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.

Multiple linear regression to estimate time-frequency electrophysiological responses in single trials.

Science.gov (United States)

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

Velocities of dislocation groups in very thin neutron-irradiated copper single crystals measured by slip line cinematography

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.

Point defects in lines in single crystalline phosphorene: directional migration and tunable band gaps.

Science.gov (United States)

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.

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.)

Velocities of dislocation groups in very thin neutron-irradiated copper single crystals measured by slip line cinematography

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)

Multiple regression equations modelling of groundwater of Ajmer-Pushkar railway line region, Rajasthan (India).

Science.gov (United States)

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.

A Generalized Least Squares Regression Approach for Computing Effect Sizes in Single-Case Research: Application Examples

Science.gov (United States)

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…

Detailed single-crystal EPR line shape measurements for the single-molecule magnets Fe8Br and Mn12-acetate

Science.gov (United States)

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.

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....

48 CFR 245.7101-3 - DD Form 1348-1, DoD Single Line Item Release/Receipt Document.

Science.gov (United States)

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...

[From clinical judgment to linear regression model.

Science.gov (United States)

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.

Numerical design of in-line X-ray phase-contrast imaging based on ellipsoidal single-bounce monocapillary

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.

Numerical design of in-line X-ray phase-contrast imaging based on ellipsoidal single-bounce monocapillary

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

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.

On-line quantile regression in the RKHS (Reproducing Kernel Hilbert Space) for operational probabilistic forecasting of wind power

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.

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

A Seemingly Unrelated Poisson Regression Model

OpenAIRE

King, Gary

1989-01-01

This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.

Determination of the mass-ratio distribution, I: single-lined spectroscopic binary stars

NARCIS (Netherlands)

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

Single-shot dual-wavelength in-line and off-axis hybrid digital holography

Science.gov (United States)

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.

Standards for Standardized Logistic Regression Coefficients

Science.gov (United States)

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

Linear regression in astronomy. I

Science.gov (United States)

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

1990-01-01

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

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...

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.

Linear Regression Analysis

CERN Document Server

Seber, George A F

2012-01-01

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

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.

Spherical Projection Based Straight Line Segment Extraction for Single Station Terrestrial Laser Point Cloud

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.

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)

On-line scheduling on a single machine : maximizing the number of early jobs

NARCIS (Netherlands)

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

Principal components based support vector regression model for on-line instrument calibration monitoring in NPPs

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

Differential-interference-contrast digital in-line holography microscopy based on a single-optical-element.

Science.gov (United States)

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.

Detecting the single line to ground short circuit fault in the submarine’s power system using the artificial neural network

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.

Logic regression and its extensions.

Science.gov (United States)

Schwender, Holger; Ruczinski, Ingo

2010-01-01

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

Reconfigurable Transmission Line for a Series-Fed Ku-Band Phased Array Using a Single Feed

Science.gov (United States)

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.

Zero-phonon-line emission of single molecules for applications in quantum information processing

Science.gov (United States)

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.

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.

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

In vitro radiosensitivity of six human cell lines. A comparative study with different statistical models

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

Modeling Group Differences in OLS and Orthogonal Regression: Implications for Differential Validity Studies

Science.gov (United States)

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…

Universal control and measuring system for modern classic and amorphous magnetic materials single/on-line strip testers

Science.gov (United States)

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.

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)

Forecasting with Dynamic Regression Models

CERN Document Server

Pankratz, Alan

2012-01-01

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

On-line mass spectrometry system for measurements at single-crystal electrodes in hanging meniscus configuration

NARCIS (Netherlands)

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

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.

Voigt equivalent widths and spectral-bin single-line transmittances: Exact expansions and the MODTRAN®5 implementation

Science.gov (United States)

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.

Single-phase AutoReClosure ARC failure on 400 kV combinedcable/overhead line with permanently connected shunt reactor

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....

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

Regimen durability in HIV-infected children and adolescents initiating first-line ART in a large public sector HIV cohort in South Africa.

Science.gov (United States)

Bonawitz, Rachael; Brennan, Alana T; Long, Lawrence; Heeren, Timothy; Maskew, Mhairi; Sanne, Ian; Fox, Matthew P

2018-04-15

In April 2010 tenofovir and abacavir replaced stavudine in public-sector first-line antiretroviral therapy (ART) for children under 20 years old in South Africa. The association of both abacavir and tenofovir with fewer side-effects and toxicities compared to stavudine could translate to increased durability of tenofovir or abacavir-based regimens. We evaluated changes over time in regimen durability for pediatric patients 3 to 19 years of age at 8 public sector clinics in Johannesburg, South Africa. Cohort analysis of treatment naïve, non-pregnant pediatric patients from 3 to 19 years old initiated on ART between April 2004-December 2013. First-line ART regimens before April 2010 consisted of stavudine or zidovudine with lamivudine and either efavirenz or nevirapine. Tenofovir and/or abacavir was substituted for stavudine after April 2010 in first-line ART. We evaluated the frequency and type of single-drug substitutions, treatment interruptions, and switches to second-line therapy. Fine and Gray competing risk regression models were used to evaluate the association of antiretroviral drug type with single-drug substitutions, treatment interruptions, and second-line switches in the first 24-months on treatment. 398 (15.3%) single-drug substitutions, 187 (7.2%) treatment interruptions and 86 (3.3%) switches to second-line therapy occurred among 2602 pediatric patients over 24-months on ART. Overall, the rate of single-drug substitutions started to increase in 2009, peaked in 2011 at 25%, then declined to 10% in 2013, well after the integration of tenofovir into pediatric regimens; no patients over the age of 3 were initiated on abacavir for first-line therapy. Competing risk regression models showed patients on zidovudine or stavudine had upwards of a 5-fold increase in single-drug substitution vs. patients initiated on tenofovir in the first 24-months on ART. Older adolescents also had a 2-3-fold increase in treatment interruptions and switches to second-line

Applicability of a Single Time Point Strategy for the Prediction of Area Under the Concentration Curve of Linezolid in Patients: Superiority of Ctrough- over Cmax-Derived Linear Regression Models.

Science.gov (United States)

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.

Splenectomy vs. rituximab as a second-line therapy in immune thrombocytopenic purpura: a single center experience.

Science.gov (United States)

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.

Single image super-resolution using locally adaptive multiple linear regression.

Science.gov (United States)

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.

A design of a high speed dual spectrometer by single line scan camera

Science.gov (United States)

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.

Impact of SSSC on Measured Impedance in Single Phase to Ground Fault Condition on 220 kV Transmission Line

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.

Combination chemotherapy versus single-agent therapy as first- and second-line treatment in metastatic breast cancer

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...

Genetics Home Reference: caudal regression syndrome

Science.gov (United States)

... 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 ...

Near single-line operation of a free-burning CS2/O2/N2O flame laser with a nondispersive optical cavity

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.)

Line Laser as an Assistance for Facial and Dental Midlines Evaluation in Single-Splint Orthognathic Surgery.

Science.gov (United States)

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.

An In Vivo Evaluation of the Fit of Zirconium-Oxide Based, Ceramic Single Crowns with Vertical and Horizontal Finish Line Preparations.

Science.gov (United States)

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.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

Science.gov (United States)

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

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.

Differential responses to radiation and hyperthermia of cloned cell lines derived from a single human melanoma xenograft

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

Bayesian ARTMAP for regression.

Science.gov (United States)

Sasu, L M; Andonie, R

2013-10-01

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

Precise predictions of H2O line shapes over a wide pressure range using simulations corrected by a single measurement

Science.gov (United States)

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.

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.

Characterizing performances of solder paste printing process at flexible manufacturing lines

International Nuclear Information System (INIS)

Siew, Jit Ping; Low, Heng Chin; Teoh, Ping Chow

2015-01-01

Solder paste printing (SPP) has been a challenge on printed circuit board (PCB) manufacturing, evident by the proliferation of solder paste inspection equipment, or substituted by rigorous non-value added activity of manual inspections. The objective of this study is to characterize the SPP performance of various products manufactured in flexible production lines with different equipment configurations, and determine areas for process improvement. The study began by collecting information on SPP performance relative to component placement (CP) process, and to the proportion of mixed products. Using a clustering algorithm to group similar elements together, SPP performance across all product-production line pairs are statistically modeled to discover the trend and the influential factors. The main findings are: (a) Ratio of overall dpku for CP and SPP processes are 2:1; (b) logistic regression models of SPP performance indicated that only effects of product-production line and solder paste printer configuration are significant; (c) PCB circuitry design with BGA components and single solder paste printer line configurations generated the highest monthly defects, with the highest variation in the latter

Characterizing performances of solder paste printing process at flexible manufacturing lines

Energy Technology Data Exchange (ETDEWEB)

Siew, Jit Ping; Low, Heng Chin [University of Science Malaysia, 11800 Minden, Penang (Malaysia); Teoh, Ping Chow [Wawasan Open University, 54 Jalan Sultan Ahmad Shah, 10050 Penang (Malaysia)

2015-02-03

Solder paste printing (SPP) has been a challenge on printed circuit board (PCB) manufacturing, evident by the proliferation of solder paste inspection equipment, or substituted by rigorous non-value added activity of manual inspections. The objective of this study is to characterize the SPP performance of various products manufactured in flexible production lines with different equipment configurations, and determine areas for process improvement. The study began by collecting information on SPP performance relative to component placement (CP) process, and to the proportion of mixed products. Using a clustering algorithm to group similar elements together, SPP performance across all product-production line pairs are statistically modeled to discover the trend and the influential factors. The main findings are: (a) Ratio of overall dpku for CP and SPP processes are 2:1; (b) logistic regression models of SPP performance indicated that only effects of product-production line and solder paste printer configuration are significant; (c) PCB circuitry design with BGA components and single solder paste printer line configurations generated the highest monthly defects, with the highest variation in the latter.

Optimization of cell line development in the GS-CHO expression system using a high-throughput, single cell-based clone selection system.

Science.gov (United States)

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.

Estimating Engineering and Manufacturing Development Cost Risk Using Logistic and Multiple Regression

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...

Strapdown Airborne Gravimetry Quality Assessment Method Based on Single Survey Line Data: A Study by SGA-WZ02 Gravimeter

Science.gov (United States)

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

Taking into account latency, amplitude, and morphology: improved estimation of single-trial ERPs by wavelet filtering and multiple linear regression.

Science.gov (United States)

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.

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.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

Science.gov (United States)

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.

Differentiating regressed melanoma from regressed lichenoid keratosis.

Science.gov (United States)

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

2017-04-01

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

FogBank: a single cell segmentation across multiple cell lines and image modalities.

Science.gov (United States)

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

Complex regression Doppler optical coherence tomography

Science.gov (United States)

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.

Influence of picosecond multiple/single line ablation on copper nanoparticles fabricated for surface enhanced Raman spectroscopy and photonics applications

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)

A single CD4 test with 250 cells/mm3 threshold predicts viral suppression in HIV-infected adults failing first-line therapy by clinical criteria.

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

A single CD4 test with 250 cells/mm3 threshold predicts viral suppression in HIV-infected adults failing first-line therapy by clinical criteria.

Science.gov (United States)

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.

Chebyshev approximations for the transmission integral for one single line in Moessbauer spectroscopy

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.))

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

Comparison of partial least squares and lasso regression techniques as applied to laser-induced breakdown spectroscopy of geological samples

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

Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

International Nuclear Information System (INIS)

Riaz, Nadeem; Wiersma, Rodney; Mao Weihua; Xing Lei; Shanker, Piyush; Gudmundsson, Olafur; Widrow, Bernard

2009-01-01

Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

Compact Single-Layer Traveling-Wave Antenna DesignUsing Metamaterial Transmission Lines

Science.gov (United States)

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.

Application of single-step genomic best linear unbiased prediction with a multiple-lactation random regression test-day model for Japanese Holsteins.

Science.gov (United States)

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.

A precise evaluation of glomerular filtration rate (GFR) in two plasma samples following a single administration of 57Co-B12 vitamin

International Nuclear Information System (INIS)

Camargo, E.E.; Rockmann, R.L.; Barreto, T.M.; Eston, T.E.; Papaleo Netto, M.; Carvalho, N.

1974-01-01

Through a logarithmic regression performed with the contings of 4 plasma samples withdrawn at 20,40,60 and 80 minutes after a venous injection of vitamin B 12 - 57 Co, the glomerular filtration-rate(GFR) in 11 patients, performing simultaneously the same study with EDTA- 51 Cr in 3 of them, is evaluated. The values obtained through the regression straight line are compared with those given by only 2 points, in the 6 possible combinations: 20 and 40 minutes, 20 and 60 minutes, 20 and 80 minutes, 40 and 60 minutes, 40 and 80 minutes, 60 and 80 minutes. The pair of points obtained at 20 and 80 minutes determined the straight line most similar to the logarithmic regression and as a simplification of the method, the withdraw of only 2 plasma samples, at and 80 minutes after a single injection of vitamin B 12 -57 Co is proposed [pt

Using Quartile-Quartile Lines as Linear Models

Science.gov (United States)

Gordon, Sheldon P.

2015-01-01

This article introduces the notion of the quartile-quartile line as an alternative to the regression line and the median-median line to produce a linear model based on a set of data. It is based on using the first and third quartiles of a set of (x, y) data. Dynamic spreadsheets are used as exploratory tools to compare the different approaches and…

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

Energy Technology Data Exchange (ETDEWEB)

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

2000-07-01

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

Evaluating lane-by-lane gap-out based signal control for isolated intersection under stop-line, single and multiple advance detection systems

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.

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)

Retro-regression--another important multivariate regression improvement.

Science.gov (United States)

Randić, M

2001-01-01

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

Modified Regression Correlation Coefficient for Poisson Regression Model

Science.gov (United States)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

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

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

Measured, calculated and predicted Stark widths of the singly ionized C, N, O, F, Ne, Si, P, S, Cl and Ar spectral lines

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.

Dual HER2\\PIK3CA targeting overcomes single-agent acquired resistance in HER2 amplified uterine serous carcinoma cell lines in vitro and in vivo

Science.gov (United States)

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

Dual HER2/PIK3CA Targeting Overcomes Single-Agent Acquired Resistance in HER2-Amplified Uterine Serous Carcinoma Cell Lines In Vitro and In Vivo.

Science.gov (United States)

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.

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.

Simple and multiple linear regression: sample size considerations.

Science.gov (United States)

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 © 2016 Elsevier Inc. All rights reserved.

Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line.

Science.gov (United States)

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.

Simulation Experiments in Practice: Statistical Design and Regression Analysis

OpenAIRE

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...

Cell Line Controls for the Genotyping of a Spectrum of Human Single Nucleotide Polymorphisms in the Clinical Laboratory.

Science.gov (United States)

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.

Image superresolution using support vector regression.

Science.gov (United States)

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.

The role of verbal memory in regressions during reading is modulated by the target word's recency in memory.

Science.gov (United States)

Guérard, Katherine; Saint-Aubin, Jean; Maltais, Marilyne; Lavoie, Hugo

2014-10-01

During reading, a number of eye movements are made backward, on words that have already been read. Recent evidence suggests that such eye movements, called regressions, are guided by memory. Several studies point to the role of spatial memory, but evidence for the role of verbal memory is more limited. In the present study, we examined the factors that modulate the role of verbal memory in regressions. Participants were required to make regressions on target words located in sentences displayed on one or two lines. Verbal interference was shown to affect regressions, but only when participants executed a regression on a word located in the first part of the sentence, irrespective of the number of lines on which the sentence was displayed. Experiments 2 and 3 showed that the effect of verbal interference on words located in the first part of the sentence disappeared when participants initiated the regression from the middle of the sentence. Our results suggest that verbal memory is recruited to guide regressions, but only for words read a longer time ago.

A Closed-Form Error Model of Straight Lines for Improved Data Association and Sensor Fusing

Directory of Open Access Journals (Sweden)

Volker Sommer

2018-04-01

Full Text Available Linear regression is a basic tool in mobile robotics, since it enables accurate estimation of straight lines from range-bearing scans or in digital images, which is a prerequisite for reliable data association and sensor fusing in the context of feature-based SLAM. This paper discusses, extends and compares existing algorithms for line fitting applicable also in the case of strong covariances between the coordinates at each single data point, which must not be neglected if range-bearing sensors are used. Besides, in particular, the determination of the covariance matrix is considered, which is required for stochastic modeling. The main contribution is a new error model of straight lines in closed form for calculating quickly and reliably the covariance matrix dependent on just a few comprehensible and easily-obtainable parameters. The model can be applied widely in any case when a line is fitted from a number of distinct points also without a priori knowledge of the specific measurement noise. By means of extensive simulations, the performance and robustness of the new model in comparison to existing approaches is shown.

Dual Regression

OpenAIRE

Spady, Richard; Stouli, Sami

2012-01-01

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

Performance enhancement of the single-phase series active filter by employing the load voltage waveform reconstruction and line current sampling delay reduction methods

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...

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

Science.gov (United States)

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.

Shigella mediated depletion of macrophages in a murine breast cancer model is associated with tumor regression.

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.

Bivariate least squares linear regression: Towards a unified analytic formalism. I. Functional models

Science.gov (United States)

Caimmi, R.

2011-08-01

Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts ( York, 1966, 1969) is reviewed using a new formalism in terms of deviation (matrix) traces which, for unweighted data, reduce to usual quantities leaving aside an unessential (but dimensional) multiplicative factor. Within the framework of classical error models, the dependent variable relates to the independent variable according to the usual additive model. The classes of linear models considered are regression lines in the general case of correlated errors in X and in Y for weighted data, and in the opposite limiting situations of (i) uncorrelated errors in X and in Y, and (ii) completely correlated errors in X and in Y. The special case of (C) generalized orthogonal regression is considered in detail together with well known subcases, namely: (Y) errors in X negligible (ideally null) with respect to errors in Y; (X) errors in Y negligible (ideally null) with respect to errors in X; (O) genuine orthogonal regression; (R) reduced major-axis regression. In the limit of unweighted data, the results determined for functional models are compared with their counterparts related to extreme structural models i.e. the instrumental scatter is negligible (ideally null) with respect to the intrinsic scatter ( Isobe et al., 1990; Feigelson and Babu, 1992). While regression line slope and intercept estimators for functional and structural models necessarily coincide, the contrary holds for related variance estimators even if the residuals obey a Gaussian distribution, with the exception of Y models. An example of astronomical application is considered, concerning the [O/H]-[Fe/H] empirical relations deduced from five samples related to different stars and/or different methods of oxygen abundance determination. For selected samples and assigned methods, different regression models yield consistent results within the errors (∓ σ) for both

Regression calibration with more surrogates than mismeasured variables

KAUST Repository

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

KAUST Repository

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.

Comparison of partial least squares and lasso regression techniques as applied to laser-induced breakdown spectroscopy of geological samples

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

Comparison of outcomes between overlapping-spot and single-spot photodynamic therapy for circumscribed choroidal hemangioma

Directory of Open Access Journals (Sweden)

Zhao-An Su

2014-02-01

Full Text Available AIM:To compare the efficacy and safety of photodynamic therapy (PDT with overlapping multiple spots and single spot for treating circumscribed choroidal hemangioma.METHODS:Twenty-two patients (22 eyes with symptomatic circumscribed choroidal hemangioma received PDT treatment. Fourteen patients received overlapping spots (two to three spots PDT, whereas eight patients received single-spot PDT. Laser was used at 50J/cm2 for 83s in the overlapping-spot group and 50J/cm2 for 166s in the single-spot group. Clinical examination, funduscopy, fluorescein angiography, and ultrasonography were performed at baseline and after treatment.RESULTS:The mean follow-up time was 28.5±8.0 months in the overlapping-spot group and 27.0±5.0 months in the single-spot group. Nine patients (64.2% had their vision improved over two lines on the Snellen chart, and five patients showed stable visual acuity in the overlapping-spot group. The mean thickness of tumor decreased from 2.7±0.8mm to 1.2±0.9mm, and the mean greatest tumor linear dimension decreased from 7.4±1.5mm to 4.5±3.5mm after treatment. In the single-spot group, two patients (25% had their vision improved over two lines on the Snellen chart, and six patients had unchanged stable vision. The mean tumor thickness in this group decreased from 2.5±0.7mm to 1.4±1.0mm, and the mean greatest tumor linear dimension decreased from 7.2±1.3mm to 4.7±3.6mm. No significant differences in visual improvement and tumor regression were found between the two groups.CONCLUSION: Overlapping-spot PDT under appropriate treatment parameters and strategies is as effective and safe as single-spot PDT for treating symptomatic circumscribed choroidal hemangioma. Improved or stabilized visual acuity was achieved as a result of tumor regression.

Auto-associative Kernel Regression Model with Weighted Distance Metric for Instrument Drift Monitoring

International Nuclear Information System (INIS)

Shin, Ho Cheol; Park, Moon Ghu; You, Skin

2006-01-01

Recently, many on-line approaches to instrument channel surveillance (drift monitoring and fault detection) have been reported worldwide. On-line monitoring (OLM) method evaluates instrument channel performance by assessing its consistency with other plant indications through parametric or non-parametric models. The heart of an OLM system is the model giving an estimate of the true process parameter value against individual measurements. This model gives process parameter estimate calculated as a function of other plant measurements which can be used to identify small sensor drifts that would require the sensor to be manually calibrated or replaced. This paper describes an improvement of auto associative kernel regression (AAKR) by introducing a correlation coefficient weighting on kernel distances. The prediction performance of the developed method is compared with conventional auto-associative kernel regression

LINEAR REGRESSION MODEL ESTİMATİON FOR RIGHT CENSORED DATA

Directory of Open Access Journals (Sweden)

Ersin Yılmaz

2016-05-01

Full Text Available In this study, firstly we will define a right censored data. If we say shortly right-censored data is censoring values that above the exact line. This may be related with scaling device. And then  we will use response variable acquainted from right-censored explanatory variables. Then the linear regression model will be estimated. For censored data’s existence, Kaplan-Meier weights will be used for  the estimation of the model. With the weights regression model  will be consistent and unbiased with that.   And also there is a method for the censored data that is a semi parametric regression and this method also give  useful results  for censored data too. This study also might be useful for the health studies because of the censored data used in medical issues generally.

OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis.

Science.gov (United States)

Vajargah, Kianoush Fathi; Sadeghi-Bazargani, Homayoun; Mehdizadeh-Esfanjani, Robab; Savadi-Oskouei, Daryoush; Farhoudi, Mehdi

2012-01-01

The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.

Cell Line Data Base: structure and recent improvements towards molecular authentication of human cell lines.

Science.gov (United States)

Romano, Paolo; Manniello, Assunta; Aresu, Ottavia; Armento, Massimiliano; Cesaro, Michela; Parodi, Barbara

2009-01-01

The Cell Line Data Base (CLDB) is a well-known reference information source on human and animal cell lines including information on more than 6000 cell lines. Main biological features are coded according to controlled vocabularies derived from international lists and taxonomies. HyperCLDB (http://bioinformatics.istge.it/hypercldb/) is a hypertext version of CLDB that improves data accessibility by also allowing information retrieval through web spiders. Access to HyperCLDB is provided through indexes of biological characteristics and navigation in the hypertext is granted by many internal links. HyperCLDB also includes links to external resources. Recently, an interest was raised for a reference nomenclature for cell lines and CLDB was seen as an authoritative system. Furthermore, to overcome the cell line misidentification problem, molecular authentication methods, such as fingerprinting, single-locus short tandem repeat (STR) profile and single nucleotide polymorphisms validation, were proposed. Since this data is distributed, a reference portal on authentication of human cell lines is needed. We present here the architecture and contents of CLDB, its recent enhancements and perspectives. We also present a new related database, the Cell Line Integrated Molecular Authentication (CLIMA) database (http://bioinformatics.istge.it/clima/), that allows to link authentication data to actual cell lines.

Compressive sensing sectional imaging for single-shot in-line self-interference incoherent holography

Science.gov (United States)

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.

Geographically weighted regression and multicollinearity: dispelling the myth

Science.gov (United States)

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.

Regressive Progression: The Quest for Self-Transcendence in Western Tragedy

Directory of Open Access Journals (Sweden)

Bahee Hadaegh

2009-07-01

Full Text Available Regressive progression is a concept which interestingly describes the developmental process of Western tragedy based on the recurring motif of the quest for the higher self and Nietzsche’s understanding of Dionysian tragic hero. This motif reveals itself in three manifestations - action, imagination and inaction- respectively visible in the three major dramatic eras of the Renaissance tragedy, European nineteenth-century drama, and the Absurd Theatre. Although the approach of the quest regressively shifts from action to inaction, the degree of success of the tragic questers in approximating the wished-for higher self reveals a progressive line in the developmental process of Western tragedy.

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.

Regression: A Bibliography.

Science.gov (United States)

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

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

Use of probabilistic weights to enhance linear regression myoelectric control.

Science.gov (United States)

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.

Customized Pull Systems for Single-Product Flow Lines

NARCIS (Netherlands)

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

Analysis of the quadrupolar coupling effect on the line intensities using single-crystal nutation NMR in α-Al2O3 crystals

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

Testing and Modeling Fuel Regression Rate in a Miniature Hybrid Burner

Directory of Open Access Journals (Sweden)

Luciano Fanton

2012-01-01

Full Text Available Ballistic characterization of an extended group of innovative HTPB-based solid fuel formulations for hybrid rocket propulsion was performed in a lab-scale burner. An optical time-resolved technique was used to assess the quasisteady regression history of single perforation, cylindrical samples. The effects of metalized additives and radiant heat transfer on the regression rate of such formulations were assessed. Under the investigated operating conditions and based on phenomenological models from the literature, analyses of the collected experimental data show an appreciable influence of the radiant heat flux from burnt gases and soot for both unloaded and loaded fuel formulations. Pure HTPB regression rate data are satisfactorily reproduced, while the impressive initial regression rates of metalized formulations require further assessment.

Effectiveness of electronic stability control on single-vehicle accidents.

Science.gov (United States)

Lyckegaard, Allan; Hels, Tove; Bernhoft, Inger Marie

2015-01-01

This study aims at evaluating the effectiveness of electronic stability control (ESC) on single-vehicle injury accidents while controlling for a number of confounders influencing the accident risk. Using police-registered injury accidents from 2004 to 2011 in Denmark with cars manufactured in the period 1998 to 2011 and the principle of induced exposure, 2 measures of the effectiveness of ESC were calculated: The crude odds ratio and the adjusted odds ratio, the latter by means of logistic regression. The logistic regression controlled for a number of confounding factors, of which the following were significant. For the driver: Age, gender, driving experience, valid driving license, and seat belt use. For the vehicle: Year of registration, weight, and ESC. For the accident surroundings: Visibility, light, and location. Finally, for the road: Speed limit, surface, and section characteristics. The present study calculated the crude odds ratio for ESC-equipped cars of getting in a single-vehicle injury accident as 0.40 (95% confidence interval [CI], 0.34-0.47) and the adjusted odds ratio as 0.69 (95% CI, 0.54-0.88). No difference was found in the effectiveness of ESC across the injury severity categories (slight, severe, and fatal). In line with previous results, this study concludes that ESC reduces the risk for single-vehicle injury accidents by 31% when controlling for various confounding factors related to the driver, the car, and the accident surroundings. Furthermore, it is concluded that it is important to control for human factors (at a minimum age and gender) in analyses where evaluations of this type are performed.

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

Science.gov (United States)

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.

Yield Stability of Sorghum Hybrids and Parental Lines | Kenga ...

African Journals Online (AJOL)

Seventy-five sorghum hybrids and twenty parental lines were evaluated for two consecutive years at two locations. Our objective was to compare relative stability of grain yields among hybrids and parental lines. Mean grain yields and stability analysis of variance, which included linear regression coefficient (bi) and ...

SINGLE AGENT DOCETAXEL AS SECOND- LINE CHEMOTHERAPY FOR PRETREATED PATIENTS WITH RECURRENT NON- SMALL CELL LUNG CANCER

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.

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Pinning in the flux-line-cutting regime of Bi 2Sr 2Ca 1Cu 2O 8 single crystals at high field

Science.gov (United States)

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.

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)

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)

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

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

Cost-effective master cell bank validation of multiple clinical-grade human pluripotent stem cell lines from a single donor.

Science.gov (United States)

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.

Validity and reliability of the single-trial line drill test of anaerobic power in basketball players.

Science.gov (United States)

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.

Picosecond wide-field time-correlated single photon counting fluorescence microscopy with a delay line anode detector

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.

The UIC 406 capacity method used on single track sections

DEFF Research Database (Denmark)

Landex, Alex; Kaas, Anders H.; Jacobsen, Erik M.

2007-01-01

This paper describes the relatively new UIC 406 capacity method which is an easy and effective way of calculating capacity consumption on railway lines. However, it is possible to expound the method in different ways which can lead to different capacity consumptions. This paper describes the UIC...... 406 method for single track lines and how it is expounded in Denmark. Many capacity analyses using the UIC 406 capacity method for double track lines have been carried out and presented internationally but only few capacity analyses using the UIC 406 capacity method on single track lines have been...... presented. Therefore, the differences between capacity analysis for double track lines and single track lines are discussed in the beginning of this paper. Many of the principles of the UIC 406 capacity analyses on double track lines can be used on single track lines – at least when more than one train...

Quantile Regression Methods

DEFF Research Database (Denmark)

Fitzenberger, Bernd; Wilke, Ralf Andreas

2015-01-01

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

Insulin activates single amiloride-blockable Na channels in a distal nephron cell line (A6).

Science.gov (United States)

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.

A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

Science.gov (United States)

Meaney, Christopher; Moineddin, Rahim

2014-01-24

In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

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

Regression Phalanxes

OpenAIRE

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

2017-01-01

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

Many-body calculation of the coincidence L3 photoelectron spectroscopy main line of Ni metal

International Nuclear Information System (INIS)

Ohno, Masahide

2008-01-01

The partial singles L 3 photoelectron spectroscopy (PES) main line of Ni metal correlated with Auger electrons emitted by the localized L 3 -VV Auger decay is calculated by a many-body theory. The partial singles L 3 PES main line of Ni metal almost coincides in both line shape and peak kinetic energy (KE) with the singles one. The former main line peak shows a KE shift of only 0.01 eV toward the lower KE and a very small asymmetric line shape change compared to the singles one. The asymmetric line shape change and the peak KE shift of the partial singles L 3 main line are very small. However, they are due to the variation with photoelectron KE in the branching ratio of the partial Auger decay width in the partial singles L 3 PES main line by the photoelectron KE dependent imaginary part of the shakeup self-energy. The L 3 PES main line of Ni metal measured in coincidence with the L 3 -VV ( 1 G) Auger electron spectroscopy (AES) main line peak is the partial singles one modulated by a spectral function R a of a fixed energy Auger electron analyzer so that it should show only a symmetric line narrowing by R a compared to the singles one. The L 3 PES main line peak of Ni metal measured in coincidence with the delocalized band-like L 3 -VV AES peak or not completely split-off (or not completely localized) L 3 -VV ( 3 F) AES peak, will show an asymmetric line narrowing and a KE shift compared to the singles one. Thus, the L 3 PES main line of Ni metal in coincidence with various parts of the L 3 -VV AES spectrum depends on which part of the L 3 -VV AES spectrum a fixed energy Auger electron analyzer is set. The experimental verification is in need

Critically Evaluated Energy Levels, Spectral Lines, Transition Probabilities, and Intensities of Singly Ionized Vanadium (V ii)

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.

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

Science.gov (United States)

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Straight line fitting and predictions: On a marginal likelihood approach to linear regression and errors-in-variables models

Science.gov (United States)

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.

Regression of a vaginal leiomyoma after ovariohysterectomy in a dog: a case report.

Science.gov (United States)

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.

Electromyographic analyses of muscle pre-activation induced by single joint exercise.

Science.gov (United States)

Júnior, Valdinar A R; Bottaro, Martim; Pereira, Maria C C; Andrade, Marcelino M; P Júnior, Paulo R W; Carmo, Jake C

2010-01-01

To investigate whether performing a low-intensity, single-joint exercises for knee extensors was an efficient strategy for increasing the number of motor units recruited in the vastus lateralis muscle during a subsequent multi-joint exercises. Nine healthy male participants (23.33+/-3.46 yrs) underwent bouts of exercise in which knee extension and 45 degrees , and leg press exercises were performed in sequence. In the low-intensity bout (R30), 15 unilateral knee extensions were performed, followed by 15 repetitions of the leg presses at 30% and 60% of one maximum repetition load (1-MR), respectively. In the high-intensity bout (R60), the same sequence was performed, but the applied load was 60% of 1-MR for both exercises. A single set of 15 repetitions of the leg press at 60% of 1-MR was performed as a control exercise (CR). The surface electromyographic signals of the vastus lateralis muscle were recorded by means of a linear electrode array. The root mean square (RMS) values were determined for each repetition of the leg press, and linear regressions were calculated from these results. The slopes of the straight lines obtained were then normalized using the linear coefficients of the regression equations and compared using one-way ANOVAs for repeated measures. The slopes observed in the CR were significantly lower than those in the R30 and R60 (precruitment of motor units was more effective when a single-joint exercise preceded the multi-joint exercise. Article registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) under the number ACTRN12609000413224.

Biostatistics Series Module 6: Correlation and Linear Regression.

Science.gov (United States)

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.

Different FTE signatures generated by the bursty single X line reconnection and the multiple X line reconnection at the dayside magnetopause

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

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.

Boosted beta regression.

Directory of Open Access Journals (Sweden)

Matthias Schmid

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

Accuracy of Bayes and Logistic Regression Subscale Probabilities for Educational and Certification Tests

Science.gov (United States)

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…

Efficacy and safety of trastuzumab as a single agent in first-line treatment of HER2-overexpressing metastatic breast cancer.

Science.gov (United States)

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.

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...

Online Support Vector Regression with Varying Parameters for Time-Dependent Data

International Nuclear Information System (INIS)

Omitaomu, Olufemi A.; Jeong, Myong K.; Badiru, Adedeji B.

2011-01-01

Support vector regression (SVR) is a machine learning technique that continues to receive interest in several domains including manufacturing, engineering, and medicine. In order to extend its application to problems in which datasets arrive constantly and in which batch processing of the datasets is infeasible or expensive, an accurate online support vector regression (AOSVR) technique was proposed. The AOSVR technique efficiently updates a trained SVR function whenever a sample is added to or removed from the training set without retraining the entire training data. However, the AOSVR technique assumes that the new samples and the training samples are of the same characteristics; hence, the same value of SVR parameters is used for training and prediction. This assumption is not applicable to data samples that are inherently noisy and non-stationary such as sensor data. As a result, we propose Accurate On-line Support Vector Regression with Varying Parameters (AOSVR-VP) that uses varying SVR parameters rather than fixed SVR parameters, and hence accounts for the variability that may exist in the samples. To accomplish this objective, we also propose a generalized weight function to automatically update the weights of SVR parameters in on-line monitoring applications. The proposed function allows for lower and upper bounds for SVR parameters. We tested our proposed approach and compared results with the conventional AOSVR approach using two benchmark time series data and sensor data from nuclear power plant. The results show that using varying SVR parameters is more applicable to time dependent data.

Evaluation of scatter correction using a single isotope for simultaneous emission and transmission data

International Nuclear Information System (INIS)

Yang, J.; Kuikka, J.T.; Vanninen, E.; Laensimies, E.; Kauppinen, T.; Patomaeki, L.

1999-01-01

Photon scatter is one of the most important factors degrading the quantitative accuracy of SPECT images. Many scatter correction methods have been proposed. The single isotope method was proposed by us. Aim: We evaluate the scatter correction method of improving the quality of images by acquiring emission and transmission data simultaneously with single isotope scan. Method: To evaluate the proposed scatter correction method, a contrast and linearity phantom was studied. Four female patients with fibromyalgia (FM) syndrome and four with chronic back pain (BP) were imaged. Grey-to-cerebellum (G/C) and grey-to-white matter (G/W) ratios were determined by one skilled operator for 12 regions of interest (ROIs) in each subject. Results: The linearity of activity response was improved after the scatter correction (r=0.999). The y-intercept value of the regression line was 0.036 (p [de

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

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....

Measurement error in a single regressor

NARCIS (Netherlands)

Meijer, H.J.; Wansbeek, T.J.

2000-01-01

For the setting of multiple regression with measurement error in a single regressor, we present some very simple formulas to assess the result that one may expect when correcting for measurement error. It is shown where the corrected estimated regression coefficients and the error variance may lie,

The current and future use of ridge regression for prediction in quantitative genetics

OpenAIRE

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...

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

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.

Incentive-Compatible Robust Line Planning

Science.gov (United States)

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.

First-line single agent treatment with gefitinib in patients with advanced non-small-cell lung cancer

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.

Regression Techniques for Determining the Effective Impervious Area in Southern California Watersheds

Science.gov (United States)

Sultana, R.; Mroczek, M.; Dallman, S.; Sengupta, A.; Stein, E. D.

2016-12-01

The portion of the Total Impervious Area (TIA) that is hydraulically connected to the storm drainage network is called the Effective Impervious Area (EIA). The remaining fraction of impervious area, called the non-effective impervious area, drains onto pervious surfaces which do not contribute to runoff for smaller events. Using the TIA instead of EIA in models and calculations can lead to overestimates of runoff volumes peak discharges and oversizing of drainage system since it is assumed all impervious areas produce urban runoff that is directly connected to storm drains. This makes EIA a better predictor of actual runoff from urban catchments for hydraulic design of storm drain systems and modeling non-point source pollution. Compared to TIA, determining the EIA is considerably more difficult to calculate since it cannot be found by using remote sensing techniques, readily available EIA datasets, or aerial imagery interpretation alone. For this study, EIA percentages were calculated by two successive regression methods for five watersheds (with areas of 8.38 - 158mi2) located in Southern California using rainfall-runoff event data for the years 2004 - 2007. Runoff generated from the smaller storm events are considered to be emanating only from the effective impervious areas. Therefore, larger events that were considered to have runoff from both impervious and pervious surfaces were successively removed in the regression methods using a criterion of (1) 1mm and (2) a max (2 , 1mm) above the regression line. MSE is calculated from actual runoff and runoff predicted by the regression. Analysis of standard deviations showed that criterion of max (2 , 1mm) better fit the regression line and is the preferred method in predicting the EIA percentage. The estimated EIAs have shown to be approximately 78% to 43% of the TIA which shows use of EIA instead of TIA can have significant impact on the cost building urban hydraulic systems and stormwater capture devices.

Morphological changes in cultured bovine lymphoid cell lines associated with bovine viral diarrhea virus (BVDV) single and dual infections with bovine leukemia virus (BLV)

Science.gov (United States)

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...

Investigation of distribution microhomogeneity of doped elements in oxide single crystals by means of LMA-AES

International Nuclear Information System (INIS)

Nikolova, L.; Krasnobaeva, N.; Manuilov, N.

1989-01-01

The distribution of V and Ti in oxide single crystals Al 2 O 3 :V 3+ , Y 3 Al 5 O 12 :V 3+ , Al 2 O 3 :Ti 3+ , Y 3 Al 5 O 12 :Ti 3+ is investigated by laser emission microspectral analysis with photographic registration of spectra. Single crystals have been grown by the method of vertical directed crystallization (method of Bridgman-Stockbarger). For evaluation of microhomogeneity of the investigated elements distribution the following statistical methods are applied: one-way variance analysis, two-way variance analysis, regression models and gradient method. A PC programme package is developed allowing to process photoregistration data, to choose the internal standard line by scatter diagrams, to perform all statistical analysis and to plot the distribution diagrams of the elements in the samples. 2 refs. (author)

26 CFR 1.132-4 - Line of business limitation.

Science.gov (United States)

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...

Parallel field line and stream line tracing algorithms for space physics applications

Science.gov (United States)

Toth, G.; de Zeeuw, D.; Monostori, G.

2004-05-01

Field line and stream line tracing is required in various space physics applications, such as the coupling of the global magnetosphere and inner magnetosphere models, the coupling of the solar energetic particle and heliosphere models, or the modeling of comets, where the multispecies chemical equations are solved along stream lines of a steady state solution obtained with single fluid MHD model. Tracing a vector field is an inherently serial process, which is difficult to parallelize. This is especially true when the data corresponding to the vector field is distributed over a large number of processors. We designed algorithms for the various applications, which scale well to a large number of processors. In the first algorithm the computational domain is divided into blocks. Each block is on a single processor. The algorithm folows the vector field inside the blocks, and calculates a mapping of the block surfaces. The blocks communicate the values at the coinciding surfaces, and the results are interpolated. Finally all block surfaces are defined and values inside the blocks are obtained. In the second algorithm all processors start integrating along the vector field inside the accessible volume. When the field line leaves the local subdomain, the position and other information is stored in a buffer. Periodically the processors exchange the buffers, and continue integration of the field lines until they reach a boundary. At that point the results are sent back to the originating processor. Efficiency is achieved by a careful phasing of computation and communication. In the third algorithm the results of a steady state simulation are stored on a hard drive. The vector field is contained in blocks. All processors read in all the grid and vector field data and the stream lines are integrated in parallel. If a stream line enters a block, which has already been integrated, the results can be interpolated. By a clever ordering of the blocks the execution speed can be

Adaptation of bread-wheat lines across different environment of Pakistan

International Nuclear Information System (INIS)

Mujhid, M.Y.; Ahmad, Z.; Khan, M.A.; Qamar, M.; Kisana, N.S.; Asif, M.

2009-01-01

Ten advance wheat-lines developed by National Agricultural Research Centre (NARC), Islamabad, were evaluated for stability of grain-yield over five locations. The experiment was conducted during 2006-07 at NARC, Islamabad, AARI, Faisalabad, RARI, Bahawalpur, CCRI, Pirsabak and NIFA, Peshawar, by following randomized complete block design with three replications. At maturity, grain-yield was taken from standard plot and data were analyzed statistically. Genotypes x locations interactions were found highly significant. Predictable (linear) portion of variation was important, but non-linear component was non significant. None of the regression coefficients differ significantly from unity. Hence deviation from regression and average grain-yield was used to identify superior genotypes. Above average grain-yields were observed in five genotypes. V4 and V8 were stable across environments with low deviation from regression and gave above-average yield. The study provides valuable information for selecting advance wheat-lines under different locations of the country, to be considered potential as breeding material for release as varieties. (author)

The Checkpoint Kinase 1 Inhibitor Prexasertib Induces Regression of Preclinical Models of Human Neuroblastoma.

Science.gov (United States)

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.

Use of different marker pre-selection methods based on single SNP regression in the estimation of Genomic-EBVs

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.

Application and validation of Cox regression models in a single-center series of double kidney transplantation.

Science.gov (United States)

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.

Use of probabilistic weights to enhance linear regression myoelectric control

Science.gov (United States)

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.

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.

Shorter lines facilitate reading in those who struggle.

Directory of Open Access Journals (Sweden)

Matthew H Schneps

Full Text Available People with dyslexia, who ordinarily struggle to read, sometimes remark that reading is easier when e-readers are used. Here, we used eye tracking to observe high school students with dyslexia as they read using these devices. Among the factors investigated, we found that reading using a small device resulted in substantial benefits, improving reading speeds by 27%, reducing the number of fixations by 11%, and importantly, reducing the number of regressive saccades by more than a factor of 2, with no cost to comprehension. Given that an expected trade-off between horizontal and vertical regression was not observed when line lengths were altered, we speculate that these effects occur because sluggish attention spreads perception to the left as the gaze shifts during reading. Short lines eliminate crowded text to the left, reducing regression. The effects of attention modulation by the hand, and of increased letter spacing to reduce crowding, were also found to modulate the oculomotor dynamics in reading, but whether these factors resulted in benefits or costs depended on characteristics, such as visual attention span, that varied within our sample.

Univariate and multiple linear regression analyses for 23 single nucleotide polymorphisms in 14 genes predisposing to chronic glomerular diseases and IgA nephropathy in Han Chinese.

Science.gov (United States)

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.

Delay line clipping in a scintillation camera system

International Nuclear Information System (INIS)

Hatch, K.F.

1979-01-01

The present invention provides a novel base line restoring circuit and a novel delay line clipping circuit in a scintillation camera system. Single and double delay line clipped signal waveforms are generated for increasing the operational frequency and fidelity of data detection of the camera system by base line distortion such as undershooting, overshooting, and capacitive build-up. The camera system includes a set of photomultiplier tubes and associated amplifiers which generate sequences of pulses. These pulses are pulse-height analyzed for detecting a scintillation having an energy level which falls within a predetermined energy range. Data pulses are combined to provide coordinates and energy of photopeak events. The amplifiers are biassed out of saturation over all ranges of pulse energy level and count rate. Single delay line clipping circuitry is provided for narrowing the pulse width of the decaying electrical data pulses which increase operating speed without the occurrence of data loss. (JTA)

Single camera multi-view anthropometric measurement of human height and mid-upper arm circumference using linear regression.

Science.gov (United States)

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

Single-electron multiplication statistics as a combination of Poissonian pulse height distributions using constraint regression methods

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.)

Acquired TGF beta 1 sensitivity and TGF beta 1 expression in cell lines established from a single small cell lung cancer patient during clinical progression

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...

On logistic regression analysis of dichotomized responses.

Science.gov (United States)

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.

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

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.

Spontaneous regression of retinopathy of prematurity:incidence and predictive factors

Directory of Open Access Journals (Sweden)

Rui-Hong Ju

2013-08-01

Full Text Available AIM:To evaluate the incidence of spontaneous regression of changes in the retina and vitreous in active stage of retinopathy of prematurity(ROP and identify the possible relative factors during the regression.METHODS: This was a retrospective, hospital-based study. The study consisted of 39 premature infants with mild ROP showed spontaneous regression (Group A and 17 with severe ROP who had been treated before naturally involuting (Group B from August 2008 through May 2011. Data on gender, single or multiple pregnancy, gestational age, birth weight, weight gain from birth to the sixth week of life, use of oxygen in mechanical ventilation, total duration of oxygen inhalation, surfactant given or not, need for and times of blood transfusion, 1,5,10-min Apgar score, presence of bacterial or fungal or combined infection, hyaline membrane disease (HMD, patent ductus arteriosus (PDA, duration of stay in the neonatal intensive care unit (NICU and duration of ROP were recorded.RESULTS: The incidence of spontaneous regression of ROP with stage 1 was 86.7%, and with stage 2, stage 3 was 57.1%, 5.9%, respectively. With changes in zone Ⅲ regression was detected 100%, in zoneⅡ 46.2% and in zoneⅠ 0%. The mean duration of ROP in spontaneous regression group was 5.65±3.14 weeks, lower than that of the treated ROP group (7.34±4.33 weeks, but this difference was not statistically significant (P=0.201. GA, 1min Apgar score, 5min Apgar score, duration of NICU stay, postnatal age of initial screening and oxygen therapy longer than 10 days were significant predictive factors for the spontaneous regression of ROP (P＜0.05. Retinal hemorrhage was the only independent predictive factor the spontaneous regression of ROP (OR 0.030, 95%CI 0.001-0.775, P=0.035.CONCLUSION:This study showed most stage 1 and 2 ROP and changes in zone Ⅲ can spontaneously regression in the end. Retinal hemorrhage is weakly inversely associated with the spontaneous regression.

Evaluation of Railway Networks with Single Track Operation Using the UIC 406 Capacity Method

DEFF Research Database (Denmark)

Landex, Alex

2009-01-01

lines and single track lines are discussed in this article. The principles of the UIC 406 of double track lines can be applied to single track lines-at least when more than one train follows each other in the same direction. In a presentation of the UIC 406 for single track operations, it is important...

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.

Common y-intercept and single compound regressions of gas-particle partitioning data vs 1/T

Science.gov (United States)

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.

Applicability of a Single Time Point Strategy for the Prediction of Area Under the Concentration Curve of Linezolid in Patients

DEFF Research Database (Denmark)

Srinivas, Nuggehally R; Syed, Muzeeb

2016-01-01

Background and Objectives: 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. Methods: 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...

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....

On-line single server dial-a-ride problems

NARCIS (Netherlands)

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

[Application of detecting and taking overdispersion into account in Poisson regression model].

Science.gov (United States)

Bouche, G; Lepage, B; Migeot, V; Ingrand, P

2009-08-01

Researchers often use the Poisson regression model to analyze count data. Overdispersion can occur when a Poisson regression model is used, resulting in an underestimation of variance of the regression model parameters. Our objective was to take overdispersion into account and assess its impact with an illustration based on the data of a study investigating the relationship between use of the Internet to seek health information and number of primary care consultations. Three methods, overdispersed Poisson, a robust estimator, and negative binomial regression, were performed to take overdispersion into account in explaining variation in the number (Y) of primary care consultations. We tested overdispersion in the Poisson regression model using the ratio of the sum of Pearson residuals over the number of degrees of freedom (chi(2)/df). We then fitted the three models and compared parameter estimation to the estimations given by Poisson regression model. Variance of the number of primary care consultations (Var[Y]=21.03) was greater than the mean (E[Y]=5.93) and the chi(2)/df ratio was 3.26, which confirmed overdispersion. Standard errors of the parameters varied greatly between the Poisson regression model and the three other regression models. Interpretation of estimates from two variables (using the Internet to seek health information and single parent family) would have changed according to the model retained, with significant levels of 0.06 and 0.002 (Poisson), 0.29 and 0.09 (overdispersed Poisson), 0.29 and 0.13 (use of a robust estimator) and 0.45 and 0.13 (negative binomial) respectively. Different methods exist to solve the problem of underestimating variance in the Poisson regression model when overdispersion is present. The negative binomial regression model seems to be particularly accurate because of its theorical distribution ; in addition this regression is easy to perform with ordinary statistical software packages.

Quantitative evaluation of a single-distance phase-retrieval method applied on in-line phase-contrast images of a mouse lung

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

Frequency Characteristics of Surface Wave Generated by Single-Line Pulsed Laser Beam with Two Kinds of Spatial Energy Profile Models: Gaussian and Square-Like

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.

Regression analysis by example

CERN Document Server

Chatterjee, Samprit

2012-01-01

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

Multiple regression analysis of anthropometric measurements influencing the cephalic index of male Japanese university students.

Science.gov (United States)

Hossain, Md Golam; Saw, Aik; Alam, Rashidul; Ohtsuki, Fumio; Kamarul, Tunku

2013-09-01

Cephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students. This study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI. The variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p regression analysis showed a greater likelihood for minimum frontal breadth (p regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI. The results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.

Unconditional and Conditional QTL Mapping for Tiller Numbers at Various Stages with Single Segment Substitution Lines in Rice (Oryza sativa L.)

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.

Applied logistic regression

CERN Document Server

Hosmer, David W; Sturdivant, Rodney X

2013-01-01

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

Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

Science.gov (United States)

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…

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

Development of a User Interface for a Regression Analysis Software Tool

Science.gov (United States)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

An easy-to -use user interface was implemented in a highly automated regression analysis tool. The user interface was developed from the start to run on computers that use the Windows, Macintosh, Linux, or UNIX operating system. Many user interface features were specifically designed such that a novice or inexperienced user can apply the regression analysis tool with confidence. Therefore, the user interface s design minimizes interactive input from the user. In addition, reasonable default combinations are assigned to those analysis settings that influence the outcome of the regression analysis. These default combinations will lead to a successful regression analysis result for most experimental data sets. The user interface comes in two versions. The text user interface version is used for the ongoing development of the regression analysis tool. The official release of the regression analysis tool, on the other hand, has a graphical user interface that is more efficient to use. This graphical user interface displays all input file names, output file names, and analysis settings for a specific software application mode on a single screen which makes it easier to generate reliable analysis results and to perform input parameter studies. An object-oriented approach was used for the development of the graphical user interface. This choice keeps future software maintenance costs to a reasonable limit. Examples of both the text user interface and graphical user interface are discussed in order to illustrate the user interface s overall design approach.

Vector regression introduced

Directory of Open Access Journals (Sweden)

Mok Tik

2014-06-01

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

Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

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.

[Accuracy of attenuation coefficient obtained by 137Cs single-transmission scanning in PET: comparison with conventional germanium line source].

Science.gov (United States)

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

Accuracy of attenuation coefficient obtained by 137Cs single-transmission scanning in PET. Comparison with conventional germanium line source

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

Applied linear regression

CERN Document Server

Weisberg, Sanford

2013-01-01

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

Height and Weight Estimation From Anthropometric Measurements Using Machine Learning Regressions.

Science.gov (United States)

Rativa, Diego; Fernandes, Bruno J T; Roque, Alexandre

2018-01-01

Height and weight are measurements explored to tracking nutritional diseases, energy expenditure, clinical conditions, drug dosages, and infusion rates. Many patients are not ambulant or may be unable to communicate, and a sequence of these factors may not allow accurate estimation or measurements; in those cases, it can be estimated approximately by anthropometric means. Different groups have proposed different linear or non-linear equations which coefficients are obtained by using single or multiple linear regressions. In this paper, we present a complete study of the application of different learning models to estimate height and weight from anthropometric measurements: support vector regression, Gaussian process, and artificial neural networks. The predicted values are significantly more accurate than that obtained with conventional linear regressions. In all the cases, the predictions are non-sensitive to ethnicity, and to gender, if more than two anthropometric parameters are analyzed. The learning model analysis creates new opportunities for anthropometric applications in industry, textile technology, security, and health care.

Evaluation of in-line Raman data for end-point determination of a coating process: Comparison of Science-Based Calibration, PLS-regression and univariate data analysis.

Science.gov (United States)

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.

Magnitude conversion to unified moment magnitude using orthogonal regression relation

Science.gov (United States)

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

Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.

Science.gov (United States)

Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun

2016-06-01

The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (Plogistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.

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.

Understanding poisson regression.

Science.gov (United States)

Hayat, Matthew J; Higgins, Melinda

2014-04-01

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

Investigation on single carbon atom transporting through the single-walled carbon nanotube by MD simulation

International Nuclear Information System (INIS)

Ding Yinfeng; Zhang Zhibin; Ke Xuezhi; Zhu Zhiyuan; Zhu Dezhang; Wang Zhenxia; Xu Hongjie

2005-01-01

The single carbon atom transporting through the single-walled carbon nanotube has been studied by molecular-dynamics (MD) simulation. We got different trajectories of the carbon atom by changing the input parameters. The simulation results indicate that the single carbon atom with low energy can transport through the carbon nanotube under some input conditions and result in different trajectories being straight line or 'rosette' or circular. (authors)

Alternative Methods of Regression

CERN Document Server

Birkes, David

2011-01-01

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

Development of Elite BPH-Resistant Wide-Spectrum Restorer Lines for Three and Two Line Hybrid Rice.

Science.gov (United States)

Fan, Fengfeng; Li, Nengwu; Chen, Yunping; Liu, Xingdan; Sun, Heng; Wang, Jie; He, Guangcun; Zhu, Yingguo; Li, Shaoqing

2017-01-01

Hybrid rice has contributed significantly to the world food security. Breeding of elite high-yield, strong-resistant broad-spectrum restorer line is an important strategy for hybrid rice in commercial breeding programs. Here, we developed three elite brown planthopper (BPH)-resistant wide-spectrum restorer lines by pyramiding big-panicle gene Gn8.1 , BPH-resistant genes Bph6 and Bph9 , fertility restorer genes Rf3, Rf4, Rf5 , and Rf6 through molecular marker assisted selection. Resistance analysis revealed that the newly developed restorer lines showed stronger BPH-resistance than any of the single-gene donor parent Luoyang-6 and Luoyang-9. Moreover, the three new restorer lines had broad spectrum recovery capabilities for Honglian CMS, Wild abortive CMS and two-line GMS sterile lines, and higher grain yields than that of the recurrent parent 9,311 under nature field conditions. Importantly, the hybrid crosses also showed good performance for grain yield and BPH-resistance. Thus, the development of elite BPH-resistant wide-spectrum restorer lines has a promising future for breeding of broad spectrum BPH-resistant high-yield varieties.

The End of the Lines for OX 169: No Binary Broad-Line Region

Science.gov (United States)

Halpern, J. P.; Eracleous, M.

2000-03-01

We show that unusual Balmer emission-line profiles of the quasar OX 169, frequently described as either self-absorbed or double peaked, are actually neither. The effect is an illusion resulting from two coincidences. First, the forbidden lines are quite strong and broad. Consequently, the [N II] λ6583 line and the associated narrow-line component of Hα present the appearance of twin Hα peaks. Second, the redshift of 0.2110 brings Hβ into coincidence with Na I D at zero redshift, and ISM absorption in Na I D divides the Hβ emission line. In spectra obtained over the past decade, we see no substantial change in the character of the line profiles and no indication of intrinsic double-peaked structure. The Hγ, Mg II, and Lyα emission lines are single peaked, and all of the emission-line redshifts are consistent once they are correctly attributed to their permitted and forbidden-line identifications. A systematic shift of up to 700 km s-1 between broad and narrow lines is seen, but such differences are common and could be due to gravitational and transverse redshift in a low-inclination disk. Stockton & Farnham had called attention to an apparent tidal tail in the host galaxy of OX 169 and speculated that a recent merger had supplied the nucleus with a coalescing pair of black holes that was now revealing its existence in the form of two physically distinct broad-line regions. Although there is no longer any evidence for two broad emission-line regions in OX 169, binary black holes should form frequently in galaxy mergers, and it is still worthwhile to monitor the radial velocities of emission lines that could supply evidence of their existence in certain objects.

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.

Accelerated Generation of Selfed Pure Line Plants for Gene Identification and Crop Breeding

Directory of Open Access Journals (Sweden)

Guijun Yan

2017-10-01

Full Text Available Production of pure lines is an important step in biological studies and breeding of many crop plants. The major types of pure lines for biological studies and breeding include doubled haploid (DH lines, recombinant inbred lines (RILs, and near isogenic lines (NILs. DH lines can be produced through microspore and megaspore culture followed by chromosome doubling while RILs and NILs can be produced through introgressions or repeated selfing of hybrids. DH approach was developed as a quicker method than conventional method to produce pure lines. However, its drawbacks of genotype-dependency and only a single chance of recombination limited its wider application. A recently developed fast generation cycling system (FGCS achieved similar times to those of DH for the production of selfed pure lines but is more versatile as it is much less genotype-dependent than DH technology and does not restrict recombination to a single event. The advantages and disadvantages of the technologies and their produced pure line populations for different purposes of biological research and breeding are discussed. The development of a concept of complete in vitro meiosis and mitosis system is also proposed. This could integrate with the recently developed technologies of single cell genomic sequencing and genome wide selection, leading to a complete laboratory based pre-breeding scheme.

ABCC5, ERCC2, XPA and XRCC1 transcript abundance levels correlate with cisplatin chemoresistance in non-small cell lung cancer cell lines

Directory of Open Access Journals (Sweden)

Khuder Sadik A

2005-05-01

Full Text Available Abstract Background Although 40–50% of non-small cell lung cancer (NSCLC tumors respond to cisplatin chemotherapy, there currently is no way to prospectively identify potential responders. The purpose of this study was to determine whether transcript abundance (TA levels of twelve selected DNA repair or multi-drug resistance genes (LIG1, ERCC2, ERCC3, DDIT3, ABCC1, ABCC4, ABCC5, ABCC10, GTF2H2, XPA, XPC and XRCC1 were associated with cisplatin chemoresistance and could therefore contribute to the development of a predictive marker. Standardized RT (StaRT-PCR, was employed to assess these genes in a set of NSCLC cell lines with a previously published range of sensitivity to cisplatin. Data were obtained in the form of target gene molecules relative to 106 β-actin (ACTB molecules. To cancel the effect of ACTB variation among the different cell lines individual gene expression values were incorporated into ratios of one gene to another. Each two-gene ratio was compared as a single variable to chemoresistance for each of eight NSCLC cell lines using multiple regression. In an effort to validate these results, six additional lines then were evaluated. Results Following validation, single variable models best correlated with chemoresistance (p ERCC2/XPC, ABCC5/GTF2H2, ERCC2/GTF2H2, XPA/XPC and XRCC1/XPC. All single variable models were examined hierarchically to achieve two variable models. The two variable model with the highest correlation was (ABCC5/GTF2H2, ERCC2/GTF2H2 with an R2 value of 0.96 (p Conclusion These results provide markers suitable for assessment of small fine needle aspirate biopsies in an effort to prospectively identify cisplatin resistant tumors.

Introduction to regression graphics

CERN Document Server

Cook, R Dennis

2009-01-01

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

Measurements on the He-Ne laser lines near 633 nm

Science.gov (United States)

Steinhaus, David W.

1983-09-01

The red line from an inexpensive He-Ne laser is made up of several closely spaced lines. To separate these lines very high spectral resolution is required. This apparatus requirement can be met by a simple modification of a student Fabry-Perot interferometer. Laboratory measurements can then be made to verify the expected number, spacing, and polarization of these lines during a single afternoon laboratory session.

The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

Directory of Open Access Journals (Sweden)

Ronald de Vlaming

2015-01-01

Full Text Available In 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 commonly used methods in animal breeding, (iii the computational feasibility, and (iv the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis. Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N<10,000 the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP. However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

Music-to-Color Associations of Single-Line Piano Melodies in Non-synesthetes.

Science.gov (United States)

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.

Use of two-part regression calibration model to correct for measurement error in episodically consumed foods in a single-replicate study design: EPIC case study.

Science.gov (United States)

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.

High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

Science.gov (United States)

Laurens, L M L; Wolfrum, E J

2013-12-18

One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

Science.gov (United States)

MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.

2005-01-01

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

Signal Integrity Analysis in Single and Bundled Carbon Nanotube Interconnects

International Nuclear Information System (INIS)

Majumder, M.K.; Pandya, N.D.; Kaushik, B.K.; Manhas, S.K.

2013-01-01

Carbon nanotube (CN T) can be considered as an emerging interconnect material in current nano scale regime. They are more promising than other interconnect materials such as Al or Cu because of their robustness to electromigration. This research paper aims to address the crosstalk-related issues (signal integrity) in interconnect lines. Different analytical models of single- (SWCNT), double- (DWCNT), and multiwalled CNTs (MWCNT) are studied to analyze the crosstalk delay at global interconnect lengths. A capacitively coupled three-line bus architecture employing CMOS driver is used for accurate estimation of crosstalk delay. Each line in bus architecture is represented with the equivalent RLC models of single and bundled SWCNT, DWCNT, and MWCNT interconnects. Crosstalk delay is observed at middle line (victim) when it switches in opposite direction with respect to the other two lines (aggressors). Using the data predicted by ITRS 2012, a comparative analysis on the basis of crosstalk delay is performed for bundled SWCNT/DWCNT and single MWCNT interconnects. It is observed that the overall crosstalk delay is improved by 40.92% and 21.37% for single MWCNT in comparison to bundled SWCNT and bundled DWCNT interconnects, respectively.

Multimoded rf delay line distribution system for the Next Linear Collider

Directory of Open Access Journals (Sweden)

S. G. Tantawi

2002-03-01

Full Text Available The delay line distribution system is an alternative to conventional pulse compression, which enhances the peak power of rf sources while matching the long pulse of those sources to the shorter filling time of accelerator structures. We present an implementation of this scheme that combines pairs of parallel delay lines of the system into single lines. The power of several sources is combined into a single waveguide delay line using a multimode launcher. The output mode of the launcher is determined by the phase coding of the input signals. The combined power is extracted from the delay line using mode-selective extractors, each of which extracts a single mode. Hence, the phase coding of the sources controls the output port of the combined power. The power is then fed to the local accelerator structures. We present a detailed design of such a system, including several implementation methods for the launchers, extractors, and ancillary high power rf components. The system is designed so that it can handle the 600 MW peak power required by the Next Linear Collider design while maintaining high efficiency.

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.

High-voltage shared-service line in the Stuttgart area

Energy Technology Data Exchange (ETDEWEB)

Goerler, W; Benz, A [Technische Werke der Stadt Stuttgart A.G. (F.R. Germany)

1976-01-01

In congested areas the line construction engineer has to cope with a great variety of difficulties - amenity problems, line crossings, and road crossings. The authors describe the prerequisites for and the construction of a HV shared-service line of approx. 25 km in the congested area of Stuttgart, where several three-phase and single- phase a.c. systems are run on one set of pylons.

The allure of multi-line games in modern slot machines.

Science.gov (United States)

Dixon, Mike J; Graydon, Candice; Harrigan, Kevin A; Wojtowicz, Lisa; Siu, Vivian; Fugelsang, Jonathan A

2014-11-01

In multi-line slot machines, players can wager on more than one line per spin. We sought to show that players preferred multi-line over single-line games, and that certain game features could cause multi-line game play to feel more rewarding. Reward was measured using post-reinforcement pauses (PRPs) following each outcome (the time between outcome delivery and the next spin). Gamblers (n = 102) played 250 spins on a 20-line game and 250 spins on a one-line game (answering questions about game experiences following each session). Playing one-line, a small credit gain (e.g. 2 cents) was a net win. In the 20-line game it was a net loss of 18 credits but was still accompanied by 'winning' sights and sounds. Most players (94%) preferred the 20-line game. PRPs for small credit gains (net losses) in the 20-line game were equivalent, or larger than in the one-line game where such gains were wins. The largest increase in PRP size was between the 0 and 2 credit conditions for both games. Thus 20-line players reacted as though these net losses of 18 credits were rewarding. Players' estimates of the number of true wins were accurate in the one-line game, but they significantly over-estimated the number of true wins in the 20-line game (P game play. Multi-line games appear to be more appealing to gaming machine ('slots') players than single-line games. These games may be particularly absorbing for those with gambling problems. © 2014 Society for the Study of Addiction.

Quantitation of triacylglycerols in edible oils by off-line comprehensive two-dimensional liquid chromatography-atmospheric pressure chemical ionization mass spectrometry using a single column.

Science.gov (United States)

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

In-line near real time monitoring of fluid streams in separation processes for used nuclear fuel - 5146

International Nuclear Information System (INIS)

Nee, K.; Nilsson, M.

2015-01-01

Applying spectroscopic tools for chemical processes has been intensively studied in various industries owing to its rapid and non-destructive analysis for detecting chemical components and determine physical characteristic in a process stream. The general complexity of separation processes for used nuclear fuel, e.g., chemical speciation, temperature variations, and prominent process security and safety concerns, require a well-secured and robust monitoring system to provide precise information of the process streams at real time without interference. Multivariate analysis accompanied with spectral measurements is a powerful statistic technique that can be used to monitor this complex chemical system. In this work, chemometric models that respond to the chemical components in the fluid samples were calibrated and validated to establish an in-line near real time monitoring system. The models show good prediction accuracy using partial least square regression analysis on the spectral data obtained from UV/Vis/NIR spectroscopies. The models were tested on a solvent extraction process using a single stage centrifugal contactor in our laboratory to determine the performance of an in-line near real time monitoring system. (authors)

Inbreeding depression in maize populations and its effects on the obtention of promising inbred lines

Directory of Open Access Journals (Sweden)

Deoclecio Domingos Garbuglio

2017-10-01

Full Text Available Inbreeding can potentially be used for the development of inbred lines containing alleles of interest, but the genetic causes that control inbreeding depression are not completely known, and there are few studies found in the literature. The present study aimed to obtain estimates of inbreeding depression for eight traits in seven tropical maize populations, analyze the effects of inbreeding over generations and environments, and predict the behavior of inbred lines in future generation S? through linear regression methods. It was found that regardless of the base population used, prediction values could vary when the model was based on only 2 generations of inbreeding due to the environmental component. The influence of the environment in this type of study could be reduced when considering 3 generations of inbreeding, allowing greater precision in predicting the phenotypes of inbred lines. The use of linear regression was effective for inbred line prediction for the different agronomic traits evaluated. The use of 3 levels of inbreeding minimizes the effects of the environmental component in inbred line prediction for grain yield. GO-S was the most promising population for inbred line extraction.

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

Science.gov (United States)

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

The Pulse Line Ion Accelerator Concept

Energy Technology Data Exchange (ETDEWEB)

Briggs, Richard J.

2006-02-15

The Pulse Line Ion Accelerator concept was motivated by the desire for an inexpensive way to accelerate intense short pulse heavy ion beams to regimes of interest for studies of High Energy Density Physics and Warm Dense Matter. A pulse power driver applied at one end of a helical pulse line creates a traveling wave pulse that accelerates and axially confines the heavy ion beam pulse. Acceleration scenarios with constant parameter helical lines are described which result in output energies of a single stage much larger than the several hundred kilovolt peak voltages on the line, with a goal of 3-5 MeV/meter acceleration gradients. The concept might be described crudely as an ''air core'' induction linac where the PFN is integrated into the beam line so the accelerating voltage pulse can move along with the ions to get voltage multiplication.

Flexible meta-regression to assess the shape of the benzene-leukemia exposure-response curve.

NARCIS (Netherlands)

Vlaanderen, J.J.|info:eu-repo/dai/nl/31403160X; Portengen, L.|info:eu-repo/dai/nl/269224742; Rothman, N.; Lan, Q.; Kromhout, H.|info:eu-repo/dai/nl/074385224; Vermeulen, R.|info:eu-repo/dai/nl/216532620

2010-01-01

BACKGROUND: Previous evaluations of the shape of the benzene-leukemia exposure-response curve (ERC) were based on a single set or on small sets of human occupational studies. Integrating evidence from all available studies that are of sufficient quality combined with flexible meta-regression models

Evaluation of Spring Wheat Recombinant Inbred Lines under Drought Stress

Directory of Open Access Journals (Sweden)

M. Moghaddaszadeh-Ahrabi

2012-07-01

Full Text Available Iran is one of arid and semi-arid regions of the world. Wheat as a strategic agricultural products faces water deficiency in most areas of the country. Therefore, identification of the resistant varieties to drought stress is one of main aims for breeders. To assess effect of drought stress at heading on 72 spring wheat recombinant inbred lines derived from American Yecora Rojo (high yielder, dwarf and early maturity as paternal parent and Iranian No. 49 line (tall and late maturiting as maternal parent cross were studied. The experiment was conducted at the Research Station of the University of Tabriz using a randomized complete block design with two replications during 2009 growing season. Based on the results from combined analysis of variance significant difference was observed among lines for all of traits studied, except for harvest index, grain number per spike and days to heading. There was significant difference between normal and drought stress conditions. Since the interaction between line and conditions was insignificant for all traits, it does therefore, provide the possibility of comparing the lines without regard to irrigation levels. Based on the means of, the traits it was found that the lines 96, 122, 123 and 155 were superior. MP, GMP and STI indices were recognized to be suitable indices to identify superior lines. With respect to these indices, lines 96, 122, 123, 138, 149 and 155 were found superior as compared with remaining lines. Based on stepwise regression analysis of grain yield with other traits, respectively grain number per spike, number of spikes/m2 and 1000 kernel weight were inserted into final model as effective variables on grain yield, which made 81/9 percent of the grain yield variation. Path analysis of grain yield and related traits, based on stepwise regression, demonstrated the significant positive direct effect for grain number per spike, number of spikes/m2 and 1000 kernel weight on grain yield

A primer for biomedical scientists on how to execute model II linear regression analysis.

Science.gov (United States)

Ludbrook, John

2012-04-01

1. There are two very different ways of executing linear regression analysis. One is Model I, when the x-values are fixed by the experimenter. The other is Model II, in which the x-values are free to vary and are subject to error. 2. I have received numerous complaints from biomedical scientists that they have great difficulty in executing Model II linear regression analysis. This may explain the results of a Google Scholar search, which showed that the authors of articles in journals of physiology, pharmacology and biochemistry rarely use Model II regression analysis. 3. I repeat my previous arguments in favour of using least products linear regression analysis for Model II regressions. I review three methods for executing ordinary least products (OLP) and weighted least products (WLP) regression analysis: (i) scientific calculator and/or computer spreadsheet; (ii) specific purpose computer programs; and (iii) general purpose computer programs. 4. Using a scientific calculator and/or computer spreadsheet, it is easy to obtain correct values for OLP slope and intercept, but the corresponding 95% confidence intervals (CI) are inaccurate. 5. Using specific purpose computer programs, the freeware computer program smatr gives the correct OLP regression coefficients and obtains 95% CI by bootstrapping. In addition, smatr can be used to compare the slopes of OLP lines. 6. When using general purpose computer programs, I recommend the commercial programs systat and Statistica for those who regularly undertake linear regression analysis and I give step-by-step instructions in the Supplementary Information as to how to use loss functions. © 2011 The Author. Clinical and Experimental Pharmacology and Physiology. © 2011 Blackwell Publishing Asia Pty Ltd.

Delivery of single accelerated particles

International Nuclear Information System (INIS)

McNulty, P.J.; Pease, V.P.; Bond, V.P.; Schimmerling, W.; Vosburgh, K.G.; Crebbin, K.; Everette, W.; Howard, J.

1978-01-01

It is desirable for certain experiments involving accelerators to have the capability of delivering just a single beam particle to the target area. The essential features of such a one-at-a-time facility are discussed. Two such facilities are described which were implemented at high-energy heavy ion accelerators without having to make major structural changes in the existing beam lines or substantially interfering with other accelerator uses. Two accelerator facilities are described which had the capability of delivering a single beam particle to the target area. This feature is necessary in certain experiments investigating visual phenomena induced by charged particles, other single particle interactions in biology, and other experiments in which the low intensities of cosmic rays need to be simulated. Both facilities were implemented without having to make structural changes in the existing beam lines or substantially interfering with other accelerator uses. (Auth.)

Reliability of single kidney glomerular filtration rate measured by a 99mTc-DTPA gamma camera technique

International Nuclear Information System (INIS)

Rehling, M.; Moller, M.L.; Jensen, J.J.; Thamdrup, B.; Lund, J.O.; Trap-Jensen, J.

1986-01-01

The reliability of a previously published method for determination of single kidney glomerular filtration rate (SKGFR) by means of technetium-99m-diethylenetriaminepenta-acetate (99mTc-DTPA) gamma camera renography was evaluated. The day-to-day variation in the calculated SKGFR values was earlier found to be 8.8%. The technique was compared to the simultaneously measured renal clearance of inulin in 19 unilaterally nephrectomized patients with GFR varying from 11 to 76 ml/min. The regression line (y = 1.04 X -2.5) did not differ significantly from the line of identity. The standard error of estimate was 4.3 ml/min. In 17 patients the inter- and intraobserver variation of the calculated SKGFR values was 1.2 ml/min and 1.3 ml/min, respectively. In 21 of 25 healthy subjects studied (age range 27-29 years), total GFR calculated from the renograms was within an established age-dependent normal range of GFR

Capacitance Regression Modelling Analysis on Latex from Selected Rubber Tree Clones

International Nuclear Information System (INIS)

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

2015-01-01

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

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.

Widespread Amazon forest tree mortality from a single cross-basin squall line event

Science.gov (United States)

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.

Construction of multiple linear regression models using blood biomarkers for selecting against abdominal fat traits in broilers.

Science.gov (United States)

Dong, J Q; Zhang, X Y; Wang, S Z; Jiang, X F; Zhang, K; Ma, G W; Wu, M Q; Li, H; Zhang, H

2018-01-01

Plasma very low-density lipoprotein (VLDL) can be used to select for low body fat or abdominal fat (AF) in broilers, but its correlation with AF is limited. We investigated whether any other biochemical indicator can be used in combination with VLDL for a better selective effect. Nineteen plasma biochemical indicators were measured in male chickens from the Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF) in the fed state at 46 and 48 d of age. The average concentration of every parameter for the 2 d was used for statistical analysis. Levels of these 19 plasma biochemical parameters were compared between the lean and fat lines. The phenotypic correlations between these plasma biochemical indicators and AF traits were analyzed. Then, multiple linear regression models were constructed to select the best model used for selecting against AF content. and the heritabilities of plasma indicators contained in the best models were estimated. The results showed that 11 plasma biochemical indicators (triglycerides, total bile acid, total protein, globulin, albumin/globulin, aspartate transaminase, alanine transaminase, gamma-glutamyl transpeptidase, uric acid, creatinine, and VLDL) differed significantly between the lean and fat lines (P linear regression models based on albumin/globulin, VLDL, triglycerides, globulin, total bile acid, and uric acid, had higher R2 (0.73) than the model based only on VLDL (0.21). The plasma parameters included in the best models had moderate heritability estimates (0.21 ≤ h2 ≤ 0.43). These results indicate that these multiple linear regression models can be used to select for lean broiler chickens. © 2017 Poultry Science Association Inc.

Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

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)

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

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)

An analysis of representative heating load lines for residential HSPF ratings

Energy Technology Data Exchange (ETDEWEB)

Rice, C. Keith [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shen, Bo [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shrestha, Som S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2015-07-01

This report describes an analysis to investigate representative heating loads for single-family detached homes using current EnergyPlus simulations (DOE 2014a). Hourly delivered load results are used to determine binned load lines using US Department of Energy (DOE) residential prototype building models (DOE 2014b) developed by Pacific Northwest National Laboratory (PNNL). The selected residential single-family prototype buildings are based on the 2006 International Energy Conservation Code (IECC 2006) in the DOE climate regions. The resulting load lines are compared with the American National Standards Institute (ANSI)/Air-Conditioning, Heating, and Refrigeration Institute (AHRI) Standard 210/240 (AHRI 2008) minimum and maximum design heating requirement (DHR) load lines of the heating seasonal performance factor (HSPF) ratings procedure for each region. The results indicate that a heating load line closer to the maximum DHR load line, and with a lower zero load ambient temperature, is more representative of heating loads predicted for EnergyPlus prototype residential buildings than the minimum DHR load line presently used to determine HSPF ratings. An alternative heating load line equation was developed and compared to binned load lines obtained from the EnergyPlus simulation results. The effect on HSPF of the alternative heating load line was evaluated for single-speed and two-capacity heat pumps, and an average HSPF reduction of 16% was found. The alternative heating load line relationship is tied to the rated cooling capacity of the heat pump based on EnergyPlus autosizing, which is more representative of the house load characteristics than the rated heating capacity. The alternative heating load line equation was found to be independent of climate for the six DOE climate regions investigated, provided an adjustable zero load ambient temperature is used. For Region IV, the default DOE climate region used for HSPF ratings, the higher load line results in an ~28

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.

riskRegression

DEFF Research Database (Denmark)

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

2017-01-01

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

An Assessment of Polynomial Regression Techniques for the Relative Radiometric Normalization (RRN of High-Resolution Multi-Temporal Airborne Thermal Infrared (TIR Imagery

Directory of Open Access Journals (Sweden)

Mir Mustafizur Rahman

2014-11-01

Full Text Available Thermal Infrared (TIR remote sensing images of urban environments are increasingly available from airborne and satellite platforms. However, limited access to high-spatial resolution (H-res: ~1 m TIR satellite images requires the use of TIR airborne sensors for mapping large complex urban surfaces, especially at micro-scales. A critical limitation of such H-res mapping is the need to acquire a large scene composed of multiple flight lines and mosaic them together. This results in the same scene components (e.g., roads, buildings, green space and water exhibiting different temperatures in different flight lines. To mitigate these effects, linear relative radiometric normalization (RRN techniques are often applied. However, the Earth’s surface is composed of features whose thermal behaviour is characterized by complexity and non-linearity. Therefore, we hypothesize that non-linear RRN techniques should demonstrate increased radiometric agreement over similar linear techniques. To test this hypothesis, this paper evaluates four (linear and non-linear RRN techniques, including: (i histogram matching (HM; (ii pseudo-invariant feature-based polynomial regression (PIF_Poly; (iii no-change stratified random sample-based linear regression (NCSRS_Lin; and (iv no-change stratified random sample-based polynomial regression (NCSRS_Poly; two of which (ii and iv are newly proposed non-linear techniques. When applied over two adjacent flight lines (~70 km2 of TABI-1800 airborne data, visual and statistical results show that both new non-linear techniques improved radiometric agreement over the previously evaluated linear techniques, with the new fully-automated method, NCSRS-based polynomial regression, providing the highest improvement in radiometric agreement between the master and the slave images, at ~56%. This is ~5% higher than the best previously evaluated linear technique (NCSRS-based linear regression.

Comparison of single-word and adjective-noun phrase production using event-related brain potentials

DEFF Research Database (Denmark)

Lange, Violaine Michel

2015-01-01

stimuli varying in complexity -black and white line drawings, coloured line drawings, and arrays of drawings-in participants producing single nouns. Whilst naming latencies were similar for single noun production between visual stimuli conditions, ERPs differed between drawing arrays and single drawings...... in a time-window extending beyond early visual analysis. In a second experiment, different participants were asked to produce either single noun or adjective-noun dual-word phrases to black-and-white and coloured line drawings, respectively. Adjective-noun phrase production (2W) resulted in naming latencies...

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...

Theory of Moessbauer line broadening due to diffusion

International Nuclear Information System (INIS)

Schroeder, K.; Wolf, D.; Dederichs, P.H.

1981-12-01

We have calculated the line broadening of the Moessbauer line due to diffusion of Moessbauer atoms via single vacanices. We take into account the perturbation of vacancy jumps in the neighbourhood of an impurity Moessbauer atom (e.g. Fe in Al) using the 5-frequency model. The anisotropy of the line width is given by the Fourier transform of the final distribution of a Moessbauer atom after an encounter with a vacancy. This distribution is calculated by Monte Carlo computer simulation. 3 figures, 1 tables

A single incision transaxillary thoracoscopic sympathectomy

Directory of Open Access Journals (Sweden)

Marić Nebojša

2014-01-01

Full Text Available Background/Aim. Primary hyperhidrosis causes are unknown. The disorder begins in early childhood. It intensifies in puberty and maturity. It is equally present in both sexes. The symptoms exacerbate when the body temperature rises and due to emotional stimuli affecting the sympathetic nerve system. The aim of this study was to demonstrate that videoassisted thoracoscopic surgery (VATS sympathectomy is a method for primary focal hyperhidrosis permanent treatment. The single incision method in properly selected patients maximizes the intervention effectiveness and minimizes aesthetic side effects. Methods. This prospective study analysed the findings in patients who had been operated on due to primary focal hyperhidrosis (face, palms, and armpits using a single small transaxilarry incision in the third inter-rib space at the level of the anterior axillary line with two 5 mm flexible ports. All the patients, with T2-T5 thoracoscopic sympathectomy of the sympathetic chain using a single small incision in the third inter-rib space in the anterior axillary line, were analysed in the period from September 2009 to November 2010 regarding the postoperative morbidity and outcomes of the operation (clinical evaluation and visual analogue scale with a view to assessing the effectiveness of the surgery conducted in this manner. Results. A total of 47 patients (18 men, 29 women, 18 to 48 years old (29 on average had underwent 94 bilateral video-assisted thoracoscopic sympathectomies. The sympathectomy was indicated in cases of facial blushing and sweating (6.38%, palmary sweating (34.04%, axillary sweating (14.89% or both palmary and axillary sweating (44.68%. The largest percentage of patients (98.6% had left the hospital the following day. The postoperative 30 day’s mortality was 0 and the conversion into open surgery was not necessary. As for complications, there had been an occurrence of partial pneumothorax in two patients treated by means of

Measurement of the single 100 diffraction line and evaluation of the average crystallite sizes along the fiber axis for mesophase-pitch-based carbon fiber P100

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)

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

Registration of Urban Aerial Image and LiDAR Based on Line Vectors

Directory of Open Access Journals (Sweden)

Qinghong Sheng

2017-09-01

Full Text Available In a traditional registration of a single aerial image with airborne light detection and ranging (LiDAR data using linear features that regard line direction as a control or linear features as constraints in the solution, lacking the constraint of linear position leads to the error propagation of the adjustment model. To solve this problem, this paper presents a line vector-based registration mode (LVR in which image rays and LiDAR lines are expressed by a line vector that integrates the line direction and the line position. A registration equation of line vector is set up by coplanar imaging rays and corresponding control lines. Three types of datasets consisting of synthetic, theInternational Society for Photogrammetry and Remote Sensing (ISPRS test project, and real aerial data are used. A group of progressive experiments is undertaken to evaluate the robustness of the LVR. Experimental results demonstrate that the integrated line direction and the line position contributes a great deal to the theoretical and real accuracies of the unknowns, as well as the stability of the adjustment model. This paper provides a new suggestion that, for a single image and LiDAR data, registration in urban areas can be accomplished by accommodating rich line features.

Type 2 Active Galactic Nuclei with Double-peaked [O III] Lines. II. Single AGNs with Complex Narrow-line Region Kinematics are More Common than Binary AGNs

Science.gov (United States)

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

Regression in autistic spectrum disorders.

Science.gov (United States)

Stefanatos, Gerry A

2008-12-01

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

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression.

Science.gov (United States)

Yu, Xu; Lin, Jun-Yu; Jiang, Feng; Du, Jun-Wei; Han, Ji-Zhong

2018-01-01

Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

Understanding logistic regression analysis

OpenAIRE

Sperandei, Sandro

2014-01-01

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

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?

Science.gov (United States)

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.

A Generalized Logistic Regression Procedure to Detect Differential Item Functioning among Multiple Groups

Science.gov (United States)

Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul

2011-01-01

We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…

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

Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

Science.gov (United States)

Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

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.

Multiple linear stepwise regression of liver lipid levels: proton MR spectroscopy study in vivo at 3.0 T

International Nuclear Information System (INIS)

Xu Li; Liang Changhong; Xiao Yuanqiu; Zhang Zhonglin

2010-01-01

Objective: To analyze the correlations between liver lipid level determined by liver 3.0 T 1 H-MRS in vivo and influencing factors using multiple linear stepwise regression. Methods: The prospective study of liver 1 H-MRS was performed with 3.0 T system and eight-channel torso phased-array coils using PRESS sequence. Forty-four volunteers were enrolled in this study. Liver spectra were collected with a TR of 1500 ms, TE of 30 ms, volume of interest of 2 cm×2 cm×2 cm, NSA of 64 times. The acquired raw proton MRS data were processed by using a software program SAGE. For each MRS measurement, using water as the internal reference, the amplitude of the lipid signal was normalized to the sum of the signal from lipid and water to obtain percentage lipid within the liver. The statistical description of height, weight, age and BMI, Line width and water suppression were recorded, and Pearson analysis was applied to test their relationships. Multiple linear stepwise regression was used to set the statistical model for the prediction of Liver lipid content. Results: Age (39.1±12.6) years, body weight (64.4±10.4) kg, BMI (23.3±3.1) kg/m 2 , linewidth (18.9±4.4) and the water suppression (90.7±6.5)% had significant correlation with liver lipid content (0.00 to 0.96%, median 0.02%), r were 0.11, 0.44, 0.40, 0.52, -0.73 respectively (P<0.05). But only age, BMI, line width, and the water suppression entered into the multiple linear regression equation. Liver lipid content prediction equation was as follows: Y= 1.395 - (0.021×water suppression) + (0.022×BMI) + (0.014×line width) - (0.004×age), and the coefficient of determination was 0. 613, corrected coefficient of determination was 0.59. Conclusion: The regression model fitted well, since the variables of age, BMI, width, and water suppression can explain about 60% of liver lipid content changes. (authors)

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...

Determining the Pressure Shift of Helium I Lines Using White Dwarf Stars

Science.gov (United States)

Camarota, Lawrence

This dissertation explores the non-Doppler shifting of Helium lines in the high pressure conditions of a white dwarf photosphere. In particular, this dissertation seeks to mathematically quantify the shift in a way that is simple to reproduce and account for in future studies without requiring prior knowledge of the star's bulk properties (mass, radius, temperature, etc.). Two main methods will be used in this analysis. First, the spectral line will be quantified with a continuous wavelet transformation, and the components will be used in a chi2 minimizing linear regression to predict the shift. Second, the position of the lines will be calculated using a best-fit Levy-alpha line function. These techniques stand in contrast to traditional methods of quantifying the center of often broad spectral lines, which usually assume symmetry on the parts of the lines.

The concentrations of clinafloxacin in alveolar macrophages, epithelial lining fluid, bronchial mucosa and serum after administration of single 200 mg oral doses to patients undergoing fibre-optic bronchoscopy.

Science.gov (United States)

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.

Defect dependence of the irreversibility line in Bi2Sr2CaCu2O8 single crystals

Science.gov (United States)

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.

Quantile regression theory and applications

CERN Document Server

Davino, Cristina; Vistocco, Domenico

2013-01-01

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

Fungible weights in logistic regression.

Science.gov (United States)

Jones, Jeff A; Waller, Niels G

2016-06-01

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

Spontaneous regression of cerebral arteriovenous malformations: clinical and angiographic analysis with review of the literature

International Nuclear Information System (INIS)

Lee, S.K.; Vilela, P.; Willinsky, R.; TerBrugge, K.G.

2002-01-01

Spontaneous regression of cerebral arteriovenous malformation (AVM) is rare and poorly understood. We reviewed the clinical and angiographic findings in patients who had spontaneous regression of cerebral AVMs to determine whether common features were present. The clinical and angiographic findings of four cases from our series and 29 cases from the literature were retrospectively reviewed. The clinical and angiographic features analyzed were: age at diagnosis, initial presentation, venous drainage pattern, number of draining veins, location of the AVM, number of arterial feeders, clinical events during the interval period to thrombosis, and interval period to spontaneous thrombosis. Common clinical and angiographic features of spontaneous regression of cerebral AVMs are: intracranial hemorrhage as an initial presentation, small AVMs, and a single draining vein. Spontaneous regression of cerebral AVMs can not be predicted by clinical or angiographic features, therefore it should not be considered as an option in cerebral AVM management, despite its proven occurrence. (orig.)

Integration of association statistics over genomic regions using Bayesian adaptive regression splines

Directory of Open Access Journals (Sweden)

Zhang Xiaohua

2003-11-01

Full Text Available Abstract In the search for genetic determinants of complex disease, two approaches to association analysis are most often employed, testing single loci or testing a small group of loci jointly via haplotypes for their relationship to disease status. It is still debatable which of these approaches is more favourable, and under what conditions. The former has the advantage of simplicity but suffers severely when alleles at the tested loci are not in linkage disequilibrium (LD with liability alleles; the latter should capture more of the signal encoded in LD, but is far from simple. The complexity of haplotype analysis could be especially troublesome for association scans over large genomic regions, which, in fact, is becoming the standard design. For these reasons, the authors have been evaluating statistical methods that bridge the gap between single-locus and haplotype-based tests. In this article, they present one such method, which uses non-parametric regression techniques embodied by Bayesian adaptive regression splines (BARS. For a set of markers falling within a common genomic region and a corresponding set of single-locus association statistics, the BARS procedure integrates these results into a single test by examining the class of smooth curves consistent with the data. The non-parametric BARS procedure generally finds no signal when no liability allele exists in the tested region (ie it achieves the specified size of the test and it is sensitive enough to pick up signals when a liability allele is present. The BARS procedure provides a robust and potentially powerful alternative to classical tests of association, diminishes the multiple testing problem inherent in those tests and can be applied to a wide range of data types, including genotype frequencies estimated from pooled samples.

Multidimensional Models of Type Ia Supernova Nebular Spectra: Strong Emission Lines from Stripped Companion Gas Rule Out Classic Single-degenerate Systems

Science.gov (United States)

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.

Multiple Lines of Evidence

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

Tumor regression induced by intratumor therapy with a disabled infectious single cycle (DISC) herpes simplex virus (HSV) vector, DISC/HSV/murine granulocyte-macrophage colony-stimulating factor, correlates with antigen-specific adaptive immunity.

Science.gov (United States)

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.

Principal component regression analysis with SPSS.

Science.gov (United States)

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

UPregulated single-stranded DNA-binding protein 1 induces cell chemoresistance to cisplatin in lung cancer cell lines.

Science.gov (United States)

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.

Single Parenthood and Children's Reading Performance in Asia

Science.gov (United States)

Park, Hyunjoon

2007-01-01

Using the data from Program for International Student Assessment, I examine the gap in reading performance between 15-year-old students in single-parent and intact families in 5 Asian countries in comparison to the United States. The ordinary least square regression analyses show negligible disadvantages of students with a single parent in Hong…

Testing of a Fiber Optic Wear, Erosion and Regression Sensor

Science.gov (United States)

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.

ALFA: an automated line fitting algorithm

Science.gov (United States)

Wesson, R.

2016-03-01

I present the automated line fitting algorithm, ALFA, a new code which can fit emission line spectra of arbitrary wavelength coverage and resolution, fully automatically. In contrast to traditional emission line fitting methods which require the identification of spectral features suspected to be emission lines, ALFA instead uses a list of lines which are expected to be present to construct a synthetic spectrum. The parameters used to construct the synthetic spectrum are optimized by means of a genetic algorithm. Uncertainties are estimated using the noise structure of the residuals. An emission line spectrum containing several hundred lines can be fitted in a few seconds using a single processor of a typical contemporary desktop or laptop PC. I show that the results are in excellent agreement with those measured manually for a number of spectra. Where discrepancies exist, the manually measured fluxes are found to be less accurate than those returned by ALFA. Together with the code NEAT, ALFA provides a powerful way to rapidly extract physical information from observations, an increasingly vital function in the era of highly multiplexed spectroscopy. The two codes can deliver a reliable and comprehensive analysis of very large data sets in a few hours with little or no user interaction.

Differential Radiosensitizing Potential of Temozolomide in MGMT Promoter Methylated Glioblastoma Multiforme Cell Lines

International Nuclear Information System (INIS)

Nifterik, Krista A. van; Berg, Jaap van den; Stalpers, Lukas J.A.; Lafleur, M. Vincent M.; Leenstra, Sieger; Slotman, Ben J.; Hulsebos, Theo J.M.; Sminia, Peter

2007-01-01

Purpose: To investigate the radiosensitizing potential of temozolomide (TMZ) for human glioblastoma multiforme (GBM) cell lines using single-dose and fractionated γ-irradiation. Methods and Materials: Three genetically characterized human GBM cell lines (AMC-3046, VU-109, and VU-122) were exposed to various single (0-6 Gy) and daily fractionated doses (2 Gy per fraction) of γ-irradiation. Repeated TMZ doses were given before and concurrent with irradiation treatment. Immediately plated clonogenic cell-survival curves were determined for both the single-dose and the fractionated irradiation experiments. To establish the net effect of clonogenic cell survival and cell proliferation, growth curves were determined, expressed as the number of surviving cells. Results: All three cell lines showed MGMT promoter methylation, lacked MGMT protein expression, and were sensitive to TMZ. The isotoxic TMZ concentrations used were in a clinically feasible range of 10 μmol/L (AMC-3046), 3 μmol/L (VU-109), and 2.5 μmol/L (VU-122). Temozolomide was able to radiosensitize two cell lines (AMC 3046 and VU-122) using single-dose irradiation. A reduction in the number of surviving cells after treatment with the combination of TMZ and fractionated irradiation was seen in all three cell lines, but only AMC 3046 showed a radiosensitizing effect. Conclusions: This study on TMZ-sensitive GBM cell lines shows that TMZ can act as a radiosensitizer and is at least additive to γ-irradiation. Enhancement of the radiation response by TMZ seems to be independent of the epigenetically silenced MGMT gene

Transfer line tests take centre stage

CERN Multimedia

Katarina Anthony

2014-01-01

Last weekend, proton beams came knocking on the LHC's door. Shooting from the SPS and into the two LHC transfer lines, the proton beams were dumped just short of entering the accelerator.   The upper plot shows the trajectory of the first TI2 beam, which reached the end of the transfer line in a single attempt after 18 months of technical stop. Below, a smoother beam trajectory in TI2 after some corrections. For the first time since Run 1, the SPS to LHC transfer lines (TI8 and TI2) transported proton beams just short of the LHC. "We tested the beam instrumentation, the devices that measure the beam intensity, transverse beam profile, position and losses, as well as the beam collimators along the transfer lines," says Reyes Alemany Fernandez, the engineer in charge of the LHC. "We were also able to spot possible bottle necks in the beam trajectory and to perform the first optics measurements." Once the beams arrived at the transfer line beam dumps...

Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items

Science.gov (United States)

Lu, Irene R. R.; Thomas, D. Roland

2008-01-01

This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…

Single-electron tunnel junction array

International Nuclear Information System (INIS)

Likharev, K.K.; Bakhvalov, N.S.; Kazacha, G.S.; Serdyukova, S.I.

1989-01-01

The authors have carried out an analysis of statics and dynamics of uniform one-dimensional arrays of ultrasmall tunnel junctions. The correlated single-electron tunneling in the junctions of the array results in its behavior qualitatively similar to that of the Josephson transmission line. In particular, external electric fields applied to the array edges can inject single-electron-charged solitons into the array interior. Shape of such soliton and character of its interactions with other solitons and the array edges are very similar to those of the Josephson vortices (sine-Gordon solitons) in the Josephson transmission line. Under certain conditions, a coherent motion of the soliton train along the array is possible, resulting in generation of narrowband SET oscillations with frequency f/sub s/ = /e where is the dc current flowing along the array

Line outage contingency analysis including the system islanding scenario

Energy Technology Data Exchange (ETDEWEB)

Hazarika, D.; Bhuyan, S. [Assam Engineering College, Jalukbari, Guwahati 781013 (India); Chowdhury, S.P. [Jadavpur University, Jadavpur, Kolkata 700 032 (India)

2006-05-15

The paper describes an algorithm for determining the line outage contingency of a line taking into account of line over load effect in remaining lines and subsequent tripping of over loaded line(s) leading to possible system split or islanding of a power system. The optimally ordered sparse [B'], [B'] matrices for the integrated system are used for load flow analysis to determine modified values of voltage phase angles [{delta}] and bus voltages [V] to determine the over loading effect on the remaining lines due to outage of a selected line outage contingency. In case of over loading in remaining line(s), the over loaded lines are removed from the system and a topology processor is used to find the islands. A fast decoupled load flow (FDLF) analysis is carried out for finding out the system variables for the islanded (or single island) system by incorporating appropriate modification in the [B'] and [B'] matrices of the integrated system. Line outage indices based on line overload, loss of load, loss of generation and static voltage stability are computed to indicate severity of a line outage of a selected line. (author)

Retrieving relevant factors with exploratory SEM and principal-covariate regression: A comparison.

Science.gov (United States)

Vervloet, Marlies; Van den Noortgate, Wim; Ceulemans, Eva

2018-02-12

Behavioral researchers often linearly regress a criterion on multiple predictors, aiming to gain insight into the relations between the criterion and predictors. Obtaining this insight from the ordinary least squares (OLS) regression solution may be troublesome, because OLS regression weights show only the effect of a predictor on top of the effects of other predictors. Moreover, when the number of predictors grows larger, it becomes likely that the predictors will be highly collinear, which makes the regression weights' estimates unstable (i.e., the "bouncing beta" problem). Among other procedures, dimension-reduction-based methods have been proposed for dealing with these problems. These methods yield insight into the data by reducing the predictors to a smaller number of summarizing variables and regressing the criterion on these summarizing variables. Two promising methods are principal-covariate regression (PCovR) and exploratory structural equation modeling (ESEM). Both simultaneously optimize reduction and prediction, but they are based on different frameworks. The resulting solutions have not yet been compared; it is thus unclear what the strengths and weaknesses are of both methods. In this article, we focus on the extents to which PCovR and ESEM are able to extract the factors that truly underlie the predictor scores and can predict a single criterion. The results of two simulation studies showed that for a typical behavioral dataset, ESEM (using the BIC for model selection) in this regard is successful more often than PCovR. Yet, in 93% of the datasets PCovR performed equally well, and in the case of 48 predictors, 100 observations, and large differences in the strengths of the factors, PCovR even outperformed ESEM.

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression

Directory of Open Access Journals (Sweden)

Xu Yu

2018-01-01

Full Text Available Cross-domain collaborative filtering (CDCF solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR. We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

Narrow line-width Tm3+ doped double-clad silica fiber laser based on in-line cascade biconical tapers filter

International Nuclear Information System (INIS)

Tian, Y; Zhao, J Q; Wang, W; Wang, Y Z; Gao, W

2010-01-01

Narrow line-width 793 nm laser diode cladding pumped Tm 3+ doped double cladding silica fiber laser with in-line four concatenated tapers filter was reported for the first time to our knowledge. These cascade tapers located 3.6 cm from the output end of the fiber laser was fabricated by heating and stretching method. The taper's transmitted power response as a function of wavelength was described by using local mode coupling theory and successive tapers filter model. The wavelength filter function of the in-line cascade tapers in a linear cavity fiber laser was demonstrated, and the experimental result agreed with these theories. The maximum output laser power was 736 mW, corresponding to single peak of laser spectrum with narrow line-width of ∼ 60 pm

Detection of sensor degradation using K-means clustering and support vector regression in nuclear power plant

International Nuclear Information System (INIS)

Seo, Inyong; Ha, Bokam; Lee, Sungwoo; Shin, Changhoon; Lee, Jaeyong; Kim, Seongjun

2011-01-01

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be rectified. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this study, an on-line calibration monitoring called KPCSVR using k-means clustering and principal component based Auto-Associative support vector regression (PCSVR) is proposed for nuclear power plant. To reduce the training time of the model, k-means clustering method was used. Response surface methodology is employed to efficiently determine the optimal values of support vector regression hyperparameters. The proposed KPCSVR model was confirmed with actual plant data of Kori Nuclear Power Plant Unit 3 which were measured from the primary and secondary systems of the plant, and compared with the PCSVR model. By using data clustering, the average accuracy of PCSVR improved from 1.228×10 -4 to 0.472×10 -4 and the average sensitivity of PCSVR from 0.0930 to 0.0909, which results in good detection of sensor drift. Moreover, the training time is greatly reduced from 123.5 to 31.5 sec. (author)

Logistic regression models

CERN Document Server

Hilbe, Joseph M

2009-01-01

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

Calculation of the Magnetic Fields of the Electric Power Line

Directory of Open Access Journals (Sweden)

Patsiuk V.

2016-12-01

Full Text Available The task of calculation of per unit length parameters of multi-conductor electrical overhead transmission lines has been treated in the paper. The calculation of distribution of electric and magnetic fields has been performed by means of the finite volume method for entire span of the line. The theoretical justification of the method for calculation the parameters of electromagnetic field taking into account the change of the vector of magnetic potential along the line has been given. The problems of electrostatic and magnetostatic for a single electric conductor and unlimited long conductor with current have been solved. For the inner and total inductivities of a single conductor under the current have been obtained relationships and drawn dependences. Dependence between the speeds of light and of electromagnetic wave’s propagation has been presented. Based on the characteristics of distribution of electric and magnetic fields of multi-conductor lines has been provided the method of calculation of the matrix of own and mutual capacitances and inductivities the calculated values of per unit length parameters of compact 110 kV electric line which is in concordance with one of basic physical constant – the speed of light.

Living alone: exploring variations in single motherhood and child ...

African Journals Online (AJOL)

Two specifications were fitted to analyze the effect of single mother characteristics on child health using binomial logistic regression. The result of unadjusted and adjusted models indicates that never married, cohabiting, are important correlates of child health. When adjusted for covariates, the effect of single motherhood on ...

In-line moisture monitoring in fluidized bed granulation using a novel multi-resonance microwave sensor.

Science.gov (United States)

Peters, Johanna; Bartscher, Kathrin; Döscher, Claas; Taute, Wolfgang; Höft, Michael; Knöchel, Reinhard; Breitkreutz, Jörg

2017-08-01

Microwave resonance technology (MRT) is known as a process analytical technology (PAT) tool for moisture measurements in fluid-bed granulation. It offers a great potential for wet granulation processes even where the suitability of near-infrared (NIR) spectroscopy is limited, e.g. colored granules, large variations in bulk density. However, previous sensor systems operating around a single resonance frequency showed limitations above approx. 7.5% granule moisture. This paper describes the application of a novel sensor working with four resonance frequencies. In-line data of all four resonance frequencies were collected and further processed. Based on calculation of density-independent microwave moisture values multiple linear regression (MLR) models using Karl-Fischer titration (KF) as well as loss on drying (LOD) as reference methods were build. Rapid, reliable in-process moisture control (RMSEP≤0.5%) even at higher moisture contents was achieved. Copyright © 2017 Elsevier B.V. All rights reserved.

Computing group cardinality constraint solutions for logistic regression problems.

Science.gov (United States)

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.

Logistic regression applied to natural hazards: rare event logistic regression with replications

Science.gov (United States)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Electromagnetic energy flow lines as possible paths of photons

Energy Technology Data Exchange (ETDEWEB)

Davidovic, M [Faculty of Civil Engineering, University of Belgrade, Bulevar Kralja Aleksandra 73, 11000 Belgrade (Serbia); Sanz, A S; Miret-Artes, S [Instituto de Fisica Fundamental, Consejo Superior de Investigaciones CientIficas, Serrano 123, 28006 Madrid (Spain); Arsenovic, D; Bozic, M [Institute of Physics, University of Belgrade, Pregrevica 118, 11080 Belgrade (Serbia)], E-mail: milena@grf.bg.ac.yu, E-mail: asanz@imaff.cfmac.csic.es, E-mail: arsenovic@phy.bg.ac.yu, E-mail: bozic@phy.bg.ac.yu, E-mail: s.miret@imaff.cfmac.csic.es

2009-07-15

Motivated by recent experiments where interference patterns behind a grating are obtained by accumulating single photon events, we provide here an electromagnetic energy flow-line description to explain the emergence of such patterns. We find and discuss an analogy between the equation describing these energy flow lines and the equation of Bohmian trajectories used to describe the motion of massive particles.

In-Line Oil-Water Separation in Swirling Flow (USB stick)

NARCIS (Netherlands)

Slot, J.J.; van Campen, L.J.A.M.; Hoeijmakers, Hendrik Willem Marie; Mudde, R.F.; Johansen, S.T.

2011-01-01

An in-line oil-water separator has been designed and is investigated for single- and two-phase flow. Numerical single-phase flow results show an annular reversed flow region. This flow pattern agrees qualitatively with results from measurements. In the two-phase flow simulations two different drag

Pair- ${v}$ -SVR: A Novel and Efficient Pairing nu-Support Vector Regression Algorithm.

Science.gov (United States)

Hao, Pei-Yi

This paper proposes a novel and efficient pairing nu-support vector regression (pair--SVR) algorithm that combines successfully the superior advantages of twin support vector regression (TSVR) and classical -SVR algorithms. In spirit of TSVR, the proposed pair--SVR solves two quadratic programming problems (QPPs) of smaller size rather than a single larger QPP, and thus has faster learning speed than classical -SVR. The significant advantage of our pair--SVR over TSVR is the improvement in the prediction speed and generalization ability by introducing the concepts of the insensitive zone and the regularization term that embodies the essence of statistical learning theory. Moreover, pair--SVR has additional advantage of using parameter for controlling the bounds on fractions of SVs and errors. Furthermore, the upper bound and lower bound functions of the regression model estimated by pair--SVR capture well the characteristics of data distributions, thus facilitating automatic estimation of the conditional mean and predictive variance simultaneously. This may be useful in many cases, especially when the noise is heteroscedastic and depends strongly on the input values. The experimental results validate the superiority of our pair--SVR in both training/prediction speed and generalization ability.This paper proposes a novel and efficient pairing nu-support vector regression (pair--SVR) algorithm that combines successfully the superior advantages of twin support vector regression (TSVR) and classical -SVR algorithms. In spirit of TSVR, the proposed pair--SVR solves two quadratic programming problems (QPPs) of smaller size rather than a single larger QPP, and thus has faster learning speed than classical -SVR. The significant advantage of our pair--SVR over TSVR is the improvement in the prediction speed and generalization ability by introducing the concepts of the insensitive zone and the regularization term that embodies the essence of statistical learning theory

Understanding logistic regression analysis.

Science.gov (United States)

Sperandei, Sandro

2014-01-01

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

Single-dose radiosurgical treatment for hepatic metastases - therapeutic outcome of 138 treated lesions from a single institution

International Nuclear Information System (INIS)

Habermehl, Daniel; Herfarth, Klaus K; Bermejo, Justo Lorenzo; Hof, Holger; Rieken, Stefan; Kuhn, Sabine; Welzel, Thomas; Debus, Jürgen; Combs, Stephanie E

2013-01-01

Local ablative therapies such as stereotactically guided single-dose radiotherapy or helical intensity-modulated radiotherapy (tomotherapy) with high single-doses are successfully applied in many centers in patients with liver metastasis not suitable for surgical resection. This study presents results from more than 10 years of clinical experience and evaluates long-term outcome and efficacy of this therapeutic approach. From 1997 to 2009 a total of 138 intrahepatic tumors of 90 patients were irradiated with single doses of 17 to 30 Gy (median dose 24 Gy). Median age of the patients was 64 years (range 31–89 years). Most frequent underlying tumor histologies were colorectal adenocarcinoma (70 lesions) and breast cancer (27 lesions). In 35 treatment sessions multiple targets were simultaneously irradiated (up to four lesions at once). Local progression-free (PFS) and overall survival (OS) after treatment were investigated using uni- and multiple survival regression models. Median overall survival of all patients was 24.3 months. Local PFS was 87%, 70% and 59% after 6, 12 and 18 months, respectively. Median time to local progression was 25.5 months. Patients with a single lesion and no further metastases at time of RT had a favorable median PFS of 43.1 months according to the Kaplan-Meier estimator. The type of tumor showed a statistical significant influence on local PFS, with a better prognosis for breast cancer histology than for colorectal carcinoma in uni- and multiple regression analysis (p = 0.05). Multiple regression analysis revealed no influence of planning target volume (PTV), patient age and radiation dose on local PFS. Treatment was well tolerated with no severe adverse events. This study confirms safety of SBRT in liver lesions, with 6- and 12 months local control of 87% and 70%. The dataset represents the clinical situation in a large oncology setting, with many competing treatment options and heterogeneous patient characteristics

Computational neural network regression model for Host based Intrusion Detection System

Directory of Open Access Journals (Sweden)

Sunil Kumar Gautam

2016-09-01

Full Text Available The current scenario of information gathering and storing in secure system is a challenging task due to increasing cyber-attacks. There exists computational neural network techniques designed for intrusion detection system, which provide security to single machine and entire network's machine. In this paper, we have used two types of computational neural network models, namely, Generalized Regression Neural Network (GRNN model and Multilayer Perceptron Neural Network (MPNN model for Host based Intrusion Detection System using log files that are generated by a single personal computer. The simulation results show correctly classified percentage of normal and abnormal (intrusion class using confusion matrix. On the basis of results and discussion, we found that the Host based Intrusion Systems Model (HISM significantly improved the detection accuracy while retaining minimum false alarm rate.

Identification of Single Nucleotide Polymorphisms and analysis of Linkage Disequilibrium in sunflower elite inbred lines using the candidate gene approach

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

DRREP: deep ridge regressed epitope predictor.

Science.gov (United States)

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.

Potencial de híbridos simples de milho para extração de linhagens Potential of maize single hybrids to generate inbred lines

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

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

Science.gov (United States)

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

2016-03-01

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

Effect of Single or Combined Climatic and Hygienic Stress in Four Layer Lines: 1. Performance

NARCIS (Netherlands)

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

Minimax Regression Quantiles

DEFF Research Database (Denmark)

Bache, Stefan Holst

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

Natural Head Posture in the Setting of Sagittal Spinal Deformity: Validation of Chin-Brow Vertical Angle, Slope of Line of Sight, and McGregor's Slope With Health-Related Quality of Life.

Science.gov (United States)

Lafage, Renaud; Challier, Vincent; Liabaud, Barthelemy; Vira, Shaleen; Ferrero, Emmanuelle; Diebo, Bassel G; Liu, Shian; Vital, Jean-Marc; Mazda, Keyvan; Protopsaltis, Themistocles S; Errico, Thomas J; Schwab, Frank J; Lafage, Virginie

2016-07-01

The maintenance of horizontal gaze is an essential function of upright posture and global sagittal spinal alignment. Horizontal gaze is classically measured by the chin-brow vertical angle (CBVA), which is not readily measured on most lateral spine radiographs. To evaluate relations between CBVA and the slope of the line of sight, the slope of McGregor's line (McGS), and Oswestry Disability Index. Patients were identified from a single center database of 531 spine patients who underwent full-body EOS x-rays. Correlations between CBVA, the slope of the line of sight, and McGS were assessed. Using a quadratic regression with Oswestry Disability Index and CBVA, windows of low disability were identified. Comparison of sagittal spinopelvic parameters was carried out between patients with "ascending gaze" and "neutral position." Three hundred three patients were included (74% female, mean age 54.8 years, body mass index 26.6 ± 6.0 kg/m). CBVA strongly correlated with the slope of the line of sight (r = 0.996) and McGS (r = 0.862). Regression studies between Oswestry Disability Index and CBVA yielded a range of values corresponding to low disability (-4.7 degrees to 17.7 degrees). Similarly, a low disability range for the slope of the line of sight (-5.1 degrees to 18.5 degrees) and McGS (-5.7 degrees to 14.3 degrees) was computed. Patients with "ascending gaze" had a worse spinopelvic alignment than "neutral position" patients. The slope of the line of sight and McGS correlated strongly with CBVA and can be used as surrogate measures. The range of values for these measures corresponding to low disability was identified. These values can be used as a general guideline to assess alignment for diagnostic purposes. Cervical compensatory mechanism may modify the natural head position in sagittally misaligned patients. CBVA, chin-brow vertical angleHRQoL, health-related quality of lifeMcGS, slope of McGregor's lineODI, Oswestry Disability IndexSLs, slope of the line of sight.

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...

Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models

Energy Technology Data Exchange (ETDEWEB)

Pappas, S.S. [Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi, 83 200 Samos (Greece); Ekonomou, L.; Chatzarakis, G.E. [Department of Electrical Engineering Educators, ASPETE - School of Pedagogical and Technological Education, N. Heraklion, 141 21 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24100 Kalamata (Greece); Katsikas, S.K. [Department of Technology Education and Digital Systems, University of Piraeus, 150 Androutsou Srt., 18 532 Piraeus (Greece); Liatsis, P. [Division of Electrical Electronic and Information Engineering, School of Engineering and Mathematical Sciences, Information and Biomedical Engineering Centre, City University, Northampton Square, London EC1V 0HB (United Kingdom)

2008-09-15

This study addresses the problem of modeling the electricity demand loads in Greece. The provided actual load data is deseasonilized and an AutoRegressive Moving Average (ARMA) model is fitted on the data off-line, using the Akaike Corrected Information Criterion (AICC). The developed model fits the data in a successful manner. Difficulties occur when the provided data includes noise or errors and also when an on-line/adaptive modeling is required. In both cases and under the assumption that the provided data can be represented by an ARMA model, simultaneous order and parameter estimation of ARMA models under the presence of noise are performed. The produced results indicate that the proposed method, which is based on the multi-model partitioning theory, tackles successfully the studied problem. For validation purposes the produced results are compared with three other established order selection criteria, namely AICC, Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The developed model could be useful in the studies that concern electricity consumption and electricity prices forecasts. (author)

Logistic regression applied to natural hazards: rare event logistic regression with replications

Directory of Open Access Journals (Sweden)

M. Guns

2012-06-01

Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Logistic regression model for identification of right ventricular dysfunction in patients with acute pulmonary embolism by means of computed tomography

International Nuclear Information System (INIS)

Staskiewicz, Grzegorz; Czekajska-Chehab, Elżbieta; Uhlig, Sebastian; Przegalinski, Jerzy; Maciejewski, Ryszard; Drop, Andrzej

2013-01-01

Purpose: Diagnosis of right ventricular dysfunction in patients with acute pulmonary embolism (PE) is known to be associated with increased risk of mortality. The aim of the study was to calculate a logistic regression model for reliable identification of right ventricular dysfunction (RVD) in patients diagnosed with computed tomography pulmonary angiography. Material and methods: Ninety-seven consecutive patients with acute pulmonary embolism were divided into groups with and without RVD basing upon echocardiographic measurement of pulmonary artery systolic pressure (PASP). PE severity was graded with the pulmonary obstruction score. CT measurements of heart chambers and mediastinal vessels were performed; position of interventricular septum and presence of contrast reflux into the inferior vena cava were also recorded. The logistic regression model was prepared by means of stepwise logistic regression. Results: Among the used parameters, the final model consisted of pulmonary obstruction score, short axis diameter of right ventricle and diameter of inferior vena cava. The calculated model is characterized by 79% sensitivity and 81% specificity, and its performance was significantly better than single CT-based measurements. Conclusion: Logistic regression model identifies RVD significantly better, than single CT-based measurements

Lambing behaviour of Merino ewes from lines subjected to divergent ...

African Journals Online (AJOL)

No line difference was observed in the period that ewes spent grooming. Ewes caring for viable multiples groomed their offspring for a longer period than those caring for singles. Mature ewes tended to groom their lambs for a longer period than primi-parous maidens. A higher proportion of High (H) line ewes groomed their ...

Proliferation of epithelial cell rests, formation of apical cysts, and regression of apical cysts after periapical wound healing.

Science.gov (United States)

Lin, Louis M; Huang, George T-J; Rosenberg, Paul A

2007-08-01

There is continuing controversy regarding the potential for inflammatory apical cysts to heal after nonsurgical endodontic therapy. Molecular cell biology may provide answers to a series of related questions. How are the epithelial cell rests of Malassez stimulated to proliferate? How are the apical cysts formed? How does the lining epithelium of apical cysts regress after endodontic therapy? Epithelial cell rests are induced to divide and proliferate by inflammatory mediators, proinflammatory cytokines, and growth factors released from host cells during periradicular inflammation. Quiescent epithelial cell rests can behave like restricted-potential stem cells if stimulated to proliferate. Formation of apical cysts is most likely caused by the merging of proliferating epithelial strands from all directions to form a three-dimensional ball mass. After endodontic therapy, epithelial cells in epithelial strands of periapical granulomas and the lining epithelium of apical cysts may stop proliferating because of a reduction in inflammatory mediators, proinflammatory cytokines, and growth factors. Epithelial cells will also regress because of activation of apoptosis or programmed cell death through deprivation of survival factors or by receiving death signals during periapical wound healing.

Diffusion coefficient and Kolmogorov entropy of magnetic field lines

International Nuclear Information System (INIS)

Zimbardo, G.; Veltri, P.; Malara, F.

1984-01-01

A diffusion equation for magnetic field lines of force in a turbulent magnetic field, which describes both the random walk of a single line and how two nearby lines separate from each other, has been obtained using standard statistical techniques. Starting from such an equation, a closed set of equations for the moments may be obtained, in general, with suitable assumptions. From such a set of equations the Kolmogorov entropy may be explicitly calculated. The results have been applied to the most interesting examples of magnetic field geometries. (author)

Analytical, Practical and Emotional Intelligence and Line Manager Competencies

Directory of Open Access Journals (Sweden)

Anna Baczyńska

2015-12-01

Full Text Available Purpose: The research objective was to examine to what extent line manager competencies are linked to intelligence, and more specifically, three types of intelligence: analytical (fluid, practical and emotional. Methodology: The research was carried out with line managers (N=98 who took part in 12 Assessment Centre sessions and completed tests measuring analytical, practical and emotional intelligence. The adopted hypotheses were tested using a multiple regression. In the regression model, the dependent variable was a managerial competency (management and striving for results, social skills, openness to change, problem solving, employee development and the explanatory variables were the three types of intelligence. Five models, each for a separate management competency, were tested in this way. Findings: In the study, it was hypothesized that practical intelligence relates to procedural tacit knowledge and is the strongest indicator of managerial competency. Analysis of the study results testing this hypothesis indicated that practical intelligence largely accounts for the level of competency used in managerial work (from 21% to 38%. The study findings suggest that practical intelligence is a better indicator of managerial competencies among line managers than traditionally measured IQ or emotional intelligence. Originality: This research fills an important gap in the literature on the subject, indicating the links between major contemporary selection indicators (i.e., analytical, practical and emotional intelligence and managerial competencies presented in realistic work simulations measured using the Assessment Centre process.

Post-processing through linear regression

Science.gov (United States)

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.

Single-pass BPM system of the Photon Factory storage ring.

Science.gov (United States)

Honda, T; Katoh, M; Mitsuhashi, T; Ueda, A; Tadano, M; Kobayashi, Y

1998-05-01

At the 2.5 GeV ring of the Photon Factory, a single-pass beam-position monitor (BPM) system is being prepared for the storage ring and the beam transport line. In the storage ring, the injected beam position during the first several turns can be measured with a single injection pulse. The BPM system has an adequate performance, useful for the commissioning of the new low-emittance lattice. Several stripline BPMs are being installed in the beam transport line. The continuous monitoring of the orbit in the beam transport line will be useful for the stabilization of the injection energy as well as the injection beam orbit.

Splitting Terraced Houses Into Single Units Using Oblique Aerial Imagery

Science.gov (United States)

Dahlke, D.

2017-05-01

This paper introduces a method to subdivide complex building structures like terraced houses into single house units comparable to units available in a cadastral map. 3D line segments are detected with sub-pixel accuracy in traditional vertical true orthomosaics as well as in innovative oblique true orthomosaics and their respective surface models. Hereby high gradient strengths on roofs as well as façades are taken into account. By investigating the coplanarity and frequencies within a set of 3D line segments, individual cut lines for a building complex are found. The resulting regions ideally describe single houses and thus the object complexity is reduced for subsequent topological, semantical or geometrical considerations. For the chosen study area with 70 buidling outlines a hit rate of 80% for cut lines is achieved.

Regression modeling methods, theory, and computation with SAS

CERN Document Server

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,

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.

Support vector regression model for the estimation of γ-ray buildup factors for multi-layer shields

International Nuclear Information System (INIS)

Trontl, Kresimir; Smuc, Tomislav; Pevec, Dubravko

2007-01-01

The accuracy of the point-kernel method, which is a widely used practical tool for γ-ray shielding calculations, strongly depends on the quality and accuracy of buildup factors used in the calculations. Although, buildup factors for single-layer shields comprised of a single material are well known, calculation of buildup factors for stratified shields, each layer comprised of different material or a combination of materials, represent a complex physical problem. Recently, a new compact mathematical model for multi-layer shield buildup factor representation has been suggested for embedding into point-kernel codes thus replacing traditionally generated complex mathematical expressions. The new regression model is based on support vector machines learning technique, which is an extension of Statistical Learning Theory. The paper gives complete description of the novel methodology with results pertaining to realistic engineering multi-layer shielding geometries. The results based on support vector regression machine learning confirm that this approach provides a framework for general, accurate and computationally acceptable multi-layer buildup factor model

The current role of on-line extraction approaches in clinical and forensic toxicology.

Science.gov (United States)

Mueller, Daniel M

2014-08-01

In today's clinical and forensic toxicological laboratories, automation is of interest because of its ability to optimize processes, to reduce manual workload and handling errors and to minimize exposition to potentially infectious samples. Extraction is usually the most time-consuming step; therefore, automation of this step is reasonable. Currently, from the field of clinical and forensic toxicology, methods using the following on-line extraction techniques have been published: on-line solid-phase extraction, turbulent flow chromatography, solid-phase microextraction, microextraction by packed sorbent, single-drop microextraction and on-line desorption of dried blood spots. Most of these published methods are either single-analyte or multicomponent procedures; methods intended for systematic toxicological analysis are relatively scarce. However, the use of on-line extraction will certainly increase in the near future.

Multiple gamma lines from semi-annihilation

International Nuclear Information System (INIS)

D'Eramo, Francesco; McCullough, Matthew; Thaler, Jesse

2013-01-01

Hints in the Fermi data for a 130 GeV gamma line from the galactic center have ignited interest in potential gamma line signatures of dark matter. Explanations of this line based on dark matter annihilation face a parametric tension since they often rely on large enhancements of loop-suppressed cross sections. In this paper, we pursue an alternative possibility that dark matter gamma lines could arise from ''semi-annihilation'' among multiple dark sector states. The semi-annihilation reaction ψ i ψ j → ψ k γ with a single final state photon is typically enhanced relative to ordinary annihilation ψ i ψ-bar i → γγ into photon pairs. Semi-annihilation allows for a wide range of dark matter masses compared to the fixed mass value required by annihilation, opening the possibility to explain potential dark matter signatures at higher energies. The most striking prediction of semi-annihilation is the presence of multiple gamma lines, with as many as order N 3 lines possible for N dark sector states, allowing for dark sector spectroscopy. A smoking gun signature arises in the simplest case of degenerate dark matter, where a strong semi-annihilation line at 130 GeV would be accompanied by a weaker annihilation line at 173 GeV. As a proof of principle, we construct two explicit models of dark matter semi-annihilation, one based on non-Abelian vector dark matter and the other based on retrofitting Rayleigh dark matter

A versatile optical microscope for time-dependent single-molecule and single-particle spectroscopy

Science.gov (United States)

Li, Hao; Yang, Haw

2018-03-01

This work reports the design and implementation of a multi-function optical microscope for time-dependent spectroscopy on single molecules and single nanoparticles. It integrates the now-routine single-object measurements into one standalone platform so that no reconfiguration is needed when switching between different types of sample or spectroscopy modes. The illumination modes include evanescent field through total internal reflection, dark-field illumination, and epi-excitation onto a diffraction-limited spot suitable for confocal detection. The detection modes include spectrally resolved line imaging, wide-field imaging with dual-color capability, and two-color single-element photon-counting detection. The switch between different spectroscopy and data acquisition modes is fully automated and executed through computer programming. The capability of this microscope is demonstrated through selected proof-of-principle experiments.

A versatile optical microscope for time-dependent single-molecule and single-particle spectroscopy.

Science.gov (United States)

Li, Hao; Yang, Haw

2018-03-28

This work reports the design and implementation of a multi-function optical microscope for time-dependent spectroscopy on single molecules and single nanoparticles. It integrates the now-routine single-object measurements into one standalone platform so that no reconfiguration is needed when switching between different types of sample or spectroscopy modes. The illumination modes include evanescent field through total internal reflection, dark-field illumination, and epi-excitation onto a diffraction-limited spot suitable for confocal detection. The detection modes include spectrally resolved line imaging, wide-field imaging with dual-color capability, and two-color single-element photon-counting detection. The switch between different spectroscopy and data acquisition modes is fully automated and executed through computer programming. The capability of this microscope is demonstrated through selected proof-of-principle experiments.

Genetic analysis of partial egg production records in Japanese quail using random regression models.

Science.gov (United States)

Abou Khadiga, G; Mahmoud, B Y F; Farahat, G S; Emam, A M; El-Full, E A

2017-08-01

The main objectives of this study were to detect the most appropriate random regression model (RRM) to fit the data of monthly egg production in 2 lines (selected and control) of Japanese quail and to test the consistency of different criteria of model choice. Data from 1,200 female Japanese quails for the first 5 months of egg production from 4 consecutive generations of an egg line selected for egg production in the first month (EP1) was analyzed. Eight RRMs with different orders of Legendre polynomials were compared to determine the proper model for analysis. All criteria of model choice suggested that the adequate model included the second-order Legendre polynomials for fixed effects, and the third-order for additive genetic effects and permanent environmental effects. Predictive ability of the best model was the highest among all models (ρ = 0.987). According to the best model fitted to the data, estimates of heritability were relatively low to moderate (0.10 to 0.17) showed a descending pattern from the first to the fifth month of production. A similar pattern was observed for permanent environmental effects with greater estimates in the first (0.36) and second (0.23) months of production than heritability estimates. Genetic correlations between separate production periods were higher (0.18 to 0.93) than their phenotypic counterparts (0.15 to 0.87). The superiority of the selected line over the control was observed through significant (P egg production in earlier ages (first and second months) than later ones. A methodology based on random regression animal models can be recommended for genetic evaluation of egg production in Japanese quail. © 2017 Poultry Science Association Inc.

Workshop on Radio Recombination Lines

CERN Document Server

1980-01-01

Since their first detection 15 years ago, radio recombination lines from several elements have been observed in a wide variety of objects including HII regions, planetary nebulae, molecular clouds, the diffuse interstellar medium, and recently, other galaxies. The observations span almost the entire range from 0.1 to 100 GHz, and employ both single­ djsh and aperture synthesis techniques. The theory of radio recombination lines has also advanced strongly, to the point where it is perhaps one of the best-understood in astro­ physics. In a parallel development, it has become possible over the last decade to study these same highly-excited atoms in the laboratory; this work provides further confirmation of the theoretical framework. However there has been continuing controversy over the astrophysical interpre­ tation of radio recombination line observations, especially regarding the role of stimulated emission. A workshop was held in Ottawa on 24-25 August, 1979, bringing together many of the active scientist...

Semiparametric regression during 2003–2007

KAUST Repository

Ruppert, David; Wand, M.P.; Carroll, Raymond J.

2009-01-01

Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

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...

Displacement of location in illusory line motion.

Science.gov (United States)

Hubbard, Timothy L; Ruppel, Susan E

2013-05-01

Six experiments examined displacement in memory for the location of the line in illusory line motion (ILM; appearance or disappearance of a stationary cue is followed by appearance of a stationary line that is presented all at once, but the stationary line is perceived to "unfold" or "be drawn" from the end closest to the cue to the end most distant from the cue). If ILM was induced by having a single cue appear, then memory for the location of the line was displaced toward the cue, and displacement was larger if the line was closer to the cue. If ILM was induced by having one of two previously visible cues vanish, then memory for the location of the line was displaced away from the cue that vanished. In general, the magnitude of displacement increased and then decreased as retention interval increased from 50 to 250 ms and from 250 to 450 ms, respectively. Displacement of the line (a) is consistent with a combination of a spatial averaging of the locations of the cue and the line with a relatively weaker dynamic in the direction of illusory motion, (b) might be implemented in a spreading activation network similar to networks previously suggested to implement displacement resulting from implied or apparent motion, and (c) provides constraints and challenges for theories of ILM.

Hybrid adaptive radiotherapy with on-line MRI in cervix cancer IMRT

International Nuclear Information System (INIS)

Oh, Seungjong; Stewart, James; Moseley, Joanne; Kelly, Valerie; Lim, Karen; Xie, Jason; Fyles, Anthony; Brock, Kristy K.; Lundin, Anna; Rehbinder, Henrik; Milosevic, Michael; Jaffray, David

2014-01-01

Purpose: Substantial organ motion and tumor shrinkage occur during radiotherapy for cervix cancer. IMRT planning studies have shown that the quality of radiation delivery is influenced by these anatomical changes, therefore the adaptation of treatment plans may be warranted. Image guidance with off-line replanning, i.e. hybrid-adaptation, is recognized as one of the most practical adaptation strategies. In this study, we investigated the effects of soft tissue image guidance using on-line MR while varying the frequency of off-line replanning on the adaptation of cervix IMRT. Materials and method: 33 cervical cancer patients underwent planning and weekly pelvic MRI scans during radiotherapy. 5 patients of 33 were identified in a previous retrospective adaptive planning study, in which the coverage of gross tumor volume/clinical target volume (GTV/CTV) was not acceptable given single off-line IMRT replan using a 3 mm PTV margin with bone matching. These 5 patients and a randomly selected 10 patients from the remaining 28 patients, a total of 15 patients of 33, were considered in this study. Two matching methods for image guidance (bone to bone and soft tissue to dose matrix) and three frequencies of off-line replanning (none, single, and weekly) were simulated and compared with respect to target coverage (cervix, GTV, lower uterus, parametrium, upper vagina, tumor related CTV and elective lymph node CTV) and OAR sparing (bladder, bowel, rectum, and sigmoid). Cost (total process time) and benefit (target coverage) were analyzed for comparison. Results: Hybrid adaptation (image guidance with off-line replanning) significantly enhanced target coverage for both 5 difficult and 10 standard cases. Concerning image guidance, bone matching was short of delivering enough doses for 5 difficult cases even with a weekly off-line replan. Soft tissue image guidance proved successful for all cases except one when single or more frequent replans were utilized in the difficult cases

Rapidly rotating single late-type giants: New FK Comae stars?

Science.gov (United States)

Fekel, Francis C.

1986-01-01

A group of rapidly rotating single late-type giants was found from surveys of chromospherically active stars. These stars have V sin I's ranging from 6 to 46 km/sec, modest ultraviolet emission line fluxes, and strong H alpha absorption lines. Although certainly chromospherically active, their characteristics are much less extreme than those of FK Com and one or two other similar systems. One possible explanation for the newly identified systems is that they have evolved from stars similar to FK Com. The chromospheric activity and rotation of single giant stars like FK Com would be expected to decrease with time as they do in single dwarfs. Alternatively, this newly identified group may have evolved from single rapidly rotating A, or early F stars.

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

Science.gov (United States)

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.

Interpretation of commonly used statistical regression models.

Science.gov (United States)

Kasza, Jessica; Wolfe, Rory

2014-01-01

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

Linear regression

CERN Document Server

Olive, David J

2017-01-01

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

Regression modeling of ground-water flow

Science.gov (United States)

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)

Estimating HIES Data through Ratio and Regression Methods for Different Sampling Designs

Directory of Open Access Journals (Sweden)

Faqir Muhammad

2007-01-01

Full Text Available In this study, comparison has been made for different sampling designs, using the HIES data of North West Frontier Province (NWFP for 2001-02 and 1998-99 collected from the Federal Bureau of Statistics, Statistical Division, Government of Pakistan, Islamabad. The performance of the estimators has also been considered using bootstrap and Jacknife. A two-stage stratified random sample design is adopted by HIES. In the first stage, enumeration blocks and villages are treated as the first stage Primary Sampling Units (PSU. The sample PSU’s are selected with probability proportional to size. Secondary Sampling Units (SSU i.e., households are selected by systematic sampling with a random start. They have used a single study variable. We have compared the HIES technique with some other designs, which are: Stratified Simple Random Sampling. Stratified Systematic Sampling. Stratified Ranked Set Sampling. Stratified Two Phase Sampling. Ratio and Regression methods were applied with two study variables, which are: Income (y and Household sizes (x. Jacknife and Bootstrap are used for variance replication. Simple Random Sampling with sample size (462 to 561 gave moderate variances both by Jacknife and Bootstrap. By applying Systematic Sampling, we received moderate variance with sample size (467. In Jacknife with Systematic Sampling, we obtained variance of regression estimator greater than that of ratio estimator for a sample size (467 to 631. At a sample size (952 variance of ratio estimator gets greater than that of regression estimator. The most efficient design comes out to be Ranked set sampling compared with other designs. The Ranked set sampling with jackknife and bootstrap, gives minimum variance even with the smallest sample size (467. Two Phase sampling gave poor performance. Multi-stage sampling applied by HIES gave large variances especially if used with a single study variable.

Research on cutoff wavelength of dominant mode and field patterns in trapezoidal microshield lines

OpenAIRE

SUN, Hai; WU, Yujiang

2012-01-01

The influence of the position of the metallic signal strip on the cutoff characteristic of the dominant mode and the field patterns in 3 types of trapezoidal microshield lines are calculated by the edge-based finite element method. These trapezoidal microshield lines include trapezoidal microshield lines with a single signal line, dual signal lines, and 3 signal lines. The cutoff wavelength of the dominant mode can be adjusted by changing the dimensions of metallic signal strips as w...

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.

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

Science.gov (United States)

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

2013-10-30

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

Peculiar A star HD 43819 - A photographic region line-identification study

International Nuclear Information System (INIS)

Adelman, S.J.; The Citadel, Charleston, SC)

1985-01-01

A line identification study of the sharp-lined silicon star HD 43819 has been performed for the photographic region 3759-4924 A. Comparison of this star's spectrum with those of other silicon stars shows that it shares many of their apparent abundance anomalies. The TiII, CrII, FeI, and FeII spectra are well represented while the singly ionized rare earths are represented by at best a few lines per species. 21 references

Logistic regression applied to natural hazards: rare event logistic regression with replications

OpenAIRE

Guns, M.; Vanacker, Veerle

2012-01-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logisti...

Design, Modeling and Control of a Biped Line-Walking Robot

Directory of Open Access Journals (Sweden)

Ludan Wang

2010-12-01

Full Text Available The subject of this paper is the design and analysis of a biped line walking robot for inspection of power transmission lines. With a novel mechanism the centroid of the robot can be concentrated on the axis of hip joint to minimize the drive torque of the hip joint. The mechanical structure of the robot is discussed, as well as forward kinematics. Dynamic model is established in this paper to analyze the inverse kinematics for motion planning. The line-walking cycle of the line-walking robot is composed of a single-support phase and a double-support phase. Locomotion of the line-walking robot is discussed in details and the obstacle-navigation process is planed according to the structure of power transmission line. To fulfill the demands of line-walking, a control system and trajectories generation method are designed for the prototype of the line-walking robot. The feasibility of this concept is then confirmed by performing experiments with a simulated line environment.

On-Line Self-Calibrating Single Crystal Sapphire Optical Sensor Instrumentation for Accurate and Reliable Coal Gasifier Temperature Measurement

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.

Flux Cloning in Josephson Transmission Lines

International Nuclear Information System (INIS)

Gulevich, D.R.; Kusmartsev, F.V.

2006-01-01

We describe a novel effect related to the controlled birth of a single Josephson vortex. In this phenomenon, the vortex is created in a Josephson transmission line at a T-shaped junction. The 'baby' vortex arises at the moment when a 'mother' vortex propagating in the adjacent transmission line passes the T-shaped junction. In order to give birth to a new vortex, the mother vortex must have enough kinetic energy. Its motion can also be supported by an externally applied driving current. We determine the critical velocity and the critical driving current for the creation of the baby vortices and briefly discuss the potential applications of the found effect

Application of Multi-Layered Polyurethane Foams for Flat-Walled Anechoic Linings

DEFF Research Database (Denmark)

Xu, J. F.; Buchholz, Jörg; Fricke, Fergus R.

2006-01-01

of the application of multi-layered polyurethane foams as the flat-walled anechoic lining. The investigation includes aspects such as the efficacy of a single layer of material, the minimum number of layers of linings to achieve the minimum overall thickness for low (100Hz), mid (250Hz) and high (500Hz) cut...

Overview of The Pulse Line Ion Accelerator

International Nuclear Information System (INIS)

Briggs, R.J.; Bieniosek, F.M.; Coleman, J.E.; Eylon, S.; Henestroza, E.; Leitner, M.; Logan, B.G.; Reginato, L.L.; Roy, P.K.; Seidl, P.A.; Waldron, W.L.; Yu, S.S.; Barnard, J.J.; Caporaso, G.J.; Friedman, A.; Grote, D.P.; Nelson, S.D.

2006-01-01

An overview of the Pulse Line Ion Accelerator (PLIA) concept and its development is presented. In the PLIA concept a pulse power driver applied to one end of a helical pulse line creates a traveling wave pulse that accelerates and axially confines a heavy ion beam pulse The motivation for its development at the IFE-VNL is the acceleration of intense, short pulse, heavy ion beams to regimes of interest for studies of High Energy Density Physics and Warm Dense Matter. Acceleration scenarios with constant parameter helical lines are described which result in output energies of a single stage much larger than the several hundred kilovolt peak voltages on the line, with a goal of 3-5 MeV/meter acceleration gradients. The main attraction of the concept is the very low cost it promises. It might be described crudely as an ''air core'' induction linac where the pulse-forming network is integrated into the beam line so the accelerating voltage pulse can move along with the ions to get voltage multiplication

Recursive Algorithm For Linear Regression

Science.gov (United States)

Varanasi, S. V.

1988-01-01

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

A randomized, controlled, single-blind, 6-month pilot study to evaluate the efficacy of MS-Line!: a cognitive rehabilitation programme for patients with multiple sclerosis.

Science.gov (United States)

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.

In vitro response of the human breast cancer cell line MDAMB-231 and human peripheral blood mononuclear cells exposed to 60Co at single fraction

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)

Applied regression analysis a research tool

CERN Document Server

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...

Convergence diagnostics for Eigenvalue problems with linear regression model

International Nuclear Information System (INIS)

Shi, Bo; Petrovic, Bojan

2011-01-01

Although the Monte Carlo method has been extensively used for criticality/Eigenvalue problems, a reliable, robust, and efficient convergence diagnostics method is still desired. Most methods are based on integral parameters (multiplication factor, entropy) and either condense the local distribution information into a single value (e.g., entropy) or even disregard it. We propose to employ the detailed cycle-by-cycle local flux evolution obtained by using mesh tally mechanism to assess the source and flux convergence. By applying a linear regression model to each individual mesh in a mesh tally for convergence diagnostics, a global convergence criterion can be obtained. We exemplify this method on two problems and obtain promising diagnostics results. (author)

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

Science.gov (United States)

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

Modification of First-line Antiretroviral Therapy in Treatment-naive, HIV Positive Patients

Directory of Open Access Journals (Sweden)

Smita Shenoy

2017-10-01

Full Text Available Introduction: Modification of initial Antiretroviral Therapy (ART program is an important issue in HIV infected patients as the number of ART regimens available is limited. Hence, there is a need to understand the factors that affect modification and therefore, the durability of the initial antiretroviral regimen. Aim: To study the type of modification of first line ART in treatment-naive HIV positive patients and factors influencing it. Materials and Methods: A retrospective observational study was carried out in the HIV clinic of a tertiary care hospital, using data obtained from the case records of the subjects who were initiated on ART between January 2012 to December 2014. Data on patient baseline characteristics, proportion of patients who required modification, type and time of modification was collected. The determinants of time to modification were analysed using Chi-square test. Binomial logistic regression was utilized to assess independent risk factors for change in regimen. Results: Out of 200 case records analysed, 54 patients had to undergo a modification in their initial regimen. The mean age of patients was 44.68 ± 11.31 years. Majority of the patients were males. The most common reason for modification was Adverse Drug Reactions (ADRs (79.63% followed by treatment failure (9.25%. In 85.18% cases, modification involved substitution. Occurrence of ADRs and non-tenofovir based first-line regimens were associated with higher likelihood of substitution in regimen (p<0.05. The median time (IQR to modification was 173 (152.25, 293.50 days. Conclusion: ADRs and the use of non-tenofovir based regimens resulted in significantly higher rates of modification of antiretroviral therapy. There should be monitoring of patients on ART to detect ADRs at the earliest and to obtain increased use of single tablet containing tenofovir based regimen to improve durability of first line regimens.

Correlation between cell survival and DNA single-strand break repair proficiency in the Chinese hamster ovary cell lines AA8 and EM9 irradiated with 365-nm ultraviolet-A radiation

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).

A NLTE line formation for neutral and singly-ionised calcium in model atmospheres of B-F stars

Science.gov (United States)

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

Science.gov (United States)

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.

Logistic regression for dichotomized counts.

Science.gov (United States)

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

2016-12-01

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

Children's cognitive representation of the mathematical number line.

Science.gov (United States)

Rouder, Jeffrey N; Geary, David C

2014-07-01

Learning of the mathematical number line has been hypothesized to be dependent on an inherent sense of approximate quantity. Children's number line placements are predicted to conform to the underlying properties of this system; specifically, placements are exaggerated for small numerals and compressed for larger ones. Alternative hypotheses are based on proportional reasoning; specifically, numerals are placed relative to set anchors such as end points on the line. Traditional testing of these alternatives involves fitting group medians to corresponding regression models which assumes homogenous residuals and thus does not capture useful information from between- and within-child variation in placements across the number line. To more fully assess differential predictions, we developed a novel set of hierarchical statistical models that enable the simultaneous estimation of mean levels of and variation in performance, as well as developmental transitions. Using these techniques we fitted the number line placements of 224 children longitudinally assessed from first to fifth grade, inclusive. The compression pattern was evident in mean performance in first grade, but was the best fit for only 20% of first graders when the full range of variation in the data are modeled. Most first graders' placements suggested use of end points, consistent with proportional reasoning. Developmental transition involved incorporation of a mid-point anchor, consistent with a modified proportional reasoning strategy. The methodology introduced here enables a more nuanced assessment of children's number line representation and learning than any previous approaches and indicates that developmental improvement largely results from midpoint segmentation of the line. © 2014 John Wiley & Sons Ltd.

SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients.

Science.gov (United States)

Weaver, Bruce; Wuensch, Karl L

2013-09-01

Several procedures that use summary data to test hypotheses about Pearson correlations and ordinary least squares regression coefficients have been described in various books and articles. To our knowledge, however, no single resource describes all of the most common tests. Furthermore, many of these tests have not yet been implemented in popular statistical software packages such as SPSS and SAS. In this article, we describe all of the most common tests and provide SPSS and SAS programs to perform them. When they are applicable, our code also computes 100 × (1 - α)% confidence intervals corresponding to the tests. For testing hypotheses about independent regression coefficients, we demonstrate one method that uses summary data and another that uses raw data (i.e., Potthoff analysis). When the raw data are available, the latter method is preferred, because use of summary data entails some loss of precision due to rounding.

Optimal multi-dimensional poverty lines: The state of poverty in Iraq

Science.gov (United States)

Ameen, Jamal R. M.

2017-09-01

Poverty estimation based on calories intake is unrealistic. The established concept of multidimensional poverty has methodological weaknesses in the treatment of different dimensions and there is disagreement in methods of combining them into a single poverty line. This paper introduces a methodology to estimate optimal multidimensional poverty lines and uses the Iraqi household socio-economic survey data of 2012 to demonstrate the idea. The optimal poverty line for Iraq is found to be 170.5 Thousand Iraqi Dinars (TID).

Regression of an atlantoaxial rheumatoid pannus following posterior instrumented fusion.

Science.gov (United States)

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.

Mechanisms of neuroblastoma regression

Science.gov (United States)

Brodeur, Garrett M.; Bagatell, Rochelle

2014-01-01

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

Least square regularized regression in sum space.

Science.gov (United States)

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.

Using the Ridge Regression Procedures to Estimate the Multiple Linear Regression Coefficients

Science.gov (United States)

Gorgees, HazimMansoor; Mahdi, FatimahAssim

2018-05-01

This article concerns with comparing the performance of different types of ordinary ridge regression estimators that have been already proposed to estimate the regression parameters when the near exact linear relationships among the explanatory variables is presented. For this situations we employ the data obtained from tagi gas filling company during the period (2008-2010). The main result we reached is that the method based on the condition number performs better than other methods since it has smaller mean square error (MSE) than the other stated methods.

Multicollinearity and Regression Analysis

Science.gov (United States)

Daoud, Jamal I.

2017-12-01

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

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...

Hierarchical Neural Regression Models for Customer Churn Prediction

Directory of Open Access Journals (Sweden)

Golshan Mohammadi

2013-01-01

Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

Credit Scoring Problem Based on Regression Analysis

OpenAIRE

Khassawneh, Bashar Suhil Jad Allah

2014-01-01

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

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...

Autistic Regression

Science.gov (United States)

Matson, Johnny L.; Kozlowski, Alison M.

2010-01-01

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

Sirenomelia and severe caudal regression syndrome.

Science.gov (United States)

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.

Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation

Directory of Open Access Journals (Sweden)

Sharad Damodar Gore

2009-10-01

Full Text Available Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR. This estimator is obtained from unbiased ridge regression (URR in the same way that ordinary ridge regression (ORR is obtained from ordinary least squares (OLS. Properties of MUR are derived. Results on its matrix mean squared error (MMSE are obtained. MUR is compared with ORR and URR in terms of MMSE. These results are illustrated with an example based on data generated by Hoerl and Kennard (1975.

Discriminative Elastic-Net Regularized Linear Regression.

Science.gov (United States)

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.

Categorical regression dose-response modeling

Science.gov (United States)

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...

Abstract Expression Grammar Symbolic Regression

Science.gov (United States)

Korns, Michael F.

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

Soft Sensor Modeling Based on Multiple Gaussian Process Regression and Fuzzy C-mean Clustering

Directory of Open Access Journals (Sweden)

Xianglin ZHU

2014-06-01

Full Text Available In order to overcome the difficulties of online measurement of some crucial biochemical variables in fermentation processes, a new soft sensor modeling method is presented based on the Gaussian process regression and fuzzy C-mean clustering. With the consideration that the typical fermentation process can be distributed into 4 phases including lag phase, exponential growth phase, stable phase and dead phase, the training samples are classified into 4 subcategories by using fuzzy C- mean clustering algorithm. For each sub-category, the samples are trained using the Gaussian process regression and the corresponding soft-sensing sub-model is established respectively. For a new sample, the membership between this sample and sub-models are computed based on the Euclidean distance, and then the prediction output of soft sensor is obtained using the weighting sum. Taking the Lysine fermentation as example, the simulation and experiment are carried out and the corresponding results show that the presented method achieves better fitting and generalization ability than radial basis function neutral network and single Gaussian process regression model.

Work life and mental wellbeing of single and non-single working mothers in Scandinavia.

Science.gov (United States)

Bull, Torill; Mittelmark, Maurice B

2009-08-01

This study examined levels and predictors of mental wellbeing in Scandinavian working single and non-single mothers, with a special focus on financial stress, job characteristics and work-family conflict. The European Social Survey Round 2 (2005) provided questionnaire data from 73 single and 432 non-single working mothers in Denmark, Sweden and Norway. Respondents answered questions about the outcome variables life satisfaction, happiness, and positive affect, and predictor variables financial stress, job characteristics, work-family conflict, and social support. Hierarchical multiple regression was used to assess the relationships between predictor variables and mental wellbeing outcomes. Single working mothers scored significantly lower on life satisfaction and happiness, but not on positive affect, than did non-single mothers. Financial stress was higher in the single mother group. There were no significant differences in levels of enriching or stressful job characteristics, or in levels of social support. While financial stress and work-family conflict were important predictors in both groups, the relationship between financial stress and wellbeing was far stronger in the single mother group. Confidant support was a significant predictor only in the single mother group, and social participation only in the non-single mothers group. This study suggests that the Scandinavian welfare democracies have not yet been successful in relieving the financial pressure experienced by single working mothers. Development of efficient financial support systems should be prioritized. Ways to reduce work-family conflict in both single and non-single mothers in Scandinavia should also be given increased attention.

A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

Science.gov (United States)

Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

2017-06-01

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

Microbeam mapping of single event latchups and single event upsets in CMOS SRAMs

International Nuclear Information System (INIS)

Barak, J.; Adler, E.; Fischer, B.E.; Schloegl, M.; Metzger, S.

1998-01-01

The first simultaneous microbeam mapping of single event upset (SEU) and latchup (SEL) in the CMOS RAM HM65162 is presented. The authors found that the shapes of the sensitive areas depend on V DD , on the ions being used and on the site on the chip being hit by the ion. In particular, they found SEL sensitive sites close to the main power supply lines between the memory-bit-arrays by detecting the accompanying current surge. All these SELs were also accompanied by bit-flips elsewhere in the memory (which they call indirect SEUs in contrast to the well known SEUs induced in the hit memory cell only). When identical SEL sensitive sites were hit farther away from the supply lines only indirect SEL sensitive sites could be detected. They interpret these events as latent latchups in contrast to the classical ones detected by their induced current surge. These latent SELs were probably decoupled from the main supply lines by the high resistivity of the local supply lines

Power flow studies of magnetically insulated lines

International Nuclear Information System (INIS)

McDaniel, D.H.; Poukey, J.W.; Bergeron, K.D.; VanDevender, J.P.; Johnson, D.L.

1977-01-01

The designs for relativistic electron beam accelerators with power levels of 20 to 100 TW are greatly restricted by the inductance of a single diode of reasonable size. This fact leads to modular designs of very large accelerators. One concept uses several small insulators at a large radius arranged around the accelerator center. The total effective inductance is then low, but the energy must then be transported by self-magnetic insulated vacuum lines to the target volume. A triplate vacuum line configuration eases many mechanical support problems and allows more A-K gaps or feeds to be packaged around a given radius. This type of vacuum transmission line was chosen for initial experiments at Sandia. The experiments were conducted on the MITE (Magnetically Insulated Transmission Experiment) accelerator. The water pulse forming lines are connected to a vacuum triplate line through a conventional stacked insulator. Diagnostics on the experiment consisted of: (1) input V; (2) input I; (3) I monitors at the input, middle, and output of both the center conductor and ground plane of the transmission line; (4) magnetic energy analyzer to view peak electron energy in the A-K gap; (5) calorimetry; and (6) Faraday cups to look at electron current flowing across the transmission line. The main goal of the experiment is to obtain input impedance of the transmission line as a function of voltage and to measure electron loss currents. These measurements are compared to theoretical models for the input impedance and energy losses

Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

OpenAIRE

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...

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.

Delay estimation on a railway-line with smart use of micro-simulation

DEFF Research Database (Denmark)

Cerreto, Fabrizio; Harrod, Steven; Nielsen, Otto Anker

2017-01-01

This paper formulates a delay propagation model that estimates total railway line delay as a polynomial function of a single primary delay. The estimate is derived from a finite series of delays over a horizon that spans two dimensions: the length of the railway line and the number of trains in t...

Logistic Regression: Concept and Application

Science.gov (United States)

Cokluk, Omay

2010-01-01

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

Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

Science.gov (United States)

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.

EEG/MEG Source Reconstruction with Spatial-Temporal Two-Way Regularized Regression

KAUST Repository

Tian, Tian Siva

2013-07-11

In this work, we propose a spatial-temporal two-way regularized regression method for reconstructing neural source signals from EEG/MEG time course measurements. The proposed method estimates the dipole locations and amplitudes simultaneously through minimizing a single penalized least squares criterion. The novelty of our methodology is the simultaneous consideration of three desirable properties of the reconstructed source signals, that is, spatial focality, spatial smoothness, and temporal smoothness. The desirable properties are achieved by using three separate penalty functions in the penalized regression framework. Specifically, we impose a roughness penalty in the temporal domain for temporal smoothness, and a sparsity-inducing penalty and a graph Laplacian penalty in the spatial domain for spatial focality and smoothness. We develop a computational efficient multilevel block coordinate descent algorithm to implement the method. Using a simulation study with several settings of different spatial complexity and two real MEG examples, we show that the proposed method outperforms existing methods that use only a subset of the three penalty functions. © 2013 Springer Science+Business Media New York.

Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha

2014-12-08

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha; Huang, Jianhua Z.

2014-01-01

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

Effects of the single and combined treatment with dopamine agonist, somatostatin analog and mTOR inhibitors in a human lung carcinoid cell line: an in vitro study.

Science.gov (United States)

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

Failure analysis of high strength pipeline with single and multiple corrosions

International Nuclear Information System (INIS)

Chen, Yanfei; Zhang, Hong; Zhang, Juan; Li, Xin; Zhou, Jing

2015-01-01

Highlights: • We study failure of high strength pipelines with single corrosion. • We give regression equations for failure pressure prediction. • We propose assessment procedure for pipelines with multiple corrosions. - Abstract: Corrosion will compromise safety operation of oil and gas pipelines, accurate determination of failure pressure finds importance in residual strength assessment and corrosion allowance design of onshore and offshore pipelines. This paper investigates failure pressure of high strength pipeline with single and multiple corrosions using nonlinear finite element analysis. On the basis of developed regression equations for failure pressure prediction of high strength pipeline with single corrosion, the paper proposes an assessment procedure for predicting failure pressure of high strength pipeline with multiple corrosions. Furthermore, failure pressures predicted by proposed solutions are compared with experimental results and various assessment methods available in literature, where accuracy and versatility are demonstrated

Metal Free Graphene Oxide (GO) Nanosheets and Pristine-Single Wall Carbon Nanotubes (p-SWCNTs) Biocompatibility Investigation: A Comparative Study in Different Human Cell Lines.

Science.gov (United States)

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.

Changes in corticospinal excitability during consolidation predict acute exercise-induced off-line gains in procedural memory

DEFF Research Database (Denmark)

Ostadan, Fatemeh; Centeno, Carla; Daloze, Jean-Felix

2016-01-01

A single bout of cardiovascular exercise performed immediately after practicing a motor task improves the long-term retention of the skill through an optimization of memory consolidation. However, the specific brain mechanisms underlying the effects of acute cardiovascular exercise on procedural...... exercise correlated with the magnitude of off-line gains in skill level assessed in a retention test performed 8h after motor practice. A single bout of exercise modulates short-term neuroplasticity mechanisms subserving consolidation processes that predict off-line gains in procedural memory....... memory are poorly understood. We sought to determine if a single bout of exercise modifies corticospinal excitability (CSE) during the early stages of memory consolidation. In addition, we investigated if changes in CSE are associated with exercise-induced off-line gains in procedural memory...

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)

Influences on call outcomes among Veteran callers to the National Veterans Crisis Line

Science.gov (United States)

Britton, Peter C.; Bossarte, Robert M.; Thompson, Caitlin; Kemp, Janet; Conner, Kenneth R.

2016-01-01

This evaluation examined the association of caller and call characteristics with proximal outcomes of Veterans Crisis Line calls. From October 1-7, 2010, 665 Veterans with recent suicidal ideation or a history of attempted suicide called the Veterans Crisis Line, 646 had complete data and were included in the analyses. A multivariable multinomial logistic regression was conducted to identify correlates of a favorable outcome, either a resolution or a referral, when compared to an unfavorable outcome, no resolution or referral. A multivariable logistic regression was used to identify correlates of responder-rated caller risk in a subset of calls. Approximately 84% of calls ended with a favorable outcome, 25% with a resolution and 59% with a referral to a local health care provider. Calls from high-risk callers had greater odds of ending with a referral than without a resolution or referral, as did weekday calls (6:00 am to 5:59 pm EST, Monday through Friday). Responders used caller intent to die and the absence of future plans to determine caller risk. Findings suggest that the Veterans Crisis Line is a useful mechanism for generating referrals for high-risk Veteran callers. Responders appeared to use known risk and protective factors to determine caller risk. PMID:23611446

Confidence intervals for distinguishing ordinal and disordinal interactions in multiple regression.

Science.gov (United States)

Lee, Sunbok; Lei, Man-Kit; Brody, Gene H

2015-06-01

Distinguishing between ordinal and disordinal interaction in multiple regression is useful in testing many interesting theoretical hypotheses. Because the distinction is made based on the location of a crossover point of 2 simple regression lines, confidence intervals of the crossover point can be used to distinguish ordinal and disordinal interactions. This study examined 2 factors that need to be considered in constructing confidence intervals of the crossover point: (a) the assumption about the sampling distribution of the crossover point, and (b) the possibility of abnormally wide confidence intervals for the crossover point. A Monte Carlo simulation study was conducted to compare 6 different methods for constructing confidence intervals of the crossover point in terms of the coverage rate, the proportion of true values that fall to the left or right of the confidence intervals, and the average width of the confidence intervals. The methods include the reparameterization, delta, Fieller, basic bootstrap, percentile bootstrap, and bias-corrected accelerated bootstrap methods. The results of our Monte Carlo simulation study suggest that statistical inference using confidence intervals to distinguish ordinal and disordinal interaction requires sample sizes more than 500 to be able to provide sufficiently narrow confidence intervals to identify the location of the crossover point. (c) 2015 APA, all rights reserved).

The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

Science.gov (United States)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.

Use of TCSR with Split Windings for Shortening the Spar Cycle Time in 500 kV Lines

Energy Technology Data Exchange (ETDEWEB)

Matinyan, A. M., E-mail: al-drm@mail.ru; Peshkov, M. V.; Karpov, V. N.; Alekseev, N. A. [JSC “R& D Center at Federal Grid Company of Unified Power System,” (Russian Federation)

2017-01-15

The arc-fault recharge phenomenon in single-phase automatic reclosure (SPAR) of a line is examined. Abrief description is given of the design of a 500 kV thyristor controlled shunt reactor (TCSR) with split valve-side windings. This type of TCSR is shown to effectively quench a single-phase arc fault in a power transmission line and shortens the SPAR cycle time.

Stochastic theory of relaxation and collisional broadening of spectral line shapes

International Nuclear Information System (INIS)

Faid, K.

1986-01-01

A complete stochastic theory of relaxation is developed in terms of a homogeneous equation for the averaged density matrix of a system immersed in a thermal bath. This theory is then used as the basis of a new stochastic approach to the phenomenon of collisional broadening of spectral line shapes. Single-photon and multiphoton processes are studied. The features of a line shape are linked by simple expressions to the statistical properties of a stochastic hermitian Hamiltonian. The ordinary line shape predicted by Kubo's approach is generalized. The present approach predicts broadening as well as asymmetry and shift. A representation of line shapes in multiphoton processes by diagrams is also developed

Frequency-multiplexed bias and readout of a 16-pixel superconducting nanowire single-photon detector array

Science.gov (United States)

Doerner, S.; Kuzmin, A.; Wuensch, S.; Charaev, I.; Boes, F.; Zwick, T.; Siegel, M.

2017-07-01

We demonstrate a 16-pixel array of microwave-current driven superconducting nanowire single-photon detectors with an integrated and scalable frequency-division multiplexing architecture, which reduces the required number of bias and readout lines to a single microwave feed line. The electrical behavior of the photon-sensitive nanowires, embedded in a resonant circuit, as well as the optical performance and timing jitter of the single detectors is discussed. Besides the single pixel measurements, we also demonstrate the operation of a 16-pixel array with a temporal, spatial, and photon-number resolution.

Single molecules and single nanoparticles as windows to the nanoscale

Science.gov (United States)

Caldarola, Martín; Orrit, Michel

2018-05-01

Since the first optical detection of single molecules, they have been used as nanometersized optical sensors to explore the physical properties of materials and light-matter interaction at the nanoscale. Understanding nanoscale properties of materials is fundamental for the development of new technology that requires precise control of atoms and molecules when the quantum nature of matter cannot be ignored. In the following lines, we illustrate this journey into nanoscience with some experiments from our group.

The Fourth Workshop on Lineshape Code Comparison: Line Merging

Directory of Open Access Journals (Sweden)

Spiros Alexiou

2018-03-01

Full Text Available For a given set of plasma parameters, along a single series (Lyman, Balmer, etc. the lines with higher principal quantum number (n lines get progressively wider, closer to each other, and start merging for a certain critical n. In the present work, four different codes (with further options are used to calculate the entire Balmer series for moderate and high electron densities. Particular attention is paid to the relevant physics, such as the cutoff criteria, strong and penetrating electron collisions.

Regression and Sparse Regression Methods for Viscosity Estimation of Acid Milk From it’s Sls Features

DEFF Research Database (Denmark)

Sharifzadeh, Sara; Skytte, Jacob Lercke; Nielsen, Otto Højager Attermann

2012-01-01

Statistical solutions find wide spread use in food and medicine quality control. We investigate the effect of different regression and sparse regression methods for a viscosity estimation problem using the spectro-temporal features from new Sub-Surface Laser Scattering (SLS) vision system. From...... with sparse LAR, lasso and Elastic Net (EN) sparse regression methods. Due to the inconsistent measurement condition, Locally Weighted Scatter plot Smoothing (Loess) has been employed to alleviate the undesired variation in the estimated viscosity. The experimental results of applying different methods show...

Testing discontinuities in nonparametric regression

KAUST Repository

Dai, Wenlin

2017-01-19

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

Testing discontinuities in nonparametric regression

KAUST Repository

Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

2017-01-01

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

Vibrational analysis of single-layered graphene sheets

Energy Technology Data Exchange (ETDEWEB)

Sakhaee-Pour, A; Ahmadian, M T [Center of Excellence in Design, Robotics and Automation (CEDRA), Department of Mechanical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Naghdabadi, R [Department of Mechanical Engineering and Institute for Nano Science and Technology, Sharif University of Technology, Tehran (Iran, Islamic Republic of)], E-mail: sakhaee@alum.sharif.edu, E-mail: naghdabd@sharif.edu

2008-02-27

A molecular structural mechanics method has been implemented to investigate the vibrational behavior of single-layered graphene sheets. By adopting this approach, mode shapes and natural frequencies are obtained. Vibrational analysis is performed with different chirality and boundary conditions. Numerical results from the atomistic modeling are employed to develop predictive equations via a statistical nonlinear regression model. With the proposed equations, fundamental frequencies of single-layered graphene sheets with considered boundary conditions can be predicted within 3% difference with respect to the atomistic simulation.

Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression data [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Linh Nguyen

2016-12-01

Full Text Available Background: Selected gene mutations are routinely used to guide the selection of cancer drugs for a given patient tumour. Large pharmacogenomic data sets were introduced to discover more of these single-gene markers of drug sensitivity. Very recently, machine learning regression has been used to investigate how well cancer cell line sensitivity to drugs is predicted depending on the type of molecular profile. The latter has revealed that gene expression data is the most predictive profile in the pan-cancer setting. However, no study to date has exploited GDSC data to systematically compare the performance of machine learning models based on multi-gene expression data against that of widely-used single-gene markers based on genomics data. Methods: Here we present this systematic comparison using Random Forest (RF classifiers exploiting the expression levels of 13,321 genes and an average of 501 tested cell lines per drug. To account for time-dependent batch effects in IC50 measurements, we employ independent test sets generated with more recent GDSC data than that used to train the predictors and show that this is a more realistic validation than K-fold cross-validation. Results and Discussion: Across 127 GDSC drugs, our results show that the single-gene markers unveiled by the MANOVA analysis tend to achieve higher precision than these RF-based multi-gene models, at the cost of generally having a poor recall (i.e. correctly detecting only a small part of the cell lines sensitive to the drug. Regarding overall classification performance, about two thirds of the drugs are better predicted by multi-gene RF classifiers. Among the drugs with the most predictive of these models, we found pyrimethamine, sunitinib and 17-AAG. Conclusions: We now know that this type of models can predict in vitro tumour response to these drugs. These models can thus be further investigated on in vivo tumour models.

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.

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

Science.gov (United States)

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

2008-02-18

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

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

Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

Directory of Open Access Journals (Sweden)

Peter S. Kristensen

2018-02-01

Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

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.

Photoluminescence studies of single InGaAs quantum dots

DEFF Research Database (Denmark)

Leosson, Kristjan; Jensen, Jacob Riis; Hvam, Jørn Märcher

1999-01-01

Semiconductor quantum dots are considered a promising material system for future optical devices and quantum computers. We have studied the low-temperature photoluminescence properties of single InGaAs quantum dots embedded in GaAs. The high spatial resolution required for resolving single dots...... to resolve luminescence lines from individual quantum dots, revealing an atomic-like spectrum of sharp transition lines. A parameter of fundamental importance is the intrinsic linewidth of these transitions. Using high-resolution spectroscopy we have determined the linewidth and investigated its dependence...... on temperature, which gives information about how the exciton confined to the quantum dot interacts with the surrounding lattice....

Stark shift measurements of Xe II and Xe III spectral lines

International Nuclear Information System (INIS)

Cirisan, M; Pelaez, R J; Djurovic, S; Aparicio, J A; Mar, S

2007-01-01

Stark shift measurements of singly and doubly ionized Xe spectral lines are presented in this paper. Shifts of 110 Xe II lines and 42 Xe III lines are reported, including a significant number of new results. A low-pressure-pulsed arc with 95% of He and 5% of Xe was used as a plasma source. All measurements were performed under the following plasma conditions: electron density (0.2-1.4) x 10 23 m -3 and electron temperature 18 000-23 000 K. The measured Stark shifts are compared with other experimental and theoretical data

Multiclass Prediction with Partial Least Square Regression for Gene Expression Data: Applications in Breast Cancer Intrinsic Taxonomy

Directory of Open Access Journals (Sweden)

Chi-Cheng Huang

2013-01-01

Full Text Available Multiclass prediction remains an obstacle for high-throughput data analysis such as microarray gene expression profiles. Despite recent advancements in machine learning and bioinformatics, most classification tools were limited to the applications of binary responses. Our aim was to apply partial least square (PLS regression for breast cancer intrinsic taxonomy, of which five distinct molecular subtypes were identified. The PAM50 signature genes were used as predictive variables in PLS analysis, and the latent gene component scores were used in binary logistic regression for each molecular subtype. The 139 prototypical arrays for PAM50 development were used as training dataset, and three independent microarray studies with Han Chinese origin were used for independent validation (n=535. The agreement between PAM50 centroid-based single sample prediction (SSP and PLS-regression was excellent (weighted Kappa: 0.988 within the training samples, but deteriorated substantially in independent samples, which could attribute to much more unclassified samples by PLS-regression. If these unclassified samples were removed, the agreement between PAM50 SSP and PLS-regression improved enormously (weighted Kappa: 0.829 as opposed to 0.541 when unclassified samples were analyzed. Our study ascertained the feasibility of PLS-regression in multi-class prediction, and distinct clinical presentations and prognostic discrepancies were observed across breast cancer molecular subtypes.

Molecular Genetic Changes Associated With Colorectal Carcinogenesis Are Not Prognostic for Tumor Regression Following Preoperative Chemoradiation of Rectal Carcinoma

International Nuclear Information System (INIS)

Zauber, N. Peter; Marotta, Steven P.; Berman, Errol; Grann, Alison; Rao, Maithili; Komati, Naga; Ribiero, Kezia; Bishop, D. Timothy

2009-01-01

Purpose: Preoperative chemotherapy and radiation has become the standard of care for many patients with rectal cancer. The therapy may have toxicity and delays definitive surgery. It would therefore be desirable to identify those cancers that will not regress with preoperative therapy. We assessed a series of rectal cancers for the molecular changes of loss of heterozygosity of the APC and DCC genes, K-ras mutations, and microsatellite instability, changes that have clearly been associated with rectal carcinogenesis. Methods and Materials: Diagnostic colonoscopic biopsies from 53 patients who received preoperative chemotherapy and radiation were assayed using polymerase chain reaction techniques followed by single-stranded conformation polymorphism and DNA sequencing. Regression of the primary tumor was evaluated using the surgically removed specimen. Results: Twenty-three lesions (45%) were found to have a high degree of regression. None of the molecular changes were useful as indicators of regression. Conclusions: Recognized molecular changes critical for rectal carcinogenesis including APC and DCC loss of heterozygosity, K-ras mutations, and microsatellite instability are not useful as indicators of tumor regression following chemoradiation for rectal carcinoma.

A comparison of alternative methods for estimating the self-thinning boundary line

Science.gov (United States)

Lianjun Zhang; Huiquan Bi; Jeffrey H. Gove; Linda S. Heath

2005-01-01

The fundamental validity of the self-thinning "law" has been debated over the last three decades. A long-sanding concern centers on how to objectively select data points for fitting the self-thinning line and the most appropriate regression method for estimating the two coefficients. Using data from an even-aged Pinus strobus L. stand as an...

Regression Analysis by Example. 5th Edition

Science.gov (United States)

Chatterjee, Samprit; Hadi, Ali S.

2012-01-01

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

Gaussian process regression analysis for functional data

CERN Document Server

Shi, Jian Qing

2011-01-01

Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime

Is past life regression therapy ethical?

Science.gov (United States)

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.

Efficacy of S-1 plus nedaplatin compared to standard second-line chemotherapy in EGFR-negative lung adenocarcinoma after failure of first-line chemotherapy.

Science.gov (United States)

Tang, Yu; Wang, Wei; Teng, Xiu-Zhi; Shi, Lin

2014-09-01

For patients with advanced non-small cell lung adenocarcinoma that fail to respond to first-line chemotherapy and that do not involve epidermal growth factor receptor (EGFR) mutations, previous empirical analysis showed that a single second-line chemotherapy agent may be inadequate for the control of further tumor development. This study examines the combination of S-1 drugs and nedaplatin that has no cross-resistance to first-line treatments; 179 cases of IIIb-IV stage non-small-cell lung adenocarcinoma that failed to respond to first-line chemotherapy were included, and these subjects did not have mutated EGFRs. In the present study, S-1 plus nedaplatin chemotherapy was better than standard second-line chemotherapy options in the treatment of advanced lung adenocarcinoma that did not involve EGFR mutations and that failed to respond to first-line chemotherapy. Additionally, the combination of S-1 and nedaplatin seemed to be well tolerated, making this chemotherapy technique a potentially strong candidate for the treatment of advanced non-small-cell lung adenocarcinoma.

Impact on Medical Cost, Cumulative Survival, and Cost-Effectiveness of Adding Rituximab to First-Line Chemotherapy for Follicular Lymphoma in Elderly Patients: An Observational Cohort Study Based on SEER-Medicare

International Nuclear Information System (INIS)

Griffiths, R. I.; Gleeson, M. L.; Danese, M. D.; Griffiths, R. I.; Mikhael, J.

2012-01-01

Rituximab improves survival in follicular lymphoma (FL), but is considerably more expensive than conventional chemotherapy. We estimated the total direct medical costs, cumulative survival, and cost-effectiveness of adding rituximab to first-line chemotherapy for FL, based on a single source of data representing routine practice in the elderly. Using surveillance, epidemiology, and end results (SEER) registry data plus Medicare claims, we identified 1,117 FL patients who received first-line CHOP (cyclophosphamide (C), doxorubicin, vincristine (V), and prednisone (P)) or CVP +/− rituximab. Multivariate regression was used to estimate adjusted cumulative cost and survival differences between the two groups over four years after beginning treatment. The median age was 73 years (minimum 66 years), 56% had stage III-IV disease, and 67% received rituximab. Adding rituximab to first-line chemotherapy was associated with higher adjusted incremental total cost ($18,695; 95% Confidence Interval (CI) $9,302-$28,643) and longer adjusted cumulative survival (0.18 years; 95% CI 0.10-0.27) over four years of followup. The expected cost-effectiveness was $102,142 (95% CI $34,531-296,337) per life-year gained. In routine clinical practice, adding rituximab to first-line chemotherapy for elderly patients with FL results in higher direct medical costs to Medicare and longer cumulative survival after four years.

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....

Distance protection of multiple-circuit shared tower transmission lines with different voltages

DEFF Research Database (Denmark)

Silva, Filipe Miguel Faria da; Bak, Claus Leth

2017-01-01

combined faults, being advised to increase the resistive limit of the protection zone, if the network has lower short-circuit power. It is recommended to assure that the fault can only happen for cases where the faulted phase from the higher voltage level leads the faulted phase from the lower voltage......Multiple-circuit transmission lines combining different voltage levels in one tower present extra challenges when setting a protection philosophy, as faults between voltage levels are possible. In this study, the fault loop impedance of combined faults is compared with the fault loop impedance......-phase-to-ground faults. It is also demonstrated that the fault loop impedance of combined faults is more resistive, when compared with equivalent single-phase-to-ground faults. It is concluded that the settings used to protect a line against single-phase-to-ground faults are capable of protecting the line against...