Deriving the Regression Line with Algebra
Quintanilla, John A.
2017-01-01
Exploration with spreadsheets and reliance on previous skills can lead students to determine the line of best fit. To perform linear regression on a set of data, students in Algebra 2 (or, in principle, Algebra 1) do not have to settle for using the mysterious "black box" of their graphing calculators (or other classroom technologies).…
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...
Hybrid single node genetic programming for symbolic regression
Kubalìk, Jiřì; Alibekov, Eduard; Žegklitz, Jan; Babuska, R.; Nguyen, NT; Kowalczyk, R; Filipe, J
2016-01-01
This paper presents a first step of our research on designing an effective and efficient GP-based method for symbolic regression. First, we propose three extensions of the standard Single Node GP, namely (1) a selection strategy for choosing nodes to be mutated based on depth and performance of
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
Muñoz, Neus; Sánchez-Delgado, Jordi; Baylina, Mireia; Puig, Ignasi; López-Góngora, Sheila; Suarez, David; Calvet, Xavier
2018-06-01
Multiple Helicobacter pylori second-line schedules have been described as potentially useful. It remains unclear, however, which are the best combinations, and which features of second-line treatments are related to better cure rates. The aim of this study was to determine that second-line treatments achieved excellent (>90%) cure rates by performing a systematic review and when possible a meta-analysis. A meta-regression was planned to determine the characteristics of treatments achieving excellent cure rates. A systematic review for studies evaluating second-line Helicobacter pylori treatment was carried out in multiple databases. A formal meta-analysis was performed when an adequate number of comparative studies was found, using RevMan5.3. A meta-regression for evaluating factors predicting cure rates >90% was performed using Stata Statistical Software. The systematic review identified 115 eligible studies, including 203 evaluable treatment arms. The results were extremely heterogeneous, with 61 treatment arms (30%) achieving optimal (>90%) cure rates. The meta-analysis favored quadruple therapies over triple (83.2% vs 76.1%, OR: 0.59:0.38-0.93; P = .02) and 14-day quadruple treatments over 7-day treatments (91.2% vs 81.5%, OR; 95% CI: 0.42:0.24-0.73; P = .002), although the differences were significant only in the per-protocol analysis. The meta-regression did not find any particular characteristics of the studies to be associated with excellent cure rates. Second-line Helicobacter pylori treatments achieving>90% cure rates are extremely heterogeneous. Quadruple therapy and 14-day treatments seem better than triple therapies and 7-day ones. No single characteristic of the treatments was related to excellent cure rates. Future approaches suitable for infectious diseases-thus considering antibiotic resistances-are needed to design rescue treatments that consistently achieve excellent cure rates. © 2018 John Wiley & Sons Ltd.
Genomic prediction based on data from three layer lines using non-linear regression models.
Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L
2014-11-06
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. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional
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...
Mathur, Praveen; Sharma, Sarita; Soni, Bhupendra
2010-01-01
In the present work, an attempt is made to formulate multiple regression equations using all possible regressions method for groundwater quality assessment of Ajmer-Pushkar railway line region in pre- and post-monsoon seasons. Correlation studies revealed the existence of linear relationships (r 0.7) for electrical conductivity (EC), total hardness (TH) and total dissolved solids (TDS) with other water quality parameters. The highest correlation was found between EC and TDS (r = 0.973). EC showed highly significant positive correlation with Na, K, Cl, TDS and total solids (TS). TH showed highest correlation with Ca and Mg. TDS showed significant correlation with Na, K, SO4, PO4 and Cl. The study indicated that most of the contamination present was water soluble or ionic in nature. Mg was present as MgCl2; K mainly as KCl and K2SO4, and Na was present as the salts of Cl, SO4 and PO4. On the other hand, F and NO3 showed no significant correlations. The r2 values and F values (at 95% confidence limit, alpha = 0.05) for the modelled equations indicated high degree of linearity among independent and dependent variables. Also the error % between calculated and experimental values was contained within +/- 15% limit.
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...... 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...
International Nuclear Information System (INIS)
Seo, In Yong; Ha, Bok Nam; Lee, Sung Woo; Shin, Chang Hoon; Kim, Seong Jun
2010-01-01
In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method
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
International Nuclear Information System (INIS)
Yang, Jianhong; Yi, Cancan; Xu, Jinwu; Ma, Xianghong
2015-01-01
A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine. - Highlights: • Both training and testing samples are considered for analytical lines selection. • The analytical lines are auto-selected based on the built-in characteristics of spectral lines. • The new method can achieve better prediction accuracy and modeling robustness. • Model predictions are given with confidence interval of probabilistic distribution
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
Multimode electromagnetically induced transparency on a single atomic line
International Nuclear Information System (INIS)
Campbell, Geoff; Ordog, Anna; Lvovsky, A I
2009-01-01
We experimentally investigate electromagnetically induced transparency (EIT) created on an inhomogeneously broadened 5S 1/2 -5P 1/2 transition in rubidium vapor using a control field of a complex temporal shape. A comb-shaped transparency spectrum enhances the delay-bandwidth product and the light storage capacity for a matched probe pulse by a factor of about 50 compared to a single EIT line (Yavuz 2007 Phys. Rev. A 75 031801). If the temporal mode of the control field is slowly changed while the probe is propagating through the EIT medium, the probe will adiabatically follow, providing a means to perform frequency conversion and optical routing.
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.
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.
Maggin, Daniel M.; Swaminathan, Hariharan; Rogers, Helen J.; O'Keeffe, Breda V.; Sugai, George; Horner, Robert H.
2011-01-01
A new method for deriving effect sizes from single-case designs is proposed. The strategy is applicable to small-sample time-series data with autoregressive errors. The method uses Generalized Least Squares (GLS) to model the autocorrelation of the data and estimate regression parameters to produce an effect size that represents the magnitude of…
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.
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
Toeless pulse shaping with a single delay-line network
International Nuclear Information System (INIS)
Tauhata, L.; Binns, D.C.
1976-04-01
New unipolar delay-line clippers producing negligible cancellation remnant have been developed. Near perfect clipping is achieved using a combination of several types of coaxial cable tranformers working as a phase inverter, a new pulse adder, or an impedance transformer. Only passive elements are used in the bridge network. The construction is simple and the performance is extremely stable and wide in dynamic range and frequency band width. Completely symmetrical bipolar pulses are also easily obtained using this technique
On-line single server dial-a-ride problems
Feuerstein, E.; Stougie, L.
1998-01-01
In this paper results on the dial-a-ride problem with a single server are presented. Requests for rides consist of two points in a metric space, a source and a destination. A ride has to be made by the server from the source to the destination. The server travels at unit speed in the metric space
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.
Granato, Gregory E.
2006-01-01
The Kendall-Theil Robust Line software (KTRLine-version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables. The KTRLine software was developed by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, for use in stochastic data modeling with local, regional, and national hydrologic data sets to develop planning-level estimates of potential effects of highway runoff on the quality of receiving waters. The Kendall-Theil robust line was selected because this robust nonparametric method is resistant to the effects of outliers and nonnormality in residuals that commonly characterize hydrologic data sets. The slope of the line is calculated as the median of all possible pairwise slopes between points. The intercept is calculated so that the line will run through the median of input data. A single-line model or a multisegment model may be specified. The program was developed to provide regression equations with an error component for stochastic data generation because nonparametric multisegment regression tools are not available with the software that is commonly used to develop regression models. The Kendall-Theil robust line is a median line and, therefore, may underestimate total mass, volume, or loads unless the error component or a bias correction factor is incorporated into the estimate. Regression statistics such as the median error, the median absolute deviation, the prediction error sum of squares, the root mean square error, the confidence interval for the slope, and the bias correction factor for median estimates are calculated by use of nonparametric methods. These statistics, however, may be used to formulate estimates of mass, volume, or total loads. The program is used to read a two- or three-column tab-delimited input file with variable names in the first row and
SCREAMER: a single-line pulsed-power design tool
International Nuclear Information System (INIS)
Kiefer, M.L.; Widner, M.M.
1985-01-01
SCREAMER is a special purpose circuit code developed as a design tool for single module accelerators. It is fast, accurate, flexible, and user-friendly. Its development was motivated by the excessive costs and long turn-around times incurred when using the SCEPTRE circuit analysis code to perform simulations of circuits with large numbers of nodes and with nonlinear components. Comparable simulations between SCREAMER running on a VAX 11/780 and SCEPTRE running on a CRAY-1S show that turn-around times and costs can be two orders of magnitude lower when using SCREAMER
SCREAMER - A single-line pulsed-power design tool
International Nuclear Information System (INIS)
Kiefer, M.L.; Widner, M.M.
1985-01-01
SCREAMER is a special purpose circuit code developed as a design tool for single module accelerators. it is fast, accurate, flexible, and user-friendly. Its development was motivated by the excessive costs and long turn-around times incurred when using the SCEPTRE circuit analysis code to perform simulations of circuits with large numbers of modes and with nonlinear components. Comparable simulations between SCREAMER running on a VAX 11/780 and SCEPTRE running on a CRAY-1S show that turn-around times and costs can be two orders of magnitude lower when using SCREAMER
Advanced statistics: linear regression, part I: simple linear regression.
Marill, Keith A
2004-01-01
Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.
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.
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)
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.
Zero-phonon-line emission of single molecules for applications in quantum information processing
Kiraz, Alper; Ehrl, M.; Mustecaplioglu, O. E.; Hellerer, T.; Brauchle, C.; Zumbusch, A.
2005-07-01
A single photon source which generates transform limited single photons is highly desirable for applications in quantum optics. Transform limited emission guarantees the indistinguishability of the emitted single photons. This, in turn brings groundbreaking applications in linear optics quantum information processing within an experimental reach. Recently, self-assembled InAs quantum dots and trapped atoms have successfully been demonstrated as such sources for highly indistinguishable single photons. Here, we demonstrate that nearly transform limited zero-phonon-line (ZPL) emission from single molecules can be obtained by using vibronic excitation. Furthermore we report the results of coincidence detection experiments at the output of a Michelson-type interferometer. These experiments reveal Hong-Ou-Mandel correlations as a proof of the indistinguishability of the single photons emitted consecutively from a single molecule. Therefore, single molecules constitute an attractive alternative to single InAs quantum dots and trapped atoms for applications in linear optics quantum information processing. Experiments were performed with a home-built confocal microscope keeping the sample in a superfluid liquid Helium bath at 1.4K. We investigated terrylenediimide (TDI) molecules highly diluted in hexadecane (Shpol'skii matrix). A continuous wave single mode dye laser was used for excitation of vibronic transitions of individual molecules. From the integral fluorescence, the ZPL of single molecules was selected with a spectrally narrow interference filter. The ZPL emission was then sent to a scanning Fabry-Perot interferometer for linewidth measurements or a Michelson-type interferometer for coincidence detection.
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.
On-line scheduling on a single machine : maximizing the number of early jobs
Hoogeveen, J.A.; Potts, C.N.; Woeginger, G.J.
2000-01-01
This note deals with the scheduling problem of maximizing the number of early jobs on a single machine. We investigate the on-line version of this problem in the Preemption-Restart model. This means that jobs may be preempted, but preempting results in all the work done on this job so far being
Determination of the mass-ratio distribution, I: single-lined spectroscopic binary stars
Hogeveen, S.J.
1992-01-01
For single-lined spectroscopic binary stars (sbi), the mass ratio q = Msec=Mprim is calculated from the mass function f(m), which is determined from observations. For statistical investigations of the mass-ratio distribution, the term sin^3 i, that remains in the cubic equation from which q is
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.
Santori, G; Fontana, I; Bertocchi, M; Gasloli, G; Magoni Rossi, A; Tagliamacco, A; Barocci, S; Nocera, A; Valente, U
2010-05-01
A useful approach to reduce the number of discarded marginal kidneys and to increase the nephron mass is double kidney transplantation (DKT). In this study, we retrospectively evaluated the potential predictors for patient and graft survival in a single-center series of 59 DKT procedures performed between April 21, 1999, and September 21, 2008. The kidney recipients of mean age 63.27 +/- 5.17 years included 16 women (27%) and 43 men (73%). The donors of mean age 69.54 +/- 7.48 years included 32 women (54%) and 27 men (46%). The mean posttransplant dialysis time was 2.37 +/- 3.61 days. The mean hospitalization was 20.12 +/- 13.65 days. Average serum creatinine (SCr) at discharge was 1.5 +/- 0.59 mg/dL. In view of the limited numbers of recipient deaths (n = 4) and graft losses (n = 8) that occurred in our series, the proportional hazards assumption for each Cox regression model with P DKT (P = .043), and SCr 6 months post-DKT (P = .017). All significant univariate models for graft survival passed the Schoenfeld test. A final multivariate model retained SCr at 6 months (beta = 1.746, P = .042) and donor SCr (beta = .767, P = .090). In our analysis, SCr at 6 months seemed to emerge from both univariate and multivariate Cox models as a potential predictor of graft survival among DKT. Multicenter studies with larger recipient populations and more graft losses should be performed to confirm our findings. Copyright (c) 2010 Elsevier Inc. All rights reserved.
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....
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
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...... types of renewable energy sources (RES) and energy storage systems (ESS). Specifically, the recharging process of secondary battery, the most prominent ESS, should be done in a specific manner to preserve its life-time, microgrid line voltage must be kept within the bounds and the energy offered by RES...
Single-shot dual-wavelength in-line and off-axis hybrid digital holography
Wang, Fengpeng; Wang, Dayong; Rong, Lu; Wang, Yunxin; Zhao, Jie
2018-02-01
We propose an in-line and off-axis hybrid holographic real-time imaging technique. The in-line and off-axis digital holograms are generated simultaneously by two lasers with different wavelengths, and they are recorded using a color camera with a single shot. The reconstruction is carried using an iterative algorithm in which the initial input is designed to include the intensity of the in-line hologram and the approximate phase distributions obtained from the off-axis hologram. In this way, the complex field in the object plane and the output by the iterative procedure can produce higher quality amplitude and phase images compared to traditional iterative phase retrieval. The performance of the technique has been demonstrated by acquiring the amplitude and phase images of a green lacewing's wing and a living moon jellyfish.
Single-cell printing to form three-dimensional lines of olfactory ensheathing cells
International Nuclear Information System (INIS)
Othon, Christina M; Ringeisen, Bradley R; Wu Xingjia; Anders, Juanita J
2008-01-01
Biological laser printing (BioLP(TM)) is a unique tool capable of printing high resolution two- and three-dimensional patterns of living mammalian cells, with greater than 95% viability. These results have been extended to primary cultured olfactory ensheathing cells (OECs), harvested from adult Sprague-Dawley rats. OECs have been found to provide stimulating environments for neurite outgrowth in spinal cord injury models. BioLP is unique in that small load volumes (∼μLs) are required to achieve printing, enabling low numbers of OECs to be harvested, concentrated and printed. BioLP was used to form several 8 mm lines of OECs throughout a multilayer hydrogel scaffold. The line width was as low as 20 μm, with most lines comprising aligned single cells. Fluorescent confocal microscopy was used to determine the functionality of the printed OECs, to monitor interactions between printed OECs, and to determine the extent of cell migration throughout the 3D scaffold. High-resolution printing of low cell count, harvested OECs is an important advancement for in vitro study of cell interactions and functionality. In addition, these cell-printed scaffolds may provide an alternative for spinal cord repair studies, as the single-cell patterns formed here are on relevant size scales for neurite outgrowth
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.)
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
Spady, Richard; Stouli, Sami
2012-01-01
We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...
Sliding three-phase contact line of printed droplets for single-crystal arrays
International Nuclear Information System (INIS)
Kuang, Minxuan; Wu, Lei; Li, Yifan; Gao, Meng; Zhang, Xingye; Jiang, Lei; Song, Yanlin
2016-01-01
Controlling the behaviours of printed droplets is an essential requirement for inkjet printing of delicate three-dimensional (3D) structures or high-resolution patterns. In this work, molecular deposition and crystallization are regulated by manipulating the three-phase contact line (TCL) behaviour of the printed droplets. The results show that oriented single-crystal arrays are fabricated based on the continuously sliding TCL. Owing to the sliding of the TCL on the substrate, the outward capillary flow within the evaporating droplet is suppressed and the molecules are brought to the centre of the droplet, resulting in the formation of a single crystal. This work provides a facile strategy for controlling the structures of printed units by manipulating the TCL of printed droplets, which is significant for realizing high-resolution patterns and delicate 3D structures. (paper)
Common y-intercept and single compound regressions of gas-particle partitioning data vs 1/T
Pankow, James F.
Confidence intervals are placed around the log Kp vs 1/ T correlation equations obtained using simple linear regressions (SLR) with the gas-particle partitioning data set of Yamasaki et al. [(1982) Env. Sci. Technol.16, 189-194]. The compounds and groups of compounds studied include the polycylic aromatic hydrocarbons phenanthrene + anthracene, me-phenanthrene + me-anthracene, fluoranthene, pyrene, benzo[ a]fluorene + benzo[ b]fluorene, chrysene + benz[ a]anthracene + triphenylene, benzo[ b]fluoranthene + benzo[ k]fluoranthene, and benzo[ a]pyrene + benzo[ e]pyrene (note: me = methyl). For any given compound, at equilibrium, the partition coefficient Kp equals ( F/ TSP)/ A where F is the particulate-matter associated concentration (ng m -3), A is the gas-phase concentration (ng m -3), and TSP is the concentration of particulate matter (μg m -3). At temperatures more than 10°C from the mean sampling temperature of 17°C, the confidence intervals are quite wide. Since theory predicts that similar compounds sorbing on the same particulate matter should possess very similar y-intercepts, the data set was also fitted using a special common y-intercept regression (CYIR). For most of the compounds, the CYIR equations fell inside of the SLR 95% confidence intervals. The CYIR y-intercept value is -18.48, and is reasonably close to the type of value that can be predicted for PAH compounds. The set of CYIR regression equations is probably more reliable than the set of SLR equations. For example, the CYIR-derived desorption enthalpies are much more highly correlated with vaporization enthalpies than are the SLR-derived desorption enthalpies. It is recommended that the CYIR approach be considered whenever analysing temperature-dependent gas-particle partitioning data.
Single corn kernel wide-line NMR oil analysis for breeding purpose
Energy Technology Data Exchange (ETDEWEB)
Wilmers, M C.C.; Rettori, C; Vargas, H; Barberis, G E [Universidade Estadual de Campinas (Brazil). Inst. de Fisica; da Silva, W J [Universidade Estadual de Campinas (Brazil). Inst. de Biologia
1978-12-01
The Wide-Line NMR technique was used to determine the oil content in single corn seeds. Using distinct radio frequency (RF) power, a systematic work was done in kernels with about 10% of moisture, and also in artificially dried seeds with approximated 5% of moisture. For nondried seeds NMR spectra showed clearly the presence of three resonances with different RF saturation factor. For dried seeds, the oil concentration determined by NMR was highly correlated (r = 0,997) with that determined by a gravimetric method. The highest discrepancy between the two methods was found to be about 1,3%. When relative measurements are required as in the case of single kernel for recurrent selection program, precision in the individual selected kernel will be about 2,5%. Applying this technique, a first cycle of recurrent selection using S/sub 1/ lines for low and high oil content was performed in an open pollinated variety. Gain from selection was 12.0 and 14.1% in the populations for high and low oil contents, respectively.
A design of a high speed dual spectrometer by single line scan camera
Palawong, Kunakorn; Meemon, Panomsak
2018-03-01
A spectrometer that can capture two orthogonal polarization components of s light beam is demanded for polarization sensitive imaging system. Here, we describe the design and implementation of a high speed spectrometer for simultaneous capturing of two orthogonal polarization components, i.e. vertical and horizontal components, of light beam. The design consists of a polarization beam splitter, two polarization-maintain optical fibers, two collimators, a single line-scan camera, a focusing lens, and a reflection blaze grating. The alignment of two beam paths was designed to be symmetrically incident on the blaze side and reverse blaze side of reflection grating, respectively. The two diffracted beams were passed through the same focusing lens and focused on the single line-scan sensors of a CMOS camera. The two spectra of orthogonal polarization were imaged on 1000 pixels per spectrum. With the proposed setup, the amplitude and shape of the two detected spectra can be controlled by rotating the collimators. The technique for optical alignment of spectrometer will be presented and discussed. The two orthogonal polarization spectra can be simultaneously captured at a speed of 70,000 spectra per second. The high speed dual spectrometer can simultaneously detected two orthogonal polarizations, which is an important component for the development of polarization-sensitive optical coherence tomography. The performance of the spectrometer have been measured and analyzed.
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)
DEFF Research Database (Denmark)
Puig Arnavat, Maria; López-Villada, Jesús; Bruno, Joan Carles
2010-01-01
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 o...... chillers. The characteristic parameters for these chillers are given and can be incorporated as a chiller module in thermal modelling and simulation packages....
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
Energy Technology Data Exchange (ETDEWEB)
Sun, Weiyuan; Liu, Zhiguo [The Key Laboratory of Beam Technology and Materials Modification of the Ministry of Education, Beijing Normal University, Beijing 100875 (China); College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875 (China); Beijing Radiation Center, Beijing 100875 (China); Sun, Tianxi, E-mail: stx@bnu.edu.cn [The Key Laboratory of Beam Technology and Materials Modification of the Ministry of Education, Beijing Normal University, Beijing 100875 (China); College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875 (China); Beijing Radiation Center, Beijing 100875 (China); Peng, Song [The Key Laboratory of Beam Technology and Materials Modification of the Ministry of Education, Beijing Normal University, Beijing 100875 (China); College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875 (China); Beijing Radiation Center, Beijing 100875 (China); Ma, Yongzhong [Center for Disease Control and Prevention of Beijing, Beijing 100013 (China); Ding, Xunliang [The Key Laboratory of Beam Technology and Materials Modification of the Ministry of Education, Beijing Normal University, Beijing 100875 (China); College of Nuclear Science and Technology, Beijing Normal University, Beijing 100875 (China); Beijing Radiation Center, Beijing 100875 (China)
2014-05-11
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.
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.))
Discrete event model-based simulation for train movement on a single-line railway
International Nuclear Information System (INIS)
Xu Xiao-Ming; Li Ke-Ping; Yang Li-Xing
2014-01-01
The aim of this paper is to present a discrete event model-based approach to simulate train movement with the considered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption. (general)
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.
Energy Technology Data Exchange (ETDEWEB)
Saloman, Edward B. [Dakota Consulting, Inc., 1110 Bonifant Street, Suite 310, Silver Spring, MD 20910 (United States); Kramida, Alexander [National Institute of Standards and Technology, Gaithersburg, MD 20899 (United States)
2017-08-01
The energy levels, observed spectral lines, and transition probabilities of singly ionized vanadium, V ii, have been compiled. The experimentally derived energy levels belong to the configurations 3 d {sup 4}, 3 d {sup 3} ns ( n = 4, 5, 6), 3 d {sup 3} np , and 3 d {sup 3} nd ( n = 4, 5), 3 d {sup 3}4 f , 3 d {sup 2}4 s {sup 2}, and 3 d {sup 2}4 s 4 p . Also included are values for some forbidden lines that may be of interest to the astrophysical community. Experimental Landé g -factors and leading percentages for the levels are included when available, as well as Ritz wavelengths calculated from the energy levels. Wavelengths and transition probabilities are reported for 3568 and 1896 transitions, respectively. From the list of observed wavelengths, 407 energy levels are determined. The observed intensities, normalized to a common scale, are provided. From the newly optimized energy levels, a revised value for the ionization energy is derived, 118,030(60) cm{sup −1}, corresponding to 14.634(7) eV. This is 130 cm{sup −1} higher than the previously recommended value from Iglesias et al.
FogBank: a single cell segmentation across multiple cell lines and image modalities.
Chalfoun, Joe; Majurski, Michael; Dima, Alden; Stuelten, Christina; Peskin, Adele; Brady, Mary
2014-12-30
Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting, identification and measurement of individual cells. Over-segmentation of single cells continues to be a major problem for methods based on morphological watershed due to the high level of noise in microscopy cell images. There is a need for a new segmentation method that is robust over a wide variety of biological images and can accurately separate individual cells even in challenging datasets such as confluent sheets or colonies. We present a new automated segmentation method called FogBank that accurately separates cells when confluent and touching each other. This technique is successfully applied to phase contrast, bright field, fluorescence microscopy and binary images. The method is based on morphological watershed principles with two new features to improve accuracy and minimize over-segmentation. First, FogBank uses histogram binning to quantize pixel intensities which minimizes the image noise that causes over-segmentation. Second, FogBank uses a geodesic distance mask derived from raw images to detect the shapes of individual cells, in contrast to the more linear cell edges that other watershed-like algorithms produce. We evaluated the segmentation accuracy against manually segmented datasets using two metrics. FogBank achieved segmentation accuracy on the order of 0.75 (1 being a perfect match). We compared our method with other available segmentation techniques in term of achieved performance over the reference data sets. FogBank outperformed all related algorithms. The accuracy has also been visually verified on data sets with 14 cell lines across 3 imaging modalities leading to 876 segmentation evaluation images. FogBank produces single cell segmentation from confluent cell
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.
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.
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.
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.
Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.
2017-01-01
Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...
Energy Technology Data Exchange (ETDEWEB)
Potthoff, H.H. (Technische Univ. Braunschweig (Germany, F.R.). Inst. fuer Metallphysik und Nukleare Festkoerperphysik)
1983-05-16
Slip line development on very thin flat single crystals of neutron-irradiated Cu (thickness down to only 15 to 20 ..mu..m, orientation for single glide, yield region, room temperature) is recorded by high-speed cinematography during tensile deformation. In such very thin crystals glide dislocations on the slip plane must be arranged in a rather simple way. Drops in tensile load occuring during initiation of single slip lines at the Lueders band front indicate that in the beginning of a slip line development dislocation groups traverse the whole glide plane in very short times. Evaluating the data measured for the slip line growth v/sub s/ >= 10 cm/s is found for screw dislocations and v/sub e/ >= v/sub s/ for edge dislocations. For later stages on thin crystals and for all stages on thick crystals (>= several 100 ..mu..m) slip line development is much slower and slip line show many cross slip events which then appear to control the mean velocity of the dislocations.
International Nuclear Information System (INIS)
Potthoff, H.H.
1983-01-01
Slip line development on very thin flat single crystals of neutron-irradiated Cu (thickness down to only 15 to 20 μm, orientation for single glide, yield region, room temperature) is recorded by high-speed cinematography during tensile deformation. In such very thin crystals glide dislocations on the slip plane must be arranged in a rather simple way. Drops in tensile load occuring during initiation of single slip lines at the Lueders band front indicate that in the beginning of a slip line development dislocation groups traverse the whole glide plane in very short times. Evaluating the data measured for the slip line growth v/sub s/ >= 10 cm/s is found for screw dislocations and v/sub e/ >= v/sub s/ for edge dislocations. For later stages on thin crystals and for all stages on thick crystals (>= several 100 μm) slip line development is much slower and slip line show many cross slip events which then appear to control the mean velocity of the dislocations. (author)
Widespread Amazon forest tree mortality from a single cross-basin squall line event
Negrón-Juárez, Robinson I.; Chambers, Jeffrey Q.; Guimaraes, Giuliano; Zeng, Hongcheng; Raupp, Carlos F. M.; Marra, Daniel M.; Ribeiro, Gabriel H. P. M.; Saatchi, Sassan S.; Nelson, Bruce W.; Higuchi, Niro
2010-08-01
Climate change is expected to increase the intensity of extreme precipitation events in Amazonia that in turn might produce more forest blowdowns associated with convective storms. Yet quantitative tree mortality associated with convective storms has never been reported across Amazonia, representing an important additional source of carbon to the atmosphere. Here we demonstrate that a single squall line (aligned cluster of convective storm cells) propagating across Amazonia in January, 2005, caused widespread forest tree mortality and may have contributed to the elevated mortality observed that year. Forest plot data demonstrated that the same year represented the second highest mortality rate over a 15-year annual monitoring interval. Over the Manaus region, disturbed forest patches generated by the squall followed a power-law distribution (scaling exponent α = 1.48) and produced a mortality of 0.3-0.5 million trees, equivalent to 30% of the observed annual deforestation reported in 2005 over the same area. Basin-wide, potential tree mortality from this one event was estimated at 542 ± 121 million trees, equivalent to 23% of the mean annual biomass accumulation estimated for these forests. Our results highlight the vulnerability of Amazon trees to wind-driven mortality associated with convective storms. Storm intensity is expected to increase with a warming climate, which would result in additional tree mortality and carbon release to the atmosphere, with the potential to further warm the climate system.
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.
MAPPIX: A software package for off-line micro-pixe single particle aerosol analysis
International Nuclear Information System (INIS)
Ceccato, D.
2009-01-01
In the framework of a multiannual experiment performed at Baia Terra Nova, Antarctica, size-segregated aerosol samples were collected by using a 12-stage SDI impactor (Hillamo design). Approximately 2800 particles, belonging to the first four supermicrometric SDI stages - 8.39, 4.08, 2.68, 1.66 μm dynamic aerosol diameter cuts - were analyzed at the INFN-LNL micro-PIXE facility, a three lens Oxford Microprobe (OM) product, installed in the early nineties. Four regions on each of the 12 sub-samples were measured; 60 aerosol particles were detected on average in each of the analyzed regions. The off-line single aerosol particle (SAP) analysis of such big amount of data required software that is able to rapidly handle the acquired data, with a simple and fast area selection procedure; the subsequent automated PIXE spectra analysis with a specialized code was also needed. The MAPPIX 2.0 software was designed to make easier and faster the user jobs during the SAP analysis. The package is composed of two separate routines: the first one is devoted to data format conversion (OM-LMF file format to MAPPIX format), while the second one is devoted to micro-PIXE maps graphical presentation and aerosol particle selection procedure. The MAPPIX data format and software features will be discussed; a short report of the speed performances will be presented.
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)
Directory of Open Access Journals (Sweden)
Mohamed ZELLAGUI
2012-08-01
Full Text Available This paper presents and compares the impact of SSSC on measured impedance for single phase to ground fault condition. The presence of Static Synchronous SSSC on a transmission line has a great influence on the ZRelay in distance protection. The protection of the high voltage 220 kV single circuit transmission line in eastern Algerian electrical transmission networks is affected in the case with resistance fault RF. The paper investigate the effect of Static Synchronous Series Compensator (SSSC on the measured impedance (Relay taking into account the distance fault point (n and fault resistance (RF. The resultants simulation is performed in MATLAB software environment.
Reconfigurable Transmission Line for a Series-Fed Ku-Band Phased Array Using a Single Feed
Host, Nicholas K.; Chen, Chi-Chih; Volakis, John L.; Miranda. Felix, A.
2013-01-01
The paper presents a novel approach to realize a lowcost phased array using a simple feeding mechanism. Specifically, a single coplanar stripline (CPS) transmission line is used to feed the antenna array elements. By controlling the CPS's dielectric properties using a movable dielectric plunger, scanning is achieved. Due to its simplicity, single feed, and no phase shifters, this approach leads to a dramatic reduction in cost which does not scale for larger arrays.
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.
Berk, Alexander
2013-03-01
Exact expansions for Voigt line-shape total, line-tail and spectral bin equivalent widths and for Voigt finite spectral bin single-line transmittances have been derived in terms of optical depth dependent exponentially-scaled modified Bessel functions of integer order and optical depth independent Fourier integral coefficients. The series are convergent for the full range of Voigt line-shapes, from pure Doppler to pure Lorentzian. In the Lorentz limit, the expansion reduces to the Ladenburg and Reiche function for the total equivalent width. Analytic expressions are derived for the first 8 Fourier coefficients for pure Lorentzian lines, for pure Doppler lines and for Voigt lines with at most moderate Doppler dependence. A strong-line limit sum rule on the Fourier coefficients is enforced to define an additional Fourier coefficient and to optimize convergence of the truncated expansion. The moderate Doppler dependence scenario is applicable to and has been implemented in the MODTRAN5 atmospheric band model radiative transfer software. Finite-bin transmittances computed with the truncated expansions reduce transmittance residuals compared to the former Rodgers-Williams equivalent width based approach by ∼2 orders of magnitude.
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.
SINGLE-LINED SPECTROSCOPIC BINARY STAR CANDIDATES IN THE RAVE SURVEY
International Nuclear Information System (INIS)
Matijevic, G.; Zwitter, T.; Bienayme, O.; Siebert, A.; Watson, F. G.; Bland-Hawthorn, J.; Parker, Q. A.; Freeman, K. C.; Gilmore, G.; Grebel, E. K.; Helmi, A.; Munari, U.; Siviero, A.; Navarro, J. F.; Reid, W.; Seabroke, G. M.; Steinmetz, M.; Williams, M.; Wyse, R. F. G.
2011-01-01
Repeated spectroscopic observations of stars in the RAdial Velocity Experiment (RAVE) database are used to identify and examine single-lined binary (SB1) candidates. The RAVE latest internal database (VDR3) includes radial velocities, atmospheric parameters, and other parameters for approximately a quarter of a million different stars with slightly less than 300,000 observations. In the sample of ∼20,000 stars observed more than once, 1333 stars with variable radial velocities were identified. Most of them are believed to be SB1 candidates. The fraction of SB1 candidates among stars with several observations is between 10% and 15% which is the lower limit for binarity among RAVE stars. Due to the distribution of time spans between the re-observation that is biased toward relatively short timescales (days to weeks), the periods of the identified SB1 candidates are most likely in the same range. Because of the RAVE's narrow magnitude range most of the dwarf candidates belong to the thin Galactic disk while the giants are part of the thick disk with distances extending to up to a few kpc. The comparison of the list of SB1 candidates to the VSX catalog of variable stars yielded several pulsating variables among the giant population with radial velocity variations of up to few tens of km s -1 . There are 26 matches between the catalog of spectroscopic binary orbits (S B 9 ) and the whole RAVE sample for which the given periastron time and the time of RAVE observation were close enough to yield a reliable comparison. RAVE measurements of radial velocities of known spectroscopic binaries are consistent with their published radial velocity curves.
Wonders, A.H.; Housmans, T.H.M.; Rosca, V.; Koper, M.T.M.
2006-01-01
We present the construction and some first applications of an On-line electrochemical mass spectrometry system for detecting volatile products formed during electrochemical reactions at a single-crystal electrode in hanging meniscus configuration. The system is based on a small inlet tip made of
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.
Srinivas, Nuggehally R; Syed, Muzeeb
2016-03-01
Linezolid, a oxazolidinone, was the first in class to be approved for the treatment of bacterial infections arising from both susceptible and resistant strains of Gram-positive bacteria. Since overt exposure of linezolid may precipitate serious toxicity issues, therapeutic drug monitoring (TDM) may be required in certain situations, especially in patients who are prescribed other co-medications. Using appropriate oral pharmacokinetic data (single dose and steady state) for linezolid, both maximum plasma drug concentration (Cmax) versus area under the plasma concentration-time curve (AUC) and minimum plasma drug concentration (Cmin) versus AUC relationship was established by linear regression models. The predictions of the AUC values were performed using published mean/median Cmax or Cmin data and appropriate regression lines. The quotient of observed and predicted values rendered fold difference calculation. The mean absolute error (MAE), root mean square error (RMSE), correlation coefficient (r), and the goodness of the AUC fold prediction were used to evaluate the two models. The Cmax versus AUC and trough plasma concentration (Ctrough) versus AUC models displayed excellent correlation, with r values of >0.9760. However, linezolid AUC values were predicted to be within the narrower boundary of 0.76 to 1.5-fold by a higher percentage by the Ctrough (78.3%) versus Cmax model (48.2%). The Ctrough model showed superior correlation of predicted versus observed values and RMSE (r = 0.9031; 28.54%, respectively) compared with the Cmax model (r = 0.5824; 61.34%, respectively). A single time point strategy of using Ctrough level is possible as a prospective tool to measure the AUC of linezolid in the patient population.
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.
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.
Matson, Johnny L.; Kozlowski, Alison M.
2010-01-01
Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…
Yu, Chung-Chih; Chen, Yu-Ray; Lin, James Cheng-Yi
2017-10-01
Coincidence of facial and dental midlines is one of the important goals in orthognathic-orthodontic treatment to achieve optimum facial aesthetics and good occlusal functions. Tools assisting diagnosis of facial midline are usually ruler or dental floss. These tools are usually hand held and hinder the global sight required in facial evaluation. Line laser device projects a steady narrow laser line and is commonly used in construction and carpentry to replace traditional chalk line tool. The authors take the advantages of line laser and incorporate it into facial evaluation in the authors' practice of single-splint orthognathic surgery.During June 2013 to May 2015, the authors used line laser device to evaluate facial and dental midlines in 28 patients of facial asymmetry requiring orthognathic surgery during consultation in office and intraoperative evaluation. The details of integrating this device to practice are described. All the patients showed improved facial symmetry and coincidence of facial and dental midlines after operation. Postoperative orthodontics were finished smoothly.Line laser is available from general utility stores and is safe to use according to laser safety regulation. From the authors' experiences, it is burden free to apply in facial and dental midlines evaluation and improves the practice.
International Nuclear Information System (INIS)
Hamad, Syed; Tewari, Surya P; Podagatlapalli, G Krishna; Rao, S Venugopal
2013-01-01
A comprehensive study comprising fabrication of copper nanoparticles (NPs) using picosecond (ps) multiple/single line ablation in various solvents such as acetone, dichloromethane (DCM), acetonitrile (ACN) and chloroform followed by optical, nonlinear optical (NLO), and surface enhanced Raman spectroscopy (SERS) characterization was performed. The influence of surrounding liquid media and the writing conditions resulted in fabrication of Cu NPs in acetone, CuCl NPs in DCM, CuO NPs in ACN and CuCl 2 NPs in chloroform. Prepared colloids were characterized through transmission electron microscopy, energy dispersive x-ray spectra, selected area electron diffraction and UV-visible absorption spectra. A detailed investigation of the surface enhanced Raman scattering (SERS) activity and the ps NLO properties of the colloids prepared through multiple/single line ablation techniques revealed that the best performance was achieved by Cu NPs for SERS applications and CuCl 2 NPs for NLO applications. (paper)
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...
Schwantes-An, Tae-Hwi; Sung, Heejong; Sabourin, Jeremy A; Justice, Cristina M; Sorant, Alexa J M; Wilson, Alexander F
2016-01-01
In this study, the effects of (a) the minor allele frequency of the single nucleotide variant (SNV), (b) the degree of departure from normality of the trait, and (c) the position of the SNVs on type I error rates were investigated in the Genetic Analysis Workshop (GAW) 19 whole exome sequence data. To test the distribution of the type I error rate, 5 simulated traits were considered: standard normal and gamma distributed traits; 2 transformed versions of the gamma trait (log 10 and rank-based inverse normal transformations); and trait Q1 provided by GAW 19. Each trait was tested with 313,340 SNVs. Tests of association were performed with simple linear regression and average type I error rates were determined for minor allele frequency classes. Rare SNVs (minor allele frequency < 0.05) showed inflated type I error rates for non-normally distributed traits that increased as the minor allele frequency decreased. The inflation of average type I error rates increased as the significance threshold decreased. Normally distributed traits did not show inflated type I error rates with respect to the minor allele frequency for rare SNVs. There was no consistent effect of transformation on the uniformity of the distribution of the location of SNVs with a type I error.
Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo
2011-03-04
Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.
Kimbacher, Christine; Paar, Christian; Freystetter, Andrea; Berg, Joerg
2018-05-01
Genotyping for clinically important single nucleotide polymorphisms (SNPs) is performed by many clinical routine laboratories. To support testing, quality controls and reference materials are needed. Those may be derived from residual patient samples, left over samples of external quality assurance schemes, plasmid DNA or DNA from cell lines. DNAs from cell lines are commutable and available in large amounts. DNA from 38 cell lines were examined for suitability as controls in 11 SNP assays that are frequently used in a clinical routine laboratory: FV (1691G>A), FII (20210G>A), PAI-1 4G/5G polymorphism, MTHFR (677C>T, 1298A>C), HFE (H63D, S65C, C282Y), APOE (E2, E3, E4), LPH (-13910C>T), UGT1A1 (*28, *36, *37), TPMT (*2, *3A, *3B, *3C), VKORC1 (-1639G>A, 1173C>T), CYP2C9 (*2, *3, *5). Genotyping was performed by real-time PCR with melting curve analysis and confirmed by bi-directional sequencing. We find an almost complete spectrum of genotypic constellations within these 38 cell lines. About 12 cell lines appear sufficient as genotypic controls for the 11 SNP assays by covering almost all of the genotypes. However, hetero- and homozygous genotypes for FII and the alleles TPMT*2, UGT1A1*37 and CYP2C9*5 were not detected in any of the cell lines. DNA from most of the examined cell lines appear suitable as quality controls for these SNP assays in the laboratory routine, as to the implementation of those assays or to prepare samples for quality assurance schemes. Our study may serve as a pilot to further characterize these cell lines to arrive at the status of reference materials.
Seber, George A F
2012-01-01
Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.
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.
Wu, Meiping; Cao, Juliang; Zhang, Kaidong; Cai, Shaokun; Yu, Ruihang
2018-01-01
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. PMID:29373535
Line-focus acoustic microscopy of Ti-6242 α/β single colony: determination of elastic constants
International Nuclear Information System (INIS)
Kim, J.-Y.; Yakovlev, V.; Rokhlin, S.I.
2002-01-01
Time-resolved line-focus acoustic microscopy is performed for determining elastic constants of Ti-6242 α/β-single colony and Ti-6 α-phase single crystal. Surface acoustic wave (SAW) velocities are obtained as a function of the propagation angle from measured time-delays of SAW signals. The propagation of surface waves in a semi-infinite half space formed by anisotropic layers inclined arbitrarily to the sample surface is studied to model a quasi-random lamellar structure of the Ti-6242 α/β-single colony. Effective elastic constants of the multilayered structure are derived and verified through the comparison with exact ones, based on which SAW velocities in non-principal planes are calculated. Effective and constituent elastic constants of the α/β-single colony and the α-phase single crystal are inversely determined from the measured and calculated SAW velocities. The α- and β-phase elastic constants from the α/β-single colony so determined are compared with those from the α-single crystal and data in the literature
Zhao, Wei; Fan, Shaojia; Guo, Hai; Gao, Bo; Sun, Jiaren; Chen, Laiguo
2016-11-01
The quantile regression (QR) method has been increasingly introduced to atmospheric environmental studies to explore the non-linear relationship between local meteorological conditions and ozone mixing ratios. In this study, we applied QR for the first time, together with multiple linear regression (MLR), to analyze the dominant meteorological parameters influencing the mean, 10th percentile, 90th percentile and 99th percentile of maximum daily 8-h average (MDA8) ozone concentrations in 2000-2015 in Hong Kong. The dominance analysis (DA) was used to assess the relative importance of meteorological variables in the regression models. Results showed that the MLR models worked better at suburban and rural sites than at urban sites, and worked better in winter than in summer. QR models performed better in summer for 99th and 90th percentiles and performed better in autumn and winter for 10th percentile. And QR models also performed better in suburban and rural areas for 10th percentile. The top 3 dominant variables associated with MDA8 ozone concentrations, changing with seasons and regions, were frequently associated with the six meteorological parameters: boundary layer height, humidity, wind direction, surface solar radiation, total cloud cover and sea level pressure. Temperature rarely became a significant variable in any season, which could partly explain the peak of monthly average ozone concentrations in October in Hong Kong. And we found the effect of solar radiation would be enhanced during extremely ozone pollution episodes (i.e., the 99th percentile). Finally, meteorological effects on MDA8 ozone had no significant changes before and after the 2010 Asian Games.
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
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.
Lopez, Salvatore; Cocco, Emiliano; Black, Jonathan; Bellone, Stefania; Bonazzoli, Elena; Predolini, Federica; Ferrari, Francesca; Schwab, Carlton L.; English, Diana P.; Ratner, Elena; Silasi, Dan-Arin; Azodi, Masoud; Schwartz, Peter E.; Terranova, Corrado; Angioli, Roberto; Santin, Alessandro D.
2015-01-01
HER2/neu gene amplification and PIK3CA driver mutations are common in uterine serous carcinoma (USC), and may represent ideal therapeutic targets against this aggressive variant of endometrial cancer. We examined the sensitivity to neratinib, taselisib and the combination of the two compounds in in vitro and in vivo experiments using PIK3CA mutated and PIK3CA-wild type HER2/neu amplified USC cell lines. Cell viability and cell cycle distribution were assessed using flow-cytometry assays. Downstream signaling was assessed by immunoblotting. Preclinical efficacy of single versus dual inhibition was evaluated in vivo using two USC-xenografts. We found both single agent neratinib and taselisib to be active but only transiently effective in controlling the in vivo growth of USC xenografts harboring HER2/neu gene amplification with or without oncogenic PIK3CA mutations. In contrast, the combination of the two inhibitors caused a stronger and long lasting growth inhibition in both USC xenografts when compared to single agent therapy. Combined targeting of HER2 and PIK3CA was associated with a significant and dose-dependent increase in the percentage of cells in the G0/G1 phase of the cell cycle and a dose-dependent decline in the phosphorylation of S6. Importantly, dual inhibition therapy initiated after tumor progression in single agent-treated mice was still remarkably effective at inducing tumor regression in both large PIK3CA or pan-ErbB inhibitor-resistant USC xenografts. Dual HER2/PIK3CA blockade may represent a novel therapeutic option for USC patients harboring tumors with HER2/neu gene amplification and mutated or wild type PIK3CA resistant to chemotherapy. PMID:26333383
Lopez, Salvatore; Cocco, Emiliano; Black, Jonathan; Bellone, Stefania; Bonazzoli, Elena; Predolini, Federica; Ferrari, Francesca; Schwab, Carlton L; English, Diana P; Ratner, Elena; Silasi, Dan-Arin; Azodi, Masoud; Schwartz, Peter E; Terranova, Corrado; Angioli, Roberto; Santin, Alessandro D
2015-11-01
HER2/neu gene amplification and PIK3CA driver mutations are common in uterine serous carcinoma (USC) and may represent ideal therapeutic targets against this aggressive variant of endometrial cancer. We examined the sensitivity to neratinib, taselisib, and the combination of the two compounds in in vitro and in vivo experiments using PIK3CA-mutated and PIK3CA wild-type HER2/neu-amplified USC cell lines. Cell viability and cell-cycle distribution were assessed using flow-cytometry assays. Downstream signaling was assessed by immunoblotting. Preclinical efficacy of single versus dual inhibition was evaluated in vivo using two USC xenografts. We found both single-agent neratinib and taselisib to be active but only transiently effective in controlling the in vivo growth of USC xenografts harboring HER2/neu gene amplification with or without oncogenic PIK3CA mutations. In contrast, the combination of the two inhibitors caused a stronger and long-lasting growth inhibition in both USC xenografts when compared with single-agent therapy. Combined targeting of HER2 and PIK3CA was associated with a significant and dose-dependent increase in the percentage of cells in the G0-G1 phase of the cell cycle and a dose-dependent decline in the phosphorylation of S6. Importantly, dual inhibition therapy initiated after tumor progression in single-agent-treated mice was still remarkably effective at inducing tumor regression in both large PIK3CA and pan-ErbB inhibitor-resistant USC xenografts. Dual HER2/PIK3CA blockade may represent a novel therapeutic option for USC patients harboring tumors with HER2/neu gene amplification and mutated or wild-type PIK3CA resistant to chemotherapy. ©2015 American Association for Cancer Research.
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.
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
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.
Optical properties of a single-colour centre in diamond with a green zero-phonon line
International Nuclear Information System (INIS)
Smith, Jason M; Grazioso, Fabio; Patton, Brian R; Dolan, Philip R; Markham, Matthew L; Twitchen, Daniel J
2011-01-01
We report the photoluminescence characteristics of a colour centre in diamond grown by plasma-assisted chemical vapour deposition. The colour centre emits with a sharp zero-phonon line at 2.330 eV (λ=532 nm) and a lifetime of 3.3 ns, thus offering potential for a high-speed single-photon source with green emission. It displays a vibronic emission spectrum with a Huang-Rhys parameter of 2.48 at 77 K. Hanbury-Brown and Twiss measurements reveal that the electronic level structure of the defect includes a metastable state that can be populated from the optically excited state.
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.
International Nuclear Information System (INIS)
Ding, D.Q.; Lee, L.C.; Ma, Z.W.
1991-01-01
Magnetic signatures associated with the time-dependent magnetic reconnection processes at the dayside magnetopause are studied based on two-dimensional compressible MHD simulations. In the simulations, magnetic and plasma signatures resemblant to the observed flux transfer events (FTEs) can be generated either by the magnetic bulges formed during the bursty single X line reconnection (BSXR) or by the magnetic islands (flux tubes) formed during the multiple X line reconnection (MXR). It is found that the FTE magnetic signatures are not exhibited on the magnetospheric side if the FTEs are due to the BSXR process and B m /B s ≥ 1.7, where B m and B s are the magnetic field strength in the magnetosheath and in the magnetosphere, respectively. On the other hand, the bipolar FTE signatures can be detected on both the magnetosphere and magnetosheath sides if the FTEs are caused by the MXR process and B m /B s ≤ 2.6. When B m /B s > 2.6, the bipolar FTE signatures in the magnetosphere site become too small to be detected even if magnetic islands are formed during the MXR process. Futhermore, for B m /B s > 1, the region for the detection of FTE signatures in the magnetospheric side is smaller than that in the magnetosheath side. Since at the dayside magnetopause the typical value of B m /B s is 1-3, the simulation results indicate that more FTE signatures can be detected in the magnetosheath side than in the magnetosphere. It is also found that the MXR process often generates a clear bipolar B n signature while the BSXR process tends to produce FTEs with a monopolar B n signature near the reconnection region and a highly asymmetric bipolar B n signature away from the reconnection region
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...... (n = 153) received weekly epirubicin (E) 20 mg/m2 until progression or until the cumulative dose of 1,000 mg/m2, followed by mitomycin (M) 8 mg/m2 every 4 weeks, and those in the combination chemotherapy arm (n = 150) were first given cyclophosphamide 500 mg/m2, E 60 mg/m2, and fluorouracil 500 mg/m2...... younger than 50. RESULTS: An objective response (complete [CR] or partial [PR]) was obtained in 55%, 48%, 16%, and 7% of patients treated with CEF, E, M, and MV, respectively. A response to CEF tended to last longer than a response to E (median, 12 v 10.5 months; P = .07). Treatment-related toxicity...
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.
Fourier X-ray line shape analysis of lattice defects from a single reflection
International Nuclear Information System (INIS)
Misra, N.K.; Bhanumurthy, K.
1981-01-01
A method of single reflection Fourier analysis has been described considering the fact that the rms strain (averaged over a distance) is not independent of averaging distance. Following the procedure of N.K. Misra and T.B. Ghosh (1976) and considering the initial slopes of dAsub(L)/dL against L curves, (Asub(L) is the Lsub(th) order Fourier coefficient) the effective size of the coherently diffracting domains and the rms strain in them are determined. The results of this analysis for pure Ti and Ag-3.55% Ga, Ag-15% In and Cu-12.46% Ge alloys compare fairly well with those obtained from different multiple reflections techniques. (author)
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
A GRB and Broad-lined Type Ic Supernova from a Single Central Engine
Barnes, Jennifer; Duffell, Paul C.; Liu, Yuqian; Modjaz, Maryam; Bianco, Federica B.; Kasen, Daniel; MacFadyen, Andrew I.
2018-06-01
Unusually high velocities (≳0.1c) and correspondingly high kinetic energies have been observed in a subset of Type Ic supernovae (so-called “broad-lined Ic” supernovae; SNe Ic-BL), prompting a search for a central engine model capable of generating such energetic explosions. A clue to the explosion mechanism may lie in the fact that all supernovae that accompany long-duration gamma-ray bursts (GRBs) belong to the SN Ic-BL class. Using a combination of two-dimensional relativistic hydrodynamics and radiation transport calculations, we demonstrate that the central engine responsible for long GRBs can also trigger an SN Ic-BL. We find that a reasonable GRB engine injected into a stripped Wolf–Rayet progenitor produces a relativistic jet with energy ∼1051 erg, as well as an SN whose synthetic light curves and spectra are fully consistent with observed SNe Ic-BL during the photospheric phase. As a result of the jet’s asymmetric energy injection, the SN spectra and light curves depend on viewing angle. The impact of viewing angle on the spectrum is particularly pronounced at early times, while the viewing-angle dependence for the light curves (∼10% variation in bolometric luminosity) persists throughout the photospheric phase.
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.
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
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.
48 CFR 245.7101-3 - DD Form 1348-1, DoD Single Line Item Release/Receipt Document.
2010-10-01
... 48 Federal Acquisition Regulations System 3 2010-10-01 2010-10-01 false DD Form 1348-1, DoD Single Line Item Release/Receipt Document. 245.7101-3 Section 245.7101-3 Federal Acquisition Regulations... PROPERTY Plant Clearance Forms 245.7101-3 DD Form 1348-1, DoD Single Line Item Release/Receipt Document...
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....
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
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.
Defect dependence of the irreversibility line in Bi2Sr2CaCu2O8 single crystals
Lombardo, L. W.; Mitzi, D. B.; Kapitulnik, A.; Leone, A.
1992-09-01
The c-axis irreversibility line (IL) of pristine single-crystal Bi2Sr2CaCu2O8 is shown to exhibit three regimes: For fields less than 0.1 T, it obeys a power law, Hirr=H0(1-Tirr/Tc)μ, where μ and H0 vary with Tc. For fields greater than 2 T, the IL becomes linear with a slope of 0.7 T/K. For intermediate fields, there is a crossover region, which corresponds to the onset of collective vortex behavior. Defects produced by proton irradiation shift the IL in all three regimes: The high-field regime moves to higher temperatures, the low-field regime moves to lower temperatures, and the crossover to collective behavior becomes obscured. A maximal increase in the irreversibility temperature in the high-field regime is found to occur at a defect density of nearly one defect per vortex core disk.
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.
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.
Directory of Open Access Journals (Sweden)
Deyan N. Davidov
2013-04-01
Full Text Available Objective: Single agent Docetaxel is a standard therapy for patients with non- small cell lung cancer after the failure of platinum- containing regimens. The aim of this study was to explore the efficacy and safety of Docetaxel monotherapy as second- line chemotherapy in pretreated patient with inoperable non- small cell lung cancer. Methods: From January 2005 to May 2008 thirty- six consecutive patients with locally advanced or metastatic morphologically proven stage IIIB/ IV non- small cell lung cancer entered the study after failure of previous platinum- based regimens. Treatment schedule consist of Docetaxel 75 mg/m2 administered every three weeks with repetition after 21 days with Dexamethasone premedication. Results: Overall response rate, median time to progression and median survival was 16,6 %, 4,5 months and 5,6 months respectively. The main hematological toxicity was neutropenia. Conclusions: That data suggest that single agent Docetaxel remain reasonable choices for the chemotherapy in pretreated patients with non- small cell lung cancer.
Matsumoto, Keiichi; Kitamura, Keishi; Mizuta, Tetsuro; Shimizu, Keiji; Murase, Kenya; Senda, Michio
2006-02-20
Transmission scanning can be successfully performed with a Cs-137 single-photon-emitting point source for three-dimensional PET imaging. This method was effective for postinjection transmission scanning because of differences in physical energy. However, scatter contamination in the transmission data lowers measured attenuation coefficients. The purpose of this study was to investigate the accuracy of the influence of object scattering by measuring the attenuation coefficients on the transmission images. We also compared the results with the conventional germanium line source method. Two different types of PET scanner, the SET-3000 G/X (Shimadzu Corp.) and ECAT EXACT HR(+) (Siemens/CTI) , were used. For the transmission scanning, the SET-3000 G/X and ECAT HR(+) were the Cs-137 point source and Ge-68/Ga-68 line source, respectively. With the SET-3000 G/X, we performed transmission measurement at two energy gate settings, the standard 600-800 keV as well as 500-800 keV. The energy gate setting of the ECAT HR(+) was 350-650 keV. The effects of scattering in a uniform phantom with different cross-sectional areas ranging from 201 cm(2) to 314 cm(2) to 628 cm(2) (apposition of the two 20 cm diameter phantoms) and 943 cm(2) (stacking of the three 20 cm diameter phantoms) were acquired without emission activity. First, we evaluated the attenuation coefficients of the two different types of transmission scanning using region of interest (ROI) analysis. In addition, we evaluated the attenuation coefficients with and without segmentation for Cs-137 transmission images using the same analysis. The segmentation method was a histogram-based soft-tissue segmentation process that can also be applied to reconstructed transmission images. In the Cs-137 experiment, the maximum underestimation was 3% without segmentation, which was reduced to less than 1% with segmentation at the center of the largest phantom. In the Ge-68/Ga-68 experiment, the difference in mean attenuation
International Nuclear Information System (INIS)
Matsumoto, Keiichi; Shimizu, Keiji; Senda, Michio; Kitamura, Keishi; Mizuta, Tetsuro; Murase, Kenya
2006-01-01
Transmission scanning can be successfully performed with a Cs-137 single-photon-emitting point source for three-dimensional PET imaging. This method was effective for postinjection transmission scanning because of differences in physical energy. However, scatter contamination in the transmission data lowers measured attenuation coefficients. The purpose of this study was to investigate the accuracy of the influence of object scattering by measuring the attenuation coefficients on the transmission images. We also compared the results with the conventional germanium line source method. Two different types of PET scanner, the SET-3000 G/X (Shimadzu Corp.) and ECAT EXACT HR + (Siemens/CTI), were used. For the transmission scanning, the SET-3000 G/X and ECAT HR + were the Cs-137 point source and Ge-68/Ga-68 line source, respectively. With the SET-3000 G/X, we performed transmission measurement at two energy gate settings, the standard 600-800 keV as well as 500-800 keV. The energy gate setting of the ECAT HR 2 + was 350-650 keV. The effects of scattering in a uniform phantom with different cross-sectional areas ranging from 201 cm 2 to 314 cm 2 to 628 cm 2 (apposition of the two 20 cm diameter phantoms) and 943 cm 2 (stacking of the three 20 cm diameter phantoms) were acquired without emission activity. First, we evaluated the attenuation coefficients of the two different types of transmission scanning using region of interest (ROI) analysis. In addition, we evaluated the attenuation coefficients with and without segmentation for Cs-137 transmission images using the same analysis. The segmentation method was a histogram-based soft-tissue segmentation process that can also be applied to reconstructed transmission images. In the Cs-137 experiment, the maximum underestimation was 3% without segmentation, which was reduced to less than 1% with segmentation at the center of the largest phantom. In the Ge-68/Ga-68 experiment, the difference in mean attenuation coefficients
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.
Bayesian ARTMAP for regression.
Sasu, L M; Andonie, R
2013-10-01
Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.
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.
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.
Differentiating regressed melanoma from regressed lichenoid keratosis.
Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A
2017-04-01
Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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.
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.)
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.…
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.
El-Sherry, S; Ogedengbe, M E; Hafeez, M A; Sayf-Al-Din, M; Gad, N; Barta, J R
2017-10-01
The Briston strain of Eimeria dispersa Tyzzer, 1929 was isolated originally from a commercial turkey flock from Briston, Norfolk, UK. A single oocyst-derived line of E. dispersa was propagated and used to re-describe biological and morphological features of E. dispersa in the turkey. Oocysts of the Briston strain measured 26 ± 1.1 μm (24-28) by 21 ± 1 μm (19-23); these were larger than oocysts described originally by Tyzzer in 1929 (22.75 by 18.84 μm) but within dimensions (26.07 by 21.04 μm) reported by Hawkins (1952) in his description of E. dispersa isolated from turkeys. In the present study, endogenous development started mainly in duodenum and upper jejunum and then spread down toward the lower jejunum. A few parasites were detected in the ileum beginning 96 h post-infection; only few gamonts were observed in the cecal neck area at 120 h, and no parasites were detected in cecal pouches or rectum. Four asexual generations were observed before the start of gametogony, and only one large type of first generation meront was detected in duodenum and upper jejunum at 32 h. This strain has a prepatent period of 120 h. The Briston strain of E. dispersa is a mildly pathogenic coccidium. Duodenum and jejunum of infected birds were slightly dilated and paler in color than of uninfected controls. There was whitish green mucoid material in the lumen of the duodenum and jejunum. The mucosa looked slightly congested and edematous with a few scattered petechial hemorrhages.
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...
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...... current sampling delay reduction method, a single-phase SAF compensated system provides higher harmonic isolation performance and higher stability margins compared to the system using conventional synchronous-reference-frame-based methods. The analytical, simulation, and experimental studies of a 2.5 k...
Gilks, Charles F; Walker, A Sarah; Munderi, Paula; Kityo, Cissy; Reid, Andrew; Katabira, Elly; Goodall, Ruth L; Grosskurth, Heiner; Mugyenyi, Peter; Hakim, James; Gibb, Diana M
2013-01-01
In low-income countries, viral load (VL) monitoring of antiretroviral therapy (ART) is rarely available in the public sector for HIV-infected adults or children. Using clinical failure alone to identify first-line ART failure and trigger regimen switch may result in unnecessary use of costly second-line therapy. Our objective was to identify CD4 threshold values to confirm clinically-determined ART failure when VL is unavailable. 3316 HIV-infected Ugandan/Zimbabwean adults were randomised to first-line ART with Clinically-Driven (CDM, CD4s measured but blinded) or routine Laboratory and Clinical Monitoring (LCM, 12-weekly CD4s) in the DART trial. CD4 at switch and ART failure criteria (new/recurrent WHO 4, single/multiple WHO 3 event; LCM: CD4tiebreaker' of ≥250 cells/mm(3) for clinically-monitored patients failing first-line could identify ∼80% with VL<400 copies/ml, who are unlikely to benefit from second-line. Targeting CD4s to single WHO stage 3 'clinical failures' would particularly avoid premature, costly switch to second-line ART.
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.
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...
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 zirconium-oxide-based ceramic CAD/CAM crowns with vertical and horizontal finish line preparations were not different. © 2015 by the American College of Prosthodontists.
Ali, Selman A; Lynam, June; McLean, Cornelia S; Entwisle, Claire; Loudon, Peter; Rojas, José M; McArdle, Stephanie E B; Li, Geng; Mian, Shahid; Rees, Robert C
2002-04-01
Direct intratumor injection of a disabled infectious single cycle HSV-2 virus encoding the murine GM-CSF gene (DISC/mGM-CSF) into established murine colon carcinoma CT26 tumors induced a significant delay in tumor growth and complete tumor regression in up to 70% of animals. Pre-existing immunity to HSV did not reduce the therapeutic efficacy of DISC/mGM-CSF, and, when administered in combination with syngeneic dendritic cells, further decreased tumor growth and increased the incidence of complete tumor regression. Direct intratumor injection of DISC/mGM-CSF also inhibited the growth of CT26 tumor cells implanted on the contralateral flank or seeded into the lungs following i.v. injection of tumor cells (experimental lung metastasis). Proliferation of splenocytes in response to Con A was impaired in progressor and tumor-bearer, but not regressor, mice. A potent tumor-specific CTL response was generated from splenocytes of all mice with regressing, but not progressing tumors following in vitro peptide stimulation; this response was specific for the gp70 AH-1 peptide SPSYVYHQF and correlated with IFN-gamma, but not IL-4 cytokine production. Depletion of CD8(+) T cells from regressor splenocytes before in vitro stimulation with the relevant peptide abolished their cytolytic activity, while depletion of CD4(+) T cells only partially inhibited CTL generation. Tumor regression induced by DISC/mGM-CSF virus immunotherapy provides a unique model for evaluating the immune mechanism(s) involved in tumor rejection, upon which tumor immunotherapy regimes may be based.
International Nuclear Information System (INIS)
Wagatsuma, K.
1996-01-01
The relative intensities of silver emission lines from Grimm glow discharge plasmas were investigated in the wavelength range from 160 to 600 nm when using different plasma gases. It was characteristic of the plasma excitation that the spectral patterns were strongly dependent on the nature of the plasma gas employed. Intense emission lines of silver ion were observed when argon-helium mixed gases were employed as the plasma gas. Selective excitation of the ionic lines could be principally attributed to the charge transfer collisions between silver atoms and helium ions. (orig.)
Advanced statistics: linear regression, part II: multiple linear regression.
Marill, Keith A
2004-01-01
The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.
Directory of Open Access Journals (Sweden)
Charles F Gilks
Full Text Available In low-income countries, viral load (VL monitoring of antiretroviral therapy (ART is rarely available in the public sector for HIV-infected adults or children. Using clinical failure alone to identify first-line ART failure and trigger regimen switch may result in unnecessary use of costly second-line therapy. Our objective was to identify CD4 threshold values to confirm clinically-determined ART failure when VL is unavailable.3316 HIV-infected Ugandan/Zimbabwean adults were randomised to first-line ART with Clinically-Driven (CDM, CD4s measured but blinded or routine Laboratory and Clinical Monitoring (LCM, 12-weekly CD4s in the DART trial. CD4 at switch and ART failure criteria (new/recurrent WHO 4, single/multiple WHO 3 event; LCM: CD4<100 cells/mm(3 were reviewed in 361 LCM, 314 CDM participants who switched over median 5 years follow-up. Retrospective VLs were available in 368 (55% participants.Overall, 265/361 (73% LCM participants failed with CD4<100 cells/mm(3; only 7 (2% switched with CD4≥250 cells/mm(3, four switches triggered by WHO events. Without CD4 monitoring, 207/314 (66% CDM participants failed with WHO 4 events, and 77(25%/30(10% with single/multiple WHO 3 events. Failure/switching with single WHO 3 events was more likely with CD4≥250 cells/mm(3 (28/77; 36% (p = 0.0002. CD4 monitoring reduced switching with viral suppression: 23/187 (12% LCM versus 49/181 (27% CDM had VL<400 copies/ml at failure/switch (p<0.0001. Amongst CDM participants with CD4<250 cells/mm(3 only 11/133 (8% had VL<400 copies/ml, compared with 38/48 (79% with CD4≥250 cells/mm(3 (p<0.0001.Multiple, but not single, WHO 3 events predicted first-line ART failure. A CD4 threshold 'tiebreaker' of ≥250 cells/mm(3 for clinically-monitored patients failing first-line could identify ∼80% with VL<400 copies/ml, who are unlikely to benefit from second-line. Targeting CD4s to single WHO stage 3 'clinical failures' would particularly avoid premature, costly
Pinning in the flux-line-cutting regime of Bi 2Sr 2Ca 1Cu 2O 8 single crystals at high field
D'Anna, G.; André, M.-O.; Indenbom, M. V.; Benoit, W.
1994-09-01
Using a low-frequency torsion pendulum we show that in a Bi 2Sr 2Ca 1Cu 2O 8 single crystal the irreversibility line Birr( T) is frequency dependent down to 10 -5 Hz in the high-field regime. The activation energy has a logarithmic field dependence, U0( B)= U∗ 1n( B∗/ B). A microscopic model for flux-line-cutting and pancake collision yields quantitative expressions for U0 and for Birr( T)= B∗ exp(- T/T∗), which reproduce the experimental data very well.
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.
A NLTE line formation for neutral and singly ionized calcium in model atmospheres of B-F stars
Sitnova, T. M.; Mashonkina, L. I.; Ryabchikova, T. A.
2018-07-01
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 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 ≤ Teff ≤ 13 000 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 normalization 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.
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...
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…
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.
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.
International Nuclear Information System (INIS)
Woo, Ae Ja; Cho, So Hyun; Han, Duk Young
2000-01-01
With 1D-nutation NMR for a spin I = 5/2 system, the relative line intensities of central and the inner- and outer-satellite transitions are calculated as functions of quadrupolar coupling ω Q and rf pulse strength ω rf . Experimentally measured line intensities including both central and satellites are used to extract the values of ω Q and ω rf from nonlinear least-squares fits. The method is illustrated in α-Al 2 O 3 crystals (ruby and corundum) with the single-crystal 27 Al nutation NMR spectra. As a result, the new feature that the rf pulse strength shows reduced effect on the satellite transition lines according to the quadrupolar coupling is discussed by using fictitious spin-1/2 operator
Energy Technology Data Exchange (ETDEWEB)
Seo, Ho Geon; Kim, Myung Hwan; Choi, Sung Ho; Kim, Chung Seok; Jhang, Kyung Young [Hanyang University, Seoul (Korea, Republic of)
2012-08-15
Using a single-line pulsed laser beam is well known as a useful noncontact method to generate a directional surface acoustic wave. In this method, different laser beam energy profiles produce different waveforms and frequency characteristics. In this paper, we considered two typical kinds of laser beam energy profiles, Gaussian and square-like, to find out a difference in the frequency characteristics. To achieve this, mathematical models were proposed first for Gaussian laser beam profile and square-like respectively, both of which depended on the laser beam width. To verify the theoretical models, experimental setups with a cylindrical lens and a line-slit mask were respectively designed to produce a line laser beam with Gaussian spatial energy profile and square-like. The frequency responses of the theoretical models showed good agreement with experimental results in terms of the existence of harmonic frequency components and the shift of the first peak frequencies to low.
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.
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
Single-mode solid-state polymer dye laser fabricated with standard I-line UV lithography
DEFF Research Database (Denmark)
Balslev, Søren; Mironov, Andrej; Nilsson, Daniel
2005-01-01
We present single-mode solid-state polymer dye lasers fabricated with standard UV lithography. The lasers use a high-order Bragg grating and rely on index-tuning of a photosensitive polymer for waveguiding. The gain medium is Rhodamine 6G.......We present single-mode solid-state polymer dye lasers fabricated with standard UV lithography. The lasers use a high-order Bragg grating and rely on index-tuning of a photosensitive polymer for waveguiding. The gain medium is Rhodamine 6G....
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...
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...
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.
International Nuclear Information System (INIS)
Yoshida, Akira; Kaburagi, Yutaka; Hishiyama, Yoshihiro
2007-01-01
Mesophase-pitch-based carbon fiber P100 is known as a well-oriented carbon fiber in which the partially graphitized crystallites align along the fiber axis. The X-ray powder diffraction pattern for P100 measured by the X-ray diffractometer reveals the 100 diffraction line as a composite peak with the 101 diffraction line. The composite peak is usually not easy to separate into the component peaks of 100 and 101 lines. In the present article, a method to measure the single 100 diffraction line with the X-ray diffractometer using fiber samples of P100 has been developed. It has been found that there exist two types of crystallites oriented to their basal planes along the fiber axis in each of the P100 fibers; the Z-type crystallite with the zigzag boundary planes and the A-type crystallite with the armchair boundary planes, both of the boundary planes are perpendicular to the fiber axis. The average crystallite sizes along the fiber axis evaluated are 53 nm for the Z-type crystallites and 800 nm for the armchair crystallites. The average crystallite thickness for both types is about 120 nm. (author)
VanderKaay, Sandra; Letts, Lori; Jung, Bonny; Moll, Sandra E
2018-05-20
Ethics education is a critical component of training rehabilitation practitioners. There is a need for capacity-building among ethics educators regarding facilitating ethical decision-making among students. The purpose of this study was to evaluate the utility of an on-line ethics education module for occupational therapy clinician-educators (problem-based learning tutors/clinical placement preceptors/evidence-based practice facilitators). The Knowledge-to-Action Process informed development and evaluation of the module. Clinician-educators (n = 33) viewed the module and reported on its impact on knowledge and facilitation practices via pre, post, and follow-up questionnaires. Pre- and post-test data indicated improvement in self-reported ethics knowledge (t = 8.275, p ethics education module for clinician-educators. Future recommendations include broader consideration of context, adding supplemental knowledge translation components, and further research exploring outcomes with larger samples, longer follow-up and randomized trial methodology. Implications for Rehabilitation The on-line ethics module has potential to improve rehabilitation practice by addressing the noted gap in knowledge among clinician-educators. Viewing an on-line module regarding approaches to ethics education may not be sufficient to change clinician-educators' teaching practices. More time and opportunities to discuss ethics with student occupational therapists may be required to effect practice change among clinician-educators. Developing ethics education tools for clinician-educators requires ongoing and iterative input from knowledge users to optimize translation of ideas to practice.
Han, Kun; Sun, Yuanjue; Zhang, Jianjun; He, Aina; Zheng, Shui'er; Shen, Zan; Yao, Yang
2014-06-01
To investigate the feasibility and efficacy of cyclophosphamide (CTX)-hydroxycamptothecin (HCPT) as second-line chemotherapy on advanced Ewing's sarcoma. From April 2009 to November 2010, 27 patients with advanced Ewing's sarcoma who had progressive disease after the first-line chemotherapy regimen of vincristine, dactinomycin and cyclophosphamide and ifosfamide and etoposide were retrospectively reviewed in this analysis. CTX was given (0.6 g/m(2), i.v. push day 1) and HCPT (6 mg/m(2), i.v. drip days 1-5) as second-line chemotherapy every 3 weeks. The primary end-point was overall response rate, the secondary end-point included progression-free, overall survival, disease control rate and toxicities. A total of 134 cycles were given, median four cycles per patient (range 2-6). Overall response rate was 30% and disease control rate was 82%, with two complete response (8%), six partial remission (22%) and 14 stable disease (52%). The median time to progression and overall survival time were 7 months (95% CI 3-10) and 11 months (95% CI 5-18), respectively. Major severe toxicities (grade 3 and 4) were: nausea/vomiting (17%), alopecia (17%); leukopenia (27%) in total cycles. Mild toxicities (grade 1 or 2) were leukopenia (73%), nausea/vomiting (83%), hepatic lesion (14%) and anemia (44%). A CTX-HCPT regimen can control disease progression effectively and the side effects can be tolerable for Chinese advanced Ewing's sarcoma patients. Further assessment is necessary to confirm the safety and efficacy of this treatment. © 2012 Wiley Publishing Asia Pty Ltd.
Energy Technology Data Exchange (ETDEWEB)
Danly, C. R.; Day, T. H.; Herrmann, H.; Kim, Y. H.; Martinez, J. I.; Merrill, F. E.; Schmidt, D. W.; Simpson, R. A.; Volegov, P. L.; Wilde, C. H. [Los Alamos National Laboratory, Los Alamos, New Mexico 87544 (United States); Fittinghoff, D. N.; Izumi, N. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States)
2015-04-15
Neutron and x-ray imaging provide critical information about the geometry and hydrodynamics of inertial confinement fusion implosions. However, existing diagnostics at Omega and the National Ignition Facility (NIF) cannot produce images in both neutrons and x-rays along the same line of sight. This leads to difficulty comparing these images, which capture different parts of the plasma geometry, for the asymmetric implosions seen in present experiments. Further, even when opposing port neutron and x-ray images are available, they use different detectors and cannot provide positive information about the relative positions of the neutron and x-ray sources. A technique has been demonstrated on implosions at Omega that can capture x-ray images along the same line of sight as the neutron images. The technique is described, and data from a set of experiments are presented, along with a discussion of techniques for coregistration of the various images. It is concluded that the technique is viable and could provide valuable information if implemented on NIF in the near future.
Devito, Liani; Petrova, Anastasia; Miere, Cristian; Codognotto, Stefano; Blakely, Nicola; Lovatt, Archie; Ogilvie, Caroline; Khalaf, Yacoub; Ilic, Dusko
2014-10-01
Standardization guidelines for human pluripotent stem cells are still very broadly defined, despite ongoing clinical trials in the U.S., U.K., and Japan. The requirements for validation of human embryonic (hESCs) and induced pluripotent stem cells (iPSCs) in general follow the regulations for other clinically compliant biologics already in place but without addressing key differences between cell types or final products. In order to realize the full potential of stem cell therapy, validation criteria, methodology, and, most importantly, strategy, should address the shortfalls and efficiency of current approaches; without this, hESC- and, especially, iPSC-based therapy will not be able to compete with other technologies in a cost-efficient way. We addressed the protocols for testing cell lines for human viral pathogens and propose a novel strategy that would significantly reduce costs. It is highly unlikely that the multiple cell lines derived in parallel from a tissue sample taken from one donor would have different profiles of endogenous viral pathogens; we therefore argue that samples from the Master Cell Banks of sibling lines could be safely pooled for validation. We illustrate this approach with tiered validation of two sibling clinical-grade hESC lines, KCL033 and KCL034 (stage 1, sterility; stage 2, specific human pathogens; and stage 3, nonspecific human pathogens). The results of all tests were negative. This cost-effective strategy could also be applied for validation of Master Cell Banks of multiple clinical-grade iPSC lines derived from a single donor. ©AlphaMed Press.
Understanding logistic regression analysis
Sperandei, Sandro
2014-01-01
Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...
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
Valentini, Federica; Mari, Emanuela; Zicari, Alessandra; Calcaterra, Andrea; Talamo, Maurizio; Scioli, Maria Giovanna; Orlandi, Augusto; Mardente, Stefania
2018-04-28
The in vitro biocompatibility of Graphene Oxide (GO) nanosheets, which were obtained by the electrochemical exfoliation of graphite electrodes in an electrolytic bath containing salts, was compared with the pristine Single Wall Carbon Nanotubes (p-SWCNTs) under the same experimental conditions in different human cell lines. The cells were treated with different concentrations of GO and SWCNTs for up to 48 h. GO did not induce any significant morphological or functional modifications (demonstrating a high biocompatibility), while SWNCTs were toxic at any concentration used after a few hours of treatment. The cell viability or cytotoxicity were detected by the trypan blue assay and the lactate dehydrogenase LDH quantitative enzymatic test. The Confocal Laser Scanning Microscopy (CLSM) and transmission electron microscopy (TEM) analysis demonstrated the uptake and internalization of GO sheets into cells, which was localized mainly in the cytoplasm. Different results were observed in the same cell lines treated with p-SWCNTs. TEM and CLSM (Confocal Laser Scanning Microscopy) showed that the p-SWCNTs induced vacuolization in the cytoplasm, disruption of cellular architecture and damage to the nuclei. The most important result of this study is our finding of a higher GO biocompatibility compared to the p-SWCNTs in the same cell lines. This means that GO nanosheets, which are obtained by the electrochemical exfoliation of a graphite-based electrode (carried out in saline solutions or other physiological working media) could represent an eligible nanocarrier for drug delivery, gene transfection and molecular cell imaging tests.
Gich, Jordi; Freixanet, Jordi; García, Rafael; Vilanova, Joan Carles; Genís, David; Silva, Yolanda; Montalban, Xavier; Ramió-Torrentà, Lluís
2015-09-01
MS-Line! was created to provide an effective treatment for cognitive impairment in multiple sclerosis (MS) patients. To assess the efficacy of MS-Line!. A randomized, controlled, single-blind, 6-month pilot study. Patients were randomly assigned to an experimental group (cognitive rehabilitation with the programme) or to a control group (no cognitive rehabilitation). Randomization was stratified by cognitive impairment level. Cognitive assessment included: selective reminding test, 10/36 spatial recall test (10/36 SPART), symbol digit modalities test, paced auditory serial addition test, word list generation (WLG), FAS test, subtests of WAIS-III, Boston naming test (BNT), and trail making test (TMT). Forty-three patients (22 in the experimental group, 21 in the control group) were analyzed. Covariance analysis showed significant differences in 10/36 SPART (P=0.0002), 10/36 SPART delayed recall (P=0.0021), WLG (P=0.0123), LNS (P=0.0413), BNT (P=0.0007) and TMT-A (P=0.010) scores between groups. The study showed a significant improvement related to learning and visual memory, executive functions, attention and information processing speed, and naming ability in those patients who received cognitive rehabilitation. The results suggest that MS-Line! is effective in improving cognitive impairment in MS patients. © The Author(s), 2015.
Vogel, Charles L; Cobleigh, Melody A; Tripathy, Debu; Gutheil, John C; Harris, Lyndsay N; Fehrenbacher, Louis; Slamon, Dennis J; Murphy, Maureen; Novotny, William F; Burchmore, Michael; Shak, Steven; Stewart, Stanford J; Press, Michael
2002-02-01
To evaluate the efficacy and safety of first-line, single-agent trastuzumab in women with HER2-overexpressing metastatic breast cancer. One hundred fourteen women with HER2-overexpressing metastatic breast cancer were randomized to receive first-line treatment with trastuzumab 4 mg/kg loading dose, followed by 2 mg/kg weekly, or a higher 8 mg/kg loading dose, followed by 4 mg/kg weekly. The objective response rate was 26% (95% confidence interval [CI], 18.2% to 34.4%), with seven complete and 23 partial responses. Response rates in 111 assessable patients with 3+ and 2+ HER2 overexpression by immunohistochemistry (IHC) were 35% (95% CI, 24.4% to 44.7%) and none (95% CI, 0% to 15.5%), respectively. The clinical benefit rates in assessable patients with 3+ and 2+ HER2 overexpression were 48% and 7%, respectively. The response rates in 108 assessable patients with and without HER2 gene amplification by fluorescence in situ hybridization (FISH) analysis were 34% (95% CI, 23.9% to 45.7%) and 7% (95% CI, 0.8% to 22.8%), respectively. Seventeen (57%) of 30 patients with an objective response and 22 (51%) of 43 patients with clinical benefit had not experienced disease progression at follow-up at 12 months or later. The most common treatment-related adverse events were chills (25% of patients), asthenia (23%), fever (22%), pain (18%), and nausea (14%). Cardiac dysfunction occurred in two patients (2%); both had histories of cardiac disease and did not require additional intervention after discontinuation of trastuzumab. There was no clear evidence of a dose-response relationship for response, survival, or adverse events. Single-agent trastuzumab is active and well tolerated as first-line treatment of women with metastatic breast cancer with HER2 3+ overexpression by IHC or gene amplification by FISH.
Genetics Home Reference: caudal regression syndrome
... umbilical artery: Further support for a caudal regression-sirenomelia spectrum. Am J Med Genet A. 2007 Dec ... AK, Dickinson JE, Bower C. Caudal dysgenesis and sirenomelia-single centre experience suggests common pathogenic basis. Am ...
[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.
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 .
Reclosing operation characteristics of the flux-coupling type SFCL in a single-line-to ground fault
International Nuclear Information System (INIS)
Jung, B.I.; Cho, Y.S.; Choi, H.S.; Ha, K.H.; Choi, S.G.; Chul, D.C.; Sung, T.H.
2011-01-01
The recloser that is used in distribution systems is a relay system that behaves sequentially to protect power systems from transient and continuous faults. This reclosing operation of the recloser can improve the reliability and stability of the power supply. For cooperation with this recloser, the superconducting fault current limiter (SFCL) must properly perform the reclosing operation. This paper analyzed the reclosing operation characteristics of the three-phase flux-coupling type SFCL in the event of a ground fault. The fault current limiting characteristics according to the changing number of turns of the primary and secondary coils were examined. As the number of turns of the first coil increased, the first maximum fault current decreased. Furthermore, the voltage of the quenched superconducting element also decreased. This means that the power burden of the superconducting element decreases based on the increasing number of turns of the primary coil. The fault current limiting characteristic of the SFCL according to the reclosing time limited the fault current within a 0.5 cycles (8 ms), which is shorter than the closing time of the recloser. In other words, the superconducting element returned to the superconducting state before the second fault and normally performed the fault current limiting operation. If the SFCL did not recover before the recloser reclosing time, the normal current that was flowing in the transmission line after the recovery of the SFCL from the fault would have been limited and would have caused losses. Therefore, the fast recovery time of a SFCL is critical to its cooperation with the protection system.
Reclosing operation characteristics of the flux-coupling type SFCL in a single-line-to ground fault
Jung, B. I.; Cho, Y. S.; Choi, H. S.; Ha, K. H.; Choi, S. G.; Chul, D. C.; Sung, T. H.
2011-11-01
The recloser that is used in distribution systems is a relay system that behaves sequentially to protect power systems from transient and continuous faults. This reclosing operation of the recloser can improve the reliability and stability of the power supply. For cooperation with this recloser, the superconducting fault current limiter (SFCL) must properly perform the reclosing operation. This paper analyzed the reclosing operation characteristics of the three-phase flux-coupling type SFCL in the event of a ground fault. The fault current limiting characteristics according to the changing number of turns of the primary and secondary coils were examined. As the number of turns of the first coil increased, the first maximum fault current decreased. Furthermore, the voltage of the quenched superconducting element also decreased. This means that the power burden of the superconducting element decreases based on the increasing number of turns of the primary coil. The fault current limiting characteristic of the SFCL according to the reclosing time limited the fault current within a 0.5 cycles (8 ms), which is shorter than the closing time of the recloser. In other words, the superconducting element returned to the superconducting state before the second fault and normally performed the fault current limiting operation. If the SFCL did not recover before the recloser reclosing time, the normal current that was flowing in the transmission line after the recovery of the SFCL from the fault would have been limited and would have caused losses. Therefore, the fast recovery time of a SFCL is critical to its cooperation with the protection system.
International Nuclear Information System (INIS)
Yahyaoui, Imene; Segatto, Marcelo E.V.
2017-01-01
Highlights: • Automatic detection of main faults in PV systems is presented and tested. • Specific indicators detect bypass module, open-circuit string and partial shading. • The strategy efficiency is validated by experiments for two days. • The strategy allows the number of faulty PV modules and strings to be determined. • The method is effective and minimizes the use of sensors in the monitoring system. - Abstract: Improving the reliability and enhancing the performance of photovoltaic (PV) plants are important objectives that increase the competitiveness of the PV systems, especially for grid connected PV plants, for which, every kilowatt-hour is crucial, since only kilowatt-hours that are fed into the grid are remunerated. Therefore, monitoring and automatic faults detection during the PV panels operation are necessary to ensure the optimal use of the energy generated by the PV plant, and to provide a reliable power supply. In this research paper, two current and voltage indicators are used to analyze and to distinguish, in real-time, the faults related to bypassed PV modules, open-circuits strings and partial shading for a PV plant connected to a single-phase grid. Moreover, the presented strategy allows determining the total number of faulty PV modules and/or strings. The efficiencies of these indicators are tested by experiments, using a Control and Data Acquisition System, which proved the effectiveness of the proposed approach.
Directory of Open Access Journals (Sweden)
Matthias Schmid
Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.
Few crystal balls are crystal clear : eyeballing regression
International Nuclear Information System (INIS)
Wittebrood, R.T.
1998-01-01
The theory of regression and statistical analysis as it applies to reservoir analysis was discussed. It was argued that regression lines are not always the final truth. It was suggested that regression lines and eyeballed lines are often equally accurate. The many conditions that must be fulfilled to calculate a proper regression were discussed. Mentioned among these conditions were the distribution of the data, hidden variables, knowledge of how the data was obtained, the need for causal correlation of the variables, and knowledge of the manner in which the regression results are going to be used. 1 tab., 13 figs
Understanding logistic regression analysis.
Sperandei, Sandro
2014-01-01
Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.
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-
Directory of Open Access Journals (Sweden)
Victoria M. Pearson
2016-10-01
Full Text Available Understanding the structure and dynamics of microbial communities, especially those of economic concern, is of paramount importance to maintaining healthy and efficient microbial communities at agricultural sites and large industrial cultures, including bioprocessors. Wastewater treatment plants are large bioprocessors which receive water from multiple sources, becoming reservoirs for the collection of many viral families that infect a broad range of hosts. To examine this complex collection of viruses, full-length genomes of circular ssDNA viruses were isolated from a wastewater treatment facility using a combination of sucrose-gradient size selection and rolling-circle amplification and sequenced on an Illumina MiSeq. Single-stranded DNA viruses are among the least understood groups of microbial pathogens due to genomic biases and culturing difficulties, particularly compared to the larger, more often studied dsDNA viruses. However, the group contains several notable well-studied examples, including agricultural pathogens which infect both livestock and crops (Circoviridae and Geminiviridae, and model organisms for genetics and evolution studies (Microviridae. Examination of the collected viral DNA provided evidence for 83 unique genotypic groupings, which were genetically dissimilar to known viral types and exhibited broad diversity within the community. Furthermore, although these genomes express similarities to known viral families, such as Circoviridae, Geminiviridae, and Microviridae, many are so divergent that they may represent new taxonomic groups. This study demonstrated the efficacy of the protocol for separating bacteria and large viruses from the sought after ssDNA viruses and the ability to use this protocol to obtain an in-depth analysis of the diversity within this group.
Understanding poisson regression.
Hayat, Matthew J; Higgins, Melinda
2014-04-01
Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.
Pivonello, Claudia; Rousaki, Panagoula; Negri, Mariarosaria; Sarnataro, Maddalena; Napolitano, Maria; Marino, Federica Zito; Patalano, Roberta; De Martino, Maria Cristina; Sciammarella, Concetta; Faggiano, Antongiulio; Rocco, Gaetano; Franco, Renato; Kaltsas, Gregory A; Colao, Annamaria; Pivonello, Rosario
2017-06-01
Somatostatin analogues and mTOR inhibitors have been used as medical therapy in lung carcinoids with variable results. No data are available on dopamine agonists as treatment for lung carcinoids. The main aim of the current study was to evaluate the effect of the combined treatment of somatostatin analogue octreotide and the dopamine agonist cabergoline with mTOR inhibitors in an in vitro model of typical lung carcinoids: the NCI-H727 cell line. In NCI-H727 cell line, reverse transcriptase-quantitative polymerase chain reaction and immunofluorescence were assessed to characterize the expression of the somatostatin receptor 2 and 5, dopamine receptor 2 and mTOR pathway components. Fifteen typical lung carcinoids tissue samples have been used for somatostatin receptor 2, dopamine receptor 2, and the main mTOR pathway component p70S6K expression and localization by immunohistochemistry. Cell viability, fluorescence-activated cell sorting analysis and western blot have been assessed to test the pharmacological effects of octreotide, cabergoline and mTOR inhibitors, and to evaluate the activation of specific cell signaling pathways in NCI-H727 cell line. NCI-H727 cell line expressed somatostatin receptor 2, somatostatin receptor 5 and dopamine receptor 2 and all mTOR pathway components at messenger and protein levels. Somatostatin receptor 2, dopamine receptor 2, and p70S6K (non phosphorylated and phosphorylated) proteins were expressed in most typical lung carcinoids tissue samples. Octreotide and cabergoline did not reduce cell viability as single agents but, when combined with mTOR inhibitors, they potentiate mTOR inhibitors effect after long-term exposure, reducing Akt and ERK phosphorylation, mTOR escape mechanisms, and increasing the expression DNA-damage-inducible transcript 4, an mTOR suppressor. In conclusion, the single use of octreotide and cabergoline is not sufficient to block cell viability but the combined approach of these agents with mTOR inhibitors
Wei, Fang; Hu, Na; Lv, Xin; Dong, Xu-Yan; Chen, Hong
2015-07-24
In this investigation, off-line comprehensive two-dimensional liquid chromatography-atmospheric pressure chemical ionization mass spectrometry using a single column has been applied for the identification and quantification of triacylglycerols in edible oils. A novel mixed-mode phenyl-hexyl chromatographic column was employed in this off-line two-dimensional separation system. The phenyl-hexyl column combined the features of traditional C18 and silver-ion columns, which could provide hydrophobic interactions with triacylglycerols under acetonitrile conditions and can offer π-π interactions with triacylglycerols under methanol conditions. When compared with traditional off-line comprehensive two-dimensional liquid chromatography employing two different chromatographic columns (C18 and silver-ion column) and using elution solvents comprised of two phases (reversed-phase/normal-phase) for triacylglycerols separation, the novel off-line comprehensive two-dimensional liquid chromatography using a single column can be achieved by simply altering the mobile phase between acetonitrile and methanol, which exhibited a much higher selectivity for the separation of triacylglycerols with great efficiency and rapid speed. In addition, an approach based on the use of response factor with atmospheric pressure chemical ionization mass spectrometry has been developed for triacylglycerols quantification. Due to the differences between saturated and unsaturated acyl chains, the use of response factors significantly improves the quantitation of triacylglycerols. This two-dimensional liquid chromatography-mass spectrometry system was successfully applied for the profiling of triacylglycerols in soybean oils, peanut oils and lord oils. A total of 68 triacylglycerols including 40 triacylglycerols in soybean oils, 50 triacylglycerols in peanut oils and 44 triacylglycerols in lord oils have been identified and quantified. The liquid chromatography-mass spectrometry data were analyzed
Institute of Scientific and Technical Information of China (English)
ZHAO Fang-ming; LIU Gui-fu; ZHU Hai-tao; DING Xiao-hua; ZENG Rui-zhen; ZHANG Ze-min; LI Wen-tao; ZHANG Gui-quan
2008-01-01
Tiller is one of the most important agronomic traits which influences quantity and quality of effective panicles and finally influences yield in rice.It is important to understand "static" and "dynamic" information of the QTLs for tillers in rice.This work was the first time to simultaneously map unconditional and conditional QTLs for tiller numbers at various stages by using single segment substitution lines in rice.Fourteen QTLs for tiller number,distributing on the corresponding substitution segments of chromosomes 1,2,3,4,6,7 and 8 were detected.Both the number and the effect of the QTLs for tiller number were various at different stages,from 6 to 9 in the number and from 1.49 to 3.49 in the effect,respectively. Tiller number QTLs expressed in a time order,mainly detected at three stages of 0-7d,14-21d and 35-42d after transplanting with 6 positive,9 random and 6 negative expressing QTLs,respectively.Each of the QTLs expressed one time at least during the whole duration of rice.The tiller number at a specific stage was determined by sum of QTL effects estimated by the unconditional method,while the increasing or decreasing number in a given time interval was controlled by the total of QTL effects estimated by the conditional method.These results demonstrated that it is highly effective and accurate for mapping of the QTLs by using single segment substitution lines and the conditional analysis methodology.
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.
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.
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)
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.
Multicollinearity and Regression Analysis
Daoud, Jamal I.
2017-12-01
In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.
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....
DEFF Research Database (Denmark)
Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas
2017-01-01
In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....
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
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.
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
Ritz, Christian; Parmigiani, Giovanni
2009-01-01
R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. This book provides a coherent treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology.
Bounded Gaussian process regression
DEFF Research Database (Denmark)
Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan
2013-01-01
We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...... with the proposed explicit noise-model extension....
and Multinomial Logistic Regression
African Journals Online (AJOL)
This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).
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
Tarai, B; Das, P; Kumar, D; Budhiraja, S
2012-01-01
Paired blood culture (PBC) is uncommon practice in hospitals in India, leading to delayed and inadequate diagnosis. Also contamination remains a critical determinant in hampering the definitive diagnosis. To establish the need of PBC over single blood culture (SBC) along with the degree of contamination, this comparative retrospective study was initiated. We processed 2553 PBC and 4350 SBC in BacT/ALERT 3D (bioMerieux) between October 2010 and June 2011. The positive cultures were identified in VITEK 2 Compact (bioMerieux). True positivity and contaminants were also analyzed in 486 samples received from catheter and peripheral line. Out of 2553 PBC samples, positivity was seen in 350 (13.70%). In 4350 SBC samples, positivity was seen in 200 samples (4.59%). In PBC true pathogens were 267 (10.45%) and contaminants were 83 (3.25%), whereas in SBC 153 (3.51%) were true positives and contaminants were 47 (1.08%). Most of the blood cultures (99.27 %) grew within 72 h and 95.8% were isolated within 48 h. In 486 PBCs received from catheter/periphery (one each), catheter positivity was found in 85 (true positives were 48, false positives 37). In peripheral samples true positives were 50 and false positives were 8. Significantly higher positive rates were seen in PBCs compared with SBCs. Automated blood culture and identification methods significantly reduced the time required for processing of samples and also facilitated yield of diverse/rare organisms. Blood culture from catheter line had higher false positives than peripheral blood culture. Thus every positive result from a catheter must be correlated with clinical findings and requires further confirmation.
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.
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...
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.
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.
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
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...
Dinani, Soudabeh Taghian; Zekri, Maryam; Kamali, Marzieh
2015-01-01
Diabetes is considered as a global affecting disease with an increasing contribution to both mortality rate and cost damage in the society. Therefore, tight control of blood glucose levels has gained significant attention over the decades. This paper proposes a method for blood glucose level regulation in type 1 diabetics. The control strategy is based on combining the fuzzy logic theory and single order sliding mode control (SOSMC) to improve the properties of sliding mode control method and to alleviate its drawbacks. The aim of the proposed controller that is called SOSMC combined with fuzzy on-line tunable gain is to tune the gain of the controller adaptively. This merit causes a less amount of control effort, which is the rate of insulin delivered to the patient body. As a result, this method can decline the risk of hypoglycemia, a lethal phenomenon in regulating blood glucose level in diabetics caused by a low blood glucose level. Moreover, it attenuates the chattering observed in SOSMC significantly. It is worth noting that in this approach, a mathematical model called minimal model is applied instead of the intravenously infused insulin-blood glucose dynamics. The simulation results demonstrate a good performance of the proposed controller in meal disturbance rejection and robustness against parameter changes. In addition, this method is compared to fuzzy high-order sliding mode control (FHOSMC) and the superiority of the new method compared to FHOSMC is shown in the results.
Lagomarsino, Stefano; Sciortino, Silvio; Gelli, Nicla; Flatae, Assegid M.; Gorelli, Federico; Santoro, Mario; Chiari, Massimo; Czelusniac, Caroline; Massi, Mirko; Taccetti, Francesco; Agio, Mario; Giuntini, Lorenzo
2018-05-01
The line for the pulsed beam of the 3 MeV Tandetron accelerator at LABEC (Florence) has been upgraded for ion implantation experiments aiming at the fabrication of single-photon emitters in a solid-state matrix. A system based on Al attenuators has been calibrated in order to extend the energy range of the implanted ions from MeV down to the tens of keV. A new motorized XY stage has been installed in the implantation chamber for achieving ultra-fine control on the position of each implanted ion, allowing to reach the scale imposed by lateral straggling. A set-up for the activation of the implanted ions has been developed, based on an annealing furnace operating under controlled high-vacuum conditions. The first experiments have been performed with silicon ions implanted in diamond and the luminescent signal of the silicon-vacancy (SiV) center, peaked at 738 nm, has been observed for a wide range of implantation fluences (108 ÷ 1015 cm-2) and implantation depths (from a few nm to 2.4 μm). Studies on the efficiency of the annealing process have been performed and the activation yield has been measured to range from 1% to 3%. The implantation and annealing facility has thus been tuned for the production of SiV centers in diamond, but is in principle suitable for other ion species and solid-state matrices.
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
Steganalysis using logistic regression
Lubenko, Ivans; Ker, Andrew D.
2011-02-01
We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.
SEPARATION PHENOMENA LOGISTIC REGRESSION
Directory of Open Access Journals (Sweden)
Ikaro Daniel de Carvalho Barreto
2014-03-01
Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.
DEFF Research Database (Denmark)
Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas
2017-01-01
In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface......-product we obtain fast access to the baseline hazards (compared to survival::basehaz()) and predictions of survival probabilities, their confidence intervals and confidence bands. Confidence intervals and confidence bands are based on point-wise asymptotic expansions of the corresponding statistical...
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...
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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
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
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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
DEFF Research Database (Denmark)
Hansen, Henrik; Tarp, Finn
2001-01-01
This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy....... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes.......This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy...
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Dominic Simm
Full Text Available Stable single-alpha helices (SAH-domains function as rigid connectors and constant force springs between structural domains, and can provide contact surfaces for protein-protein and protein-RNA interactions. SAH-domains mainly consist of charged amino acids and are monomeric and stable in polar solutions, characteristics which distinguish them from coiled-coil domains and intrinsically disordered regions. Although the number of reported SAH-domains is steadily increasing, genome-wide analyses of SAH-domains in eukaryotic genomes are still missing. Here, we present Waggawagga-CLI, a command-line tool for predicting and analysing SAH-domains in protein sequence datasets. Using Waggawagga-CLI we predicted SAH-domains in 24 datasets from eukaryotes across the tree of life. SAH-domains were predicted in 0.5 to 3.5% of the protein-coding content per species. SAH-domains are particularly present in longer proteins supporting their function as structural building block in multi-domain proteins. In human, SAH-domains are mainly used as alternative building blocks not being present in all transcripts of a gene. Gene ontology analysis showed that yeast proteins with SAH-domains are particular enriched in macromolecular complex subunit organization, cellular component biogenesis and RNA metabolic processes, and that they have a strong nuclear and ribonucleoprotein complex localization and function in ribosome and nucleic acid binding. Human proteins with SAH-domains have roles in all types of RNA processing and cytoskeleton organization, and are predicted to function in RNA binding, protein binding involved in cell and cell-cell adhesion, and cytoskeletal protein binding. Waggawagga-CLI allows the user to adjust the stabilizing and destabilizing contribution of amino acid interactions in i,i+3 and i,i+4 spacings, and provides extensive flexibility for user-designed analyses.
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.
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Mohamed Said Abdelsalam
2018-01-01
Full Text Available Conventional hemodialysis (HD is the most common treatment modality used for renal replacement therapy. The concept of HD is based on the diffusion of solutes across a semipermeable membrane. Hemofiltration (HF is based on convective transport of solutes; hemodiafiltration (HDF is based on combined convective and diffusive therapies. Data about survival benefit of on-line HDF (OL-HDF over high-flux HD (HF-HD is conflicting. We conducted this study to investigate if there is a survival difference between the two treatment modalities. This study is a retrospective, single-center study in which 78 patients were screened; 18 were excluded and 60 patients were analyzed. The study patients were aged 47.5 ± 20.7 years, 33 patients (55% were on HF-HD, and 27 patients (45% were on OL-HDF. A total of 24 patients (40% of both groups were diabetic and, the mean duration on dialysis was 43.5 ±21.3 months in the HF-HD group and 41.2 ± 22.0 months in the OL-HDF group. The mean substitution volume for OL-HDF was 22.3 ± 2.5 L. Survival was 73% [95%, confidence interval (CI 60–84] in the HF-HD group and 65% (95%, CI 54–75 in the OL-HDF group by the end of the study period. The unadjusted hazard ratio (HR with 95% CI comparing HF-HD to high-volume postdilution OL-HDF was 0.78 (0.10–5.6; P = 0.810. Kaplan–Meier analysis for patient survival over five years showed no significant difference between the two modalities. Prospective controlled trials with a larger number of patients will be needed to assess the long-term clinical outcome of postdilution OL-HDF over HF-HD.
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.
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.
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.
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.
Regression in autistic spectrum disorders.
Stefanatos, Gerry A
2008-12-01
A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.
Sitnova, T. M.; Mashonkina, L. I.; Ryabchikova, T. A.
2016-09-01
We construct a model atom for Ti I-II using more than 3600 measured and predicted energy levels of Ti I and 1800 energy levels of Ti II, and quantum mechanical photoionization cross-sections. Non-local thermodynamical equilibrium (NLTE) line formation for Ti I and Ti II is treated through a wide range of spectral types from A to K, including metal-poor stars with [Fe/H] down to -2.6 dex. NLTE leads to weakened Ti I lines and positive abundance corrections. The magnitude of NLTE corrections is smaller compared to the literature data for FGK atmospheres. NLTE leads to strengthened Ti II lines and negative NLTE abundance corrections. For the first time, we have performed NLTE calculations for Ti I-II in the 6500 ≤ Teff ≤ 13 000 K range. For four A-type stars, we derived in LTE an abundance discrepancy of up to 0.22 dex between Ti I and Ti II, which vanishes in NLTE. For four other A-B stars, with only Ti II lines observed, NLTE leads to a decrease of line-to-line scatter. An efficiency of inelastic Ti I + H I collisions was estimated from an analysis of Ti I and Ti II lines in 17 cool stars with -2.6 ≤ [Fe/H] ≤ 0.0. Consistent NLTE abundances from Ti I and Ti II were obtained by applying classical Drawinian rates for the stars with log g ≥ 4.1, and neglecting inelastic collisions with H I for the very metal-poor (VMP) giant HD 122563. For the VMP turn-off stars ([Fe/H] ≤ -2 and log g ≤ 4.1), we obtained the positive abundance difference Ti I-II already in LTE, which increases in NLTE. Accurate collisional data for Ti I and Ti II are necessary to help solve this problem.
Time-adaptive quantile regression
DEFF Research Database (Denmark)
Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik
2008-01-01
and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....
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.
DEFF Research Database (Denmark)
Bak, Claus Leth; Søgaard, Kim
2008-01-01
400 kV power system and initiated by Danish TSO Energinet.dk after having measured the voltage of the cable/overhead line after disconnection. A particular decaying dynamic phase voltage containing voltages higher than the voltage before disconnection appeared. A simulation model for the entire system...
V. Surmont; J.G.J.V. Aerts (Joachim); K.Y. Tan; F.M.N.H. Schramel (Franz); R. Vernhout (Rene); H.C. Hoogsteden (Henk); R.J. van Klaveren (Rob)
2009-01-01
textabstractBackground. sequential chemotherapy can maintain dose intensity and preclude cumulative toxicity by increasing drug diversity. Purpose. to investigate the toxicity and efficacy of the sequential regimen of gemcitabine followed by paclitaxel in first line advanced stage non-small cell
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
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.
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
Panel Smooth Transition Regression Models
DEFF Research Database (Denmark)
González, Andrés; Terasvirta, Timo; Dijk, Dick van
We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...
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
Testing discontinuities in nonparametric regression
Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun
2017-01-01
In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100
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…
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).
International Nuclear Information System (INIS)
Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei
2007-01-01
Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age
Adamski,Tadeusz; Krystkowiak,Karolina; Kuczynska,Anetta; Mikolajczak,Krzysztof; Ogrodowicz,Piotr; Ponitka,Aleksandra; Surma,Maria; Slusarkiewicz-Jarzina,Aurelia
2014-01-01
Background: The quality of wheat grain depends on several characteristics, among which the composition of high molecular weight glutenin subunits, encoded by Glu-1 loci, are the most important. Application of biotechnological tools to accelerate the attainment of homozygous lines may influence the proportion of segregated genotypes. The objective was to determine, whether the selection pressure generated by the methods based on in vitro cultures, may cause a loss of genotypes with desirable G...
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
International Nuclear Information System (INIS)
Banini, G.K.
2005-01-01
Using a Renishaw Raman Microscope and a constructed mechanical apparatus, a novel method for determining the stress in the contact region between a ruby indenter and an MgO crystal under static contact lead is described. The experiment was performed under normal laboratory conditions at the Cavendish Laboratory, University of Cambridge, UK. Manual focusing using the white light on the microscope was made onto the ruby sphere and by replacing the light with a HeNe laser, luminescence frequency in the R-lines of chromium ions at the relaxed (unstressed) positions could be determined. The MgO crystal was then quasi-statically loaded by the ruby sphere, while in the mechanical loading apparatus, and placed on the Renishaw. Manual focusing onto the ruby sphere was made through the MgO and the shift in R-lines from the relaxed positions determined. Literature values of stress coefficients in ruby were used to convert the shifts determined in the R-lines into hydrostatic and non-hydrostatic stresses at precise intervals across the contact region. It was revealed that large stresses hydrostatic occur in the contact region during quasi-static loading and these can be quantified for transparent solids (au)
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)
Regression to Causality : Regression-style presentation influences causal attribution
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...
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
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....
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.
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.
Quantile Regression With Measurement Error
Wei, Ying; Carroll, Raymond J.
2009-01-01
. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a
Directory of Open Access Journals (Sweden)
Şeniz Öngören
2017-12-01
Full Text Available Objective: In this study, we retrospectively analyzed the clinical outcome, treatment responses, infectious complications, and survival rates of 71 hairy cell leukemia (HCL cases. Materials and Methods: Sixty-seven patients received a first-line treatment and 2-chlorodeoxyadenosine (cladribine-2-CdA was administered in 31 cases, 19 patients received interferon-alpha (INF-α, splenectomy was performed in 16 cases, and rituximab was used in one. Results: Although the highest overall response rate (ORR was observed in patients receiving 2-CdA upfront, ORRs were comparable in the 2-CdA, INF-α, and splenectomy subgroups. Relapse rates were significantly lower in patients who received first-line 2-CdA. The progression-free survival (PFS rate with 2-CdA was significantly higher than in patients with INF-α and splenectomy, but we found similar overall survival rates with all three upfront treatment modalities. Infections including tuberculosis were a major problem. Conclusion: Although purine analogues have improved the ORRs and PFS, there is still much progress to make with regard to overall survival and relapsed/refractory disease in patients with HCL.
Directory of Open Access Journals (Sweden)
V. Surmont
2009-01-01
Full Text Available Background. sequential chemotherapy can maintain dose intensity and preclude cumulative toxicity by increasing drug diversity. Purpose. to investigate the toxicity and efficacy of the sequential regimen of gemcitabine followed by paclitaxel in first line advanced stage non-small cell lung cancer (NSCLC patients with good performance status (PS. Patients and methods. gemcitabine 1250 mg/m2 was administered on day 1 and 8 of course 1 and 2; Paclitaxel 150 mg/m2 on day 1 and 8 of course 3 and 4. Primary endpoint was response rate (RR, secondary endpoints toxicity and time to progression (TTP. Results. Of the 21 patients (median age 56, range 38–80 years; 62% males, 38% females 10% (2/21 had stage IIIB, 90% (19/21 stage IV, 15% PS 0, 85% PS 1. 20% of patients had a partial response, 30% stable disease, 50% progressive disease. Median TTP was 12 weeks (range 6–52 weeks, median overall survival (OS 8 months (range 1–27 months, 1-year survival was 33%. One patient had grade 3 hematological toxicity, 2 patients a grade 3 peripheral neuropathy. Conclusions. sequential administration of gemcitabine followed by paclitaxel in first line treatment of advanced NSCLC had a favourable toxicity profile, a median TTP and OS comparable with other sequential trials and might , therefore, be a treatment option for NSCLC patients with high ERCC1 expression.
Dinani, Soudabeh Taghian; Zekri, Maryam; Kamali, Marzieh
2015-01-01
Diabetes is considered as a global affecting disease with an increasing contribution to both mortality rate and cost damage in the society. Therefore, tight control of blood glucose levels has gained significant attention over the decades. This paper proposes a method for blood glucose level regulation in type 1 diabetics. The control strategy is based on combining the fuzzy logic theory and single order sliding mode control (SOSMC) to improve the properties of sliding mode control method and...
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
International Nuclear Information System (INIS)
Arabei, S.M.; Kuzmitsky, V.A.; Solovyov, K.N.
2008-01-01
The quasi-line low-temperature (4.2 K) fluorescence excitation spectra of 2,3,12,13-tetramethyldibenzo[g,q]porphin introduced into an n-octane matrix have been measured in the range of the S 2 0 electronic transition at selective fluorescence monitoring for the two main types of impurity centers (sites). A characteristic feature of these spectra is that a conglomerate of quasi-lines - a structured complex band - is observed instead of one 0-0 quasi-line of the S 2 0 transition. In this band, the intensity distributions for the two main sites considerably differ from each other. The occurrence of such conglomerates is interpreted as a result of nonadiabatic vibrational-electronic interaction between the vibronic S 2 and S 1 states (the complex vibronic analogue of the Fermi resonance). The frequencies and intensities of individual transitions determined from the deconvolution of complex conglomerates are used as the initial data for solving the inverse spectroscopic problem: the determination of the unperturbed electronic and vibrational levels of states involved in the resonance and the vibronic-interaction matrix elements between them. This problem is solved with a method developed previously. The experimental results and their analysis are compared to the analogous data obtained earlier for meso-tetraazaporphin and meso-tetrapropylporphin. The energy intervals between the S 2 and S 1 electronic levels (ΔE S 2 S 1 ) of the two main types of impurity centers formed by molecules of a given porphyrin in the crystal matrix are found to significantly differ from each other, the values of this difference (δΔE S 2 S 1 ) being considerably greater for tetramethyldibenzoporphin, δΔE S 2 S 1 =228cm -1 , than for the two other porphyrins. At the same time, the energies of the unperturbed vibrational states of the S 1 electronic level participating in the resonance are very close to each other for these two sites
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.
Complex regression Doppler optical coherence tomography
Elahi, Sahar; Gu, Shi; Thrane, Lars; Rollins, Andrew M.; Jenkins, Michael W.
2018-04-01
We introduce a new method to measure Doppler shifts more accurately and extend the dynamic range of Doppler optical coherence tomography (OCT). The two-point estimate of the conventional Doppler method is replaced with a regression that is applied to high-density B-scans in polar coordinates. We built a high-speed OCT system using a 1.68-MHz Fourier domain mode locked laser to acquire high-density B-scans (16,000 A-lines) at high enough frame rates (˜100 fps) to accurately capture the dynamics of the beating embryonic heart. Flow phantom experiments confirm that the complex regression lowers the minimum detectable velocity from 12.25 mm / s to 374 μm / s, whereas the maximum velocity of 400 mm / s is measured without phase wrapping. Complex regression Doppler OCT also demonstrates higher accuracy and precision compared with the conventional method, particularly when signal-to-noise ratio is low. The extended dynamic range allows monitoring of blood flow over several stages of development in embryos without adjusting the imaging parameters. In addition, applying complex averaging recovers hidden features in structural images.
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.
Producing The New Regressive Left
DEFF Research Database (Denmark)
Crone, Christine
members, this thesis investigates a growing political trend and ideological discourse in the Arab world that I have called The New Regressive Left. On the premise that a media outlet can function as a forum for ideology production, the thesis argues that an analysis of this material can help to trace...... the contexture of The New Regressive Left. If the first part of the thesis lays out the theoretical approach and draws the contextual framework, through an exploration of the surrounding Arab media-and ideoscapes, the second part is an analytical investigation of the discourse that permeates the programmes aired...... becomes clear from the analytical chapters is the emergence of the new cross-ideological alliance of The New Regressive Left. This emerging coalition between Shia Muslims, religious minorities, parts of the Arab Left, secular cultural producers, and the remnants of the political,strategic resistance...
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
Directory of Open Access Journals (Sweden)
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.
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.
Correlation and simple linear regression.
Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G
2003-06-01
In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.
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.)
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.
Energy Technology Data Exchange (ETDEWEB)
Churchill, M.E.; Peak, J.G.; Peak, M.J. (Argonne National Lab., IL (USA))
1991-02-01
Cell survival parameters and the induction and repair of DNA single-strand breaks were measured in two Chinese hamster ovary cell lines after irradiation with monochromatic UVA radiation of wavelength 365 nm. The radiosensitive mutant cell line EM9 is known to repair ionizing-radiation-induced single-strand breaks (SSB) more slowly than the parent line AA8. EM9 was determined to be 1.7-fold more sensitive to killing by 365-nm radiation than AA8 at the 10% survival level, and EM9 had a smaller shoulder region on the survival curve ({alpha} = 1.76) than AA8 ({alpha} = 0.62). No significant differences were found between the cell lines in the initial yields of SSB induced either by {gamma}-radiation (as determined by alkaline sucrose gradient sedimentation) or by 365-nm UVA (as determined by alkaline elution). For measurement of initial SSB, cells were irradiated at 0.5{sup o}C to minimize DNA repair processes. Rejoining of 365-nm induced SSB was measured by irradiating cells at 0.5{sup o}C, allowing them to repair at 37{sup o}C in full culture medium, and then quantitating the remaining SSB by alkaline elution. The repair of these breaks followed biphasic kinetics in both cell lines. EM9 repaired the breaks more slowly (T{sub 1/2} values of 1.3 and 61.3 min) than did AA8 (T{sub 1/2} values of 0.9 and 53.3 min), and EM9 also left more breaks unrepaired 90 min after irradiation (24% vs 8% for AA8). Thus, the sensitivity of EM9 to 365-nm radiation correlated with its deficiency in repairing DNA lesions revealed as SSB in alkaline elution. These results suggest that DNA may be a critical target in 365-nm induced cellular lethality and that the ability of AA8 and EM9 cells to repair DNA strand breaks may be related to their ability to survive 365-nm radiation. (author).
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
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…
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
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
Kernel regression with functional response
Ferraty, Frédéric; Laksaci, Ali; Tadj, Amel; Vieu, Philippe
2011-01-01
We consider kernel regression estimate when both the response variable and the explanatory one are functional. The rates of uniform almost complete convergence are stated as function of the small ball probability of the predictor and as function of the entropy of the set on which uniformity is obtained.
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.
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.
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...
Directory of Open Access Journals (Sweden)
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.
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
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.
Multivariate and semiparametric kernel regression
Härdle, Wolfgang; Müller, Marlene
1997-01-01
The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...
Regression algorithm for emotion detection
Berthelon , Franck; Sander , Peter
2013-01-01
International audience; We present here two components of a computational system for emotion detection. PEMs (Personalized Emotion Maps) store links between bodily expressions and emotion values, and are individually calibrated to capture each person's emotion profile. They are an implementation based on aspects of Scherer's theoretical complex system model of emotion~\\cite{scherer00, scherer09}. We also present a regression algorithm that determines a person's emotional feeling from sensor m...
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
Polylinear regression analysis in radiochemistry
International Nuclear Information System (INIS)
Kopyrin, A.A.; Terent'eva, T.N.; Khramov, N.N.
1995-01-01
A number of radiochemical problems have been formulated in the framework of polylinear regression analysis, which permits the use of conventional mathematical methods for their solution. The authors have considered features of the use of polylinear regression analysis for estimating the contributions of various sources to the atmospheric pollution, for studying irradiated nuclear fuel, for estimating concentrations from spectral data, for measuring neutron fields of a nuclear reactor, for estimating crystal lattice parameters from X-ray diffraction patterns, for interpreting data of X-ray fluorescence analysis, for estimating complex formation constants, and for analyzing results of radiometric measurements. The problem of estimating the target parameters can be incorrect at certain properties of the system under study. The authors showed the possibility of regularization by adding a fictitious set of data open-quotes obtainedclose quotes from the orthogonal design. To estimate only a part of the parameters under consideration, the authors used incomplete rank models. In this case, it is necessary to take into account the possibility of confounding estimates. An algorithm for evaluating the degree of confounding is presented which is realized using standard software or regression analysis
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.
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
Simulation Experiments in Practice: Statistical Design and Regression Analysis
Kleijnen, J.P.C.
2007-01-01
In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic DOE and regression analysis assume a single simulation response that is normally and independen...
Energy Technology Data Exchange (ETDEWEB)
Revaz, B. [Geneva Univ. (Switzerland). Dept. de Physique de la Matiere Condensee; Triscone, G. [Geneva Univ. (Switzerland). Dept. de Physique de la Matiere Condensee; Fabrega, L. [Geneva Univ. (Switzerland). Dept. de Physique de la Matiere Condensee; Junod, A. [Geneva Univ. (Switzerland). Dept. de Physique de la Matiere Condensee; Muller, J. [Geneva Univ. (Switzerland). Dept. de Physique de la Matiere Condensee
1996-03-20
The mixed-state magnetization M(H parallel c, T) of a Bi-2212 single crystal has been investigated with high resolution using a SQUID magnetometer. In the high-temperature region (50 K < T < T{sub c} = 80.2 K), we found that the slope {partial_derivative}M/{partial_derivative}H vertical stroke {sub T} vs. H shows a positive step at H{sub trans}(T) {approx} H{sub 0} x (1 - T/T{sub c}){sup n} with H{sub 0} = 2340 Oe and n = 1.28. This observation is compatible with a first-order phase transition with a distribution of internal fields, and is attributed to the melting of the 3D vortex lattice. The estimated entropy jump is 1 k{sub B}/vortex/layer CuO. However, when T is lower than 50 K, we observe radical changes in M(H); the 3D melting line divides into a decoupling line at a temperature-independent field and the onset of the irreversibility. (orig.).
International Nuclear Information System (INIS)
Revaz, B.; Triscone, G.; Fabrega, L.; Junod, A.; Muller, J.
1996-01-01
The mixed-state magnetization M(H parallel c, T) of a Bi-2212 single crystal has been investigated with high resolution using a SQUID magnetometer. In the high-temperature region (50 K c = 80.2 K), we found that the slope ∂M/∂H vertical stroke T vs. H shows a positive step at H trans (T) ∼ H 0 x (1 - T/T c ) n with H 0 = 2340 Oe and n = 1.28. This observation is compatible with a first-order phase transition with a distribution of internal fields, and is attributed to the melting of the 3D vortex lattice. The estimated entropy jump is 1 k B /vortex/layer CuO. However, when T is lower than 50 K, we observe radical changes in M(H); the 3D melting line divides into a decoupling line at a temperature-independent field and the onset of the irreversibility. (orig.)
Spontaneous regression of pulmonary bullae
International Nuclear Information System (INIS)
Satoh, H.; Ishikawa, H.; Ohtsuka, M.; Sekizawa, K.
2002-01-01
The natural history of pulmonary bullae is often characterized by gradual, progressive enlargement. Spontaneous regression of bullae is, however, very rare. We report a case in which complete resolution of pulmonary bullae in the left upper lung occurred spontaneously. The management of pulmonary bullae is occasionally made difficult because of gradual progressive enlargement associated with abnormal pulmonary function. Some patients have multiple bulla in both lungs and/or have a history of pulmonary emphysema. Others have a giant bulla without emphysematous change in the lungs. Our present case had treated lung cancer with no evidence of local recurrence. He had no emphysematous change in lung function test and had no complaints, although the high resolution CT scan shows evidence of underlying minimal changes of emphysema. Ortin and Gurney presented three cases of spontaneous reduction in size of bulla. Interestingly, one of them had a marked decrease in the size of a bulla in association with thickening of the wall of the bulla, which was observed in our patient. This case we describe is of interest, not only because of the rarity with which regression of pulmonary bulla has been reported in the literature, but also because of the spontaneous improvements in the radiological picture in the absence of overt infection or tumor. Copyright (2002) Blackwell Science Pty Ltd
Quantum algorithm for linear regression
Wang, Guoming
2017-07-01
We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.
Interpretation of commonly used statistical regression models.
Kasza, Jessica; Wolfe, Rory
2014-01-01
A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.
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.
Conjoined legs: Sirenomelia or caudal regression syndrome?
Das, Sakti Prasad; Ojha, Niranjan; Ganesh, G Shankar; Mohanty, Ram Narayan
2013-07-01
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 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.
Least square regularized regression in sum space.
Xu, Yong-Li; Chen, Di-Rong; Li, Han-Xiong; Liu, Lu
2013-04-01
This paper proposes a least square regularized regression algorithm in sum space of reproducing kernel Hilbert spaces (RKHSs) for nonflat function approximation, and obtains the solution of the algorithm by solving a system of linear equations. This algorithm can approximate the low- and high-frequency component of the target function with large and small scale kernels, respectively. The convergence and learning rate are analyzed. We measure the complexity of the sum space by its covering number and demonstrate that the covering number can be bounded by the product of the covering numbers of basic RKHSs. For sum space of RKHSs with Gaussian kernels, by choosing appropriate parameters, we tradeoff the sample error and regularization error, and obtain a polynomial learning rate, which is better than that in any single RKHS. The utility of this method is illustrated with two simulated data sets and five real-life databases.
DEFF Research Database (Denmark)
Kiib, Hans
2015-01-01
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....... 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...
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.
Regression calibration with more surrogates than mismeasured variables
Kipnis, Victor; Midthune, Douglas; Freedman, Laurence S.; Carroll, Raymond J.
2012-01-01
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.
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...
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...
On Weighted Support Vector Regression
DEFF Research Database (Denmark)
Han, Xixuan; Clemmensen, Line Katrine Harder
2014-01-01
We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...... shrinks the coefficient of each observation in the estimated functions; thus, it is widely used for minimizing influence of outliers. We propose to additionally add weights to the slack variables in the constraints (CF‐weights) and call the combination of weights the doubly weighted SVR. We illustrate...... the differences and similarities of the two types of weights by demonstrating the connection between the Least Absolute Shrinkage and Selection Operator (LASSO) and the SVR. We show that an SVR problem can be transformed to a LASSO problem plus a linear constraint and a box constraint. We demonstrate...
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
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.
Credit Scoring Problem Based on Regression Analysis
Khassawneh, Bashar Suhil Jad Allah
2014-01-01
ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....
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.
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.
Bultas, Margaret W; Pohlman, Shawn
2014-01-01
The purpose of this interpretive phenomenological study was to gain a better understanding of the experiences of 11 mothers of preschool children with autism spectrum disorder (ASD). Mothers were interviewed three times over a 6 week period. Interviews were analyzed using interpretive methods. This manuscript highlights one particular theme-a positive perspective mothers described as the "silver lining." This "silver lining" represents optimism despite the adversities associated with parenting a child with ASD. A deeper understanding of this side of mothering children with ASD may help health care providers improve rapport, communication, and result in more authentic family centered care. Copyright © 2014 Elsevier Inc. All rights reserved.
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
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.
Spectral Line Shapes. Proceedings
International Nuclear Information System (INIS)
Zoppi, M.; Ulivi, L.
1997-01-01
These proceedings represent papers presented at the 13th International Conference on Spectral Line Shapes which was held in Firenze,Italy from June 16-21, 1996. The topics covered a wide range of subjects emphasizing the physical processes associated with the formation of line profiles: high and low density plasma; atoms and molecules in strong laser fields, Dopple-free and ultra-fine spectroscopy; the line shapes generated by the interaction of neutrals, atoms and molecules, where the relavant quantities are single particle properties, and the interaction-induced spectroscopy. There were 131 papers presented at the conference, out of these, 6 have been abstracted for the Energy Science and Technology database
International Nuclear Information System (INIS)
Fertil, B.; Deschavanne, P.J.; Lachet, B.; Malaise, E.P.
1980-01-01
The intrinsic radiosensitivity of human cell lines (five tumor and one nontransformed fibroblastic) was studied in vitro. The survival curves were fitted by the single-hit multitarget, the two-hit multitarget, the single-hit multitarget with initial slope, and the quadratic models. The accuracy of the experimental results permitted evaluation of the various fittings. Both a statistical test (comparison of variances left unexplained by the four models) and a biological consideration (check for independence of the fitted parameters vis-a-vis the portion of the survival curve in question) were carried out. The quadratic model came out best with each of them. It described the low-dose effects satisfactorily, revealing a single-hit lethal component. This finding and the fact that the six survival curves displayed a continuous curvature ruled out the adoption of the target models as well as the widely used linear regression. As calculated by the quadratic model, the parameters of the six cell lines lead to the following conclusions: (a) the intrinsic radiosensitivity varies greatly among the different cell lines; (b) the interpretation of the fibroblast survival curve is not basically different from that of the tumor cell lines; and (c) the radiosensitivity of these human cell lines is comparable to that of other mammalian cell lines
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; Wand, M.P.; Carroll, Raymond J.
2009-01-01
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.
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
Sirenomelia and severe caudal regression syndrome.
Seidahmed, Mohammed Z; Abdelbasit, Omer B; Alhussein, Khalid A; Miqdad, Abeer M; Khalil, Mohammed I; Salih, Mustafa A
2014-12-01
To describe cases of sirenomelia and severe caudal regression syndrome (CRS), to report the prevalence of sirenomelia, and compare our findings with the literature. Retrospective data was retrieved from the medical records of infants with the diagnosis of sirenomelia and CRS and their mothers from 1989 to 2010 (22 years) at the Security Forces Hospital, Riyadh, Saudi Arabia. A perinatologist, neonatologist, pediatric neurologist, and radiologist ascertained the diagnoses. The cases were identified as part of a study of neural tube defects during that period. A literature search was conducted using MEDLINE. During the 22-year study period, the total number of deliveries was 124,933 out of whom, 4 patients with sirenomelia, and 2 patients with severe forms of CRS were identified. All the patients with sirenomelia had single umbilical artery, and none were the infant of a diabetic mother. One patient was a twin, and another was one of triplets. The 2 patients with CRS were sisters, their mother suffered from type II diabetes mellitus and morbid obesity on insulin, and neither of them had a single umbilical artery. Other associated anomalies with sirenomelia included an absent radius, thumb, and index finger in one patient, Potter's syndrome, abnormal ribs, microphthalmia, congenital heart disease, hypoplastic lungs, and diaphragmatic hernia. The prevalence of sirenomelia (3.2 per 100,000) is high compared with the international prevalence of one per 100,000. Both cases of CRS were infants of type II diabetic mother with poor control, supporting the strong correlation of CRS and maternal diabetes.
Geographically weighted regression and multicollinearity: dispelling the myth
Fotheringham, A. Stewart; Oshan, Taylor M.
2016-10-01
Geographically weighted regression (GWR) extends the familiar regression framework by estimating a set of parameters for any number of locations within a study area, rather than producing a single parameter estimate for each relationship specified in the model. Recent literature has suggested that GWR is highly susceptible to the effects of multicollinearity between explanatory variables and has proposed a series of local measures of multicollinearity as an indicator of potential problems. In this paper, we employ a controlled simulation to demonstrate that GWR is in fact very robust to the effects of multicollinearity. Consequently, the contention that GWR is highly susceptible to multicollinearity issues needs rethinking.
Regression Analysis by Example. 5th Edition
Chatterjee, Samprit; Hadi, Ali S.
2012-01-01
Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…
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...
Spontaneous regression of a congenital melanocytic nevus
Directory of Open Access Journals (Sweden)
Amiya Kumar Nath
2011-01-01
Full Text Available Congenital melanocytic nevus (CMN may rarely regress which may also be associated with a halo or vitiligo. We describe a 10-year-old girl who presented with CMN on the left leg since birth, which recently started to regress spontaneously with associated depigmentation in the lesion and at a distant site. Dermoscopy performed at different sites of the regressing lesion demonstrated loss of epidermal pigments first followed by loss of dermal pigments. Histopathology and Masson-Fontana stain demonstrated lymphocytic infiltration and loss of pigment production in the regressing area. Immunohistochemistry staining (S100 and HMB-45, however, showed that nevus cells were present in the regressing areas.
Loughman, R. P.; Bhartia, P. K.; Moy, L.; Kramarova, N. A.; Wargan, K.
2016-12-01
Many remote sensing techniques used to monitor the Earth's upper atmosphere fall into the broad category of "limb viewing" (LV) measurements, which includes any method for which the line of sight (LOS) fails to intersect the surface. Occultation, limb emission and limb scattering (LS) measurements are all LV methods that offer strong sensitivity to changes in the atmosphere near the tangent point of the LOS, due to the enhanced geometric path through the tangent layer (where the concentration also typically peaks, for most atmospheric species). But many of the retrieval algorithms used to interpret LV measurements assume that the atmosphere consists of "spherical shells", in which the atmospheric properties vary only with altitude (creating a 1D atmosphere). This assumption simplifies the analysis, but at the possible price of misinterpreting measurements made in the real atmosphere. In this presentation, we focus on the problem of LOS inhomogeneity for LS measurements made by the OMPS Limb Profiler (LP) instrument during the 2015 ozone hole period. The GSLS radiative transfer model (RTM) used in the default OMPS LP algorithms assumes a spherical-shell atmosphere defined at levels spaced 1 km apart, with extinction coefficients assumed to vary linearly with height between levels. Several recent improvements enable an updated single-scattering version of the GSLS RTM to ingest 3D MERRA-2 analysis fields (including temperature, pressure, and ozone concentration) when creating the model atmosphere, by introducing flexible altitude grids, flexible atmospheric specification along the LOS, and improved treatment of the radiative transfer within each atmospheric layer. As a result, the effect of LOS inhomogeneity on the current (1D) OMPS LP retrieval algorithm can now be studied theoretically, using realistic 3D atmospheric profiles. This work also represents a step towards enabling OMPS LP data to be ingested as part of future data assimilation efforts.
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.
Rapid line scan MR angiography
International Nuclear Information System (INIS)
Frahm, J.; Merboldt, K.D.; Hanicke, W.; Bruhn, H.
1987-01-01
Direct MR angiography may be performed using line scan imaging techniques combined with presaturation of stationary spins. Thus, a single line scan echo yields a projection of vessels due to the signal from reflowing unsaturated spins. Reconstruction of an angiographic image is performed line by line at slightly incremented positions. In particular, line scan angiography is direct and fast without a sensitivity to artifacts even for high flow rates. Image resolution and field of view may be chosen without restrictions, and zoom images using enhanced gradients may be recorded without aliasing artifacts. The method is robust with respect to eddy currents and pulsatile flow. Line scan MR angiograms of phantoms, animals, and human volunteers have been recorded using 90 0 radio frequency pulses and gradient-recalled echoes
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.
Miyake, Kentaro; Murakami, Takashi; Kiyuna, Tasuku; Igarashi, Kentaro; Kawaguchi, Kei; Miyake, Masuyo; Li, Yunfeng; Nelson, Scott D; Dry, Sarah M; Bouvet, Michael; Elliott, Irmina A; Russell, Tara A; Singh, Arun S; Eckardt, Mark A; Hiroshima, Yukihiko; Momiyama, Masashi; Matsuyama, Ryusei; Chishima, Takashi; Endo, Itaru; Eilber, Fritz C; Hoffman, Robert M
2017-11-28
The aim of the present study was to determine the usefulness of a patient-derived orthotopic xenograft (PDOX) nude-mouse model of a doxorubicin-resistant metastatic Ewing's sarcoma, with a unique combination of a FUS-ERG fusion and CDKN2A deletion, to identify effective drugs for third-line chemotherapy of the patient. Our previous study showed that cyclin-dependent kinase 4/6 (CDK4/6) and insulin-like growth factor-1 receptor (IGF-1R) inhibitors were effective on the Ewing's sarcoma PDOX, but not doxorubicin, similar to the patient's resistance to doxorubicin. The results of the previous PDOX study were successfully used for second-line therapy of the patiend. In the present study, the PDOX mice established with the Ewing's sarcoma in the right chest wall were randomized into 5 groups when the tumor volume reached 60 mm 3 : untreated control; gemcitabine combined with docetaxel (intraperitoneal [i.p.] injection, weekly, for 2 weeks); irinotecan combined with temozolomide (irinotecan: i.p. injection; temozolomide: oral administration, daily, for 2 weeks); pazopanib (oral administration, daily, for 2 weeks); yondelis (intravenous injection, weekly, for 2 weeks). All mice were sacrificed on day 15. Body weight and tumor volume were assessed 2 times per week. Tumor weight was measured after sacrifice. Irinotecan combined with temozolomide was the most effective regimen compared to the untreated control group (p=0.022). Gemcitabine combined with docetaxel was also effective (p=0.026). Pazopanib and yondelis did not have significant efficacy compared to the untreated control (p=0.130, p=0.818). These results could be obtained within two months after the physician's request and were used for third-line therapy of the patient.
Semiempirical formulas for single-particle energies of neutrons and protons
International Nuclear Information System (INIS)
Lodhi, M.A.K.; Waak, B.T.
1978-01-01
The stepwise multiple linear regression technique has been used to analyze the single-particle energies of neutrons and protons in nuclei along the line of beta stability. Their regular and systematic trends lead to semiempirical model-independent formulas for single-particle energies of neutrons and protons in the bound nuclei as functions of nuclear parameters A and Z for given states specified by nl/sub j/. These formulas are almost as convenient as the harmonic oscillator energy formulas to use. The single-particle energies computed from these formulas have been compared with the experimental data and are found in reasonable agreement
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.
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.
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.
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...
International Nuclear Information System (INIS)
Dyar, M.D.; Carmosino, M.L.; Breves, E.A.; Ozanne, M.V.; Clegg, S.M.; Wiens, R.C.
2012-01-01
A remote laser-induced breakdown spectrometer (LIBS) designed to simulate the ChemCam instrument on the Mars Science Laboratory Rover Curiosity was used to probe 100 geologic samples at a 9-m standoff distance. ChemCam consists of an integrated remote LIBS instrument that will probe samples up to 7 m from the mast of the rover and a remote micro-imager (RMI) that will record context images. The elemental compositions of 100 igneous and highly-metamorphosed rocks are determined with LIBS using three variations of multivariate analysis, with a goal of improving the analytical accuracy. Two forms of partial least squares (PLS) regression are employed with finely-tuned parameters: PLS-1 regresses a single response variable (elemental concentration) against the observation variables (spectra, or intensity at each of 6144 spectrometer channels), while PLS-2 simultaneously regresses multiple response variables (concentrations of the ten major elements in rocks) against the observation predictor variables, taking advantage of natural correlations between elements. Those results are contrasted with those from the multivariate regression technique of the least absolute shrinkage and selection operator (lasso), which is a penalized shrunken regression method that selects the specific channels for each element that explain the most variance in the concentration of that element. To make this comparison, we use results of cross-validation and of held-out testing, and employ unscaled and uncentered spectral intensity data because all of the input variables are already in the same units. Results demonstrate that the lasso, PLS-1, and PLS-2 all yield comparable results in terms of accuracy for this dataset. However, the interpretability of these methods differs greatly in terms of fundamental understanding of LIBS emissions. PLS techniques generate principal components, linear combinations of intensities at any number of spectrometer channels, which explain as much variance in the
Energy Technology Data Exchange (ETDEWEB)
Dyar, M.D., E-mail: mdyar@mtholyoke.edu [Dept. of Astronomy, Mount Holyoke College, 50 College St., South Hadley, MA 01075 (United States); Carmosino, M.L.; Breves, E.A.; Ozanne, M.V. [Dept. of Astronomy, Mount Holyoke College, 50 College St., South Hadley, MA 01075 (United States); Clegg, S.M.; Wiens, R.C. [Los Alamos National Laboratory, P.O. Box 1663, MS J565, Los Alamos, NM 87545 (United States)
2012-04-15
A remote laser-induced breakdown spectrometer (LIBS) designed to simulate the ChemCam instrument on the Mars Science Laboratory Rover Curiosity was used to probe 100 geologic samples at a 9-m standoff distance. ChemCam consists of an integrated remote LIBS instrument that will probe samples up to 7 m from the mast of the rover and a remote micro-imager (RMI) that will record context images. The elemental compositions of 100 igneous and highly-metamorphosed rocks are determined with LIBS using three variations of multivariate analysis, with a goal of improving the analytical accuracy. Two forms of partial least squares (PLS) regression are employed with finely-tuned parameters: PLS-1 regresses a single response variable (elemental concentration) against the observation variables (spectra, or intensity at each of 6144 spectrometer channels), while PLS-2 simultaneously regresses multiple response variables (concentrations of the ten major elements in rocks) against the observation predictor variables, taking advantage of natural correlations between elements. Those results are contrasted with those from the multivariate regression technique of the least absolute shrinkage and selection operator (lasso), which is a penalized shrunken regression method that selects the specific channels for each element that explain the most variance in the concentration of that element. To make this comparison, we use results of cross-validation and of held-out testing, and employ unscaled and uncentered spectral intensity data because all of the input variables are already in the same units. Results demonstrate that the lasso, PLS-1, and PLS-2 all yield comparable results in terms of accuracy for this dataset. However, the interpretability of these methods differs greatly in terms of fundamental understanding of LIBS emissions. PLS techniques generate principal components, linear combinations of intensities at any number of spectrometer channels, which explain as much variance in the
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.
Regression models of reactor diagnostic signals
International Nuclear Information System (INIS)
Vavrin, J.
1989-01-01
The application is described of an autoregression model as the simplest regression model of diagnostic signals in experimental analysis of diagnostic systems, in in-service monitoring of normal and anomalous conditions and their diagnostics. The method of diagnostics is described using a regression type diagnostic data base and regression spectral diagnostics. The diagnostics is described of neutron noise signals from anomalous modes in the experimental fuel assembly of a reactor. (author)
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…
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.
Multivariate Regression Analysis and Slaughter Livestock,
AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY
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.
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.
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
RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,
This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)
A Simulation Investigation of Principal Component Regression.
Allen, David E.
Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…
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
Categorical regression dose-response modeling
The goal of this training is to provide participants with training on the use of the U.S. EPA’s Categorical Regression soft¬ware (CatReg) and its application to risk assessment. Categorical regression fits mathematical models to toxicity data that have been assigned ord...
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
Stepwise versus Hierarchical Regression: Pros and Cons
Lewis, Mitzi
2007-01-01
Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…
Suppression Situations in Multiple Linear Regression
Shieh, Gwowen
2006-01-01
This article proposes alternative expressions for the two most prevailing definitions of suppression without resorting to the standardized regression modeling. The formulation provides a simple basis for the examination of their relationship. For the two-predictor regression, the author demonstrates that the previous results in the literature are…
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...
Regression Analysis and the Sociological Imagination
De Maio, Fernando
2014-01-01
Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.
Repeated Results Analysis for Middleware Regression Benchmarking
Czech Academy of Sciences Publication Activity Database
Bulej, Lubomír; Kalibera, T.; Tůma, P.
2005-01-01
Roč. 60, - (2005), s. 345-358 ISSN 0166-5316 R&D Projects: GA ČR GA102/03/0672 Institutional research plan: CEZ:AV0Z10300504 Keywords : middleware benchmarking * regression benchmarking * regression testing Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.756, year: 2005
Principles of Quantile Regression and an Application
Chen, Fang; Chalhoub-Deville, Micheline
2014-01-01
Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…
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
Regression of environmental noise in LIGO data
International Nuclear Information System (INIS)
Tiwari, V; Klimenko, S; Mitselmakher, G; Necula, V; Drago, M; Prodi, G; Frolov, V; Yakushin, I; Re, V; Salemi, F; Vedovato, G
2015-01-01
We address the problem of noise regression in the output of gravitational-wave (GW) interferometers, using data from the physical environmental monitors (PEM). The objective of the regression analysis is to predict environmental noise in the GW channel from the PEM measurements. One of the most promising regression methods is based on the construction of Wiener–Kolmogorov (WK) filters. Using this method, the seismic noise cancellation from the LIGO GW channel has already been performed. In the presented approach the WK method has been extended, incorporating banks of Wiener filters in the time–frequency domain, multi-channel analysis and regulation schemes, which greatly enhance the versatility of the regression analysis. Also we present the first results on regression of the bi-coherent noise in the LIGO data. (paper)
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.
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.
VT Digital Line Graph Miscellaneous Transmission Lines
Vermont Center for Geographic Information — (Link to Metadata) This datalayer is comprised of Miscellaineous Transmission Lines. Digital line graph (DLG) data are digital representations of cartographic...
Puz, Przemysław; Lasek-Bal, Anetta
2016-11-10
BACKGROUND In Poland, natalizumab or fingolimod treatment can be delivered as a second-line therapy to those patients with relapsing-remitting multiple sclerosis (RRMS) who demonstrated no response to interferon or glatiramer acetate treatment for a minimum of one year. MATERIAL AND METHODS Analysis covered 44 RRMS patients switched from first- to second-line therapy. The annualized relapse rate, disability progression (assessed with Expanded Disability Status Scale, EDSS) and MRI results (new or enlarged T2 lesions and new Gd-positive lesions) before and after switching were compared. The occurrence of adverse events was also assessed. RESULTS The annualized relapse rate for second-line therapy was significantly lower than for first-line therapy (0.35±0.74 vs. 2.13±0.87, p=0.00005). Median of EDSS progression with first-line therapy was significantly higher than that with natalizumab or fingolimod treatment (p=0.00002). The mean number of new or enlarged T2 and Gd+ lesions in MRI after one-year second-line treatment was significantly lower in comparison to lesions in MRI performed at the end of the first-line therapy (for T2: 0.61 vs. 4.56, p=0.0004; for Gd+: 0.13 vs. 1.98, p=0.0009). No significant differences in the clinical data, MRI results, and side effects between fingolimod and natalizumab patients have been observed. CONCLUSIONS Treatment with natalizumab or fingolimod as a second-line therapy in RRMS patients is safe and effective. Less restrictive criteria for switching should be considered.
Lowery, Caitlin D; VanWye, Alle B; Dowless, Michele; Blosser, Wayne; Falcon, Beverly L; Stewart, Julie; Stephens, Jennifer; Beckmann, Richard P; Bence Lin, Aimee; Stancato, Louis F
2017-08-01
Purpose: Checkpoint kinase 1 (CHK1) is a key regulator of the DNA damage response and a mediator of replication stress through modulation of replication fork licensing and activation of S and G 2 -M cell-cycle checkpoints. We evaluated prexasertib (LY2606368), a small-molecule CHK1 inhibitor currently in clinical testing, in multiple preclinical models of pediatric cancer. Following an initial assessment of prexasertib activity, this study focused on the preclinical models of neuroblastoma. Experimental Design: We evaluated the antiproliferative activity of prexasertib in a panel of cancer cell lines; neuroblastoma cell lines were among the most sensitive. Subsequent Western blot and immunofluorescence analyses measured DNA damage and DNA repair protein activation. Prexasertib was investigated in several cell line-derived xenograft mouse models of neuroblastoma. Results: Within 24 hours, single-agent prexasertib promoted γH2AX-positive double-strand DNA breaks and phosphorylation of DNA damage sensors ATM and DNA-PKcs, leading to neuroblastoma cell death. Knockdown of CHK1 and/or CHK2 by siRNA verified that the double-strand DNA breaks and cell death elicited by prexasertib were due to specific CHK1 inhibition. Neuroblastoma xenografts rapidly regressed following prexasertib administration, independent of starting tumor volume. Decreased Ki67 and increased immunostaining of endothelial and pericyte markers were observed in xenografts after only 6 days of exposure to prexasertib, potentially indicating a swift reduction in tumor volume and/or a direct effect on tumor vasculature. Conclusions: Overall, these data demonstrate that prexasertib is a specific inhibitor of CHK1 in neuroblastoma and leads to DNA damage and cell death in preclinical models of this devastating pediatric malignancy. Clin Cancer Res; 23(15); 4354-63. ©2017 AACR . ©2017 American Association for Cancer Research.
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.
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...
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
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 correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its 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.
A tangent subsolar merging line
International Nuclear Information System (INIS)
Crooker, N.U.; Siscoe, G.L.; Toffoletto, F.R.
1990-01-01
The authors describe a global magnetospheric model with a single subsolar merging line whose position is determined neither locally by the relative orientations and strengths of the merging fields nor globally by the orientation of a separator line--the governing parameters of most previous models--but by the condition of tangential contact between the external field and the magnetopause. As in previous models, the tilt of the merging line varies with IMF orientation, but here it also depends upon the ratio of Earth's magnetic flux that leaks out of the magnetopause to IMF flux that penetrates in. In the limiting case treated by Alekseyev and Belen'kaya, with no leakage of Earth's field and total IMF penetration, the merging line forms a great circle around a spherical magnetosphere where undeviated IMF lines lie tangent to its surface. This tangent merging line lies perpendicular to the IMF. They extend their work to the case of finite leakage and partial penetration, which distort the IMF into a draped pattern, thus changing the locus of tangency to the sphere. In the special case where the penetrating IMF flux is balanced by an equal amount of Earth flux leakage, the tangent merging line bisects the angle between the IMF and Earth's northward subsolar field. This result is identical to the local merging line model result for merging fields with equal magnitude. Here a global flux balance condition replaces the local equal magnitude condition
The U-line line balancing problem
Miltenburg, G.J.; Wijngaard, J.
1994-01-01
The traditional line balancing (LB) problem considers a production line in which stations are arranged consecutively in a line. A balance is determined by grouping tasks into stations while moving forward (or backward) through a precedence network. Recently many production lines are being arranged
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
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...
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 should be used in model selection. PMID:28638214
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.
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
There is No Quantum Regression Theorem
International Nuclear Information System (INIS)
Ford, G.W.; OConnell, R.F.
1996-01-01
The Onsager regression hypothesis states that the regression of fluctuations is governed by macroscopic equations describing the approach to equilibrium. It is here asserted that this hypothesis fails in the quantum case. This is shown first by explicit calculation for the example of quantum Brownian motion of an oscillator and then in general from the fluctuation-dissipation theorem. It is asserted that the correct generalization of the Onsager hypothesis is the fluctuation-dissipation theorem. copyright 1996 The American Physical Society
Caudal regression syndrome : a case report
International Nuclear Information System (INIS)
Lee, Eun Joo; Kim, Hi Hye; Kim, Hyung Sik; Park, So Young; Han, Hye Young; Lee, Kwang Hun
1998-01-01
Caudal regression syndrome is a rare congenital anomaly, which results from a developmental failure of the caudal mesoderm during the fetal period. We present a case of caudal regression syndrome composed of a spectrum of anomalies including sirenomelia, dysplasia of the lower lumbar vertebrae, sacrum, coccyx and pelvic bones,genitourinary and anorectal anomalies, and dysplasia of the lung, as seen during infantography and MR imaging
Caudal regression syndrome : a case report
Energy Technology Data Exchange (ETDEWEB)
Lee, Eun Joo; Kim, Hi Hye; Kim, Hyung Sik; Park, So Young; Han, Hye Young; Lee, Kwang Hun [Chungang Gil Hospital, Incheon (Korea, Republic of)
1998-07-01
Caudal regression syndrome is a rare congenital anomaly, which results from a developmental failure of the caudal mesoderm during the fetal period. We present a case of caudal regression syndrome composed of a spectrum of anomalies including sirenomelia, dysplasia of the lower lumbar vertebrae, sacrum, coccyx and pelvic bones,genitourinary and anorectal anomalies, and dysplasia of the lung, as seen during infantography and MR imaging.
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.
Forecasting exchange rates: a robust regression approach
Preminger, Arie; Franck, Raphael
2005-01-01
The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...
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.
Marginal longitudinal semiparametric regression via penalized splines
Al Kadiri, M.; Carroll, R.J.; Wand, M.P.
2010-01-01
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.
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
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
Post-processing through linear regression
van Schaeybroeck, B.; Vannitsem, S.
2011-03-01
Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.
Post-processing through linear regression
Directory of Open Access Journals (Sweden)
B. Van Schaeybroeck
2011-03-01
Full Text Available Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS method, a new time-dependent Tikhonov regularization (TDTR method, the total least-square method, a new geometric-mean regression (GM, a recently introduced error-in-variables (EVMOS method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified.
These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise. At long lead times the regression schemes (EVMOS, TDTR which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.
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...... 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...
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.
Virtual machine consolidation enhancement using hybrid regression algorithms
Directory of Open Access Journals (Sweden)
Amany Abdelsamea
2017-11-01
Full Text Available Cloud computing data centers are growing rapidly in both number and capacity to meet the increasing demands for highly-responsive computing and massive storage. Such data centers consume enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions. The reason for this extremely high energy consumption is not just the quantity of computing resources and the power inefficiency of hardware, but rather lies in the inefficient usage of these resources. VM consolidation involves live migration of VMs hence the capability of transferring a VM between physical servers with a close to zero down time. It is an effective way to improve the utilization of resources and increase energy efficiency in cloud data centers. VM consolidation consists of host overload/underload detection, VM selection and VM placement. Most of the current VM consolidation approaches apply either heuristic-based techniques, such as static utilization thresholds, decision-making based on statistical analysis of historical data; or simply periodic adaptation of the VM allocation. Most of those algorithms rely on CPU utilization only for host overload detection. In this paper we propose using hybrid factors to enhance VM consolidation. Specifically we developed a multiple regression algorithm that uses CPU utilization, memory utilization and bandwidth utilization for host overload detection. The proposed algorithm, Multiple Regression Host Overload Detection (MRHOD, significantly reduces energy consumption while ensuring a high level of adherence to Service Level Agreements (SLA since it gives a real indication of host utilization based on three parameters (CPU, Memory, Bandwidth utilizations instead of one parameter only (CPU utilization. Through simulations we show that our approach reduces power consumption by 6 times compared to single factor algorithms using random workload. Also using PlanetLab workload traces we show that MRHOD improves
Regression analysis using dependent Polya trees.
Schörgendorfer, Angela; Branscum, Adam J
2013-11-30
Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.
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.
Learning Supervised Topic Models for Classification and Regression from Crowds
DEFF Research Database (Denmark)
Rodrigues, Filipe; Lourenco, Mariana; Ribeiro, Bernardete
2017-01-01
problems, which account for the heterogeneity and biases among different annotators that are encountered in practice when learning from crowds. We develop an efficient stochastic variational inference algorithm that is able to scale to very large datasets, and we empirically demonstrate the advantages...... annotation tasks, prone to ambiguity and noise, often with high volumes of documents, deem learning under a single-annotator assumption unrealistic or unpractical for most real-world applications. In this article, we propose two supervised topic models, one for classification and another for regression...
26 CFR 1.132-4 - Line of business limitation.
2010-04-01
... athletic facilities. (iii) Performance of substantial services in more than one line of business. An... one line of business, such lines of business will be treated as a single line of business where and to... business. For example, assume that on the same premises an employer sells both women's apparel and jewelry...
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.
Refractive regression after laser in situ keratomileusis.
Yan, Mabel K; Chang, John Sm; Chan, Tommy Cy
2018-04-26
Uncorrected refractive errors are a leading cause of visual impairment across the world. In today's society, laser in situ keratomileusis (LASIK) has become the most commonly performed surgical procedure to correct refractive errors. However, regression of the initially achieved refractive correction has been a widely observed phenomenon following LASIK since its inception more than two decades ago. Despite technological advances in laser refractive surgery and various proposed management strategies, post-LASIK regression is still frequently observed and has significant implications for the long-term visual performance and quality of life of patients. This review explores the mechanism of refractive regression after both myopic and hyperopic LASIK, predisposing risk factors and its clinical course. In addition, current preventative strategies and therapies are also reviewed. © 2018 Royal Australian and New Zealand College of Ophthalmologists.
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.
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 ...
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 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
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
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
KELEŞ, Taliha; ALTUN, Murat
2016-01-01
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 wa...
Method for nonlinear exponential regression analysis
Junkin, B. G.
1972-01-01
Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.
Measurement Error in Education and Growth Regressions
Portela, Miguel; Alessie, Rob; Teulings, Coen
2010-01-01
The use of the perpetual inventory method for the construction of education data per country leads to systematic measurement error. This paper analyzes its effect on growth regressions. We suggest a methodology for correcting this error. The standard attenuation bias suggests that using these
The M Word: Multicollinearity in Multiple Regression.
Morrow-Howell, Nancy
1994-01-01
Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…
Regression Discontinuity Designs Based on Population Thresholds
DEFF Research Database (Denmark)
Eggers, Andrew C.; Freier, Ronny; Grembi, Veronica
In many countries, important features of municipal government (such as the electoral system, mayors' salaries, and the number of councillors) depend on whether the municipality is above or below arbitrary population thresholds. Several papers have used a regression discontinuity design (RDD...
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)
Targeting: Logistic Regression, Special Cases and Extensions
Directory of Open Access Journals (Sweden)
Helmut Schaeben
2014-12-01
Full Text Available Logistic regression is a classical linear model for logit-transformed conditional probabilities of a binary target variable. It recovers the true conditional probabilities if the joint distribution of predictors and the target is of log-linear form. Weights-of-evidence is an ordinary logistic regression with parameters equal to the differences of the weights of evidence if all predictor variables are discrete and conditionally independent given the target variable. The hypothesis of conditional independence can be tested in terms of log-linear models. If the assumption of conditional independence is violated, the application of weights-of-evidence does not only corrupt the predicted conditional probabilities, but also their rank transform. Logistic regression models, including the interaction terms, can account for the lack of conditional independence, appropriate interaction terms compensate exactly for violations of conditional independence. Multilayer artificial neural nets may be seen as nested regression-like models, with some sigmoidal activation function. Most often, the logistic function is used as the activation function. If the net topology, i.e., its control, is sufficiently versatile to mimic interaction terms, artificial neural nets are able to account for violations of conditional independence and yield very similar results. Weights-of-evidence cannot reasonably include interaction terms; subsequent modifications of the weights, as often suggested, cannot emulate the effect of interaction terms.
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.
Regression testing Ajax applications : Coping with dynamism
Roest, D.; Mesbah, A.; Van Deursen, A.
2009-01-01
Note: This paper is a pre-print of: Danny Roest, Ali Mesbah and Arie van Deursen. Regression Testing AJAX Applications: Coping with Dynamism. In Proceedings of the 3rd International Conference on Software Testing, Verification and Validation (ICST’10), Paris, France. IEEE Computer Society, 2010.
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
Functional data analysis of generalized regression quantiles
Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl
2013-01-01
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.
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...
Function approximation with polynomial regression slines
International Nuclear Information System (INIS)
Urbanski, P.
1996-01-01
Principles of the polynomial regression splines as well as algorithms and programs for their computation are presented. The programs prepared using software package MATLAB are generally intended for approximation of the X-ray spectra and can be applied in the multivariate calibration of radiometric gauges. (author)
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.
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…
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,
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…
Fast multi-output relevance vector regression
Ha, Youngmin
2017-01-01
This paper aims to decrease the time complexity of multi-output relevance vector regression from O(VM^3) to O(V^3+M^3), where V is the number of output dimensions, M is the number of basis functions, and V
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 ...
Superquantile Regression: Theory, Algorithms, and Applications
2014-12-01
Highway, Suite 1204, Arlington, Va 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1...Navy submariners, reliability engineering, uncertainty quantification, and financial risk management . Superquantile, superquantile regression...Royset Carlos F. Borges Associate Professor of Operations Research Dissertation Supervisor Professor of Applied Mathematics Lyn R. Whitaker Javier
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
Panel data specifications in nonparametric kernel regression
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...
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 ...
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…
Regression of an atlantoaxial rheumatoid pannus following posterior instrumented fusion.
Bydon, Mohamad; Macki, Mohamed; Qadi, Mohamud; De la Garza-Ramos, Rafael; Kosztowski, Thomas A; Sciubba, Daniel M; Wolinsky, Jean-Paul; Witham, Timothy F; Gokaslan, Ziya L; Bydon, Ali
2015-10-01
Rheumatoid patients may develop a retrodental lesion (atlantoaxial rheumatoid pannus) that may cause cervical instability and/or neurological compromise. The objective is to characterize clinical and radiographic outcomes after posterior instrumented fusion for atlantoaxial rheumatoid pannus. We retrospectively reviewed all patients who underwent posterior fusions for an atlantoaxial rheumatoid pannus at a single institution. Both preoperative and postoperative imaging was available for all patients. Anterior or circumferential operations, non-atlantoaxial panni, or prior C1-C2 operations were excluded. Primary outcome measures included Nurick score, Ranawat score (neurologic status in patients with rheumatoid arthritis), pannus regression, and reoperation. Pannus volume was determined with axial and sagittal views on both preoperative and postoperative radiological images. Thirty patients surgically managed for an atlantoaxial rheumatoid pannus were followed for a mean of 24.43 months. Nine patients underwent posterior instrumented fusion alone, while 21 patients underwent posterior decompression and instrumented fusion. Following a posterior instrumented fusion in all 30 patients, the pannus statistically significantly regressed by 44.44%, from a mean volume of 1.26cm(3) to 0.70cm(3) (ppannus radiographically regressed by 44.44% over a mean of 8.02 months, and patients clinically improved per the Nurick score. The Ranawat score did not improve, and 20% of patients required reoperation over a mean of 13.18 months. The annualized reoperation rate was approximately 13.62%. Copyright © 2015 Elsevier B.V. All rights reserved.
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.
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.
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.
Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun
2014-12-01
Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.
Revised Line Profile Function for Hydrogenic Species
Directory of Open Access Journals (Sweden)
Sapar A.
2012-09-01
Full Text Available Analytical series expansions for the hydrogenic spectral line profile functions are derived starting from the three single expressions, obtained by integrating twice the convolution of the Holtsmark, Lorentz and Doppler line profile functions. We get well converging series expansions for the line wings and centers by reducing the number of arguments in the profile function by one, introducing the module of the Holtsmark and Lorentz profiles as a new argument. In the intermediate part of the line, the parabolic cylinder functions expressed via the confluent hypergeometric series, are used. The multi-component Stark splitting of the hydrogenic spectral lines and the modeled stochastic electron transitions in the electric field of the adjacent ions generate wide Doppler plateaux at the line centers, with the characteristic widths estimated from the fit to the characteristic width of the Holtsmark profile. This additional Doppler broadening of the line profile function removes the central dip typical to the Holtsmark profile.
Incentive-Compatible Robust Line Planning
Bessas, Apostolos; Kontogiannis, Spyros; Zaroliagis, Christos
The problem of robust line planning requests for a set of origin-destination paths (lines) along with their frequencies in an underlying railway network infrastructure, which are robust to fluctuations of real-time parameters of the solution. In this work, we investigate a variant of robust line planning stemming from recent regulations in the railway sector that introduce competition and free railway markets, and set up a new application scenario: there is a (potentially large) number of line operators that have their lines fixed and operate as competing entities issuing frequency requests, while the management of the infrastructure itself remains the responsibility of a single entity, the network operator. The line operators are typically unwilling to reveal their true incentives, while the network operator strives to ensure a fair (or socially optimal) usage of the infrastructure, e.g., by maximizing the (unknown to him) aggregate incentives of the line operators.
Controlling attribute effect in linear regression
Calders, Toon; Karim, Asim A.; Kamiran, Faisal; Ali, Wasif Mohammad; Zhang, Xiangliang
2013-01-01
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.
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...... the Method of Moments procedure that matches known constraints on moments of the observations conditional on the latent variables. The performance of the model is investigated in a simulation example using data on finite dimensional landmark manifolds....
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.
Testing homogeneity in Weibull-regression models.
Bolfarine, Heleno; Valença, Dione M
2005-10-01
In survival studies with families or geographical units it may be of interest testing whether such groups are homogeneous for given explanatory variables. In this paper we consider score type tests for group homogeneity based on a mixing model in which the group effect is modelled as a random variable. As opposed to hazard-based frailty models, this model presents survival times that conditioned on the random effect, has an accelerated failure time representation. The test statistics requires only estimation of the conventional regression model without the random effect and does not require specifying the distribution of the random effect. The tests are derived for a Weibull regression model and in the uncensored situation, a closed form is obtained for the test statistic. A simulation study is used for comparing the power of the tests. The proposed tests are applied to real data sets with censored data.
Are increases in cigarette taxation regressive?
Borren, P; Sutton, M
1992-12-01
Using the latest published data from Tobacco Advisory Council surveys, this paper re-evaluates the question of whether or not increases in cigarette taxation are regressive in the United Kingdom. The extended data set shows no evidence of increasing price-elasticity by social class as found in a major previous study. To the contrary, there appears to be no clear pattern in the price responsiveness of smoking behaviour across different social classes. Increases in cigarette taxation, while reducing smoking levels in all groups, fall most heavily on men and women in the lowest social class. Men and women in social class five can expect to pay eight and eleven times more of a tax increase respectively, than their social class one counterparts. Taken as a proportion of relative incomes, the regressive nature of increases in cigarette taxation is even more pronounced.
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.
Regression Models For Multivariate Count Data.
Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei
2017-01-01
Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.
Model selection in kernel ridge regression
DEFF Research Database (Denmark)
Exterkate, Peter
2013-01-01
Kernel ridge regression is a technique to perform ridge regression with a potentially infinite number of nonlinear transformations of the independent variables as regressors. This method is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts....... The influence of the choice of kernel and the setting of tuning parameters on forecast accuracy is investigated. Several popular kernels are reviewed, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. The latter two kernels are interpreted in terms of their smoothing properties......, and the tuning parameters associated to all these kernels are related to smoothness measures of the prediction function and to the signal-to-noise ratio. Based on these interpretations, guidelines are provided for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study...
Regressing Atherosclerosis by Resolving Plaque Inflammation
2017-07-01
regression requires the alteration of macrophages in the plaques to a tissue repair “alternatively” activated state. This switch in activation state... tissue repair “alternatively” activated state. This switch in activation state requires the action of TH2 cytokines interleukin (IL)-4 or IL-13. To...regulation of tissue macrophage and dendritic cell population dynamics by CSF-1. J Exp Med. 2011;208(9):1901–1916. 35. Xu H, Exner BG, Chilton PM
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
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
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.
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…
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.
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.
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.
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.
Modeling oil production based on symbolic regression
International Nuclear Information System (INIS)
Yang, Guangfei; Li, Xianneng; Wang, Jianliang; Lian, Lian; Ma, Tieju
2015-01-01
Numerous models have been proposed to forecast the future trends of oil production and almost all of them are based on some predefined assumptions with various uncertainties. In this study, we propose a novel data-driven approach that uses symbolic regression to model oil production. We validate our approach on both synthetic and real data, and the results prove that symbolic regression could effectively identify the true models beneath the oil production data and also make reliable predictions. Symbolic regression indicates that world oil production will peak in 2021, which broadly agrees with other techniques used by researchers. Our results also show that the rate of decline after the peak is almost half the rate of increase before the peak, and it takes nearly 12 years to drop 4% from the peak. These predictions are more optimistic than those in several other reports, and the smoother decline will provide the world, especially the developing countries, with more time to orchestrate mitigation plans. -- Highlights: •A data-driven approach has been shown to be effective at modeling the oil production. •The Hubbert model could be discovered automatically from data. •The peak of world oil production is predicted to appear in 2021. •The decline rate after peak is half of the increase rate before peak. •Oil production projected to decline 4% post-peak
Face Alignment via Regressing Local Binary Features.
Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian
2016-03-01
This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.
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.
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...
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.
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)
The current and future use of ridge regression for prediction in quantitative genetics
Vlaming, Ronald; Groenen, Patrick
2015-01-01
textabstractIn recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i) the theoretical foundations of ridge regression, (ii) its link to...
Regression of a vaginal leiomyoma after ovariohysterectomy in a dog: a case report.
Sathya, Suresh; Linn, Kathleen
2014-01-01
An 11 yr old female mixed-breed Siberian husky was presented with a history of sanguineous vaginal discharge, swelling of the perineal area, decreased appetite, and lethargy. A single, large vaginal leiomyoma and multiple mammary tumors were diagnosed. Mastectomy and ovariohysterectomy were performed. The vaginal leiomyoma regressed completely after ovariohysterectomy. This is the first reported case of spontaneous regression of a vaginal leiomyoma after ovariohysterectomy in a dog.
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.
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 activit...... 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....
Hsu, J. W. P.; Mitzi, D. B.; Kapitulnik, A.; Lee, Mark
1991-10-01
Measurements of the in-plane resistive transition of Bi2Sr2CaCu2O(8+delta) single crystals in perpendicular magnetic fields reveal that in oxygen-reduced samples a giant resistance maximum evolves with field. This is not seen in oxygenated samples with similar metallic normal resistivities. As the peak resistivity may exceed the normal resistivity, it cannot arise from ordinary vortex-motion dissipation. A model is proposed where the excess resistance results from nonrigid vortex motion coupling the out-of-plane dissipation to the in-plane resistance at temperatures where pinning effects are negligible.
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.
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
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.
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.
A method for nonlinear exponential regression analysis
Junkin, B. G.
1971-01-01
A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.
Multinomial logistic regression in workers' health
Grilo, Luís M.; Grilo, Helena L.; Gonçalves, Sónia P.; Junça, Ana
2017-11-01
In European countries, namely in Portugal, it is common to hear some people mentioning that they are exposed to excessive and continuous psychosocial stressors at work. This is increasing in diverse activity sectors, such as, the Services sector. A representative sample was collected from a Portuguese Services' organization, by applying a survey (internationally validated), which variables were measured in five ordered categories in Likert-type scale. A multinomial logistic regression model is used to estimate the probability of each category of the dependent variable general health perception where, among other independent variables, burnout appear as statistically significant.
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 test ing 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
SDE based regression for random PDEs
Bayer, Christian
2016-01-01
A simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour.
Bayesian regression of piecewise homogeneous Poisson processes
Directory of Open Access Journals (Sweden)
Diego Sevilla
2015-12-01
Full Text Available In this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing simulated data. The resulting method is valuable for detecting breaking points in the count rate of time series for Poisson processes. Received: 2 November 2015, Accepted: 27 November 2015; Edited by: R. Dickman; Reviewed by: M. Hutter, Australian National University, Canberra, Australia.; DOI: http://dx.doi.org/10.4279/PIP.070018 Cite as: D J R Sevilla, Papers in Physics 7, 070018 (2015
Selecting a Regression Saturated by Indicators
DEFF Research Database (Denmark)
Hendry, David F.; Johansen, Søren; Santos, Carlos
We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the fin...... the finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest....
Selecting a Regression Saturated by Indicators
DEFF Research Database (Denmark)
Hendry, David F.; Johansen, Søren; Santos, Carlos
We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the fin...... the finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest...
Mapping geogenic radon potential by regression kriging
Energy Technology Data Exchange (ETDEWEB)
Pásztor, László [Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, Department of Environmental Informatics, Herman Ottó út 15, 1022 Budapest (Hungary); Szabó, Katalin Zsuzsanna, E-mail: sz_k_zs@yahoo.de [Department of Chemistry, Institute of Environmental Science, Szent István University, Páter Károly u. 1, Gödöllő 2100 (Hungary); Szatmári, Gábor; Laborczi, Annamária [Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, Department of Environmental Informatics, Herman Ottó út 15, 1022 Budapest (Hungary); Horváth, Ákos [Department of Atomic Physics, Eötvös University, Pázmány Péter sétány 1/A, 1117 Budapest (Hungary)
2016-02-15
Radon ({sup 222}Rn) gas is produced in the radioactive decay chain of uranium ({sup 238}U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly. - Highlights: • A new method
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
Regression analysis for the social sciences
Gordon, Rachel A
2010-01-01
The book provides graduate students in the social sciences with the basic skills that they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set.
SDE based regression for random PDEs
Bayer, Christian
2016-01-06
A simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour.
Neutrosophic Correlation and Simple Linear Regression
Directory of Open Access Journals (Sweden)
A. A. Salama
2014-09-01
Full Text Available Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache. Recently, Salama et al., introduced the concept of correlation coefficient of neutrosophic data. In this paper, we introduce and study the concepts of correlation and correlation coefficient of neutrosophic data in probability spaces and study some of their properties. Also, we introduce and study the neutrosophic simple linear regression model. Possible applications to data processing are touched upon.
Spectral density regression for bivariate extremes
Castro Camilo, Daniela
2016-05-11
We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods. © 2016 Springer-Verlag Berlin Heidelberg
SPE dose prediction using locally weighted regression
International Nuclear Information System (INIS)
Hines, J. W.; Townsend, L. W.; Nichols, T. F.
2005-01-01
When astronauts are outside earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events (SPEs). The total dose received from a major SPE in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be mitigated with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train and provides predictions as accurate as neural network models previously used. (authors)
Mapping geogenic radon potential by regression kriging
International Nuclear Information System (INIS)
Pásztor, László; Szabó, Katalin Zsuzsanna; Szatmári, Gábor; Laborczi, Annamária; Horváth, Ákos
2016-01-01
Radon ( 222 Rn) gas is produced in the radioactive decay chain of uranium ( 238 U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly. - Highlights: • A new method, regression
SPE dose prediction using locally weighted regression
International Nuclear Information System (INIS)
Hines, J. W.; Townsend, L. W.; Nichols, T. F.
2005-01-01
When astronauts are outside Earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events. The total dose received from a major solar particle event in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be reduced with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train, and provides predictions as accurate as the neural network models that were used previously. (authors)
AIRLINE ACTIVITY FORECASTING BY REGRESSION MODELS
Directory of Open Access Journals (Sweden)
Н. Білак
2012-04-01
Full Text Available Proposed linear and nonlinear regression models, which take into account the equation of trend and seasonality indices for the analysis and restore the volume of passenger traffic over the past period of time and its prediction for future years, as well as the algorithm of formation of these models based on statistical analysis over the years. The desired model is the first step for the synthesis of more complex models, which will enable forecasting of passenger (income level airline with the highest accuracy and time urgency.