Posture Control of Transmission Line Single Arm Inspection Robot
Yan, Yu; Liu, Xiaqing; Li, Jinliang; Ou, Yuexiong
2017-07-01
To control the walking posture according to transmission line single arm inspection robot, the robot is divided into normal walking and climbing walking two state, and gives the definition, then based on the state space method of state variable feedback and PD control method is used to control the two states, two kinds of control method of simulation by using Matlab, in the end, the two control methods proposed is validated in the actual circuit structures. The results show that, the proposed control method is rapid and effective, and can meet the needs of practical application.
Single Image Super-Resolution by Non-Linear Sparse Representation and Support Vector Regression
Directory of Open Access Journals (Sweden)
Yungang Zhang
2017-02-01
Full Text Available Sparse representations are widely used tools in image super-resolution (SR tasks. In the sparsity-based SR methods, linear sparse representations are often used for image description. However, the non-linear data distributions in images might not be well represented by linear sparse models. Moreover, many sparsity-based SR methods require the image patch self-similarity assumption; however, the assumption may not always hold. In this paper, we propose a novel method for single image super-resolution (SISR. Unlike most prior sparsity-based SR methods, the proposed method uses non-linear sparse representation to enhance the description of the non-linear information in images, and the proposed framework does not need to assume the self-similarity of image patches. Based on the minimum reconstruction errors, support vector regression (SVR is applied for predicting the SR image. The proposed method was evaluated on various benchmark images, and promising results were obtained.
Single-trial regression elucidates the role of prefrontal theta oscillations in response conflict
Directory of Open Access Journals (Sweden)
Michael X Cohen
2011-02-01
Full Text Available In most cognitive neuroscience experiments there are many behavioral and experimental dynamics, and many indices of brain activity, that vary from trial to trial. For example, in studies of response conflict, conflict is usually treated as a binary variable (i.e., response conflict exists or does not in any given trial, whereas some evidence and intuition suggests that conflict may vary in intensity from trial to trial. Here we demonstrate that single-trial multiple regression of time-frequency electrophysiological activity reveals neural mechanisms of cognitive control that are not apparent in cross-trial averages. We also introduce a novel extension to oscillation phase coherence and synchronization analyses, based on weighted phase modulation, that has advantages over standard coherence measures in terms of linking electrophysiological dynamics to trial-varying behavior and experimental variables. After replicating previous response conflict findings using trial-averaged data, we extend these findings using single trial analytic methods to provide novel evidence for the role of medial frontal-lateral prefrontal theta-band synchronization in conflict-induced response time dynamics, including a role for lateral prefrontal theta-band activity in biasing response times according to perceptual conflict. Given that these methods shed new light on the prefrontal mechanisms of response conflict, they are also likely to be useful for investigating other neurocognitive processes.
On-line Nonparametric Regression to learn State-Dependent Disturbances
de Kruif, B.J.; de Vries, Theodorus J.A.
2003-01-01
A combination of recursive least squares and weighted least squares is made which can adapt its structure such that a relation between in- and output can he approximated, even when the structure of this relation is unknown beforehand. This method can adapt its structure on-line while it preserves
Directory of Open Access Journals (Sweden)
B. Karacaören
2016-07-01
Full Text Available Development of body hair is an important physiological and cellular process that leads to better adaption in tropical environments for dairy cattle. Various studies suggested a major gene and, more recently, associated genes for hairy locus in dairy cattle. Main aim of this study was to i employ a variant of the discordant sib pair model, in which half sibs from the same sires are randomly sampled using their affection statues, ii use various single marker regression approaches, and iii use whole genome regression approaches to dissect genetic architecture of the hairy gene in the cattle. Whole and single genome regression approaches detected strong genomic signals from Chromosome 23. Although there is a major gene effect on hairy phenotype sourced from chromosome 23: whole genome regression approach also suggested polygenic component related with other parts of the genome. Such a result could not be obtained by any of the single marker approaches.
Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.
Choi, Jae-Seok; Kim, Munchurl
2017-03-01
Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower
International Nuclear Information System (INIS)
Gallego-Castillo, Cristobal; Bessa, Ricardo; Cavalcante, Laura; Lopez-Garcia, Oscar
2016-01-01
Wind power probabilistic forecast is being used as input in several decision-making problems, such as stochastic unit commitment, operating reserve setting and electricity market bidding. This work introduces a new on-line quantile regression model based on the Reproducing Kernel Hilbert Space (RKHS) framework. Its application to the field of wind power forecasting involves a discussion on the choice of the bias term of the quantile models, and the consideration of the operational framework in order to mimic real conditions. Benchmark against linear and splines quantile regression models was performed for a real case study during a 18 months period. Model parameter selection was based on k-fold crossvalidation. Results showed a noticeable improvement in terms of calibration, a key criterion for the wind power industry. Modest improvements in terms of Continuous Ranked Probability Score (CRPS) were also observed for prediction horizons between 6 and 20 h ahead. - Highlights: • New online quantile regression model based on the Reproducing Kernel Hilbert Space. • First application to operational probabilistic wind power forecasting. • Modest improvements of CRPS for prediction horizons between 6 and 20 h ahead. • Noticeable improvements in terms of Calibration due to online learning.
Spontaneous Regression of Lymphangiomas in a Single Center Over 34 Years
Directory of Open Access Journals (Sweden)
Motoi Kato, MD
2017-09-01
Conclusions:. We concluded that elderly patients with macrocystic or mixed type lymphangioma may have to wait for treatment for over 3 months from the initial onset. Conversely, microcystic type could not be expected to show regression in a short period, and prompt initiation of the treatments may be required. The difference of the regression or not may depend on the characteristics of the lymph flow.
Modified Regression Rate Formula of PMMA Combustion by a Single Plane Impinging Jet
Directory of Open Access Journals (Sweden)
Tsuneyoshi Matsuoka
2017-01-01
Full Text Available A modified regression rate formula for the uppermost stage of CAMUI-type hybrid rocket motor is proposed in this study. Assuming a quasi-steady, one-dimensional, an energy balance against a control volume near the fuel surface is considered. Accordingly, the regression rate formula which can calculate the local regression rate by the quenching distance between the flame and the regression surface is derived. An experimental setup which simulates the combustion phenomenon involved in the uppermost stage of a CAMUI-type hybrid rocket motor was constructed and the burning tests with various flow velocities and impinging distances were performed. A PMMA slab of 20 mm height, 60 mm width, and 20 mm thickness was chosen as a sample specimen and pure oxygen and O2/N2 mixture (50/50 vol.% were employed as the oxidizers. The time-averaged regression rate along the fuel surface was measured by a laser displacement sensor. The quenching distance during the combustion event was also identified from the observation. The comparison between the purely experimental and calculated values showed good agreement, although a large systematic error was expected due to the difficulty in accurately identifying the quenching distance.
Shojai, Mohadese; Kazemnejad, Anoshirvan; Zayeri, Farid; Vahedi, Mohsen
2013-01-01
For the purpose of cost modeling, the semi-parametric single-index two-part model was utilized in the paper. Furthermore, as functional gastrointestinal diseases which are well-known as common causes of illness among the society people in terms of both the number of patients and prevalence in a specific time interval, this research estimated the average cost of functional gastrointestinal diseases. Health care policy-makers seek for real and accurate estimations of society's future medical costs. However, data dealt with in hygienic studies have characteristics which make their analysis complicated; distribution of cost data is highly skewed since many patients pay great costs. In addition, medical costs of many persons are zero in a specific time interval. Indeed, medical costs data are often right skewed, including remarkable number of zeros, and may be distributed non-homogeneously. In modeling these costs by the semi-parametric single-index two-part model, parameters were determined by method of least squares; a result of this method was compared with the results yielded from two-part parametric model. Average costs of functional gastrointestinal diseases and their standard deviation in semi-parametric and parametric methods were yielded as $72.69±108.96 (R(2)=0.38) and $75.93±122.29 (R(2)=0.33) respectively. Based on R(2) index, the semi-parametric model is recognized as the best model. Totally, the two-part parametric regression model is a simple and available model which can be easily interpreted; on the other hand, though the single-index two-part semi-parametric model cannot be easily interpreted, it has considerable flexibility. The study goals can be indeed used as the main factor for choosing one of these two models.
Ross, Sarah G; Begeny, John C
2014-08-01
Growing from demands for accountability and research-based practice in the field of education, there is recent focus on developing standards for the implementation and analysis of single-case designs. Effect size methods for single-case designs provide a useful way to discuss treatment magnitude in the context of individual intervention. Although a standard effect size methodology does not yet exist within single-case research, panel experts recently recommended pairing regression and non-parametric approaches when analyzing effect size data. This study compared two single-case effect size methods: the regression-based, Allison-MT method and the newer, non-parametric, Tau-U method. Using previously published research that measured the Words read Correct per Minute (WCPM) variable, these two methods were examined by comparing differences in overall effect size scores and rankings of intervention effect. Results indicated that the regression method produced significantly larger effect sizes than the non-parametric method, but the rankings of the effect size scores had a strong, positive relation. Implications of these findings for research and practice are discussed. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Single image super-resolution using locally adaptive multiple linear regression.
Yu, Soohwan; Kang, Wonseok; Ko, Seungyong; Paik, Joonki
2015-12-01
This paper presents a regularized superresolution (SR) reconstruction method using locally adaptive multiple linear regression to overcome the limitation of spatial resolution of digital images. In order to make the SR problem better-posed, the proposed method incorporates the locally adaptive multiple linear regression into the regularization process as a local prior. The local regularization prior assumes that the target high-resolution (HR) pixel is generated by a linear combination of similar pixels in differently scaled patches and optimum weight parameters. In addition, we adapt a modified version of the nonlocal means filter as a smoothness prior to utilize the patch redundancy. Experimental results show that the proposed algorithm better restores HR images than existing state-of-the-art methods in the sense of the most objective measures in the literature.
Customized Pull Systems for Single-Product Flow Lines
Gaury, E.G.A.; Kleijnen, J.P.C.; Pierreval, H.
1998-01-01
Traditionally pull production systems are managed through classic control systems such as Kanban, Conwip, or Base stock, but this paper proposes ‘customized’ pull control. Customization means that a given production line is managed through a pull control system that in principle connects each stage
Sim, K S; Norhisham, S
2016-11-01
A new method based on nonlinear least squares regression (NLLSR) is formulated to estimate signal-to-noise ratio (SNR) of scanning electron microscope (SEM) images. The estimation of SNR value based on NLLSR method is compared with the three existing methods of nearest neighbourhood, first-order interpolation and the combination of both nearest neighbourhood and first-order interpolation. Samples of SEM images with different textures, contrasts and edges were used to test the performance of NLLSR method in estimating the SNR values of the SEM images. It is shown that the NLLSR method is able to produce better estimation accuracy as compared to the other three existing methods. According to the SNR results obtained from the experiment, the NLLSR method is able to produce approximately less than 1% of SNR error difference as compared to the other three existing methods. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.
Sargent, Garrett C.; Ratliff, Bradley M.; Asari, Vijayan K.
2017-08-01
The advantage of division of focal plane imaging polarimeters is their ability to obtain temporally synchronized intensity measurements across a scene; however, they sacrifice spatial resolution in doing so due to their spatially modulated arrangement of the pixel-to-pixel polarizers and often result in aliased imagery. Here, we propose a super-resolution method based upon two previously trained extreme learning machines (ELM) that attempt to recover missing high frequency and low frequency content beyond the spatial resolution of the sensor. This method yields a computationally fast and simple way of recovering lost high and low frequency content from demosaicing raw microgrid polarimetric imagery. The proposed method outperforms other state-of-the-art single-image super-resolution algorithms in terms of structural similarity and peak signal-to-noise ratio.
In-Line Fiber Optic Interferometric Sensors in Single-Mode Fibers
De-Wen Duan; Min Liu; Di Wu; Tao Zhu
2012-01-01
In-line fiber optic interferometers have attracted intensive attention for their potential sensing applications in refractive index, temperature, pressure and strain measurement, etc. Typical in-line fiber-optic interferometers are of two types: Fabry-Perot interferometers and core-cladding-mode interferometers. It’s known that the in-line fiber optic interferometers based on single-mode fibers can exhibit compact structures, easy fabrication and low cost. In this paper, ...
Caballero Gaudes, César; Petridou, Natalia; Francis, Susan T; Dryden, Ian L; Gowland, Penny A
2013-03-01
The ability to detect single trial responses in functional magnetic resonance imaging (fMRI) studies is essential, particularly if investigating learning or adaptation processes or unpredictable events. We recently introduced paradigm free mapping (PFM), an analysis method that detects single trial blood oxygenation level dependent (BOLD) responses without specifying prior information on the timing of the events. PFM is based on the deconvolution of the fMRI signal using a linear hemodynamic convolution model. Our previous PFM method (Caballero-Gaudes et al., 2011: Hum Brain Mapp) used the ridge regression estimator for signal deconvolution and required a baseline signal period for statistical inference. In this work, we investigate the application of sparse regression techniques in PFM. In particular, a novel PFM approach is developed using the Dantzig selector estimator, solved via an efficient homotopy procedure, along with statistical model selection criteria. Simulation results demonstrated that, using the Bayesian information criterion to select the regularization parameter, this method obtains high detection rates of the BOLD responses, comparable with a model-based analysis, but requiring no information on the timing of the events and being robust against hemodynamic response function variability. The practical operation of this sparse PFM method was assessed with single-trial fMRI data acquired at 7T, where it automatically detected all task-related events, and was an improvement on our previous PFM method, as it does not require the definition of a baseline state and amplitude thresholding and does not compromise on specificity and sensitivity. Copyright © 2011 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Zachary J. Smith
2015-12-01
Full Text Available Current analysis of exosomes focuses primarily on bulk analysis, where exosome-to-exosome variability cannot be assessed. In this study, we used Raman spectroscopy to study the chemical composition of single exosomes. We measured spectra of individual exosomes from 8 cell lines. Cell-line-averaged spectra varied considerably, reflecting the variation in total exosomal protein, lipid, genetic, and cytosolic content. Unexpectedly, single exosomes isolated from the same cell type also exhibited high spectral variability. Subsequent spectral analysis revealed clustering of single exosomes into 4 distinct groups that were not cell-line specific. Each group contained exosomes from multiple cell lines, and most cell lines had exosomes in multiple groups. The differences between these groups are related to chemical differences primarily due to differing membrane composition. Through a principal components analysis, we identified that the major sources of spectral variation among the exosomes were in cholesterol content, relative expression of phospholipids to cholesterol, and surface protein expression. For example, exosomes derived from cancerous versus non-cancerous cell lines can be largely separated based on their relative expression of cholesterol and phospholipids. We are the first to indicate that exosome subpopulations are shared among cell types, suggesting distributed exosome functionality. The origins of these differences are likely related to the specific role of extracellular vesicle subpopulations in both normal cell function and carcinogenesis, and they may provide diagnostic potential at the single exosome level.
Neto, Elias Chaibub; Jang, In Sock; Friend, Stephen H; Margolin, Adam A
2014-01-01
Computational efficiency is important for learning algorithms operating in the "large p, small n" setting. In computational biology, the analysis of data sets containing tens of thousands of features ("large p"), but only a few hundred samples ("small n"), is nowadays routine, and regularized regression approaches such as ridge-regression, lasso, and elastic-net are popular choices. In this paper we propose a novel and highly efficient Bayesian inference method for fitting ridge-regression. Our method is fully analytical, and bypasses the need for expensive tuning parameter optimization, via cross-validation, by employing Bayesian model averaging over the grid of tuning parameters. Additional computational efficiency is achieved by adopting the singular value decomposition reparametrization of the ridge-regression model, replacing computationally expensive inversions of large p × p matrices by efficient inversions of small and diagonal n × n matrices. We show in simulation studies and in the analysis of two large cancer cell line data panels that our algorithm achieves slightly better predictive performance than cross-validated ridge-regression while requiring only a fraction of the computation time. Furthermore, in comparisons based on the cell line data sets, our algorithm systematically out-performs the lasso in both predictive performance and computation time, and shows equivalent predictive performance, but considerably smaller computation time, than the elastic-net.
Li, Xiuling; Ma, Liang; Wang, Dayong; Zeng, Xiao Cheng; Wu, Xiaojun; Yang, Jinlong
2016-10-20
Extended line defects in two-dimensional (2D) materials can play an important role in modulating their electronic properties. During the experimental synthesis of 2D materials, line defects are commonly generated at grain boundaries between domains of different orientations. In this work, twelve types of line-defect structures in single crystalline phosphorene are examined by using first-principles calculations. These line defects are typically formed via migration and aggregation of intrinsic point defects, including the Stone-Wales (SW), single or double vacancy (SV or DV) defects. Our calculated results demonstrate that the migration of point defects in phosphorene is anisotropic, for instance, the lowest migration energy barriers are 1.39 (or 0.40) and 2.58 (or 0.49) eV for SW (or SV) defects in zigzag and armchair directions, respectively. The aggregation of point defects into lines is energetically favorable compared with the separated point defects in phosphorene. In particular, the axis of line defects in phosphorene is direction-selective, depending on the composed point defects. The presence of line defects effectively modulates the electronic properties of phosphorene, rendering the defect-containing phosphorene either metallic or semiconducting with a tunable band gap. Of particular interest is the fact that the SV-based line defect can behave as a metallic wire, suggesting a possibility to fabricate a circuit with subnanometer widths in the semiconducting phosphorene for nanoscale electronic application.
Parallel superconducting strip-line detectors: reset behaviour in the single-strip switch regime
International Nuclear Information System (INIS)
Casaburi, A; Heath, R M; Tanner, M G; Hadfield, R H; Cristiano, R; Ejrnaes, M; Nappi, C
2014-01-01
Superconducting strip-line detectors (SSLDs) are an important emerging technology for the detection of single molecules in time-of-flight mass spectrometry (TOF-MS). We present an experimental investigation of a SSLD laid out in a parallel configuration, designed to address selected single strip-lines operating in the single-strip switch regime. Fast laser pulses were tightly focused onto the device, allowing controllable nucleation of a resistive region at a specific location and study of the subsequent device response dynamics. We observed that in this regime, although the strip-line returns to the superconducting state after triggering, no effective recovery of the bias current occurs, in qualitative agreement with a phenomenological circuit simulation that we performed. Moreover, from theoretical considerations and by looking at the experimental pulse amplitude distribution histogram, we have the first confirmation of the fact that the phenomenological London model governs the current redistribution in these large area devices also after detection events. (paper)
Parallel superconducting strip-line detectors: reset behaviour in the single-strip switch regime
Casaburi, A.; Heath, R. M.; Tanner, M. G.; Cristiano, R.; Ejrnaes, M.; Nappi, C.; Hadfield, R. H.
2014-04-01
Superconducting strip-line detectors (SSLDs) are an important emerging technology for the detection of single molecules in time-of-flight mass spectrometry (TOF-MS). We present an experimental investigation of a SSLD laid out in a parallel configuration, designed to address selected single strip-lines operating in the single-strip switch regime. Fast laser pulses were tightly focused onto the device, allowing controllable nucleation of a resistive region at a specific location and study of the subsequent device response dynamics. We observed that in this regime, although the strip-line returns to the superconducting state after triggering, no effective recovery of the bias current occurs, in qualitative agreement with a phenomenological circuit simulation that we performed. Moreover, from theoretical considerations and by looking at the experimental pulse amplitude distribution histogram, we have the first confirmation of the fact that the phenomenological London model governs the current redistribution in these large area devices also after detection events.
Christiansen, Bo
2015-04-01
Linear regression methods are without doubt the most used approaches to describe and predict data in the physical sciences. They are often good first order approximations and they are in general easier to apply and interpret than more advanced methods. However, even the properties of univariate regression can lead to debate over the appropriateness of various models as witnessed by the recent discussion about climate reconstruction methods. Before linear regression is applied important choices have to be made regarding the origins of the noise terms and regarding which of the two variables under consideration that should be treated as the independent variable. These decisions are often not easy to make but they may have a considerable impact on the results. We seek to give a unified probabilistic - Bayesian with flat priors - treatment of univariate linear regression and prediction by taking, as starting point, the general errors-in-variables model (Christiansen, J. Clim., 27, 2014-2031, 2014). Other versions of linear regression can be obtained as limits of this model. We derive the likelihood of the model parameters and predictands of the general errors-in-variables model by marginalizing over the nuisance parameters. The resulting likelihood is relatively simple and easy to analyze and calculate. The well known unidentifiability of the errors-in-variables model is manifested as the absence of a well-defined maximum in the likelihood. However, this does not mean that probabilistic inference can not be made; the marginal likelihoods of model parameters and the predictands have, in general, well-defined maxima. We also include a probabilistic version of classical calibration and show how it is related to the errors-in-variables model. The results are illustrated by an example from the coupling between the lower stratosphere and the troposphere in the Northern Hemisphere winter.
Single-dose and fractionated irradiation of four human lung cancer cell lines in vitro
International Nuclear Information System (INIS)
Brodin, O.; Lennartsson, L.; Nilsson, S.
1991-01-01
Four established human lung cancer cell lines were exposed to single-dose irradiation. The survival curves of 2 small cell lung carcinomas (SCLC) were characterized by a limited capacity for repair with small and moderate shoulders with extrapolation numbers (n) of 1.05 and 1.60 respectively. Two non-small cell lung carcinoma (NSCLC) cell lines, one squamous cell (SQCLC) and one large cell (LCLC) had large shoulders with n-values of 73 and 15 respectively. The radiosensitivity when measured as D 0 did not, however, differ as much from cell line to cell line, with values from 1.22 to 1.65. The surviving fraction after 2 Gy (SF2) was 0.24 and 0.42 respectively in the SCLC cell lines and 0.90 and 0.88 respectively in the NSCLC cell lines. Fractionated irradiation delivered according to 3 different schedules was also investigated. All the schedules delivered a total dose of 10 Gy in 5 days and were applied in 1, 2 and 5 Gy dose fractions respectively. Survival followed the pattern found after single-dose irradiation; it was lowest in the SCLC cell line with the lowest SF and highest in the two NSCLC cell lines. In the SCLC cell lines all schedules were approximately equally efficient. In the LCLC and in the SQCLC cell lines, the 5 Gy schedule killed more cells than the 1 and 2 Gy schedules. The results indicate that the size of the shoulder of the survival curve is essential when choosing the most tumoricidal fractionation schedule. (orig.)
Directory of Open Access Journals (Sweden)
Corrado Dimauro
2010-01-01
Full Text Available Two methods of SNPs pre-selection based on single marker regression for the estimation of genomic breeding values (G-EBVs were compared using simulated data provided by the XII QTL-MAS workshop: i Bonferroni correction of the significance threshold and ii Permutation test to obtain the reference distribution of the null hypothesis and identify significant markers at P<0.01 and P<0.001 significance thresholds. From the set of markers significant at P<0.001, random subsets of 50% and 25% markers were extracted, to evaluate the effect of further reducing the number of significant SNPs on G-EBV predictions. The Bonferroni correction method allowed the identification of 595 significant SNPs that gave the best G-EBV accuracies in prediction generations (82.80%. The permutation methods gave slightly lower G-EBV accuracies even if a larger number of SNPs resulted significant (2,053 and 1,352 for 0.01 and 0.001 significance thresholds, respectively. Interestingly, halving or dividing by four the number of SNPs significant at P<0.001 resulted in an only slightly decrease of G-EBV accuracies. The genetic structure of the simulated population with few QTL carrying large effects, might have favoured the Bonferroni method.
Directory of Open Access Journals (Sweden)
ZHANG Fan
2015-06-01
Full Text Available Due to the discrete distribution computing errors and lack of adaptability are ubiquitous in the current straight line extraction for TLS data methods. A 3D straight line segment extraction method is proposed based on spherical projection for single station terrestrial laser point clouds. Firstly, horizontal and vertical angles of each laser point are calculated by means of spherical coordinates, intensity panoramic image according to the two angles is generated. Secondly, edges which include straight line features are detected from intensity panoramic image by using of edge detection algorithm. Thirdly, great circles are detected from edges of panoramic image using spherical Hough transform. According to the axiom that a straight line segment in 3D space is a spherical great circle after spherical projection, detecting great circles from spherical projected data sets is essentially detecting straight line segments from 3D data sets without spherical projection. Finally, a robust 3D straight line fitting method is employed to fitting the straight lines and calculating parameters of the straight line segments. Experiments using different data sets and comparison with other methods show the accuracy and applicability of the proposed method.
RADIAL VELOCITIES OF GALACTIC O-TYPE STARS. II. SINGLE-LINED SPECTROSCOPIC BINARIES
International Nuclear Information System (INIS)
Williams, S. J.; Gies, D. R.; Hillwig, T. C.; McSwain, M. V.; Huang, W.
2013-01-01
We report on new radial velocity measurements of massive stars that are either suspected binaries or lacking prior observations. This is part of a survey to identify and characterize spectroscopic binaries among O-type stars with the goal of comparing the binary fraction of field and runaway stars with those in clusters and associations. We present orbits for HDE 308813, HD 152147, HD 164536, BD–16°4826, and HDE 229232, Galactic O-type stars exhibiting single-lined spectroscopic variation. By fitting model spectra to our observed spectra, we obtain estimates for effective temperature, surface gravity, and rotational velocity. We compute orbital periods and velocity semiamplitudes for each system and note the lack of photometric variation for any system. These binaries probably appear single-lined because the companions are faint and because their orbital Doppler shifts are small compared to the width of the rotationally broadened lines of the primary.
Single step high-speed printing of continuous silver lines by laser-induced forward transfer
Energy Technology Data Exchange (ETDEWEB)
Puerto, D., E-mail: puerto@lp3.univ-mrs.fr [Aix-Marseille University, CNRS, LP3 laboratory Campus de Luminy, C.917, Marseille (France); Biver, E. [Aix-Marseille University, CNRS, LP3 laboratory Campus de Luminy, C.917, Marseille (France); Oxford Lasers Ltd., Unit 8, Moorbrook Park, Didcot, OX11 7HP (United Kingdom); Alloncle, A.-P.; Delaporte, Ph. [Aix-Marseille University, CNRS, LP3 laboratory Campus de Luminy, C.917, Marseille (France)
2016-06-30
Highlights: • We have performed an experimental study on laser micro-printing of silver nanoparticle inks. • We have achieved the printing of lines in a single pass at velocities of 17 m/s (1 MHz laser). • The ejection dynamics has been investigated by means of a time-resolved imaging technique. • The control of the donor film properties is of prime importance to print lines at high velocities. • Continuous conductive lines of silver inks are laser-printed on PET flexible substrates. - Abstract: The development of high-speed ink printing process by Laser-Induced Forward Transfer (LIFT) is of great interest for the printing community. To address the problems and the limitations of this process that have been previously identified, we have performed an experimental study on laser micro-printing of silver nanoparticle inks by LIFT and demonstrated for the first time the printing of continuous conductive lines in a single pass at velocities of 17 m/s using a 1 MHz repetition rate laser. We investigated the printing process by means of a time-resolved imaging technique to visualize the ejection dynamics of single and adjacent jets. The control of the donor film properties is of prime importance to achieve single step printing of continuous lines at high velocities. We use a 30 ps pulse duration laser with a wavelength of 343 nm and a repetition rate from 0.2 to 1 MHz. A galvanometric mirror head controls the distance between two consecutives jets by scanning the focused beam along an ink-coated donor substrate at different velocities. Droplets and lines of silver inks are laser-printed on glass and PET flexible substrates and we characterized their morphological quality by atomic force microscope (AFM) and optical microscope.
Linewidth statistics of single InGaAs quantum dot photolumincescence lines
DEFF Research Database (Denmark)
Leosson, Kristjan; Jensen, Jacob Riis; Hvam, Jørn Märcher
2000-01-01
We have used photoluminescence spectroscopy with high spatial and spectral resolution to measure the linewidths of single emission lines from In0.5Ga0.5As/GaAs self-assembled quantum dots. At 10 K, we find a broad, asymmetric distribution of linewidths with a maximum at 50 mu eV. The distribution......-dot luminescence lines depends only weakly on temperature up to 50 K, showing a broadening of 0.4 mu eV/K. Above 50 K, a thermally activated behavior of the linewidth is observed. This temperature dependence is consistent with the discrete energy level structure of the dots....
Targeted genetics in Drosophila cell lines: Inserting single transgenes in vitro.
Manivannan, Sathiya N; Simcox, Amanda
2016-07-02
A long-standing problem with analyzing transgene expression in tissue-culture cells is the variation caused by random integration of different copy numbers of transfected transgenes. In mammalian cells, single transgenes can be inserted by homologous recombination but this process is inefficient in Drosophila cells. To tackle this problem, our group, and the Cherbas group, used recombination-mediated cassette exchange (RMCE) to introduce single-copy transgenes into specific locations in the Drosophila genome. In both cases, ϕC31 was used to catalyze recombination between its target sequences attP in the genome, and attB flanking the donor sequence. We generated cell lines de novo with a single attP-flanked cassette for recombination, whereas, Cherbas et al. introduced a single attP-flanked cassette into existing cell lines. In both approaches, a 2-drug selection scheme was used to select for cells with a single copy of the donor sequence inserted by RMCE and against cells with random integration of multiple copies. Here we describe the general advantages of using RMCE to introduce genes into fly cells, the different attributes of the 2 methods, and how future work could make use of other recombinases and CRISPR/Cas9 genome editing to further enable genetic manipulation of Drosophila cells in vitro.
Strong field line shapes and photon statistics from a single molecule under anomalous noise.
Sanda, Frantisek
2009-10-01
We revisit the line-shape theory of a single molecule with anomalous stochastic spectral diffusion. Waiting time profiles for bath induced spectral jumps in the ground and excited states become different when a molecule, probed by continuous-wave laser field, reaches the steady state. This effect is studied for the stationary dichotomic continuous-time-random-walk spectral diffusion of a single two-level chromophore with power-law distributions of waiting times. Correlated waiting time distributions, line shapes, two-point fluorescence correlation function, and Mandel Q parameter are calculated for arbitrary magnitude of laser field. We extended previous weak field results and examined the breakdown of the central limit theorem in photon statistics, indicated by asymptotic power-law growth of Mandel Q parameter. Frequency profile of the Mandel Q parameter identifies the peaks of spectrum, which are related to anomalous spectral diffusion dynamics.
Meta-heuristic and Constraint-Based Approaches for Single-Line Railway Timetabling
Barber, Federico; Ingolotti, Laura; Lova, Antonio; Tormos, Pilar; Salido, Miguel A.
This chapter is devoted to recent advances in heuristic and metaheuristic procedures, arising from the areas of Computer Science and Artificial Intelligence, which are able to cope with large scale problems as those in single-line railway timetable optimization. Timetable design is a central problem in railway planning. In the basic timetabling problem, we are given a line plan as well as demand and infrastructure information. The goal is to compute timetables for passengers and cargo trains that satisfy infrastructure capacity and achieve multicriteria objectives: minimal passenger waiting time (both at changeovers and onboard), efficient use of trains, etc. Due to its central role in the planning process of railway scheduling, timetable design has many interfaces with other classical problems: line planning, vehicle scheduling, and delay management.
Arterial hypertension: second-line treatment. Try other single-agent treatments.
2008-06-01
(1) Reliable evidence supports the use of thiazide diuretics (chlortalidone or hydrochlorothiazide) as first-line treatment for uncomplicated arterial hypertension. (2) When patients fail to reach blood pressure targets with well-conducted treatment with thiazide diuretics, or this treatment is poorly tolerated, what are the best second-line options? To answer this question, we reviewed the available evidence, based on our standard in-house methodology. (3) We found no published trials specifically designed to evaluate second-line antihypertensive treatments in cardiovascular prevention. There were no available trials of dual- versus single-agent therapy after failure of a thiazide diuretic. (4) When the blood pressure target is not reached, inadequate drug efficacy is only one of several possible causes. Various other factors affecting blood pressure should also be investigated. (5) Dual-agent therapy carries an increased risk of adverse effects and drug interactions compared to monotherapy. (6) There is no consensus among clinical practice guidelines on second-line antihypertensive therapy. However, to minimise the risk of adverse effects, it is clearly better to select single-agent therapy with a drug that has been shown to prevent cardiovascular events in first-line treatment of otherwise healthy hypertensive patients. Possible options include: angiotensin-converting-enzyme inhibitors, angiotensin II antagonists, calcium channel blockers or betablockers. In patients over the age of 60, betablockers seem less effective that the other drugs in preventing strokes. (7) There is too little evidence to choose a specific third-line combination rather than another. However, any adverse effects that the patient experienced during prior treatments should be taken into account.
Conservative site-specific and single-copy transgenesis in human LINE-1 elements.
Vijaya Chandra, Shree Harsha; Makhija, Harshyaa; Peter, Sabrina; Myint Wai, Cho Mar; Li, Jinming; Zhu, Jindong; Ren, Zhonglu; D'Alcontres, Martina Stagno; Siau, Jia Wei; Chee, Sharon; Ghadessy, Farid John; Dröge, Peter
2016-04-07
Genome engineering of human cells plays an important role in biotechnology and molecular medicine. In particular, insertions of functional multi-transgene cassettes into suitable endogenous sequences will lead to novel applications. Although several tools have been exploited in this context, safety issues such as cytotoxicity, insertional mutagenesis and off-target cleavage together with limitations in cargo size/expression often compromise utility. Phage λ integrase (Int) is a transgenesis tool that mediates conservative site-specific integration of 48 kb DNA into a safe harbor site of the bacterial genome. Here, we show that an Int variant precisely recombines large episomes into a sequence, term edattH4X, found in 1000 human Long INterspersed Elements-1 (LINE-1). We demonstrate single-copy transgenesis through attH4X-targeting in various cell lines including hESCs, with the flexibility of selecting clones according to transgene performance and downstream applications. This is exemplified with pluripotency reporter cassettes and constitutively expressed payloads that remain functional in LINE1-targeted hESCs and differentiated progenies. Furthermore, LINE-1 targeting does not induce DNA damage-response or chromosomal aberrations, and neither global nor localized endogenous gene expression is substantially affected. Hence, this simple transgene addition tool should become particularly useful for applications that require engineering of the human genome with multi-transgenes. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Field Geometric Calibration Method for Line Structured Light Sensor Using Single Circular Target
Directory of Open Access Journals (Sweden)
Tianfei Chen
2017-01-01
Full Text Available To achieve fast calibration of line structured light sensor, a geometric calibration approach based on single circular calibration target is proposed. The proposed method uses the circular points to establish linear equations, and according to the angle constraint, the camera intrinsic parameters can be calculated through optimization. Then, the light plane calibration is accomplished in two steps. Firstly, when the vanishing lines of target plane at various postures are obtained, the intersections between vanishing lines and laser stripe can be computed, and the normal vector of light plane can be calibrated via line fitting method using intersection points. After that, the distance from the origin of camera coordinate system to the light plane can be derived based on the model of perspective-three-point. The actual experimental result shows that this calibration method has high accuracy, its average measuring accuracy is 0.0451 mm, and relative error is 0.2314%. In addition, the entire calibration process has no complex operations. It is simple, convenient, and suitable for calibration on sites.
Single-shot in-line digital holography without twin image
Nomura, Takanori
2018-01-01
In-line digital holography is conventional but still attractive because of its simple optical setup. In general, sequential phase-shifting technique is mandatory to remove twin-image which makes the reconstructed image quality low. However, sequential phase-shifting technique requires multiple recording. Multiple recording means that it is not suitable for a dynamic phenomenon. In this paper, two kinds of a single-shot in-line digital holography without twin-image using a diffused illumination are presented. One is a generalized phase-shifting digital holography and the other is a computational removal of twin-image. The ideas and their experimental results are given to confirm the feasibility.
2000-08-01
Georgetown U. Med. Ctr., 3900 Reservoir Rd., Washington, DC 20007; 2Applied Mathematics Program, Johns Hopkins University, 9601 Medical Center Dr., Rockville...TERMS Nonlinear regresion , Monte-Carlo 15. NUMBER OF PAGES randomization, Scheffe’s test, radioligand binding 16. PRICE CODE 24 17. SECURITY 18...appropriate for this situation. Indeed, here it is necessary to formulate this problem as a multiple linear regression model expressed with the aid of
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Dongxiao Niu
2017-12-01
Full Text Available Accurate and stable prediction of icing thickness on transmission lines is of great significance for ensuring the safe operation of the power grid. In order to improve the accuracy and stability of icing prediction, an innovative prediction model based on the generalized regression neural network (GRNN and the fruit fly optimization algorithm (FOA is proposed. Firstly, a feature selection method based on the data inconsistency rate (IR is adopted to select the optimal feature, which aims to reduce redundant input vectors. Then, the fruit FOA is utilized for optimization of smoothing factor for the GRNN. Lastly, the icing forecasting method FOA-IR-GRNN is established. Two cases in different locations and different months are selected to validate the proposed model. The results indicate that the new hybrid FOA-IR-GRNN model presents better accuracy, robustness, and generality in icing forecasting.
International Nuclear Information System (INIS)
Ballini, J.-P.; Cazes, P.; Turpin, P.-Y.
1976-01-01
Analysing the histogram of anode pulse amplitudes allows a discussion of the hypothesis that has been proposed to account for the statistical processes of secondary multiplication in a photomultiplier. In an earlier work, good agreement was obtained between experimental and reconstructed spectra, assuming a first dynode distribution including two Poisson distributions of distinct mean values. This first approximation led to a search for a method which could give the weights of several Poisson distributions of distinct mean values. Three methods have been briefly exposed: classical linear regression, constraint regression (d'Esopo's method), and regression on variables subject to error. The use of these methods gives an approach of the frequency function which represents the dispersion of the punctual mean gain around the whole first dynode mean gain value. Comparison between this function and the one employed in Polya distribution allows the statement that the latter is inadequate to describe the statistical process of secondary multiplication. Numerous spectra obtained with two kinds of photomultiplier working under different physical conditions have been analysed. Then two points are discussed: - Does the frequency function represent the dynode structure and the interdynode collection process. - Is the model (the multiplication process of all dynodes but the first one, is Poissonian) valid whatever the photomultiplier and the utilization conditions. (Auth.)
Charge transport across a single-Cooper-pair transistor coupled to a resonant transmission line
Energy Technology Data Exchange (ETDEWEB)
Leppaekangas, Juha [Institut fuer Theoretische Festkoerperphysik, Karlsruhe Institute of Technology, D-76128 Karlsruhe (Germany); Department of Physical Sciences, University of Oulu, FI-90014 Oulu (Finland); Pashkin, Yuri [NEC Nano Electronics Research Laboratories, RIKEN Advanced Science Institute, Tsukuba, Ibaraki 305-8501 (Japan); Thuneberg, Erkki [Department of Physical Sciences, University of Oulu, FI-90014 Oulu (Finland)
2010-07-01
We have investigated charge transport in ultrasmall superconducting single and double Josephson junctions coupled to a transmission-line resonator. The microstrip resonator is naturally formed by the on-chip leads and the sample holder. We observe equidistant peaks in the transport characteristics of both types of devices and attribute them to the process involving simultaneous tunneling of Cooper pairs and photon emission into the resonator. The experimental data is well reproduced with the orthodox model of Cooper pair tunneling that accounts for the microwave photon emission into the resonator.
Liu, Yingying; Sowmya, Arcot; Khamis, Heba
2018-01-01
Manually measured anthropometric quantities are used in many applications including human malnutrition assessment. Training is required to collect anthropometric measurements manually, which is not ideal in resource-constrained environments. Photogrammetric methods have been gaining attention in recent years, due to the availability and affordability of digital cameras. The primary goal is to demonstrate that height and mid-upper arm circumference (MUAC)-indicators of malnutrition-can be accurately estimated by applying linear regression to distance measurements from photographs of participants taken from five views, and determine the optimal view combinations. A secondary goal is to observe the effect on estimate error of two approaches which reduce complexity of the setup, computational requirements and the expertise required of the observer. Thirty-one participants (11 female, 20 male; 18-37 years) were photographed from five views. Distances were computed using both camera calibration and reference object techniques from manually annotated photos. To estimate height, linear regression was applied to the distances between the top of the participants head and the floor, as well as the height of a bounding box enclosing the participant's silhouette which eliminates the need to identify the floor. To estimate MUAC, linear regression was applied to the mid-upper arm width. Estimates were computed for all view combinations and performance was compared to other photogrammetric methods from the literature-linear distance method for height, and shape models for MUAC. The mean absolute difference (MAD) between the linear regression estimates and manual measurements were smaller compared to other methods. For the optimal view combinations (smallest MAD), the technical error of measurement and coefficient of reliability also indicate the linear regression methods are more reliable. The optimal view combination was the front and side views. When estimating height by linear
Plane-based optimization for 3D object reconstruction from single line drawings.
Liu, Jianzhuang; Cao, Liangliang; Li, Zhenguo; Tang, Xiaoou
2008-02-01
In previous optimization-based methods of 3D planar-faced object reconstruction from single 2D line drawings, the missing depths of the vertices of a line drawing (and other parameters in some methods) are used as the variables of the objective functions. A 3D object with planar faces is derived by finding values for these variables that minimize the objective functions. These methods work well for simple objects with a small number N of variables. As N grows, however, it is very difficult for them to find expected objects. This is because with the nonlinear objective functions in a space of large dimension N, the search for optimal solutions can easily get trapped into local minima. In this paper, we use the parameters of the planes that pass through the planar faces of an object as the variables of the objective function. This leads to a set of linear constraints on the planes of the object, resulting in a much lower dimensional nullspace where optimization is easier to achieve. We prove that the dimension of this nullspace is exactly equal to the minimum number of vertex depths which define the 3D object. Since a practical line drawing is usually not an exact projection of a 3D object, we expand the nullspace to a larger space based on the singular value decomposition of the projection matrix of the line drawing. In this space, robust 3D reconstruction can be achieved. Compared with two most related methods, our method not only can reconstruct more complex 3D objects from 2D line drawings, but also is computationally more efficient.
Running the number line: Rapid shifts of attention in single-digit arithmetic.
Mathieu, Romain; Gourjon, Audrey; Couderc, Auriane; Thevenot, Catherine; Prado, Jérôme
2016-01-01
It has been recently proposed that adults might solve single-digit addition and subtraction problems by rapidly moving through an ordered representation of numbers. In the present study, we tested whether these movements manifest themselves by on-line shifts of attention during arithmetic problem-solving. In two experiments, adult participants were presented with single-digit addition, subtraction and multiplication problems. Operands and operator were presented sequentially on the screen. Although both the first operand and the operator were presented at the center of the screen, the second operand was presented either to the left or to the right side of space. We found that addition problems were solved faster when the second operand appeared to the right than to the left side (Experiments 1 & 2). In contrast, subtraction problems were solved faster when the second operand appeared to the left than to the right side (Experiment 1). No operation-dependent spatial bias was observed in the same time window when the second operand was zero (Experiment 1), and no bias was observed when the operation was a multiplication (Experiment 2). Therefore, our results demonstrate that solving single-digit addition and subtraction, but not multiplication, is associated with horizontal shifts of attention. Our findings support the idea that mental movements to the left or right of a sequential representation of numbers are elicited during single-digit arithmetic. Copyright © 2015 Elsevier B.V. All rights reserved.
DEFF Research Database (Denmark)
Puig Arnavat, Maria; López-Villada, Jesús; Bruno, Joan Carles
2010-01-01
of the characteristic equation method developed by Kühn and Ziegler (2005) is the simplest and that it provides similar or better accuracy than the other approach. This selected approach has been used to fit catalogue and experimental data of single-effect chillers and has been extended to double-effect commercial......Two approaches to the characteristic equation method have been compared in order to find a simple model that best describes the performance of thermal chillers. After comparing the results obtained using experimental data from a single-effect absorption chiller, we concluded that the adaptation...
Single-phased Fault Location on Transmission Lines Using Unsynchronized Voltages
Directory of Open Access Journals (Sweden)
ISTRATE, M.
2009-10-01
Full Text Available The increased accuracy into the fault's detection and location makes it easier for maintenance, this being the reason to develop new possibilities for a precise estimation of the fault location. In the field literature, many methods for fault location using voltages and currents measurements at one or both terminals of power grids' lines are presented. The double-end synchronized data algorithms are very precise, but the current transformers can limit the accuracy of these estimations. The paper presents an algorithm to estimate the location of the single-phased faults which uses only voltage measurements at both terminals of the transmission lines by eliminating the error due to current transformers and without introducing the restriction of perfect data synchronization. In such conditions, the algorithm can be used with the actual equipment of the most power grids, the installation of phasor measurement units with GPS system synchronized timer not being compulsory. Only the positive sequence of line parameters and sources are used, thus, eliminating the incertitude in zero sequence parameter estimation. The algorithm is tested using the results of EMTP-ATP simulations, after the validation of the ATP models on the basis of registered results in a real power grid.
Radiosensitivity evaluation of Human tumor cell lines by single cell gel electrophoresis
International Nuclear Information System (INIS)
Zhang Yipei; Cao Jia; Wang Yan; Du Liqing; Li Jin; Wang Qin; Fan Feiyue; Liu Qiang
2011-01-01
Objective: To explore the feasibility of determining radiosensitivity of human tumor cell lines in vitro using single cell gel electrophoresis (SCGE). Methods: Three human tumor cell lines were selected in this study, HepG 2 , EC-9706 and MCF-7. The surviving fraction (SF) and DNA damage were detected by MTT assay, nested PCR technique and comet assay respectively. Results: MTT assay: The SF of HepG 2 and EC-9706 after irradiated by 2, 4 and 8 Gy was lower significantly than that of MCF-7, which showed that the radiosensitivity of HepG 2 and EC-9706 was higher than that of MCF-7. But there was no statistical difference of SF between HepG 2 and EC-9706. SCGE: The difference of radiosensitivity among these three tumor cell lines was significant after 8 Gy γ-ray irradiation. Conclusion: The multi-utilization of many biological parameter is hopeful to evaluate the radiosensitivity of tumor cells more objectively and exactly. (authors)
International Nuclear Information System (INIS)
Sun, Weiyuan; Liu, Zhiguo; Sun, Tianxi; Peng, Song; Ma, Yongzhong; Ding, Xunliang
2014-01-01
A new device using an ellipsoidal single-bounce monocapillary X-ray optics was numerically designed to realize in-line X-ray phase-contrast imaging by using conventional laboratory X-ray source with a large spot. Numerical simulation results validated the effectiveness of the proposed device and approach. The ellipsoidal single-bounce monocapillary X-ray optics had potential applications in the in-line phase contrast imaging with polychromatic X-rays
Directory of Open Access Journals (Sweden)
Goar Mosoyan
Full Text Available BACKGROUND: Breast cancer cell lines are widely used tools to investigate breast cancer biology and to develop new therapies. Breast cancer tissue contains molecularly heterogeneous cell populations. Thus, it is important to understand which cell lines best represent the primary tumor and have similarly diverse phenotype. Here, we describe the development of five breast cancer cell lines from a single patient's breast cancer tissue. We characterize the molecular profiles, tumorigenicity and metastatic ability in vivo of all five cell lines and compare their responsiveness to 4-hydroxytamoxifen (4-OHT treatment. METHODS: Five breast cancer cell lines were derived from a single patient's primary breast cancer tissue. Expression of different antigens including HER2, estrogen receptor (ER, CK8/18, CD44 and CD24 was determined by flow cytometry, western blotting and immunohistochemistry (IHC. In addition, a Fluorescent In Situ Hybridization (FISH assay for HER2 gene amplification and p53 genotyping was performed on all cell lines. A xenograft model in nude mice was utilized to assess the tumorigenic and metastatic abilities of the breast cancer cells. RESULTS: We have isolated, cloned and established five new breast cancer cell lines with different tumorigenicity and metastatic abilities from a single primary breast cancer. Although all the cell lines expressed low levels of ER, their growth was estrogen-independent and all had high-levels of expression of mutated non-functional p53. The HER2 gene was rearranged in all cell lines. Low doses of 4-OHT induced proliferation of these breast cancer cell lines. CONCLUSIONS: All five breast cancer cell lines have different antigenic expression profiles, tumorigenicity and organ specific metastatic abilities although they derive from a single tumor. None of the studied markers correlated with tumorigenic potential. These new cell lines could serve as a model for detailed genomic and proteomic analyses to
Fernández-Espinosa, Antonio J
2016-01-01
This study presents a systematized method for predicting water content, fat content and free acidity in olive fruits by on-line NIR Spectroscopy combined with chemometric techniques (PCA, LDA and PLSR). Three cultivar varieties of Olea europaea - Hojiblanca cv., Picual cv. and Arbequina cv. - were monitored. Five olive cultivation areas of Southern Spain (Andalucia) and Southern Portugal (Alentejo) were studied in 2011 and 2012. 465 olive samples were collected during the ripening process (non-mature olives) and compared with other 203 samples of mature olives collected at the final ripening stage. NIR spectra were measured directly in the olive fruits in the wavelength region from 1000 to 2300 nm in reflectance mode. The reference analyses were performed on the olive paste by oven drying for the moisture, by mini-Soxhlet extraction for the fat content and by acid titration of the oil extracted from the olive paste. Calibrations and predictive models were developed by Partial Least Square Regression (PLSR) previous Principal Component and Linear Discriminant analyses (PCA and LDA) were employed as exploratory and clean-up tools of data sets. The final models obtained for the total samples showed acceptable statistics of prediction with R(2)=0.88, RMSEV%=4.88 and RMSEP%=4.98 for water content, R(2)=0.76, RMSECV%=19.5 and RMSEP%=20.0 for fat content and R(2)=0.83, RMSECV%=36.8 and RMSEP%=38.8 for free acidity. Regression coefficients were better for only one maturity state (ripe period) than for olive fruit with different composition (ripening period). All models obtained were applied to predict LQPs on a new set of samples with satisfactory results, a good prediction potential of the models. Copyright © 2015 Elsevier B.V. All rights reserved.
Wang, Haijun; Gao, Xinbo; Zhang, Kaibing; Li, Jie
2017-05-03
Gaussian process regression (GPR) is an effective statistical learning method for modeling non-linear mapping from an observed space to an expected latent space. When applying it to example learning-based super-resolution (SR), two outstanding issues remain. One is its high computational complexity restricts SR application when a large dataset is available for learning task. The other is that the commonly used Gaussian likelihood in GPR is incompatible with the true observation model for SR reconstruction. To alleviate the above two issues, we propose a GPR-based SR method by using dictionary-based sampling and student-t likelihood, called DSGPR. Considering that dictionary atoms effectively span the original training sample space, we adopt a dictionary-based sampling strategy by combining all the neighborhood samples of each atom into a compact representative training subset so as to reduce the computational complexity. Based on statistical tests, we statistically validate that Studentt likelihood is more suitable to build the observation model for SR problem. Extensive experimental results show that the proposed method outperforms other competitors and produces more pleasing details in texture regions.
International Nuclear Information System (INIS)
Flores-Lamas, H.
1994-01-01
An analytic expansion, to arbitrary accuracy, of the transmission integral (TI) for a single Moessbauer line is presented. This serves for calculating the effective thickness (T a ) of an absorber in Moessbauer spectroscopy even for T a >10. The new analytic expansion arises from substituting in the TI expression the exponential function by a Chebyshev polynomials series. A very fast converging series for TI is obtained and used as a test function in a least squares fit to a simulated spectrum. The test yields satisfactory results. The area and height parameters calculated were found to be in good agreement with earlier results. The present analytic method assumes that the source and absorber widths are different. ((orig.))
The Single Minute Exchange of Die Methodology in a High-Mix Processing Line
Directory of Open Access Journals (Sweden)
Filla Jan
2016-06-01
Full Text Available Because of turbulence in the economic environment, enterprises must react flexibly to the changing demands of their customers. Thus, a changeover process is required. If an enterprise has a large product portfolio, there are basically only two process options; to integrate production into large batches or to change the production programme frequently. Frequent changes associated with the changeover process of machinery are optimized by using the SMED method. The main goal of this paper is to apply SMED (Single Minute Exchange of Die to a High-Mix processing line. The case study is undertaken in a flat glass processing company which manufactures hundreds of types of products. The results of the case study demonstrate that it is possible to save up to 30% annually of the time currently spent on changeovers.
Control of single-phase islanded PV/battery minigrids based on power-line signaling
DEFF Research Database (Denmark)
Quintana, Pablo; Guerrero, Josep M.; Dragicevic, Tomislav
2014-01-01
Power regulation of all converter units in a micro-grid should not be only determined by load demand, but also by the available power of each unit, i.e. a converter fed by a battery. Energy management control is essential in order to handle the variety of prime movers which may include different...... should be utilized as efficiently as possible. This paper proposes a coordinated control strategy based on power-line signaling (PLS), instead of common communications, for a single-phase minigrid in which each unit can operate in different operation modes taking into account the resource limitation....... The whole system is explained ahead and finally, Hardware in the loop results obtained with a dSPACE are presented in order to validate the proposed control strategy....
A new on-line luminometer and beam conditions monitor using single crystal diamond sensors
CMS Collaboration
2015-01-01
Instrumentation near the beam-pipe requires extremely radiation hard sensors. Inside CMS two rings instrumented with 12 single crystal diamond sensors each are installed on both sides of the interaction point. The sensors are subdivided in two pads, and each pad is read out by a dedicated fast radiation hard ASIC in 130 nm CMOS technology. Due to the excellent time resolution collision products will be separated from machine induced background. In the backend a dead-time less histogramming unit is used, and a fast microTCA system with GHz sampling rate is under development. The detector will measure both the on-line luminosity and the background bunch-by-bunch. The performance of a prototype detector in a test-beam will be reported, and results from the operation during data taking will be presented.
A new on-line luminometer and beam conditions monitor using single crystal diamond sensors
Karacheban, Olena
2015-01-01
Instrumentation near the beam-pipe requires extremely radiation hardsensors. Inside CMS two rings instrumented with 12 single crystal diamondsensors each are installed on both sides of the interaction point. Thesensors are subdivided in two pads, and each pad is read out by adedicated fast radiation hard ASIC in 130 nm CMOS technology.Due to the excellent time resolution collision products will be separatedfrom machine induced background. In the backend a dead-time lesshistogramming unit is udsed, and a fast microTCA system with GHz samplingrate is under development.The detector will measure both the on-line luminosity and the backgroundbunch-by-bunch.The performance of a prototype detector in a test-beam will be reported,and results from the operation during data taking will be presented.
Weng, Jiawen; Clark, David C.; Kim, Myung K.
2016-05-01
A numerical reconstruction method based on compressive sensing (CS) for self-interference incoherent digital holography (SIDH) is proposed to achieve sectional imaging by single-shot in-line self-interference incoherent hologram. The sensing operator is built up based on the physical mechanism of SIDH according to CS theory, and a recovery algorithm is employed for image restoration. Numerical simulation and experimental studies employing LEDs as discrete point-sources and resolution targets as extended sources are performed to demonstrate the feasibility and validity of the method. The intensity distribution and the axial resolution along the propagation direction of SIDH by angular spectrum method (ASM) and by CS are discussed. The analysis result shows that compared to ASM the reconstruction by CS can improve the axial resolution of SIDH, and achieve sectional imaging. The proposed method may be useful to 3D analysis of dynamic systems.
pH sensing through a single optical fibre using SERS and CMOS SPAD line arrays.
Ehrlich, K; Kufcsák, A; McAughtrie, S; Fleming, H; Krstajic, N; Campbell, C J; Henderson, R K; Dhaliwal, K; Thomson, R R; Tanner, M G
2017-12-11
Full exploitation of fibre Raman probes has been limited by the obstruction of weak Raman signals by background fluorescence of the sample and the intrinsic Raman signal of the delivery fibre. Here we utilised functionalised gold nanoshells (NS) to take advantage of the surface-enhanced Raman spectroscopy (SERS) effect to enhance the pH responsive spectrum of 4-mercaptobenzoic acid (MBA). However, the fibre background is still dominant. Using the photon arrival time-resolving capability of a CMOS single-photon avalanche diode (SPAD) based line sensor, we recover the SERS spectrum without a fibre background in a 10 s measurement. In this manner, pH sensing through a multimode fibre at a low excitation power that is safe for future in vivo applications, with short acquisition times (10 or 60 s), is demonstrated. A measurement precision of ± 0.07 pH units is thus achieved.
Insulin activates single amiloride-blockable Na channels in a distal nephron cell line (A6).
Marunaka, Y; Hagiwara, N; Tohda, H
1992-09-01
Using the patch-clamp technique, we studied the effect of insulin on an amiloride-blockable Na channel in the apical membrane of a distal nephron cell line (A6) cultured on permeable collagen films for 10-14 days. NPo (N, number of channels per patch membrane; Po, average value of open probability of individual channels in the patch) under baseline conditions was 0.88 +/- 0.12 (SE)(n = 17). After making cell-attached patches on the apical membrane which contained Na channels, insulin (1 mU/ml) was applied to the serosal bath. While maintaining the cell-attached patch, NPo significantly increased to 1.48 +/- 0.19 (n = 17; P less than 0.001) after 5-10 min of insulin application. The open probability of Na channels was 0.39 +/- 0.01 (n = 38) under baseline condition, and increased to 0.66 +/- 0.03 (n = 38, P less than 0.001) after addition of insulin. The baseline single-channel conductance was 4pS, and neither the single-channel conductance nor the current-voltage relationship was significantly changed by insulin. These results indicate that insulin increases Na absorption in the distal nephron by increasing the open probability of the amiloride-blockable Na channel.
Directory of Open Access Journals (Sweden)
Minas Bakalchev
2015-10-01
Full Text Available The perception of elements in a system often creates their interdependence, interconditionality, and suppression. The lines from a basic geometrical element have become the model of a reductive world based on isolation according to certain criteria such as function, structure, and social organization. Their traces are experienced in the contemporary world as fragments or ruins of a system of domination of an assumed hierarchical unity. How can one release oneself from such dependence or determinism? How can the lines become less “systematic” and forms more autonomous, and less reductive? How is a form released from modernistic determinism on the new controversial ground? How can these elements or forms of representation become forms of action in the present complex world? In this paper, the meaning of lines through the ideas of Le Corbusier, Leonidov, Picasso, and Hitchcock is presented. Spatial research was made through a series of examples arising from the projects of the architectural studio “Residential Transformations”, which was a backbone for mapping the possibilities ranging from playfulness to exactness, as tactics of transformation in the different contexts of the contemporary world.
Hu, L; Liang, M; Mouraux, A; Wise, R G; Hu, Y; Iannetti, G D
2011-12-01
Across-trial averaging is a widely used approach to enhance the signal-to-noise ratio (SNR) of event-related potentials (ERPs). However, across-trial variability of ERP latency and amplitude may contain physiologically relevant information that is lost by across-trial averaging. Hence, we aimed to develop a novel method that uses 1) wavelet filtering (WF) to enhance the SNR of ERPs and 2) a multiple linear regression with a dispersion term (MLR(d)) that takes into account shape distortions to estimate the single-trial latency and amplitude of ERP peaks. Using simulated ERP data sets containing different levels of noise, we provide evidence that, compared with other approaches, the proposed WF+MLR(d) method yields the most accurate estimate of single-trial ERP features. When applied to a real laser-evoked potential data set, the WF+MLR(d) approach provides reliable estimation of single-trial latency, amplitude, and morphology of ERPs and thereby allows performing meaningful correlations at single-trial level. We obtained three main findings. First, WF significantly enhances the SNR of single-trial ERPs. Second, MLR(d) effectively captures and measures the variability in the morphology of single-trial ERPs, thus providing an accurate and unbiased estimate of their peak latency and amplitude. Third, intensity of pain perception significantly correlates with the single-trial estimates of N2 and P2 amplitude. These results indicate that WF+MLR(d) can be used to explore the dynamics between different ERP features, behavioral variables, and other neuroimaging measures of brain activity, thus providing new insights into the functional significance of the different brain processes underlying the brain responses to sensory stimuli.
Second-line immunosuppressive treatment of childhood nephrotic syndrome: a single-center experience.
Kim, J; Patnaik, N; Chorny, N; Frank, R; Infante, L; Sethna, C
2014-01-01
Most cases of idiopathic nephrotic syndrome in childhood are responsive to corticosteroids. However, there is a small group of children that demonstrate steroid resistance (steroid-resistant nephrotic syndrome; SRNS), steroid dependence, or that frequently relapse (frequent-relapse steroid-sensitive nephrotic syndrome; FR-SSNS) which are more clinically difficult to treat. Therefore, second-line immunosuppressants, such as alkylating agents, calcineurin inhibitors, antimetabolites and, more recently, rituximab, have been used with varying success. The objective was to evaluate the response rates of various second-line therapies in the treatment of childhood nephrotic syndrome. A retrospective chart review of pediatric subjects with idiopathic nephrotic syndrome was conducted at a single tertiary care center (2007-2012). Drug responses were classified as complete response, partial response, and no response. Of the 188 charts reviewed, 121 children were classified as SSNS and 67 children as SRNS; 58% were classified as FR-SSNS. Sixty-five subjects were diagnosed with focal segmental glomerulosclerosis via biopsy. Follow-up ranged from 6 months to 21 years. The combined rate of complete and partial response for mycophenolate mofetil (MMF) was 65% (33/51) in SSNS and 67% (6/9) in SRNS. For tacrolimus, the response rate was 96% (22/23) for SSNS and 77% (17/22) for SRNS. Eighty-three percent (5/6) of SSNS subjects treated with rituximab went into complete remission; 60% relapsed after B-cell repletion. Eight refractory subjects were treated with combined MMF/tacrolimus/corticosteroid therapy with a 75% response rate. Our experience demonstrates that older medications can be replaced with newer ones such as MMF, tacrolimus, and rituximab with good outcomes and better side effect profiles. The treatment of refractory cases with combination therapy is promising.
Second-Line Immunosuppressive Treatment of Childhood Nephrotic Syndrome: A Single-Center Experience
Directory of Open Access Journals (Sweden)
J. Kim
2014-01-01
Full Text Available Objective: Most cases of idiopathic nephrotic syndrome in childhood are responsive to corticosteroids. However, there is a small group of children that demonstrate steroid resistance (steroid-resistant nephrotic syndrome; SRNS, steroid dependence, or that frequently relapse (frequent-relapse steroid-sensitive nephrotic syndrome; FR-SSNS which are more clinically difficult to treat. Therefore, second-line immunosuppressants, such as alkylating agents, calcineurin inhibitors, antimetabolites and, more recently, rituximab, have been used with varying success. The objective was to evaluate the response rates of various second-line therapies in the treatment of childhood nephrotic syndrome. Study Design: A retrospective chart review of pediatric subjects with idiopathic nephrotic syndrome was conducted at a single tertiary care center (2007-2012. Drug responses were classified as complete response, partial response, and no response. Results: Of the 188 charts reviewed, 121 children were classified as SSNS and 67 children as SRNS; 58% were classified as FR-SSNS. Sixty-five subjects were diagnosed with focal segmental glomerulosclerosis via biopsy. Follow-up ranged from 6 months to 21 years. The combined rate of complete and partial response for mycophenolate mofetil (MMF was 65% (33/51 in SSNS and 67% (6/9 in SRNS. For tacrolimus, the response rate was 96% (22/23 for SSNS and 77% (17/22 for SRNS. Eighty-three percent (5/6 of SSNS subjects treated with rituximab went into complete remission; 60% relapsed after B-cell repletion. Eight refractory subjects were treated with combined MMF/tacrolimus/corticosteroid therapy with a 75% response rate. Conclusion: Our experience demonstrates that older medications can be replaced with newer ones such as MMF, tacrolimus, and rituximab with good outcomes and better side effect profiles. The treatment of refractory cases with combination therapy is promising.
Baba, Toshimi; Gotoh, Yusaku; Yamaguchi, Satoshi; Nakagawa, Satoshi; Abe, Hayato; Masuda, Yutaka; Kawahara, Takayoshi
2017-08-01
This study aimed to evaluate a validation reliability of single-step genomic best linear unbiased prediction (ssGBLUP) with a multiple-lactation random regression test-day model and investigate an effect of adding genotyped cows on the reliability. Two data sets for test-day records from the first three lactations were used: full data from February 1975 to December 2015 (60 850 534 records from 2 853 810 cows) and reduced data cut off in 2011 (53 091 066 records from 2 502 307 cows). We used marker genotypes of 4480 bulls and 608 cows. Genomic enhanced breeding values (GEBV) of 305-day milk yield in all the lactations were estimated for at least 535 young bulls using two marker data sets: bull genotypes only and both bulls and cows genotypes. The realized reliability (R 2 ) from linear regression analysis was used as an indicator of validation reliability. Using only genotyped bulls, R 2 was ranged from 0.41 to 0.46 and it was always higher than parent averages. The very similar R 2 were observed when genotyped cows were added. An application of ssGBLUP to a multiple-lactation random regression model is feasible and adding a limited number of genotyped cows has no significant effect on reliability of GEBV for genotyped bulls. © 2016 Japanese Society of Animal Science.
DEFF Research Database (Denmark)
Joensuu, H; Holli, K; Heikkinen, M
1998-01-01
PURPOSE: We report results of a randomized prospective study that compared single agents of low toxicity given both as the first-line and second-line chemotherapy with combination chemotherapy in advanced breast cancer with distant metastases. PATIENTS AND METHODS: Patients in the single-agent arm...... three times per week (CEF) followed by M 8 mg/m2 plus vinblastine (V) 6 mg/m2 every 4 weeks. Exclusion criteria included age greater than 70 years, World Health Organization (WHO) performance status greater than 2, prior chemotherapy for metastatic disease, and presence of liver metastases in patients...
Line-edge roughness induced single event transient variation in SOI FinFETs
International Nuclear Information System (INIS)
Wu Weikang; An Xia; Jiang Xiaobo; Chen Yehua; Liu Jingjing; Zhang Xing; Huang Ru
2015-01-01
The impact of process induced variation on the response of SOI FinFET to heavy ion irradiation is studied through 3-D TCAD simulation for the first time. When FinFET biased at OFF state configuration (V gs = 0, V ds = V dd ) is struck by a heavy ion, the drain collects ionizing charges under the electric field and a current pulse (single event transient, SET) is consequently formed. The results reveal that with the presence of line-edge roughness (LER), which is one of the major variation sources in nano-scale FinFETs, the device-to-device variation in terms of SET is observed. In this study, three types of LER are considered: type A has symmetric fin edges, type B has irrelevant fin edges and type C has parallel fin edges. The results show that type A devices have the largest SET variation while type C devices have the smallest variation. Further, the impact of the two main LER parameters, correlation length and root mean square amplitude, on SET variation is discussed as well. The results indicate that variation may be a concern in radiation effects with the down scaling of feature size. (paper)
Compact Single-Layer Traveling-Wave Antenna DesignUsing Metamaterial Transmission Lines
Alibakhshikenari, Mohammad; Virdee, Bal Singh; Limiti, Ernesto
2017-12-01
This paper presents a single-layer traveling-wave antenna (TWA) that is based on composite right/left-handed (CRLH)-metamaterial (MTM) transmission line (TL) structure, which is implemented by using a combination of interdigital capacitors and dual-spiral inductive slots. By embedding dual-spiral inductive slots inside the CRLH MTM-TL results in a compact TWA. Dimensions of the proposed CRLH MTM-TL TWA is 21.5 × 30.0 mm2 or 0.372λ0 × 0.520λ0 at 5.2 GHz (center frequency). The fabricated TWA operates over 1.8-8.6 GHz with a fractional bandwidth greater than 120%, and it exhibits a peak gain and radiation efficiency of 4.2 dBi and 81%, respectively, at 5 GHz. By avoiding the use of lumped components, via-holes or defected ground structures, the proposed TWA design is economic for mass production as well as easy to integrate with wireless communication systems.
Timetable Design for Minimizing Passenger Travel Time and Congestion for a Single Metro Line
Directory of Open Access Journals (Sweden)
Yi Shen
2018-02-01
Full Text Available This paper brings a proposal for a timetable optimization model for minimizing the passenger travel time and congestion for a single metro line under time-dependent demand. The model is an integer-programming model that systemically considers the passenger travel time, the capacity of trains, and the capacity of platforms. A multi-objective function and a recursive optimization method are presented to solve the optimization problem. Using the model we can obtain an efficient timetable with minimal passenger travel time and minimal number of congestion events on platforms. Moreover, by increasing the number of dispatches, the critical point from congestion state to free-flow state and the optimal timetable with minimal cost for avoiding congestion on platforms can be obtained. The effectiveness of the model is evaluated by a real example. A half-regular timetable with fixed headways in each operation period and an irregular timetable with unfixed headway are investigated for comparison.
Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos
2016-08-01
This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.
Horibe, Tomohisa; Torisawa, Aya; Akiyoshi, Ryutaro; Hatta-Ohashi, Yoko; Suzuki, Hirobumi; Kawakami, Koji
2014-02-01
The bioluminescence system (luciferase reporter assay system) is widely used to study gene expression, signal transduction and other cellular activities. Although transfection of reporter plasmid DNA to mammalian cell lines is an indispensable experimental step, the transfection efficiency of DNA varies among cell lines, and several cell lines are not suitable for this type of assay because of the low transfection efficiency. In this study, we confirm the transfection efficiency of reporter DNA to several cancer and normal cell lines after transient transfection by single-cell imaging. Luminescence images could be obtained from living single cells after transient transfection, and the calculated transfection efficiency of this method was similar to that of the conventional reporter assay using a luminometer. We attempted to measure the activity of the Bip promoter under endoplasmic reticulum stress conditions using both high and low transfection efficiency cells for plasmid DNA at the single-cell level, and observed activation of this promoter even in cells with the lowest transfection efficiency. These results show that bioluminescence imaging of single cells is a powerful tool for the analysis of gene expression based on a reporter assay using limited samples such as clinical specimens or cells from primary culture, and could provide additional information compared with the conventional assay. Copyright © 2013 John Wiley & Sons, Ltd.
Agogo, George O; van der Voet, Hilko; van't Veer, Pieter; Ferrari, Pietro; Leenders, Max; Muller, David C; Sánchez-Cantalejo, Emilio; Bamia, Christina; Braaten, Tonje; Knüppel, Sven; Johansson, Ingegerd; van Eeuwijk, Fred A; Boshuizen, Hendriek
2014-01-01
In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.
Directory of Open Access Journals (Sweden)
George O Agogo
Full Text Available In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.
Agogo, George O.; van der Voet, Hilko; Veer, Pieter van’t; Ferrari, Pietro; Leenders, Max; Muller, David C.; Sánchez-Cantalejo, Emilio; Bamia, Christina; Braaten, Tonje; Knüppel, Sven; Johansson, Ingegerd; van Eeuwijk, Fred A.; Boshuizen, Hendriek
2014-01-01
In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model. PMID:25402487
Can you build an iPhone app without writing a single line of code?
Ramachandran, R.; Maskey, M.
2011-12-01
At the last ESIP summer meeting, a study was conducted to explore different commercial tools now available that allow one to create a mobile app without writing a single line of code. The proposed research comprised of two components. First, systematically evaluate different tools to create mobile apps along the dimensions of features and price. Second, create an iPhone app prototype for the ESIP community using some of these tools. The initial assessment classified the currently available tools to create mobile app tools into two categories. The tools that fall under the first category require no programming, but the content for the mobile apps are fed to it either via a web site RSS feed or entered manually. Consequently, these tools only support limited user interactivity. These tools follow the business model of website hosting services. This business model offers a set of templates to the end users with limited customization features to create their content in order to publish to websites. The second category of tools requires programming, but the code can be written in popular languages such as Javascript (compatible with most mobile platforms) rather than mobile app specific languages. For the second component of the study, two ESIP iPhone app prototypes were created. The first prototype required no programming and used the AppMakr tool. Objective C was used to create the second iPhone prototype from scratch and the source code for this prototype is available on the ESIP website. The study concluded that existing tools do make it easy to create a simple mobile app especially if one already has a well designed website. The associated costs are adequate but not cheap. However, if the mobile app has requirements that require interactivity and specialized customization then one needs to work with a mobile app developer.
Music-to-Color Associations of Single-Line Piano Melodies in Non-synesthetes.
Palmer, Stephen E; Langlois, Thomas A; Schloss, Karen B
2016-01-01
Prior research has shown that non-synesthetes' color associations to classical orchestral music are strongly mediated by emotion. The present study examines similar cross-modal music-to-color associations for much better controlled musical stimuli: 64 single-line piano melodies that were generated from four basic melodies by Mozart, whose global musical parameters were manipulated in tempo(slow/fast), note-density (sparse/dense), mode (major/minor) and pitch-height (low/high). Participants first chose the three colors (from 37) that they judged to be most consistent with (and, later, the three that were most inconsistent with) the music they were hearing. They later rated each melody and each color for the strength of its association along four emotional dimensions: happy/sad, agitated/calm, angry/not-angry and strong/weak. The cross-modal choices showed that faster music in the major mode was associated with lighter, more saturated, yellower (warmer) colors than slower music in the minor mode. These results replicate and extend those of Palmer et al. (2013, Proc. Natl Acad. Sci. 110, 8836-8841) with more precisely controlled musical stimuli. Further results replicated strong evidence for emotional mediation of these cross-modal associations, in that the emotional ratings of the melodies were very highly correlated with the emotional associations of the colors chosen as going best/worst with the melodies (r = 0.92, 0.85, 0.82 and 0.70 for happy/sad, strong/weak,angry/not-angry and agitated/calm, respectively). The results are discussed in terms of common emotional associations forming a cross-modal bridge between highly disparate sensory inputs.
Ngo, N. H.; Nguyen, H. T.; Tran, H.
2018-03-01
In this work, we show that precise predictions of the shapes of H2O rovibrational lines broadened by N2, over a wide pressure range, can be made using simulations corrected by a single measurement. For that, we use the partially-correlated speed-dependent Keilson-Storer (pcsdKS) model whose parameters are deduced from molecular dynamics simulations and semi-classical calculations. This model takes into account the collision-induced velocity-changes effects, the speed dependences of the collisional line width and shift as well as the correlation between velocity and internal-state changes. For each considered transition, the model is corrected by using a parameter deduced from its broadening coefficient measured for a single pressure. The corrected-pcsdKS model is then used to simulate spectra for a wide pressure range. Direct comparisons of the corrected-pcsdKS calculated and measured spectra of 5 rovibrational lines of H2O for various pressures, from 0.1 to 1.2 atm, show very good agreements. Their maximum differences are in most cases well below 1%, much smaller than residuals obtained when fitting the measurements with the Voigt line shape. This shows that the present procedure can be used to predict H2O line shapes for various pressure conditions and thus the simulated spectra can be used to deduce the refined line-shape parameters to complete spectroscopic databases, in the absence of relevant experimental values.
Wang, Hui; Sui, Weiguo; Xue, Wen; Wu, Junyong; Chen, Jiejing; Dai, Yong
2014-09-01
Immunoglobulin A nephropathy (IgAN) is a complex trait regulated by the interaction among multiple physiologic regulatory systems and probably involving numerous genes, which leads to inconsistent findings in genetic studies. One possibility of failure to replicate some single-locus results is that the underlying genetics of IgAN nephropathy is based on multiple genes with minor effects. To learn the association between 23 single nucleotide polymorphisms (SNPs) in 14 genes predisposing to chronic glomerular diseases and IgAN in Han males, the 23 SNPs genotypes of 21 Han males were detected and analyzed with a BaiO gene chip, and their associations were analyzed with univariate analysis and multiple linear regression analysis. Analysis showed that CTLA4 rs231726 and CR2 rs1048971 revealed a significant association with IgAN. These findings support the multi-gene nature of the etiology of IgAN and propose a potential gene-gene interactive model for future studies.
Grégoire, G.
2014-12-01
The logistic regression originally is intended to explain the relationship between the probability of an event and a set of covariables. The model's coefficients can be interpreted via the odds and odds ratio, which are presented in introduction of the chapter. The observations are possibly got individually, then we speak of binary logistic regression. When they are grouped, the logistic regression is said binomial. In our presentation we mainly focus on the binary case. For statistical inference the main tool is the maximum likelihood methodology: we present the Wald, Rao and likelihoods ratio results and their use to compare nested models. The problems we intend to deal with are essentially the same as in multiple linear regression: testing global effect, individual effect, selection of variables to build a model, measure of the fitness of the model, prediction of new values… . The methods are demonstrated on data sets using R. Finally we briefly consider the binomial case and the situation where we are interested in several events, that is the polytomous (multinomial) logistic regression and the particular case of ordinal logistic regression.
Effect of Single or Combined Climatic and Hygienic Stress in Four Layer Lines: 1. Performance
Star, L.; Kemp, B.; Anker, van den I.; Parmentier, H.K.
2008-01-01
Effects of long-term climatic stress (heat exposure), short-term hygienic stress [lipopolysaccharide (LPS)], or a combination of both challenges on performance of 4 layer lines were investigated. The lines were earlier characterized by natural humoral immune competence and survival rate. At 22 wk of
Al Askar, Ahmed S; Shaheen, Naila A; Al Zahrani, Mohsen; Al Otaibi, Mohammed G; Al Qahtani, Bader S; Ahmed, Faris; Al Zughaibi, Mohand; Kamran, Ismat; Mendoza, May Anne; Khan, Altaf
2018-01-01
Immune thrombocytopenic purpura (ITP) is a common hematological disease treated primarily by corticosteroids. The aim of the present study was to compare response rate between patients, underwent splenectomy vs. rituximab as second-line therapy. Adult patients diagnosed with ITP who did not respond to corticosteroids or relapsed during the period 1990-2014 were included in a quasi-experimental study. Categorical variables were compared using Fisher exact test. Response to treatment was compared using logistic regression. Data were analyzed using SAS V9.2. One-hundred and forty-three patients with ITP were identified through medical records. Of 62 patients treated, 30 (48.38%) required second-line therapy. 19 (63%) patients received rituximab, and 11 (37%) underwent splenectomy. Platelets at diagnosis were not different between study groups (p = 0.062). Splenectomy group patients were younger (p = 0.011). Response to second-line therapy showed no significant difference between two groups (OR 2.03, 95% CI (0.21-22.09), p = 0.549). Results did not show a statistically significant difference in platelet counts over time between treatment groups (p = 0.101). When used exclusively as a second-line therapy for steroid-refractory ITP, the response rate was not statistically different between rituximab and splenectomy. However, further large studies are needed to assess the response rates for these treatment modalities as a second-line therapy.
Rendall, Ricardo; Pereira, Ana Cristina; Reis, Marco S
2017-08-15
In this paper we test and compare advanced predictive approaches for estimating wine age in the context of the production of a high quality fortified wine - Madeira Wine. We consider four different data sets, namely, volatile, polyphenols, organic acids and the UV-vis spectra. Each one of these data sets contain chemical information of a different nature and present diverse data structures, namely a different dimensionality, level of collinearity and degree of sparsity. These different aspects may imply the use of different modelling approaches in order to better explore the data set's information content, namely their predictive potential for wine age. This happens to be so, because different regression methods have different prior assumptions regarding the predictors, response variable(s) and the data generating mechanism, which may or may not find good adherence to the case study under analysis. In order to cover a wide range of modelling domains, we have incorporated in this work methods belonging to four very distinct classes of approaches that cover most applications found in practice: linear regression with variable selection, penalized regression, latent variables regression and tree-based ensemble methods. We have also developed a rigorous comparison framework based on a double Monte Carlo cross-validation scheme, in order to perform the relative assessment of the performance of the various methods. Upon comparison, models built using the polyphenols and volatile composition data sets led to better wine age predictions, showing lower errors under testing conditions. Furthermore, the results obtained for the polyphenols data set suggest a more sparse structure that can be further explored in order to reduce the number of measured variables. In terms of regression methods, tree-based methods, and boosted regression trees in particular, presented the best results for the polyphenols, volatile and the organic acid data sets, suggesting a possible presence of a
National Research Council Canada - National Science Library
Dovichi, Norman J
2005-01-01
.... Capillary sieving electrophoresis and capillary micellar electrophoresis were used to characterize proteins in single cells in one-dimensional separations, while the two techniques were combined...
Hill, S.; Maccagnano, S.; Park, Kyungwha; Achey, R. M.; North, J. M.; Dalal, N. S.
2002-06-01
It is shown that our multi-high-frequency (40-200 GHz) resonant cavity technique yields distortion-free high-field electron paramagnetic resonance (EPR) spectra for single-crystal samples of the uniaxial and biaxial spin S=10 single-molecule magnets (SMM's) [Mn12O12(CH3COO)16(H2O)4].2CH3COOH.4H2O and [Fe8O2(OH)12(tacn)6]Br8.9H2O. The observed line shapes exhibit a pronounced dependence on temperature, magnetic field, and the spin quantum numbers (MS values) associated with the levels involved in the transitions. Measurements at many frequencies allow us to separate various contributions to the EPR linewidths, including significant D strain, g strain, and broadening due to the random dipolar fields of neighboring molecules. We also identify asymmetry in some of the EPR line shapes for Fe8 and a previously unobserved fine structure to some of the EPR lines for both the Fe8 and Mn12 systems. These findings prove relevant to the mechanism of quantum tunneling of magnetization in these SMM's.
Wang, Minghao; Wu, Meiping; Cao, Juliang; Zhang, Kaidong; Cai, Shaokun; Yu, Ruihang
2018-01-26
Quality assessment is an important part in the strapdown airborne gravimetry. Root mean square error (RMSE) evaluation method is a classical way to evaluate the gravimetry quality, but classical evaluation methods are preconditioned by extra flight or reference data. Thus, a method, which is able to largely conquer the premises of classical quality assessment methods and can be used in single survey line, has been developed in this paper. According to theoretical analysis, the method chooses the stability of two horizontal attitude angles, horizontal specific force and vertical specific force as the determinants of quality assessment method. The actual data, collected by SGA-WZ02 from 13 flights 21 lines in certain survey, was used to build the model and elaborate the method. To substantiate the performance of the quality assessment model, the model is applied in extra repeat line flights from two surveys. Compared with internal RMSE, standard deviation of assessment residuals are 0.23 mGal and 0.16 mGal in two surveys, which shows that the quality assessment method is reliable and stricter. The extra flights are not necessary by specially arranging the route of flights. The method, summarized from SGA-WZ02, is a feasible approach to assess gravimetry quality using single line data and is also suitable for other strapdown gravimeters.
Olive, David J
2017-01-01
This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...
Directory of Open Access Journals (Sweden)
Igor K. Kochanenko
2013-01-01
Full Text Available Procedures of construction of curve regress by criterion of the least fractals, i.e. the greatest probability of the sums of degrees of the least deviations measured intensity from their modelling values are proved. The exponent is defined as fractal dimension of a time number. The difference of results of a well-founded method and a method of the least squares is quantitatively estimated.
International Nuclear Information System (INIS)
Rofstad, E.K.; Brustad, T.
1984-01-01
One uncloned and five cloned cell lines were derived from a single human melanoma xenograft. Cells from passages 7-12 were exposed to either radiation or hyperthermia (42.5 0 C, pH = 7.4) under aerobic conditions and the colony forming ability of the cells was assayed in soft agar. The five cloned lines showed individual and characteristic responses to radiation as well as to hyperthermia. The variation in the response to radiation was mainly reflected in the size of the shoulders of the survival curves rather than in the D 0 -values. The variation in the response to hyperthermia was mainly reflected in the terminal slopes of the survival curves. The survival curve of cells from the uncloned line, both when exposed to radiation and hyperthermia, was positioned in the midst of those of the cloned lines. The response of the cloned lines to radiation did not correlate with the response to hyperthermia, indicating that tumor cell subpopulations which are resistant to radiation may respond well to hyperthermia
Geng, Xindu; Ke, Congyu; Chen, Gang; Liu, Peng; Wang, Fei; Zhang, Huiqiang; Sun, Xuan
2009-04-17
This paper reports the on-line separation of native (N) proteins by two-dimensional liquid chromatography (2D-LC) using a single column with one phase (called 2D column). The 2D column exhibits excellent resolution, selectivity, and retention of proteins in the N state and functions in two retention modes--hydrophobic interaction chromatography (HIC) and weak-cation exchange chromatography (WCX). We describe a new approach to on-line buffer exchange and collection of fractions from the first retention mode and their quantitative re-injection into the same column, followed by re-separation in the second retention mode. Thus, liquid chromatography in a closed system and in an on-line manner could be successfully carried out. This method was termed on-line protein separation by 2D-LC using only a single column (on-line 2D-LC-1C). The applicability of this method was experimentally demonstrated using standard proteins and a human serum sample. The total hypothetical maximum possible peak capacity n(c,total) and total sample peak capacity n(c,total)(*) of the 2D column were 329 and 199, respectively. By comparison against several popular commercially available columns, it was found that the 2D column had not only comparable resolution and better selectivity but also some unique characteristics. This 2D-LC-1C method could be applied to the fast purification of intact proteins in the N state, such protein drugs from natural products, and recombinant proteins and also for the fast pre-fractionation of intact proteins in the "top-down" MS strategy in proteomics.
Zemánek, Ivan; Havlíček, Václav
2006-09-01
A new universal control and measuring system for classic and amorphous soft magnetic materials single/on-line strip testing has been developed at the Czech Technical University in Prague. The measuring system allows to measure magnetization characteristic and specific power losses of different tested materials (strips) at AC magnetization of arbitrary magnetic flux density waveform at wide range of frequencies 20 Hz-20 kHz. The measuring system can be used for both single strip testing in laboratories and on-line strip testing during the production process. The measuring system is controlled by two-stage master-slave control system consisting of the external PC (master) completed by three special A/D measuring plug-in boards, and local executing control unit (slave) with one-chip microprocessor 8051, connected with PC by the RS232 serial line. The "user friendly" powerful control software implemented on the PC and the effective program code for the microprocessor give possibility for full automatic measurement with high measuring power and high measuring accuracy.
Thermo-Mechanical Analysis of a Single-Pass Weld Overlay and Girth Welding in Lined Pipe
Obeid, Obeid; Alfano, Giulio; Bahai, Hamid
2017-08-01
The paper presents a nonlinear heat-transfer and mechanical finite-element (FE) analyses of a two-pass welding process of two segments of lined pipe made of a SUS304 stainless steel liner and a C-Mn steel pipe. The two passes consist of the single-pass overlay welding (inner lap weld) of the liner with the C-Mn steel pipe for each segment and the single-pass girth welding (outer butt weld) of the two segments. A distributed power density of the moving welding torch and a nonlinear heat-transfer coefficient accounting for both radiation and convection have been used in the analysis and implemented in user subroutines for the FE code ABAQUS. The modeling procedure has been validated against previously published experimental results for stainless steel and carbon steel welding separately. The model has been then used to determine the isotherms induced by the weld overlay and the girth welding and to clarify their influence on the transient temperature field and residual stress in the lined pipe. Furthermore, the influence of the cooling time between weld overlay and girth welding and of the welding speed have been examined thermally and mechanically as they are key factors that can affect the quality of lined pipe welding.
A Method for Robust Strategic Railway Dispatch Applied to a Single Track Line
DEFF Research Database (Denmark)
Harrod, Steven
2013-01-01
A method is presented for global optimization of a dispatch plan assuming perfect information over a given time horizon. An example problem is solved for the North American case of a single dominant high-speed train sharing a network with a majority flow of slower trains. Initial dispatch priority...
Linear regression in astronomy. II
Feigelson, Eric D.; Babu, Gutti J.
1992-01-01
A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.
Morrical, Bradley D; Balaxi, Maria; Fergenson, David
2015-07-15
The use of single particle aerosol mass spectrometry (SPAMS) was evaluated for the analysis of inhaled pharmaceuticals to determine the mass distribution of the individual active pharmaceutical ingredients (API) in both single ingredient and combination drug products. SPAMS is an analytical technique where the individual aerodynamic diameters and chemical compositions of many aerosol particles are determined in real-time. The analysis was performed using a Livermore Instruments SPAMS 3.0, which allowed the efficient analysis of aerosol particles with broad size distributions and can acquire data even under a very large particle load. Data similar to what would normally require roughly three days of experimentation and analysis was collected in a five minute period and analyzed automatically. The results were computed to be comparable to those returned by a typical Next Generation Impactor (NGI) particle size distribution experiment. Copyright © 2015. Published by Elsevier B.V.
Absorption line profiles in a moving atmosphere - A single scattering linear perturbation theory
Hays, P. B.; Abreu, V. J.
1989-01-01
An integral equation is derived which linearly relates Doppler perturbations in the spectrum of atmospheric absorption features to the wind system which creates them. The perturbation theory is developed using a single scattering model, which is validated against a multiple scattering calculation. The nature and basic properties of the kernels in the integral equation are examined. It is concluded that the kernels are well behaved and that wind velocity profiles can be recovered using standard inversion techniques.
Reactions and single-particle structure of nuclei near the drip lines
International Nuclear Information System (INIS)
Hansen, P.G.; Sherrill, B.M.
2001-01-01
The techniques that have allowed the study of reactions of nuclei situated at or near the neutron or proton drip line are described. Nuclei situated just inside the drip line have low nucleon separation energies and, at most, a few bound states. If the angular momentum in addition is small, large halo states are formed where the wave function of the valency nucleon extends far beyond the nuclear radius. We begin with examples of the properties of nuclear halos and of their study in radioactive-beam experiments. We then turn to the continuum states existing above the particle threshold and also discuss the possibility of exciting them from the halo states in processes that may be thought of as 'collateral damage'. Finally, we show that the experience from studies of halo states has pointed to knockout reactions as a new way to perform spectroscopic studies of more deeply bound non-halo states. Examples are given of measurements of l values and spectroscopic factors
SLG(Single-Line-to-Ground Fault Location in NUGS(Neutral Un-effectively Grounded System
Directory of Open Access Journals (Sweden)
Zhang Wenhai
2018-01-01
Full Text Available This paper reviews the SLG(Single-Line-to-Ground fault location methods in NUGS(Neutral Un-effectively Grounded System, including ungrounded system, resonant grounded system and high-resistance grounded system which are widely used in Northern Europe and China. This type of fault is hard to detect and location because fault current is the sum of capacitance current of the system which is always small(about tens of amperes. The characteristics of SLG fault in NUGS and the fault location methods are introduced in the paper.
Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line.
Teo, Audrey S M; Verzotto, Davide; Yao, Fei; Nagarajan, Niranjan; Hillmer, Axel M
2015-01-01
Next-generation sequencing (NGS) technologies have changed our understanding of the variability of the human genome. However, the identification of genome structural variations based on NGS approaches with read lengths of 35-300 bases remains a challenge. Single-molecule optical mapping technologies allow the analysis of DNA molecules of up to 2 Mb and as such are suitable for the identification of large-scale genome structural variations, and for de novo genome assemblies when combined with short-read NGS data. Here we present optical mapping data for two human genomes: the HapMap cell line GM12878 and the colorectal cancer cell line HCT116. High molecular weight DNA was obtained by embedding GM12878 and HCT116 cells, respectively, in agarose plugs, followed by DNA extraction under mild conditions. Genomic DNA was digested with KpnI and 310,000 and 296,000 DNA molecules (≥ 150 kb and 10 restriction fragments), respectively, were analyzed per cell line using the Argus optical mapping system. Maps were aligned to the human reference by OPTIMA, a new glocal alignment method. Genome coverage of 6.8× and 5.7× was obtained, respectively; 2.9× and 1.7× more than the coverage obtained with previously available software. Optical mapping allows the resolution of large-scale structural variations of the genome, and the scaffold extension of NGS-based de novo assemblies. OPTIMA is an efficient new alignment method; our optical mapping data provide a resource for genome structure analyses of the human HapMap reference cell line GM12878, and the colorectal cancer cell line HCT116.
Zhang, Yuchao; Xie, Changqing
2015-11-01
Both digital in-line holography (DIH) and zone plate-based microscopy have received considerable interest as powerful imaging tools. However, the former suffers from a twin-image noise problem. The latter suffers from low efficiency and difficulty in fabrication. Here, we present an effective and efficient phase-contrast imaging approach, named differential-interference-contrast digital in-line holography (DIC-DIH), by using a single optical element to split the incident light into a plane wave and a converging spherical wave and generate a two-dimensional (2D) DIC effect simultaneously. Specifically, to improve image contrast, we present a new single optical element, termed 2D DIC compound photon sieves, by combining two overlaid binary gratings and a compound photon sieve through two logical XOR operations. The proof-of-concept experiments demonstrate that the proposed technique can eliminate the twin-image noise problem and improve image contrast with high efficiency. Additionally, we present an example of the phase-contrast imaging nonuniform thick photoresist development process.
Analysis of T-DNA/Host-Plant DNA Junction Sequences in Single-Copy Transgenic Barley Lines
Directory of Open Access Journals (Sweden)
Joanne G. Bartlett
2014-01-01
Full Text Available Sequencing across the junction between an integrated transfer DNA (T-DNA and a host plant genome provides two important pieces of information. The junctions themselves provide information regarding the proportion of T-DNA which has integrated into the host plant genome, whilst the transgene flanking sequences can be used to study the local genetic environment of the integrated transgene. In addition, this information is important in the safety assessment of GM crops and essential for GM traceability. In this study, a detailed analysis was carried out on the right-border T-DNA junction sequences of single-copy independent transgenic barley lines. T-DNA truncations at the right-border were found to be relatively common and affected 33.3% of the lines. In addition, 14.3% of lines had rearranged construct sequence after the right border break-point. An in depth analysis of the host-plant flanking sequences revealed that a significant proportion of the T-DNAs integrated into or close to known repetitive elements. However, this integration into repetitive DNA did not have a negative effect on transgene expression.
Namazi, Soha; Rostami-Yalmeh, Javad; Sahebi, Ebrahim; Jaberipour, Mansooreh; Razmkhah, Mahboobeh; Hosseini, Ahmad
2014-06-01
Innate and acquired tamoxifen (TAM) resistance in estrogen receptor positive (ER+) breast cancer is an important problem in adjuvant endocrine therapy. The underlying mechanisms of TAM resistance is yet unknown. In the present study, we evaluated the role of renin-angiotensin system (RAS) in the acquisition of TAM resistance in human breast cancer cell line MCF-7, and the potential role of captopril and captopril+losartan combination in the prevention and reversion of the TAM resistant phenotype. MCF-7 cells were continuously exposed to 1 μmol/L TAM to develop TAM resistant cells (TAM-R). MTT cell viability assay was used to determine the growth response of MCF-7 and TAM-R cells, and quantitative real-time polymerase chain reaction (qRT-PCR) was used to assess angiotensin I converting enzyme (ACE), angiotensin II receptor type-1 and type-2 (AGTR1 and AGTR2) mRNA expressions. Preventive and therapeutic effects of RAS blockers - captopril and losartan - were examined on MCF-7 and TAM-R cells. Based on qRT-PCR, TAM-R cells compared to MCF-7 cells, had a mean ± SD fold increase of 319.1 ± 204.1 (P = 0.002) in production of ACE mRNA level, 2211.8 ± 777.9 (P = 0.002) in AGTR1 mRNA level, and 265.9 ± 143.9 (P = 0.037) in production of AGTR2 mRNA level. The combination of either captopril or captopril+losartan with TAM led to the prevention and even reversion of TAM resistant phenotype. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
On-line monitoring system development for single-phase flow accelerated corrosion
International Nuclear Information System (INIS)
Lee, Na Young; Lee, Seung Gi; Ryu, Kyung Ha; Hwang, Il Soon
2007-01-01
Aged nuclear piping has been reported to undergo corrosion-induced accelerated failures, often without giving signatures to current inspection campaigns. Therefore, we need diverse sensors which can cover a wide area in an on-line application. We suggest an integrated approach to monitor the flow accelerated corrosion (FAC) susceptible piping. Since FAC is a combined phenomenon, we need to monitor as many parameters as possible and that cover wide area, since we do not know where the FAC occurs. For this purpose, we introduce the wearing rate model which focuses on the electrochemical parameters. Using this model, we can predict the wearing rate and then compare testing results. Through analysis we identified feasibility and then developed electrochemical sensors for high temperature application; we also introduced a mechanical monitoring system which is still under development. To support the validation of the monitored results, we adopted high temperature ultrasonic transducer (UT), which shows good resolution in the testing environment. As such, all the monitored results can be compared in terms of thickness. Our validation tests demonstrated the feasibility of sensors. To support direct thickness measurement for a wide-area, the direct current potential drop (DCPD) method will be researched to integrate into the developed framework
48 CFR 245.7101-3 - DD Form 1348-1, DoD Single Line Item Release/Receipt Document.
2010-10-01
... PROPERTY Plant Clearance Forms 245.7101-3 DD Form 1348-1, DoD Single Line Item Release/Receipt Document. Use for shipments of excess industrial plant equipment and contractor inventory redistribution system...
Shen, Yue; Liu, Xin; Greene, Jenny E.; Strauss, Michael A.
2011-07-01
Approximately 1% of low-redshift (z interpreted as either due to kinematics, such as biconical outflows and/or disk rotation of the narrow line region (NLR) around single black holes, or due to the relative motion of two distinct NLRs in a merging pair of AGNs. Here, we report follow-up near-infrared (NIR) imaging and optical slit spectroscopy of 31 double-peaked [O III] type 2 AGNs drawn from the Sloan Digital Sky Survey (SDSS) parent sample presented in Liu et al. The NIR imaging traces the old stellar population in each galaxy, while the optical slit spectroscopy traces the NLR gas. These data reveal a mixture of origins for the double-peaked feature. Roughly 10% of our objects are best explained by binary AGNs at (projected) kpc-scale separations, where two stellar components with spatially coincident NLRs are seen. ~50% of our objects have [O III] emission offset by a few kpc, corresponding to the two velocity components seen in the SDSS spectra, but there are no spatially coincident double stellar components seen in the NIR imaging. For those objects with sufficiently high-quality slit spectra, we see velocity and/or velocity dispersion gradients in [O III] emission, suggestive of the kinematic signatures of a single NLR. The remaining ~40% of our objects are ambiguous and will need higher spatial resolution observations to distinguish between the two scenarios. Our observations therefore favor the kinematics scenario with a single AGN for the majority of these double-peaked [O III] type 2 AGNs. We emphasize the importance of combining imaging and slit spectroscopy in identifying kpc-scale binary AGNs, i.e., in no cases does one of these alone allow an unambiguous identification. We estimate that ~0.5%-2.5% of the z ~ 150 km s-1. Based in part on observations obtained with the 6.5 m Magellan telescopes located at Las Campanas Observatory, Chile, and with the Apache Point Observatory 3.5 m telescope, which is owned and operated by the Astrophysical Research
Directory of Open Access Journals (Sweden)
Auwal Mustapha Imam
2017-12-01
Full Text Available Optical fiber cables are materials whose core is made of silica and other materials such as chalcogenide glasses; they transmit a digital signal via light pulses through an extremely thin strand of glass. The light propagates and is being guided by the core which is surrounded by the cladding. Light travels in the optical fiber in the form of total internal reflection in the core of the fibers. The flexibility, low tensile strength, low signal loss, high bandwidth and other characteristics of optical fibers favors it for use as a delay medium in many applications. Another favorable characteristic of optical fiber delay lines is are their relative insensitivities to environmental effects and electromagnetic interferences. The immunity of optical fibers to interferences and their less weight added advantages to it for use as delay medium. Single-mode and multi-mode are the two most popular types of optical fibers. Single-mode fibers have good propagation and delay properties with a minimal loss that allows the signal to propagate in a large distance with insignificant distortion or attenuation. The percentage of power transmission of single-mode fibers is found to be higher than that of the multi-mode fibers. It is, therefore, a preferred type for use as a delay line. In this paper, relative studies of the two optical fibers modes, and the results of power input/output measurement of the two modes are presented with a view to coming up with a better type for use as a delay medium.
Muzi, Laura; Tardani, Franco; La Mesa, Camillo; Bonincontro, Adalberto; Bianco, Alberto; Risuleo, Gianfranco
2016-04-01
Functionalized carbon nanotubes (CNTs) have shown great promise in several biomedical contexts, spanning from drug delivery to tissue regeneration. Thanks to their unique size-related properties, single-walled CNTs (SWCNTs) are particularly interesting in these fields. However, their use in nanomedicine requires a clear demonstration of their safety in terms of tissue damage, toxicity and pro-inflammatory response. Thus, a better understanding of the cytotoxicity mechanisms, the cellular interactions and the effects that these materials have on cell survival and on biological membranes is an important first step for an appropriate assessment of their biocompatibility. In this study we show how bovine serum albumin (BSA) is able to generate homogeneous and stable dispersions of SWCNTs (BSA-CNTs), suggesting their possible use in the biomedical field. On the other hand, this study wishes to shed more light on the impact and the interactions of protein-stabilized SWCNTs with two different cell types exploiting multidisciplinary techniques. We show that BSA-CNTs are efficiently taken up by cells. We also attempt to describe the effect that the interaction with cells has on the dielectric characteristics of the plasma membrane and ion flux using electrorotation. We then focus on the BSA-CNTs’ acute toxicity using different cellular models. The novel aspect of this work is the evaluation of the membrane alterations that have been poorly investigated to date.
DEFF Research Database (Denmark)
Bak, Claus Leth; Søgaard, Kim
2008-01-01
consisting of overhead lines, crossbonded cable sections and shunt reactor has been created in PSCAD/EMTDC and verified against measurements with good results. Main focus has been put on the likelihood of having a successful single-phase autoreclosure ARC in such a combined cable/OHL line....
Fedyanin, Mikahil; Tryakin, Alexey; Vybarava, Anna; Chekini, Dzhennet; Pokataev, Ilya; Sekhina, Olga; Gordeev, Sergey; Aliev, Vechaslav; Tjulandin, Sergei
2015-01-01
A role of maintenance chemotherapy (mCT) in patients (pts) with metastatic colorectal cancer (mCRC) is still controversial. The purpose of this retrospective study was to investigate the toxicity and efficacy of mCT in pts with mCRC. There were 97/291 (33 %) pts with mCRC completed 18-20 weeks of first-line CT from 2007 to 2013 in our center. Then, pts who had no disease progression were non-randomly allocated to mCT with capecitabine ± bevacizumab (n = 35) or surveillance (n = 62). PFS was used as a primary endpoint and was calculated from the date of completion of first-line CT. Multivariate Cox stepwise regression analysis was performed to determine independent prognostic factors. Median follow-up time was 15 (range 5-60) months. Median PFS and OS were higher in pts with mCT: 7 versus 3 months (HR 0.5, 95 %CI 0.28-0.82, p = 0.007) and 29 vs 16 months (HR 0.6, 95 %CI 0.3-1.1, 0.04-Gehan-Breslow-Wilcoxon test). Following independent negative prognostic factors was significant on multivariate analysis: CEA level >2.5 ng/ml before start of first-line CT (p = 0.02), liver metastases (p = 0.03) and number of metastatic zones >2 (p = 0.008). MCT had an independent positive impact on PFS (HR 0.5, p = 0.003). MCT prolonged PFS in pts with at least one negative prognostic factors (7 vs. 3 months, p = 0.001, HR 0.38, 95 % CI 0.22-0.68). The mCT was most beneficial in pts with negative prognostic factors: CEA level >2.5 ng/ml before start of first-line CT and/or liver metastases and/or number of metastatic zones >2.
Zhou, Jinzhe; Zhou, Yanbing; Cao, Shougen; Li, Shikuan; Wang, Hao; Niu, Zhaojian; Chen, Dong; Wang, Dongsheng; Lv, Liang; Zhang, Jian; Li, Yu; Jiao, Xuelong; Tan, Xiaojie; Zhang, Jianli; Wang, Haibo; Zhang, Bingyuan; Lu, Yun; Sun, Zhenqing
2016-01-01
Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity. We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system. Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation, p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed, p = 1/(1 + e((4.810-1.287X1-0.504X2-0.500X3-0.474X4-0.405X5-0.318X6-0.316X7-0.305X8-0.278X9-0.255X10-0.138X11))). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively. This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient's risk factors, estimate patients' risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups.
Directory of Open Access Journals (Sweden)
Heinz Ruth A
2008-01-01
Full Text Available Abstract Background Association analysis is a powerful tool to identify gene loci that may contribute to phenotypic variation. This includes the estimation of nucleotide diversity, the assessment of linkage disequilibrium structure (LD and the evaluation of selection processes. Trait mapping by allele association requires a high-density map, which could be obtained by the addition of Single Nucleotide Polymorphisms (SNPs and short insertion and/or deletions (indels to SSR and AFLP genetic maps. Nucleotide diversity analysis of randomly selected candidate regions is a promising approach for the success of association analysis and fine mapping in the sunflower genome. Moreover, knowledge of the distance over which LD persists, in agronomically meaningful sunflower accessions, is important to establish the density of markers and the experimental design for association analysis. Results A set of 28 candidate genes related to biotic and abiotic stresses were studied in 19 sunflower inbred lines. A total of 14,348 bp of sequence alignment was analyzed per individual. In average, 1 SNP was found per 69 nucleotides and 38 indels were identified in the complete data set. The mean nucleotide polymorphism was moderate (θ = 0.0056, as expected for inbred materials. The number of haplotypes per region ranged from 1 to 9 (mean = 3.54 ± 1.88. Model-based population structure analysis allowed detection of admixed individuals within the set of accessions examined. Two putative gene pools were identified (G1 and G2, with a large proportion of the inbred lines being assigned to one of them (G1. Consistent with the absence of population sub-structuring, LD for G1 decayed more rapidly (r2 = 0.48 at 643 bp; trend line, pooled data than the LD trend line for the entire set of 19 individuals (r2 = 0.64 for the same distance. Conclusion Knowledge about the patterns of diversity and the genetic relationships between breeding materials could be an invaluable aid in crop
DEFF Research Database (Denmark)
Senturk, O.S.; Hava, A.M.
2011-01-01
This paper proposes the waveform reconstruction method (WRM), which is utilized in the single-phase series active filter's (SAF's) control algorithm, in order to extract the load harmonic voltage component of voltage harmonic type single-phase diode rectifier loads. Employing WRM and the line...
Energy Technology Data Exchange (ETDEWEB)
Hirvonen, Liisa M.; Le Marois, Alix; Suhling, Klaus, E-mail: klaus.suhling@kcl.ac.uk [Department of Physics, King' s College London, Strand, London WC2R 2LS (United Kingdom); Becker, Wolfgang; Smietana, Stefan [Becker & Hickl GmbH, Nahmitzer Damm 30, 12277 Berlin (Germany); Milnes, James; Conneely, Thomas [Photek Ltd., 26 Castleham Rd, Saint Leonards-on-Sea TN38 9NS (United Kingdom); Jagutzki, Ottmar [Institut für Kernphysik, Max-von-Laue-Str. 1, 60438 Frankfurt (Germany)
2016-08-15
We perform wide-field time-correlated single photon counting-based fluorescence lifetime imaging (FLIM) with a crossed delay line anode image intensifier, where the pulse propagation time yields the photon position. This microchannel plate-based detector was read out with conventional fast timing electronics and mounted on a fluorescence microscope with total internal reflection (TIR) illumination. The picosecond time resolution of this detection system combines low illumination intensity of microwatts with wide-field data collection. This is ideal for fluorescence lifetime imaging of cell membranes using TIR. We show that fluorescence lifetime images of living HeLa cells stained with membrane dye di-4-ANEPPDHQ exhibit a reduced lifetime near the coverslip in TIR compared to epifluorescence FLIM.
On-line study of growth kinetics of single hyphae of Aspergillus oryzae in a flow-through cell
DEFF Research Database (Denmark)
Christiansen, Torben; Spohr, Anders Bendsen; Nielsen, Jens Bredal
1999-01-01
Using image analysis the growth kinetics of the single hyphae of the filamentous fungus Aspergillus oryzae has been determined on-line in a flow-through cell at different glucose concentrations in the range from 26 mg L-1 to 20 g L-1. The tip extension rate of the individual hyphae can be described...... with saturation type kinetics with respect to the length of the hyphae. The maximum tip extension rate is constant for all hyphae measured at the same glucose concentration, whereas the saturation constant for the hyphae varies significantly between the hyphae even within the same hyphal element. When apical...... branching occurs, it is observed that the tip extension rate decreases temporarily. The number of branches formed on a hypha is proportional to the length of the hypha that exceeds a certain minimum length required to support the growth of a new branch. The observed kinetics has been used to simulate...
Fatouros, I G; Laparidis, K; Kambas, A; Chatzinikolaou, A; Techlikidou, E; Katrabasas, I; Douroudos, I; Leontsini, D; Berberidou, F; Draganidis, D; Christoforidis, C; Tsoukas, D; Kelis, S; Taxildaris, K
2011-03-01
This study evaluated the validity, reliability, and sensitivity of the single-trial line drill test (SLDT) for anaerobic power assessment. Twenty-four volunteers were assigned to either a control (C, N.=12) or an experimental (BP, N.=12 basketball players) group. SLDT's (time-to-complete) concurrent validity was evaluated against the Wingate testing (WAnT: mean [MP] and peak power [PP]) and a 30-sec vertical jump testing test (VJT: mean height and MP). Blood lactate concentration was measured at rest and immediately post-test. SLDT's reliability [test-retest intraclass correlation coefficients (ICC), coefficient of variation (CV), Bland-Altman plots] and sensitivity were determined (one-way ANOVA). Kendall's tau correlation analysis revealed correlations (Pbasketball players.
Yu, Jie; Wang, Xiaoxiao; Xu, Tao; Jin, Qiuheng; Duan, Jinyuan; Wu, Jie; Wu, Haiyan; Xu, Ting; Ye, Sheng
2017-10-27
Combinations of different antibodies have been shown to be more effective for managing certain diseases than monotherapy. Co-expression of the antibody mixture in a single cell line is key to reducing complexity during antibody development and manufacturing. However, co-transfection of multiple light and heavy chains into cells often leads to production of mismatched, heterodimeric by-products that are inactive, making the development of co-expression systems that robustly and efficiently produce highly active antibody mixtures a high priority. In this study, we modified the CH3 domain interface of the antibody fragment crystallizable (Fc) region by changing several charge pairs to create electrostatic interactions favoring Fc homodimer formation and disfavoring Fc heterodimer formation. When co-expressed, these modified antibodies with altered charge polarity across the Fc dimer interface preferentially formed homodimers that fully preserved the functions of each component, rather than inactive heterodimers whose formation was reduced because of rationally designed repulsive interactions. We designed eight different combinations and experimentally screened the best one, which enabled us to produce a binary antibody mixture against the EGF receptor with a minimal heterodimer contaminant. We further determined the crystal structure of a triple-mutated Fc variant in the best combination, and we elucidated the molecular interactions favoring Fc homodimer over heterodimer formation, which provided a structural basis for further optimization. The approach presented here demonstrates the feasibility of rational antibody modification for efficient and consistent production of monoclonal antibody mixtures in a single cell line and thus broadens our options for manufacturing more effective antibody-based therapeutic agents. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
Greenhalgh, Janette; Bagust, Adrian; Boland, Angela; Blundell, Michaela; Oyee, James; Beale, Sophie; Dundar, Yenal; Hockenhull, Juliet; Proudlove, Chris; Chu, Patrick
2013-05-01
The National Institute for Health and Clinical Excellence (NICE) invited the manufacturer of rituximab (RTX) [Roche] to submit evidence for the clinical and cost effectiveness of RTX as first-line maintenance treatment for patients with follicular non-Hodgkin's lymphoma (fNHL) whose disease has responded to induction therapy with RTX plus cytotoxic chemotherapy (R-CTX) in accordance with the Institute's Single Technology Appraisal (STA) process. The Liverpool Reviews and Implementation Group (LRiG) at the University of Liverpool was commissioned to act as the Evidence Review Group (ERG). This article summarizes the ERG's review of the evidence submitted by the manufacturer and provides a summary of the Appraisal Committee's (AC) decision. The clinical evidence was derived from a multi-centred, open-label, randomized phase III study (PRIMA) comparing first-line maintenance treatment with RTX with observation only in 1,018 patients with previously untreated advanced fNHL. Median time to event (MTE) for the primary endpoint of progression-free survival (PFS) in the RTX arm was not estimable due to data immaturity; median PFS in the observation arm was 48.36 months. A statistically significant benefit of RTX maintenance therapy for PFS was reported (hazard ratio [HR] 0.55, 95 % CI 0.44-0.68; p Markov methodology rather than patient simulations, the impact of patient age on the outcome and the projective PFS modelling. The ERG considered it impossible to draw firm conclusions regarding the clinical or cost effectiveness of the intervention as the dataset was as yet too immature. At a third meeting, the AC concluded that RTX could be recommended as first-line maintenance treatment for patients with fNHL whose disease has responded to induction R-CTX.
Directory of Open Access Journals (Sweden)
UNLU, M.
2015-05-01
Full Text Available A simple power electronic interface based on the line-commutated inverter (LCI has been developed in order to inject sinusoidal current to the grid for single-phase grid-connected photovoltaic (PV energy generation systems. The proposed inverter facilitates controlling the injecting/grid current with a controllable power factor in contrast to the conventional LCI system. It is achieved that the total harmonic distortion (THD of the injecting currents for the different firing angles/power factors and reference currents is about 5% or less than 5%. Thus, the grid-connected standards for injecting current are satisfied without filter equipment unlike the conventional LCI system. The proposed system has been built in MATLAB/Simulink and examined experimentally on PV array of 160 W. The simulation and experimental results are better performance than the conventional line-commutated inverter methods reported in the literature. The proposed LCI has a simple and robust structure, and it can be easily synchronized with grid thanks to self-latching property of SCRs. Therefore, it is a good alternative for the power transferring from PV panels to the utility grid in grid-connected PV systems.
Linear regression in astronomy. I
Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh
1990-01-01
Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.
Wein, Nicolas; Vulin, Adeline; Findlay, Andrew R; Gumienny, Felecia; Huang, Nianyuan; Wilton, Steve D; Flanigan, Kevin M
2017-01-01
Exon skipping strategies in Duchenne muscular dystrophy (DMD) have largely been directed toward altering splicing of exons flanking out-of-frame deletions, with the goal of restoring an open mRNA reading frame that leads to production of an internally deleted but partially functional dystrophin protein. We sought to apply exon skipping to duplication mutations, assuming that the inherently limited efficiency of antisense oligonucleotide-induced exon skipping would more frequently skip a single copy of a duplicated exon, rather than both and result in significant amounts of wild-type DMD mRNA. We tested this hypothesis in fibroblast cell lines derived from patients with a variety of single or multiple exon duplications that have been modified to allow transdifferentiation into a myogenic lineage. Using a variety of 2'O-methyl antisense oligonucleotides, significant skipping was induced for each duplication leading to a wild-type transcript as a major mRNA product. This study provides another proof of concept for the feasibility of therapeutic skipping in patients carrying exon duplications in order to express wild-type, full-length mRNA, although careful evaluation of the skipping efficiency should be performed as some exons are easier to skip than others. Such a personalized strategy is expected to be highly beneficial for this subset of DMD patients, compared to inducing expression of an internally-deleted dystrophin.
Directory of Open Access Journals (Sweden)
Shu Yong-Qian
2010-09-01
Full Text Available Abstract Background Lung cancer is a malignant carcinoma which has the highest morbidity and mortality in Chinese population. Gefitinib, a tyrosine kinase (TK inhibitor of epidermal growth factor receptor (EGFR, displays anti-tumor activity. The present data regarding first-line treatment with single agent gefitinib against non-small-cell lung cancer (NSCLC in Chinese population are not sufficient. Purpose To assess the efficacy and toxicity of gefitinib in Chinese patients with advanced non-small-cell lung cancer (NSCLC, a study of single agent treatment with gefitinib in Chinese patients was conducted. Methods 45 patients with advanced NSCLC were treated with gefitinib (250 mg daily until the disease progression or intolerable toxicity. Results Among the 45 patients, 15 patients achieved partial response (PR, 17 patients experienced stable disease (SD, and 13 patients developed progression disease (PD. None of the patients achieved complete response (CR. The tumor response rate and disease control rate was 33% and 71.1%, respectively. Symptom remission rate was 72.5%, and median remission time was 8 days. Median overall survival and median progression-free survival was 15.3 months and 6.0 months, respectively. The main induced toxicities by gefitinib were skin rash and diarrhea (53.3% and 33.3%, respectively. The minor induced toxicities included dehydration and pruritus of skin (26.7% and 22.2%, respectively. In addition, hepatic toxicity and oral ulceration occurred in few patients (6.7% and 4.4%2, respectively. Conclusions Single agent treatment with gefitinib is effective and well tolerated in Chinese patients with advanced NSCLC.
Zhao, Xiang; He, Rong; Liu, Yu; Wu, Yongkai; Kang, Leitao
2017-07-01
Cisplatin and its analogues are widely used as anti-tumor drugs in lung cancer but many cisplatin-resistant lung cancer cases have been identified in recent years. Single-stranded DNA-binding protein 1 (SSDBP1) can effectively induce H69 cell resistance to cisplatin in our previous identification; thus, it is necessary to explore the mechanism underlying the effects of SSDBP1-induced resistance to cisplatin. First, SSDBP1-overexpressed or silent cell line was constructed and used to analyze the effects of SSDBP1 on chemoresistance of lung cancer cells to cisplatin. SSDBP1 expression was assayed by real-time PCR and Western blot. Next, the effects of SSDBP1 on cisplatin sensitivity, proliferation, and apoptosis of lung cancer cell lines were assayed by MTT and flow cytometry, respectively; ABC transporters, apoptosis-related genes, and cell cycle-related genes by real-time PCR, and DNA wound repair by comet assay. Low expression of SSDBP1 was observed in H69 cells, while increased expression in cisplatin-resistant H69 cells. Upregulated expression of SSDBP1 in H69AR cells was identified to promote proliferation and cisplatin resistance and inhibit apoptosis, while downregulation of SSDBP1 to inhibit cisplatin resistance and proliferation and promoted apoptosis. Moreover, SSDBP1 promoted the expression of P2gp, MRP1, Cyclin D1, and CDK4 and inhibited the expression of caspase 3 and caspase 9. Furthermore, SSDBP1 promoted the DNA wound repair. These results indicated that SSDBP1 may induce cell chemoresistance of cisplatin through promoting DNA repair, resistance-related gene expression, cell proliferation, and inhibiting apoptosis.
International Nuclear Information System (INIS)
Wang Hao; Wang Junjie; Qu Ang; Li Jin'na; Liu Jingjia
2012-01-01
Objective: To investigate the effect and underlying mechanism of single, fractioned and continuous low dose rate radiation on CL187 colorectal cancer cell line. Methods: CL187 cells were exposed to 6 MV X-rays at a high dose rate of 4 Gy/min and 125 I seed at a low dose rate of 2.77 cGy/h with three groups:single dose radiation group (SDR), fractioned dose radiation group (FDR) by 2 Gy/f, and continuous low dose rate radiation group (CLDR). The radiation doses were 0, 2, 4 and 8 Gy. Total cell number and cell viability were determined by trypan blue. Clone forming assay was used to evaluate the cell proliferation ability. The percentage of apoptosis cells was analyzed by flow cytometry. Western blot was used to detect the protein expression levels of PHLPP2, PTEN and Bax. Results: Compared with SDR and FDR groups, the total cell number and survival fraction of CLDR group decreased. The relative biological effect (RBE) for 125 I seeds compared with 6 MV X-rays was 1.41. The percentage of apoptosis cells of CLDR group was significantly increased (t=-15.08, -11.99, P<0.05). The expression level of Bax increased in CLDR group, while no obvious changes were observed on PHLPP2 and PTEN among three groups. Conclusions: The expression level of PHLPP2 increases in SDR, FDR and CLDR group, while it seems that it was not influenced by dose rate. The expression level of Bax increased in three groups, while more colorectal CL187 cells in CLDR group may be killed due to the increase of Bax expression. (authors)
Energy Technology Data Exchange (ETDEWEB)
Kristie Cooper; Gary Pickrell; Anbo Wang
2005-11-01
This report summarizes technical progress April-September 2005 on the Phase II program ''On-Line Self-Calibrating Single Crystal Sapphire Optical Sensor Instrumentation for Accurate and Reliable Coal Gasifier Temperature Measurement'', funded by the Federal Energy Technology Center of the U.S. Department of Energy, and performed by the Center for Photonics Technology of the Bradley Department of Electrical and Computer Engineering at Virginia Tech. The outcome of the first phase of this program was the selection of broadband polarimetric differential interferometry (BPDI) for further prototype instrumentation development. This approach is based on the measurement of the optical path difference (OPD) between two orthogonally polarized light beams in a single-crystal sapphire disk. The objective of this program is to bring the sensor technology, which has already been demonstrated in the laboratory, to a level where the sensor can be deployed in the harsh industrial environments and will become commercially viable. Due to the difficulties described on the last report, field testing of the BPDI system has not continued to date. However, we have developed an alternative high temperature sensing solution, which is described in this report. The sensing system will be installed and tested at TECO's Polk Power Station. Following a site visit in June 2005, our efforts have been focused on preparing for that field test, including he design of the sensor mechanical packaging, sensor electronics, the data transfer module, and the necessary software codes to accommodate this application.. We are currently ready to start sensor fabrication.
Directory of Open Access Journals (Sweden)
Behniafar Ali
2013-01-01
Full Text Available The electric marine instruments are newly inserted in the trade and industry, for which the existence of an equipped and reliable power system is necessitated. One of the features of such a power system is that it cannot have an earth system causing the protection relays not to be able to detect the single line to ground short circuit fault. While on the other hand, the occurrence of another similar fault at the same time can lead to the double line fault and thereby the tripping of relays and shortening of vital loads. This in turn endangers the personals' security and causes the loss of military plans. From the above considerations, it is inferred that detecting the single line to ground fault in the marine instruments is of a special importance. In this way, this paper intends to detect the single line to ground fault in the power systems of the marine instruments using the wavelet transform and Multi-Layer Perceptron (MLP neural network. In the numerical analysis, several different types of short circuit faults are simulated on several marine power systems and the proposed approach is applied to detect the single line to ground fault. The results are of a high quality and preciseness and perfectly demonstrate the effectiveness of the proposed approach.
Ko, Peggy; Misaghi, Shahram; Hu, Zhilan; Zhan, Dejin; Tsukuda, Joni; Yim, Mandy; Sanford, Mark; Shaw, David; Shiratori, Masaru; Snedecor, Brad; Laird, Michael; Shen, Amy
2017-12-11
In the past few decades, a large variety of therapeutic antibodies and proteins have been expressed in Chinese hamster ovary (CHO) cells. This mammalian expression system is robust, scalable, relatively inexpensive, and importantly allows for post-translational modifications that are important for some therapeutic proteins. Historically, CHO cell lines were derived from colonies of cells grown in semi-solid or liquid plates using either serum-containing or serum-free media. Current advancements in cell sorting and imaging technologies have allowed for isolating and imaging single cell progenitors at the seeding step, significantly increasing the probability of isolating clonally derived cell lines. However, it is debatable how much population heterogeneity can be eliminated when clonally derived cell lines, originated from a single cell progenitor, are scaled up. To further investigate this phenomenon, we subcloned two different clonally derived (day 0 imaged and visually inspected) cell lines expressing antibody-X. The results showed that when six randomly chosen subclones of each line were evaluated in a production assay, these subclones displayed a range of variation in titer, specific productivity, growth, and product quality attributes. Some subclones displayed variations in transgene copy numbers. Additionally, clonal derivation did not assure stability of the derived cell lines. Our findings show that cell heterogeneity exists in a population even when derived from a single cell progenitor. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 2017. © 2017 American Institute of Chemical Engineers.
Henare, S J; Kikuchi, M; Talbot, R T; Cockrem, J F
2011-12-01
1. Simultaneous changes of cloacal gland area (CGA) and plasma luteinising hormone (LH), follicle stimulating hormone (FSH), testosterone (T), prolactin (PRL), thyroxine (T(4)) and triiodothyronine (T(3)) during photo-induced testicular growth and regression were measured in commercially bred Japanese quail from a heavy body weight line. 2. Somatically mature male Japanese quail were transferred from short days (light:dark 8L:16D) at 10°C, to long days (16L:8D) at 20°C; and sexually mature male Japanese quail were transferred from long to short days. All variables were measured at transfer and every 5 d thereafter for 35 d. 3. Transfer from short to long days caused significant increases in LH, FSH, T and testis weight (TW) after 5 d, and in CGA after 10 d. T(3) decreased after 5 d, whereas T(4) increased significantly after 25 long days and PRL did not undergo any consistent change. The testicular growth rate was k = 0·1146. 4. Transferring quail from long to short days caused significant decreases in LH and FSH after 5 d, and decreases in T, TW and CGA after 10 d. T(4) decreased after 5 d whilst T(3) increased significantly by day 15. PRL decreased significantly after 10 d then rose before declining again. The testicular regression rate was k = 0·0582. 5. The rates of photo-induced testicular development and regression in a strain of large Japanese quail did not differ from rates reported for other strains of quail. CGA was a better indicator of TW than plasma T concentrations during growth and regression. The role of PRL in photo-induced reproductive cycles in male Japanese quail remains to be determined. 6. The photoperiod-induced changes in gonad size and hormone concentrations, together provide valuable information that can be used in future studies of the endocrinology and neuroendocrinology of photoperiodism in birds.
A Novel Protection Method for Single Line-to-Ground Faults in Ungrounded Low-Inertia Microgrids
Directory of Open Access Journals (Sweden)
Liuming Jing
2016-06-01
Full Text Available This paper proposes a novel protection method for single line-to-ground (SLG faults in ungrounded low-inertia microgrids. The proposed method includes microgrid interface protection and unit protection. The microgrid interface protection is based on the difference between the zero-sequence voltage angle and the zero-sequence current angle at the microgrid interconnection transformer for fast selection of the faulty feeder. The microgrid unit protection is based on a comparison of the three zero-sequence current phase directions at each junction point of load or distributed energy resources. Methods are also included to locate the minimum fault section. The fault section location technology operates according to the coordination of microgrid unit protection. The proposed method responds to SLG faults that may occur in both the grid and the microgrid. Simulations of an ungrounded low-inertia microgrid with a relay model were carried out using Power System Computer Aided Design (PSCAD/Electromagnetic Transients including DC (EMTDC.
International Nuclear Information System (INIS)
Foster, K.D.; Kimbell, G.H.; Snelling, D.R.
1975-01-01
The CS 2 /O 2 /N 2 O flame laser has been operated for the first time under conditions in which the spectral output is nearly single line. This transition is the P 10 - 9 (17) of CO at 5.4265 μm, the same transition which was observed to oscillate in single-line fashion by Hirose et al. in an electrically initiated CO chemical laser. It is suggested that the unique behavior of this line may be due to its close proximity to a P branch transition in an adjacent band, namely the P 9 - 8 (23) line, such that the gain profiles of the two lines overlap. Calculations suggest that at the conditions of these experiments, the separation of the line centers for this pair is about 0.3 A or less. The P 10 - 9 (17) transition was also found to be totally absent under certain conditions of high multiline power, particulary at low O 2 and N 2 O flows. This may be due to absorption by a high-band R branch transition at 5.4266 μm, namely the R 15 - 16 (32) line. (U.S.)
Small angle neutron scattering study of the magnetic flux-line lattice in single crystal 2H-NbSe2
DEFF Research Database (Denmark)
Gammel, P.L.; Huse, D.A.; Kleiman, R.N.
1994-01-01
We report on a small angle neutron scattering study of the flux-line lattice in single crystal 2H-NbSe2. As the magnetic field is tilted away from the crystalline c axis, we find distortions in the flux lattice as would be expected for a mass anisotropy GAMMA = 10.1 +/- 0.9. However, we find...
Directory of Open Access Journals (Sweden)
Gee-Chen Chang
2013-09-01
Conclusion: The objective response rate, disease control rate, and safety and tolerability profile in this population of Taiwanese patients were consistent with the published findings that were conducted using Asian and Western populations. These findings support the use of single-agent, second-line pemetrexed for the treatment of advanced nonsmall cell lung cancer in Taiwanese patients.
Currently, American Type Culture Collection (ATCC) makes available two cell lines derived from the same lymphoblast-like suspension cell that have been confirmed by next-generation sequencing and RT-PCR to have either a single contaminate of BVDV2a (CRL-8037) or dual contaminates of both BVDV and BL...
An Identity for Kernel Ridge Regression
Zhdanov, Fedor; Kalnishkan, Yuri
2011-01-01
This paper derives an identity connecting the square loss of ridge regression in on-line mode with the loss of the retrospectively best regressor. Some corollaries about the properties of the cumulative loss of on-line ridge regression are also obtained.
Pedrini, D. T.; Pedrini, Bonnie C.
Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…
Puglisi, Fabio; Rea, Daniel; Kroes, Michel A; Pronzato, Paolo
2016-02-01
No 'gold standard' exists for single-agent chemotherapy of human epidermal growth factor receptor 2-negative (HER2-negative) metastatic breast cancer (MBC) in the second-line. The objective of this systematic review is to identify and appraise overall survival (OS), progression-free survival (PFS), time to progression (TTP) and Grade ≥3 adverse event evidence for single-agent chemotherapy in this setting. MEDLINE, Embase and the Cochrane Library were searched to October 2013, and PubMed October 2013 to November 2014. Electronic database searches were supplemented with hand searching of reference lists and conferences. Eligible randomised controlled trials (RCTs) employed at least one single-agent chemotherapy treatment, enrolled HER2-negative or unselected MBC patients who had progressed following first-line chemotherapy within the metastatic setting, and reported outcomes of interest for the second-line setting. Fifty-three RCTs were included in total, with most containing mixed populations by HER2 status and treatment line. Fourteen studies reported data specifically for second- and later-line treatment within the metastatic setting. Median overall survival (OS) in most trials was 8-13 months. Only one trial reported a significant difference between studied interventions in the second-line metastatic setting: nab-paclitaxel (n=131) conferred a statistically significant OS advantage vs. three-weekly paclitaxel (n=136) (median OS 13.0 vs. 10.7 months, respectively; hazard ratio 0.73, p=0.024) and improved overall safety. One RCT demonstrated significant benefit in this setting in confirmed HER2-negative MBC alongside favourable safety. Treatment line terminology was imprecise. To reliably inform patient treatment decisions, quality-of-life data are needed and precise OS estimation according to underlying patient characteristics. Copyright © 2015 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Šimko Milan
2017-09-01
Full Text Available The paper deals with the issue of constructing delay lines on the basis of surface acoustic waves and their application to single-mode oscillators. As a result of a theoretical analysis concrete delay lines are proposed.
Barimani, Shirin; Kleinebudde, Peter
2017-10-01
A multivariate analysis method, Science-Based Calibration (SBC), was used for the first time for endpoint determination of a tablet coating process using Raman data. Two types of tablet cores, placebo and caffeine cores, received a coating suspension comprising a polyvinyl alcohol-polyethylene glycol graft-copolymer and titanium dioxide to a maximum coating thickness of 80µm. Raman spectroscopy was used as in-line PAT tool. The spectra were acquired every minute and correlated to the amount of applied aqueous coating suspension. SBC was compared to another well-known multivariate analysis method, Partial Least Squares-regression (PLS) and a simpler approach, Univariate Data Analysis (UVDA). All developed calibration models had coefficient of determination values (R 2 ) higher than 0.99. The coating endpoints could be predicted with root mean square errors (RMSEP) less than 3.1% of the applied coating suspensions. Compared to PLS and UVDA, SBC proved to be an alternative multivariate calibration method with high predictive power. Copyright © 2017 Elsevier B.V. All rights reserved.
Kong, Byung-Whi; Hudson, Nicholas; Seo, Dongwon; Lee, Seok; Khatri, Bhuwan; Lassiter, Kentu; Cook, Devin; Piekarski, Alissa; Dridi, Sami; Anthony, Nicholas; Bottje, Walter
2017-01-13
Modern broiler chickens exhibit very rapid growth and high feed efficiency compared to unselected chicken breeds. The improved production efficiency in modern broiler chickens was achieved by the intensive genetic selection for meat production. This study was designed to investigate the genetic alterations accumulated in modern broiler breeder lines during selective breeding conducted over several decades. To identify genes important in determining muscle growth and feed efficiency in broilers, RNA sequencing (RNAseq) was conducted with breast muscle in modern pedigree male (PeM) broilers (n = 6 per group), and with an unselected foundation broiler line (Barred Plymouth Rock; BPR). The RNAseq analysis was carried out using Ilumina Hiseq (2 x 100 bp paired end read) and raw reads were assembled with the galgal4 reference chicken genome. With normalized RPM values, genes showing >10 average read counts were chosen and genes showing 1.3 fold change were considered as differentially expressed (DE) between PeM and BPR. DE genes were subjected to Ingenuity Pathway Analysis (IPA) for bioinformatic functional interpretation. The results indicate that 2,464 DE genes were identified in the comparison between PeM and BPR. Interestingly, the expression of genes encoding mitochondrial proteins in chicken are significantly biased towards the BPR group, suggesting a lowered mitochondrial content in PeM chicken muscles compared to BPR chicken. This result is inconsistent with more slow muscle fibers bearing a lower mitochondrial content in the PeM. The molecular, cellular and physiological functions of DE genes in the comparison between PeM and BPR include organismal injury, carbohydrate metabolism, cell growth/proliferation, and skeletal muscle system development, indicating that cellular mechanisms in modern broiler lines are tightly associated with rapid growth and differential muscle fiber contents compared to the unselected BPR line. Particularly, PDGF (platelet derived
DEFF Research Database (Denmark)
Nørgaard, P; Damstrup, L; Rygaard, K
1996-01-01
Three small cell lung cancer cell lines established from a single patient during longitudinal follow-up were examined for in vitro expression of TGF beta and TGF beta receptors, i.e. the components of an autocrine loop. GLC 14 was established prior to treatment, GLC 16 on relapse after chemotherapy...... was found in GLC 16 and GLC 19. These cell lines were also growth inhibited by exogenously administrated TGF beta 1. TGF beta 1 mRNA and protein in its latent form was only expressed in the radiotherapy-resistant cell line, GLC 19. The results indicate that disease progression in this patient was paralleled...... II receptor gene, as examined by Southern blotting. Also, the type I receptor could not be detected by ligand binding assay in this cell line, despite expression of mRNA for this receptor. This agrees with previous findings that type I receptor cannot bind TGF beta 1 without co-expression of the type...
Star, L.; Decuypere, E.; Parmentier, H.K.; Kemp, B.
2008-01-01
Effects of long-term climatic stress (heat exposure), short-term hygienic stress [lipopolysaccharide (LPS)], or combined exposure to these stressors on endocrine and oxidative stress parameters of 4 layer lines (B1, WA, WB, and WF) were investigated. The lines were earlier characterized for natural
Forecasting with Dynamic Regression Models
Pankratz, Alan
2012-01-01
One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.
Vigolo, Paolo; Mutinelli, Sabrina; Biscaro, Leonello; Stellini, Edoardo
2015-12-01
Different types of tooth preparations influence the marginal precision of zirconium-oxide based ceramic single crowns. In this in vivo study, the marginal fits of zirconium-oxide based ceramic single crowns with vertical and horizontal finish lines were compared. Forty-six teeth were chosen in eight patients indicated for extraction for implant placement. CAD/CAM technology was used for the production of 46 zirconium-oxide-based ceramic single crowns: 23 teeth were prepared with vertical finishing lines, 23 with horizontal finishing lines. One operator accomplished all clinical procedures. The zirconia crowns were cemented with glass ionomer cement. The teeth were extracted 1 month later. Marginal gaps along vertical planes were measured for each crown, using a total of four landmarks for each tooth by means of a microscope at 50× magnification. On conclusion of microscopic assessment, ESEM evaluation was completed on all specimens. The comparison of the gap between the two types of preparation was performed with a nonparametric test (two-sample Wilcoxon rank-sum test) with a level of significance fixed at p crowns with vertical and horizontal finish line preparations were not different. © 2015 by the American College of Prosthodontists.
Walton, Joseph M.; And Others
1978-01-01
Ridge regression is an approach to the problem of large standard errors of regression estimates of intercorrelated regressors. The effect of ridge regression on the estimated squared multiple correlation coefficient is discussed and illustrated. (JKS)
A NLTE line formation for neutral and singly-ionised calcium in model atmospheres of B-F stars
Sitnova, T. M.; Mashonkina, L. I.; Ryabchikova, T. A.
2018-03-01
We present non-local thermodynamic equilibrium (NLTE) line formation calculations for Ca I and Ca II in B-F stars. The sign and the magnitude of NLTE abundance corrections depend on line and stellar parameters. We determine calcium abundances for nine stars with reliable stellar parameters. For all stars, where the lines of both species could be measured, the NLTE abundances are found to be consistent within the error bars. We obtain consistent NLTE abundances from Ca II lines in the visible and near infra-red (IR, 8912-27, 9890 Å) spectrum range, in contrast with LTE, where the discrepancy between the two groups of lines ranges from -0.5 dex to 0.6 dex for different stars. Our NLTE method reproduces the Ca II 8912-27, 9890 Å lines observed in emission in the late B-type star HD 160762 with the classical plane-parallel and LTE model atmosphere. NLTE abundance corrections for lines of Ca I and Ca II were calculated in a grid of model atmospheres with 7000 K ≤ Teff ≤ 13000 K, 3.2 ≤ log g ≤ 5.0, -0.5 ≤ [Fe/H] ≤0.5, ξt= 2.0 km s-1. Our NLTE results can be applied for calcium NLTE abundance determination from Gaia spectra, given that accurate continuum normalisation and proper treatment of the hydrogen Paschen lines are provided. The NLTE method can be useful to refine calcium underabundances in Am stars and to provide accurate observational constraints on the models of diffusion.
Directory of Open Access Journals (Sweden)
Djeniže S.
2000-01-01
Full Text Available In order to find reliable Stark width data, needed in plasma spectroscopy comparision between the existing measured, calculated and predicted Stark width values was performed for ten singly ionized emitters: C, N, O, F, Ne Si, P, S, Cl and Ar in the lower lying 3s - 3p, 3p - 3d and 4s - 4p transitions. These emitters are present in many cosmic light sources. On the basis of the agreement between mentioned values 17 spectral lines from six singly ionized spectra have been recommended, for the first time, for plasma spectroscopy as spectral lines with reliable Stark width data. Critical analysis of the existing Stark width data is also given.
Nakamura, Tsuyoshi; Omasa, Takeshi
2015-09-01
Therapeutic antibodies are commonly produced by high-expressing, clonal and recombinant Chinese hamster ovary (CHO) cell lines. Currently, CHO cells dominate as a commercial production host because of their ease of use, established regulatory track record, and safety profile. CHO-K1SV is a suspension, protein-free-adapted CHO-K1-derived cell line employing the glutamine synthetase (GS) gene expression system (GS-CHO expression system). The selection of high-producing mammalian cell lines is a crucial step in process development for the production of therapeutic antibodies. In general, cloning by the limiting dilution method is used to isolate high-producing monoclonal CHO cells. However, the limiting dilution method is time consuming and has a low probability of monoclonality. To minimize the duration and increase the probability of obtaining high-producing clones with high monoclonality, an automated single cell-based clone selector, the ClonePix FL system, is available. In this study, we applied the high-throughput ClonePix FL system for cell line development using CHO-K1SV cells and investigated efficient conditions for single cell-based clone selection. CHO-K1SV cell growth at the pre-picking stage was improved by optimizing the formulation of semi-solid medium. The efficiency of picking and cell growth at the post-picking stage was improved by optimization of the plating time without decreasing the diversity of clones. The conditions for selection, including the medium formulation, were the most important factors for the single cell-based clone selection system to construct a high-producing CHO cell line. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.
A Seemingly Unrelated Poisson Regression Model
King, Gary
1989-01-01
This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.
Standards for Standardized Logistic Regression Coefficients
Menard, Scott
2011-01-01
Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…
Semagn, Kassa; Magorokosho, Cosmos; Vivek, Bindiganavile S; Makumbi, Dan; Beyene, Yoseph; Mugo, Stephen; Prasanna, B M; Warburton, Marilyn L
2012-03-25
Knowledge of germplasm diversity and relationships among elite breeding materials is fundamentally important in crop improvement. We genotyped 450 maize inbred lines developed and/or widely used by CIMMYT breeding programs in both Kenya and Zimbabwe using 1065 SNP markers to (i) investigate population structure and patterns of relationship of the germplasm for better exploitation in breeding programs; (ii) assess the usefulness of SNPs for identifying heterotic groups commonly used by CIMMYT breeding programs; and (iii) identify a subset of highly informative SNP markers for routine and low cost genotyping of CIMMYT germplasm in the region using uniplex assays. Genetic distance for about 94% of the pairs of lines fell between 0.300 and 0.400. Eighty four percent of the pairs of lines also showed relative kinship values ≤ 0.500. Model-based population structure analysis, principal component analysis, neighbor-joining cluster analysis and discriminant analysis revealed the presence of 3 major groups and generally agree with pedigree information. The SNP markers did not show clear separation of heterotic groups A and B that were established based on combining ability tests through diallel and line x tester analyses. Our results demonstrated large differences among the SNP markers in terms of reproducibility, ease of scoring, polymorphism, minor allele frequency and polymorphic information content. About 40% of the SNPs in the multiplexed chip-based GoldenGate assays were found to be uninformative in this study and we recommend 644 of the 1065 for low to medium density genotyping in tropical maize germplasm using uniplex assays. There were high genetic distance and low kinship coefficients among most pairs of lines, clearly indicating the uniqueness of the majority of the inbred lines in these maize breeding programs. The results from this study will be useful to breeders in selecting best parental combinations for new breeding crosses, mapping population development
Directory of Open Access Journals (Sweden)
Semagn Kassa
2012-03-01
Full Text Available Abstract Background Knowledge of germplasm diversity and relationships among elite breeding materials is fundamentally important in crop improvement. We genotyped 450 maize inbred lines developed and/or widely used by CIMMYT breeding programs in both Kenya and Zimbabwe using 1065 SNP markers to (i investigate population structure and patterns of relationship of the germplasm for better exploitation in breeding programs; (ii assess the usefulness of SNPs for identifying heterotic groups commonly used by CIMMYT breeding programs; and (iii identify a subset of highly informative SNP markers for routine and low cost genotyping of CIMMYT germplasm in the region using uniplex assays. Results Genetic distance for about 94% of the pairs of lines fell between 0.300 and 0.400. Eighty four percent of the pairs of lines also showed relative kinship values ≤ 0.500. Model-based population structure analysis, principal component analysis, neighbor-joining cluster analysis and discriminant analysis revealed the presence of 3 major groups and generally agree with pedigree information. The SNP markers did not show clear separation of heterotic groups A and B that were established based on combining ability tests through diallel and line x tester analyses. Our results demonstrated large differences among the SNP markers in terms of reproducibility, ease of scoring, polymorphism, minor allele frequency and polymorphic information content. About 40% of the SNPs in the multiplexed chip-based GoldenGate assays were found to be uninformative in this study and we recommend 644 of the 1065 for low to medium density genotyping in tropical maize germplasm using uniplex assays. Conclusions There were high genetic distance and low kinship coefficients among most pairs of lines, clearly indicating the uniqueness of the majority of the inbred lines in these maize breeding programs. The results from this study will be useful to breeders in selecting best parental combinations
DEFF Research Database (Denmark)
Johansen, Søren
2008-01-01
The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...
Yang, Jian; Ma, Shexia; Gao, Bo; Li, Xiaoying; Zhang, Yanjun; Cai, Jing; Li, Mei; Yao, Ling'ai; Huang, Bo; Zheng, Mei
2017-09-01
In order to accurately apportion the many distinct types of individual particles observed, it is necessary to characterize fingerprints of individual particles emitted directly from known sources. In this study, single particle mass spectral signatures from vehicle exhaust particles in a tunnel were performed. These data were used to evaluate particle signatures in a real-world PM 2.5 apportionment study. The dominant chemical type originating from average positive and negative mass spectra for vehicle exhaust particles are EC species. Four distinct particle types describe the majority of particles emitted by vehicle exhaust particles in this tunnel. Each particle class is labeled according to the most significant chemical features in both average positive and negative mass spectral signatures, including ECOC, NaK, Metal and PAHs species. A single particle aerosol mass spectrometry (SPAMS) was also employed during the winter of 2013 in Guangzhou to determine both the size and chemical composition of individual atmospheric particles, with vacuum aerodynamic diameter (d va ) in the size range of 0.2-2μm. A total of 487,570 particles were chemically analyzed with positive and negative ion mass spectra and a large set of single particle mass spectra was collected and analyzed in order to identify the speciation. According to the typical tracer ions from different source types and classification by the ART-2a algorithm which uses source fingerprints for apportioning ambient particles, the major sources of single particles were simulated. Coal combustion, vehicle exhaust, and secondary ion were the most abundant particle sources, contributing 28.5%, 17.8%, and 18.2%, respectively. The fraction with vehicle exhaust species particles decreased slightly with particle size in the condensation mode particles. Copyright © 2017 Elsevier B.V. All rights reserved.
Bondarenko, A; Zhu, Y; Qiao, L; Cortés Salazar, F; Pick, H; Girault, H H
2016-05-23
Herein, we present the intact cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) for the fingerprinting of human melanoma cancer cell lines grown on aluminium foil. To perform the MALDI-MS assay, melanoma cells were cultured on a flat and thin foil, which was directly transferred to the target plate of MALDI-MS for analysis. The influence of a wide range of cell fixation protocols (i.e. formalin-based and alcohol-based methods) and MALDI matrices on the obtained characteristic spectra was investigated. For the optimization of the MALDI-MS protocol, the MS fingerprints of the melanoma WM-239 cell line with and without an overexpressed enhanced green fluorescent protein were employed. The fingerprints obtained from WM-239 cells grown on aluminium foil were compared with the intact cell MALDI-MS of the cell pellet and presented higher sensitivity in a high m/z range. The optimized protocol was subsequently applied to characterise melanoma cell lines derived from different cancer stages and allowed identification of unique MS signals that could be used for differentiation between the studied cell lines (i.e. molecular weight equal to 10.0 kDa and 26.1 kDa).
Logic regression and its extensions.
Schwender, Holger; Ruczinski, Ingo
2010-01-01
Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.
Zhang, Yong; Gou, Miaomiao; Han, Chun; Li, Juan; Wang, Lijie; Qiao, Qian; Hu, Yi; Bai, Li; Liu, Zhefeng
2017-12-05
Apatinib has been proven to be effective and safe among patients in the third-line treatment of advanced gastric cancer in phase II and III trials. We aimed to evaluate its efficacy and safety in second-line practice, and to explore the factors associated with efficacy. Between April 2015 and May 2017, a total of 23 patients with advanced gastric adenocarcinoma or adenocarcinoma of gastroesophageal junction were enrolled and followed up retrospectively after failing the first line of systemic therapy. The median progression-free survival was 4.43 months (95% confidence interval: 1.63-7.22) and the median overall survival was 9.11 months (95% confidence interval: 8.22-9.99). Two patients achieved a partial response and 14 patients achieved stable disease. The disease control rate was 69.6% and the objective response rate was 8.7%. The most common adverse events over grade 3 were hypertension (8.7%) and thrombocytopenia (8.7%). No treatment-related death was documented during the drug administration. Apatinib is an effective regimen for the second-line treatment of advanced gastric and gastroesophageal cancer with manageable toxicity.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/.
Directory of Open Access Journals (Sweden)
Jinghan Wang
Full Text Available BACKGROUND: Intratumoral heterogeneity reflects subclonal diversity and accounts for a variety of clinically defined phenotypes including the development of drug resistance and recurrence. However, intratumoral heterogeneity of bile duct carcinoma (BDC is rarely studied. METHODS: Two highly heterogeneous cell lines named EH-CA1a and EH-CA1b were established from a primary tumor tissue of a pathologically proven BDC. Distinct heterogeneity and underlying mechanisms of two cell lines in karyotype, colony formation, tumorgenicity, and sensitivity to chemoradiotherapy were intensively studied. RESULTS: Both cell lines showed typical morphology of cancer cells. EH-CA1a cells grew as free-floating aggregates, while EH-CA1b cells grew adherently as a monolayer. EH-CA1a cells had higher cloning efficiencies and were able to keep proliferating under hypoxic condition. Coincidentally, hypoxia-induced factor-1α (HIF1α and vascular endothelial growth factor (VEGF mRNA were significantly higher in EH-CA1a cells than in EH-CA1b cells. Both cell lines were tumorigenic in nude mouse, however, EH-CA1a cells showed more aggressive characteristics. Most importantly, the EH-CA1a cells showed much more resistance against radiation and chemotherapy with gemcitabine. Metastasis-related genes including matrix metalloproteinase 2 (MMP-2, MMP-9, epithelial-mesenchymal transition (EMT markers such as Vimentin, Snail, and Twist, are more highly expressed in EH-CA1a cells than in EH-CA1b cells. Moreover, the percentage of cells expressing cancer stem cell-like marker, CD133, in EH-CA1a cells is much higher than that in EH-CA1b cells. Moreover, knockdown of CD133 in both EH-CA1a and EH-CA1b cells significantly reduced their invasive potential and increased their sensitivities to radiation and gemcitabine, suggesting the differential expression of CD133 protein may partially account for the difference in malignancy between these two cancer cells. CONCLUSION: Establishment
DEFF Research Database (Denmark)
Lali-Dastjerdi, Zohreh; Ozolins, Oskars; An, Yi
2012-01-01
The performance of cascaded single-pump fiber optical parametric amplifiers (FOPAs) is experimentally studied for the first time using recirculating loop transmission with 80-km dispersion managed spans. Error-free performance has been achieved over 320 km for 40-Gbit/s CSRZ-OOK and CSRZ...
Regression analysis by example
Chatterjee, Samprit
2012-01-01
Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded
Nonparametric modal regression
Chen, Yen-Chi; Genovese, Christopher R.; Tibshirani, Ryan J.; Wasserman, Larry
2016-01-01
Modal regression estimates the local modes of the distribution of $Y$ given $X=x$, instead of the mean, as in the usual regression sense, and can hence reveal important structure missed by usual regression methods. We study a simple nonparametric method for modal regression, based on a kernel density estimate (KDE) of the joint distribution of $Y$ and $X$. We derive asymptotic error bounds for this method, and propose techniques for constructing confidence sets and prediction sets. The latter...
Directory of Open Access Journals (Sweden)
Chandan Keerthi Kancharla
2016-12-01
Full Text Available In isolated intersection’s actuated signal control, inductive loop detector layout plays a crucial role in providingthe vehicle information to the signal controller. Based on vehicle actuations at the detector, the green time is extended till a pre-defined threshold gap-out occurs. The Federal Highway Administration (FHWA proposed various guidelines for detec-tor layouts on low-speed and high-speed approaches. This paper proposes single and multiple advance detection schemes for low-speed traffic movements, that utilizes vehicle actuations from advance detectors located upstream of the stop-line, which are able to detect spill-back queues. The proposed detection schemes operate with actuated signal control based on lane-by-lane gap-out criteria. The performance of the proposed schemes is compared with FHWA’s stop-line and single advance detection schemes in the VISSIM simulation tool. Results have shown that the proposed single advance detection schemes showed improved performance in reducing travel time delay and average number of stops per vehicle under low volumes while the multiple advance detection scheme performed well under high volumes.
Flexible survival regression modelling
DEFF Research Database (Denmark)
Cortese, Giuliana; Scheike, Thomas H; Martinussen, Torben
2009-01-01
Regression analysis of survival data, and more generally event history data, is typically based on Cox's regression model. We here review some recent methodology, focusing on the limitations of Cox's regression model. The key limitation is that the model is not well suited to represent time-varyi...
Multinomial logistic regression ensembles.
Lee, Kyewon; Ahn, Hongshik; Moon, Hojin; Kodell, Ralph L; Chen, James J
2013-05-01
This article proposes a method for multiclass classification problems using ensembles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit model can be applied to each mutually exclusive subset of the feature space without variable selection. By combining multiple models the proposed method can handle a huge database without a constraint needed for analyzing high-dimensional data, and the random partition can improve the prediction accuracy by reducing the correlation among base classifiers. The proposed method is implemented using R, and the performance including overall prediction accuracy, sensitivity, and specificity for each category is evaluated on two real data sets and simulation data sets. To investigate the quality of prediction in terms of sensitivity and specificity, the area under the receiver operating characteristic (ROC) curve (AUC) is also examined. The performance of the proposed model is compared to a single multinomial logit model and it shows a substantial improvement in overall prediction accuracy. The proposed method is also compared with other classification methods such as the random forest, support vector machines, and random multinomial logit model.
DEFF Research Database (Denmark)
Fitzenberger, Bernd; Wilke, Ralf Andreas
2015-01-01
if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...
Shalygin, A V; Vigont, V A; Glushankova, L N; Zimina, O A; Kolesnikov, D O; Skopin, A Yu; Kaznacheeva, E V
2017-07-01
An important role in intracellular calcium signaling is played by store-operated channels activated by STIM proteins, calcium sensors of the endoplasmic reticulum. In stable STIM1 knockdown HEK S4 cells, single channels activated by depletion of intracellular calcium stores were detected by cell-attached patch-clamp technique and their electrophysiological parameters were described. Comparison of the properties of single channels in HEK293 and HEK S4 cells revealed no significant differences in their current-voltage curves, while regulation of store-operated calcium channels in these cell lines depended on the level of STIM1 expression. We can conclude that electrophysiological peculiarities of store-regulated calcium entry observed in different cells can be explained by differences in STIM1 expression.
Single-channel properties of a stretch-sensitive chloride channel in the human mast cell line HMC-1.
Wang, Lina; Ding, Guanghong; Gu, Quanbao; Schwarz, Wolfgang
2010-04-01
A stretch-activated (SA) Cl(-) channel in the plasma membrane of the human mast cell line HMC-1 was identified in outside-out patch-clamp experiments. SA currents, induced by pressure applied to the pipette, exhibited voltage dependence with strong outward rectification (55.1 pS at +100 mV and an about tenfold lower conductance at -100 mV). The probability of the SA channel being open (P (o)) also showed steep outward rectification and pressure dependence. The open-time distribution was fitted with three components with time constants of tau(1o) = 755.1 ms, tau(2o) = 166.4 ms, and tau(3o) = 16.5 ms at +60 mV. The closed-time distribution also required three components with time constants of tau(1c) = 661.6 ms, tau(2c) = 253.2 ms, and tau(3c) = 5.6 ms at +60 mV. Lowering extracellular Cl(-) concentration reduced the conductance, shifted the reversal potential toward chloride reversal potential, and decreased the P (o) at positive potentials. The SA Cl(-) currents were reversibly blocked by the chloride channel blocker 4,4'-diisothiocyanatostilbene-2,2'-disulfonic acid (DIDS) but not by (Z)-1-(p-dimethylaminoethoxyphenyl)-1,2-diphenyl-1-butene (tamoxifen). Furthermore, in HMC-1 cells swelling due to osmotic stress, DIDS could inhibit the increase in intracellular [Ca(2+)] and degranulation. We conclude that in the HMC-1 cell line, the SA outward currents are mediated by Cl(-) influx. The SA Cl(-) channel might contribute to mast cell degranulation caused by mechanical stimuli or accelerate membrane fusion during the degranulation process.
Introduction to regression graphics
Cook, R Dennis
2009-01-01
Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava
Alternative Methods of Regression
Birkes, David
2011-01-01
Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s
Baik, Jong Youn; Lee, Kelvin H
2017-05-01
Chinese hamster ovary (CHO) cells, the major mammalian host cells for biomanufacturing of therapeutic proteins, have been extensively investigated to enhance productivity and product quality. However, cell line instability resulting in unexpected changes in productivity or product quality continues to be a challenge. Based on previous reports about causes and characteristics of production instability, we hypothesized that chromosomal rearrangements due to genomic instability are associated with production instability and that these events can be characterized. We developed a production instability model using secreted alkaline phosphatase (SEAP)-expressing CHO cells (CHO-SEAP) as well as a framework to quantify chromosomal rearrangements by karyotyping. In the absence of methotrexate (MTX), CHO-SEAP cells exhibited a slightly increased growth rate, a significantly decreased specific productivity, and changes in the chromosomal rearrangement ratio of seven chromosomes. In contrast, when MTX was re-introduced, the growth rate and SEAP productivity reversed to the initial values, demonstrating the reversibility of production instability in CHO-SEAP cells. Fluorescence in situ hybridization analysis identified that the SEAP genes were incorporated in the chromosomal rearrangement (insertion) part of the der(Z9) chromosome. Karyotype analysis indicated that the insertion ratio of the der(Z9) chromosome decreased in the CHO-SEAP cells grown without MTX, demonstrating a correlation between chromosomal rearrangement and production instability. Our results support a mechanism for production instability, wherein a randomly generated chromosomal rearrangement (or genotype) results in cells with a growth advantage that is also associated with non (or low)-producing traits. As a result, the non-producing cells grow faster and thereby outgrow the producing population. Biotechnol. Bioeng. 2017;114: 1045-1053. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Ali Meftah
2017-06-01
Full Text Available In an attempt to improve U II analysis, the lowest configurations of both parities have been interpreted by means of the Racah-Slater parametric method, using Cowan codes. In the odd parity, including the ground state, 253 levels of the interacting configurations 5 f 3 7 s 2 + 5 f 3 6 d 7 s + 5 f 3 6 d 2 + 5 f 4 7 p + 5 f 5 are interpreted by 24 free parameters and 64 constrained ones, with a root mean square (rms deviation of 60 cm − 1 . In the even parity, the four known configurations 5 f 4 7 s , 5 f 4 6 d , 5 f 2 6 d 2 7 s , 5 f 2 6 d 7 s 2 and the unknown 5 f 2 6 d 3 form a basis for interpreting 125 levels with a rms deviation of 84 cm − 1 . Due to perturbations, the theoretical description of the higher configurations 5 f 3 7 s 7 p + 5 f 3 6 d 7 p remains unsatisfactory. The known and predicted levels of U II are used for a determination of the partition function. The parametric study led us to a re-investigation of high resolution ultraviolet spectrum of uranium recorded at the Meudon Observatory in the late eighties, of which the analysis was unachieved. In the course of the present study, a number of 451 lines of U II has been classified in the region 2344 –2955 Å. One new level has been established as 5 f 3 6 d 7 p ( 4 I 6 K ( J = 5.5 at 39113.98 ± 0.1 cm − 1 .
P.M.C. de Boer (Paul); C.M. Hafner (Christian)
2005-01-01
textabstractWe argue in this paper that general ridge (GR) regression implies no major complication compared with simple ridge regression. We introduce a generalization of an explicit GR estimator derived by Hemmerle and by Teekens and de Boer and show that this estimator, which is more
Choi, Jeongmi; Choi, Kihwan; Kim, Jihye; Ahmed, Ahmed Yacine Badjah Hadj; Al-Othman, Zeid A; Chung, Doo Soo
2011-10-14
In order to analyze amino acids sensitively without derivatization, we have developed carrier-mediated single drop microextraction (SDME). Nonane-1-sulfonic acid was added to an acidic sample donor solution as a carrier to form neutral ion pair complexes with amino acids. The ion pair complexes were extracted to the organic phase, covering a drop of an aqueous basic acceptor phase hanging at the tip of a capillary, and then back-extracted to the basic acceptor phase, where both the amino acids and the carrier have negative charges and the ion pair complexes are broken. The resulting extract of enriched amino acids was injected into the capillary and analyzed by capillary electrophoresis. With 20-min SDME with agitation of the donor phase, enrichment factors of four aromatic amino acids were up to 120-fold, yielding the LOD of 70-500 nM. The linear dynamic ranges for corrected peak areas were 1-100 μM with linear correlation coefficients larger than 0.9959. With internal standardization, the intraday RSDs of migration times and corrected peak areas were 0.01-0.04% and 2.0-3.7%, respectively. The capabilities of sample cleanup including desalting and preconcentration of carrier-mediated SDME were demonstrated with the analysis of human urine after minimal pretreatment of acidification and centrifugation. Copyright © 2011. Published by Elsevier B.V.
[From clinical judgment to linear regression model.
Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2013-01-01
When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.
Weisberg, Sanford
2013-01-01
Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus
Hosmer, David W; Sturdivant, Rodney X
2013-01-01
A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-
Balestre, M; Von Pinho, R G; Souza, J C; Machado, J C
2008-10-21
The present study examined the importance of mean (m+a' and d) components in the performance of single-cross hybrids for the formation of new populations and determined the contribution of the mixed model (best linear unbiased predictor of random effects, BLUP) method associated with molecular markers for the choice of crosses to obtain interpopulation hybrids. Ten single-cross commercial hybrids of different companies were used for this purpose, producing all possible double-cross hybrids through a complete diallel. The hybrids were evaluated in 15 locations in the agricultural year 2005/2006, using randomized complete block design with three repetitions. In three of these locations, estimates of m+a' and d were obtained. DNA was extracted from the single-cross hybrids and 20 SSR primers were used, nine of which were linked to QTL for yield. There was no correlation between m+a' of the single-cross hybrids with general combining ability (r = -0.15) inferring that populations with lines with high means do not always produce good hybrids. Also, it was observed that the correlation between the genetic distances with specific combining ability varied from 0.31 to 0.80 in the inter-group hybrids, while in the intra-group hybrids these estimates were low and non-significant. The heritability value obtained by BLUP was high and greater than that obtained by ordinary least squares (h(2) = 0.95 and 0.86), confirming the greater selection accuracy by the BLUP method. There were no differences between the accuracy values obtained with microsatellite information and without this information, inferring that there was no advantage of progenitor information on balanced data. It can be concluded that the estimate m+a' should not be used as a deciding parameter about the potential for extracting lines from a given population. The heritability and accuracy values obtained by BLUP allow the inference that it is possible to predict success in the choice of progenitors to obtain
Grégoire, G.
2014-12-01
This chapter deals with the multiple linear regression. That is we investigate the situation where the mean of a variable depends linearly on a set of covariables. The noise is supposed to be gaussian. We develop the least squared method to get the parameter estimators and estimates of their precisions. This leads to design confidence intervals, prediction intervals, global tests, individual tests and more generally tests of submodels defined by linear constraints. Methods for model's choice and variables selection, measures of the quality of the fit, residuals study, diagnostic methods are presented. Finally identification of departures from the model's assumptions and the way to deal with these problems are addressed. A real data set is used to illustrate the methodology with software R. Note that this chapter is intended to serve as a guide for other regression methods, like logistic regression or AFT models and Cox regression.
Glyph: Symbolic Regression Tools
Quade, Markus; Gout, Julien; Abel, Markus
2018-01-01
We present Glyph - a Python package for genetic programming based symbolic regression. Glyph is designed for usage let by numerical simulations let by real world experiments. For experimentalists, glyph-remote provides a separation of tasks: a ZeroMQ interface splits the genetic programming optimization task from the evaluation of an experimental (or numerical) run. Glyph can be accessed at http://github.com/ambrosys/glyph . Domain experts are be able to employ symbolic regression in their ex...
Pansharpening via sparse regression
Tang, Songze; Xiao, Liang; Liu, Pengfei; Huang, Lili; Zhou, Nan; Xu, Yang
2017-09-01
Pansharpening is an effective way to enhance the spatial resolution of a multispectral (MS) image by fusing it with a provided panchromatic image. Instead of restricting the coding coefficients of low-resolution (LR) and high-resolution (HR) images to be equal, we propose a pansharpening approach via sparse regression in which the relationship between sparse coefficients of HR and LR MS images is modeled by ridge regression and elastic-net regression simultaneously learning the corresponding dictionaries. The compact dictionaries are learned based on the sampled patch pairs from the high- and low-resolution images, which can greatly characterize the structural information of the LR MS and HR MS images. Later, taking the complex relationship between the coding coefficients of LR MS and HR MS images into account, the ridge regression is used to characterize the relationship of intrapatches. The elastic-net regression is employed to describe the relationship of interpatches. Thus, the HR MS image can be almost identically reconstructed by multiplying the HR dictionary and the calculated sparse coefficient vector with the learned regression relationship. The simulated and real experimental results illustrate that the proposed method outperforms several well-known methods, both quantitatively and perceptually.
International Nuclear Information System (INIS)
Anthemidis, Aristidis N.; Adam, Ibrahim S.I.
2009-01-01
A novel automatic sequential injection (SI) single-drop micro-extraction (SDME) system is proposed as versatile approach for on-line metal preconcentration and/or separation. Coupled to electrothermal atomic absorption spectrometry (ETAAS) the potentials of this SI scheme are demonstrated for trace cadmium determination in water samples. A non-charged complex of cadmium with ammonium diethyldithiophosphate (DDPA) was produced and extracted on-line into a 60 μL micro-drop of di-isobutyl ketone (DIBK). The extraction procedure was performed into a newly designed flow-through extraction cell coupled on a sequential injection manifold. As the complex Cd(II)-DDPA flowed continuously around the micro-droplet, the analyte was extracting into the solvent micro-drop. All the critical parameters were optimized and offered good performance characteristics and high preconcentration ratios. For 600 s micro-extraction time, the enhancement factor was 10 and the sampling frequency was 6 h -1 . The detection limit was 0.01 μg L -1 and the precision (RSD at 0.1 μg L -1 of cadmium) was 3.9%. The proposed method was evaluated by analyzing certified reference material
Koley, Ebha; Verma, Khushaboo; Ghosh, Subhojit
2015-01-01
Restrictions on right of way and increasing power demand has boosted development of six phase transmission. It offers a viable alternative for transmitting more power, without major modification in existing structure of three phase double circuit transmission system. Inspite of the advantages, low acceptance of six phase system is attributed to the unavailability of a proper protection scheme. The complexity arising from large number of possible faults in six phase lines makes the protection quite challenging. The proposed work presents a hybrid wavelet transform and modular artificial neural network based fault detector, classifier and locator for six phase lines using single end data only. The standard deviation of the approximate coefficients of voltage and current signals obtained using discrete wavelet transform are applied as input to the modular artificial neural network for fault classification and location. The proposed scheme has been tested for all 120 types of shunt faults with variation in location, fault resistance, fault inception angles. The variation in power system parameters viz. short circuit capacity of the source and its X/R ratio, voltage, frequency and CT saturation has also been investigated. The result confirms the effectiveness and reliability of the proposed protection scheme which makes it ideal for real time implementation.
Kuchtey, J; Fewtrell, C
1996-03-01
Ca2+ imaging experiments have revealed that for a wide variety of cell types, including RBL-2H3 mucosal mast cells, there are considerable cell-to-cell differences of the Ca2+ responses of individual cells. This heterogeneity is evident in both the shape and latency of the responses. Mast cells within a single microscopic field of view, which have experienced identical culture conditions and experimental preparation, display a wide variety of responses upon antigen stimulation. We have subcloned the RBL-2H3 mucosal mast cell line to test the hypothesis that genetic heterogeneity within the population is the cause of the Ca2+ response heterogeneity. We found that cell-to-cell variability was significantly reduced in four of five clonal lines. The response heterogeneity remaining within the clones was not an experimental artifact caused by differences in the amount of fura-2 loaded by individual cells. Factors other than genetic heterogeneity must partly account for Ca2+ response heterogeneity. It is possible that the complex shapes and variability of the Ca2+ responses are reflections of the fact that there are multiple factors underlying the Ca2-response to antigen stimulation. Small differences from cell to cell in one or more of these factors could be a cause of the remaining Ca2+ response heterogeneity.
Botyánszki, János; Kasen, Daniel; Plewa, Tomasz
2018-01-01
The classic single-degenerate model for the progenitors of Type Ia supernova (SN Ia) predicts that the supernova ejecta should be enriched with solar-like abundance material stripped from the companion star. Spectroscopic observations of normal SNe Ia at late times, however, have not resulted in definite detection of hydrogen. In this Letter, we study line formation in SNe Ia at nebular times using non-LTE spectral modeling. We present, for the first time, multidimensional radiative transfer calculations of SNe Ia with stripped material mixed in the ejecta core, based on hydrodynamical simulations of ejecta–companion interaction. We find that interaction models with main-sequence companions produce significant Hα emission at late times, ruling out these types of binaries being viable progenitors of SNe Ia. We also predict significant He I line emission at optical and near-infrared wavelengths for both hydrogen-rich or helium-rich material, providing an additional observational probe of stripped ejecta. We produce models with reduced stripped masses and find a more stringent mass limit of M st ≲ 1 × 10‑4 M ⊙ of stripped companion material for SN 2011fe.
International Nuclear Information System (INIS)
Andrade, Lidia Maria; Campos, Tarcisio Passos Ribeiro de; Leite, M.F.; Goes, A.M.
2005-01-01
Radiotherapy using gamma rays is a common modality of breast cancer treatment. The aim of this research is to investigate the biological response of the human breast cancer cell line MDAMB-231 and human peripheral blood mononuclear cells (PBMC) exposed in vitro to 60 Co irradiation at a single fraction of 10 Gy, 25 Gy and 50 Gy doses at 136,4 cGy.min -1 rate. Cells were irradiated at room temperature by the Theratron 80 radiotherapy system. Biological response was evaluated through cellular viability using MTT assay and nucleus damages visualized by Propidium Iodide assay and electrophoresis agarose gel after gamma irradiation. Nucleus damages induced by 60 Co irradiation were compared to damage caused by cell exposure to 10% methanol. The 50 Gy dose of irradiation did not stimulate nucleus damages at the same level as that affected by 10% methanol induction in the MDAMB-231. Further studies are necessary to understand these mechanisms in the MDAMB-231 human breast carcinoma cell line.(author)
Energy Technology Data Exchange (ETDEWEB)
Andrade, Lidia Maria; Campos, Tarcisio Passos Ribeiro de [Universidade Federal de Minas Gerais, Belo Horizonte, MG (Brazil). Dept. de Engenharia Nuclear]. E-mail: lidia.andrade@unifenas.br; Leite, M.F. [Universidade Federal de Minas Gerais, Belo Horizonte, MG (Brazil). Dept. de Fisiologia e Biofisica; Goes, A.M. [Universidade Federal de Minas Gerais, Belo Horizonte, MG (Brazil). Dept. de Bioquimica e Imunologia
2005-10-15
Radiotherapy using gamma rays is a common modality of breast cancer treatment. The aim of this research is to investigate the biological response of the human breast cancer cell line MDAMB-231 and human peripheral blood mononuclear cells (PBMC) exposed in vitro to {sup 60} Co irradiation at a single fraction of 10 Gy, 25 Gy and 50 Gy doses at 136,4 cGy.min{sup -1} rate. Cells were irradiated at room temperature by the Theratron 80 radiotherapy system. Biological response was evaluated through cellular viability using MTT assay and nucleus damages visualized by Propidium Iodide assay and electrophoresis agarose gel after gamma irradiation. Nucleus damages induced by {sup 60} Co irradiation were compared to damage caused by cell exposure to 10% methanol. The 50 Gy dose of irradiation did not stimulate nucleus damages at the same level as that affected by 10% methanol induction in the MDAMB-231. Further studies are necessary to understand these mechanisms in the MDAMB-231 human breast carcinoma cell line.(author)
Sanz, Martin; Picazo-Bueno, Jose A.; Garcia, Javier; Micó, Vicente
2015-05-01
In this contribution we introduce MISHELF microscopy, a new concept and design of a lensless holographic microscope based on wavelength multiplexing, single hologram acquisition and digital image processing. The technique which name comes from Multi-Illumination Single-Holographic-Exposure Lensless Fresnel microscopy, is based on the simultaneous illumination and recording of three diffraction patterns in the Fresnel domain. In combination with a novel and fast iterative phase retrieval algorithm, MISHELF microscopy is capable of high-resolution (micron range) phase-retrieved (twin image elimination) biological imaging of dynamic events (video rate recording speed) since it avoids the time multiplexing needed for the in-line hologram sequence recording when using conventional phase-shifting or phase retrieval algorithms. MISHELF microscopy is validated using two different experimental layouts: one using RGB illumination and detection schemes and another using IRRB as illumination while keeping the RGB color camera as detection device. Preliminary experimental results are provided for both experimental layouts using a synthetic object (USAF resolution test target).
Energy Technology Data Exchange (ETDEWEB)
Mohammadi, Sara, E-mail: sara.mohammadi@elettra.trieste.it [The Abdus Salam International Centre for Theoretical Physics, Trieste (Italy); Synchrotron Light Source ‘Elettra’ Trieste, Strada Statale 14, km 163.5 in AREA Science Park, Basovizza 34149 (Italy); Larsson, Emanuel [Synchrotron Light Source ‘Elettra’ Trieste, Strada Statale 14, km 163.5 in AREA Science Park, Basovizza 34149 (Italy); Linköping University, SE-581 83 (Sweden); University of Trieste, Trieste (Italy); Alves, Frauke [University Hospital Goettingen, Robert Koch Strasse 40, Goettingen, Lower Saxony 37075 (Germany); Dal Monego, Simeone [Cluster in Biomedicine s.c.r.l., AREA Science Park, Strada Statale 14, km 163.5, Basovizza, 34149 Trieste (Italy); Biffi, Stefania; Garrovo, Chiara [IRCCS Burlo Garofolo, via dell’Istria 65/1, 34137 Trieste (Italy); Lorenzon, Andrea [Cluster in Biomedicine s.c.r.l., AREA Science Park, Strada Statale 14, km 163.5, Basovizza, 34149 Trieste (Italy); Tromba, Giuliana [Synchrotron Light Source ‘Elettra’ Trieste, Strada Statale 14, km 163.5 in AREA Science Park, Basovizza 34149 (Italy); Dullin, Christian, E-mail: sara.mohammadi@elettra.trieste.it [University Hospital Goettingen, Robert Koch Strasse 40, Goettingen, Lower Saxony 37075 (Germany)
2014-05-16
Quantitative analysis concerning the application of a single-distance phase-retrieval algorithm on in-line phase-contrast images of a mouse lung at different sample-to-detector distances is presented. Propagation-based X-ray phase-contrast computed tomography (PBI) has already proven its potential in a great variety of soft-tissue-related applications including lung imaging. However, the strong edge enhancement, caused by the phase effects, often hampers image segmentation and therefore the quantitative analysis of data sets. Here, the benefits of applying single-distance phase retrieval prior to the three-dimensional reconstruction (PhR) are discussed and quantified compared with three-dimensional reconstructions of conventional PBI data sets in terms of contrast-to-noise ratio (CNR) and preservation of image features. The PhR data sets show more than a tenfold higher CNR and only minor blurring of the edges when compared with PBI in a predominately absorption-based set-up. Accordingly, phase retrieval increases the sensitivity and provides more functionality in computed tomography imaging.
International Nuclear Information System (INIS)
Mohammadi, Sara; Larsson, Emanuel; Alves, Frauke; Dal Monego, Simeone; Biffi, Stefania; Garrovo, Chiara; Lorenzon, Andrea; Tromba, Giuliana; Dullin, Christian
2014-01-01
Quantitative analysis concerning the application of a single-distance phase-retrieval algorithm on in-line phase-contrast images of a mouse lung at different sample-to-detector distances is presented. Propagation-based X-ray phase-contrast computed tomography (PBI) has already proven its potential in a great variety of soft-tissue-related applications including lung imaging. However, the strong edge enhancement, caused by the phase effects, often hampers image segmentation and therefore the quantitative analysis of data sets. Here, the benefits of applying single-distance phase retrieval prior to the three-dimensional reconstruction (PhR) are discussed and quantified compared with three-dimensional reconstructions of conventional PBI data sets in terms of contrast-to-noise ratio (CNR) and preservation of image features. The PhR data sets show more than a tenfold higher CNR and only minor blurring of the edges when compared with PBI in a predominately absorption-based set-up. Accordingly, phase retrieval increases the sensitivity and provides more functionality in computed tomography imaging
Marker-assisted selection using ridge regression.
Whittaker, J C; Thompson, R; Denham, M C
2000-04-01
In cross between inbred lines, linear regression can be used to estimate the correlation of markers with a trait of interest; these marker effects then allow marker assisted selection (MAS) for quantitative traits. Usually a subset of markers to include in the model must be selected: no completely satisfactory method of doing this exists. We show that replacing this selection of markers by ridge regression can improve the mean response to selection and reduce the variability of selection response.
Directory of Open Access Journals (Sweden)
Mok Tik
2014-06-01
Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.
DEFF Research Database (Denmark)
Bache, Stefan Holst
A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....
Practical Session: Logistic Regression
Clausel, M.; Grégoire, G.
2014-12-01
An exercise is proposed to illustrate the logistic regression. One investigates the different risk factors in the apparition of coronary heart disease. It has been proposed in Chapter 5 of the book of D.G. Kleinbaum and M. Klein, "Logistic Regression", Statistics for Biology and Health, Springer Science Business Media, LLC (2010) and also by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr341.pdf). This example is based on data given in the file evans.txt coming from http://www.sph.emory.edu/dkleinb/logreg3.htm#data.
Software Regression Verification
2013-12-11
of recursive procedures. Acta Informatica , 45(6):403 – 439, 2008. [GS11] Benny Godlin and Ofer Strichman. Regression verifica- tion. Technical Report...functions. Therefore, we need to rede - fine m-term. – Mutual termination. If either function f or function f ′ (or both) is non- deterministic, then their
Multiple linear regression analysis
Edwards, T. R.
1980-01-01
Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.
Mechanisms of neuroblastoma regression
Brodeur, Garrett M.; Bagatell, Rochelle
2014-01-01
Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179
Bounded Gaussian process regression
DEFF Research Database (Denmark)
Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan
2013-01-01
We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
Directory of Open Access Journals (Sweden)
Odair Bison
2003-04-01
Full Text Available A utilização de híbridos simples comerciais de milho é uma das opções de populações para a extração de linhagens, porque são adaptados e provavelmente concentram alta freqüência de alelos favoráveis já fixados. Mesmo nos locos que estão segregando, a freqüência de alelos favoráveis é 0,5. Assim, a identificação de populações promissoras, derivadas de híbridos simples superiores, é uma boa estratégia para aumentar a eficiência dos programas de melhoramento. As populações derivadas dos híbridos simples comerciais AG9012 e C333 foram avaliadas com o objetivo de verificar o potencial dessas para extração de linhagens superiores, por meio das estimativas de parâmetros genéticos e fenotípicos, da estimativa de m+a e a metodologia proposta por Jinks & Pooni (1976. Foram avaliadas 169 famílias S1 de cada população, durante a safra agrícola de 1999/2000, na área experimental do Departamento de Biologia da UFLA, em Lavras - MG, em látice simples 13x13, sendo as parcelas constituídas por uma linha de 3 m. As características analisadas foram incidência de Phaeosphaeria maydis em duas épocas, altura de plantas, altura de espigas e produtividade de espigas despalhadas. Foi constatado que há possibilidade de se obterem linhagens com bom desempenho per se, sendo a população derivada do C333 a mais promissora, por associar resistência a Phaeosphaeria maydis e possuir média mais alta e maior probabilidade de obtenção de linhagens superiores. A metodologia proposta por Jinks & Pooni (1976 mostrou-se mais informativa do que a estimativa de m+a para a escolha de populações, mas, quando possível, as duas podem ser utilizadas simultaneamente para auxiliar na decisão dos melhoristas.Populations derived from commercial single hybrids are one of the breeder options for inbred line extraction because of their adaptation and probable high frequency of loci with fixed favorable alleles. Even the segregating loci carry
Lavaud, C; Baviere, M; Le Roy, G; Hervé, M R; Moussart, A; Delourme, R; Pilet-Nayel, M-L
2016-07-27
Understanding the effects of resistance QTL on pathogen development cycle is an important issue for the creation of QTL combination strategies to durably increase disease resistance in plants. The oomycete pathogen Aphanomyces euteiches, causing root rot disease, is one of the major factors limiting the pea crop in the main producing countries. No commercial resistant varieties are currently available in Europe. Resistance alleles at seven main QTL were recently identified and introgressed into pea agronomic lines, resulting in the creation of Near Isogenic Lines (NILs) at the QTL. This study aimed to determine the effect of main A. euteiches resistance QTL in NILs on different steps of the pathogen life cycle. NILs carrying resistance alleles at main QTL in susceptible genetic backgrounds were evaluated in a destructive test under controlled conditions. The development of root rot disease severity and pathogen DNA levels in the roots was measured during ten days after inoculation. Significant effects of several resistance alleles at the two major QTL Ae-Ps7.6 and Ae-Ps4.5 were observed on symptom appearance and root colonization by A. euteiches. Some resistance alleles at three other minor-effect QTL (Ae-Ps2.2, Ae-Ps3.1 and Ae-Ps5.1) significantly decreased root colonization. The combination of resistance alleles at two or three QTL including the major QTL Ae-Ps7.6 (Ae-Ps5.1/Ae-Ps7.6 or Ae-Ps2.2/Ae-Ps3.1/Ae-Ps7.6) had an increased effect on delaying symptom appearance and/or slowing down root colonization by A. euteiches and on plant resistance levels, compared to the effects of individual or no resistance alleles. This study demonstrated the effects of single or multiple resistance QTL on delaying symptom appearance and/or slowing down colonization by A. euteiches in pea roots, using original plant material and a precise pathogen quantification method. Our findings suggest that single resistance QTL can act on multiple or specific steps of the disease development
Directory of Open Access Journals (Sweden)
Khosravi A
2015-01-01
Full Text Available Background: Platinum-based doublet chemotherapy is the backbone of treatment in advanced non-small cell lung cancer (NSCLC however second-line treatment options are controversial particularly in patients with borderline performance status (PS of 2. The aim of this study was to compare efficacy and toxicity of weekly docetaxel versus gemcitabine in this clinical setting. Patients and methods: A total of 70 patients with advanced (stage IIIB, IV NSCLC entered this single institute study. Cases of this study had experienced disease progression after the first-line platinum-based doublet chemotherapy, with PS 0- 2 in “Eastern Cooperative Oncology Group” scale. They were randomly assigned by stratified blocks to receive docetaxel 35 mg/m2 (Arm A, n=34 or gemcitabine 1000 mg/m2 (Arm B, n=36 days 1, 8 and 15, every three weeks, for up to six cycles. Primary end point was progression free survival (PFS and secondary end points were objective response rate, disease control rate, median overall survival (OS and toxicity. Dose modification was permitted upon clinician’s discretion for each individual patient. Results: Median of PFS was 2.02 months in arm A and 2.63 months in arm B (HR= 1.279; 95% CI: 0.710-2.304, P= 0.551. Although median OS for arm A was numerically greater (9.2 months than arm B (8.3 months it was statistically non-significant (HR= 1.384; 95% CI: 0.632 to 2.809, P= 0.59. Objective response was higher in Arm B than that in Arm A (P= 0.20 but disease control rates were statistically different in both arms (P= 0.034. Statistically significant differences in term of leukopenia was seen in arm B (P= 0.013. Conclusion: This study, with limited number of cases, indicates that in advanced NSCLC, weekly docetaxel and gemcitabine are reasonable second-line treatment options with statistically similar effectiveness in terms of PFS and median OS with manageable toxicities in patients with PS 0-2.
Verze, Paolo; Imbimbo, Ciro; Cancelmo, Gennaro; Creta, Massimiliano; Palmieri, Alessandro; Mangiapia, Francesco; Buonopane, Roberto; Mirone, Vincenzo
2010-12-01
To compare extracorporeal shockwave lithotripsy (ESWL) and ureteroscopy (URS) as first-line treatments for patients with distal ureteric stones. In all, 273 patients with single, monolateral, radiopaque, distal ureteric stones of 0.5-1.5 cm were enrolled in a prospective randomized trial. Patients were randomized to undergo ESWL (137) or URS (136). The electromagnetic Modulith SLX lithotripter (Storz Medical, Switzerland) was used for ESWL and a semi-rigid ureteroscope was used for URS. Patients in both groups were compared for overall stone-free rates (SFRs), re-treatment rates, need for auxiliary procedures and complication rates. A subgroup analysis was performed in both groups according to stone size of ≤1 cm and >1 cm. Patients in the ESWL group achieved a 92.70% overall SFR with a 44.88% re-treatment rate and an 11.02% auxiliary procedure rate. Complications occurred in 15.32% of patients treated with ESWL. Patients in the URS group achieved a 94.85% overall SFR with a re-treatment rate of 7.75% and an auxiliary procedure rate of 18.60%. Complications occurred in 19.11% of patients treated with URS. In the ESWL group, the need for re-treatments and for auxiliary procedures as well as the incidence of complications was significantly higher in patients with stones of >1 cm. In patients with stones of ≤1 cm treated with ESWL the need for re-treatments and for auxiliary procedures as well as the incidence of complications was significantly lower than for those treated with URS. In centres where both techniques are available, ESWL should be the preferred treatment for patients with single distal ureteric stones of ≤1 cm and URS should be reserved for patients with stones of >1 cm. © 2010 THE AUTHORS. JOURNAL COMPILATION © 2010 BJU INTERNATIONAL.
Subset selection in regression
Miller, Alan
2002-01-01
Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...
Ridge Regression Signal Processing
Kuhl, Mark R.
1990-01-01
The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.
Regression in organizational leadership.
Kernberg, O F
1979-02-01
The choice of good leaders is a major task for all organizations. Inforamtion regarding the prospective administrator's personality should complement questions regarding his previous experience, his general conceptual skills, his technical knowledge, and the specific skills in the area for which he is being selected. The growing psychoanalytic knowledge about the crucial importance of internal, in contrast to external, object relations, and about the mutual relationships of regression in individuals and in groups, constitutes an important practical tool for the selection of leaders.
Classification and regression trees
Breiman, Leo; Olshen, Richard A; Stone, Charles J
1984-01-01
The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Better Autologistic Regression
Directory of Open Access Journals (Sweden)
Mark A. Wolters
2017-11-01
Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.
DEFF Research Database (Denmark)
Hansen, Henrik; Tarp, Finn
2001-01-01
. There are, however, decreasing returns to aid, and the estimated effectiveness of aid is highly sensitive to the choice of estimator and the set of control variables. When investment and human capital are controlled for, no positive effect of aid is found. Yet, aid continues to impact on growth via...... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes....
Hilbe, Joseph M
2009-01-01
This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...
DEFF Research Database (Denmark)
Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas
2017-01-01
In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interfac...... functionals. The software presented here is implemented in the riskRegression package.......In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...
Zimmermann, R.; Bente, M.; Sklorz, M.
2007-12-01
Polycyclic aromatic hydrocarbons (PAH) are formed as trace products in combustion processes and are emitted to the atmosphere. Larger PAH have low vapour pressure and are predominantly bound to the ambient fine particulate matter (PM). Upon inhalation, PAH show both, chronic human toxicity (i.e. many PAH are potent carcinogens) as well as acute human toxicity (i.e. inflammatory effects due to oxi-dative stress) and are discussed to be relevant for the observed health effect of ambient PM. Therefore a better understanding of the occurrence, dynamics and particle size dependence of particle bound-PAH is of great interest. On-line aerosol mass spectrometry in principle is the method of choice to investigate the size resolved changes in the chemical speciation of particles as well the status of internal vs. external mixing of chemical constituents. However the present available aerosol mass spectrometers (ATOFMS and AMS) do not allow detection of PAH from ambient air PM. In order to allow a single particle based monitoring of PAH from ambient PM a new single particle laser ionisation mass spectrometer was built and applied. The system is based on ATOFMS principle but uses a two- step photo-ionization. A tracked and sized particle firstly is laser desorbed (LD) by a IR-laser pulse (CO2-laser, λ=10.2 μm) and subsequently the released PAH are selectively ionized by an intense UV-laser pulse (ArF excimer, λ=248 nm) in a resonance enhanced multiphoton ionisation process (REMPI). The PAH-ions are detected in a time of flight mass spectrometer (TOFMS). A virtual impactor enrichment unit is used to increase the detection frequency of the ambient particles. With the current inlet system particles from about 400 nm to 10 μm are accessible. Single particle based temporal profiles of PAH containing particles ion (size distribution and PAH speciation) have been recorded in Oberschleissheim, Germany from ambient air. Furthermore profiles of relevant emission sources (e
Ridge Regression: A Regression Procedure for Analyzing correlated Independent Variables
Rakow, Ernest A.
1978-01-01
Ridge regression is a technique used to ameliorate the problem of highly correlated independent variables in multiple regression analysis. This paper explains the fundamentals of ridge regression and illustrates its use. (JKS)
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...
Adaptive metric kernel regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
2000-01-01
Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...
Adaptive Metric Kernel Regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
1998-01-01
Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...
International Nuclear Information System (INIS)
Thaler, Josef; Köhne, Claus-Henning; Karthaus, Meinolf; Mineur, Laurent; Greil, Richard; Letocha, Henry; Hofheinz, Ralf; Fernebro, Eva; Gamelin, Erick; Baños, Ana
2012-01-01
Integument-related toxicities are common during epidermal growth factor receptor (EGFR)-targeted therapy. Panitumumab is a fully human monoclonal antibody targeting the EGFR that significantly improves progression-free survival when added to chemotherapy in patients with metastatic colorectal cancer who have wild-type (WT) KRAS tumours. Primary efficacy and tolerability results from a phase II single-arm study of first-line panitumumab plus FOLFIRI in patients with metastatic colorectal cancer have been reported. Here we report additional descriptive tolerability and quality of life data from this trial. Integument-related toxicities and quality of life were analysed; toxicities were graded using modified National Cancer Institute Common Toxicity Criteria. Kaplan-Meier estimates of time to and duration of first integument-related toxicity were prepared. Quality of life was measured using EuroQoL EQ-5D and EORTC QLQ-C30. Best overall response was analysed by skin toxicity grade and baseline quality of life. Change in quality of life was analysed by skin toxicity severity. 154 patients were enrolled (WT KRAS n = 86; mutant KRAS n = 59); most (98%) experienced integument-related toxicities (most commonly rash [42%], dry skin [40%] and acne [36%]). Median time to first integument-related toxicity was 8 days; median duration was 334 days. Overall, proportionally more patients with grade 2+ skin toxicity responded (56%) compared with those with grade 0/1 (29%). Mean overall EQ-5D health state index scores (0.81 vs. 0.78), health rating scores (72.5 vs. 71.0) and QLQ-C30 global health status scores (65.8 vs. 66.7) were comparable at baseline vs. safety follow-up (8 weeks after completion), respectively and appeared unaffected by skin toxicity severity. First-line panitumumab plus FOLFIRI has acceptable tolerability and appears to have little impact on quality of life, despite the high incidence of integument-related toxicity. ClinicalTrials.gov NCT00508404
Directory of Open Access Journals (Sweden)
Lídia Maria Andrade
2005-10-01
Full Text Available Radiotherapy using gamma rays is a common modality of breast cancer treatment. The aim of this research is to investigate the biological response of the human breast cancer cell line MDAMB-231 and human peripheral blood mononuclear cells (PBMC exposed in vitro to 60 Co irradiation at a single fraction of 10 Gy, 25 Gy and 50 Gy doses at 136,4 cGy.min-1 rate. Cells were irradiated at room temperature by the Theratron 80 radiotherapy system. Biological response was evaluated through cellular viability using MTT assay and nucleus damages visualized by Propidium Iodide assay and electrophoresis agarose gel after gamma irradiation. Nucleus damages induced by 60Co irradiation were compared to damage caused by cell exposure to 10% methanol. The 50 Gy dose of irradiation did not stimulate nuclus damages at the same level as that affected by 10% methanol induction in the MDAMB-231. Further studies are necessary to understand these mechanisms in the MDAMB-231 human breast carcinoma cell line.Radioterapia utilizando radiação gama é uma modalidade comum no tratamento do câncer de mama. A proposta deste estudo é investigar a resposta biológica in vitro da linhagem celular MDAMB-231 de câncer de mama humano e células do sangue periférico humano (PBMC expostas à irradiação pelo Co60 em frações simples de 10Gy, 25Gy e 50Gy e 136,4cGy min-1 rate. As células foram irradiadas a temperatura ambiente usando o equipamento de radioterapia Theratron 80 radiotherapy system. A resposta biológica, após irradiação gama, foi avaliada através do ensaio do MTT para viabilidade celular e o do ensaio com Iodeto de Propídio para visualização do dano nuclear, além da eletroforese em gel de agarose. Os danos nucleares induzidos pelo Co60 foram comparados aos danos causados pela exposição das células à solução de metanol a 10%. Nós observamos que a dose de 50Gy não estimulou a mesma quantidade de danos nucleares que a solução de metanol a 10% nas c
Directory of Open Access Journals (Sweden)
Thaler Josef
2012-09-01
Full Text Available Abstract Background Integument-related toxicities are common during epidermal growth factor receptor (EGFR-targeted therapy. Panitumumab is a fully human monoclonal antibody targeting the EGFR that significantly improves progression-free survival when added to chemotherapy in patients with metastatic colorectal cancer who have wild-type (WT KRAS tumours. Primary efficacy and tolerability results from a phase II single-arm study of first-line panitumumab plus FOLFIRI in patients with metastatic colorectal cancer have been reported. Here we report additional descriptive tolerability and quality of life data from this trial. Methods Integument-related toxicities and quality of life were analysed; toxicities were graded using modified National Cancer Institute Common Toxicity Criteria. Kaplan-Meier estimates of time to and duration of first integument-related toxicity were prepared. Quality of life was measured using EuroQoL EQ-5D and EORTC QLQ-C30. Best overall response was analysed by skin toxicity grade and baseline quality of life. Change in quality of life was analysed by skin toxicity severity. Results 154 patients were enrolled (WT KRAS n = 86; mutant KRAS n = 59; most (98% experienced integument-related toxicities (most commonly rash [42%], dry skin [40%] and acne [36%]. Median time to first integument-related toxicity was 8 days; median duration was 334 days. Overall, proportionally more patients with grade 2+ skin toxicity responded (56% compared with those with grade 0/1 (29%. Mean overall EQ-5D health state index scores (0.81 vs. 0.78, health rating scores (72.5 vs. 71.0 and QLQ-C30 global health status scores (65.8 vs. 66.7 were comparable at baseline vs. safety follow-up (8 weeks after completion, respectively and appeared unaffected by skin toxicity severity. Conclusions First-line panitumumab plus FOLFIRI has acceptable tolerability and appears to have little impact on quality of life, despite the high incidence of integument
Sammak, Majed; Thorbergsson, Egill; Grönstedt, Tomas; Genrup, Magnus
2013-08-01
The aim of this study was to compare single- and twin-shaft oxy-fuel gas turbines in a semiclosed oxy-fuel combustion combined cycle (SCOC-CC). This paper discussed the turbomachinery preliminary mean-line design of oxy-fuel compressor and turbine. The conceptual turbine design was performed using the axial through-flow code luax-t, developed at Lund University. A tool for conceptual design of axial compressors developed at Chalmers University was used for the design of the compressor. The modeled SCOC-CC gave a net electrical efficiency of 46% and a net power of 106 MW. The production of 95% pure oxygen and the compression of CO 2 reduced the gross efficiency of the SCOC-CC by 10 and 2 percentage points, respectively. The designed oxy-fuel gas turbine had a power of 86 MW. The rotational speed of the single-shaft gas turbine was set to 5200 rpm. The designed turbine had four stages, while the compressor had 18 stages. The turbine exit Mach number was calculated to be 0.6 and the calculated value of AN 2 was 40 · 10 6 rpm 2 m 2 . The total calculated cooling mass flow was 25% of the compressor mass flow, or 47 kg/s. The relative tip Mach number of the compressor at the first rotor stage was 1.15. The rotational speed of the twin-shaft gas generator was set to 7200 rpm, while that of the power turbine was set to 4800 rpm. A twin-shaft turbine was designed with five turbine stages to maintain the exit Mach number around 0.5. The twin-shaft turbine required a lower exit Mach number to maintain reasonable diffuser performance. The compressor turbine was designed with two stages while the power turbine had three stages. The study showed that a four-stage twin-shaft turbine produced a high exit Mach number. The calculated value of AN 2 was 38 · 10 6 rpm 2 m 2 . The total calculated cooling mass flow was 23% of the compressor mass flow, or 44 kg/s. The compressor was designed with 14 stages. The preliminary design parameters of the turbine and
Lecture notes on ridge regression
van Wieringen, Wessel N.
2015-01-01
The linear regression model cannot be fitted to high-dimensional data, as the high-dimensionality brings about empirical non-identifiability. Penalized regression overcomes this non-identifiability by augmentation of the loss function by a penalty (i.e. a function of regression coefficients). The ridge penalty is the sum of squared regression coefficients, giving rise to ridge regression. Here many aspect of ridge regression are reviewed e.g. moments, mean squared error, its equivalence to co...
Variable Selection in ROC Regression
Directory of Open Access Journals (Sweden)
Binhuan Wang
2013-01-01
Full Text Available Regression models are introduced into the receiver operating characteristic (ROC analysis to accommodate effects of covariates, such as genes. If many covariates are available, the variable selection issue arises. The traditional induced methodology separately models outcomes of diseased and nondiseased groups; thus, separate application of variable selections to two models will bring barriers in interpretation, due to differences in selected models. Furthermore, in the ROC regression, the accuracy of area under the curve (AUC should be the focus instead of aiming at the consistency of model selection or the good prediction performance. In this paper, we obtain one single objective function with the group SCAD to select grouped variables, which adapts to popular criteria of model selection, and propose a two-stage framework to apply the focused information criterion (FIC. Some asymptotic properties of the proposed methods are derived. Simulation studies show that the grouped variable selection is superior to separate model selections. Furthermore, the FIC improves the accuracy of the estimated AUC compared with other criteria.
Chiba, Mitsuro; Tsuji, Tsuyotoshi; Nakane, Kunio; Tsuda, Satoko; Ishii, Hajime; Ohno, Hideo; Watanabe, Kenta; Ito, Mai; Komatsu, Masafumi; Sugawara, Takeshi
2017-01-01
Approximately 30% of patients with Crohn disease (CD) are unresponsive to biologics. No previous study has focused on a plant-based diet in an induction phase of CD treatment. To investigate the remission rate of infliximab combined with a plant-based diet as first-line (IPF) therapy for CD. This was a prospective single-group trial conducted at tertiary hospitals. Subjects included consecutive adults with a new diagnosis (n = 26), children with a new diagnosis (n = 11), and relapsing adults (n = 9) with CD who were naïve to treatment with biologics. Patients were admitted and administered a standard induction therapy with infliximab (5 mg/kg; 3 infusions at 0, 2, and 6 weeks). Additionally, they received a lacto-ovo-semivegetarian diet. The primary end point was remission, defined as the disappearance of active CD symptoms at week 6. Secondary end points were Crohn Disease Activity Index (CDAI) score, C-reactive protein (CRP) concentration, and mucosal healing. Two adults with a new diagnosis were withdrawn from the treatment protocol because of intestinal obstruction. The remission rates by the intention-to-treat and per-protocol analyses were 96% (44/46) and 100% (44/44), respectively. Mean CDAI score (314) on admission decreased to 63 at week 6 (p < 0.0001). Mean CRP level on admission (5.3 mg/dL) decreased to 0.2 (p < 0.0001). Mucosal healing was achieved in 46% (19/41) of cases. IPF therapy can induce remission in most patients with CD who are naïve to biologics regardless of age or whether they have a new diagnosis or relapse.
Turner, T R; Hayhurst, J D; Hayward, D R; Bultitude, W P; Barker, D J; Robinson, J; Madrigal, J A; Mayor, N P; Marsh, S G E
2018-02-01
The hyperpolymorphic HLA genes play important roles in disease and transplantation and act as genetic markers of migration and evolution. A panel of 107 B-lymphoblastoid cell lines (B-LCLs) was established in 1987 at the 10th International Histocompatibility Workshop as a resource for the immunogenetics community. These B-LCLs are well characterised and represent diverse ethnicities and HLA haplotypes. Here we have applied Pacific Biosciences' Single Molecule Real-Time (SMRT) DNA sequencing to HLA type 126 B-LCL, including the 107 International HLA and Immunogenetics Workshop (IHIW) cells, to ultra-high resolution. Amplicon sequencing of full-length HLA class I genes (HLA-A, -B and -C) and partial length HLA class II genes (HLA-DRB1, -DQB1 and -DPB1) was performed. We typed a total of 931 HLA alleles, 895 (96%) of which were consistent with the typing in the IPD-IMGT/HLA Database (Release 3.27.0, January 20, 2017), with 595 (64%) typed at a higher resolution. Discrepant types, including novel alleles (n = 10) and changes in zygosity (n = 13), as well as previously unreported types (n = 34) were observed. In addition, patterns of linkage disequilibrium were distinguished by four-field resolution typing of HLA-B and HLA-C. By improving and standardising the HLA typing of these B-LCLs, we have ensured their continued usefulness as a resource for the immunogenetics community in the age of next generation DNA sequencing. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Ramos, Patrícia; Schmitz, Marcos; Filgueira, Daza; Votto, Ana Paula; Durruthy, Michael; Gelesky, Marcos; Ruas, Caroline; Yunes, João; Tonel, Mariana; Fagan, Solange; Monserrat, José
2017-07-01
Saxitoxins (STXs) are potent neurotoxins that also induce cytotoxicity through the generation of reactive oxygen species. Carbon nanotubes (CNTs) are nanomaterials that can promote a Trojan horse effect, facilitating the entry of toxic molecules to cells when adsorbed to nanomaterials. The interaction of pristine single-walled (SW)CNTs and carboxylated (SWCNT-COOH) nanotubes with STX was evaluated by ab initio simulation and bioassays using the cell line HT-22. Cells (5 × 10 4 cells/mL) were exposed to SWCNT and SWCNT-COOH (5 μg mL -1 ), STX (200 μg L -1 ), SWCNT+STX, and SWCNT-COOH+STX for 30 min or 24 h. Results of ab initio simulation showed that the interaction between SWCNT and SWCNT-COOH with STX occurs in a physisorption. The interaction of SWCNT+STX induced a decrease in cell viability. Cell proliferation was not affected in any treatment after 30 min or 24 h of exposure (p > 0.05). Treatment with SWCNT-COOH induced high reactive oxygen species levels, an effect attenuated in SWCNT-COOH+STX treatment. In terms of cellular oxygen consumption, both CNTs when coexposed with STX antagonize the toxin effect. Based on these results, it can be concluded that the results obtained in vitro corroborate the semiempirical evidence found using density functional theory ab initio simulation. Environ Toxicol Chem 2017;36:1728-1737. © 2016 SETAC. © 2016 SETAC.
Kuhl, Mark R.
1990-01-01
Current navigation requirements depend on a geometric dilution of precision (GDOP) criterion. As long as the GDOP stays below a specific value, navigation requirements are met. The GDOP will exceed the specified value when the measurement geometry becomes too collinear. A new signal processing technique, called Ridge Regression Processing, can reduce the effects of nearly collinear measurement geometry; thereby reducing the inflation of the measurement errors. It is shown that the Ridge signal processor gives a consistently better mean squared error (MSE) in position than the Ordinary Least Mean Squares (OLS) estimator. The applicability of this technique is currently being investigated to improve the following areas: receiver autonomous integrity monitoring (RAIM), coverage requirements, availability requirements, and precision approaches.
Rigoni, Marta; Torri, Emanuele; Nollo, Giandomenico; Zarantonello, Diana; Laudon, Alessandro; Sottini, Laura; Guarrera, Giovanni Maria; Brunori, Giuliano
2017-06-01
Despite several studies reporting similar outcomes for peritoneal dialysis (PD) and hemodialysis (HD), the former is underused worldwide, with a PD prevalence of 15% in Italy. In 2008, the Unit of Nephrology and Dialysis of the Healthcare Trust of the Autonomous Province of Trento implemented a successful PD program which has increased the proportion of PD incident patients from 7 to 47%. We aimed to assess the effect of this extensive use of PD by comparing HD and PD in terms of survival and time-to-transplantation. A total of 334 HD and 153 PD incident patients were enrolled between January 2008 and December 2014. After screening for exclusion criteria and propensity score matching, 279 HD and 132 PD patients were analyzed. Survival and time-to-transplantation were assessed by competing-risks regression models, using death and transplantation as primary and competing events. Crude and adjusted regression models for survival revealed the absence of significant differences between HD and PD cumulative incidence functions (subhazard ratio: 1.09, p = 0.62 and 1.34, p = 0.10, respectively). Differently, crude and adjusted regression models for transplantation revealed a lower time-to-transplantation for PD versus HD patients (subhazard ratio: 2.34, p < 0.01, and 2.57, p < 0.01, respectively). The waiting time for placement in the transplant waiting list was longer in HD than PD patients (330 vs. 224 days, p < 0.01). The extensive use of PD did not lead to any statistically significant difference in mortality. Furthermore, PD was associated with lower time to transplantation. PD may be a viable option for large-scale dialytic treatment in the advanced chronic kidney disease population.
Calculating a Stepwise Ridge Regression.
Morris, John D.
1986-01-01
Although methods for using ordinary least squares regression computer programs to calculate a ridge regression are available, the calculation of a stepwise ridge regression requires a special purpose algorithm and computer program. The correct stepwise ridge regression procedure is given, and a parallel FORTRAN computer program is described.…
Modified Regression Correlation Coefficient for Poisson Regression Model
Kaengthong, Nattacha; Domthong, Uthumporn
2017-09-01
This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).
Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun
2016-07-01
In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Directory of Open Access Journals (Sweden)
Aktas G
2016-04-01
Full Text Available Gokmen Aktas,1 Tulay Kus,1 Mehmet Emin Kalender,1 Alper Sevinc,1 Celaletdin Camci,1 Seval Kul2 1Division of Medical Oncology, Department of Internal Medicine, School of Medicine, Gaziantep Oncology Hospital, Gaziantep University, Gaziantep, Turkey; 2Department of Biostatistics, School of Medicine, Gaziantep University, Gaziantep, Turkey Purpose: The number of patients who make it to receive third-line chemotherapy is increasing owing to the improvements in adverse-event management of chemotherapy for small-cell lung cancer (SCLC. Sequencing of optimal treatment for SCLC is still a challenge for oncologists. In this paper, we aim to present a different approach to the treatment of SCLC.Methods: Between January 2008 and July 2014, all patients diagnosed with extensive-stage SCLC and treated with third-line chemotherapy at Gaziantep University Oncology Hospital were analyzed retrospectively. Disease control rates and progression-free survival (PFS for first-, second-, and third-line chemotherapy, and overall survival (OS were recorded. Survival analysis was calculated by using Kaplan–Meier method.Results: A total of 255 SCLC patients were screened, and 25 of those patients who received third-line chemotherapy were included in this study. Median age was 57±10.131 years (range: 39–74 years. Disease control rates at first-, second-, and third-line chemotherapy were 92%, 68%, and 44%, respectively. Fourteen patients received irinotecan followed by topotecan, and eleven patients received topotecan followed by irinotecan. Second-line median PFS was statistically better in patients treated with irinotecan at second-line compared with those treated with topotecan (21 vs 12 weeks, P=0.018. Comparison of third-line median PFS of the two groups was not statistically significant (14 vs 12 weeks, P=0.986. Median OS was not statistically significant in patients who received irinotecan followed by topotecan vs those who received topotecan followed by
Andrews, J; Honeybourne, D; Jevons, G; Boyce, M; Wise, R; Bello, A; Gajjar, D
2003-03-01
A microbiological assay was used to measure concentrations of garenoxacin (BMS-284756) in plasma, bronchial mucosa (BM), alveolar macrophages (AM) and epithelial lining fluid (ELF), following a single 600 mg oral dose. Twenty-four healthy subjects were allocated into four nominal time intervals after the dose, 2.5-3.5, 4.5-5.5, 10.5-11.5 and 23.5-24.5 h. Mean concentrations in plasma, BM, AM and ELF, respectively, for the four nominal time windows were for 2.5-3.5 h 10.0 mg/L (S.D. 2.8), 7.0 mg/kg (S.D. 1.3), 106.1 mg/L (S.D. 60.3) and 9.2 mg/L (S.D. 3.6); 4.5-5.5 h 8.7 mg/L (S.D. 2.2), 6.0 mg/kg (S.D. 1.9), 158.6 mg/L (S.D. 137.4) and 14.3 mg/L (S.D. 8.2); 10.5-11.5 h 6.1 mg/L (S.D. 1.9), 4.0 mg/kg (S.D. 1.4), 76.0 mg/L (S.D. 47.7) and 7.9 mg/L (S.D. 4.6); and 23.5-24.5 h 2.1 mg/L (S.D. 0.5), 1.7 mg/kg (S.D. 0.7), 30.7 mg/L (S.D. 12.9) and 3.3 mg/L (S.D. 2.3). Concentrations at all sites exceeded MIC(90)s for the common respiratory pathogens Haemophilus influenzae (0.03 mg/L), Moraxella catarrhalis (0.015 mg/L) and Streptococcus pneumoniae (0.06 mg/L). These data suggest that garenoxacin should be effective in the treatment of community-acquired pneumonia and chronic obstructive pulmonary disease.
Lanier, Claire M; McTyre, Emory; LeCompte, Michael; Cramer, Christina K; Hughes, Ryan; Watabe, Kounosuke; Lo, Hui-Wen; O'Neill, Stacey; Munley, Michael T; Laxton, Adrian W; Tatter, Stephen B; Ruiz, Jimmy; Chan, Michael D
2018-02-01
It is presently unknown whether patients with brain metastases from heavily pre-treated cancers have a significantly different prognosis than those with less pre-treatment. In this study we sought to identify whether the number of prior lines of systemic therapy are associated with clinical outcomes in patients with brain metastases who received stereotactic radiosurgery (SRS). Between July 2000 and July 2017, 377 patients with brain metastases were treated with upfront SRS. We performed a large, single institution retrospective analysis of these patients. Kaplan Meier analysis was used to estimate survival times. Competing risk analysis was used to estimate times to local failure (LF) and distant brain failure (DBF). Multivariate analysis was performed to estimate the hazard ratios (HRs) for overall survival (OS), neurologic and non-neurologic death for patients with 1, 2 and 3+ lines of prior systemic therapy. Of the 1077 patients with brain metastases treated with SRS, 377 received prior systemic therapy with a median of 1 (range: 1-9) lines of prior therapy. Median OS was 8.70 months (95% CI, 7.9-9.5). Median OS for patients with 1 prior line of therapy, 2 prior lines of therapy and 3 or greater lines of therapy were 9.93-, 9.05-, and 6.18-months, respectively (log rank p = .04). Lines of therapy as a continuous variable was not associated with LF or DBF on competing risk analysis. The percentage of patients that died of neurological death was 36%. Greater prior lines of therapy (1 vs. 2 vs. 3 and greater) was associated with a greater likelihood of dying of non-neurologic death (gray's p = .01), but was not associated with likelihood of dying of neurologic death (p = .57). Lines of therapy are associated with OS and non-neurologic death but are not associated with neurologic death, LF or DBF. Copyright © 2017 Elsevier B.V. All rights reserved.
Polynomial regression analysis and significance test of the regression function
International Nuclear Information System (INIS)
Gao Zhengming; Zhao Juan; He Shengping
2012-01-01
In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)
Recursive Algorithm For Linear Regression
Varanasi, S. V.
1988-01-01
Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.
DEFF Research Database (Denmark)
Hansen, Torben Frøstrup; Christensen, René Depont; Andersen, Rikke Fredslund
2012-01-01
PURPOSE: Bevacizumab and chemotherapy is a common choice for first-line treatment of metastatic colorectal cancer (mCRC). So far, no predictive markers have been identified. The aim was to investigate the possible predictive value of single nucleotide polymorphisms (SNPs) in the vascular endothel......PURPOSE: Bevacizumab and chemotherapy is a common choice for first-line treatment of metastatic colorectal cancer (mCRC). So far, no predictive markers have been identified. The aim was to investigate the possible predictive value of single nucleotide polymorphisms (SNPs) in the vascular...... endothelial growth factor (VEGF) system in this setting. METHODS: Pre-treatment blood samples and response evaluations were available from 218 of the 249 included patients. All patients received bevacizumab and chemotherapy comprising fluorouracil and leucovorin or capecitabine combined with either...... marker for bevacizumab plus chemotherapy in patients with mCRC. Patients with the A allele appeared to have increased response rates. The results call for validation....
DEFF Research Database (Denmark)
Yethiraj, M.; Mook, H.A.; Forgan, E.M.
1994-01-01
A flux‐line lattice (FLL) was observed in a single crystal of Bi2.15Sr1.95CaCu2O8+x (BSCCO) using small‐angle neutron scattering methods. The sample has a superconducting transition at 85 K. The flux‐line lattice is observed to melt, evidenced by the rapid disappearance of diffracted intensity...... as the temperature is increased above a field‐dependent melting temperature. Diffracted intensity due to the vortex lattice also falls off as the applied field is increased. It is believed that this is a manifestation of the transition of the three‐dimensional flux lines into two‐dimensional pancake vortices...
Methods of Detecting Outliers in A Regression Analysis Model ...
African Journals Online (AJOL)
PROF. O. E. OSUAGWU
2013-06-01
Jun 1, 2013 ... This is the type of linear regression that involves only two variables one independent and one dependent plus the random error term. The simple linear regression model assumes that there is a straight line (linear) relationship between the dependent variable Y and the independent variable X. This can be.
Combining Alphas via Bounded Regression
Directory of Open Access Journals (Sweden)
Zura Kakushadze
2015-11-01
Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.
Zavala, Anamaria G; O'Dowd, John M; Fortunato, Elizabeth A
2015-12-16
Previously, we reported that the absence of the ataxia telangiectasia mutated (ATM) kinase, a critical DNA damage response (DDR) signaling component for double-strand breaks, caused no change in HCMV Towne virion production. Later, others reported decreased AD169 viral titers in the absence of ATM. To address this discrepancy, human foreskin fibroblasts (HFF) and three ATM(-) lines (GM02530, GM05823, and GM03395) were infected with both Towne and AD169. Two additional ATM(-) lines (GM02052 and GM03487) were infected with Towne. Remarkably, both previous studies' results were confirmed. However, the increased number of cell lines and infections with both lab-adapted strains confirmed that ATM was not necessary to produce wild-type-level titers in fibroblasts. Instead, interactions between individual virus strains and the cellular microenvironment of the individual ATM(-) line determined efficiency of virion production. Surprisingly, these two commonly used lab-adapted strains produced drastically different titers in one ATM(-) cell line, GM05823. The differences in titer suggested a rapid method for identifying genes involved in differential virion production. In silico comparison of the Towne and AD169 genomes determined a list of 28 probable candidates responsible for the difference. Using serial iterations of an experiment involving virion entry and input genome nuclear trafficking with a panel of related strains, we reduced this list to four (UL129, UL145, UL147, and UL148). As a proof of principle, reintroduction of UL148 largely rescued genome trafficking. Therefore, use of a battery of related strains offers an efficient method to narrow lists of candidate genes affecting various virus life cycle checkpoints. Human cytomegalovirus (HCMV) infection of multiple cell lines lacking ataxia telangiectasia mutated (ATM) protein produced wild-type levels of infectious virus. Interactions between virus strains and the microenvironment of individual ATM(-) lines
Dudurych, [No Value; Rosolowski, E
2000-01-01
Overhead ground wires (GW) of extra high voltage (EHV) power transmission lines, apart from lightning-induced overvoltage protection are frequently used for carrier-current communication. In this case the ground wires are suspended on insulators, the dielectric strength of which should be sufficient
Directory of Open Access Journals (Sweden)
Jaime Araujo Cobuci
2012-09-01
Full Text Available Milk yield test-day records on the first three lactations of 25,500 Holstein cows were used to estimate genetic parameters and predict breeding values for nine measures of persistency and 305-d milk yield in a random regression animal model using two criteria to define the fixed regression. Legendre polynomials of fourth and fifth orders were used to model the fixed and random regressions of lactation curves. The fixed regressions were adjusted for average milk yield on populations (single or subpopulations (multiple formed by cows that calved at the same age and in the same season. Akaike Information (AIC and Bayesian Information (BIC criteria indicated that models with multiple regression lactation curves had the best fit to test-day milk records of first lactations, while models with a single regression curve had the best fit for the second and third lactations. Heritability and genetic correlation estimates between persistency and milk yield differed significantly depending on the lactation order and the measures of persistency used. These parameters did not differ significantly depending on the criteria used for defining the fixed regressions for lactation curves. In general, the heritability estimates were higher for first (0.07 to 0.43, followed by the second (0.08 to 0.21 and third (0.04 to 0.10 lactation. The rank of sires resulting from the processes of genetic evaluation for milk yield or persistency using random regression models differed according to the criteria used for determining the fixed regression of lactation curve.
Conjoined legs: Sirenomelia or caudal regression syndrome?
Das, Sakti Prasad; Ojha, Niranjan; Ganesh, G Shankar; Mohanty, Ram Narayan
2013-01-01
Presence of single umbilical persistent vitelline artery distinguishes sirenomelia from caudal regression syndrome. We report a case of a12-year-old boy who had bilateral umbilical arteries presented with fusion of both legs in the lower one third of leg. Both feet were rudimentary. The right foot had a valgus rocker-bottom deformity. All toes were present but rudimentary. The left foot showed absence of all toes. Physical examination showed left tibia vara. The chest evaluation in sitting re...
Time-adaptive quantile regression
DEFF Research Database (Denmark)
Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik
2008-01-01
An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....
Hofstetter, Robert; Fassauer, Georg M; Link, Andreas
2018-02-15
On-line solid-phase supercritical fluid extraction (SFE) and chromatography (SFC) coupled to mass spectrometry (MS) has been evaluated for its usefulness with respect to metabolic profiling and pharmacological investigations of ketamine in humans. The aim of this study was to develop and validate a rapid, highly selective and sensitive SFE-SFC-MS method for the quantification of ketamine and its metabolites in miniature amounts in human urine excluding liquid-liquid extraction (LLE). Several conditions were optimized systematically following the requirements of the European Medicines Agency: selectivity, carry-over, calibration curve parameters (LLOQ, range and linearity), within- and between-run accuracy and precision, dilution integrity, matrix effect, and stability. The method, which required a relatively small volume of human urine (20 μL per sample), was validated for pharmacologically and toxicologically relevant concentrations ranging from 25.0 to 1000 ng/mL (r 2 > 0.995). The lower limit of quantification (LLOQ) for all compounds was found to be as low as 0.5 ng. In addition, stability of analytes during removal of water from the urine samples using different conditions (filter paper or ISOLUTE® HM-N) was studied. In conclusion, the method developed in this study can be successfully applied to studies of ketamine metabolites in humans, and may pave the way for routine application of on-line SFE-SFC-MS in clinical investigations. Copyright © 2018 Elsevier B.V. All rights reserved.
Retro-regression--another important multivariate regression improvement.
Randić, M
2001-01-01
We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.
Bias-corrected quantile regression estimation of censored regression models
Cizek, Pavel; Sadikoglu, Serhan
2018-01-01
In this paper, an extension of the indirect inference methodology to semiparametric estimation is explored in the context of censored regression. Motivated by weak small-sample performance of the censored regression quantile estimator proposed by Powell (J Econom 32:143–155, 1986a), two- and
Quantile regression theory and applications
Davino, Cristina; Vistocco, Domenico
2013-01-01
A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and
DEFF Research Database (Denmark)
Nissen, K.K.; Vogel, Ulla Birgitte; Nexo, B.A.
2009-01-01
We studied the importance of certain polymorphisms on human chromosome 19q13.3 for drug sensitivity in human tumor cell cultures. NCI60 is a panel of 60 established tumor-derived cell lines, which have been tested for their sensitivity to tens of thousands of different drugs. Here we investigate...... the correlations between the responses of the NCI60 cells to different anticancer drugs and their respective alleles of five DNA polymorphisms located in a cancer-related chromosomal area. One polymorphism, located in the 5' noncoding region of the gene ASE-1, alias CD3EAP, proved to be associated with drug...... sensitivity (P=0.025). The same polymorphism has previously been associated with treatment response of multiple myeloma after bone marrow ablation. The polymorphism ASE-1-e1 was of importance for the drug response in the human cancer cell lines investigated and could eventually become important...
Czech Academy of Sciences Publication Activity Database
Pól, Jaroslav; Hyötyläinen, T.; Ranta-Aho, O.; Riekkola, M. L.
2004-01-01
Roč. 1052, 1-2 (2004), s. 25-31 ISSN 0021-9673 R&D Projects: GA AV ČR KJB4031405 Grant - others:Academy of Finland Projects(FI) 48867; Academy of Finland Projects(FI) 52746 Institutional research plan: CEZ:AV0Z4031919 Keywords : lycopene * on-line SFE-LC * supercritical fluid extraction Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 3.359, year: 2004
Directory of Open Access Journals (Sweden)
Qing Chen
Full Text Available To investigate the effects of trastuzumab (herceptin and fulvestrant (falsodex either in combination or alone, on downstream cell signaling pathways in lab-cultured human HR+/HER2+ breast cancer cell lines ZR-75-1 and BT-474, as well as on protein expression levels in mouse xenograft tissue.Cells were cultivated in the presence of trastuzumab or fulvestrant or both. Molecular events that resulted in an inhibition of cell proliferation and cell cycle progression or in an increased rate of apoptosis were studied. The distribution and abundance of the proteins p-Akt and p-Erk expressed in these cells in response to single agents or combinatorial treatment were also investigated. In addition, the effects of trastuzumab and fulvestrant, either as single agents or in combination on tumor growth as well as on expression of the protein p-MED1 expressed in in vivo mouse xenograft models was also examined.Cell proliferation was increasingly inhibited by trastuzumab or fulvestrant or both, with a CI1 in both human cell lines. The rate of apoptosis increased only in the BT-474 cell line and not in the ZR-75-1 cell line upon treatment with fulvestrant and not trastuzumab as a single agent (P0.05. Cell accumulation in the G1 phase of cell cycle was investigated in all treatment groups (P<0.05, and the combination of trastuzumab and fulvestrant reversed the effects of fulvestrant alone on p-Akt and p-Erk protein expression levels. Using ZR-75-1 or BT-474 to generate in vivo tumor xenografts in BALB/c athymic mouse models, we showed that a combination of both drugs resulted in a stronger inhibition of tumor growth (P<0.05 and a greater decrease in the levels of activated MED1 (p-MED1 expressed in tumor issues compared with the use of either drug as a single agent.We demonstrate that the administration of trastuzumab and fulvestrant in combination results in positive synergistic effects on both, ZR-75-1 and BT-474 cell lines. This combinatorial approach is
DEFF Research Database (Denmark)
Mizuno, Takayuki; Shibahara, K.; Ono, Hirotaka
2016-01-01
We demonstrate 32-core dense space-division multiplexed (DSDM) unidirectional transmission of PDM-16QAM 20-WDM signals over 1644.8 km employing a low-crosstalk single-mode heterogeneous 32-core fiber in a partial recirculating-loop system.......We demonstrate 32-core dense space-division multiplexed (DSDM) unidirectional transmission of PDM-16QAM 20-WDM signals over 1644.8 km employing a low-crosstalk single-mode heterogeneous 32-core fiber in a partial recirculating-loop system....
Vaeth, Michael; Skovlund, Eva
2004-06-15
For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.
Confidence bands for inverse regression models
International Nuclear Information System (INIS)
Birke, Melanie; Bissantz, Nicolai; Holzmann, Hajo
2010-01-01
We construct uniform confidence bands for the regression function in inverse, homoscedastic regression models with convolution-type operators. Here, the convolution is between two non-periodic functions on the whole real line rather than between two periodic functions on a compact interval, since the former situation arguably arises more often in applications. First, following Bickel and Rosenblatt (1973 Ann. Stat. 1 1071–95) we construct asymptotic confidence bands which are based on strong approximations and on a limit theorem for the supremum of a stationary Gaussian process. Further, we propose bootstrap confidence bands based on the residual bootstrap and prove consistency of the bootstrap procedure. A simulation study shows that the bootstrap confidence bands perform reasonably well for moderate sample sizes. Finally, we apply our method to data from a gel electrophoresis experiment with genetically engineered neuronal receptor subunits incubated with rat brain extract
Logistic Regression: Concept and Application
Cokluk, Omay
2010-01-01
The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…
Testing discontinuities in nonparametric regression
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
Illuminance Flow Estimation by Regression
Karlsson, S.M.; Pont, S.C.; Koenderink, J.J.; Zisserman, A.
2010-01-01
We investigate the estimation of illuminance flow using Histograms of Oriented Gradient features (HOGs). In a regression setting, we found for both ridge regression and support vector machines, that the optimal solution shows close resemblance to the gradient based structure tensor (also known as
Directory of Open Access Journals (Sweden)
Taliha KELEŞ
2016-12-01
Full Text Available Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR and the comparison of classical linear regression (CLR and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it was seen that OR line has appeared to present a much better fit for the data than CLR line. Depending on those results, the OR is thought to be a regression technique to obtain more accurate results than CLR at simple linear regression studies.
Fungible weights in logistic regression.
Jones, Jeff A; Waller, Niels G
2016-06-01
In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Tumor regression patterns in retinoblastoma
International Nuclear Information System (INIS)
Zafar, S.N.; Siddique, S.N.; Zaheer, N.
2016-01-01
To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)
Khokhlov, S. A.; Miroshnichenko, A. S.; Zharikov, S. V.; Manset, N.; Arkharov, A. A.; Efimova, N.; Klimanov, S.; Larionov, V. M.; Kusakin, A. V.; Kokumbaeva, R. I.; Omarov, Ch. T.; Kuratov, K. S.; Kuratova, A. K.; Rudy, R. J.; Laag, E. A.; Crawford, K. B.; Swift, T. K.; Puetter, R. C.; Perry, R. B.; Chojnowski, S. D.; Agishev, A.; Caton, D. B.; Hawkins, R. L.; Smith, A. B.; Reichart, D. E.; Kouprianov, V. V.; Haislip, J. B.
2018-04-01
We report the results of spectroscopic and photometric observations of the emission-line object AS 386. For the first time we found that it exhibits the B[e] phenomenon and fits the definition of an FS CMa type object. The optical spectrum shows the presence of a B-type star with the following properties: T eff = 11,000 ± 500 K, log L/L ⊙ = 3.7 ± 0.3, a mass of 7 ± 1 M ⊙, and a distance D = 2.4 ± 0.3 kpc from the Sun. We detected regular radial velocity variations of both absorption and emission lines with the following orbital parameters: P orb =131.27 ± 0.09 days, semiamplitude K 1 = 51.7 ± 3.0 km s‑1, systemic radial velocity γ = ‑31.8 ± 2.6 km s‑1, and a mass function of f(m) = 1.9 ± 0.3 M ⊙. AS 386 exhibits irregular variations of the optical brightness (V = 10.92 ± 0.05 mag), while the near-IR brightness varies up to ∼0.3 mag following the spectroscopic period. We explain this behavior by a variable illumination of the dusty disk inner rim by the B-type component. Doppler tomography based on the orbital variations of emission-line profiles shows that the material is distributed near the B-type component and in a circumbinary disk. We conclude that the system has undergone a strong mass transfer that created the circumstellar material and increased the B-type component mass. The absence of any traces of a secondary component, whose mass should be ≥7 M ⊙, suggests that it is most likely a black hole.
Honeybourne, D; Andrews, J M; Cunningham, B; Jevons, G; Wise, R
1999-01-01
The concentrations of clinafloxacin were measured in serum, bronchial mucosa, alveolar macrophages and epithelial lining fluid after single 200 mg oral doses of clinafloxacin had been administered to 15 subjects who were undergoing bronchoscopy. Concentrations were measured using a microbiological assay method. Mean concentrations in serum, bronchial mucosa, alveolar macrophages and epithelial lining fluid at a mean of 1.27 h post-dose were 1.54, 2.65, 15.60 and 2.71 mg/L respectively. These site concentrations exceeded the MIC90 for common respiratory pathogens and indicate that clinafloxacin is likely to be effective in the treatment of a wide range of respiratory tract infections.
Regression analysis with categorized regression calibrated exposure: some interesting findings
Directory of Open Access Journals (Sweden)
Hjartåker Anette
2006-07-01
Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a
Directory of Open Access Journals (Sweden)
Mohamed Mesmoudi
2016-06-01
Full Text Available Background: The goal of this study is to determine the efficacy and toxicity of a non-platinum based chemotherapy combination using irinotecan associated to bolus 5-FU as first line treatment in advanced gastric cancer. Materiel and methods: Retrospective analysis of a population of patients treated for metastatic and locally advanced gastric cancer with irinotecan and 5-FU as upfront chemotherapy. Results: Thirteen patients were enrolled. The median age was 56 years. Seven patients were males and six were of females. Ten patients had a metastatic disease and three patients had a locally advanced disease. Patients received a total number of 43 cycles of chemotherapy. Overall response rate was 38,4%, median time to progression (TTP was 3 months, and median overall survival was 4 months. Three patients (23,1% presented grade 3 /4 neutropenia complicated with an infectious episode with fever in two cases, three patients (23,1% required blood transfusion for a grade 4 anemia, and one patient (7,6% was hospitalized for a severe episode of diarrhea. Conclusion: Three weekly irinotecan and bolus 5-FU is an interesting combination as first line treatment of advanced gastric cancer; designed clinical trials are needed to confirm the activity of this combination.
Abstract Expression Grammar Symbolic Regression
Korns, Michael F.
This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.
Matsuura, Ryosuke; Takada, Marina; Kokuho, Takehiro; Tsuboi, Takamitsu; Kameyama, Ken-Ichiro; Takeuchi, Kaoru
2017-08-01
The bovine parainfluenza virus type 3 BN-CE vaccine strain was obtained by serial passage of the BN-1 strain in chicken embryonic fibroblasts (CEF). We previously identified a substitution (L288I) in the fusion (F) protein between the two strains. To examine the effect of the substitution on CEF adaptation and attenuation, we generated a recombinant BN-1 strain with the L288I substitution in the F protein (F L288I -EGFP). F L288I -EGFP replicated more efficiently than a recombinant BN-1 strain (wt-EGFP) in semi-suitable cell lines, suggesting that the L288I substitution was established in the BN-1 strain during the process of adaptation in CEF.
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Ohara-Imaizumi, Mica; Aoyagi, Kyota [Department of Biochemistry, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo 181-8611 (Japan); Akimoto, Yoshihiro [Department of Anatomy, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo 181-8611 (Japan); Nakamichi, Yoko; Nishiwaki, Chiyono [Department of Biochemistry, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo 181-8611 (Japan); Kawakami, Hayato [Department of Anatomy, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo 181-8611 (Japan); Nagamatsu, Shinya, E-mail: shinya@ks.kyorin-u.ac.jp [Department of Biochemistry, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo 181-8611 (Japan)
2009-12-04
To analyze the exocytosis of glucagon-like peptide-1 (GLP-1) granules, we imaged the motion of GLP-1 granules labeled with enhanced yellow fluorescent protein (Venus) fused to human growth hormone (hGH-Venus) in an enteroendocrine cell line, STC-1 cells, by total internal reflection fluorescent (TIRF) microscopy. We found glucose stimulation caused biphasic GLP-1 granule exocytosis: during the first phase, fusion events occurred from two types of granules (previously docked granules and newcomers), and thereafter continuous fusion was observed mostly from newcomers during the second phase. Closely similar to the insulin granule fusion from pancreatic {beta} cells, the regulated biphasic exocytosis from two types of granules may be a common mechanism in glucose-evoked hormone release from endocrine cells.
Maubec, Eve; Petrow, Peter; Scheer-Senyarich, Isabelle; Duvillard, Pierre; Lacroix, Ludovic; Gelly, Julien; Certain, Agnès; Duval, Xavier; Crickx, Béatrice; Buffard, Valérie; Basset-Seguin, Nicole; Saez, Pierre; Duval-Modeste, Anne-Bénédicte; Adamski, Henri; Mansard, Sandrine; Grange, Florent; Dompmartin, Anne; Faivre, Sandrine; Mentré, France; Avril, Marie-Françoise
2011-09-01
To evaluate the efficacy and safety of cetuximab, a monoclonal antibody that inhibits the epidermal growth factor receptor (EGFR), as a first-line monotherapy in patients with unresectable squamous cell carcinoma of the skin (SCCS). Thirty-six patients received cetuximab (initial dose of 400 mg/m(2) followed by subsequent weekly doses of 250 mg/m(2)) for at least 6 weeks with a 48-week follow-up. The primary end point was the disease control rate (DCR) at 6 weeks (according to Response Evaluation Criteria in Solid Tumors [RECIST] criteria). Secondary end points included best response rate, overall survival, progression-free survival (PFS), and toxicity assessment. Association of treatment efficacy with RAS mutations or FcγR genotypes was investigated. Median age of the study population was 79 years. DCR at 6 weeks was obtained in 25 of 36 patients (69%; 95% CI, 52% to 84%) of the intention-to-treat population. The best responses were eight partial responses and two complete responses. There were no cetuximab-related deaths. There were three related serious adverse events: two grade 4 infusion reactions and one grade 3 interstitial pneumopathy. Grade 1 to 2 acne-like rash occurred in 78% of patients and was associated with prolonged PFS. One HRAS mutation was identified. Combined FcγRIIa-131H/H and/or FcγRIIIa-158V/V polymorphisms were not associated with the clinical outcomes. As a first-line treatment in patients with unresectable SCCS, cetuximab achieved 69% DCR. A randomized phase III trial is warranted to confirm that cetuximab may be considered as a therapeutic option especially in elderly patients. The low frequency of RAS mutations in SCCS makes SCCS tumors attractive for EGFR inhibition.
Puri, Prem; Kutasy, Balazs; Colhoun, Eric; Hunziker, Manuela
2012-10-01
In recent years the endoscopic injection of dextranomer/hyaluronic acid has become an established alternative to long-term antibiotic prophylaxis and the surgical management of vesicoureteral reflux. We determined the safety and effectiveness of the endoscopic injection of dextranomer/hyaluronic acid as first line treatment for high grade vesicoureteral reflux. Between 2001 and 2010, 1,551 children (496 male, 1,055 female, median age 1.6 years) underwent endoscopic correction of intermediate and high grade vesicoureteral reflux using dextranomer/hyaluronic acid soon after the diagnosis of vesicoureteral reflux on initial voiding cystourethrogram. Vesicoureteral reflux was unilateral in 761 children and bilateral in 790. Renal scarring was detected in 369 (26.7%) of the 1,384 patients who underwent dimercapto-succinic acid imaging. Reflux grade in the 2,341 ureters was II in 98 (4.2%), III in 1,340 (57.3%), IV in 818 (34.9%) and V in 85 (3.6%). Followup ultrasound and voiding cystourethrogram were performed 3 months after the outpatient procedure, and renal ultrasound was performed annually thereafter. Patients were followed for 3 months to 10 years (median 5.6 years). Vesicoureteral reflux resolved after the first, second and third endoscopic injection of dextranomer/hyaluronic acid in 2,039 (87.1%), 264 (11.3%) and 38 (1.6%) ureters, respectively. Febrile urinary tract infections developed during followup in 69 (4.6%) patients. None of the patients in the series needed reimplantation of ureters or experienced any significant complications. Our results confirm the safety and efficacy of the endoscopic injection of dextranomer/hyaluronic acid in the eradication of high grade vesicoureteral reflux. We recommend this 15-minute outpatient procedure as the first line of treatment for high grade vesicoureteral reflux. Copyright © 2012 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
From Rasch scores to regression
DEFF Research Database (Denmark)
Christensen, Karl Bang
2006-01-01
Rasch models provide a framework for measurement and modelling latent variables. Having measured a latent variable in a population a comparison of groups will often be of interest. For this purpose the use of observed raw scores will often be inadequate because these lack interval scale propertie....... This paper compares two approaches to group comparison: linear regression models using estimated person locations as outcome variables and latent regression models based on the distribution of the score....
Testing Heteroscedasticity in Robust Regression
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2011-01-01
Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf
Regression methods for medical research
Tai, Bee Choo
2013-01-01
Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the
Dimension Reduction Regression in R
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Sanford Weisberg
2002-01-01
Full Text Available Regression is the study of the dependence of a response variable y on a collection predictors p collected in x. In dimension reduction regression, we seek to find a few linear combinations β1x,...,βdx, such that all the information about the regression is contained in these linear combinations. If d is very small, perhaps one or two, then the regression problem can be summarized using simple graphics; for example, for d=1, the plot of y versus β1x contains all the regression information. When d=2, a 3D plot contains all the information. Several methods for estimating d and relevant functions of β1,..., βdhave been suggested in the literature. In this paper, we describe an R package for three important dimension reduction methods: sliced inverse regression or sir, sliced average variance estimates, or save, and principal Hessian directions, or phd. The package is very general and flexible, and can be easily extended to include other methods of dimension reduction. It includes tests and estimates of the dimension , estimates of the relevant information including β1,..., βd, and some useful graphical summaries as well.
Lines of Best Fit by Graphics and the Wald Line.
Henriksen, Melvin, Ed.; Wagon, Stan, Ed.
1991-01-01
Using a graphical analysis of the linear best fit for a set of Cartesian data points, the drawbacks of the least-squares method for determining this best fit are discussed. The Wald Line, which utilizes a variation of the geometric mean, is proposed as the best alternative to the least-squares regression line particularly when the data contain…
International Nuclear Information System (INIS)
Hebert, S; Perkins, G K; El-Salam, M Abd; Caplin, A D
2003-01-01
The interaction between vortices and columnar defects has been investigated in detail in Bi 2 Sr 2 CaCu 2 O 8 crystals irradiated with heavy ions along one direction, in one sample at 45 deg. from the c-axis, and in another at 75 deg. At all temperatures down to ∼30 K the irreversible magnetization is a maximum when the field is aligned with columns, although this peak is much more prominent at high temperatures and when the irreversibility field is approached. In the temperature-field-angle regime where the effect of the columns is dominant, the creep rate is close to 0.3, with little field or temperature dependence. These results can be understood in terms of line-like vortices, pinned both by columns and by point-like disorder, with much of the latter arising from collateral damage by the irradiation. The narrowness of the peak in the angular dependences is consistent with a locked state of the vortices to the columns
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Luca Laurenti
2013-05-01
Full Text Available Currently standard first line therapy for fit patients with B-CLL/SLL are fludarabine-based regimens. Elderly patients or patients with comorbidities poorly tolerate purine analogue-based chemotherapy and they are often treated with Chlorambucil (Chl. However, complete response (CR and overall response (OR rates with Chl are relatively low. We now investigated whether the addition of Rituximab to Chl will improve the efficacy without impairing the tolerability in elderly and unfit patients. We included in our study 27 elderly or unfit patients that had not received prior therapy. All patients were treated with Chl (1mg/Kg per 28-day cycle for 8 cycles plus Rituximab (375 mg/m2 for the first course and 500 mg/m2 for subsequent cycles until the 6th cycle. We obtained an OR rate of 74%. The most frequent adverse effect was grade 3-4 neutropenia, which occurred in 18.5% of the patients. Infections or grade 3-4 extra-hematological side effects were not recorded. None of the patients required reduction of dose, delay of therapy or hospitalization. Overall, these data suggest that Chl-R is an effective and well tolerated regimen in elderly/unfit patients with CLL.
Hypothesis Testing of Parameters for Ordinary Linear Circular Regression
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Abdul Ghapor Hussin
2006-07-01
Full Text Available This paper presents the hypothesis testing of parameters for ordinary linear circular regression model assuming the circular random error distributed as von Misses distribution. The main interests are in testing of the intercept and slope parameter of the regression line. As an illustration, this hypothesis testing will be used in analyzing the wind and wave direction data recorded by two different techniques which are HF radar system and anchored wave buoy.
Logistic regression for dichotomized counts.
Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W
2016-12-01
Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.
Indian Academy of Sciences (India)
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GENERAL ARTICLE. Single-Molecule Spectroscopy. Every Molecule is Different! Kankan Bhattacharyya. Keywords. Single-molecule spectroscopy. (SMS), confocal microscopy,. FCS, sm-FRET, FLIM. 1 High-resolution spectrum re- fers to a spectrum consisting of very sharp lines. The sharp lines clearly display transitions to ...
International Nuclear Information System (INIS)
Prost, Lionel Robert
2007-01-01
The High Current Experiment (HCX) at Lawrence Berkeley National Laboratory is part of the US program that explores heavy-ion beam as the driver option for fusion energy production in an Inertial Fusion Energy (IFE) plant. The HCX is a beam transport experiment at a scale representative of the low-energy end of an induction linear accelerator driver. The primary mission of this experiment is to investigate aperture fill factors acceptable for the transport of space-charge-dominated heavy-ion beams at high intensity (line charge density ∼0.2 (micro)C/m) over long pulse durations (4 (micro)s) in alternating gradient focusing lattices of electrostatic or magnetic quadrupoles. This experiment is testing transport issues resulting from nonlinear space-charge effects and collective modes, beam centroid alignment and steering, envelope matching, image charges and focusing field nonlinearities, halo and, electron and gas cloud effects. We present the results for a coasting 1 MeV K + ion beam transported through ten electrostatic quadrupoles. The measurements cover two different fill factor studies (60% and 80% of the clear aperture radius) for which the transverse phase-space of the beam was characterized in detail, along with beam energy measurements and the first halo measurements. Electrostatic quadrupole transport at high beam fill factor (∼80%) is achieved with acceptable emittance growth and beam loss. We achieved good envelope control, and re-matching may only be needed every ten lattice periods (at 80% fill factor) in a longer lattice of similar design. We also show that understanding and controlling the time dependence of the envelope parameters is critical to achieving high fill factors, notably because of the injector and matching section dynamics
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Prost, Lionel Robert [Univ. of California, Berkeley, CA (United States)
2004-01-01
The High Current Experiment (HCX) at Lawrence Berkeley National Laboratory is part of the US program that explores heavy-ion beam as the driver option for fusion energy production in an Inertial Fusion Energy (IFE) plant. The HCX is a beam transport experiment at a scale representative of the low-energy end of an induction linear accelerator driver. The primary mission of this experiment is to investigate aperture fill factors acceptable for the transport of space-charge-dominated heavy-ion beams at high intensity (line charge density ~0.2 μC/m) over long pulse durations (4 μs) in alternating gradient focusing lattices of electrostatic or magnetic quadrupoles. This experiment is testing transport issues resulting from nonlinear space-charge effects and collective modes, beam centroid alignment and steering, envelope matching, image charges and focusing field nonlinearities, halo and, electron and gas cloud effects. We present the results for a coasting 1 MeV K^{+} ion beam transported through ten electrostatic quadrupoles. The measurements cover two different fill factor studies (60% and 80% of the clear aperture radius) for which the transverse phase-space of the beam was characterized in detail, along with beam energy measurements and the first halo measurements. Electrostatic quadrupole transport at high beam fill factor (~80%) is achieved with acceptable emittance growth and beam loss. We achieved good envelope control, and re-matching may only be needed every ten lattice periods (at 80% fill factor) in a longer lattice of similar design. We also show that understanding and controlling the time dependence of the envelope parameters is critical to achieving high fill factors, notably because of the injector and matching section dynamics.
Nonparametric Mixture of Regression Models.
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.
Regression filter for signal resolution
International Nuclear Information System (INIS)
Matthes, W.
1975-01-01
The problem considered is that of resolving a measured pulse height spectrum of a material mixture, e.g. gamma ray spectrum, Raman spectrum, into a weighed sum of the spectra of the individual constituents. The model on which the analytical formulation is based is described. The problem reduces to that of a multiple linear regression. A stepwise linear regression procedure was constructed. The efficiency of this method was then tested by transforming the procedure in a computer programme which was used to unfold test spectra obtained by mixing some spectra, from a library of arbitrary chosen spectra, and adding a noise component. (U.K.)
Logistic regression for circular data
Al-Daffaie, Kadhem; Khan, Shahjahan
2017-05-01
This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.
Bayesian variable selection in regression
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Mitchell, T.J.; Beauchamp, J.J.
1987-01-01
This paper is concerned with the selection of subsets of ''predictor'' variables in a linear regression model for the prediction of a ''dependent'' variable. We take a Bayesian approach and assign a probability distribution to the dependent variable through a specification of prior distributions for the unknown parameters in the regression model. The appropriate posterior probabilities are derived for each submodel and methods are proposed for evaluating the family of prior distributions. Examples are given that show the application of the Bayesian methodology. 23 refs., 3 figs.
Jiao, Yanjing; Cheng, Wang; Deng, Qiang; Yang, Huan; Wen, Hai-Hu
2018-02-01
Measurements on magnetization and relaxation have been carried out on an optimally doped Ba1-xKxBiO3+δ single crystal with Tc = 31.3 K. Detailed analysis is undertaken on the data. Both the dynamical relaxation and conventional relaxation have been measured leading to the self-consistent determination of the magnetization relaxation rate. It is found that the data are well described by the collective pinning model leading to the glassy exponent of about μ ≈ 1.64-1.68 with the magnetic fields of 1 and 3 T. The analysis based on Maley's method combining with the conventional relaxation data allows us to determine the current dependent activation energy U which yields a μ value of about 1.23-1.29 for the magnetic fields of 1 and 3 T. The second magnetization peaks appear in wide temperature region from 2 K to 24 K. The separation between the second peak field and the irreversibility field becomes narrow when temperature is increased. When the two fields are close to each other, we find that the second peak evolves into a step-like transition of magnetization. Finally, we present a vortex phase diagram and demonstrate that the vortex dynamics in Ba1-xKxBiO3 can be used as a model system for studying the collective vortex pining.
A Matlab program for stepwise regression
Directory of Open Access Journals (Sweden)
Yanhong Qi
2016-03-01
Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.
A novel generalized ridge regression method for quantitative genetics.
Shen, Xia; Alam, Moudud; Fikse, Freddy; Rönnegård, Lars
2013-04-01
As the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithm for situations in which the number of parameters largely exceeds the number of observations. The computationally demanding parts of the method depend mainly on the number of observations and not the number of parameters. The algorithm was implemented in the R package bigRR based on the previously developed package hglm. Using such an approach, a heteroscedastic effects model (HEM) was also developed, implemented, and tested. The efficiency for different data sizes were evaluated via simulation. The method was tested for a bacteria-hypersensitive trait in a publicly available Arabidopsis data set including 84 inbred lines and 216,130 SNPs. The computation of all the SNP effects required <10 sec using a single 2.7-GHz core. The advantage in run time makes permutation test feasible for such a whole-genome model, so that a genome-wide significance threshold can be obtained. HEM was found to be more robust than ordinary RR (a.k.a. SNP-best linear unbiased prediction) in terms of QTL mapping, because SNP-specific shrinkage was applied instead of a common shrinkage. The proposed algorithm was also assessed for genomic evaluation and was shown to give better predictions than ordinary RR.
Grigoryan, Rita S; Yang, Bo; Keshelava, Nino; Barnhart, Jerry R; Reynolds, C Patrick
2007-11-01
The F7-26 monoclonal antibody (Mab) has been reported to be specific for single-strand DNA damage (ssDNA) and to also identify cells in apoptosis. We carriedout studies to determine if F7-26 binding measured by flow cytometry was able to specifically identify exogenous ssDNA as opposed to DNA damage from apoptosis. Neuroblastoma cells were treated with melphalan (L-PAM), fenretinide, 4-hydroperoxycyclophosphamide (4-HC)+/-pan-caspase inhibitor BOC-d-fmk, topotecan or with 10Gy gamma radiation+/-hydrogen peroxide (H2O2) and fixed immediately postradiation. Cytotoxicity was measured by DIMSCAN digital imaging fluorescence assay. The degree of ssDNA damage was analyzed by flow cytometry using Mab F7-26, with DNA visualized by propidium iodide counterstaining. Flow cytometry was used to measure apoptosis detected by terminal deoxynucleotidyltransferase (TUNEL) assay and reactive oxygen species (ROS) by carboxy-dichlorofluorescein diacetate. Irradiated and immediately fixed neuroblastoma cells showed increased ssDNA, but not apoptosis by TUNEL (TUNEL-negative). 4-HC or L-PAM+/-BOC-d-fmk increased ssDNA (F7-26-positive), but BOC-d-fmk prevented TUNEL staining. Fenretinide increased apoptosis by TUNEL but not ssDNA damage detected with F7-26. Enhanced ssDNA in neuroblastoma cells treated with radiation+H2O2 was associated with increased ROS. Topotecan increased both ssDNA and cytotoxicity in 4-HC-treated cells. These data demonstrate that Mab F7-26 recognized ssDNA due to exogenous DNA damage, rather than apoptosis. This assay should be useful to characterize the mechanism of action of antineoplastic drugs. Copyright (c) 2007 International Society for Analytical Cytology.
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Azmi Nor Mohd Farez Ahmat
2017-12-01
Full Text Available Introduction: Pazopanib is the standard of care for metastatic renal cell carcinoma (mRCC. Previous studies on this indication were limited to patients who were selected on the basis of a fairly preserved performance status and normal organ function. Thus, the clinical trial population may not be representative of all patients seen in real-world practice. Based on these considerations, this prospective single-centre observational study was designed to evaluate the treatment outcomes and safety profile of pazopanib in Malaysian population. Patients and methods: Patients prescribed with pazopanib between June 2015 and June 2017 were recruited and followed up for 2-years or till death whichever comes first. Progression-free survival (PFS and overall survival (OS were evaluated. Multivariate and survival analysis were performed. Results: Twenty-seven patients were treated with pazopanib where 89% had clear cell histology. Sixteen patients (59% were intermediate risk and 41% were poor risk based on Memorial Sloan Kettering Cancer Center (MSKCC criteria. All patients experienced at least one adverse event. The most common were cutaneous toxicity (92% followed by proteinuria, hypertension, diarrhoea and mucositis. Treatment interruption was needed in 15 patients. The median PFS and OS were 9.57 months and 15.5 months, respectively. In multivariate analysis, MSKCC risk score demonstrates strong predictive treatment outcome. The median PFS was 14.5 months in intermediate risk and 3.96 months in poor risk (OR: 0.2, p<0.001. However, the median OS is still immature to be reported since 63% of intermediate risk group is still alive at 2-years follow-up. Conclusion: In mRCC patients, treatment with pazopanib was effective in patients with intermediate risk group. In terms of safety, patient tolerated pazopanib quite well with mostly experienced grade 1 to 2 adverse events.
On logistic regression analysis of dichotomized responses.
Lu, Kaifeng
2017-01-01
We study the properties of treatment effect estimate in terms of odds ratio at the study end point from logistic regression model adjusting for the baseline value when the underlying continuous repeated measurements follow a multivariate normal distribution. Compared with the analysis that does not adjust for the baseline value, the adjusted analysis produces a larger treatment effect as well as a larger standard error. However, the increase in standard error is more than offset by the increase in treatment effect so that the adjusted analysis is more powerful than the unadjusted analysis for detecting the treatment effect. On the other hand, the true adjusted odds ratio implied by the normal distribution of the underlying continuous variable is a function of the baseline value and hence is unlikely to be able to be adequately represented by a single value of adjusted odds ratio from the logistic regression model. In contrast, the risk difference function derived from the logistic regression model provides a reasonable approximation to the true risk difference function implied by the normal distribution of the underlying continuous variable over the range of the baseline distribution. We show that different metrics of treatment effect have similar statistical power when evaluated at the baseline mean. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Leukemia prediction using sparse logistic regression.
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Tapio Manninen
Full Text Available We describe a supervised prediction method for diagnosis of acute myeloid leukemia (AML from patient samples based on flow cytometry measurements. We use a data driven approach with machine learning methods to train a computational model that takes in flow cytometry measurements from a single patient and gives a confidence score of the patient being AML-positive. Our solution is based on an [Formula: see text] regularized logistic regression model that aggregates AML test statistics calculated from individual test tubes with different cell populations and fluorescent markers. The model construction is entirely data driven and no prior biological knowledge is used. The described solution scored a 100% classification accuracy in the DREAM6/FlowCAP2 Molecular Classification of Acute Myeloid Leukaemia Challenge against a golden standard consisting of 20 AML-positive and 160 healthy patients. Here we perform a more extensive validation of the prediction model performance and further improve and simplify our original method showing that statistically equal results can be obtained by using simple average marker intensities as features in the logistic regression model. In addition to the logistic regression based model, we also present other classification models and compare their performance quantitatively. The key benefit in our prediction method compared to other solutions with similar performance is that our model only uses a small fraction of the flow cytometry measurements making our solution highly economical.
Image superresolution using support vector regression.
Ni, Karl S; Nguyen, Truong Q
2007-06-01
A thorough investigation of the application of support vector regression (SVR) to the superresolution problem is conducted through various frameworks. Prior to the study, the SVR problem is enhanced by finding the optimal kernel. This is done by formulating the kernel learning problem in SVR form as a convex optimization problem, specifically a semi-definite programming (SDP) problem. An additional constraint is added to reduce the SDP to a quadratically constrained quadratic programming (QCQP) problem. After this optimization, investigation of the relevancy of SVR to superresolution proceeds with the possibility of using a single and general support vector regression for all image content, and the results are impressive for small training sets. This idea is improved upon by observing structural properties in the discrete cosine transform (DCT) domain to aid in learning the regression. Further improvement involves a combination of classification and SVR-based techniques, extending works in resolution synthesis. This method, termed kernel resolution synthesis, uses specific regressors for isolated image content to describe the domain through a partitioned look of the vector space, thereby yielding good results.
Survival analysis II: Cox regression
Stel, Vianda S.; Dekker, Friedo W.; Tripepi, Giovanni; Zoccali, Carmine; Jager, Kitty J.
2011-01-01
In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the
Regression of lumbar disk herniation
Directory of Open Access Journals (Sweden)
G. Yu Evzikov
2015-01-01
Full Text Available Compression of the spinal nerve root, giving rise to pain and sensory and motor disorders in the area of its innervation is the most vivid manifestation of herniated intervertebral disk. Different treatment modalities, including neurosurgery, for evolving these conditions are discussed. There has been recent evidence that spontaneous regression of disk herniation can regress. The paper describes a female patient with large lateralized disc extrusion that has caused compression of the nerve root S1, leading to obvious myotonic and radicular syndrome. Magnetic resonance imaging has shown that the clinical manifestations of discogenic radiculopathy, as well myotonic syndrome and morphological changes completely regressed 8 months later. The likely mechanism is inflammation-induced resorption of a large herniated disk fragment, which agrees with the data available in the literature. A decision to perform neurosurgery for which the patient had indications was made during her first consultation. After regression of discogenic radiculopathy, there was only moderate pain caused by musculoskeletal diseases (facet syndrome, piriformis syndrome that were successfully eliminated by minimally invasive techniques.
Ridge Regression for Interactive Models.
Tate, Richard L.
1988-01-01
An exploratory study of the value of ridge regression for interactive models is reported. Assuming that the linear terms in a simple interactive model are centered to eliminate non-essential multicollinearity, a variety of common models, representing both ordinal and disordinal interactions, are shown to have "orientations" that are…
Regression Models for Repairable Systems
Czech Academy of Sciences Publication Activity Database
Novák, Petr
2015-01-01
Roč. 17, č. 4 (2015), s. 963-972 ISSN 1387-5841 Institutional support: RVO:67985556 Keywords : Reliability analysis * Repair models * Regression Subject RIV: BB - Applied Statistics , Operational Research Impact factor: 0.782, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/novak-0450902.pdf
Cactus: An Introduction to Regression
Hyde, Hartley
2008-01-01
When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…
Kane, Michael T.; Mroch, Andrew A.
2010-01-01
In evaluating the relationship between two measures across different groups (i.e., in evaluating "differential validity") it is necessary to examine differences in correlation coefficients and in regression lines. Ordinary least squares (OLS) regression is the standard method for fitting lines to data, but its criterion for optimal fit…
National Research Council Canada - National Science Library
Bielecki, John
2003-01-01
.... Previous research has demonstrated the use of a two-step logistic and multiple regression methodology to predicting cost growth produces desirable results versus traditional single-step regression...
Ortiz Rubiano, Andres Eduardo
The problem of a single human operator monitoring multiple UAVs in reconnaissance missions is addressed in this work. In such missions, the operator inspects and classifies targets as they appear on video feeds from the various UAVs. In parallel, the aircraft autonomously execute a flight plan and transmit real-time video of an unknown terrain. The main contribution of this work is the development of a system that autonomously schedules the display of video feeds such that the human operator is able to inspect each target in real time (i.e., no video data is recorded and queued for later inspection). The construction of this non-overlapping schedule is made possible by commanding changes to the flight plan of the UAVs. These changes are constructed such that the impact on the mission time is minimized. The development of this system is addressed in the context of both fixed and arbitrary target inspection times. Under the assumption that the inspection time is constant, a Linear Program (LP) formulation is used to optimally solve the display scheduling problem in the time domain. The LP solution is implemented in the space domain via velocity and trajectory modifications to the flight plan of the UAVs. An online algorithm is proposed to resolve scheduling conflicts between multiple video feeds as targets are discovered by the UAVs. Properties of this algorithm are studied to develop conflict resolution strategies that ensure correctness regardless of the target placement. The effect of such strategies on the mission time is evaluated via numerical simulations. In the context of arbitrary inspection time, the human operator indicates the end of target inspection in real time. A set of maneuvers is devised that enable the operator to inspect each target uninterruptedly and indefinitely. In addition, a cuing mechanism is proposed to increase the situational awareness of the operator and potentially reduce the inspection times. The benefits of operator cuing on mission
Energy Technology Data Exchange (ETDEWEB)
Balermpas, P.; Bauer, C.; Fraunholz, I.; Ottinger, A.; Fokas, E.; Roedel, C.; Weiss, C. [Goethe University Frankfurt, Department of Radiation Therapy and Oncology, Frankfurt am Main (Germany); Wagenblast, J.; Stoever, T. [Goethe University, Department of Otorhinolaryngology, Frankfurt am Main (Germany); Seitz, O. [Goethe University, Department of Oral Maxillofacial and Plastic Facial Surgery, Frankfurt am Main (Germany)
2014-03-15
Despite the lack of evidence to support its implementation in the clinical practice, induction chemotherapy (IC) before chemoradiotherapy (CRT) is often used in patients with locally advanced squamous cell carcinoma of the head and neck (SCCHN). We retrospectively examined the tolerability, feasibility, and clinical outcome of both concepts in a single center analysis. In all, 83 patients were treated between 2007 and 2010 with IC + CRT (n = 42) or CRT alone (n = 41). IC consisted of docetaxel, cisplatin and 5-fluorouracil (TPF), or cisplatin and 5-fluorouracil (PF). All patients were scheduled to receive 2 cycles of PF during concurrent CRT. Adverse events were assessed according to the common toxicity criteria of adverse events (CTCAE v. 3.0). Associations were tested using the χ{sup 2} test, and survival estimates were calculated according to Kaplan-Meier. The median follow-up was 30.35 months (range 2.66-61.25 months). At 2 years, the overall survival rate was significantly higher for primary CRT compared to IC + CRT group (74.8 % vs. 54 %, respectively; p = 0.041). Significantly more treatment-related overall grade 4 toxicities were documented in the IC + CRT group compared to the CRT group (42.9% vs. 9.8%; p = 0.001). Renal toxicity ≥ grade 2 occurred in 52.4 % vs. 7.3 % (p < 0.001), respectively. In all, 93 % of the patients with primary CRT compared to 71 % with IC + CRT received the planned full radiotherapy dose (p = 0.012). This is, to our knowledge, the largest retrospective study to compare IC + CRT with primary CRT. IC showed high acute toxicity, compromised the feasibility of concurrent CRT, and was associated with reduced overall survival rates compared to primary CRT. The lack of clinical benefit in conjunction with the increased toxicity does not support implementation of IC. (orig.) [German] Trotz fehlender Studienergebnisse, die den Einsatz einer Induktionschemotherapie (IC) vor einer simultanen Radiochemotherapie (RCT) in der klinischen
Quantile Regression With Measurement Error
Wei, Ying
2009-08-27
Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The method corrects the measurement error induced bias by constructing joint estimating equations that simultaneously hold for all the quantile levels. An iterative EM-type estimation algorithm to obtain the solutions to such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure. © 2009 American Statistical Association.
Active set support vector regression.
Musicant, David R; Feinberg, Alexander
2004-03-01
This paper presents active set support vector regression (ASVR), a new active set strategy to solve a straightforward reformulation of the standard support vector regression problem. This new algorithm is based on the successful ASVM algorithm for classification problems, and consists of solving a finite number of linear equations with a typically large dimensionality equal to the number of points to be approximated. However, by making use of the Sherman-Morrison-Woodbury formula, a much smaller matrix of the order of the original input space is inverted at each step. The algorithm requires no specialized quadratic or linear programming code, but merely a linear equation solver which is publicly available. ASVR is extremely fast, produces comparable generalization error to other popular algorithms, and is available on the web for download.
Producing The New Regressive Left
DEFF Research Database (Denmark)
Crone, Christine
This thesis is the first comprehensive research work conducted on the Beirut based TV station, an important representative of the post-2011 generation of Arab satellite news media. The launch of al-Mayadeen in June 2012 was closely linked to the political developments across the Arab world...... members, this thesis investigates a growing political trend and ideological discourse in the Arab world that I have called The New Regressive Left. On the premise that a media outlet can function as a forum for ideology production, the thesis argues that an analysis of this material can help to trace...... the contexture of The New Regressive Left. If the first part of the thesis lays out the theoretical approach and draws the contextual framework, through an exploration of the surrounding Arab media-and ideoscapes, the second part is an analytical investigation of the discourse that permeates the programmes aired...
AUTISTIC EPILEPTIFORM REGRESSION (A REVIEW
Directory of Open Access Journals (Sweden)
L. Yu. Glukhova
2012-01-01
Full Text Available The author represents the review of current scientific literature devoted to autistic epileptiform regression — the special form of autistic disorder, characterized by development of severe communicative disorders in children as a result of continuous prolonged epileptiform activity on EEG. This condition has been described by R.F. Tuchman and I. Rapin in 1997. The author describes the aspects of pathogenesis, clinical pictures and diagnostics of this disorder, including the peculiar anomalies on EEG (benign epileptiform patterns of childhood, with a high index of epileptiform activity, especially in the sleep. The especial attention is given to approaches to the treatment of autistic epileptiform regression. Efficacy of valproates, corticosteroid hormones and antiepileptic drugs of other groups is considered.
Polynomial Regressions and Nonsense Inference
Directory of Open Access Journals (Sweden)
Daniel Ventosa-Santaulària
2013-11-01
Full Text Available Polynomial specifications are widely used, not only in applied economics, but also in epidemiology, physics, political analysis and psychology, just to mention a few examples. In many cases, the data employed to estimate such specifications are time series that may exhibit stochastic nonstationary behavior. We extend Phillips’ results (Phillips, P. Understanding spurious regressions in econometrics. J. Econom. 1986, 33, 311–340. by proving that an inference drawn from polynomial specifications, under stochastic nonstationarity, is misleading unless the variables cointegrate. We use a generalized polynomial specification as a vehicle to study its asymptotic and finite-sample properties. Our results, therefore, lead to a call to be cautious whenever practitioners estimate polynomial regressions.
Spontaneous regression of colon cancer.
Kihara, Kyoichi; Fujita, Shin; Ohshiro, Taihei; Yamamoto, Seiichiro; Sekine, Shigeki
2015-01-01
A case of spontaneous regression of transverse colon cancer is reported. A 64-year-old man was diagnosed as having cancer of the transverse colon at a local hospital. Initial and second colonoscopy examinations revealed a typical cancer of the transverse colon, which was diagnosed as moderately differentiated adenocarcinoma. The patient underwent right hemicolectomy 6 weeks after the initial colonoscopy. The resected specimen showed only a scar at the tumor site, and no cancerous tissue was proven histologically. The patient is alive with no evidence of recurrence 1 year after surgery. Although an antitumor immune response is the most likely explanation, the exact nature of the phenomenon was unclear. We describe this rare case and review the literature pertaining to spontaneous regression of colorectal cancer. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Directional quantile regression in R
Czech Academy of Sciences Publication Activity Database
Boček, Pavel; Šiman, Miroslav
2017-01-01
Roč. 53, č. 3 (2017), s. 480-492 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : multivariate quantile * regression quantile * halfspace depth * depth contour Subject RIV: BD - Theory of Information OBOR OECD: Applied mathematics Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf
Optimization of DWDM Demultiplexer Using Regression Analysis
Directory of Open Access Journals (Sweden)
Venkatachalam Rajarajan Balaji
2016-01-01
Full Text Available We propose a novel twelve-channel Dense Wavelength Division Multiplexing (DWDM demultiplexer, using the two-dimensional photonic crystal (2D PC with square resonant cavity (SRC of ITU-T G.694.1 standard. The DWDM demultiplexer consists of an input waveguide, SRC, and output waveguide. The SRC in the proposed demultiplexer consists of square resonator and microcavity. The microcavity center rod radius (Rm is proportional to refractive index. The refractive index property of the rods filters the wavelengths of odd and even channels. The proposed microcavity can filter twelve ITU-T G.694.1 standard wavelengths with 0.2 nm/25 GHz channel spacing between the wavelengths. From the simulation, we optimize the rod radius and wavelength with linear regression analysis. From the regression analysis, we can achieve 95% of accuracy with an average quality factor of 7890, the uniform spectral line-width of 0.2 nm, the transmission efficiency of 90%, crosstalk of −42 dB, and footprint of about 784 μm2.
Gaussian Process Regression Model in Spatial Logistic Regression
Sofro, A.; Oktaviarina, A.
2018-01-01
Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.
Directory of Open Access Journals (Sweden)
Aurélio Mendes Aguiar
2003-02-01
Full Text Available The utilization of diallel crosses for identification of superior combinations is a common practice in maize (Zea mays L. breeding programs. This methodology allows the estimation of the combining ability of genotypes being evaluated. In this work, five inbred lines were evaluated as to their general (GCA and specific (SCA combining abilities, by using a complete diallel scheme. The single-crosses produced between these inbred lines were evaluated in seven environments, along with two checks, by using a randomized complete block design. Traits analized were: grain yield, plant height, ear height, ear placement, and prolificacy. A diallel analysis was carried out, following an adaptation of Griffing's method IV, in addition to hybrid stability and adaptability analyses. Significant differences were detected for entries and environments for all traits. The interaction genotype vs. environment was significant for all traits. GCA's were significant for all traits, while SCA's were non-significant only for ear placement. For grain yield, both additive (GCA and non-additive (SCA effects were important, while for the remaining traits additive effects were more important. The high yielding single-cross was obtained from the cross of lines L-08-05F and L-38-05D. Those inbred lines showed higher GCA's and their cross also had high SCA; also, it is responsive to environment improvements and reasonably stable. The second in rank high yielding single-cross, L-46-10D x L-08-05F, showed wide adaptability and stability.No melhoramento de milho (Zea mays L., a utilização de cruzamentos dialélicos visando identificação de combinações superiores é uma prática comum. Esta metodologia visa estimar a capacidade de combinação dos materiais avaliados. Neste trabalho, cinco linhagens endogâmicas foram avaliadas quanto às capacidades gerais (CGC e específica (CEC de combinação, utilizando o esquema de dialelo completo. Os híbridos simples produzidos
Language regression in children with Autism Spectrum Disorders.
Kumar, Suman; Karmakar, Probir; Mohanan, Akhil
2014-02-01
Regression in autism applies to the phenomenon of apparently normal early development followed by the loss of previously acquired skills and manifestation of symptoms of autism. Estimates of the frequency of regression in autism range from 10% to 50%. Although there are tools available to evaluate and diagnose Autism Spectrum Disorders, however, there is no published tool available in Indian context to identify the children with ASD at an early age. The study was aimed to describe the differences in language regression between children with ASD and typically developing children and also to determine the age of regression. Regression screening tool, a questionnaire was developed based on Regression Supplement Form (Goldberg et al., 2003). The skills were validated by five Clinical Psychologists. It comprised of 16 skills which included domains like, 'spoken language and non verbal communication', 'social interest and responsiveness' and 'play and imagination'. This retrospective study was conducted on a single group. The participants consisted of parents of 30 children with ASD (22 males and 8 females). The findings revealed a significant regression in children with ASD. The mean regression age is 20.19 months (SD-5.2). The regression profile of the children with ASD revealed regression of language skills occurred at 19.16 months followed by non language skills at 20.5 months. Based on the findings it can be stated that inclusion of regression screening tool will offer clinicians a convenient tool to examine the phenomena of regression in children with ASD and identify them as early as 21 months of age for early intervention. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
On Weighted Support Vector Regression
DEFF Research Database (Denmark)
Han, Xixuan; Clemmensen, Line Katrine Harder
2014-01-01
We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...... the differences and similarities of the two types of weights by demonstrating the connection between the Least Absolute Shrinkage and Selection Operator (LASSO) and the SVR. We show that an SVR problem can be transformed to a LASSO problem plus a linear constraint and a box constraint. We demonstrate...
Conjoined legs: Sirenomelia or caudal regression syndrome?
Directory of Open Access Journals (Sweden)
Sakti Prasad Das
2013-01-01
Full Text Available Presence of single umbilical persistent vitelline artery distinguishes sirenomelia from caudal regression syndrome. We report a case of a12-year-old boy who had bilateral umbilical arteries presented with fusion of both legs in the lower one third of leg. Both feet were rudimentary. The right foot had a valgus rocker-bottom deformity. All toes were present but rudimentary. The left foot showed absence of all toes. Physical examination showed left tibia vara. The chest evaluation in sitting revealed pigeon chest and elevated right shoulder. Posterior examination of the trunk showed thoracic scoliosis with convexity to right. The patient was operated and at 1 year followup the boy had two separate legs with a good aesthetic and functional results.
DEFF Research Database (Denmark)
Kiib, Hans
2015-01-01
. The High Line project has been carried out as part of an open conversion strategy. The result is a remarkable urban architectural project, which works as a catalyst for the urban development of Western Manhattan. The greater project includes the restoration and reuse of many old industrial buildings......At just over 10 meters above street level, the High Line extends three kilometers through three districts of Southwestern Manhattan in New York. It consists of simple steel construction, and previously served as an elevated rail line connection between Penn Station on 34th Street and the many...... in close proximity to the park bridge and new projects being added to fit the context. The outcome is a conglomeration of non-contemporary urban activities along the High Line, where mechanical workshops, small wholesale stores. etc. mix with new exclusive residential buildings, eminent cafés...
Waser Jürgen; Fuchs Raphael; Ribicic Hrvoje; Schindler Benjamin; Blöschl Günther; Gröller Eduard
2010-01-01
In this paper we present World Lines as a novel interactive visualization that provides complete control over multiple heterogeneous simulation runs. In many application areas decisions can only be made by exploring alternative scenarios. The goal of the suggested approach is to support users in this decision making process. In this setting the data domain is extended to a set of alternative worlds where only one outcome will actually happen. World Lines integrate simulation visualization and...
Ordinary least squares regression is indicated for studies of allometry.
Kilmer, J T; Rodríguez, R L
2017-01-01
When it comes to fitting simple allometric slopes through measurement data, evolutionary biologists have been torn between regression methods. On the one hand, there is the ordinary least squares (OLS) regression, which is commonly used across many disciplines of biology to fit lines through data, but which has a reputation for underestimating slopes when measurement error is present. On the other hand, there is the reduced major axis (RMA) regression, which is often recommended as a substitute for OLS regression in studies of allometry, but which has several weaknesses of its own. Here, we review statistical theory as it applies to evolutionary biology and studies of allometry. We point out that the concerns that arise from measurement error for OLS regression are small and straightforward to deal with, whereas RMA has several key properties that make it unfit for use in the field of allometry. The recommended approach for researchers interested in allometry is to use OLS regression on measurements taken with low (but realistically achievable) measurement error. If measurement error is unavoidable and relatively large, it is preferable to correct for slope attenuation rather than to turn to RMA regression, or to take the expected amount of attenuation into account when interpreting the data. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.
Energy Technology Data Exchange (ETDEWEB)
Chuang, Hsiao-Chi [School of Respiratory Therapy, College of Medicine, Taipei Medical University, Taipei, Taiwan (China); Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, Taipei, Taiwan (China); Cheng, Yi-Ling; Lei, Yu-Chen [Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, Taipei, Taiwan (China); Chang, Hui-Hsien [Institute of Environmental Health, College of Public Health, National Taiwan University, Taipei, Taiwan (China); Cheng, Tsun-Jen, E-mail: tcheng@ntu.edu.tw [Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, Taipei, Taiwan (China); Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan (China)
2013-02-01
Pulmonary epithelial lining fluid (ELF) is the first substance to make contact with inhaled particulate matter (PM) and interacts chemically with PM components. The objective of this study was to determine the role of ELF in oxidative stress, DNA damage and the production of proinflammatory cytokines following physicochemical exposure to PM. Ultrafine carbon black (ufCB, 15 nm; a model carbonaceous core), ferrous sulphate (FeSO{sub 4}; a model transition metal) and a diesel exhaust particle (DEP) extract (a model organic compound) were used to examine the acellular oxidative potential of synthetic ELF and non-ELF systems. We compared the effects of exposure to ufCB, FeSO{sub 4} and DEP extract on human alveolar epithelial Type II (A549) cells to determine the levels of oxidative stress, DNA single-strand breaks and interleukin-8 (IL-8) production in ELF and non-ELF systems. The effects of ufCB and FeSO{sub 4} on the acellular oxidative potential, cellular oxidative stress and DNA single-strand breakage were mitigated significantly by the addition of ELF, whereas there was no decrease following treatment with the DEP extract. There was no significant effect on IL-8 production following exposure to samples that were suspended in ELF/non-ELF systems. The results of the present study indicate that ELF plays an important role in the initial defence against PM in the pulmonary environment. Experimental components, such as ufCB and FeSO{sub 4}, induced the production of oxidative stress and led to DNA single-strand breaks, which were moderately prevented by the addition of ELF. These findings suggest that ELF plays a protective role against PM-driven oxidative stress and DNA damage. -- Highlights: ► To determine the role of ELF in ROS, DNA damage and IL-8 after exposure to PM. ► ufCB, FeSO{sub 4} and DEP extract were used to examine the protective effects of ELF. ► PM-driven oxidative stress and DNA single-strand breakage were mitigated by ELF. ► The findings
Regression calibration with more surrogates than mismeasured variables
Kipnis, Victor
2012-06-29
In a recent paper (Weller EA, Milton DK, Eisen EA, Spiegelman D. Regression calibration for logistic regression with multiple surrogates for one exposure. Journal of Statistical Planning and Inference 2007; 137: 449-461), the authors discussed fitting logistic regression models when a scalar main explanatory variable is measured with error by several surrogates, that is, a situation with more surrogates than variables measured with error. They compared two methods of adjusting for measurement error using a regression calibration approximate model as if it were exact. One is the standard regression calibration approach consisting of substituting an estimated conditional expectation of the true covariate given observed data in the logistic regression. The other is a novel two-stage approach when the logistic regression is fitted to multiple surrogates, and then a linear combination of estimated slopes is formed as the estimate of interest. Applying estimated asymptotic variances for both methods in a single data set with some sensitivity analysis, the authors asserted superiority of their two-stage approach. We investigate this claim in some detail. A troubling aspect of the proposed two-stage method is that, unlike standard regression calibration and a natural form of maximum likelihood, the resulting estimates are not invariant to reparameterization of nuisance parameters in the model. We show, however, that, under the regression calibration approximation, the two-stage method is asymptotically equivalent to a maximum likelihood formulation, and is therefore in theory superior to standard regression calibration. However, our extensive finite-sample simulations in the practically important parameter space where the regression calibration model provides a good approximation failed to uncover such superiority of the two-stage method. We also discuss extensions to different data structures.
Isotonic Regression under Lipschitz Constraint
Wilbur, W.J.
2018-01-01
The pool adjacent violators (PAV) algorithm is an efficient technique for the class of isotonic regression problems with complete ordering. The algorithm yields a stepwise isotonic estimate which approximates the function and assigns maximum likelihood to the data. However, if one has reasons to believe that the data were generated by a continuous function, a smoother estimate may provide a better approximation to that function. In this paper, we consider the formulation which assumes that the data were generated by a continuous monotonic function obeying the Lipschitz condition. We propose a new algorithm, the Lipschitz pool adjacent violators (LPAV) algorithm, which approximates that function; we prove the convergence of the algorithm and examine its complexity. PMID:29456266
Prediction, Regression and Critical Realism
DEFF Research Database (Denmark)
Næss, Petter
2004-01-01
This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...
ESR powder line shape calculations
Energy Technology Data Exchange (ETDEWEB)
Vitko, J. Jr.; Huddleston, R.E.
1976-05-01
A program has been developed for computing the ESR spectrum of a collection of randomly oriented spins subject only to an electronic Zeeman interaction and having a Lorentzian single crystal line shape. Other single crystal line shapes, including numerical solutions of the Bloch equations, can be accommodated with minor modifications. The program differs in several features from those existing elsewhere, thus enabling one to study saturation effects, over-modulation effects, both absorptive and dispersive signals, and second and higher order derivative signals.
Lumbar herniated disc: spontaneous regression.
Altun, Idiris; Yüksel, Kasım Zafer
2017-01-01
Low back pain is a frequent condition that results in substantial disability and causes admission of patients to neurosurgery clinics. To evaluate and present the therapeutic outcomes in lumbar disc hernia (LDH) patients treated by means of a conservative approach, consisting of bed rest and medical therapy. This retrospective cohort was carried out in the neurosurgery departments of hospitals in Kahramanmaraş city and 23 patients diagnosed with LDH at the levels of L3-L4, L4-L5 or L5-S1 were enrolled. The average age was 38.4 ± 8.0 and the chief complaint was low back pain and sciatica radiating to one or both lower extremities. Conservative treatment was administered. Neurological examination findings, durations of treatment and intervals until symptomatic recovery were recorded. Laségue tests and neurosensory examination revealed that mild neurological deficits existed in 16 of our patients. Previously, 5 patients had received physiotherapy and 7 patients had been on medical treatment. The number of patients with LDH at the level of L3-L4, L4-L5, and L5-S1 were 1, 13, and 9, respectively. All patients reported that they had benefit from medical treatment and bed rest, and radiologic improvement was observed simultaneously on MRI scans. The average duration until symptomatic recovery and/or regression of LDH symptoms was 13.6 ± 5.4 months (range: 5-22). It should be kept in mind that lumbar disc hernias could regress with medical treatment and rest without surgery, and there should be an awareness that these patients could recover radiologically. This condition must be taken into account during decision making for surgical intervention in LDH patients devoid of indications for emergent surgery.
Gao, Wenhua; Chen, Yunsheng; Chen, Gaopan; Xi, Jing; Chen, Yaowen; Yang, Jianying; Xu, Ning
2012-09-01
A rapid and efficient dual preconcentration method of on-line single drop liquid-liquid-liquid microextraction (SD-LLLME) coupled to sweeping micellar electrokinetic chromatography (MEKC) was developed for trace analysis of three antihistamines (mizolastine, chlorpheniramine and pheniramine) in human urine. Three analytes were firstly extracted from donor phase (4 mL urine sample) adjusted to alkaline condition (0.5 M NaOH). The unionized analytes were subsequently extracted into a drop of n-octanol layered over the urine sample, and then into a microdrop of acceptor phase (100 mM H(3)PO(4)) suspended from a capillary inlet. The enriched acceptor phase was on-line injected into capillary with a height difference and then analyzed directly by sweeping MEKC. Good linear relationships were obtained for all analytes in a range of 6.25 × 10(-6) to 2.5 × 10(-4)g/L with correlation coefficients (r) higher than 0.987. The proposed method achieved limits of detections (LOD) varied from 1.2 × 10(-7) to 9.5 × 10(-7)g/L based on a signal-to-noise of 3 (S/N=3) with 751- to 1372-fold increases in detection sensitivity for analytes, and it was successfully applied to the pharmacokinetic study of three antihistamines in human urine after an oral administration. The results demonstrated that this method was a promising combination for the rapid trace analysis of antihistamines in human urine with the advantages of operation simplicity, high enrichment factor and little solvent consumption. Copyright © 2012 Elsevier B.V. All rights reserved.
Inferring gene regression networks with model trees
Directory of Open Access Journals (Sweden)
Aguilar-Ruiz Jesus S
2010-10-01
Full Text Available Abstract Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear
Generalized regression for fuzzy rule bases using the Hough transform
Barone, Joseph M.; Fileu, Dimitar P.
1993-12-01
The extended Hough transform permits weight functions of arbitrary type and complexity to help guide the choice of a `regression' line in polar coordinate space. This paper suggests that this transform may be helpful in locating the best linear approximation to gaps and areas of conflict in fuzzy rule bases. Using the sliding mode approximation of a fuzzy controller as an example, this paper shows how global properties of the rule base can be used to help guide the search for good approximations. The notion of `representativeness' of centroids and its effect on regression via the Hough transform is also considered. Finally, a different approach based on OWA operators is discussed briefly.
Use of Multiple Regression in Counseling Psychology Research: A Flexible Data-Analytic Strategy.
Wampold, Bruce E.; Freund, Richard D.
1987-01-01
Explains multiple regression, demonstrates its flexibility for analyzing data from various designs, and discusses interpretation of results from multiple regression analysis. Presents regression equations for single independent variable and for two or more independent variables, followed by a discussion of coefficients related to these. Compares…
Bayesian logistic regression in detection of gene–steroid interaction ...
Indian Academy of Sciences (India)
cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene– steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer. (P < 0.05); especially, SNP rs6532496 revealed the strongest association with cancer ...
Feature Selection for Ridge Regression with Provable Guarantees.
Paul, Saurabh; Drineas, Petros
2016-04-01
We introduce single-set spectral sparsification as a deterministic sampling-based feature selection technique for regularized least-squares classification, which is the classification analog to ridge regression. The method is unsupervised and gives worst-case guarantees of the generalization power of the classification function after feature selection with respect to the classification function obtained using all features. We also introduce leverage-score sampling as an unsupervised randomized feature selection method for ridge regression. We provide risk bounds for both single-set spectral sparsification and leverage-score sampling on ridge regression in the fixed design setting and show that the risk in the sampled space is comparable to the risk in the full-feature space. We perform experiments on synthetic and real-world data sets; a subset of TechTC-300 data sets, to support our theory. Experimental results indicate that the proposed methods perform better than the existing feature selection methods.
Insulin resistance: regression and clustering.
Yoon, Sangho; Assimes, Themistocles L; Quertermous, Thomas; Hsiao, Chin-Fu; Chuang, Lee-Ming; Hwu, Chii-Min; Rajaratnam, Bala; Olshen, Richard A
2014-01-01
In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be.
Insulin resistance: regression and clustering.
Directory of Open Access Journals (Sweden)
Sangho Yoon
Full Text Available In this paper we try to define insulin resistance (IR precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ, a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT. We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be.
Regularized Label Relaxation Linear Regression.
Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung; Fang, Bingwu
2018-04-01
Linear regression (LR) and some of its variants have been widely used for classification problems. Most of these methods assume that during the learning phase, the training samples can be exactly transformed into a strict binary label matrix, which has too little freedom to fit the labels adequately. To address this problem, in this paper, we propose a novel regularized label relaxation LR method, which has the following notable characteristics. First, the proposed method relaxes the strict binary label matrix into a slack variable matrix by introducing a nonnegative label relaxation matrix into LR, which provides more freedom to fit the labels and simultaneously enlarges the margins between different classes as much as possible. Second, the proposed method constructs the class compactness graph based on manifold learning and uses it as the regularization item to avoid the problem of overfitting. The class compactness graph is used to ensure that the samples sharing the same labels can be kept close after they are transformed. Two different algorithms, which are, respectively, based on -norm and -norm loss functions are devised. These two algorithms have compact closed-form solutions in each iteration so that they are easily implemented. Extensive experiments show that these two algorithms outperform the state-of-the-art algorithms in terms of the classification accuracy and running time.
Gómez-España, Auxiliadora; Massutí, Bartomeu; Sastre, Javier; Abad, Albert; Valladares, Manuel; Rivera, Fernando; Safont, Maria J.; Martínez de Prado, Purificación; Gallén, Manuel; González, Encarnación; Marcuello, Eugenio; Benavides, Manuel; Fernández-Martos, Carlos; Losa, Ferrán; Escudero, Pilar; Arrivi, Antonio; Cervantes, Andrés; Dueñas, Rosario; López-Ladrón, Amelia; Lacasta, Adelaida; Llanos, Marta; Tabernero, Jose M.; Antón, Antonio; Aranda, Enrique
2012-01-01
Purpose. The aim of this phase III trial was to compare the efficacy and safety of bevacizumab alone with those of bevacizumab and capecitabine plus oxaliplatin (XELOX) as maintenance treatment following induction chemotherapy with XELOX plus bevacizumab in the first-line treatment of patients with metastatic colorectal cancer (mCRC). Patients and Methods. Patients were randomly assigned to receive six cycles of bevacizumab, capecitabine, and oxaliplatin every 3 weeks followed by XELOX plus bevacizumab or bevacizumab alone until progression. The primary endpoint was the progression-free survival (PFS) interval; secondary endpoints were the overall survival (OS) time, objective response rate (RR), time to response, duration of response, and safety. Results. The intent-to-treat population comprised 480 patients (XELOX plus bevacizumab, n = 239; bevacizumab, n = 241); there were no significant differences in baseline characteristics. The median follow-up was 29.0 months (range, 0–53.2 months). There were no statistically significant differences in the median PFS or OS times or in the RR between the two arms. The most common grade 3 or 4 toxicities in the XELOX plus bevacizumab versus bevacizumab arms were diarrhea, hand–foot syndrome, and neuropathy. Conclusion. Although the noninferiority of bevacizumab versus XELOX plus bevacizumab cannot be confirmed, we can reliably exclude a median PFS detriment >3 weeks. This study suggests that maintenance therapy with single-agent bevacizumab may be an appropriate option following induction XELOX plus bevacizumab in mCRC patients. PMID:22234633
Directory of Open Access Journals (Sweden)
Zhang QQ
2015-04-01
Full Text Available Qianqian Zhang,1 Zhehai Wang,2 Jun Guo,2 Liyan Liu,2 Xiao Han,2 Minmin Li,1 Shu Fang,1 Xiang Bi,1 Ning Tang,1 Yang Liu1 1School of Medicine and Life Sciences, Shandong Academy of Medical Sciences, University of Jinan, 2Department of Oncology, Shandong Cancer Hospital, Jinan, People’s Republic of China Purpose: The aim of this study was to compare single-agent chemotherapy with targeted therapy in initial treatment and to explore a better choice of treatment for patients aged 80 years and older with advanced non-small-cell lung cancer (NSCLC.Patients and methods: A retrospective chart review was conducted for 136 patients aged 80 years and older who were cytopathologically diagnosed and staged as advanced (stage IIIB or IV NSCLC. The patient population was divided into two treatment groups: 78 patients were allocated to the chemotherapy group (group A, pemetrexed or gemcitabine or docetaxel as a single agent, and 60 patients were allocated to another group and received epidermal growth factor-receptor tyrosine-kinase inhibitors (group B, erlotinib or gefitinib as a single agent. The primary end points were overall survival (OS and progression-free survival (PFS, and the secondary end points were response rate, disease-control rate, safety, and quality of life.Results: In group A and group B, respectively, the median PFS was 2 versus 4 months (P=0.013, and the median OS was 8 versus 16 months (P=0.025. The 1- and 2-year survival rates of the two groups were 23.7% (group A, 18 of 76 versus 76.7% (group B, 46 of 60 and 13.2% (group A, ten of 76 versus 10% (group B, six of 60, respectively. The response rate and disease-control rate were 28.9% versus 36.7% (P=0.39 and 57.9% versus 76.7% (P=0.022 in group A and group B, respectively.Conclusion: Elders aged 80 years and over with advanced NSCLC in group B had longer PFS and OS compared with group A. It was well tolerated in group B because of the mild adverse effects. Targeted therapy can be
Use of probabilistic weights to enhance linear regression myoelectric control.
Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J
2015-12-01
Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts' law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p linear regression control. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.
DRREP: deep ridge regressed epitope predictor.
Sher, Gene; Zhi, Degui; Zhang, Shaojie
2017-10-03
The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been numerous advancements and improvements in epitope prediction, on average the best benchmark prediction accuracies are still only around 60%. New machine learning algorithms have arisen within the domain of deep learning, text mining, and convolutional networks. This paper presents a novel analytically trained and string kernel using deep neural network, which is tailored for continuous epitope prediction, called: Deep Ridge Regressed Epitope Predictor (DRREP). DRREP was tested on long protein sequences from the following datasets: SARS, Pellequer, HIV, AntiJen, and SEQ194. DRREP was compared to numerous state of the art epitope predictors, including the most recently published predictors called LBtope and DMNLBE. Using area under ROC curve (AUC), DRREP achieved a performance improvement over the best performing predictors on SARS (13.7%), HIV (8.9%), Pellequer (1.5%), and SEQ194 (3.1%), with its performance being matched only on the AntiJen dataset, by the LBtope predictor, where both DRREP and LBtope achieved an AUC of 0.702. DRREP is an analytically trained deep neural network, thus capable of learning in a single step through regression. By combining the features of deep learning, string kernels, and convolutional networks, the system is able to perform residue-by-residue prediction of continues epitopes with higher accuracy than the current state of the art predictors.
Principal component regression analysis with SPSS.
Liu, R X; Kuang, J; Gong, Q; Hou, X L
2003-06-01
The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.
Salar, Antonio; Domingo-Domenech, Eva; Panizo, Carlos; Nicolás, Concepción; Bargay, Joan; Muntañola, Ana; Canales, Miguel; Bello, José Luis; Sancho, Juan Manuel; Tomás, José Francisco; Rodríguez, María José; Peñalver, Francisco Javier; Grande, Carlos; Sánchez-Blanco, José Javier; Palomera, Luis; Arranz, Reyes; Conde, Eulogio; García, Mar; García, Juan Fernando; Caballero, Dolores; Montalbán, Carlos
2014-12-01
No standard first-line systemic treatment for mucosa-associated lymphoid tissue (MALT) lymphoma is available. In a phase 2 study we aimed to assess the safety and activity of a response-adapted combination of bendamustine plus rituximab as upfront treatment for this type of lymphoma. In a multicentre, single-arm, non-randomised, phase 2 trial, we enrolled patients with MALT lymphoma at any site and stage and treated them with bendamustine (90 mg/m(2) on days 1 and 2) plus rituximab (375 mg/m(2) on day 1), every 4 weeks. Inclusion criteria were measurable or evaluable disease, age 18-85 years, and unequivocal active lymphoma; we also enrolled patients with MALT lymphoma arising in the stomach after failure of Helicobacter pylori eradication and primary cutaneous cases after failure of local therapies. Exclusion criteria included evidence of histological transformation, CNS involvement, and active hepatitis B or C virus or HIV infection. After three cycles, patients achieving complete response received one additional cycle (total four cycles) and those achieving partial response received three additional cycles (total six cycles). The primary endpoint was 2-year event-free survival. Analysis was by modified intention to treat. This trial is registered with ClinicalTrials.gov, number NCT01015248. 60 patients from 19 centres in Spain were enrolled between May 27, 2009, and May 23, 2011, and received treatment; 57 patients were evaluable for the primary endpoint. Only 14 (25%) patients needed more than four cycles of treatment. After a median follow-up of 43 months (IQR 37-51), median event-free survival was not reached. Event-free survival at 2 years was 93% (95% CI 84-97) and at 4 years was 88% (95% CI 74-95). The most frequently observed grade 3-4 adverse events were haematological: lymphopenia in 20 (33%) patients, neutropenia in 12 (20%) patients, and leucopenia in three (5%) patients. Grade 3-4 febrile neutropenia or infections were reported in three (5%) and four
Mathematical model of subscriber extension line
Petříková, Iva; Diviš, Zdeněk; Tesař, Zdeněk
2012-01-01
The paper focuses on measurement properties of metallic subscriber extension lines to build regression mathematical model for a symmetric pair cable. The regression model is compared with an analytical model based on a theoretical description of transfer parameters for this type of line. The output of the paper should demonstrate the impact of electromagnetic interference on the symmetric pair. The paper also describes the method to identify the interference sources and ...
Gaussian process regression analysis for functional data
Shi, Jian Qing
2011-01-01
Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime
Unbalanced Regressions and the Predictive Equation
DEFF Research Database (Denmark)
Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo
Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...
Semiparametric regression during 2003–2007
Ruppert, David
2009-01-01
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.
New ridge parameters for ridge regression
Dorugade, A.V.
2014-01-01
Hoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinary least squares (OLS) estimator in the presence of multicollinearity. In ridge regression, ridge parameter plays an important role in parameter estimation. In this article, a new method for estimating ridge parameters in both situations of ordinary ridge regression (ORR) and generalized ridge regression (GRR) is proposed. The simulation study evaluates the performance of the proposed estimator ...
Inoue, Kenichi; Kuroi, Katsumasa; Shimizu, Satoru; Rai, Yoshiaki; Aogi, Kenjiro; Masuda, Norikazu; Nakayama, Takahiro; Iwata, Hiroji; Nishimura, Yuichiro; Armour, Alison; Sasaki, Yasutsuna
2015-12-01
Lapatinib is the human epidermal growth factor receptor 2 (HER2) targeting agent approved globally for HER2-positive metastatic breast cancer (MBC). The efficacy, safety and pharmacokinetics (PK) of lapatinib combined with paclitaxel (L+P) were investigated in this study, to establish clear evidence regarding the combination in Japanese patients. In this two-part, single-arm, open-label study, the tolerability of L+P as first-line treatment in Japanese patients with HER2-positive MBC was evaluated in six patients in the first part, and the safety, efficacy and PK were evaluated in a further six patients (making a total of twelve patients) in the second part. Eligible women were enrolled and received lapatinib 1500 mg once daily and paclitaxel 80 mg/m(2) weekly for at least 6 cycles. The only dose-limiting toxicity reported was Grade 3 diarrhea in one patient. The systemic exposure to maximum plasma concentration and area under the plasma concentration curve (AUC) for lapatinib, as well as the AUC of paclitaxel, were increased when combined. The most common adverse events (AEs) related to the study treatment were alopecia, diarrhea and decreased hemoglobin. The majority of drug-related AEs were Grade 1 or 2. The median overall survival was 35.6 months (95 % confidence interval 23.9, not reached). The response rate and clinical benefit rate were both 83 % (95 % confidence interval 51.6, 97.9). The L+P treatment was well tolerated in Japanese patients with HER2-positive MBC. Although the PK profiles of lapatinib and paclitaxel influenced each other, the magnitudes were not greatly different from those in non-Japanese patients.
An Interactive Approach to Ridge Regression
Marquette, J. F.; Dufala, M. M.
1978-01-01
Ridge regression is an approach to ameliorating the problem of large standard errors of regression estimates when predictor variables are highly intercorrelated. An interactive computer program is presented which allows for investigation of the effects of using various ridge regression adjustment values. (JKS)
An ovarian regression syndrome in the platyfish, Xiphophorus maculatus.
Burns, J R; Kallman, K D
1985-02-01
The highly inbred Coatzacoalcos (Cp) strain of the platyfish, Xiphophorus maculatus, was noted for a high percentage of infertile females (XX). The ovaries of approximately one-quarter of all females regress. The time of gonadal atrophy varied from before sexual maturation up to 11 months of age. The gonadotropic zone of the pituitary was hypertrophied in regressed females. Transplants of immature testes and ovarian tissue into the caudal musculature of regressed females and the subsequent maturation of the grafts demonstrated that the ovarian degeneration was not due to pituitary or hypothalamic malfunction or an autoimmune disease. The cause of the gonadal degeneration was apparently localized to the ovary itself. This phenomenon was never observed in males (XY). Regressed ovaries fell into two categories, designated types I and II, with all being characterized by the presence of ductlike structures which resembled male efferent ducts, lined by Sertoli cells. Type I ovaries bore a marked similarity to certain mammalian dysgenetic gonads, while type II ovaries contained many proliferating germ cells and could be compared to the human neoplasm termed gonadoblastoma. It is suggested that the physiological lesion responsible for the ovarian regression syndrome involves the processes that control the determination and differentiation of the germ cells similar to those found in human 46,XY gonadal dysgenesis.
Regression with Sparse Approximations of Data
DEFF Research Database (Denmark)
Noorzad, Pardis; Sturm, Bob L.
2012-01-01
We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...
Directory of Open Access Journals (Sweden)
Jingshan Li
2000-01-01
Full Text Available In this work, serial production lines with finished goods buffers operating in the pull regime are considered. The machines are assumed to obey Bernoulli reliability model. The problem of satisfying customers demand is addressed. The level of demand satisfaction is quantified by the due-time performance (DTP, which is defined as the probability to ship to the customer a required number of parts during a fixed time interval. Within this scenario, the definitions of DTP bottlenecks are introduced and a method for their identification is developed.
Assumptions of Multiple Regression: Correcting Two Misconceptions
Directory of Open Access Journals (Sweden)
Matt N. Williams
2013-09-01
Full Text Available In 2002, an article entitled - Four assumptions of multiple regression that researchers should always test- by.Osborne and Waters was published in PARE. This article has gone on to be viewed more than 275,000 times.(as of August 2013, and it is one of the first results displayed in a Google search for - regression.assumptions- . While Osborne and Waters' efforts in raising awareness of the need to check assumptions.when using regression are laudable, we note that the original article contained at least two fairly important.misconceptions about the assumptions of multiple regression: Firstly, that multiple regression requires the.assumption of normally distributed variables; and secondly, that measurement errors necessarily cause.underestimation of simple regression coefficients. In this article, we clarify that multiple regression models.estimated using ordinary least squares require the assumption of normally distributed errors in order for.trustworthy inferences, at least in small samples, but not the assumption of normally distributed response or.predictor variables. Secondly, we point out that regression coefficients in simple regression models will be.biased (toward zero estimates of the relationships between variables of interest when measurement error is.uncorrelated across those variables, but that when correlated measurement error is present, regression.coefficients may be either upwardly or downwardly biased. We conclude with a brief corrected summary of.the assumptions of multiple regression when using ordinary least squares.
International Nuclear Information System (INIS)
1998-08-01
This book deals with line facilities. The contents of this book are outline line of wire telecommunication ; development of line, classification of section of line and theory of transmission of line, cable line ; structure of line, line of cable in town, line out of town, domestic cable and other lines, Optical communication ; line of optical cable, transmission method, measurement of optical communication and cable of the sea bottom, Equipment of telecommunication line ; telecommunication line facilities and telecommunication of public works, construction of cable line and maintenance and Regulation of line equipment ; regulation on technique, construction and maintenance.
Directory of Open Access Journals (Sweden)
Katharina Galmbacher
Full Text Available A tumor promoting role of macrophages has been described for a transgenic murine breast cancer model. In this model tumor-associated macrophages (TAMs represent a major component of the leukocytic infiltrate and are associated with tumor progression. Shigella flexneri is a bacterial pathogen known to specificly induce apotosis in macrophages. To evaluate whether Shigella-induced removal of macrophages may be sufficient for achieving tumor regression we have developed an attenuated strain of S. flexneri (M90TDeltaaroA and infected tumor bearing mice. Two mouse models were employed, xenotransplantation of a murine breast cancer cell line and spontanous breast cancer development in MMTV-HER2 transgenic mice. Quantitative analysis of bacterial tumor targeting demonstrated that attenuated, invasive Shigella flexneri primarily infected TAMs after systemic administration. A single i.v. injection of invasive M90TDeltaaroA resulted in caspase-1 dependent apoptosis of TAMs followed by a 74% reduction in tumors of transgenic MMTV-HER-2 mice 7 days post infection. TAM depletion was sustained and associated with complete tumor regression.These data support TAMs as useful targets for antitumor therapy and highlight attenuated bacterial pathogens as potential tools.
Learning from data with localized regression and differential evolution
Buckner, Mark A.
2003-07-01
Learning from data is fast becoming the rule rather than the exception for many science and engineering research problems, particularly those encountered in nuclear engineering. Problems associated with learning from data fall under the more general category of inverse problems . A data-drive inverse problem involves constructing a predictive model of a target system from a collection of input/output observations. One of the difficulties associated with constructing a model that approximates such unknown causes based solely on observations of their effects is that collinearities in the input data result in the problem being ill-posed. Ill-posed problems cause models obtained by conventional techniques, such as linear regression, neural networks and kernel techniques, to become unstable, producing unreliable results. Methods of regularization using ordinary ridge regression (ORR) and kernel regression (KR) have been proposed as viable solutions to ill-posed problems. Successful application of ORR and KR require the selection of optimal parameter values---ridge parameters for ORR and bandwidth parameters for KR. The common practice for both methods is to select a single parameter based on minimizing an objective function which is an estimate of empirical risk. The single parameter value is then applied to all predictor variables indiscriminately, in a sort of one-size-fits-all fashion. Versions of ORR and KR have been proposed that make use of individual localized ridge and a matrix of localized bandwidth parameters that are optimally selected based on the relevance of their associated predictor variables to reducing empirical risk. While the practical and theoretical value of both localized regression techniques is recognized they have obtained limited use because of the difficulties associated with selecting multiple optimal ridge parameters for localized ridge regression (LRR)---defined as the localized ridge regression problem---and multiple optimal bandwidth
Directory of Open Access Journals (Sweden)
James G. Worner
2017-05-01
Full Text Available James Worner is an Australian-based writer and scholar currently pursuing a PhD at the University of Technology Sydney. His research seeks to expose masculinities lost in the shadow of Australia’s Anzac hegemony while exploring new opportunities for contemporary historiography. He is the recipient of the Doctoral Scholarship in Historical Consciousness at the university’s Australian Centre of Public History and will be hosted by the University of Bologna during 2017 on a doctoral research writing scholarship. ‘Parallel Lines’ is one of a collection of stories, The Shapes of Us, exploring liminal spaces of modern life: class, gender, sexuality, race, religion and education. It looks at lives, like lines, that do not meet but which travel in proximity, simultaneously attracted and repelled. James’ short stories have been published in various journals and anthologies.
Andrews, J; Honeybourne, D; Ashby, J; Jevons, G; Fraise, A; Fry, P; Warrington, S; Hawser, S; Wise, R
2007-09-01
A validated microbiological assay was used to measure concentrations of iclaprim (AR-100) in plasma, bronchial mucosa (BM), alveolar macrophages (AM) and epithelial lining fluid (ELF) after a single 1.6 mg/kg intravenous 60 min iv infusion of iclaprim. Male volunteers were randomly allocated to three nominal sampling time intervals 1-2 h (Group A), 3-4 h (Group B) and 5.5-7.0 h (Group C) after the start of the drug infusion. Mean iclaprim concentrations in plasma, BM, AM and ELF, respectively, were for Group A 0.59 mg/L (SD 0.18), 0.51 mg/kg (SD 0.17), 24.51 mg/L (SD 21.22) and 12.61 mg/L (SD 7.33); Group B 0.24 mg/L (SD 0.05), 0.35 mg/kg (SD 0.17), 7.16 mg/L (SD 1.91) and 6.38 mg/L (SD 5.17); and Group C 0.14 mg/L (SD 0.05), no detectable level in BM, 5.28 mg/L (SD 2.30) and 2.66 mg/L (SD 2.08). Iclaprim concentrations in ELF and AM exceeded the MIC(90) for penicillin-susceptible Streptococcus pneumoniae (MIC90 0.06 mg/L), penicillin-intermediate S. pneumoniae (MIC90 2 mg/L), penicillin-resistant S. pneumoniae (MIC90 4 mg/L) for 7, 7 and 4 h, respectively, and Chlamydia pneumoniae (MIC90 0.5 mg/L) for 7 h. Mean iclaprim concentrations in ELF exceeded the MIC90 for Haemophilus influenzae (MIC90 4 mg/L) and Moraxella catarrhalis (MIC90 8 mg/L) for up to 4 and 2 h, respectively; in AM the MIC90 was exceeded for up to 7 h. Furthermore, the MIC90 for methicillin-resistant Staphylococcus aureus of 0.12 mg/L was exceeded at all sites for up to 7 h. These data suggest that iclaprim reaches lung concentrations that should be effective in the treatment of community-acquired pneumonia.
Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.
Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg
2009-11-01
G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
Spontaneous Regression of Lumbar Herniated Disc
Directory of Open Access Journals (Sweden)
Chun-Wei Chang
2009-12-01
Full Text Available Intervertebral disc herniation of the lumbar spine is a common disease presenting with low back pain and involving nerve root radiculopathy. Some neurological symptoms in the majority of patients frequently improve after a period of conservative treatment. This has been regarded as the result of a decrease of pressure exerted from the herniated disc on neighboring neurostructures and a gradual regression of inflammation. Recently, with advances in magnetic resonance imaging, many reports have demonstrated that the herniated disc has the potential for spontaneous regression. Regression coincided with the improvement of associated symptoms. However, the exact regression mechanism remains unclear. Here, we present 2 cases of lumbar intervertebral disc herniation with spontaneous regression. We review the literature and discuss the possible mechanisms, the precipitating factors of spontaneous disc regression and the proper timing of surgical intervention.
Applied regression analysis a research tool
Pantula, Sastry; Dickey, David
1998-01-01
Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...
Simple and multiple linear regression: sample size considerations.
Hanley, James A
2016-11-01
The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright Â© 2016 Elsevier Inc. All rights reserved.
Bulcock, J. W.
The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…
Sufficient dimension reduction and prediction in regression.
Adragni, Kofi P; Cook, R Dennis
2009-11-13
Dimension reduction for regression is a prominent issue today because technological advances now allow scientists to routinely formulate regressions in which the number of predictors is considerably larger than in the past. While several methods have been proposed to deal with such regressions, principal components (PCs) still seem to be the most widely used across the applied sciences. We give a broad overview of ideas underlying a particular class of methods for dimension reduction that includes PCs, along with an introduction to the corresponding methodology. New methods are proposed for prediction in regressions with many predictors.
Spontaneous regression of an invasive thymoma.
Yutaka, Yojiro; Omasa, Mitsugu; Shikuma, Kei; Okuda, Masato; Taki, Toshihiko
2009-05-01
Although there are many reports of spontaneous regression of noninvasive thymoma, there are no reports of spontaneous regression of an invasive thymoma. Moreover, the mechanism of the spontaneous regression is still unknown. The present case concerns a 47-year-old man who presented with chest pain. Computed tomography (CT) showed a large anterior mediastinal mass with left pleural effusion that occluded the innominate vein. The tissue obtained by video-assisted thoracic surgery suggested a diagnosis of invasive thymic carcinoma. One month later CT showed prominent regression of the tumor, and the tumor was completely resected. On pathology, the diagnosis was thymoma type B3.
Use of probabilistic weights to enhance linear regression myoelectric control
Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.
2015-12-01
Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.
Application studies of line arresters
Energy Technology Data Exchange (ETDEWEB)
Zanetta Junior, Luiz Cera; Pereira, Carlos Eduardo de Morais [Sao Paulo Univ., SP (Brazil). Escola Politecnica. Dept. de Engenharia de Energia e Automacao Eletricas]. E-mail: lzanetta@pea.usp.br
2001-07-01
This paper presents the main calculations of the line arresters impact on outage rates, by focusing their effects on critical current curves, in presence of the power frequency voltage. The present critical results obtained will help in the understanding of some variables during the outrage calculations. Energy stresses on arresters due to first stroke are also evaluated in function of tower foot resistance. The transmission line studied, has a shielded 138 kV line configuration, single circuit typical of Brazilian SE region. The alternative with Zn O arresters consider their installation at every tower, in the two lower phases b and c. (author)
Regression modeling methods, theory, and computation with SAS
Panik, Michael
2009-01-01
Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,
Energy Technology Data Exchange (ETDEWEB)
Amidan, Brett G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Venzin, Alexander M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bramer, Lisa M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2015-06-03
This paper discusses the process of identifying factors that influence the contamination level of a given decision area and then determining the likelihood that the area remains unacceptable. This process is referred to as lines of evidence. These lines of evidence then serve as inputs for the stratified compliance sampling (SCS) method, which requires a decision area to be divided into strata based upon contamination expectations. This is done in order to focus sampling efforts more within stratum where contamination is more likely and to use the domain knowledge about these likelihoods of the stratum remaining unacceptable to buy down the number of samples necessary, if possible. Two different building scenarios were considered as an example (see Table 3.1). SME expertise was elicited concerning four lines of evidence factors (see Table 3.2): 1) amount of contamination that was seen before decontamination, 2) post-decontamination air sampling information, 3) the applied decontaminant information, and 4) the surface material. Statistical experimental design and logistic regression modelling were used to help determine the likelihood that example stratum remained unacceptable for a given example scenario. The number of samples necessary for clearance was calculated by applying the SCS method to the example scenario, using the estimated likelihood of each stratum remaining unacceptable as was determined using the lines of evidence approach. The commonly used simple random sampling (SRS) method was also used to calculate the number of samples necessary for clearance for comparison purposes. The lines of evidence with SCS approach resulted in a 19% to 43% reduction in total number of samples necessary for clearance (see Table 3.6). The reduction depended upon the building scenario, as well as the level of percent clean criteria. A sensitivity analysis was also performed showing how changing the estimated likelihoods of stratum remaining unacceptable affect the number
Multispectral colormapping using penalized least square regression
DEFF Research Database (Denmark)
Dissing, Bjørn Skovlund; Carstensen, Jens Michael; Larsen, Rasmus
2010-01-01
-XYZ color matching functions. The target of the regression is a well known color chart, and the models are validated using leave one out cross validation in order to maintain best possible generalization ability. The authors compare the method with a direct linear regression and see...
Gibrat’s law and quantile regressions
DEFF Research Database (Denmark)
Distante, Roberta; Petrella, Ivan; Santoro, Emiliano
2017-01-01
The nexus between firm growth, size and age in U.S. manufacturing is examined through the lens of quantile regression models. This methodology allows us to overcome serious shortcomings entailed by linear regression models employed by much of the existing literature, unveiling a number of important...
ON REGRESSION REPRESENTATIONS OF STOCHASTIC-PROCESSES
RUSCHENDORF, L; DEVALK, [No Value
We construct a.s. nonlinear regression representations of general stochastic processes (X(n))n is-an-element-of N. As a consequence we obtain in particular special regression representations of Markov chains and of certain m-dependent sequences. For m-dependent sequences we obtain a constructive
Variable importance in latent variable regression models
Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.
2014-01-01
The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable
Ridge regression and its degrees of freedom
Dijkstra, Theo K.
2014-01-01
For ridge regression the degrees of freedom are commonly calculated by the trace of the matrix that transforms the vector of observations on the dependent variable into the ridge regression estimate of its expected value. For a fixed ridge parameter this is unobjectionable. When the ridge parameter
Hierarchical regression analysis in structural Equation Modeling
de Jong, P.F.
1999-01-01
In a hierarchical or fixed-order regression analysis, the independent variables are entered into the regression equation in a prespecified order. Such an analysis is often performed when the extra amount of variance accounted for in a dependent variable by a specific independent variable is the main
Pathological assessment of liver fibrosis regression
Directory of Open Access Journals (Sweden)
WANG Bingqiong
2017-03-01
Full Text Available Hepatic fibrosis is the common pathological outcome of chronic hepatic diseases. An accurate assessment of fibrosis degree provides an important reference for a definite diagnosis of diseases, treatment decision-making, treatment outcome monitoring, and prognostic evaluation. At present, many clinical studies have proven that regression of hepatic fibrosis and early-stage liver cirrhosis can be achieved by effective treatment, and a correct evaluation of fibrosis regression has become a hot topic in clinical research. Liver biopsy has long been regarded as the gold standard for the assessment of hepatic fibrosis, and thus it plays an important role in the evaluation of fibrosis regression. This article reviews the clinical application of current pathological staging systems in the evaluation of fibrosis regression from the perspectives of semi-quantitative scoring system, quantitative approach, and qualitative approach, in order to propose a better pathological evaluation system for the assessment of fibrosis regression.
Atherosclerotic plaque regression: fact or fiction?
Shanmugam, Nesan; Román-Rego, Ana; Ong, Peter; Kaski, Juan Carlos
2010-08-01
Coronary artery disease is the major cause of death in the western world. The formation and rapid progression of atheromatous plaques can lead to serious cardiovascular events in patients with atherosclerosis. The better understanding, in recent years, of the mechanisms leading to atheromatous plaque growth and disruption and the availability of powerful HMG CoA-reductase inhibitors (statins) has permitted the consideration of plaque regression as a realistic therapeutic goal. This article reviews the existing evidence underpinning current therapeutic strategies aimed at achieving atherosclerotic plaque regression. In this review we also discuss imaging modalities for the assessment of plaque regression, predictors of regression and whether plaque regression is associated with a survival benefit.
Should metacognition be measured by logistic regression?
Rausch, Manuel; Zehetleitner, Michael
2017-03-01
Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.
Determination of ventilatory threshold through quadratic regression analysis.
Gregg, Joey S; Wyatt, Frank B; Kilgore, J Lon
2010-09-01
Ventilatory threshold (VT) has been used to measure physiological occurrences in athletes through models via gas analysis with limited accuracy. The purpose of this study is to establish a mathematical model to more accurately detect the ventilatory threshold using the ventilatory equivalent of carbon dioxide (VE/VCO2) and the ventilatory equivalent of oxygen (VE/Vo2). The methodology is primarily a mathematical analysis of data. The raw data used were archived from the cardiorespiratory laboratory in the Department of Kinesiology at Midwestern State University. Procedures for archived data collection included breath-by-breath gas analysis averaged every 20 seconds (ParVoMedics, TrueMax 2400). A ramp protocol on a Velotron bicycle ergometer was used with increased work at 25 W.min beginning with 150 W, until volitional fatigue. The subjects consisted of 27 healthy, trained cyclists with age ranging from 18 to 50 years. All subjects signed a university approved informed consent before testing. Graphic scatterplots and statistical regression analyses were performed to establish the crossover and subsequent dissociation of VE/Vo2 to VE/VCO2. A polynomial trend line along the scatterplots for VE/VO2 and VE/VCO2 was used because of the high correlation coefficient, the coefficient of determination, and trend line. The equations derived from the scatterplots and trend lines were quadratic in nature because they have a polynomial degree of 2. A graphing calculator in conjunction with a spreadsheet was used to find the exact point of intersection of the 2 trend lines. After the quadratic regression analysis, the exact point of VE/Vo2 and VE/VCO2 crossover was established as the VT. This application will allow investigators to more accurately determine the VT in subsequent research.
Allegrini, Franco; Braga, Jez W B; Moreira, Alessandro C O; Olivieri, Alejandro C
2018-06-29
A new multivariate regression model, named Error Covariance Penalized Regression (ECPR) is presented. Following a penalized regression strategy, the proposed model incorporates information about the measurement error structure of the system, using the error covariance matrix (ECM) as a penalization term. Results are reported from both simulations and experimental data based on replicate mid and near infrared (MIR and NIR) spectral measurements. The results for ECPR are better under non-iid conditions when compared with traditional first-order multivariate methods such as ridge regression (RR), principal component regression (PCR) and partial least-squares regression (PLS). Copyright © 2018 Elsevier B.V. All rights reserved.
Regression modeling of ground-water flow
Cooley, R.L.; Naff, R.L.
1985-01-01
Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)
Directory of Open Access Journals (Sweden)
Hailun Wang
2017-01-01
Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.
Applied Regression Modeling A Business Approach
Pardoe, Iain
2012-01-01
An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a
Variable and subset selection in PLS regression
DEFF Research Database (Denmark)
Høskuldsson, Agnar
2001-01-01
The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion...... is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than...
Standardization of beam line representations
International Nuclear Information System (INIS)
Carey, David C.
1999-01-01
Standardization of beam line representations means that a single set of data can be used in many situations to represent a beam line. This set of data should be the same no matter what the program to be run or the calculation to be made. We have concerned ourselves with three types of standardization: (1) The same set of data should be usable by different programs. (2) The inclusion of other items in the data, such as calculations to be done, units to be used, or preliminary specifications, should be in a notation similar to the lattice specification. (3) A single set of data should be used to represent a given beam line, no matter what is being modified or calculated. The specifics of what is to be modified or calculated can be edited into the data as part of the calculation. These three requirements all have aspects not previously discussed in a public forum. Implementations into TRANSPORT will be discussed
Standardization of beam line representations
International Nuclear Information System (INIS)
Carey, David C.
1998-01-01
Standardization of beam line representations means that a single set of data can be used in many situations to represent a beam line. This set of data should be the same no matter what the program to be run or the calculation to be made. We have concerned ourselves with three types of standardization: (1) The same set of data should be usable by different programs. (2) The inclusion of other items in the data, such as calculations to be done, units to be used, or preliminary specifications, should be in a notation similar to the lattice specification. (3) A single set of data should be used to represent a given beam line, no matter what is being modified or calculated. The specifics of what is to be modified or calculated can be edited into the data as part of the calculation. These three requirements all have aspects not previously discussed in a public forum. Implementations into TRANSPORT will be discussed
Biostatistics Series Module 6: Correlation and Linear Regression.
Hazra, Avijit; Gogtay, Nithya
2016-01-01
Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.
Unbalanced Regressions and the Predictive Equation
DEFF Research Database (Denmark)
Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo
Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...... in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... to aggregation or unexpected level shifts. In this setup, the practitioner estimates a misspecified, unbalanced, and endogenous predictive regression. We show that the OLS estimate of this regression is inconsistent, but standard inference is possible. To obtain a consistent slope estimate, we then suggest...
Dynamic travel time estimation using regression trees.
2008-10-01
This report presents a methodology for travel time estimation by using regression trees. The dissemination of travel time information has become crucial for effective traffic management, especially under congested road conditions. In the absence of c...
Patterns of Regression in Rett Syndrome
Directory of Open Access Journals (Sweden)
J Gordon Millichap
2002-10-01
Full Text Available Patterns and features of regression in a case series of 53 girls and women with Rett syndrome were studied at the Institute of Child Health and Great Ormond Street Children’s Hospital, London, UK.
Vectors, a tool in statistical regression theory
Corsten, L.C.A.
1958-01-01
Using linear algebra this thesis developed linear regression analysis including analysis of variance, covariance analysis, special experimental designs, linear and fertility adjustments, analysis of experiments at different places and times. The determination of the orthogonal projection, yielding
Discriminative Elastic-Net Regularized Linear Regression.
Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen
2017-03-01
In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.
Stochastic development regression using method of moments
DEFF Research Database (Denmark)
Kühnel, Line; Sommer, Stefan Horst
2017-01-01
This paper considers the estimation problem arising when inferring parameters in the stochastic development regression model for manifold valued non-linear data. Stochastic development regression captures the relation between manifold-valued response and Euclidean covariate variables using...... the stochastic development construction. It is thereby able to incorporate several covariate variables and random effects. The model is intrinsically defined using the connection of the manifold, and the use of stochastic development avoids linearizing the geometry. We propose to infer parameters using...
Fuzzy multiple linear regression: A computational approach
Juang, C. H.; Huang, X. H.; Fleming, J. W.
1992-01-01
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
Computing multiple-output regression quantile regions
Czech Academy of Sciences Publication Activity Database
Paindaveine, D.; Šiman, Miroslav
2012-01-01
Roč. 56, č. 4 (2012), s. 840-853 ISSN 0167-9473 R&D Projects: GA MŠk(CZ) 1M06047 Institutional research plan: CEZ:AV0Z10750506 Keywords : halfspace depth * multiple -output regression * parametric linear programming * quantile regression Subject RIV: BA - General Mathematics Impact factor: 1.304, year: 2012 http://library.utia.cas.cz/separaty/2012/SI/siman-0376413.pdf
Flexible regression models with cubic splines.
Durrleman, S; Simon, R
1989-05-01
We describe the use of cubic splines in regression models to represent the relationship between the response variable and a vector of covariates. This simple method can help prevent the problems that result from inappropriate linearity assumptions. We compare restricted cubic spline regression to non-parametric procedures for characterizing the relationship between age and survival in the Stanford Heart Transplant data. We also provide an illustrative example in cancer therapeutics.
[Ordinal logistic regression in epidemiological studies].
Abreu, Mery Natali Silva; Siqueira, Arminda Lucia; Caiaffa, Waleska Teixeira
2009-02-01
Ordinal logistic regression models have been developed for analysis of epidemiological studies. However, the adequacy of such models for adjustment has so far received little attention. In this article, we reviewed the most important ordinal regression models and common approaches used to verify goodness-of-fit, using R or Stata programs. We performed formal and graphical analyses to compare ordinal models using data sets on health conditions from the National Health and Nutrition Examination Survey (NHANES II).
Spontaneous regression of metastatic Merkel cell carcinoma.
LENUS (Irish Health Repository)
Hassan, S J
2010-01-01
Merkel cell carcinoma is a rare aggressive neuroendocrine carcinoma of the skin predominantly affecting elderly Caucasians. It has a high rate of local recurrence and regional lymph node metastases. It is associated with a poor prognosis. Complete spontaneous regression of Merkel cell carcinoma has been reported but is a poorly understood phenomenon. Here we present a case of complete spontaneous regression of metastatic Merkel cell carcinoma demonstrating a markedly different pattern of events from those previously published.
Marginal longitudinal semiparametric regression via penalized splines
Al Kadiri, M.
2010-08-01
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.
Multiple Kernel Spectral Regression for Dimensionality Reduction
Liu, Bing; Xia, Shixiong; Zhou, Yong
2013-01-01
Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples. To solve the out-of-sample extension problem, spectral regression (SR) solves the problem of learning an embedding function by establishing a regression framework, which can avoid eigen-decomposition of dense matrices. Motivated by the effectiveness of SR, we incorporate multiple kernel learning (MKL) into SR for dimensionality...
Two Paradoxes in Linear Regression Analysis
FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong
2016-01-01
Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory shou...
Inverse regression for ridge recovery II: Numerics
Glaws, Andrew; Constantine, Paul G.; Cook, R. Dennis
2018-01-01
We investigate the application of sufficient dimension reduction (SDR) to a noiseless data set derived from a deterministic function of several variables. In this context, SDR provides a framework for ridge recovery. In this second part, we explore the numerical subtleties associated with using two inverse regression methods---sliced inverse regression (SIR) and sliced average variance estimation (SAVE)---for ridge recovery. This includes a detailed numerical analysis of the eigenvalues of th...
Multivariate Frequency-Severity Regression Models in Insurance
Directory of Open Access Journals (Sweden)
Edward W. Frees
2016-02-01
Full Text Available In insurance and related industries including healthcare, it is common to have several outcome measures that the analyst wishes to understand using explanatory variables. For example, in automobile insurance, an accident may result in payments for damage to one’s own vehicle, damage to another party’s vehicle, or personal injury. It is also common to be interested in the frequency of accidents in addition to the severity of the claim amounts. This paper synthesizes and extends the literature on multivariate frequency-severity regression modeling with a focus on insurance industry applications. Regression models for understanding the distribution of each outcome continue to be developed yet there now exists a solid body of literature for the marginal outcomes. This paper contributes to this body of literature by focusing on the use of a copula for modeling the dependence among these outcomes; a major advantage of this tool is that it preserves the body of work established for marginal models. We illustrate this approach using data from the Wisconsin Local Government Property Insurance Fund. This fund offers insurance protection for (i property; (ii motor vehicle; and (iii contractors’ equipment claims. In addition to several claim types and frequency-severity components, outcomes can be further categorized by time and space, requiring complex dependency modeling. We find significant dependencies for these data; specifically, we find that dependencies among lines are stronger than the dependencies between the frequency and average severity within each line.
Management of Industrial Performance Indicators: Regression Analysis and Simulation
Directory of Open Access Journals (Sweden)
Walter Roberto Hernandez Vergara
2017-11-01
Full Text Available Stochastic methods can be used in problem solving and explanation of natural phenomena through the application of statistical procedures. The article aims to associate the regression analysis and systems simulation, in order to facilitate the practical understanding of data analysis. The algorithms were developed in Microsoft Office Excel software, using statistical techniques such as regression theory, ANOVA and Cholesky Factorization, which made it possible to create models of single and multiple systems with up to five independent variables. For the analysis of these models, the Monte Carlo simulation and analysis of industrial performance indicators were used, resulting in numerical indices that aim to improve the goals’ management for compliance indicators, by identifying systems’ instability, correlation and anomalies. The analytical models presented in the survey indicated satisfactory results with numerous possibilities for industrial and academic applications, as well as the potential for deployment in new analytical techniques.
Detecting influential observations in nonlinear regression modeling of groundwater flow
Yager, Richard M.
1998-01-01
Nonlinear regression is used to estimate optimal parameter values in models of groundwater flow to ensure that differences between predicted and observed heads and flows do not result from nonoptimal parameter values. Parameter estimates can be affected, however, by observations that disproportionately influence the regression, such as outliers that exert undue leverage on the objective function. Certain statistics developed for linear regression can be used to detect influential observations in nonlinear regression if the models are approximately linear. This paper discusses the application of Cook's D, which measures the effect of omitting a single observation on a set of estimated parameter values, and the statistical parameter DFBETAS, which quantifies the influence of an observation on each parameter. The influence statistics were used to (1) identify the influential observations in the calibration of a three-dimensional, groundwater flow model of a fractured-rock aquifer through nonlinear regression, and (2) quantify the effect of omitting influential observations on the set of estimated parameter values. Comparison of the spatial distribution of Cook's D with plots of model sensitivity shows that influential observations correspond to areas where the model heads are most sensitive to certain parameters, and where predicted groundwater flow rates are largest. Five of the six discharge observations were identified as influential, indicating that reliable measurements of groundwater flow rates are valuable data in model calibration. DFBETAS are computed and examined for an alternative model of the aquifer system to identify a parameterization error in the model design that resulted in overestimation of the effect of anisotropy on horizontal hydraulic conductivity.
Hierarchical regression for analyses of multiple outcomes.
Richardson, David B; Hamra, Ghassan B; MacLehose, Richard F; Cole, Stephen R; Chu, Haitao
2015-09-01
In cohort mortality studies, there often is interest in associations between an exposure of primary interest and mortality due to a range of different causes. A standard approach to such analyses involves fitting a separate regression model for each type of outcome. However, the statistical precision of some estimated associations may be poor because of sparse data. In this paper, we describe a hierarchical regression model for estimation of parameters describing outcome-specific relative rate functions and associated credible intervals. The proposed model uses background stratification to provide flexible control for the outcome-specific associations of potential confounders, and it employs a hierarchical "shrinkage" approach to stabilize estimates of an exposure's associations with mortality due to different causes of death. The approach is illustrated in analyses of cancer mortality in 2 cohorts: a cohort of dioxin-exposed US chemical workers and a cohort of radiation-exposed Japanese atomic bomb survivors. Compared with standard regression estimates of associations, hierarchical regression yielded estimates with improved precision that tended to have less extreme values. The hierarchical regression approach also allowed the fitting of models with effect-measure modification. The proposed hierarchical approach can yield estimates of association that are more precise than conventional estimates when one wishes to estimate associations with multiple outcomes. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Is past life regression therapy ethical?
Andrade, Gabriel
2017-01-01
Past life regression therapy is used by some physicians in cases with some mental diseases. Anxiety disorders, mood disorders, and gender dysphoria have all been treated using life regression therapy by some doctors on the assumption that they reflect problems in past lives. Although it is not supported by psychiatric associations, few medical associations have actually condemned it as unethical. In this article, I argue that past life regression therapy is unethical for two basic reasons. First, it is not evidence-based. Past life regression is based on the reincarnation hypothesis, but this hypothesis is not supported by evidence, and in fact, it faces some insurmountable conceptual problems. If patients are not fully informed about these problems, they cannot provide an informed consent, and hence, the principle of autonomy is violated. Second, past life regression therapy has the great risk of implanting false memories in patients, and thus, causing significant harm. This is a violation of the principle of non-malfeasance, which is surely the most important principle in medical ethics.
Groupwise Retargeted Least-Squares Regression.
Wang, Lingfeng; Pan, Chunhong
2018-04-01
In this brief, we propose a new groupwise retargeted least squares regression (GReLSR) model for multicategory classification. The main motivation behind GReLSR is to utilize an additional regularization to restrict the translation values of ReLSR, so that they should be similar within same class. By analyzing the regression targets of ReLSR, we propose a new formulation of ReLSR, where the translation values are expressed explicitly. On the basis of the new formulation, discriminative least-squares regression can be regarded as a special case of ReLSR with zero translation values. Moreover, a groupwise constraint is added to ReLSR to form the new GReLSR model. Extensive experiments on various machine leaning data sets illustrate that our method outperforms the current state-of-the-art approaches.
Regression Models for Market-Shares
DEFF Research Database (Denmark)
Birch, Kristina; Olsen, Jørgen Kai; Tjur, Tue
2005-01-01
On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put on the interpretat......On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put...... on the interpretation of the parameters in relation to models for the total sales based on discrete choice models.Key words and phrases. MCI model, discrete choice model, market-shares, price elasitcity, regression model....
On Solving Lq-Penalized Regressions
Directory of Open Access Journals (Sweden)
Tracy Zhou Wu
2007-01-01
Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.
LINEAR REGRESSION WITH R AND HADOOP
Directory of Open Access Journals (Sweden)
Bogdan OANCEA
2015-07-01
Full Text Available In this paper we present a way to solve the linear regression model with R and Hadoop using the Rhadoop library. We show how the linear regression model can be solved even for very large models that require special technologies. For storing the data we used Hadoop and for computation we used R. The interface between R and Hadoop is the open source library RHadoop. We present the main features of the Hadoop and R software systems and the way of interconnecting them. We then show how the least squares solution for the linear regression problem could be expressed in terms of map-reduce programming paradigm and how could be implemented using the Rhadoop library.
Principal component regression for crop yield estimation
Suryanarayana, T M V
2016-01-01
This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...
Influence diagnostics in meta-regression model.
Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua
2017-09-01
This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology. Copyright © 2017 John Wiley & Sons, Ltd.
KINERJA JACKKNIFE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS
Directory of Open Access Journals (Sweden)
HANY DEVITA
2015-02-01
Full Text Available Ordinary least square is a parameter estimations for minimizing residual sum of squares. If the multicollinearity was found in the data, unbias estimator with minimum variance could not be reached. Multicollinearity is a linear correlation between independent variabels in model. Jackknife Ridge Regression(JRR as an extension of Generalized Ridge Regression (GRR for solving multicollinearity. Generalized Ridge Regression is used to overcome the bias of estimators caused of presents multicollinearity by adding different bias parameter for each independent variabel in least square equation after transforming the data into an orthoghonal form. Beside that, JRR can reduce the bias of the ridge estimator. The result showed that JRR model out performs GRR model.
Alquier-Bouffard, A; Franck, F; Joubert-Zakeyh, J; Barthélémy, I; Mansard, S; Ughetto, S; Aublet-Cuvelier, B; Déchelotte, P-J; Mondié, J-M; Souteyrand, P; D'incan, M
2007-01-01
The predictive value of regression in melanoma is debated. A retrospective single-centre study to evaluate the correlation between regression in primary skin tumor and the presence of micrometastases in sentinel lymph nodes. Histological signs of regression in 84 melanomas (>1 mm) with corresponding sentinel lymph nodes were studied by two independent pathologists. Regression was seen in 40 skin melanoma tumors while micrometastasis was seen in 24. Of the tumors with micrometastasis, only 10 were regressive (RR: 0.47, p=0.49). Breslow value>2 mm and male sex were predictive for node micrometastasis (RR: 4.6, p=0.03 and RR: 7.6, p=0.006, respectively). On multivariate analysis, these two factors were independent. These data suggest that regression in primary cutaneous melanoma is not predictive for lymph node metastasis.
Removing Malmquist bias from linear regressions
Verter, Frances
1993-01-01
Malmquist bias is present in all astronomical surveys where sources are observed above an apparent brightness threshold. Those sources which can be detected at progressively larger distances are progressively more limited to the intrinsically luminous portion of the true distribution. This bias does not distort any of the measurements, but distorts the sample composition. We have developed the first treatment to correct for Malmquist bias in linear regressions of astronomical data. A demonstration of the corrected linear regression that is computed in four steps is presented.
Robust median estimator in logisitc regression
Czech Academy of Sciences Publication Activity Database
Hobza, T.; Pardo, L.; Vajda, Igor
2008-01-01
Roč. 138, č. 12 (2008), s. 3822-3840 ISSN 0378-3758 R&D Projects: GA MŠk 1M0572 Grant - others:Instituto Nacional de Estadistica(ES) MPO FI - IM3/136; GA MŠk(CZ) MTM 2006-06872 Institutional research plan: CEZ:AV0Z10750506 Keywords : Logistic regression * Median * Robustness * Consistency and asymptotic normality * Morgenthaler * Bianco and Yohai * Croux and Hasellbroeck Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.679, year: 2008 http://library.utia.cas.cz/separaty/2008/SI/vajda-robust%20median%20estimator%20in%20logistic%20regression.pdf
Panel data specifications in nonparametric kernel regression
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
We discuss nonparametric regression models for panel data. A fully nonparametric panel data specification that uses the time variable and the individual identifier as additional (categorical) explanatory variables is considered to be the most suitable. We use this estimator and conventional...... 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...... found the estimates of the fully nonparametric panel data model to be more reliable....
On directional multiple-output quantile regression
Czech Academy of Sciences Publication Activity Database
Paindaveine, D.; Šiman, Miroslav
2011-01-01
Roč. 102, č. 2 (2011), s. 193-212 ISSN 0047-259X R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:Commision EC(BE) Fonds National de la Recherche Scientifique Institutional research plan: CEZ:AV0Z10750506 Keywords : multivariate quantile * quantile regression * multiple-output regression * halfspace depth * portfolio optimization * value -at risk Subject RIV: BA - General Mathematics Impact factor: 0.879, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/siman-0364128.pdf
Influence of line context on power function parameters.
Butler, D L
1983-08-01
Stimuli in experiments in which line-lengths are judged are typically single lines. In studies in which area and volume are judged, the stimuli are typically more complex. An experiment with 22 college undergraduates investigated whether differences in context (single lines versus lines in depicted boxes) influenced the exponent or scaling factor of the power function of length judgments. The scaling factor of the power function was significantly affected by context, but the exponent of the power function was not.
Demonstration of a Fiber Optic Regression Probe
Korman, Valentin; Polzin, Kurt A.
2010-01-01
The capability to provide localized, real-time monitoring of material regression rates in various applications has the potential to provide a new stream of data for development testing of various components and systems, as well as serving as a monitoring tool in flight applications. These applications include, but are not limited to, the regression of a combusting solid fuel surface, the ablation of the throat in a chemical rocket or the heat shield of an aeroshell, and the monitoring of erosion in long-life plasma thrusters. The rate of regression in the first application is very fast, while the second and third are increasingly slower. A recent fundamental sensor development effort has led to a novel regression, erosion, and ablation sensor technology (REAST). The REAST sensor allows for measurement of real-time surface erosion rates at a discrete surface location. The sensor is optical, using two different, co-located fiber-optics to perform the regression measurement. The disparate optical transmission properties of the two fiber-optics makes it possible to measure the regression rate by monitoring the relative light attenuation through the fibers. As the fibers regress along with the parent material in which they are embedded, the relative light intensities through the two fibers changes, providing a measure of the regression rate. The optical nature of the system makes it relatively easy to use in a variety of harsh, high temperature environments, and it is also unaffected by the presence of electric and magnetic fields. In addition, the sensor could be used to perform optical spectroscopy on the light emitted by a process and collected by fibers, giving localized measurements of various properties. The capability to perform an in-situ measurement of material regression rates is useful in addressing a variety of physical issues in various applications. An in-situ measurement allows for real-time data regarding the erosion rates, providing a quick method for
Graphene Oxide Nanoribbons Induce Autophagic Vacuoles in Neuroblastoma Cell Lines
Directory of Open Access Journals (Sweden)
Emanuela Mari
2016-11-01
Full Text Available Since graphene nanoparticles are attracting increasing interest in relation to medical applications, it is important to understand their potential effects on humans. In the present study, we prepared graphene oxide (GO nanoribbons by oxidative unzipping of single-wall carbon nanotubes (SWCNTs and analyzed their toxicity in two human neuroblastoma cell lines. Neuroblastoma is the most common solid neoplasia in children. The hallmark of these tumors is the high number of different clinical variables, ranging from highly metastatic, rapid progression and resistance to therapy to spontaneous regression or change into benign ganglioneuromas. Patients with neuroblastoma are grouped into different risk groups that are characterized by different prognosis and different clinical behavior. Relapse and mortality in high risk patients is very high in spite of new advances in chemotherapy. Cell lines, obtained from neuroblastomas have different genotypic and phenotypic features. The cell lines SK-N-BE(2 and SH-SY5Y have different genetic mutations and tumorigenicity. Cells were exposed to low doses of GO for different times in order to investigate whether GO was a good vehicle for biological molecules delivering individualized therapy. Cytotoxicity in both cell lines was studied by measuring cellular oxidative stress (ROS, mitochondria membrane potential, expression of lysosomial proteins and cell growth. GO uptake and cytoplasmic distribution of particles were studied by Transmission Electron Microscopy (TEM for up to 72 h. The results show that GO at low concentrations increased ROS production and induced autophagy in both neuroblastoma cell lines within a few hours of exposure, events that, however, are not followed by growth arrest or death. For this reason, we suggest that the GO nanoparticle can be used for therapeutic delivery to the brain tissue with minimal effects on healthy cells.
Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP
Directory of Open Access Journals (Sweden)
Jeffrey B. Endelman
2011-11-01
Full Text Available Many important traits in plant breeding are polygenic and therefore recalcitrant to traditional marker-assisted selection. Genomic selection addresses this complexity by including all markers in the prediction model. A key method for the genomic prediction of breeding values is ridge regression (RR, which is equivalent to best linear unbiased prediction (BLUP when the genetic covariance between lines is proportional to their similarity in genotype space. This additive model can be broadened to include epistatic effects by using other kernels, such as the Gaussian, which represent inner products in a complex feature space. To facilitate the use of RR and nonadditive kernels in plant breeding, a new software package for R called rrBLUP has been developed. At its core is a fast maximum-likelihood algorithm for mixed models with a single variance component besides the residual error, which allows for efficient prediction with unreplicated training data. Use of the rrBLUP software is demonstrated through several examples, including the identification of optimal crosses based on superior progeny value. In cross-validation tests, the prediction accuracy with nonadditive kernels was significantly higher than RR for wheat ( L. grain yield but equivalent for several maize ( L. traits.
Diagnostic profiles of acute abdominal pain with multinomial logistic regression
Directory of Open Access Journals (Sweden)
Ohmann, Christian
2007-07-01
Full Text Available Purpose: Application of multinomial logistic regression for diagnostic support of acute abdominal pain, a diagnostic problem with many differential diagnoses. Methods: The analysis is based on a prospective data base with 2280 patients with acute abdominal pain, characterized by 87 variables from history and clinical examination and 12 differential diagnoses. Associations between single variables from history and clinical examination and the final diagnoses were investigated with multinomial logistic regression. Results: Exemplarily, the results are presented for the variable rigidity. A statistical significant association was observed for generalized rigidity and the diagnoses appendicitis, bowel obstruction, pancreatitis, perforated ulcer, multiple and other diagnoses and for localized rigidity and appendicitis, diverticulitis, biliary disease and perforated ulcer. Diagnostic profiles were generated by summarizing the statistical significant associations. As an example the diagnostic profile of acute appendicitis is presented. Conclusions: Compared to alternative approaches (e.g. independent Bayes, loglinear model there are advantages for multinomial logistic regression to support complex differential diagnostic problems, provided potential traps are avoided (e.g. α-error, interpretation of odds ratio.
Regression Equations for Birth Weight Estimation using ...
African Journals Online (AJOL)
In this study, Birth Weight has been estimated from anthropometric measurements of hand and foot. Linear regression equations were formed from each of the measured variables. These simple equations can be used to estimate Birth Weight of new born babies, in order to identify those with low birth weight and referred to ...
Assessing risk factors for periodontitis using regression
Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa
2013-10-01
Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.
Piecewise linear regression splines with hyperbolic covariates
International Nuclear Information System (INIS)
Cologne, John B.; Sposto, Richard
1992-09-01
Consider the problem of fitting a curve to data that exhibit a multiphase linear response with smooth transitions between phases. We propose substituting hyperbolas as covariates in piecewise linear regression splines to obtain curves that are smoothly joined. The method provides an intuitive and easy way to extend the two-phase linear hyperbolic response model of Griffiths and Miller and Watts and Bacon to accommodate more than two linear segments. The resulting regression spline with hyperbolic covariates may be fit by nonlinear regression methods to estimate the degree of curvature between adjoining linear segments. The added complexity of fitting nonlinear, as opposed to linear, regression models is not great. The extra effort is particularly worthwhile when investigators are unwilling to assume that the slope of the response changes abruptly at the join points. We can also estimate the join points (the values of the abscissas where the linear segments would intersect if extrapolated) if their number and approximate locations may be presumed known. An example using data on changing age at menarche in a cohort of Japanese women illustrates the use of the method for exploratory data analysis. (author)
Finite Algorithms for Robust Linear Regression
DEFF Research Database (Denmark)
Madsen, Kaj; Nielsen, Hans Bruun
1990-01-01
The Huber M-estimator for robust linear regression is analyzed. Newton type methods for solution of the problem are defined and analyzed, and finite convergence is proved. Numerical experiments with a large number of test problems demonstrate efficiency and indicate that this kind of approach may...
A Skew-Normal Mixture Regression Model
Liu, Min; Lin, Tsung-I
2014-01-01
A challenge associated with traditional mixture regression models (MRMs), which rest on the assumption of normally distributed errors, is determining the number of unobserved groups. Specifically, even slight deviations from normality can lead to the detection of spurious classes. The current work aims to (a) examine how sensitive the commonly…
Durbin-Watson statistic in robust regression
Czech Academy of Sciences Publication Activity Database
Víšek, Jan Ámos
2003-01-01
Roč. 23, č. 2 (2003), s. 435-448 ISSN 0208-4147 R&D Projects: GA ČR(CZ) GA402/03/0084 Institutional research plan: CEZ:AV0Z1075907 Keywords : diagnostics * regression * M-estimators * critical values of robustified D-W statistic s Subject RIV: BA - General Mathematics
Spontaneous regression of an intraspinal disc cyst
Energy Technology Data Exchange (ETDEWEB)
Demaerel, P.; Eerens, I.; Wilms, G. [University Hospital, Leuven (Belgium). Dept. of Radiology; Goffin, J. [Dept. of Neurosurgery, University Hospitals, Leuven (Belgium)
2001-11-01
We present a patient with a so-called disc cyst. Its location in the ventrolateral epidural space and its communication with the herniated disc are clearly shown. The disc cyst developed rapidly and regressed spontaneously. This observation, which has not been reported until now, appears to support focal degeneration with cyst formation as the pathogenesis. (orig.)
Model building in nonproportional hazard regression.
Rodríguez-Girondo, Mar; Kneib, Thomas; Cadarso-Suárez, Carmen; Abu-Assi, Emad
2013-12-30
Recent developments of statistical methods allow for a very flexible modeling of covariates affecting survival times via the hazard rate, including also the inspection of possible time-dependent associations. Despite their immediate appeal in terms of flexibility, these models typically introduce additional difficulties when a subset of covariates and the corresponding modeling alternatives have to be chosen, that is, for building the most suitable model for given data. This is particularly true when potentially time-varying associations are given. We propose to conduct a piecewise exponential representation of the original survival data to link hazard regression with estimation schemes based on of the Poisson likelihood to make recent advances for model building in exponential family regression accessible also in the nonproportional hazard regression context. A two-stage stepwise selection approach, an approach based on doubly penalized likelihood, and a componentwise functional gradient descent approach are adapted to the piecewise exponential regression problem. These three techniques were compared via an intensive simulation study. An application to prognosis after discharge for patients who suffered a myocardial infarction supplements the simulation to demonstrate the pros and cons of the approaches in real data analyses. Copyright © 2013 John Wiley & Sons, Ltd.
Predicting Social Trust with Binary Logistic Regression
Adwere-Boamah, Joseph; Hufstedler, Shirley
2015-01-01
This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…
Structural Break Tests Robust to Regression Misspecification
Abi Morshed, Alaa; Andreou, E.; Boldea, Otilia
2016-01-01
Structural break tests developed in the literature for regression models are sensitive to model misspecification. We show - analytically and through simulations - that the sup Wald test for breaks in the conditional mean and variance of a time series process exhibits severe size distortions when the
Assumptions of Multiple Regression: Correcting Two Misconceptions
Williams, Matt N.; Gomez Grajales, Carlos Alberto; Kurkiewicz, Dason
2013-01-01
In 2002, an article entitled "Four assumptions of multiple regression that researchers should always test" by Osborne and Waters was published in "PARE." This article has gone on to be viewed more than 275,000 times (as of August 2013), and it is one of the first results displayed in a Google search for "regression…
Macroeconomic Forecasting Using Penalized Regression Methods
Smeekes, Stephan; Wijler, Etiënne
2016-01-01
We study the suitability of lasso-type penalized regression techniques when applied to macroeconomic forecasting with high-dimensional datasets. We consider performance of the lasso-type methods when the true DGP is a factor model, contradicting the sparsity assumption underlying penalized
Linear Regression Models for Estimating True Subsurface ...
Indian Academy of Sciences (India)
47
The objective is to minimize the processing time and computer memory required .... Survey. 65 time to acquire extra GPR or seismic data for large sites and picking the first arrival time. 66 to provide the needed datasets for the joint inversion are also .... The data utilized for the regression modelling was acquired from ground.
Dimensionality Reduction in Multiple Ordinal Regression.
Zeng, Jiabei; Liu, Yang; Leng, Biao; Xiong, Zhang; Cheung, Yiu-Ming
2017-10-10
Supervised dimensionality reduction (DR) plays an important role in learning systems with high-dimensional data. It projects the data into a low-dimensional subspace and keeps the projected data distinguishable in different classes. In addition to preserving the discriminant information for binary or multiple classes, some real-world applications also require keeping the preference degrees of assigning the data to multiple aspects, e.g., to keep the different intensities for co-occurring facial expressions or the product ratings in different aspects. To address this issue, we propose a novel supervised DR method for DR in multiple ordinal regression (DRMOR), whose projected subspace preserves all the ordinal information in multiple aspects or labels. We formulate this problem as a joint optimization framework to simultaneously perform DR and ordinal regression. In contrast to most existing DR methods, which are conducted independently of the subsequent classification or ordinal regression, the proposed framework fully benefits from both of the procedures. We experimentally demonstrate that the proposed DRMOR method (DRMOR-M) well preserves the ordinal information from all the aspects or labels in the learned subspace. Moreover, DRMOR-M exhibits advantages compared with representative DR or ordinal regression algorithms on three standard data sets.
Complex Regression Functional And Load Tests Development
Directory of Open Access Journals (Sweden)
Anton Andreevich Krasnopevtsev
2015-10-01
Full Text Available The article describes practical approaches for realization of automatized regression functional and load testing on random software-hardware complex, based on «MARSh 3.0» sample. Testing automatization is being realized for «MARSh 3.0» information security increase.
Nonlinear wavelet regression function estimator for censored ...
African Journals Online (AJOL)
Let (Y;C;X) be a vector of random variables where Y; C and X are, respectively, the interest variable, a right censoring and a covariable (predictor). In this paper, we introduce a new nonlinear wavelet-based estimator of the regression function in the right censorship model. An asymptotic expression for the mean integrated ...
Revisiting Regression in Autism: Heller's "Dementia Infantilis"
Westphal, Alexander; Schelinski, Stefanie; Volkmar, Fred; Pelphrey, Kevin
2013-01-01
Theodor Heller first described a severe regression of adaptive function in normally developing children, something he termed dementia infantilis, over one 100 years ago. Dementia infantilis is most closely related to the modern diagnosis, childhood disintegrative disorder. We translate Heller's paper, Uber Dementia Infantilis, and discuss…
Measurement Error in Education and Growth Regressions
Portela, M.; Teulings, C.N.; Alessie, R.
The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations
Measurement error in education and growth regressions
Portela, Miguel; Teulings, Coen; Alessie, R.
2004-01-01
The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations
Robust Discriminant Regression for Feature Extraction.
Lai, Zhihui; Mo, Dongmei; Wong, Wai Keung; Xu, Yong; Miao, Duoqian; Zhang, David
2017-10-09
Ridge regression (RR) and its extended versions are widely used as an effective feature extraction method in pattern recognition. However, the RR-based methods are sensitive to the variations of data and can learn only limited number of projections for feature extraction and recognition. To address these problems, we propose a new method called robust discriminant regression (RDR) for feature extraction. In order to enhance the robustness, the L₂,₁-norm is used as the basic metric in the proposed RDR. The designed robust objective function in regression form can be solved by an iterative algorithm containing an eigenfunction, through which the optimal orthogonal projections of RDR can be obtained by eigen decomposition. The convergence analysis and computational complexity are presented. In addition, we also explore the intrinsic connections and differences between the RDR and some previous methods. Experiments on some well-known databases show that RDR is superior to the classical and very recent proposed methods reported in the literature, no matter the L₂-norm or the L₂,₁-norm-based regression methods. The code of this paper can be downloaded from http://www.scholat.com/laizhihui.
Early Permian transgressive–regressive cycles: Sequence ...
Indian Academy of Sciences (India)
Biplab Bhattacharya
2018-03-08
Mar 8, 2018 ... sequence stratigraphic architecture to understand the exact paleogeographic setup of the Raniganj ... regressive cycles in the light of tectonic/basinal changes, fluctuating sea level conditions and pro- ...... allowing incursion of marine water within the basin. (Bhattacharya et al. 2016). As a result, the estu-.
Group-wise partial least square regression
Camacho, José; Saccenti, Edoardo
2018-01-01
This paper introduces the group-wise partial least squares (GPLS) regression. GPLS is a new sparse PLS technique where the sparsity structure is defined in terms of groups of correlated variables, similarly to what is done in the related group-wise principal component analysis. These groups are
Predictive efficiency of ridge regression estimator
Directory of Open Access Journals (Sweden)
Tiwari Manoj
2017-01-01
Full Text Available In this article we have considered the problem of prediction within and outside the sample for actual and average values of the study variables in case of ordinary least squares and ridge regression estimators. Finally, the performance properties of the estimators are analyzed.
Modelling Issues in Kernel Ridge Regression
P. Exterkate (Peter)
2011-01-01
textabstractKernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular
Spontaneous regression of a mandibular arteriovenous malformation
Directory of Open Access Journals (Sweden)
Scott B. Raymond, MD, PhD
2015-06-01
Full Text Available Mandibular arteriovenous malformations (AVMs are rare lesions that may initially present as catastrophic bleeding during dental surgical procedures. Owing to the significant risk of bleeding, most mandibular AVMs are treated definitively by resection or embolization. In this report, we describe a mandibular AVM that spontaneously regressed after biopsy.
Functional data analysis of generalized regression quantiles
Guo, Mengmeng
2013-11-05
Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.
Multiple Linear Regression: A Realistic Reflector.
Nutt, A. T.; Batsell, R. R.
Examples of the use of Multiple Linear Regression (MLR) techniques are presented. This is done to show how MLR aids data processing and decision-making by providing the decision-maker with freedom in phrasing questions and by accurately reflecting the data on hand. A brief overview of the rationale underlying MLR is given, some basic definitions…
transformation of independent variables in polynomial regression ...
African Journals Online (AJOL)
Ada
preferable when possible to work with a simple functional form in transformed variables rather than with a more complicated form in the original variables. In this paper, it is shown that linear transformations applied to independent variables in polynomial regression models affect the t ratio and hence the statistical ...
Yet another look at MIDAS regression
Ph.H.B.F. Franses (Philip Hans)
2016-01-01
textabstractA MIDAS regression involves a dependent variable observed at a low frequency and independent variables observed at a higher frequency. This paper relates a true high frequency data generating process, where also the dependent variable is observed (hypothetically) at the high frequency,
Regression Model to Predict Global Solar Irradiance in Malaysia
Directory of Open Access Journals (Sweden)
Hairuniza Ahmed Kutty
2015-01-01
Full Text Available A novel regression model is developed to estimate the monthly global solar irradiance in Malaysia. The model is developed based on different available meteorological parameters, including temperature, cloud cover, rain precipitate, relative humidity, wind speed, pressure, and gust speed, by implementing regression analysis. This paper reports on the details of the analysis of the effect of each prediction parameter to identify the parameters that are relevant to estimating global solar irradiance. In addition, the proposed model is compared in terms of the root mean square error (RMSE, mean bias error (MBE, and the coefficient of determination (R2 with other models available from literature studies. Seven models based on single parameters (PM1 to PM7 and five multiple-parameter models (PM7 to PM12 are proposed. The new models perform well, with RMSE ranging from 0.429% to 1.774%, R2 ranging from 0.942 to 0.992, and MBE ranging from −0.1571% to 0.6025%. In general, cloud cover significantly affects the estimation of global solar irradiance. However, cloud cover in Malaysia lacks sufficient influence when included into multiple-parameter models although it performs fairly well in single-parameter prediction models.
Computing group cardinality constraint solutions for logistic regression problems.
Zhang, Yong; Kwon, Dongjin; Pohl, Kilian M
2017-01-01
We derive an algorithm to directly solve logistic regression based on cardinality constraint, group sparsity and use it to classify intra-subject MRI sequences (e.g. cine MRIs) of healthy from diseased subjects. Group cardinality constraint models are often applied to medical images in order to avoid overfitting of the classifier to the training data. Solutions within these models are generally determined by relaxing the cardinality constraint to a weighted feature selection scheme. However, these solutions relate to the original sparse problem only under specific assumptions, which generally do not hold for medical image applications. In addition, inferring clinical meaning from features weighted by a classifier is an ongoing topic of discussion. Avoiding weighing features, we propose to directly solve the group cardinality constraint logistic regression problem by generalizing the Penalty Decomposition method. To do so, we assume that an intra-subject series of images represents repeated samples of the same disease patterns. We model this assumption by combining series of measurements created by a feature across time into a single group. Our algorithm then derives a solution within that model by decoupling the minimization of the logistic regression function from enforcing the group sparsity constraint. The minimum to the smooth and convex logistic regression problem is determined via gradient descent while we derive a closed form solution for finding a sparse approximation of that minimum. We apply our method to cine MRI of 38 healthy controls and 44 adult patients that received reconstructive surgery of Tetralogy of Fallot (TOF) during infancy. Our method correctly identifies regions impacted by TOF and generally obtains statistically significant higher classification accuracy than alternative solutions to this model, i.e., ones relaxing group cardinality constraints. Copyright © 2016 Elsevier B.V. All rights reserved.
Mai, W.; Zhang, J.-F.; Zhao, X.-M.; Li, Z.; Xu, Z.-W.
2017-11-01
Wastewater from the dye industry is typically analyzed using a standard method for measurement of chemical oxygen demand (COD) or by a single-wavelength spectroscopic method. To overcome the disadvantages of these methods, ultraviolet-visible (UV-Vis) spectroscopy was combined with principal component regression (PCR) and partial least squares regression (PLSR) in this study. Unlike the standard method, this method does not require digestion of the samples for preparation. Experiments showed that the PLSR model offered high prediction performance for COD, with a mean relative error of about 5% for two dyes. This error is similar to that obtained with the standard method. In this study, the precision of the PLSR model decreased with the number of dye compounds present. It is likely that multiple models will be required in reality, and the complexity of a COD monitoring system would be greatly reduced if the PLSR model is used because it can include several dyes. UV-Vis spectroscopy with PLSR successfully enhanced the performance of COD prediction for dye wastewater and showed good potential for application in on-line water quality monitoring.
Richter-Schrag, Hans-Jürgen; Glatz, Torben; Walker, Christine; Fischer, Andreas; Thimme, Robert
2016-11-07
To evaluate rebleeding, primary failure (PF) and mortality of patients in whom over-the-scope clips (OTSCs) were used as first-line and second-line endoscopic treatment (FLET, SLET) of upper and lower gastrointestinal bleeding (UGIB, LGIB). A retrospective analysis of a prospectively collected database identified all patients with UGIB and LGIB in a tertiary endoscopic referral center of the University of Freiburg, Germany, from 04-2012 to 05-2016 ( n = 93) who underwent FLET and SLET with OTSCs. The complete Rockall risk scores were calculated from patients with UGIB. The scores were categorized as < or ≥ 7 and were compared with the original Rockall data. Differences between FLET and SLET were calculated. Univariate and multivariate analysis were performed to evaluate the factors that influenced rebleeding after OTSC placement. Primary hemostasis and clinical success of bleeding lesions (without rebleeding) was achieved in 88/100 (88%) and 78/100 (78%), respectively. PF was significantly lower when OTSCs were applied as FLET compared to SLET (4.9% vs 23%, P = 0.008). In multivariate analysis, patients who had OTSC placement as SLET had a significantly higher rebleeding risk compared to those who had FLET (OR 5.3; P = 0.008). Patients with Rockall risk scores ≥ 7 had a significantly higher in-hospital mortality compared to those with scores < 7 (35% vs 10%, P = 0.034). No significant differences were observed in patients with scores < or ≥ 7 in rebleeding and rebleeding-associated mortality. Our data show for the first time that FLET with OTSC might be the best predictor to successfully prevent rebleeding of gastrointestinal bleeding compared to SLET. The type of treatment determines the success of primary hemostasis or primary failure.
Controlling attribute effect in linear regression
Calders, Toon
2013-12-01
In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models. © 2013 IEEE.
Beta-binomial regression and bimodal utilization.
Liu, Chuan-Fen; Burgess, James F; Manning, Willard G; Maciejewski, Matthew L
2013-10-01
To illustrate how the analysis of bimodal U-shaped distributed utilization can be modeled with beta-binomial regression, which is rarely used in health services research. Veterans Affairs (VA) administrative data and Medicare claims in 2001-2004 for 11,123 Medicare-eligible VA primary care users in 2000. We compared means and distributions of VA reliance (the proportion of all VA/Medicare primary care visits occurring in VA) predicted from beta-binomial, binomial, and ordinary least-squares (OLS) models. Beta-binomial model fits the bimodal distribution of VA reliance better than binomial and OLS models due to the nondependence on normality and the greater flexibility in shape parameters. Increased awareness of beta-binomial regression may help analysts apply appropriate methods to outcomes with bimodal or U-shaped distributions. © Health Research and Educational Trust.
Multiple Kernel Spectral Regression for Dimensionality Reduction
Directory of Open Access Journals (Sweden)
Bing Liu
2013-01-01
Full Text Available Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples. To solve the out-of-sample extension problem, spectral regression (SR solves the problem of learning an embedding function by establishing a regression framework, which can avoid eigen-decomposition of dense matrices. Motivated by the effectiveness of SR, we incorporate multiple kernel learning (MKL into SR for dimensionality reduction. The proposed approach (termed MKL-SR seeks an embedding function in the Reproducing Kernel Hilbert Space (RKHS induced by the multiple base kernels. An MKL-SR algorithm is proposed to improve the performance of kernel-based SR (KSR further. Furthermore, the proposed MKL-SR algorithm can be performed in the supervised, unsupervised, and semi-supervised situation. Experimental results on supervised classification and semi-supervised classification demonstrate the effectiveness and efficiency of our algorithm.
Rudner, Lawrence
2016-01-01
In the machine learning literature, it is commonly accepted as fact that as calibration sample sizes increase, Naïve Bayes classifiers initially outperform Logistic Regression classifiers in terms of classification accuracy. Applied to subtests from an on-line final examination and from a highly regarded certification examination, this study shows…
Directional quantile regression in Octave (and MATLAB)
Czech Academy of Sciences Publication Activity Database
Boček, Pavel; Šiman, Miroslav
2016-01-01
Roč. 52, č. 1 (2016), s. 28-51 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : quantile regression * multivariate quantile * depth contour * Matlab Subject RIV: IN - Informatics, Computer Science Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/bocek-0458380.pdf
Determination of regression laws: Linear and nonlinear
International Nuclear Information System (INIS)
Onishchenko, A.M.
1994-01-01
A detailed mathematical determination of regression laws is presented in the article. Particular emphasis is place on determining the laws of X j on X l to account for source nuclei decay and detector errors in nuclear physics instrumentation. Both linear and nonlinear relations are presented. Linearization of 19 functions is tabulated, including graph, relation, variable substitution, obtained linear function, and remarks. 6 refs., 1 tab
Three Contributions to Robust Regression Diagnostics
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2015-01-01
Roč. 11, č. 2 (2015), s. 69-78 ISSN 1336-9180 Grant - others:GA ČR(CZ) GA13-01930S; Nadační fond na podporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : robust regression * robust econometrics * hypothesis testing Subject RIV: BA - General Mathematics http://www.degruyter.com/view/j/jamsi.2015.11.issue-2/jamsi-2015-0013/jamsi-2015-0013. xml ?format=INT
In utero diagnosis of caudal regression syndrome
Directory of Open Access Journals (Sweden)
Lindsey M. Negrete, BS
2015-01-01
Full Text Available We present a case of caudal regression syndrome (CRS, a relatively uncommon defect of the lower spine accompanied by a wide range of developmental abnormalities. CRS is closely associated with pregestational diabetes and is nearly 200 times more prevalent in infants of diabetic mothers (1, 2. We report a case of prenatally suspected CRS in a fetus of a nondiabetic mother and discuss how the initial neurological abnormalities found on imaging correlate with the postnatal clinical deficits.
Logistic regression a self-learning text
Kleinbaum, David G
1994-01-01
This textbook provides students and professionals in the health sciences with a presentation of the use of logistic regression in research. The text is self-contained, and designed to be used both in class or as a tool for self-study. It arises from the author's many years of experience teaching this material and the notes on which it is based have been extensively used throughout the world.
Nonparametric and semiparametric dynamic additive regression models
DEFF Research Database (Denmark)
Scheike, Thomas Harder; Martinussen, Torben
Dynamic additive regression models provide a flexible class of models for analysis of longitudinal data. The approach suggested in this work is suited for measurements obtained at random time points and aims at estimating time-varying effects. Both fully nonparametric and semiparametric models can...... in special cases. We investigate the finite sample properties of the estimators and conclude that the asymptotic results are valid for even samll samples....
Structured Dimensionality Reduction for Additive Model Regression
Fawzi, Alhussein; Fiot, Jean-Baptiste; Chen, Bei; Sinn, Mathieu; Frossard, Pascal
2016-01-01
Additive models are regression methods which model the response variable as the sum of univariate transfer functions of the input variables. Key benefits of additive models are their accuracy and interpretability on many real-world tasks. Additive models are however not adapted to problems involving a large number (e.g., hundreds) of input variables, as they are prone to overfitting in addition to losing interpretability. In this paper, we introduce a novel framework for applying additive ...
A Convex Framework for Fair Regression
Berk, Richard; Heidari, Hoda; Jabbari, Shahin; Joseph, Matthew; Kearns, Michael; Morgenstern, Jamie; Neel, Seth; Roth, Aaron
2017-01-01
We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and they span the rang from notions of group fairness to strong individual fairness. By varying the weight on the fairness regularizer, we can compute the efficient frontier of the accuracy-fairness trade-off on any given dataset, and we measure the severity of this trade-off via a numerical quantity we call the Price of F...
Superquantile Regression: Theory, Algorithms, and Applications
2014-12-01
equivalent to the one described in Artzner et al. (1999), where axiom (i) is replaced by translation invariance . When we refer to a coherent measure...defined as Di = ( f(X)− f (i)(X) )2 mMSE = ( f(X)− f (i)(X) )2 m (f(X)− Y )2 , (II.47) where f (i)(·) represents the fitted regression function without
A Product Line Enhanced Unified Process
DEFF Research Database (Denmark)
Zhang, Weishan; Kunz, Thomas
2006-01-01
The Unified Process facilitates reuse for a single system, but falls short handling multiple similar products. In this paper we present an enhanced Unified Process, called UPEPL, integrating the product line technology in order to alleviate this problem. In UPEPL, the product line related...... activities are added and could be conducted side by side with other classical UP activities. In this way both the advantages of Unified Process and software product lines could co-exist in UPEPL. We show how to use UPEPL with an industrial mobile device product line in our case study....
Linear regression and the normality assumption.
Schmidt, Amand F; Finan, Chris
2017-12-16
Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.
Bayesian Inference of a Multivariate Regression Model
Directory of Open Access Journals (Sweden)
Marick S. Sinay
2014-01-01
Full Text Available We explore Bayesian inference of a multivariate linear regression model with use of a flexible prior for the covariance structure. The commonly adopted Bayesian setup involves the conjugate prior, multivariate normal distribution for the regression coefficients and inverse Wishart specification for the covariance matrix. Here we depart from this approach and propose a novel Bayesian estimator for the covariance. A multivariate normal prior for the unique elements of the matrix logarithm of the covariance matrix is considered. Such structure allows for a richer class of prior distributions for the covariance, with respect to strength of beliefs in prior location hyperparameters, as well as the added ability, to model potential correlation amongst the covariance structure. The posterior moments of all relevant parameters of interest are calculated based upon numerical results via a Markov chain Monte Carlo procedure. The Metropolis-Hastings-within-Gibbs algorithm is invoked to account for the construction of a proposal density that closely matches the shape of the target posterior distribution. As an application of the proposed technique, we investigate a multiple regression based upon the 1980 High School and Beyond Survey.
General regression and representation model for classification.
Directory of Open Access Journals (Sweden)
Jianjun Qian
Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.
Multitask Quantile Regression under the Transnormal Model.
Fan, Jianqing; Xue, Lingzhou; Zou, Hui
2016-01-01
We consider estimating multi-task quantile regression under the transnormal model, with focus on high-dimensional setting. We derive a surprisingly simple closed-form solution through rank-based covariance regularization. In particular, we propose the rank-based ℓ 1 penalization with positive definite constraints for estimating sparse covariance matrices, and the rank-based banded Cholesky decomposition regularization for estimating banded precision matrices. By taking advantage of alternating direction method of multipliers, nearest correlation matrix projection is introduced that inherits sampling properties of the unprojected one. Our work combines strengths of quantile regression and rank-based covariance regularization to simultaneously deal with nonlinearity and nonnormality for high-dimensional regression. Furthermore, the proposed method strikes a good balance between robustness and efficiency, achieves the "oracle"-like convergence rate, and provides the provable prediction interval under the high-dimensional setting. The finite-sample performance of the proposed method is also examined. The performance of our proposed rank-based method is demonstrated in a real application to analyze the protein mass spectroscopy data.
Spontaneous Regression of a Cervical Disk Herniation
Directory of Open Access Journals (Sweden)
Emre Delen
2014-03-01
Full Text Available A 54 years old female patient was admitted to our outpatient clinic with a two months history of muscle spasms of her neck and pain radiating to the left upper extremity. Magnetic resonance imaging had shown a large left-sided paracentral disk herniation at the C6-C7 disk space (Figure 1. Neurological examination showed no obvious neurological deficit. She received conservative treatment including bed rest, rehabilitation, and analgesic drugs. After 13 months, requested by the patient, a second magnetic resonance imaging study showed resolution of the disc herniation.(Figure 2 Although the literature contains several reports about spontaneous regression of herniated lumbar disc without surgical intervention, that of phenomenon reported for herniated cervical level is rare, and such reports are few[1]. In conclusion, herniated intervertebral disc have the potential to spontaneously regress independently from the spine level. With further studies, determining the predictive signs for prognostic evaluation for spontaneous regression which would yield to conservative treatment would be beneficial.
Satellite rainfall retrieval by logistic regression
Chiu, Long S.
1986-01-01
The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.
Geographically weighted regression model on poverty indicator
Slamet, I.; Nugroho, N. F. T. A.; Muslich
2017-12-01
In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.
Bayesian regression for group testing data.
McMahan, Christopher S; Tebbs, Joshua M; Hanson, Timothy E; Bilder, Christopher R
2017-12-01
Group testing involves pooling individual specimens (e.g., blood, urine, swabs, etc.) and testing the pools for the presence of a disease. When individual covariate information is available (e.g., age, gender, number of sexual partners, etc.), a common goal is to relate an individual's true disease status to the covariates in a regression model. Estimating this relationship is a nonstandard problem in group testing because true individual statuses are not observed and all testing responses (on pools and on individuals) are subject to misclassification arising from assay error. Previous regression methods for group testing data can be inefficient because they are restricted to using only initial pool responses and/or they make potentially unrealistic assumptions regarding the assay accuracy probabilities. To overcome these limitations, we propose a general Bayesian regression framework for modeling group testing data. The novelty of our approach is that it can be easily implemented with data from any group testing protocol. Furthermore, our approach will simultaneously estimate assay accuracy probabilities (along with the covariate effects) and can even be applied in screening situations where multiple assays are used. We apply our methods to group testing data collected in Iowa as part of statewide screening efforts for chlamydia, and we make user-friendly R code available to practitioners. © 2017, The International Biometric Society.
LOGISTIC REGRESSION ANALYSIS WITH STANDARDIZED MARKERS.
Huang, Ying; Pepe, Margaret S; Feng, Ziding
2013-09-01
Two different approaches to analysis of data from diagnostic biomarker studies are commonly employed. Logistic regression is used to fit models for probability of disease given marker values while ROC curves and risk distributions are used to evaluate classification performance. In this paper we present a method that simultaneously accomplishes both tasks. The key step is to standardize markers relative to the non-diseased population before including them in the logistic regression model. Among the advantages of this method are: (i) ensuring that results from regression and performance assessments are consistent with each other; (ii) allowing covariate adjustment and covariate effects on ROC curves to be handled in a familiar way, and (iii) providing a mechanism to incorporate important assumptions about structure in the ROC curve into the fitted risk model. We develop the method in detail for the problem of combining biomarker datasets derived from multiple studies, populations or biomarker measurement platforms, when ROC curves are similar across data sources. The methods are applicable to both cohort and case-control sampling designs. The dataset motivating this application concerns Prostate Cancer Antigen 3 (PCA3) for diagnosis of prostate cancer in patients with or without previous negative biopsy where the ROC curves for PCA3 are found to be the same in the two populations. Estimated constrained maximum likelihood and empirical likelihood estimators are derived. The estimators are compared in simulation studies and the methods are illustrated with the PCA3 dataset.
Dimensionality Reduction via Regression in Hyperspectral Imagery
Laparra, Valero; Malo, Jesus; Camps-Valls, Gustau
2015-09-01
This paper introduces a new unsupervised method for dimensionality reduction via regression (DRR). The algorithm belongs to the family of invertible transforms that generalize Principal Component Analysis (PCA) by using curvilinear instead of linear features. DRR identifies the nonlinear features through multivariate regression to ensure the reduction in redundancy between he PCA coefficients, the reduction of the variance of the scores, and the reduction in the reconstruction error. More importantly, unlike other nonlinear dimensionality reduction methods, the invertibility, volume-preservation, and straightforward out-of-sample extension, makes DRR interpretable and easy to apply. The properties of DRR enable learning a more broader class of data manifolds than the recently proposed Non-linear Principal Components Analysis (NLPCA) and Principal Polynomial Analysis (PPA). We illustrate the performance of the representation in reducing the dimensionality of remote sensing data. In particular, we tackle two common problems: processing very high dimensional spectral information such as in hyperspectral image sounding data, and dealing with spatial-spectral image patches of multispectral images. Both settings pose collinearity and ill-determination problems. Evaluation of the expressive power of the features is assessed in terms of truncation error, estimating atmospheric variables, and surface land cover classification error. Results show that DRR outperforms linear PCA and recently proposed invertible extensions based on neural networks (NLPCA) and univariate regressions (PPA).
Mixed-effects regression models in linguistics
Heylen, Kris; Geeraerts, Dirk
2018-01-01
When data consist of grouped observations or clusters, and there is a risk that measurements within the same group are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations. Regression models that contain such group-specific random effects are called mixed-effects regression models, or simply mixed models. Mixed models are a versatile tool that can handle both balanced and unbalanced datasets and that can also be applied when several layers of grouping are present in the data; these layers can either be nested or crossed. In linguistics, as in many other fields, the use of mixed models has gained ground rapidly over the last decade. This methodological evolution enables us to build more sophisticated and arguably more realistic models, but, due to its technical complexity, also introduces new challenges. This volume brings together a number of promising new evolutions in the use of mixed models in linguistics, but also addres...
Testing of a Fiber Optic Wear, Erosion and Regression Sensor
Korman, Valentin; Polzin, Kurt A.
2011-01-01
The nature of the physical processes and harsh environments associated with erosion and wear in propulsion environments makes their measurement and real-time rate quantification difficult. A fiber optic sensor capable of determining the wear (regression, erosion, ablation) associated with these environments has been developed and tested in a number of different applications to validate the technique. The sensor consists of two fiber optics that have differing attenuation coefficients and transmit light to detectors. The ratio of the two measured intensities can be correlated to the lengths of the fiber optic lines, and if the fibers and the host parent material in which they are embedded wear at the same rate the remaining length of fiber provides a real-time measure of the wear process. Testing in several disparate situations has been performed, with the data exhibiting excellent qualitative agreement with the theoretical description of the process and when a separate calibrated regression measurement is available good quantitative agreement is obtained as well. The light collected by the fibers can also be used to optically obtain the spectra and measure the internal temperature of the wear layer.
International Nuclear Information System (INIS)
Jafri, Y.Z.; Kamal, L.
2007-01-01
Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)
Polat, Esra; Gunay, Suleyman
2013-10-01
One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.
International Nuclear Information System (INIS)
Jang, Hak Sin; Kim, Sin Yeong
1998-02-01
This book is about cable line engineering. It is comprised of nine chapters, which deals with summary of cable communication such as way, process of cable communication and optical communication, Line constant of transmission on primary constant, reflection and crosstalk, communication cable line of types like flat cable, coaxial cable and loaded cable, Install of communication line with types and facility of aerial line, construction method of communication line facility, Measurement of communication line, Carrier communication of summary, PCM communication with Introduction, regeneration relay system sampling and quantization and Electric communication service and general information network with mobile communication technique and satellite communication system.
Calhelha, Ricardo C; Martínez, Mireia A; Prieto, M A; Ferreira, Isabel C F R
2017-10-23
The development of convenient tools for describing and quantifying the effects of standard and novel therapeutic agents is essential for the research community, to perform more precise evaluations. Although mathematical models and quantification criteria have been exchanged in the last decade between different fields of study, there are relevant methodologies that lack proper mathematical descriptions and standard criteria to quantify their responses. Therefore, part of the relevant information that can be drawn from the experimental results obtained and the quantification of its statistical reliability are lost. Despite its relevance, there is not a standard form for the in vitro endpoint tumor cell lines' assays (TCLA) that enables the evaluation of the cytotoxic dose-response effects of anti-tumor drugs. The analysis of all the specific problems associated with the diverse nature of the available TCLA used is unfeasible. However, since most TCLA share the main objectives and similar operative requirements, we have chosen the sulforhodamine B (SRB) colorimetric assay for cytotoxicity screening of tumor cell lines as an experimental case study. In this work, the common biological and practical non-linear dose-response mathematical models are tested against experimental data and, following several statistical analyses, the model based on the Weibull distribution was confirmed as the convenient approximation to test the cytotoxic effectiveness of anti-tumor compounds. Then, the advantages and disadvantages of all the different parametric criteria derived from the model, which enable the quantification of the dose-response drug-effects, are extensively discussed. Therefore, model and standard criteria for easily performing the comparisons between different compounds are established. The advantages include a simple application, provision of parametric estimations that characterize the response as standard criteria, economization of experimental effort and enabling
Fused Regression for Multi-source Gene Regulatory Network Inference.
Directory of Open Access Journals (Sweden)
Kari Y Lam
2016-12-01
Full Text Available Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method's utility in learning from data collected on different experimental platforms.
Drzewiecki, Wojciech
2016-12-01
In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels) was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques. The results proved that in case of sub-pixel evaluation the most accurate prediction of change may not necessarily be based on the most accurate individual assessments. When single methods are considered, based on obtained results Cubist algorithm may be advised for Landsat based mapping of imperviousness for single dates. However, Random Forest may be endorsed when the most reliable evaluation of imperviousness change is the primary goal. It gave lower accuracies for individual assessments, but better prediction of change due to more correlated errors of individual predictions. Heterogeneous model ensembles performed for individual time points assessments at least as well as the best individual models. In case of imperviousness change assessment the ensembles always outperformed single model approaches. It means that it is possible to improve the accuracy of sub-pixel imperviousness change assessment using ensembles of heterogeneous non-linear regression models.
Magnitude conversion to unified moment magnitude using orthogonal regression relation
Das, Ranjit; Wason, H. R.; Sharma, M. L.
2012-05-01
Homogenization of earthquake catalog being a pre-requisite for seismic hazard assessment requires region based magnitude conversion relationships. Linear Standard Regression (SR) relations fail when both the magnitudes have measurement errors. To accomplish homogenization, techniques like Orthogonal Standard Regression (OSR) are thus used. In this paper a technique is proposed for using such OSR for preparation of homogenized earthquake catalog in moment magnitude Mw. For derivation of orthogonal regression relation between mb and Mw, a data set consisting of 171 events with observed body wave magnitudes (mb,obs) and moment magnitude (Mw,obs) values has been taken from ISC and GCMT databases for Northeast India and adjoining region for the period 1978-2006. Firstly, an OSR relation given below has been developed using mb,obs and Mw,obs values corresponding to 150 events from this data set. M=1.3(±0.004)m-1.4(±0.130), where mb,proxy are body wave magnitude values of the points on the OSR line given by the orthogonality criterion, for observed (mb,obs, Mw,obs) points. A linear relation is then developed between these 150 mb,obs values and corresponding mb,proxy values given by the OSR line using orthogonality criterion. The relation obtained is m=0.878(±0.03)m+0.653(±0.15). The accuracy of the above procedure has been checked with the rest of the data i.e., 21 events values. The improvement in the correlation coefficient value between mb,obs and Mw estimated using the proposed procedure compared to the correlation coefficient value between mb,obs and Mw,obs shows the advantage of OSR relationship for homogenization. The OSR procedure developed in this study can be used to homogenize any catalog containing various magnitudes (e.g., ML, mb, MS) with measurement errors, by their conversion to unified moment magnitude Mw. The proposed procedure also remains valid in case the magnitudes have measurement errors of different orders, i.e. the error variance ratio is
International Nuclear Information System (INIS)
Camargo, E.E.; Rockmann, R.L.; Barreto, T.M.; Eston, T.E.; Papaleo Netto, M.; Carvalho, N.
1974-01-01
Through a logarithmic regression performed with the contings of 4 plasma samples withdrawn at 20,40,60 and 80 minutes after a venous injection of vitamin B 12 - 57 Co, the glomerular filtration-rate(GFR) in 11 patients, performing simultaneously the same study with EDTA- 51 Cr in 3 of them, is evaluated. The values obtained through the regression straight line are compared with those given by only 2 points, in the 6 possible combinations: 20 and 40 minutes, 20 and 60 minutes, 20 and 80 minutes, 40 and 60 minutes, 40 and 80 minutes, 60 and 80 minutes. The pair of points obtained at 20 and 80 minutes determined the straight line most similar to the logarithmic regression and as a simplification of the method, the withdraw of only 2 plasma samples, at and 80 minutes after a single injection of vitamin B 12 -57 Co is proposed [pt
Humanoid environmental perception with Gaussian process regression
Directory of Open Access Journals (Sweden)
Dingsheng Luo
2016-11-01
Full Text Available Nowadays, humanoids are increasingly expected acting in the real world to complete some high-level tasks humanly and intelligently. However, this is a hard issue due to that the real world is always extremely complicated and full of miscellaneous variations. As a consequence, for a real-world-acting robot, precisely perceiving the environmental changes might be an essential premise. Unlike human being, humanoid robot usually turns out to be with much less sensors to get enough information from the real world, which further leads the environmental perception problem to be more challenging. Although it can be tackled by establishing direct sensory mappings or adopting probabilistic filtering methods, the nonlinearity and uncertainty caused by both the complexity of the environment and the high degree of freedom of the robots will result in tough modeling difficulties. In our study, with the Gaussian process regression framework, an alternative learning approach to address such a modeling problem is proposed and discussed. Meanwhile, to debase the influence derived from limited sensors, the idea of fusing multiple sensory information is also involved. To evaluate the effectiveness, with two representative environment changing tasks, that is, suffering unknown external pushing and suddenly encountering sloped terrains, the proposed approach is applied to a humanoid, which is only equipped with a three-axis gyroscope and a three-axis accelerometer. Experimental results reveal that the proposed Gaussian process regression-based approach is effective in coping with the nonlinearity and uncertainty of the humanoid environmental perception problem. Further, a humanoid balancing controller is developed, which takes the output of the Gaussian process regression-based environmental perception as the seed to activate the corresponding balancing strategy. Both simulated and hardware experiments consistently show that our approach is valuable and leads to a
Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M
2007-09-01
Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.
Convex Regression with Interpretable Sharp Partitions.
Petersen, Ashley; Simon, Noah; Witten, Daniela
2016-06-01
We consider the problem of predicting an outcome variable on the basis of a small number of covariates, using an interpretable yet non-additive model. We propose convex regression with interpretable sharp partitions (CRISP) for this task. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block. Unlike other partitioning methods, CRISP is fit using a non-greedy approach by solving a convex optimization problem, resulting in low-variance fits. We explore the properties of CRISP, and evaluate its performance in a simulation study and on a housing price data set.
Fixed kernel regression for voltammogram feature extraction
International Nuclear Information System (INIS)
Acevedo Rodriguez, F J; López-Sastre, R J; Gil-Jiménez, P; Maldonado Bascón, S; Ruiz-Reyes, N
2009-01-01
Cyclic voltammetry is an electroanalytical technique for obtaining information about substances under analysis without the need for complex flow systems. However, classifying the information in voltammograms obtained using this technique is difficult. In this paper, we propose the use of fixed kernel regression as a method for extracting features from these voltammograms, reducing the information to a few coefficients. The proposed approach has been applied to a wine classification problem with accuracy rates of over 98%. Although the method is described here for extracting voltammogram information, it can be used for other types of signals