Sample records for standard deviation limits

  1. 40 CFR 63.7751 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... deviations from any emissions limitations (including operating limit), work practice standards, or operation and maintenance requirements, a statement that there were no deviations from the emissions limitations...-of-control during the reporting period. (7) For each deviation from an emissions limitation...

  2. 40 CFR 63.7951 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... the information in § 63.10(d)(5)(i). (5) If there were no deviations from any emissions limitations... that there were no deviations from the emissions limitations, work practice standards, or operation and...) For each deviation from an emissions limitation (including an operating limit) that occurs at an...

  3. 40 CFR 63.1455 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... from any emission limitations (emission limit, operating limit, opacity limit) that applies to you and... that there were no deviations from the emission limitations, work practice standards, or operation and... deviation from an emission limitation (emission limit, operating limit, opacity limit) and for each...

  4. Closed-form confidence intervals for functions of the normal mean and standard deviation.

    PubMed

    Donner, Allan; Zou, G Y

    2012-08-01

    Confidence interval methods for a normal mean and standard deviation are well known and simple to apply. However, the same cannot be said for important functions of these parameters. These functions include the normal distribution percentiles, the Bland-Altman limits of agreement, the coefficient of variation and Cohen's effect size. We present a simple approach to this problem by using variance estimates recovered from confidence limits computed for the mean and standard deviation separately. All resulting confidence intervals have closed forms. Simulation results demonstrate that this approach performs very well for limits of agreement, coefficients of variation and their differences.

  5. Determining a one-tailed upper limit for future sample relative reproducibility standard deviations.

    PubMed

    McClure, Foster D; Lee, Jung K

    2006-01-01

    A formula was developed to determine a one-tailed 100p% upper limit for future sample percent relative reproducibility standard deviations (RSD(R),%= 100s(R)/y), where S(R) is the sample reproducibility standard deviation, which is the square root of a linear combination of the sample repeatability variance (s(r)2) plus the sample laboratory-to-laboratory variance (s(L)2), i.e., S(R) = s(L)2, and y is the sample mean. The future RSD(R),% is expected to arise from a population of potential RSD(R),% values whose true mean is zeta(R),% = 100sigmaR, where sigmaR and mu are the population reproducibility standard deviation and mean, respectively.

  6. 40 CFR 90.708 - Cumulative Sum (CumSum) procedure.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... is 5.0×σ, and is a function of the standard deviation, σ. σ=is the sample standard deviation and is... individual engine. FEL=Family Emission Limit (the standard if no FEL). F=.25×σ. (2) After each test pursuant...

  7. Packing Fraction of a Two-dimensional Eden Model with Random-Sized Particles

    NASA Astrophysics Data System (ADS)

    Kobayashi, Naoki; Yamazaki, Hiroshi

    2018-01-01

    We have performed a numerical simulation of a two-dimensional Eden model with random-size particles. In the present model, the particle radii are generated from a Gaussian distribution with mean μ and standard deviation σ. First, we have examined the bulk packing fraction for the Eden cluster and investigated the effects of the standard deviation and the total number of particles NT. We show that the bulk packing fraction depends on the number of particles and the standard deviation. In particular, for the dependence on the standard deviation, we have determined the asymptotic value of the bulk packing fraction in the limit of the dimensionless standard deviation. This value is larger than the packing fraction obtained in a previous study of the Eden model with uniform-size particles. Secondly, we have investigated the packing fraction of the entire Eden cluster including the effect of the interface fluctuation. We find that the entire packing fraction depends on the number of particles while it is independent of the standard deviation, in contrast to the bulk packing fraction. In a similar way to the bulk packing fraction, we have obtained the asymptotic value of the entire packing fraction in the limit NT → ∞. The obtained value of the entire packing fraction is smaller than that of the bulk value. This fact suggests that the interface fluctuation of the Eden cluster influences the packing fraction.

  8. 40 CFR 63.9814 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... any emission limitations (emission limit, operating limit, or work practice standard) that apply to... limitations during the reporting period. (6) If there were no periods during which any affected CPMS was out... deviation from an emission limitation (emission limit, operating limit, or work practice standard) that...

  9. 40 CFR 63.9641 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... provide a statement that there were no deviations from the emission limitations, work practice standards... system was out-of-control during the reporting period. (7) For each deviation from an emission limitation... monitoring system (including a CPMS or COMS) to comply with an emission limitation in this subpart, the...

  10. U.S. Navy Marine Climatic Atlas of the World. Volume IX. World-Wide Means and Standard Deviations

    DTIC Science & Technology

    1981-10-01

    TITLE (..d SobtII,) S. TYPE OF REPORT & PERIOD COVERED U. S. Navy Marine Climatic Atlas of the World Volume IX World-wide Means and Standard Reference...Ives the best estimate of the population standard deviations. The means, , are com~nuted from: EX IIN I 90 80 70 60" 50’ 40, 30 20 10 0 1070 T- VErr ...or 10%, whichever is greater Since the mean ice limit approximates the minus two de l temperature isopleth, this analyzed lower limit was Wave Heights

  11. Role of the standard deviation in the estimation of benchmark doses with continuous data.

    PubMed

    Gaylor, David W; Slikker, William

    2004-12-01

    For continuous data, risk is defined here as the proportion of animals with values above a large percentile, e.g., the 99th percentile or below the 1st percentile, for the distribution of values among control animals. It is known that reducing the standard deviation of measurements through improved experimental techniques will result in less stringent (higher) doses for the lower confidence limit on the benchmark dose that is estimated to produce a specified risk of animals with abnormal levels for a biological effect. Thus, a somewhat larger (less stringent) lower confidence limit is obtained that may be used as a point of departure for low-dose risk assessment. It is shown in this article that it is important for the benchmark dose to be based primarily on the standard deviation among animals, s(a), apart from the standard deviation of measurement errors, s(m), within animals. If the benchmark dose is incorrectly based on the overall standard deviation among average values for animals, which includes measurement error variation, the benchmark dose will be overestimated and the risk will be underestimated. The bias increases as s(m) increases relative to s(a). The bias is relatively small if s(m) is less than one-third of s(a), a condition achieved in most experimental designs.

  12. Analytical quality goals derived from the total deviation from patients' homeostatic set points, with a margin for analytical errors.

    PubMed

    Bolann, B J; Asberg, A

    2004-01-01

    The deviation of test results from patients' homeostatic set points in steady-state conditions may complicate interpretation of the results and the comparison of results with clinical decision limits. In this study the total deviation from the homeostatic set point is defined as the maximum absolute deviation for 95% of measurements, and we present analytical quality requirements that prevent analytical error from increasing this deviation to more than about 12% above the value caused by biology alone. These quality requirements are: 1) The stable systematic error should be approximately 0, and 2) a systematic error that will be detected by the control program with 90% probability, should not be larger than half the value of the combined analytical and intra-individual standard deviation. As a result, when the most common control rules are used, the analytical standard deviation may be up to 0.15 times the intra-individual standard deviation. Analytical improvements beyond these requirements have little impact on the interpretability of measurement results.

  13. Evaluation of a Wipe Surface Sample Method for Collection of Bacillus Spores from Nonporous Surfaces▿

    PubMed Central

    Brown, Gary S.; Betty, Rita G.; Brockmann, John E.; Lucero, Daniel A.; Souza, Caroline A.; Walsh, Kathryn S.; Boucher, Raymond M.; Tezak, Mathew; Wilson, Mollye C.; Rudolph, Todd

    2007-01-01

    Polyester-rayon blend wipes were evaluated for efficiency of extraction and recovery of powdered Bacillus atrophaeus spores from stainless steel and painted wallboard surfaces. Method limits of detection were also estimated for both surfaces. The observed mean efficiency of polyester-rayon blend wipe recovery from stainless steel was 0.35 with a standard deviation of ±0.12, and for painted wallboard it was 0.29 with a standard deviation of ±0.15. Evaluation of a sonication extraction method for the polyester-rayon blend wipes produced a mean extraction efficiency of 0.93 with a standard deviation of ±0.09. Wipe recovery quantitative limits of detection were estimated at 90 CFU per unit of stainless steel sample area and 105 CFU per unit of painted wallboard sample area. The method recovery efficiency and limits of detection established in this work provide useful guidance for the planning of incident response environmental sampling following the release of a biological agent such as Bacillus anthracis. PMID:17122390

  14. Evaluation of a wipe surface sample method for collection of Bacillus spores from nonporous surfaces.

    PubMed

    Brown, Gary S; Betty, Rita G; Brockmann, John E; Lucero, Daniel A; Souza, Caroline A; Walsh, Kathryn S; Boucher, Raymond M; Tezak, Mathew; Wilson, Mollye C; Rudolph, Todd

    2007-02-01

    Polyester-rayon blend wipes were evaluated for efficiency of extraction and recovery of powdered Bacillus atrophaeus spores from stainless steel and painted wallboard surfaces. Method limits of detection were also estimated for both surfaces. The observed mean efficiency of polyester-rayon blend wipe recovery from stainless steel was 0.35 with a standard deviation of +/-0.12, and for painted wallboard it was 0.29 with a standard deviation of +/-0.15. Evaluation of a sonication extraction method for the polyester-rayon blend wipes produced a mean extraction efficiency of 0.93 with a standard deviation of +/-0.09. Wipe recovery quantitative limits of detection were estimated at 90 CFU per unit of stainless steel sample area and 105 CFU per unit of painted wallboard sample area. The method recovery efficiency and limits of detection established in this work provide useful guidance for the planning of incident response environmental sampling following the release of a biological agent such as Bacillus anthracis.

  15. Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory; determination of chromium in water by graphite furnace atomic absorption spectrophotometry

    USGS Publications Warehouse

    McLain, B.J.

    1993-01-01

    Graphite furnace atomic absorption spectrophotometry is a sensitive, precise, and accurate method for the determination of chromium in natural water samples. The detection limit for this analytical method is 0.4 microg/L with a working linear limit of 25.0 microg/L. The precision at the detection limit ranges from 20 to 57 percent relative standard deviation (RSD) with an improvement to 4.6 percent RSD for concentrations more than 3 microg/L. Accuracy of this method was determined for a variety of reference standards that was representative of the analytical range. The results were within the established standard deviations. Samples were spiked with known concentrations of chromium with recoveries ranging from 84 to 122 percent. In addition, a comparison of data between graphite furnace atomic absorption spectrophotometry and direct-current plasma atomic emission spectrometry resulted in suitable agreement between the two methods, with an average deviation of +/- 2.0 microg/L throughout the analytical range.

  16. Preliminary analysis of hot spot factors in an advanced reactor for space electric power systems

    NASA Technical Reports Server (NTRS)

    Lustig, P. H.; Holms, A. G.; Davison, H. W.

    1973-01-01

    The maximum fuel pin temperature for nominal operation in an advanced power reactor is 1370 K. Because of possible nitrogen embrittlement of the clad, the fuel temperature was limited to 1622 K. Assuming simultaneous occurrence of the most adverse conditions a deterministic analysis gave a maximum fuel temperature of 1610 K. A statistical analysis, using a synthesized estimate of the standard deviation for the highest fuel pin temperature, showed probabilities of 0.015 of that pin exceeding the temperature limit by the distribution free Chebyshev inequality and virtually nil assuming a normal distribution. The latter assumption gives a 1463 K maximum temperature at 3 standard deviations, the usually assumed cutoff. Further, the distribution and standard deviation of the fuel-clad gap are the most significant contributions to the uncertainty in the fuel temperature.

  17. Acoustic Correlates of Compensatory Adjustments to the Glottic and Supraglottic Structures in Patients with Unilateral Vocal Fold Paralysis

    PubMed Central

    2015-01-01

    The goal of this study was to analyse perceptually and acoustically the voices of patients with Unilateral Vocal Fold Paralysis (UVFP) and compare them to the voices of normal subjects. These voices were analysed perceptually with the GRBAS scale and acoustically using the following parameters: mean fundamental frequency (F0), standard-deviation of F0, jitter (ppq5), shimmer (apq11), mean harmonics-to-noise ratio (HNR), mean first (F1) and second (F2) formants frequency, and standard-deviation of F1 and F2 frequencies. Statistically significant differences were found in all of the perceptual parameters. Also the jitter, shimmer, HNR, standard-deviation of F0, and standard-deviation of the frequency of F2 were statistically different between groups, for both genders. In the male data differences were also found in F1 and F2 frequencies values and in the standard-deviation of the frequency of F1. This study allowed the documentation of the alterations resulting from UVFP and addressed the exploration of parameters with limited information for this pathology. PMID:26557690

  18. Test-retest reliability of 3D ultrasound measurements of the thoracic spine.

    PubMed

    Fölsch, Christian; Schlögel, Stefanie; Lakemeier, Stefan; Wolf, Udo; Timmesfeld, Nina; Skwara, Adrian

    2012-05-01

    To explore the reliability of the Zebris CMS 20 ultrasound analysis system with pointer application for measuring end-range flexion, end-range extension, and neutral kyphosis angle of the thoracic spine. The study was performed within the School of Physiotherapy in cooperation with the Orthopedic Department at a University Hospital. The thoracic spines of 28 healthy subjects were measured. Measurements for neutral kyphosis angle, end-range flexion, and end-range extension were taken once at each time point. The bone landmarks were palpated by one examiner and marked with a pointer containing 2 transmitters using a frequency of 40 kHz. A third transmitter was fixed to the pelvis, and 3 microphones were used as receiver. The real angle was calculated by the software. Bland-Altman plots with 95% limits of agreement, intraclass correlations (ICC), standard deviations of mean measurements, and standard error of measurements were used for statistical analyses. The test-retest reliability in this study was measured within a 24-hour interval. Statistical parameters were used to judge reliability. The mean kyphosis angle was 44.8° with a standard deviation of 17.3° at the first measurement and a mean of 45.8° with a standard deviation of 16.2° the following day. The ICC was high at 0.95 for the neutral kyphosis angle, and the Bland-Altman 95% limits of agreement were within clinical acceptable margins. The ICC was 0.71 for end-range flexion and 0.34 for end-range extension, whereas the Bland-Altman 95% limits of agreement were wider than with the static measurement of kyphosis. Compared with static measurements, the analysis of motion with 3-dimensional ultrasound showed an increased standard deviation for test-retest measurements. The test-retest reliability of ultrasound measuring of the neutral kyphosis angle of the thoracic spine was demonstrated within 24 hours. Bland-Altman 95% limits of agreement and the standard deviation of differences did not appear to be clinically acceptable for measuring flexion and extension. Copyright © 2012 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

  19. 40 CFR 91.508 - Cumulative Sum (CumSum) procedure.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... family may be determined to be in noncompliance for purposes of § 91.510. H = The Action Limit. It is 5.0 × σ, and is a function of the standard deviation, σ. σ = is the sample standard deviation and is... Equation must be final deteriorated test results as defined in § 91.509(c). Ci = max[0 0R (Ci-1 + Xi − (FEL...

  20. Retinal nerve fiber layer thickness measured with optical coherence tomography is related to visual function in glaucomatous eyes.

    PubMed

    El Beltagi, Tarek A; Bowd, Christopher; Boden, Catherine; Amini, Payam; Sample, Pamela A; Zangwill, Linda M; Weinreb, Robert N

    2003-11-01

    To determine the relationship between areas of glaucomatous retinal nerve fiber layer thinning identified by optical coherence tomography and areas of decreased visual field sensitivity identified by standard automated perimetry in glaucomatous eyes. Retrospective observational case series. Forty-three patients with glaucomatous optic neuropathy identified by optic disc stereo photographs and standard automated perimetry mean deviations >-8 dB were included. Participants were imaged with optical coherence tomography within 6 months of reliable standard automated perimetry testing. The location and number of optical coherence tomography clock hour retinal nerve fiber layer thickness measures outside normal limits were compared with the location and number of standard automated perimetry visual field zones outside normal limits. Further, the relationship between the deviation from normal optical coherence tomography-measured retinal nerve fiber layer thickness at each clock hour and the average pattern deviation in each visual field zone was examined by using linear regression (R(2)). The retinal nerve fiber layer areas most frequently outside normal limits were the inferior and inferior temporal regions. The least sensitive visual field zones were in the superior hemifield. Linear regression results (R(2)) showed that deviation from the normal retinal nerve fiber layer thickness at optical coherence tomography clock hour positions 6 o'clock, 7 o'clock, and 8 o'clock (inferior and inferior temporal) was best correlated with standard automated perimetry pattern deviation in visual field zones corresponding to the superior arcuate and nasal step regions (R(2) range, 0.34-0.57). These associations were much stronger than those between clock hour position 6 o'clock and the visual field zone corresponding to the inferior nasal step region (R(2) = 0.01). Localized retinal nerve fiber layer thinning, measured by optical coherence tomography, is topographically related to decreased localized standard automated perimetry sensitivity in glaucoma patients.

  1. Signal averaging limitations in heterodyne- and direct-detection laser remote sensing measurements

    NASA Technical Reports Server (NTRS)

    Menyuk, N.; Killinger, D. K.; Menyuk, C. R.

    1983-01-01

    The improvement in measurement uncertainty brought about by the averaging of increasing numbers of pulse return signals in both heterodyne- and direct-detection lidar systems is investigated. A theoretical analysis is presented which shows the standard deviation of the mean measurement to decrease as the inverse square root of the number of measurements, except in the presence of temporal correlation. Experimental measurements based on a dual-hybrid-TEA CO2 laser differential absorption lidar system are reported which demonstrate that the actual reduction in the standard deviation of the mean in both heterodyne- and direct-detection systems is much slower than the inverse square-root dependence predicted for uncorrelated signals, but is in agreement with predictions in the event of temporal correlation. Results thus favor the use of direct detection at relatively short range where the lower limit of the standard deviation of the mean is about 2 percent, but advantages of heterodyne detection at longer ranges are noted.

  2. Detecting long-duration cloud contamination in hyper-temporal NDVI imagery

    NASA Astrophysics Data System (ADS)

    Ali, Amjad; de Bie, C. A. J. M.; Skidmore, A. K.

    2013-10-01

    Cloud contamination impacts on the quality of hyper-temporal NDVI imagery and its subsequent interpretation. Short-duration cloud impacts are easily removed by using quality flags and an upper envelope filter, but long-duration cloud contamination of NDVI imagery remains. In this paper, an approach that goes beyond the use of quality flags and upper envelope filtering is tested to detect when and where long-duration clouds are responsible for unreliable NDVI readings, so that a user can flag those data as missing. The study is based on MODIS Terra and the combined Terra-Aqua 16-day NDVI product for the south of Ghana, where persistent cloud cover occurs throughout the year. The combined product could be assumed to have less cloud contamination, since it is based on two images per day. Short-duration cloud effects were removed from the two products through using the adaptive Savitzky-Golay filter. Then for each 'cleaned' product an unsupervised classified map was prepared using the ISODATA algorithm, and, by class, plots were prepared to depict changes over time of the means and the standard deviations in NDVI values. By comparing plots of similar classes, long-duration cloud contamination appeared to display a decline in mean NDVI below the lower limit 95% confidence interval with a coinciding increase in standard deviation above the upper limit 95% confidence interval. Regression analysis was carried out per NDVI class in two randomly selected groups in order to statistically test standard deviation values related to long-duration cloud contamination. A decline in seasonal NDVI values (growing season) were below the lower limit of 95% confidence interval as well as a concurrent increase in standard deviation values above the upper limit of the 95% confidence interval were noted in 34 NDVI classes. The regression analysis results showed that differences in NDVI class values between the Terra and the Terra-Aqua imagery were significantly correlated (p < 0.05) with the corresponding standard deviation values of the Terra imagery in case of all NDVI classes of two selected NDVI groups. The method successfully detects long-duration cloud contamination that results in unreliable NDVI values. The approach offers scientists interested in time series analysis a method of masking by area (class) the periods when pre-cleaned NDVI values remain affected by clouds. The approach requires no additional data for execution purposes but involves unsupervised classification of the imagery to carry out the evaluation of class-specific mean NDVI and standard deviation values over time.

  3. Experiments with central-limit properties of spatial samples from locally covariant random fields

    USGS Publications Warehouse

    Barringer, T.H.; Smith, T.E.

    1992-01-01

    When spatial samples are statistically dependent, the classical estimator of sample-mean standard deviation is well known to be inconsistent. For locally dependent samples, however, consistent estimators of sample-mean standard deviation can be constructed. The present paper investigates the sampling properties of one such estimator, designated as the tau estimator of sample-mean standard deviation. In particular, the asymptotic normality properties of standardized sample means based on tau estimators are studied in terms of computer experiments with simulated sample-mean distributions. The effects of both sample size and dependency levels among samples are examined for various value of tau (denoting the size of the spatial kernel for the estimator). The results suggest that even for small degrees of spatial dependency, the tau estimator exhibits significantly stronger normality properties than does the classical estimator of standardized sample means. ?? 1992.

  4. 7 CFR 32.400 - Samples of grease mohair grades; method of obtaining.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... standard deviation of fiber diameter of bulk sample were within the limits corresponding to the grade of... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS PURCHASE OF GREASE MOHAIR AND MOHAIR TOP SAMPLES § 32.400 Samples of grease...

  5. 7 CFR 31.400 - Samples for wool and wool top grades; method of obtaining.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... average and standard deviation of fiber diameter of the bulk sample are within the limits corresponding to... MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS PURCHASE OF WOOL AND WOOL TOP SAMPLES § 31.400 Samples for wool...

  6. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.

    PubMed

    Wan, Xiang; Wang, Wenqian; Liu, Jiming; Tong, Tiejun

    2014-12-19

    In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.'s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations.

  7. Inverse correlation between the standard deviation of R-R intervals in supine position and the simplified menopausal index in women with climacteric symptoms.

    PubMed

    Yanagihara, Nobuyuki; Seki, Meikan; Nakano, Masahiro; Hachisuga, Toru; Goto, Yukio

    2014-06-01

    Disturbance of autonomic nervous activity has been thought to play a role in the climacteric symptoms of postmenopausal women. This study was therefore designed to investigate the relationship between autonomic nervous activity and climacteric symptoms in postmenopausal Japanese women. The autonomic nervous activity of 40 Japanese women with climacteric symptoms and 40 Japanese women without climacteric symptoms was measured by power spectral analysis of heart rate variability using a standard hexagonal radar chart. The scores for climacteric symptoms were determined using the simplified menopausal index. Sympathetic excitability and irritability, as well as the standard deviation of mean R-R intervals in supine position, were significantly (P < 0.01, 0.05, and 0.001, respectively) decreased in women with climacteric symptoms. There was a negative correlation between the standard deviation of mean R-R intervals in supine position and the simplified menopausal index score. The lack of control for potential confounding variables was a limitation of this study. In climacteric women, the standard deviation of mean R-R intervals in supine position is negatively correlated with the simplified menopausal index score.

  8. Evaluation of the QuEChERS Method and Gas Chromatography–Mass Spectrometry for the Analysis Pesticide Residues in Water and Sediment

    PubMed Central

    de Macedo, A. N.; Vicente, G. H. L.; Nogueira, A. R. A.

    2010-01-01

    A method for the determination of pesticide residues in water and sediment was developed using the QuEChERS method followed by gas chromatography – mass spectrometry. The method was validated in terms of accuracy, specificity, linearity, detection and quantification limits. The recovery percentages obtained for the pesticides in water at different concentrations ranged from 63 to 116%, with relative standard deviations below 12%. The corresponding results from the sediment ranged from 48 to 115% with relative standard deviations below 16%. The limits of detection for the pesticides in water and sediment were below 0.003 mg L−1 and 0.02 mg kg−1, respectively. PMID:21165598

  9. Range and Energy Straggling in Ion Beam Transport

    NASA Technical Reports Server (NTRS)

    Wilson, John W.; Tai, Hsiang

    2000-01-01

    A first-order approximation to the range and energy straggling of ion beams is given as a normal distribution for which the standard deviation is estimated from the fluctuations in energy loss events. The standard deviation is calculated by assuming scattering from free electrons with a long range cutoff parameter that depends on the mean excitation energy of the medium. The present formalism is derived by extrapolating Payne's formalism to low energy by systematic energy scaling and to greater depths of penetration by a second-order perturbation. Limited comparisons are made with experimental data.

  10. 40 CFR 63.9931 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... emission limitations, work practice standards, or operation and maintenance requirements during the... reporting period. (7) For each deviation from an emission limitation in § 63.9890 that occurs at an affected source where you are not using a CPMS to comply with an emission limitation in this subpart, the...

  11. Discriminating crop and other canopies by overlapping binary image layers

    NASA Astrophysics Data System (ADS)

    Doi, Ryoichi

    2013-02-01

    For optimal management of agricultural fields by remote sensing, discrimination of the crop canopy from weeds and other objects is essential. In a digital photograph, a rice canopy was discriminated from a variety of weed and tree canopies and other objects by overlapping binary image layers of red-green-blue and other color components indicating the pixels with target canopy-specific (intensity) values based on the ranges of means ±(3×) standard deviations. By overlapping and merging the binary image layers, the target canopy specificity improved to 0.0015 from 0.027 for the yellow 1× standard deviation binary image layer, which was the best among all combinations of color components and means ±(3×) standard deviations. The most target rice canopy-likely pixels were further identified by limiting the pixels at different luminosity values. The discriminatory power was also visually demonstrated in this manner.

  12. What to use to express the variability of data: Standard deviation or standard error of mean?

    PubMed

    Barde, Mohini P; Barde, Prajakt J

    2012-07-01

    Statistics plays a vital role in biomedical research. It helps present data precisely and draws the meaningful conclusions. While presenting data, one should be aware of using adequate statistical measures. In biomedical journals, Standard Error of Mean (SEM) and Standard Deviation (SD) are used interchangeably to express the variability; though they measure different parameters. SEM quantifies uncertainty in estimate of the mean whereas SD indicates dispersion of the data from mean. As readers are generally interested in knowing the variability within sample, descriptive data should be precisely summarized with SD. Use of SEM should be limited to compute CI which measures the precision of population estimate. Journals can avoid such errors by requiring authors to adhere to their guidelines.

  13. Fish: A New Computer Program for Friendly Introductory Statistics Help

    ERIC Educational Resources Information Center

    Brooks, Gordon P.; Raffle, Holly

    2005-01-01

    All introductory statistics students must master certain basic descriptive statistics, including means, standard deviations and correlations. Students must also gain insight into such complex concepts as the central limit theorem and standard error. This article introduces and describes the Friendly Introductory Statistics Help (FISH) computer…

  14. 40 CFR 60.2775 - What else must I report if I have a deviation from the operating limits or the emission limitations?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR... Waste Incineration Units Model Rule-Recordkeeping and Reporting § 60.2775 What else must I report if I...

  15. 40 CFR 60.2775 - What else must I report if I have a deviation from the operating limits or the emission limitations?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR... Waste Incineration Units Model Rule-Recordkeeping and Reporting § 60.2775 What else must I report if I...

  16. Observation of electroweak single top-quark production.

    PubMed

    Aaltonen, T; Adelman, J; Akimoto, T; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burke, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cordelli, M; Cortiana, G; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; Di Canto, P; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Garosi, P; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heijboer, A; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Hussein, M; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, E; Lee, H S; Lee, S W; Leone, S; Lewis, J D; Lin, C-S; Linacre, J; Lindgren, M; Lipeles, E; Liss, T M; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lucchesi, D; Luci, C; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; MacQueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Potamianos, K; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Rutherford, B; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Würthwein, F; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zhang, X; Zheng, Y; Zucchelli, S

    2009-08-28

    We report the observation of single top-quark production using 3.2 fb(-1) of pp[over ] collision data with sqrt[s]=1.96 TeV collected by the Collider Detector at Fermilab. The significance of the observed data is 5.0 standard deviations, and the expected sensitivity for standard model production and decay is in excess of 5.9 standard deviations. Assuming m(t) = 175 GeV/c(2), we measure a cross section of 2.3(-0.5);(+0.6)(stat + syst) pb, extract the CKM matrix-element value |V(tb)| = 0.91 + or - 0.11(stat + syst) + or - 0.07(theory), and set the limit |V(tb)| > 0.71 at the 95% C.L.

  17. Gambling as a teaching aid in the introductory physics laboratory

    NASA Astrophysics Data System (ADS)

    Horodynski-Matsushigue, L. B.; Pascholati, P. R.; Vanin, V. R.; Dias, J. F.; Yoneama, M.-L.; Siqueira, P. T. D.; Amaku, M.; Duarte, J. L. M.

    1998-07-01

    Dice throwing is used to illustrate relevant concepts of the statistical theory of uncertainties, in particular the meaning of a limiting distribution, the standard deviation, and the standard deviation of the mean. It is an important part in a sequence of especially programmed laboratory activities, developed for freshmen, at the Institute of Physics of the University of São Paulo. It is shown how this activity is employed within a constructive teaching approach, which aims at a growing understanding of the measuring processes and of the fundamentals of correct statistical handling of experimental data.

  18. Accuracy of acoustic velocity metering systems for measurement of low velocity in open channels

    USGS Publications Warehouse

    Laenen, Antonius; Curtis, R. E.

    1989-01-01

    Acoustic velocity meter (AVM) accuracy depends on equipment limitations, the accuracy of acoustic-path length and angle determination, and the stability of the mean velocity to acoustic-path velocity relation. Equipment limitations depend on path length and angle, transducer frequency, timing oscillator frequency, and signal-detection scheme. Typically, the velocity error from this source is about +or-1 to +or-10 mms/sec. Error in acoustic-path angle or length will result in a proportional measurement bias. Typically, an angle error of one degree will result in a velocity error of 2%, and a path-length error of one meter in 100 meter will result in an error of 1%. Ray bending (signal refraction) depends on path length and density gradients present in the stream. Any deviation from a straight acoustic path between transducer will change the unique relation between path velocity and mean velocity. These deviations will then introduce error in the mean velocity computation. Typically, for a 200-meter path length, the resultant error is less than one percent, but for a 1,000 meter path length, the error can be greater than 10%. Recent laboratory and field tests have substantiated assumptions of equipment limitations. Tow-tank tests of an AVM system with a 4.69-meter path length yielded an average standard deviation error of 9.3 mms/sec, and the field tests of an AVM system with a 20.5-meter path length yielded an average standard deviation error of a 4 mms/sec. (USGS)

  19. How does social capital matter to the health status of older adults? Evidence from the China Health and Retirement Longitudinal Survey.

    PubMed

    Liu, Gordon G; Xue, Xindong; Yu, Chenxi; Wang, Yafeng

    2016-09-01

    This paper uses longitudinal data from China to examine the causal relationship between structural social capital and health among Chinese older adults. We employ various econometric strategies to control for the potential endogeneity of social capital and account for the possible contextual confounding effects by including community-level social capital. We use three indicators to measure individuals' general, physical, and mental health. Results indicate that social capital has a significant and positive effect on general and physical health. Based on our primary IV findings, a one standard-deviation increase in social capital leads to a 4.9 standard-deviation decrease in the probability of having bad health and a 2.2 standard-deviation decrease in physical activity limitations. Our results are robust to a series of sensitivity checks. Further analysis suggests heterogeneous effects by age but not by gender or area of residence. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Quantifying the heterogeneity of the tectonic stress field using borehole data

    USGS Publications Warehouse

    Schoenball, Martin; Davatzes, Nicholas C.

    2017-01-01

    The heterogeneity of the tectonic stress field is a fundamental property which influences earthquake dynamics and subsurface engineering. Self-similar scaling of stress heterogeneities is frequently assumed to explain characteristics of earthquakes such as the magnitude-frequency relation. However, observational evidence for such scaling of the stress field heterogeneity is scarce.We analyze the local stress orientations using image logs of two closely spaced boreholes in the Coso Geothermal Field with sub-vertical and deviated trajectories, respectively, each spanning about 2 km in depth. Both the mean and the standard deviation of stress orientation indicators (borehole breakouts, drilling-induced fractures and petal-centerline fractures) determined from each borehole agree to the limit of the resolution of our method although measurements at specific depths may not. We find that the standard deviation in these boreholes strongly depends on the interval length analyzed, generally increasing up to a wellbore log length of about 600 m and constant for longer intervals. We find the same behavior in global data from the World Stress Map. This suggests that the standard deviation of stress indicators characterizes the heterogeneity of the tectonic stress field rather than the quality of the stress measurement. A large standard deviation of a stress measurement might be an expression of strong crustal heterogeneity rather than of an unreliable stress determination. Robust characterization of stress heterogeneity requires logs that sample stress indicators along a representative sample volume of at least 1 km.

  1. Resistance Training Increases the Variability of Strength Test Scores

    DTIC Science & Technology

    2009-06-08

    standard deviations for pretest and posttest strength measurements. This information was recorded for every strength test used in a total of 377 samples...significant if the posttest standard deviation consistently was larger than the pretest standard deviation. This condition could be satisfied even if...the difference in the standard deviations was small. For example, the posttest standard deviation might be 1% larger than the pretest standard

  2. Incremental Sampling Methodology (ISM) for Metallic Residues

    DTIC Science & Technology

    2013-08-01

    Deviation (also %RSD) Sb Antimony Sn Tin Sr Strontium STD Standard Deviation ERDC TR-13-5 x SU Sampling Unit Ti Titanium UCL Upper Confidence Limit...Ce), chromium (Cr), Cu, Fe, Pb, mag- nesium (Mg), Mn, potassium (K), sodium (Na), strontium (Sr), titanium (Ti), W, zirconium (Zr), and Zn (Clausen...wastes. A proposed alternative to EPA SW 846 Method 3050. Environmental Science and Technology 23: 89 −900. Matzke, B., N. Hassig, J. Wilson, R. Gilber

  3. Estimate of standard deviation for a log-transformed variable using arithmetic means and standard deviations.

    PubMed

    Quan, Hui; Zhang, Ji

    2003-09-15

    Analyses of study variables are frequently based on log transformations. To calculate the power for detecting the between-treatment difference in the log scale, we need an estimate of the standard deviation of the log-transformed variable. However, in many situations a literature search only provides the arithmetic means and the corresponding standard deviations. Without individual log-transformed data to directly calculate the sample standard deviation, we need alternative methods to estimate it. This paper presents methods for estimating and constructing confidence intervals for the standard deviation of a log-transformed variable given the mean and standard deviation of the untransformed variable. It also presents methods for estimating the standard deviation of change from baseline in the log scale given the means and standard deviations of the untransformed baseline value, on-treatment value and change from baseline. Simulations and examples are provided to assess the performance of these estimates. Copyright 2003 John Wiley & Sons, Ltd.

  4. Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory; determination of low-level silver by graphite furnace atomic absorption spectrophotometry

    USGS Publications Warehouse

    Damrau, D.L.

    1993-01-01

    Increased awareness of the quality of water in the United States has led to the development of a method for determining low levels (0.2-5.0 microg/L) of silver in water samples. Use of graphite furnace atomic absorption spectrophotometry provides a sensitive, precise, and accurate method for determining low-level silver in samples of low ionic-strength water, precipitation water, and natural water. The minimum detection limit determined for low-level silver is 0.2 microg/L. Precision data were collected on natural-water samples and SRWS (Standard Reference Water Samples). The overall percent relative standard deviation for natural-water samples with silver concentrations more than 0.2 microg/L was less than 40 percent throughout the analytical range. For the SRWS with concentrations more than 0.2 microg/L, the overall percent relative standard deviation was less than 25 percent throughout the analytical range. The accuracy of the results was determined by spiking 6 natural-water samples with different known concentrations of the silver standard. The recoveries ranged from 61 to 119 percent at the 0.5-microg/L spike level. At the 1.25-microg/L spike level, the recoveries ranged from 92 to 106 percent. For the high spike level at 3.0 microg/L, the recoveries ranged from 65 to 113 percent. The measured concentrations of silver obtained from known samples were within the Branch of Quality Assurance accepted limits of 1 1/2 standard deviations on the basis of the SRWS program for Inter-Laboratory studies.

  5. Data precision of X-ray fluorescence (XRF) scanning of discrete samples with the ITRAX XRF core-scanner exemplified on loess-paleosol samples

    NASA Astrophysics Data System (ADS)

    Profe, Jörn; Ohlendorf, Christian

    2017-04-01

    XRF-scanning is the state-of-the-art technique for geochemical analyses in marine and lacustrine sedimentology for more than a decade. However, little attention has been paid to data precision and technical limitations so far. Using homogenized, dried and powdered samples (certified geochemical reference standards and samples from a lithologically-contrasting loess-paleosol sequence) minimizes many adverse effects that influence the XRF-signal when analyzing wet sediment cores. This allows the investigation of data precision under ideal conditions and documents a new application of the XRF core-scanner technology at the same time. Reliable interpretations of XRF results require data precision evaluation of single elements as a function of X-ray tube, measurement time, sample compaction and quality of peak fitting. Ten-fold measurement of each sample constitutes data precision. Data precision of XRF measurements theoretically obeys Poisson statistics. Fe and Ca exhibit largest deviations from Poisson statistics. The same elements show the least mean relative standard deviations in the range from 0.5% to 1%. This represents the technical limit of data precision achievable by the installed detector. Measurement times ≥ 30 s reveal mean relative standard deviations below 4% for most elements. The quality of peak fitting is only relevant for elements with overlapping fluorescence lines such as Ba, Ti and Mn or for elements with low concentrations such as Y, for example. Differences in sample compaction are marginal and do not change mean relative standard deviation considerably. Data precision is in the range reported for geochemical reference standards measured by conventional techniques. Therefore, XRF scanning of discrete samples provide a cost- and time-efficient alternative to conventional multi-element analyses. As best trade-off between economical operation and data quality, we recommend a measurement time of 30 s resulting in a total scan time of 30 minutes for 30 samples.

  6. Intraobserver reliability of contact pachymetry in children.

    PubMed

    Weise, Katherine K; Kaminski, Brett; Melia, Michele; Repka, Michael X; Bradfield, Yasmin S; Davitt, Bradley V; Johnson, David A; Kraker, Raymond T; Manny, Ruth E; Matta, Noelle S; Schloff, Susan

    2013-04-01

    Central corneal thickness (CCT) is an important measurement in the treatment and management of pediatric glaucoma and potentially of refractive error, but data regarding reliability of CCT measurement in children are limited. The purpose of this study was to evaluate the reliability of CCT measurement with the use of handheld contact pachymetry in children. We conducted a multicenter intraobserver test-retest reliability study of more than 3,400 healthy eyes in children aged from newborn to 17 years by using a handheld contact pachymeter (Pachmate DGH55; DGH Technology Inc, Exton, PA) in 2 clinical settings--with the use of topical anesthesia in the office and with the patient under general anesthesia in a surgical facility. The overall standard error of measurement, including only measurements with standard deviation ≤5 μm, was 8 μm; the corresponding coefficient of repeatability, or limits within which 95% of test-retest differences fell, was ±22.3 μm. However, standard error of measurement increased as CCT increased, from 6.8 μm for CCT less than 525 μm, to 12.9 μm for CCT 625 μm and greater. The standard error of measurement including measurements with standard deviation >5 μm was 10.5 μm. Age, sex, race/ethnicity group, and examination setting did not influence the magnitude of test-retest differences. CCT measurement reliability in children via the Pachmate DGH55 handheld contact pachymeter is similar to that reported for adults. Because thicker CCT measurements are less reliable than thinner measurements, a second measure may be helpful when the first exceeds 575 μm. Reliability is also improved by disregarding measurements with instrument-reported standard deviations >5 μm. Copyright © 2013 American Association for Pediatric Ophthalmology and Strabismus. Published by Mosby, Inc. All rights reserved.

  7. 7 CFR 400.204 - Notification of deviation from standards.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Notification of deviation from standards. 400.204... Contract-Standards for Approval § 400.204 Notification of deviation from standards. A Contractor shall advise the Corporation immediately if the Contractor deviates from the requirements of these standards...

  8. [Effect strength variation in the single group pre-post study design: a critical review].

    PubMed

    Maier-Riehle, B; Zwingmann, C

    2000-08-01

    In Germany, studies in rehabilitation research--in particular evaluation studies and examinations of quality of outcome--have so far mostly been executed according to the uncontrolled one-group pre-post design. Assessment of outcome is usually made by comparing the pre- and post-treatment means of the outcome variables. The pre-post differences are checked, and in case of significance, the results are increasingly presented in form of effect sizes. For this reason, this contribution presents different effect size indices used for the one-group pre-post design--in spite of fundamental doubts which exist in relation to that design due to its limited internal validity. The numerator concerning all effect size indices of the one-group pre-post design is defined as difference between the pre- and post-treatment means, whereas there are different possibilities and recommendations with regard to the denominator and hence the standard deviation that serves as the basis for standardizing the difference of the means. Used above all are standardization oriented towards the standard deviation of the pre-treatment scores, standardization oriented towards the pooled standard deviation of the pre- and post-treatment scores, and standardization oriented towards the standard deviation of the pre-post differences. Two examples are given to demonstrate that the different modes of calculating effect size indices in the one-group pre-post design may lead to very different outcome patterns. Additionally, it is pointed out that effect sizes from the uncontrolled one-group pre-post design generally tend to be higher than effect sizes from studies conducted with control groups. Finally, the pros and cons of the different effect size indices are discussed and recommendations are given.

  9. Improving IQ measurement in intellectual disabilities using true deviation from population norms

    PubMed Central

    2014-01-01

    Background Intellectual disability (ID) is characterized by global cognitive deficits, yet the very IQ tests used to assess ID have limited range and precision in this population, especially for more impaired individuals. Methods We describe the development and validation of a method of raw z-score transformation (based on general population norms) that ameliorates floor effects and improves the precision of IQ measurement in ID using the Stanford Binet 5 (SB5) in fragile X syndrome (FXS; n = 106), the leading inherited cause of ID, and in individuals with idiopathic autism spectrum disorder (ASD; n = 205). We compared the distributional characteristics and Q-Q plots from the standardized scores with the deviation z-scores. Additionally, we examined the relationship between both scoring methods and multiple criterion measures. Results We found evidence that substantial and meaningful variation in cognitive ability on standardized IQ tests among individuals with ID is lost when converting raw scores to standardized scaled, index and IQ scores. Use of the deviation z- score method rectifies this problem, and accounts for significant additional variance in criterion validation measures, above and beyond the usual IQ scores. Additionally, individual and group-level cognitive strengths and weaknesses are recovered using deviation scores. Conclusion Traditional methods for generating IQ scores in lower functioning individuals with ID are inaccurate and inadequate, leading to erroneously flat profiles. However assessment of cognitive abilities is substantially improved by measuring true deviation in performance from standardization sample norms. This work has important implications for standardized test development, clinical assessment, and research for which IQ is an important measure of interest in individuals with neurodevelopmental disorders and other forms of cognitive impairment. PMID:26491488

  10. Improving IQ measurement in intellectual disabilities using true deviation from population norms.

    PubMed

    Sansone, Stephanie M; Schneider, Andrea; Bickel, Erika; Berry-Kravis, Elizabeth; Prescott, Christina; Hessl, David

    2014-01-01

    Intellectual disability (ID) is characterized by global cognitive deficits, yet the very IQ tests used to assess ID have limited range and precision in this population, especially for more impaired individuals. We describe the development and validation of a method of raw z-score transformation (based on general population norms) that ameliorates floor effects and improves the precision of IQ measurement in ID using the Stanford Binet 5 (SB5) in fragile X syndrome (FXS; n = 106), the leading inherited cause of ID, and in individuals with idiopathic autism spectrum disorder (ASD; n = 205). We compared the distributional characteristics and Q-Q plots from the standardized scores with the deviation z-scores. Additionally, we examined the relationship between both scoring methods and multiple criterion measures. We found evidence that substantial and meaningful variation in cognitive ability on standardized IQ tests among individuals with ID is lost when converting raw scores to standardized scaled, index and IQ scores. Use of the deviation z- score method rectifies this problem, and accounts for significant additional variance in criterion validation measures, above and beyond the usual IQ scores. Additionally, individual and group-level cognitive strengths and weaknesses are recovered using deviation scores. Traditional methods for generating IQ scores in lower functioning individuals with ID are inaccurate and inadequate, leading to erroneously flat profiles. However assessment of cognitive abilities is substantially improved by measuring true deviation in performance from standardization sample norms. This work has important implications for standardized test development, clinical assessment, and research for which IQ is an important measure of interest in individuals with neurodevelopmental disorders and other forms of cognitive impairment.

  11. The Great Attractor: At the Limits of Hubble's Law of the Expanding Universe.

    ERIC Educational Resources Information Center

    Murdin, Paul

    1991-01-01

    Presents the origin and mathematics of Hubble's Law of the expanding universe. Discusses limitations to this law and the related concepts of standard candles, elliptical galaxies, and streaming motions, which are conspicuous deviations from the law. The third of three models proposed as explanations for streaming motions is designated: The Great…

  12. Accuracy of maximum likelihood estimates of a two-state model in single-molecule FRET

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gopich, Irina V.

    2015-01-21

    Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when themore » FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a “chevron” shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated.« less

  13. Accuracy of maximum likelihood estimates of a two-state model in single-molecule FRET

    PubMed Central

    Gopich, Irina V.

    2015-01-01

    Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when the FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a “chevron” shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated. PMID:25612692

  14. The Standard Deviation of Launch Vehicle Environments

    NASA Technical Reports Server (NTRS)

    Yunis, Isam

    2005-01-01

    Statistical analysis is used in the development of the launch vehicle environments of acoustics, vibrations, and shock. The standard deviation of these environments is critical to accurate statistical extrema. However, often very little data exists to define the standard deviation and it is better to use a typical standard deviation than one derived from a few measurements. This paper uses Space Shuttle and expendable launch vehicle flight data to define a typical standard deviation for acoustics and vibrations. The results suggest that 3dB is a conservative and reasonable standard deviation for the source environment and the payload environment.

  15. Comparison of Matrix Frequency-Doubling Technology (FDT) Perimetry with the SWEDISH Interactive Thresholding Algorithm (SITA) Standard Automated Perimetry (SAP) in Mild Glaucoma.

    PubMed

    Doozandeh, Azadeh; Irandoost, Farnoosh; Mirzajani, Ali; Yazdani, Shahin; Pakravan, Mohammad; Esfandiari, Hamed

    2017-01-01

    This study aimed to compare second-generation frequency-doubling technology (FDT) perimetry with standard automated perimetry (SAP) in mild glaucoma. Forty-seven eyes of 47 participants who had mild visual field defect by SAP were included in this study. All participants were examined using SITA 24-2 (SITA-SAP) and matrix 24-2 (Matrix-FDT). The correlations of global indices and the number of defects on pattern deviation (PD) plots were determined. Agreement between two sets regarding the stage of visual field damage was assessed. Pearson's correlation, intra-cluster comparison, paired t-test, and 95% limit of agreement were calculated. Although there was no significant difference between global indices, the agreement between the two devices regarding the global indices was weak (the limit of agreement for mean deviation was -6.08 to 6.08 and that for pattern standard deviation was -4.42 to 3.42). The agreement between SITA-SAP and Matrix-FDT regarding the Glaucoma Hemifield Test (GHT) and the number of defective points in each quadrant and staging of the visual field damage was also weak. Because the correlation between SITA-SAP and Matrix-FDT regarding global indices, GHT, number of defective points, and stage of the visual field damage in mild glaucoma is weak, Matrix-FDT cannot be used interchangeably with SITA-SAP in the early stages of glaucoma.

  16. Multiple-wavelength transmission measurements in rocket motor plumes

    NASA Astrophysics Data System (ADS)

    Kim, Hong-On

    1991-09-01

    Multiple-wavelength light transmission measurements were used to measure the mean particle size (d(sub 32)), index of refraction (m), and standard deviation of the small particles in the edge of the plume of a small solid propellant rocket motor. The results have shown that the multiple-wavelength light transmission measurement technique can be used to obtain these variables. The technique was shown to be more sensitive to changes in d(sub 32) and standard deviation (sigma) than to m. A GAP/AP/4.7 percent aluminum propellant burned at 25 atm produced particles with d32 = 0.150 +/- 0.006 microns, standard deviation = 1.50 +/- 0.04 and m = 1.63 +/- 0.13. The good correlation of the data indicated that only submicron particles were present in the edge of the plume. In today's budget conscious industry, the solid propellant rocket motor is an ideal propulsion system due to its low cost and simplicity. The major obstacle for solid rocket motors, however, is their limited specific impulse compared to airbreathing motors. One way to help overcome this limitation is to utilize metal fuel additives. Solid propellant rocket motors can achieve high specific impulse with metal fuel additives such as aluminum. Aluminum propellants also increase propellant densities and suppress transverse modes of combustion oscillations by damping the oscillations with the aluminum agglomerates in the combustion chamber.

  17. The linear sizes tolerances and fits system modernization

    NASA Astrophysics Data System (ADS)

    Glukhov, V. I.; Grinevich, V. A.; Shalay, V. V.

    2018-04-01

    The study is carried out on the urgent topic for technical products quality providing in the tolerancing process of the component parts. The aim of the paper is to develop alternatives for improving the system linear sizes tolerances and dimensional fits in the international standard ISO 286-1. The tasks of the work are, firstly, to classify as linear sizes the elements additionally linear coordinating sizes that determine the detail elements location and, secondly, to justify the basic deviation of the tolerance interval for the element's linear size. The geometrical modeling method of real details elements, the analytical and experimental methods are used in the research. It is shown that the linear coordinates are the dimensional basis of the elements linear sizes. To standardize the accuracy of linear coordinating sizes in all accuracy classes, it is sufficient to select in the standardized tolerance system only one tolerance interval with symmetrical deviations: Js for internal dimensional elements (holes) and js for external elements (shafts). The main deviation of this coordinating tolerance is the average zero deviation, which coincides with the nominal value of the coordinating size. Other intervals of the tolerance system are remained for normalizing the accuracy of the elements linear sizes with a fundamental change in the basic deviation of all tolerance intervals is the maximum deviation corresponding to the limit of the element material: EI is the lower tolerance for the of the internal elements (holes) sizes and es is the upper tolerance deviation for the outer elements (shafts) sizes. It is the sizes of the material maximum that are involved in the of the dimensional elements mating of the shafts and holes and determine the fits type.

  18. A standard deviation selection in evolutionary algorithm for grouper fish feed formulation

    NASA Astrophysics Data System (ADS)

    Cai-Juan, Soong; Ramli, Razamin; Rahman, Rosshairy Abdul

    2016-10-01

    Malaysia is one of the major producer countries for fishery production due to its location in the equatorial environment. Grouper fish is one of the potential markets in contributing to the income of the country due to its desirable taste, high demand and high price. However, the demand of grouper fish is still insufficient from the wild catch. Therefore, there is a need to farm grouper fish to cater to the market demand. In order to farm grouper fish, there is a need to have prior knowledge of the proper nutrients needed because there is no exact data available. Therefore, in this study, primary data and secondary data are collected even though there is a limitation of related papers and 30 samples are investigated by using standard deviation selection in Evolutionary algorithm. Thus, this study would unlock frontiers for an extensive research in respect of grouper fish feed formulation. Results shown that the fitness of standard deviation selection in evolutionary algorithm is applicable. The feasible and low fitness, quick solution can be obtained. These fitness can be further predicted to minimize cost in farming grouper fish.

  19. 7 CFR 400.174 - Notification of deviation from financial standards.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Notification of deviation from financial standards... Agreement-Standards for Approval; Regulations for the 1997 and Subsequent Reinsurance Years § 400.174 Notification of deviation from financial standards. An insurer must immediately advise FCIC if it deviates from...

  20. Degrees of Freedom for Allan Deviation Estimates of Multiple Clocks

    DTIC Science & Technology

    2016-04-01

    Allan deviation . Allan deviation will be represented by σ and standard deviation will be represented by δ. In practice, when the Allan deviation of a...the Allan deviation of standard noise types. Once the number of degrees of freedom is known, an approximate confidence interval can be assigned by...measurement errors from paired difference data. We extend this approach by using the Allan deviation to estimate the error in a frequency standard

  1. Tests of local Lorentz invariance violation of gravity in the standard model extension with pulsars.

    PubMed

    Shao, Lijing

    2014-03-21

    The standard model extension is an effective field theory introducing all possible Lorentz-violating (LV) operators to the standard model and general relativity (GR). In the pure-gravity sector of minimal standard model extension, nine coefficients describe dominant observable deviations from GR. We systematically implemented 27 tests from 13 pulsar systems to tightly constrain eight linear combinations of these coefficients with extensive Monte Carlo simulations. It constitutes the first detailed and systematic test of the pure-gravity sector of minimal standard model extension with the state-of-the-art pulsar observations. No deviation from GR was detected. The limits of LV coefficients are expressed in the canonical Sun-centered celestial-equatorial frame for the convenience of further studies. They are all improved by significant factors of tens to hundreds with existing ones. As a consequence, Einstein's equivalence principle is verified substantially further by pulsar experiments in terms of local Lorentz invariance in gravity.

  2. Modeling the Zeeman effect in high altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

    NASA Astrophysics Data System (ADS)

    Larsson, R.; Milz, M.; Rayer, P.; Saunders, R.; Bell, W.; Booton, A.; Buehler, S. A.; Eriksson, P.; John, V.

    2015-10-01

    We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Same channel, there is 1.2 K in average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Same channel, there is 1.3 K in average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies causing up to ± 7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

  3. Modeling the Zeeman effect in high-altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

    NASA Astrophysics Data System (ADS)

    Larsson, Richard; Milz, Mathias; Rayer, Peter; Saunders, Roger; Bell, William; Booton, Anna; Buehler, Stefan A.; Eriksson, Patrick; John, Viju O.

    2016-03-01

    We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high-altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Concerning the same channel, there is 1.2 K on average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Regarding the same channel, there is 1.3 K on average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies, causing up to ±7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

  4. 1 CFR 21.14 - Deviations from standard organization of the Code of Federal Regulations.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 1 General Provisions 1 2010-01-01 2010-01-01 false Deviations from standard organization of the... CODIFICATION General Numbering § 21.14 Deviations from standard organization of the Code of Federal Regulations. (a) Any deviation from standard Code of Federal Regulations designations must be approved in advance...

  5. Upgraded FAA Airfield Capacity Model. Volume 1. Supplemental User’s Guide

    DTIC Science & Technology

    1981-02-01

    SIGMAR (P4.0) cc 1-4 -standard deviation, in seconds, of arrival runway occupancy time (R.O.T.). SIGMAA (F4.0) cc 5-8 -standard deviation, in seconds...iI SI GMAC - The standard deviation of the time from departure clearance to start of roll. SIGMAR - The standard deviation of the arrival runway

  6. Implications of Higgs searches on the four-generation standard model.

    PubMed

    Kuflik, Eric; Nir, Yosef; Volansky, Tomer

    2013-03-01

    Within the four-generation standard model, the Higgs couplings to gluons and to photons deviate in a significant way from the predictions of the three-generation standard model. As a consequence, large departures in several Higgs production and decay channels are expected. Recent Higgs search results, presented by ATLAS, CMS, and CDF, hint on the existence of a Higgs boson with a mass around 125 GeV. Using these results and assuming such a Higgs boson, we derive exclusion limits on the four-generation standard model. For m(H)=125 GeV, the model is excluded above 99.95% confidence level. For 124.5 GeV≤m(H)≤127.5 GeV, an exclusion limit above 99% confidence level is found.

  7. A Visual Model for the Variance and Standard Deviation

    ERIC Educational Resources Information Center

    Orris, J. B.

    2011-01-01

    This paper shows how the variance and standard deviation can be represented graphically by looking at each squared deviation as a graphical object--in particular, as a square. A series of displays show how the standard deviation is the size of the average square.

  8. A new algorithm to reduce noise in microscopy images implemented with a simple program in python.

    PubMed

    Papini, Alessio

    2012-03-01

    All microscopical images contain noise, increasing when (e.g., transmission electron microscope or light microscope) approaching the resolution limit. Many methods are available to reduce noise. One of the most commonly used is image averaging. We propose here to use the mode of pixel values. Simple Python programs process a given number of images, recorded consecutively from the same subject. The programs calculate the mode of the pixel values in a given position (a, b). The result is a new image containing in (a, b) the mode of the values. Therefore, the final pixel value corresponds to that read in at least two of the pixels in position (a, b). The application of the program on a set of images obtained by applying salt and pepper noise and GIMP hurl noise with 10-90% standard deviation showed that the mode performs better than averaging with three-eight images. The data suggest that the mode would be more efficient (in the sense of a lower number of recorded images to process to reduce noise below a given limit) for lower number of total noisy pixels and high standard deviation (as impulse noise and salt and pepper noise), while averaging would be more efficient when the number of varying pixels is high, and the standard deviation is low, as in many cases of Gaussian noise affected images. The two methods may be used serially. Copyright © 2011 Wiley Periodicals, Inc.

  9. Simultaneous quantitative determination of 11 sesquiterpene lactones in Jerusalem artichoke (Helianthus tuberosus L.) leaves by ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry.

    PubMed

    Yuan, Xiaoyan; Yang, Qianxu

    2017-04-01

    A method of ultra high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry was developed for the simultaneous quantification of 11 sesquiterpene lactones in 11 Jerusalem artichoke leaf samples harvested in a number of areas at different periods. The optimal chromatographic conditions were achieved on a ZORBAX Eclipse Plus C 18 column (3.0 × 150 mm, 1.8 μm) with linear gradient elution of methanol and water in 8 min. Quantitative analysis was carried out under selective ion monitoring mode. All of the sesquiterpene lactones showed good linearity (R 2 ≥ 0.9949), repeatability (relative standard deviations < 4.66%), and intra- and interday precisions (relative standard deviations < 4.52%) with an accuracy of 95.24-104.84%. The recoveries measured at three concentration levels varied from 95.07 to 104.87% with relative standard deviations less than 4.9%. The limit of detection and limit of quantitation for this method were 0.89-5.05 and 1.12-44.33 ng/mL, respectively. The results showed that the contents of sesquiterpene lactones varied significantly in the Jerusalem artichoke leaf samples from different areas. Among them, the content of sesquiterpene lactones in the sample collected from Dalian, Liaoning province was the highest and the early flowering period was considered to be the optimal harvest time. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Variability of pesticide detections and concentrations in field replicate water samples collected for the National Water-Quality Assessment Program, 1992-97

    USGS Publications Warehouse

    Martin, Jeffrey D.

    2002-01-01

    Correlation analysis indicates that for most pesticides and concentrations, pooled estimates of relative standard deviation rather than pooled estimates of standard deviation should be used to estimate variability because pooled estimates of relative standard deviation are less affected by heteroscedasticity. The 2 Variability of Pesticide Detections and Concentrations in Field Replicate Water Samples, 1992–97 median pooled relative standard deviation was calculated for all pesticides to summarize the typical variability for pesticide data collected for the NAWQA Program. The median pooled relative standard deviation was 15 percent at concentrations less than 0.01 micrograms per liter (µg/L), 13 percent at concentrations near 0.01 µg/L, 12 percent at concentrations near 0.1 µg/L, 7.9 percent at concentrations near 1 µg/L, and 2.7 percent at concentrations greater than 5 µg/L. Pooled estimates of standard deviation or relative standard deviation presented in this report are larger than estimates based on averages, medians, smooths, or regression of the individual measurements of standard deviation or relative standard deviation from field replicates. Pooled estimates, however, are the preferred method for characterizing variability because they provide unbiased estimates of the variability of the population. Assessments of variability based on standard deviation (rather than variance) underestimate the true variability of the population. Because pooled estimates of variability are larger than estimates based on other approaches, users of estimates of variability must be cognizant of the approach used to obtain the estimate and must use caution in the comparison of estimates based on different approaches.

  11. Basic life support: evaluation of learning using simulation and immediate feedback devices1.

    PubMed

    Tobase, Lucia; Peres, Heloisa Helena Ciqueto; Tomazini, Edenir Aparecida Sartorelli; Teodoro, Simone Valentim; Ramos, Meire Bruna; Polastri, Thatiane Facholi

    2017-10-30

    to evaluate students' learning in an online course on basic life support with immediate feedback devices, during a simulation of care during cardiorespiratory arrest. a quasi-experimental study, using a before-and-after design. An online course on basic life support was developed and administered to participants, as an educational intervention. Theoretical learning was evaluated by means of a pre- and post-test and, to verify the practice, simulation with immediate feedback devices was used. there were 62 participants, 87% female, 90% in the first and second year of college, with a mean age of 21.47 (standard deviation 2.39). With a 95% confidence level, the mean scores in the pre-test were 6.4 (standard deviation 1.61), and 9.3 in the post-test (standard deviation 0.82, p <0.001); in practice, 9.1 (standard deviation 0.95) with performance equivalent to basic cardiopulmonary resuscitation, according to the feedback device; 43.7 (standard deviation 26.86) mean duration of the compression cycle by second of 20.5 (standard deviation 9.47); number of compressions 167.2 (standard deviation 57.06); depth of compressions of 48.1 millimeter (standard deviation 10.49); volume of ventilation 742.7 (standard deviation 301.12); flow fraction percentage of 40.3 (standard deviation 10.03). the online course contributed to learning of basic life support. In view of the need for technological innovations in teaching and systematization of cardiopulmonary resuscitation, simulation and feedback devices are resources that favor learning and performance awareness in performing the maneuvers.

  12. Parameter estimation method and updating of regional prediction equations for ungaged sites in the desert region of California

    USGS Publications Warehouse

    Barth, Nancy A.; Veilleux, Andrea G.

    2012-01-01

    The U.S. Geological Survey (USGS) is currently updating at-site flood frequency estimates for USGS streamflow-gaging stations in the desert region of California. The at-site flood-frequency analysis is complicated by short record lengths (less than 20 years is common) and numerous zero flows/low outliers at many sites. Estimates of the three parameters (mean, standard deviation, and skew) required for fitting the log Pearson Type 3 (LP3) distribution are likely to be highly unreliable based on the limited and heavily censored at-site data. In a generalization of the recommendations in Bulletin 17B, a regional analysis was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the LP3 distribution. A regional skew value of zero from a previously published report was used with a new estimated mean squared error (MSE) of 0.20. A weighted least squares (WLS) regression method was used to develop both a regional standard deviation and a mean model based on annual peak-discharge data for 33 USGS stations throughout California’s desert region. At-site standard deviation and mean values were determined by using an expected moments algorithm (EMA) method for fitting the LP3 distribution to the logarithms of annual peak-discharge data. Additionally, a multiple Grubbs-Beck (MGB) test, a generalization of the test recommended in Bulletin 17B, was used for detecting multiple potentially influential low outliers in a flood series. The WLS regression found that no basin characteristics could explain the variability of standard deviation. Consequently, a constant regional standard deviation model was selected, resulting in a log-space value of 0.91 with a MSE of 0.03 log units. Yet drainage area was found to be statistically significant at explaining the site-to-site variability in mean. The linear WLS regional mean model based on drainage area had a Pseudo- 2 R of 51 percent and a MSE of 0.32 log units. The regional parameter estimates were then used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins. The final equations are functions of drainage area.Average standard errors of prediction for these regression equations range from 214.2 to 856.2 percent.

  13. Analysis of PAEs contaminants in water sources for agriculture, industrial and residential areas from local city district

    NASA Astrophysics Data System (ADS)

    Chen, Qidan; Chen, Qixian; Wu, Fei; Liao, Jia; Zhao, Xi

    2018-02-01

    The technology of DEHP and DBP detection by high performance liquid chromatography coupled with ultraviolet detection (HPLC-UV) was developed and applied in analysis of local water sources from agriculture, industrial and residential areas. Under the optimized sample pretreatment and detection conditions, DEHP and DBP were well separated and detected in 4 mins. The detection limit of DBP was 0.002 mg/L and DEHP was 0.006 mg/L, and it meets the Chinese National Standard limitations for drinking water quality. The linear correlation coefficient of DBP and DEHP standard calibration curves was 0.9998 and 0.9995. The linear range of DBP was 0.020 mg/L ∼20.0 mg/L, with the standard deviation of 0.560% ∼5.07%, and the linear range of DEHP was 0.060 mg/L ∼15.0 mg/L, with the standard deviation of 0.546% ∼5.74%. Ten water samples from Jinwan district of Zhuhai in Guangdong province of China were analyzed. However, the PAEs amounts found in the water sources from industrial areas were higher than the agriculture and residential areas, industries grow incredibly fast in the district in recently years and more attention should be paid to the increasing risks of water sources pollution.

  14. Measurement of the single-top-quark production cross section at CDF.

    PubMed

    Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Copic, K; Cordelli, M; Cortiana, G; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kusakabe, Y; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, H S; Lee, S W; Leone, S; Lewis, J D; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Liss, T M; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R-S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlok, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Schall, I; Scheidle, T; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zheng, Y; Zucchelli, S

    2008-12-19

    We report a measurement of the single-top-quark production cross section in 2.2 fb;{-1} of pp collision data collected by the Collider Detector at Fermilab at sqrt[s]=1.96 TeV. Candidate events are classified as signal-like by three parallel analyses which use likelihood, matrix element, and neural network discriminants. These results are combined in order to improve the sensitivity. We observe a signal consistent with the standard model prediction, but inconsistent with the background-only model by 3.7 standard deviations with a median expected sensitivity of 4.9 standard deviations. We measure a cross section of 2.2(-0.6)(+0.7)(stat+syst) pb, extract the Cabibbo-Kobayashi-Maskawa matrix-element value |V(tb)|=0.88(-0.12)(+0.13)(stat+syst)+/-0.07(theory), and set the limit |V(tb)|>0.66 at the 95% C.L.

  15. How do we assign punishment? The impact of minimal and maximal standards on the evaluation of deviants.

    PubMed

    Kessler, Thomas; Neumann, Jörg; Mummendey, Amélie; Berthold, Anne; Schubert, Thomas; Waldzus, Sven

    2010-09-01

    To explain the determinants of negative behavior toward deviants (e.g., punishment), this article examines how people evaluate others on the basis of two types of standards: minimal and maximal. Minimal standards focus on an absolute cutoff point for appropriate behavior; accordingly, the evaluation of others varies dichotomously between acceptable or unacceptable. Maximal standards focus on the degree of deviation from that standard; accordingly, the evaluation of others varies gradually from positive to less positive. This framework leads to the prediction that violation of minimal standards should elicit punishment regardless of the degree of deviation, whereas punishment in response to violations of maximal standards should depend on the degree of deviation. Four studies assessed or manipulated the type of standard and degree of deviation displayed by a target. Results consistently showed the expected interaction between type of standard (minimal and maximal) and degree of deviation on punishment behavior.

  16. The Probabilistic Nature of Preferential Choice

    ERIC Educational Resources Information Center

    Rieskamp, Jorg

    2008-01-01

    Previous research has developed a variety of theories explaining when and why people's decisions under risk deviate from the standard economic view of expected utility maximization. These theories are limited in their predictive accuracy in that they do not explain the probabilistic nature of preferential choice, that is, why an individual makes…

  17. Spectrophotometric procedure using rhodamine B for determination of submicrogram quantities of antimony in rocks

    USGS Publications Warehouse

    Schnepfe, M.M.

    1973-01-01

    A spectrophotometric procedure using Rhodamine B is given for the determination of antimony in mineralized rocks after its separation as stibine. A study of the Rhodamine B reaction points to the importance of the order of addition of reagents in enhancing sensitivity and increasing the stability of the system. The tolerance of some 26 elements is established for the overall procedure. Although the limit of determination is approximately 0??5 ppm Sb in a 0??2-g sample, the procedure is intended primarily for screening samples containing more than 1 ppm Sb. In pure solutions 0??1 ??g of antimony can be determined with a relative standard deviation of 25%. For >0??2 ??g of antimony a relative standard deviation of 15% or less can be expected. ?? 1973.

  18. Joint US Navy/US Air Force climatic study of the upper atmosphere. Volume 1: January

    NASA Astrophysics Data System (ADS)

    Changery, Michael J.; Williams, Claude N.; Dickenson, Michael L.; Wallace, Brian L.

    1989-07-01

    The upper atmosphere was studied based on 1980 to 1985 twice daily gridded analyses produced by the European Centre for Medium Range Weather Forecasts. This volume is for the month of January. Included are global analyses of: (1) Mean temperature standard deviation; (2) Mean geopotential height standard deviation; (3) Mean density standard deviation; (4) Mean density standard deviation (all for 13 levels - 1000, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30 mb); (5) Mean dew point standard deviation for the 13 levels; and (6) Jet stream at levels 500 through 30 mb. Also included are global 5 degree grid point wind roses for the 13 pressure levels.

  19. 40 CFR 62.14740 - What must I include in the deviation report?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... your unit deviated from the emission limitations or operating limit requirements. (b) The averaged and recorded data for those dates. (c) Duration and causes of each deviation from the emission limitations or... that deviated from the emission limitations or operating limits specified in this subpart, include the...

  20. ECG-Based Detection of Early Myocardial Ischemia in a Computational Model: Impact of Additional Electrodes, Optimal Placement, and a New Feature for ST Deviation

    PubMed Central

    Schulze, Walther H. W.; Jiang, Yuan; Wilhelms, Mathias; Luik, Armin; Dössel, Olaf; Seemann, Gunnar

    2015-01-01

    In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 2–11% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold. PMID:26587538

  1. ECG-Based Detection of Early Myocardial Ischemia in a Computational Model: Impact of Additional Electrodes, Optimal Placement, and a New Feature for ST Deviation.

    PubMed

    Loewe, Axel; Schulze, Walther H W; Jiang, Yuan; Wilhelms, Mathias; Luik, Armin; Dössel, Olaf; Seemann, Gunnar

    2015-01-01

    In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 2-11% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold.

  2. Comparing Standard Deviation Effects across Contexts

    ERIC Educational Resources Information Center

    Ost, Ben; Gangopadhyaya, Anuj; Schiman, Jeffrey C.

    2017-01-01

    Studies using tests scores as the dependent variable often report point estimates in student standard deviation units. We note that a standard deviation is not a standard unit of measurement since the distribution of test scores can vary across contexts. As such, researchers should be cautious when interpreting differences in the numerical size of…

  3. Blood pressure variability in man: its relation to high blood pressure, age and baroreflex sensitivity.

    PubMed

    Mancia, G; Ferrari, A; Gregorini, L; Parati, G; Pomidossi, G; Bertinieri, G; Grassi, G; Zanchetti, A

    1980-12-01

    1. Intra-arterial blood pressure and heart rate were recorded for 24 h in ambulant hospitalized patients of variable age who had normal blood pressure or essential hypertension. Mean 24 h values, standard deviations and variation coefficient were obtained as the averages of values separately analysed for 48 consecutive half-hour periods. 2. In older subjects standard deviation and variation coefficient for mean arterial pressure were greater than in younger subjects with similar pressure values, whereas standard deviation and variation coefficient for mean arterial pressure were greater than in younger subjects with similar pressure values, whereas standard deviation aations and variation coefficient were obtained as the averages of values separately analysed for 48 consecurive half-hour periods. 2. In older subjects standard deviation and variation coefficient for mean arterial pressure were greater than in younger subjects with similar pressure values, whereas standard deviation and variation coefficient for heart rate were smaller. 3. In hypertensive subjects standard deviation for mean arterial pressure was greater than in normotensive subjects of similar ages, but this was not the case for variation coefficient, which was slightly smaller in the former than in the latter group. Normotensive and hypertensive subjects showed no difference in standard deviation and variation coefficient for heart rate. 4. In both normotensive and hypertensive subjects standard deviation and even more so variation coefficient were slightly or not related to arterial baroreflex sensitivity as measured by various methods (phenylephrine, neck suction etc.). 5. It is concluded that blood pressure variability increases and heart rate variability decreases with age, but that changes in variability are not so obvious in hypertension. Also, differences in variability among subjects are only marginally explained by differences in baroreflex function.

  4. Joint US Navy/US Air Force climatic study of the upper atmosphere. Volume 7: July

    NASA Astrophysics Data System (ADS)

    Changery, Michael J.; Williams, Claude N.; Dickenson, Michael L.; Wallace, Brian L.

    1989-07-01

    The upper atmosphere was studied based on 1980 to 1985 twice daily gridded analysis produced by the European Centre for Medium Range Weather Forecasts. This volume is for the month of July. Included are global analyses of: (1) Mean temperature/standard deviation; (2) Mean geopotential height/standard deviation; (3) Mean density/standard deviation; (4) Height and vector standard deviation (all at 13 pressure levels - 1000, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30 mb); (5) Mean dew point standard deviation at levels 1000 through 30 mb; and (6) Jet stream at levels 500 through 30 mb. Also included are global 5 degree grid point wind roses for the 13 pressure levels.

  5. Joint US Navy/US Air Force climatic study of the upper atmosphere. Volume 10: October

    NASA Astrophysics Data System (ADS)

    Changery, Michael J.; Williams, Claude N.; Dickenson, Michael L.; Wallace, Brian L.

    1989-07-01

    The upper atmosphere was studied based on 1980 to 1985 twice daily gridded analysis produced by the European Centre for Medium Range Weather Forecasts. This volume is for the month of October. Included are global analyses of: (1) Mean temperature/standard deviation; (2) Mean geopotential height/standard deviation; (3) Mean density/standard deviation; (4) Height and vector standard deviation (all at 13 pressure levels - 1000, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30 mb); (5) Mean dew point/standard deviation at levels 1000 through 30 mb; and (6) Jet stream at levels 500 through 30 mb. Also included are global 5 degree grid point wind roses for the 13 pressure levels.

  6. Joint US Navy/US Air Force climatic study of the upper atmosphere. Volume 3: March

    NASA Astrophysics Data System (ADS)

    Changery, Michael J.; Williams, Claude N.; Dickenson, Michael L.; Wallace, Brian L.

    1989-11-01

    The upper atmosphere was studied based on 1980 to 1985 twice daily gridded analysis produced by the European Centre for Medium Range Weather Forecasts. This volume is for the month of March. Included are global analyses of: (1) Mean Temperature Standard Deviation; (2) Mean Geopotential Height Standard Deviation; (3) Mean Density Standard Deviation; (4) Height and Vector Standard Deviation (all for 13 pressure levels - 1000, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30 mb); (5) Mean Dew Point Standard Deviation for levels 1000 through 30 mb; and (6) Jet stream for levels 500 through 30 mb. Also included are global 5 degree grid point wind roses for the 13 pressure levels.

  7. Joint US Navy/US Air Force climatic study of the upper atmosphere. Volume 2: February

    NASA Astrophysics Data System (ADS)

    Changery, Michael J.; Williams, Claude N.; Dickenson, Michael L.; Wallace, Brian L.

    1989-09-01

    The upper atmosphere was studied based on 1980 to 1985 twice daily gridded analyses produced by the European Centre for Medium Range Weather Forecasts. This volume is for the month of February. Included are global analyses of: (1) Mean temperature standard deviation; (2) Mean geopotential height standard deviation; (3) Mean density standard deviation; (4) Height and vector standard deviation (all for 13 pressure levels - 1000, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30 mb); (5) Mean dew point standard deviation for the 13 levels; and (6) Jet stream for levels 500 through 30 mb. Also included are global 5 degree grid point wind roses for the 13 pressure levels.

  8. Joint US Navy/US Air Force climatic study of the upper atmosphere. Volume 4: April

    NASA Astrophysics Data System (ADS)

    Changery, Michael J.; Williams, Claude N.; Dickenson, Michael L.; Wallace, Brian L.

    1989-07-01

    The upper atmosphere was studied based on 1980 to 1985 twice daily gridded analyses produced by the European Centre for Medium Range Weather Forecasts. This volume is for the month of April. Included are global analyses of: (1) Mean temperature standard deviation; (2) Mean geopotential height standard deviation; (3) Mean density standard deviation; (4) Height and vector standard deviation (all for 13 pressure levels - 1000, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30 mb); (5) Mean dew point standard deviation for the 13 levels; and (6) Jet stream for levels 500 through 30 mb. Also included are global 5 degree grid point wind roses for the 13 pressure levels.

  9. Precision analysis for standard deviation measurements of immobile single fluorescent molecule images.

    PubMed

    DeSantis, Michael C; DeCenzo, Shawn H; Li, Je-Luen; Wang, Y M

    2010-03-29

    Standard deviation measurements of intensity profiles of stationary single fluorescent molecules are useful for studying axial localization, molecular orientation, and a fluorescence imaging system's spatial resolution. Here we report on the analysis of the precision of standard deviation measurements of intensity profiles of single fluorescent molecules imaged using an EMCCD camera.We have developed an analytical expression for the standard deviation measurement error of a single image which is a function of the total number of detected photons, the background photon noise, and the camera pixel size. The theoretical results agree well with the experimental, simulation, and numerical integration results. Using this expression, we show that single-molecule standard deviation measurements offer nanometer precision for a large range of experimental parameters.

  10. An improved limit on the charge of antihydrogen from stochastic acceleration.

    PubMed

    Ahmadi, M; Baquero-Ruiz, M; Bertsche, W; Butler, E; Capra, A; Carruth, C; Cesar, C L; Charlton, M; Charman, A E; Eriksson, S; Evans, L T; Evetts, N; Fajans, J; Friesen, T; Fujiwara, M C; Gill, D R; Gutierrez, A; Hangst, J S; Hardy, W N; Hayden, M E; Isaac, C A; Ishida, A; Jones, S A; Jonsell, S; Kurchaninov, L; Madsen, N; Maxwell, D; McKenna, J T K; Menary, S; Michan, J M; Momose, T; Munich, J J; Nolan, P; Olchanski, K; Olin, A; Povilus, A; Pusa, P; Rasmussen, C Ø; Robicheaux, F; Sacramento, R L; Sameed, M; Sarid, E; Silveira, D M; So, C; Tharp, T D; Thompson, R I; van der Werf, D P; Wurtele, J S; Zhmoginov, A I

    2016-01-21

    Antimatter continues to intrigue physicists because of its apparent absence in the observable Universe. Current theory requires that matter and antimatter appeared in equal quantities after the Big Bang, but the Standard Model of particle physics offers no quantitative explanation for the apparent disappearance of half the Universe. It has recently become possible to study trapped atoms of antihydrogen to search for possible, as yet unobserved, differences in the physical behaviour of matter and antimatter. Here we consider the charge neutrality of the antihydrogen atom. By applying stochastic acceleration to trapped antihydrogen atoms, we determine an experimental bound on the antihydrogen charge, Qe, of |Q| < 0.71 parts per billion (one standard deviation), in which e is the elementary charge. This bound is a factor of 20 less than that determined from the best previous measurement of the antihydrogen charge. The electrical charge of atoms and molecules of normal matter is known to be no greater than about 10(-21)e for a diverse range of species including H2, He and SF6. Charge-parity-time symmetry and quantum anomaly cancellation demand that the charge of antihydrogen be similarly small. Thus, our measurement constitutes an improved limit and a test of fundamental aspects of the Standard Model. If we assume charge superposition and use the best measured value of the antiproton charge, then we can place a new limit on the positron charge anomaly (the relative difference between the positron and elementary charge) of about one part per billion (one standard deviation), a 25-fold reduction compared to the current best measurement.

  11. 40 CFR 63.7131 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... were no deviations from any emission limitations (emission limit, operating limit, opacity limit, and... deviations from the emission limitations during the reporting period. (6) If there were no periods during.... (d) For each deviation from an emission limitation (emission limit, operating limit, opacity limit...

  12. 40 CFR Appendix B to Part 136 - Definition and Procedure for the Determination of the Method Detection Limit-Revision 1.11

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) GUIDELINES ESTABLISHING TEST PROCEDURES... to a wide variety of sample types ranging from reagent (blank) water containing analyte to wastewater... times the standard deviation of replicate instrumental measurements of the analyte in reagent water. (c...

  13. The repeatability of mean defect with size III and size V standard automated perimetry.

    PubMed

    Wall, Michael; Doyle, Carrie K; Zamba, K D; Artes, Paul; Johnson, Chris A

    2013-02-15

    The mean defect (MD) of the visual field is a global statistical index used to monitor overall visual field change over time. Our goal was to investigate the relationship of MD and its variability for two clinically used strategies (Swedish Interactive Threshold Algorithm [SITA] standard size III and full threshold size V) in glaucoma patients and controls. We tested one eye, at random, for 46 glaucoma patients and 28 ocularly healthy subjects with Humphrey program 24-2 SITA standard for size III and full threshold for size V each five times over a 5-week period. The standard deviation of MD was regressed against the MD for the five repeated tests, and quantile regression was used to show the relationship of variability and MD. A Wilcoxon test was used to compare the standard deviations of the two testing methods following quantile regression. Both types of regression analysis showed increasing variability with increasing visual field damage. Quantile regression showed modestly smaller MD confidence limits. There was a 15% decrease in SD with size V in glaucoma patients (P = 0.10) and a 12% decrease in ocularly healthy subjects (P = 0.08). The repeatability of size V MD appears to be slightly better than size III SITA testing. When using MD to determine visual field progression, a change of 1.5 to 4 decibels (dB) is needed to be outside the normal 95% confidence limits, depending on the size of the stimulus and the amount of visual field damage.

  14. Quantum speed limit time in a magnetic resonance

    NASA Astrophysics Data System (ADS)

    Ivanchenko, E. A.

    2017-12-01

    A visualization for dynamics of a qudit spin vector in a time-dependent magnetic field is realized by means of mapping a solution for a spin vector on the three-dimensional spherical curve (vector hodograph). The obtained results obviously display the quantum interference of precessional and nutational effects on the spin vector in the magnetic resonance. For any spin the bottom bounds of the quantum speed limit time (QSL) are found. It is shown that the bottom bound goes down when using multilevel spin systems. Under certain conditions the non-nil minimal time, which is necessary to achieve the orthogonal state from the initial one, is attained at spin S = 2. An estimation of the product of two and three standard deviations of the spin components are presented. We discuss the dynamics of the mutual uncertainty, conditional uncertainty and conditional variance in terms of spin standard deviations. The study can find practical applications in the magnetic resonance, 3D visualization of computational data and in designing of optimized information processing devices for quantum computation and communication.

  15. Fast and robust standard-deviation-based method for bulk motion compensation in phase-based functional OCT.

    PubMed

    Wei, Xiang; Camino, Acner; Pi, Shaohua; Cepurna, William; Huang, David; Morrison, John C; Jia, Yali

    2018-05-01

    Phase-based optical coherence tomography (OCT), such as OCT angiography (OCTA) and Doppler OCT, is sensitive to the confounding phase shift introduced by subject bulk motion. Traditional bulk motion compensation methods are limited by their accuracy and computing cost-effectiveness. In this Letter, to the best of our knowledge, we present a novel bulk motion compensation method for phase-based functional OCT. Bulk motion associated phase shift can be directly derived by solving its equation using a standard deviation of phase-based OCTA and Doppler OCT flow signals. This method was evaluated on rodent retinal images acquired by a prototype visible light OCT and human retinal images acquired by a commercial system. The image quality and computational speed were significantly improved, compared to two conventional phase compensation methods.

  16. Evaluation on determination of iodine in coal by energy dispersive X-ray fluorescence

    USGS Publications Warehouse

    Wang, B.; Jackson, J.C.; Palmer, C.; Zheng, B.; Finkelman, R.B.

    2005-01-01

    A quick and inexpensive method of relative high iodine determination from coal samples was evaluated. Energy dispersive X-ray fluorescence (EDXRF) provided a detection limit of about 14 ppm (3 times of standard deviations of the blank sample), without any complex sample preparation. An analytical relative standard deviation of 16% was readily attainable for coal samples. Under optimum conditions, coal samples with iodine concentrations higher than 5 ppm can be determined using this EDXRF method. For the time being, due to the general iodine concentrations of coal samples lower than 5 ppm, except for some high iodine content coal, this method can not effectively been used for iodine determination. More work needed to meet the requirement of determination of iodine from coal samples for this method. Copyright ?? 2005 by The Geochemical Society of Japan.

  17. Exploring Students' Conceptions of the Standard Deviation

    ERIC Educational Resources Information Center

    delMas, Robert; Liu, Yan

    2005-01-01

    This study investigated introductory statistics students' conceptual understanding of the standard deviation. A computer environment was designed to promote students' ability to coordinate characteristics of variation of values about the mean with the size of the standard deviation as a measure of that variation. Twelve students participated in an…

  18. 7 CFR 801.4 - Tolerances for dockage testers.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ....10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Riddle separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Sieve separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Total...

  19. 7 CFR 801.4 - Tolerances for dockage testers.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ....10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Riddle separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Sieve separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Total...

  20. 7 CFR 801.4 - Tolerances for dockage testers.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ....10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Riddle separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Sieve separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Total...

  1. 7 CFR 801.4 - Tolerances for dockage testers.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ....10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Riddle separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Sieve separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Total...

  2. Statistics as Unbiased Estimators: Exploring the Teaching of Standard Deviation

    ERIC Educational Resources Information Center

    Wasserman, Nicholas H.; Casey, Stephanie; Champion, Joe; Huey, Maryann

    2017-01-01

    This manuscript presents findings from a study about the knowledge for and planned teaching of standard deviation. We investigate how understanding variance as an unbiased (inferential) estimator--not just a descriptive statistic for the variation (spread) in data--is related to teachers' instruction regarding standard deviation, particularly…

  3. 7 CFR 801.4 - Tolerances for dockage testers.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ....10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Riddle separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Sieve separation ±0.10 percent, mean deviation from standard dockage tester using Hard Red Winter wheat Total...

  4. 7 CFR 801.6 - Tolerances for moisture meters.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... moisture, mean deviation from National standard moisture meter using Hard Red Winter wheat Mid ±0.05 percent moisture, mean deviation from National standard moisture meter using Hard Red Winter wheat High ±0.05 percent moisture, mean deviation from National standard moisture meter using Hard Red Winter wheat...

  5. Quantification of marine aerosol subgrid variability and its correlation with clouds based on high-resolution regional modeling: Quantifying Aerosol Subgrid Variability

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lin, Guangxing; Qian, Yun; Yan, Huiping

    One limitation of most global climate models (GCMs) is that with the horizontal resolutions they typically employ, they cannot resolve the subgrid variability (SGV) of clouds and aerosols, adding extra uncertainties to the aerosol radiative forcing estimation. To inform the development of an aerosol subgrid variability parameterization, here we analyze the aerosol SGV over the southern Pacific Ocean simulated by the high-resolution Weather Research and Forecasting model coupled to Chemistry. We find that within a typical GCM grid, the aerosol mass subgrid standard deviation is 15% of the grid-box mean mass near the surface on a 1 month mean basis.more » The fraction can increase to 50% in the free troposphere. The relationships between the sea-salt mass concentration, meteorological variables, and sea-salt emission rate are investigated in both the clear and cloudy portion. Under clear-sky conditions, marine aerosol subgrid standard deviation is highly correlated with the standard deviations of vertical velocity, cloud water mixing ratio, and sea-salt emission rates near the surface. It is also strongly connected to the grid box mean aerosol in the free troposphere (between 2 km and 4 km). In the cloudy area, interstitial sea-salt aerosol mass concentrations are smaller, but higher correlation is found between the subgrid standard deviations of aerosol mass and vertical velocity. Additionally, we find that decreasing the model grid resolution can reduce the marine aerosol SGV but strengthen the correlations between the aerosol SGV and the total water mixing ratio (sum of water vapor, cloud liquid, and cloud ice mixing ratios).« less

  6. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aad G.; Abbott B.; Abdallah J.

    This Letter presents a search for the Standard Model Higgs boson in the decay channel H {yields} ZZ{sup (*)} {yields} {ell}{sup +}{ell}{sup -}{ell}{prime}{sup +}{ell}{prime}{sup -}, where {ell}, {ell}{prime} = e or {mu}, using proton-proton collisions at {radical}s = 7 TeV recorded with the ATLAS detector and corresponding to an integrated luminosity of 4.8 fb{sup -1}. The four-lepton invariant mass distribution is compared with Standard Model background expectations to derive upper limits on the cross section of a Standard Model Higgs boson with a mass between 110 GeV and 600 GeV. The mass ranges 134-156 GeV, 182-233 GeV, 256-265 GeV andmore » 268-415 GeV are excluded at the 95% confidence level. The largest upward deviations from the background-only hypothesis are observed for Higgs boson masses of 125 GeV, 244 GeV and 500 GeV with local significances of 2.1, 2.2 and 2.1 standard deviations, respectively. Once the look-elsewhere effect is considered, none of these excesses are significant.« less

  7. Study of vector boson scattering and search for new physics in events with two same-sign leptons and two jets

    DOE PAGES

    Khachatryan, Vardan

    2015-02-02

    Our study of vector boson scattering in pp collisions at a center-of-mass energy of 8 TeV is presented. The data sample corresponds to an integrated luminosity of 19.4 fb -1 collected with the CMS detector. Candidate events are selected with exactly two leptons of the same charge, two jets with large rapidity separation and high dijet mass, and moderate missing transverse energy. The signal region is expected to be dominated by electroweak same-sign W-boson pair production. The observation agrees with the standard model prediction. Furthermore, the observed significance is 2.0 standard deviations, where a significance of 3.1 standard deviations ismore » expected based on the standard model. Cross section measurements for W ±W ± and WZ processes in the fiducial region are reported. Bounds on the structure of quartic vector-boson interactions are given in the framework of dimension-eight effective field theory operators, as well as limits on the production of doubly charged Higgs bosons.« less

  8. Study of vector boson scattering and search for new physics in events with two same-sign leptons and two jets.

    PubMed

    Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Bergauer, T; Dragicevic, M; Erö, J; Friedl, M; Frühwirth, R; Ghete, V M; Hartl, C; Hörmann, N; Hrubec, J; Jeitler, M; Kiesenhofer, W; Knünz, V; Krammer, M; Krätschmer, I; Liko, D; Mikulec, I; Rabady, D; Rahbaran, B; Rohringer, H; Schöfbeck, R; Strauss, J; Treberer-Treberspurg, W; Waltenberger, W; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Alderweireldt, S; Bansal, M; Bansal, S; Cornelis, T; De Wolf, E A; Janssen, X; Knutsson, A; Lauwers, J; Luyckx, S; Ochesanu, S; Rougny, R; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Van Spilbeeck, A; Blekman, F; Blyweert, S; D'Hondt, J; Daci, N; Heracleous, N; Keaveney, J; Lowette, S; Maes, M; Olbrechts, A; Python, Q; Strom, D; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Onsem, G P; Villella, I; Caillol, C; Clerbaux, B; De Lentdecker, G; Dobur, D; Favart, L; Gay, A P R; Grebenyuk, A; Léonard, A; Mohammadi, A; Perniè, L; Reis, T; Seva, T; Thomas, L; Vander Velde, C; Vanlaer, P; Wang, J; Zenoni, F; Adler, V; Beernaert, K; Benucci, L; Cimmino, A; Costantini, S; Crucy, S; Dildick, S; Fagot, A; Garcia, G; Mccartin, J; Ocampo Rios, A A; Ryckbosch, D; Salva Diblen, S; Sigamani, M; Strobbe, N; Thyssen, F; Tytgat, M; Yazgan, E; Zaganidis, N; Basegmez, S; Beluffi, C; Bruno, G; Castello, R; Caudron, A; Ceard, L; Da Silveira, G G; Delaere, C; du Pree, T; Favart, D; Forthomme, L; Giammanco, A; Hollar, J; Jafari, A; Jez, P; Komm, M; Lemaitre, V; Nuttens, C; Pagano, D; Perrini, L; Pin, A; Piotrzkowski, K; Popov, A; Quertenmont, L; Selvaggi, M; Vidal Marono, M; Vizan Garcia, J M; Beliy, N; Caebergs, T; Daubie, E; Hammad, G H; Aldá Júnior, W L; Alves, G A; Brito, L; Correa Martins Junior, M; Dos Reis Martins, T; Mora Herrera, C; Pol, M E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Malbouisson, H; Matos Figueiredo, D; Mundim, L; Nogima, H; Prado Da Silva, W L; Santaolalla, J; Santoro, A; Sznajder, A; Tonelli Manganote, E J; Vilela Pereira, A; Bernardes, C A; Dogra, S; Fernandez Perez Tomei, T R; Gregores, E M; Mercadante, P G; Novaes, S F; Padula, Sandra S; Aleksandrov, A; Genchev, V; Iaydjiev, P; Marinov, A; Piperov, S; Rodozov, M; Sultanov, G; Vutova, M; Dimitrov, A; Glushkov, I; Hadjiiska, R; Litov, L; Pavlov, B; Petkov, P; Bian, J G; Chen, G M; Chen, H S; Chen, M; Cheng, T; Du, R; Jiang, C H; Plestina, R; Romeo, F; Tao, J; Wang, Z; Asawatangtrakuldee, C; Ban, Y; Li, Q; Liu, S; Mao, Y; Qian, S J; Wang, D; Zou, W; Avila, C; Cabrera, A; Chaparro Sierra, L F; Florez, C; Gomez, J P; Gomez Moreno, B; Sanabria, J C; Godinovic, N; Lelas, D; Polic, D; Puljak, I; Antunovic, Z; Kovac, M; Brigljevic, V; Kadija, K; Luetic, J; Mekterovic, D; Sudic, L; Attikis, A; Mavromanolakis, G; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Bodlak, M; Finger, M; Finger, M; Assran, Y; Ellithi Kamel, A; Mahmoud, M A; Radi, A; Kadastik, M; Murumaa, M; Raidal, M; Tiko, A; Eerola, P; Fedi, G; Voutilainen, M; Härkönen, J; Karimäki, V; Kinnunen, R; Kortelainen, M J; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Mäenpää, T; Peltola, T; Tuominen, E; Tuominiemi, J; Tuovinen, E; Wendland, L; Talvitie, J; Tuuva, T; Besancon, M; Couderc, F; Dejardin, M; Denegri, D; Fabbro, B; Faure, J L; Favaro, C; Ferri, F; Ganjour, S; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Locci, E; Malcles, J; Rander, J; Rosowsky, A; Titov, M; Baffioni, S; Beaudette, F; Busson, P; Charlot, C; Dahms, T; Dalchenko, M; Dobrzynski, L; Filipovic, N; Florent, A; Granier de Cassagnac, R; Mastrolorenzo, L; Miné, P; Mironov, C; Naranjo, I N; Nguyen, M; Ochando, C; Paganini, P; Regnard, S; Salerno, R; Sauvan, J B; Sirois, Y; Veelken, C; Yilmaz, Y; Zabi, A; Agram, J-L; Andrea, J; Aubin, A; Bloch, D; Brom, J-M; Chabert, E C; Collard, C; Conte, E; Fontaine, J-C; Gelé, D; Goerlach, U; Goetzmann, C; Le Bihan, A-C; Van Hove, P; Gadrat, S; Beauceron, S; Beaupere, N; Boudoul, G; Bouvier, E; Brochet, S; Carrillo Montoya, C A; Chasserat, J; Chierici, R; Contardo, D; Depasse, P; El Mamouni, H; Fan, J; Fay, J; Gascon, S; Gouzevitch, M; Ille, B; Kurca, T; Lethuillier, M; Mirabito, L; Perries, S; Ruiz Alvarez, J D; Sabes, D; Sgandurra, L; Sordini, V; Vander Donckt, M; Verdier, P; Viret, S; Xiao, H; Tsamalaidze, Z; Autermann, C; Beranek, S; Bontenackels, M; Edelhoff, M; Feld, L; Heister, A; Hindrichs, O; Klein, K; Ostapchuk, A; Raupach, F; Sammet, J; Schael, S; Weber, H; Wittmer, B; Zhukov, V; Ata, M; Brodski, M; Dietz-Laursonn, E; Duchardt, D; Erdmann, M; Fischer, R; Güth, A; Hebbeker, T; Heidemann, C; Hoepfner, K; Klingebiel, D; Knutzen, S; Kreuzer, P; Merschmeyer, M; Meyer, A; Millet, P; Olschewski, M; Padeken, K; Papacz, P; Reithler, H; Schmitz, S A; Sonnenschein, L; Teyssier, D; Thüer, S; Weber, M; Cherepanov, V; Erdogan, Y; Flügge, G; Geenen, H; Geisler, M; Haj Ahmad, W; Hoehle, F; Kargoll, B; Kress, T; Kuessel, Y; Künsken, A; Lingemann, J; Nowack, A; Nugent, I M; Perchalla, L; Pooth, O; Stahl, A; Asin, I; Bartosik, N; Behr, J; Behrens, U; Bell, A J; Bethani, A; Borras, K; Burgmeier, A; Cakir, A; Calligaris, L; Campbell, A; Choudhury, S; Costanza, F; Diez Pardos, C; Dolinska, G; Dooling, S; Dorland, T; Eckerlin, G; Eckstein, D; Eichhorn, T; Flucke, G; Garay Garcia, J; Geiser, A; Gunnellini, P; Hauk, J; Hempel, M; Jung, H; Kalogeropoulos, A; Kasemann, M; Katsas, P; Kieseler, J; Kleinwort, C; Korol, I; Krücker, D; Lange, W; Leonard, J; Lipka, K; Lobanov, A; Lohmann, W; Lutz, B; Mankel, R; Marfin, I; Melzer-Pellmann, I-A; Meyer, A B; Mittag, G; Mnich, J; Mussgiller, A; Naumann-Emme, S; Nayak, A; Ntomari, E; Perrey, H; Pitzl, D; Placakyte, R; Raspereza, A; Ribeiro Cipriano, P M; Roland, B; Ron, E; Sahin, M Ö; Salfeld-Nebgen, J; Saxena, P; Schoerner-Sadenius, T; Schröder, M; Seitz, C; Spannagel, S; Vargas Trevino, A D R; Walsh, R; Wissing, C; Aldaya Martin, M; Blobel, V; Centis Vignali, M; Draeger, A R; Erfle, J; Garutti, E; Goebel, K; Görner, M; Haller, J; Hoffmann, M; Höing, R S; Junkes, A; Kirschenmann, H; Klanner, R; Kogler, R; Lange, J; Lapsien, T; Lenz, T; Marchesini, I; Ott, J; Peiffer, T; Perieanu, A; Pietsch, N; Poehlsen, J; Poehlsen, T; Rathjens, D; Sander, C; Schettler, H; Schleper, P; Schlieckau, E; Schmidt, A; Seidel, M; Sola, V; Stadie, H; Steinbrück, G; Troendle, D; Usai, E; Vanelderen, L; Vanhoefer, A; Barth, C; Baus, C; Berger, J; Böser, C; Butz, E; Chwalek, T; De Boer, W; Descroix, A; Dierlamm, A; Feindt, M; Frensch, F; Giffels, M; Gilbert, A; Hartmann, F; Hauth, T; Husemann, U; Katkov, I; Kornmayer, A; Kuznetsova, E; Lobelle Pardo, P; Mozer, M U; Müller, T; Müller, Th; Nürnberg, A; Quast, G; Rabbertz, K; Röcker, S; Simonis, H J; Stober, F M; Ulrich, R; Wagner-Kuhr, J; Wayand, S; Weiler, T; Wolf, R; Anagnostou, G; Daskalakis, G; Geralis, T; Giakoumopoulou, V A; Kyriakis, A; Loukas, D; Markou, A; Markou, C; Psallidas, A; Topsis-Giotis, I; Agapitos, A; Kesisoglou, S; Panagiotou, A; Saoulidou, N; Stiliaris, E; Aslanoglou, X; Evangelou, I; Flouris, G; Foudas, C; Kokkas, P; Manthos, N; Papadopoulos, I; Paradas, E; Strologas, J; Bencze, G; Hajdu, C; Hidas, P; Horvath, D; Sikler, F; Veszpremi, V; Vesztergombi, G; Zsigmond, A J; Beni, N; Czellar, S; Karancsi, J; Molnar, J; Palinkas, J; Szillasi, Z; Makovec, A; Raics, P; Trocsanyi, Z L; Ujvari, B; Swain, S K; Beri, S B; Bhatnagar, V; Gupta, R; Bhawandeep, U; Kalsi, A K; Kaur, M; Kumar, R; Mittal, M; Nishu, N; Singh, J B; Kumar, Ashok; Kumar, Arun; Ahuja, S; Bhardwaj, A; Choudhary, B C; Kumar, A; Malhotra, S; Naimuddin, M; Ranjan, K; Sharma, V; Banerjee, S; Bhattacharya, S; Chatterjee, K; Dutta, S; Gomber, B; Jain, Sa; Jain, Sh; Khurana, R; Modak, A; Mukherjee, S; Roy, D; Sarkar, S; Sharan, M; Abdulsalam, A; Dutta, D; Kailas, S; Kumar, V; Mohanty, A K; Pant, L M; Shukla, P; Topkar, A; Aziz, T; Banerjee, S; Bhowmik, S; Chatterjee, R M; Dewanjee, R K; Dugad, S; Ganguly, S; Ghosh, S; Guchait, M; Gurtu, A; Kole, G; Kumar, S; Maity, M; Majumder, G; Mazumdar, K; Mohanty, G B; Parida, B; Sudhakar, K; Wickramage, N; Bakhshiansohi, H; Behnamian, H; Etesami, S M; Fahim, A; Goldouzian, R; Khakzad, M; Mohammadi Najafabadi, M; Naseri, M; Paktinat Mehdiabadi, S; Rezaei Hosseinabadi, F; Safarzadeh, B; Zeinali, M; Felcini, M; Grunewald, M; Abbrescia, M; Calabria, C; Chhibra, S S; Colaleo, A; Creanza, D; De Filippis, N; De Palma, M; Fiore, L; Iaselli, G; Maggi, G; Maggi, M; My, S; Nuzzo, S; Pompili, A; Pugliese, G; Radogna, R; Selvaggi, G; Sharma, A; Silvestris, L; Venditti, R; Abbiendi, G; Benvenuti, A C; Bonacorsi, D; Braibant-Giacomelli, S; Brigliadori, L; Campanini, R; Capiluppi, P; Castro, A; Cavallo, F R; Codispoti, G; Cuffiani, M; Dallavalle, G M; Fabbri, F; Fanfani, A; Fasanella, D; Giacomelli, P; Grandi, C; Guiducci, L; Marcellini, S; Masetti, G; Montanari, A; Navarria, F L; Perrotta, A; Primavera, F; Rossi, A M; Rovelli, T; Siroli, G P; Tosi, N; Travaglini, R; Albergo, S; Cappello, G; Chiorboli, M; Costa, S; Giordano, F; Potenza, R; Tricomi, A; Tuve, C; Barbagli, G; Ciulli, V; 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Ruchti, R; Valls, N; Wayne, M; Wolf, M; Woodard, A; Antonelli, L; Brinson, J; Bylsma, B; Durkin, L S; Flowers, S; Hart, A; Hill, C; Hughes, R; Kotov, K; Ling, T Y; Luo, W; Puigh, D; Rodenburg, M; Smith, G; Winer, B L; Wolfe, H; Wulsin, H W; Driga, O; Elmer, P; Hardenbrook, J; Hebda, P; Hunt, A; Koay, S A; Lujan, P; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Piroué, P; Quan, X; Saka, H; Stickland, D; Tully, C; Werner, J S; Zuranski, A; Brownson, E; Mendez, H; Ramirez Vargas, J E; Barnes, V E; Benedetti, D; Bortoletto, D; De Mattia, M; Gutay, L; Hu, Z; Jha, M K; Jones, M; Jung, K; Kress, M; Leonardo, N; Lopes Pegna, D; Maroussov, V; Miller, D H; Neumeister, N; Radburn-Smith, B C; Shi, X; Shipsey, I; Silvers, D; Svyatkovskiy, A; Wang, F; Xie, W; Xu, L; Yoo, H D; Zablocki, J; Zheng, Y; Parashar, N; Stupak, J; Adair, A; Akgun, B; Ecklund, K M; Geurts, F J M; Li, W; Michlin, B; Padley, B P; Redjimi, R; Roberts, J; Zabel, J; Betchart, B; Bodek, A; Covarelli, R; de Barbaro, P; Demina, R; Eshaq, Y; Ferbel, T; Garcia-Bellido, A; Goldenzweig, P; Han, J; Harel, A; Khukhunaishvili, A; Korjenevski, S; Petrillo, G; Vishnevskiy, D; Ciesielski, R; Demortier, L; Goulianos, K; Lungu, G; Mesropian, C; Arora, S; Barker, A; Chou, J P; Contreras-Campana, C; Contreras-Campana, E; Duggan, D; Ferencek, D; Gershtein, Y; Gray, R; Halkiadakis, E; Hidas, D; Kaplan, S; Lath, A; Panwalkar, S; Park, M; Patel, R; Salur, S; Schnetzer, S; Somalwar, S; Stone, R; Thomas, S; Thomassen, P; Walker, M; Rose, K; Spanier, S; York, A; Bouhali, O; Castaneda Hernandez, A; Eusebi, R; Flanagan, W; Gilmore, J; Kamon, T; Khotilovich, V; Krutelyov, V; Montalvo, R; Osipenkov, I; Pakhotin, Y; Perloff, A; Roe, J; Rose, A; Safonov, A; Suarez, I; Tatarinov, A; Akchurin, N; Cowden, C; Damgov, J; Dragoiu, C; Dudero, P R; Faulkner, J; Kovitanggoon, K; Kunori, S; Lee, S W; Libeiro, T; Volobouev, I; Appelt, E; Delannoy, A G; Greene, S; Gurrola, A; Johns, W; Maguire, C; Mao, Y; Melo, A; Sharma, M; Sheldon, P; Snook, B; Tuo, S; Velkovska, J; Arenton, M W; Boutle, S; Cox, B; Francis, B; Goodell, J; Hirosky, R; Ledovskoy, A; Li, H; Lin, C; Neu, C; Wood, J; Clarke, C; Harr, R; Karchin, P E; Kottachchi Kankanamge Don, C; Lamichhane, P; Sturdy, J; Belknap, D A; Carlsmith, D; Cepeda, M; Dasu, S; Dodd, L; Duric, S; Friis, E; Hall-Wilton, R; Herndon, M; Hervé, A; Klabbers, P; Lanaro, A; Lazaridis, C; Levine, A; Loveless, R; Mohapatra, A; Ojalvo, I; Perry, T; Pierro, G A; Polese, G; Ross, I; Sarangi, T; Savin, A; Smith, W H; Taylor, D; Verwilligen, P; Vuosalo, C; Woods, N

    2015-02-06

    A study of vector boson scattering in pp collisions at a center-of-mass energy of 8 TeV is presented. The data sample corresponds to an integrated luminosity of 19.4  fb(-1) collected with the CMS detector. Candidate events are selected with exactly two leptons of the same charge, two jets with large rapidity separation and high dijet mass, and moderate missing transverse energy. The signal region is expected to be dominated by electroweak same-sign W-boson pair production. The observation agrees with the standard model prediction. The observed significance is 2.0 standard deviations, where a significance of 3.1 standard deviations is expected based on the standard model. Cross section measurements for W(±)W(±) and WZ processes in the fiducial region are reported. Bounds on the structure of quartic vector-boson interactions are given in the framework of dimension-eight effective field theory operators, as well as limits on the production of doubly charged Higgs bosons.

  9. Event-specific qualitative and quantitative detection of five genetically modified rice events using a single standard reference molecule.

    PubMed

    Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Shin, Min-Ki; Moon, Gui-Im; Hong, Jin-Hwan; Kim, Hae-Yeong

    2017-07-01

    One novel standard reference plasmid, namely pUC-RICE5, was constructed as a positive control and calibrator for event-specific qualitative and quantitative detection of genetically modified (GM) rice (Bt63, Kemingdao1, Kefeng6, Kefeng8, and LLRice62). pUC-RICE5 contained fragments of a rice-specific endogenous reference gene (sucrose phosphate synthase) as well as the five GM rice events. An existing qualitative PCR assay approach was modified using pUC-RICE5 to create a quantitative method with limits of detection correlating to approximately 1-10 copies of rice haploid genomes. In this quantitative PCR assay, the square regression coefficients ranged from 0.993 to 1.000. The standard deviation and relative standard deviation values for repeatability ranged from 0.02 to 0.22 and 0.10% to 0.67%, respectively. The Ministry of Food and Drug Safety (Korea) validated the method and the results suggest it could be used routinely to identify five GM rice events. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Application of Mixed Effects Limits of Agreement in the Presence of Multiple Sources of Variability: Exemplar from the Comparison of Several Devices to Measure Respiratory Rate in COPD Patients

    PubMed Central

    Weir, Christopher J.; Rubio, Noah; Rabinovich, Roberto; Pinnock, Hilary; Hanley, Janet; McCloughan, Lucy; Drost, Ellen M.; Mantoani, Leandro C.; MacNee, William; McKinstry, Brian

    2016-01-01

    Introduction The Bland-Altman limits of agreement method is widely used to assess how well the measurements produced by two raters, devices or systems agree with each other. However, mixed effects versions of the method which take into account multiple sources of variability are less well described in the literature. We address the practical challenges of applying mixed effects limits of agreement to the comparison of several devices to measure respiratory rate in patients with chronic obstructive pulmonary disease (COPD). Methods Respiratory rate was measured in 21 people with a range of severity of COPD. Participants were asked to perform eleven different activities representative of daily life during a laboratory-based standardised protocol of 57 minutes. A mixed effects limits of agreement method was used to assess the agreement of five commercially available monitors (Camera, Photoplethysmography (PPG), Impedance, Accelerometer, and Chest-band) with the current gold standard device for measuring respiratory rate. Results Results produced using mixed effects limits of agreement were compared to results from a fixed effects method based on analysis of variance (ANOVA) and were found to be similar. The Accelerometer and Chest-band devices produced the narrowest limits of agreement (-8.63 to 4.27 and -9.99 to 6.80 respectively) with mean bias -2.18 and -1.60 breaths per minute. These devices also had the lowest within-participant and overall standard deviations (3.23 and 3.29 for Accelerometer and 4.17 and 4.28 for Chest-band respectively). Conclusions The mixed effects limits of agreement analysis enabled us to answer the question of which devices showed the strongest agreement with the gold standard device with respect to measuring respiratory rates. In particular, the estimated within-participant and overall standard deviations of the differences, which are easily obtainable from the mixed effects model results, gave a clear indication that the Accelerometer and Chest-band devices performed best. PMID:27973556

  11. Analysis of iodinated haloacetic acids in drinking water by reversed-phase liquid chromatography/electrospray ionization/tandem mass spectrometry with large volume direct aqueous injection.

    PubMed

    Li, Yongtao; Whitaker, Joshua S; McCarty, Christina L

    2012-07-06

    A large volume direct aqueous injection method was developed for the analysis of iodinated haloacetic acids in drinking water by using reversed-phase liquid chromatography/electrospray ionization/tandem mass spectrometry in the negative ion mode. Both the external and internal standard calibration methods were studied for the analysis of monoiodoacetic acid, chloroiodoacetic acid, bromoiodoacetic acid, and diiodoacetic acid in drinking water. The use of a divert valve technique for the mobile phase solvent delay, along with isotopically labeled analogs used as internal standards, effectively reduced and compensated for the ionization suppression typically caused by coexisting common inorganic anions. Under the optimized method conditions, the mean absolute and relative recoveries resulting from the replicate fortified deionized water and chlorinated drinking water analyses were 83-107% with a relative standard deviation of 0.7-11.7% and 84-111% with a relative standard deviation of 0.8-12.1%, respectively. The method detection limits resulting from the external and internal standard calibrations, based on seven fortified deionized water replicates, were 0.7-2.3 ng/L and 0.5-1.9 ng/L, respectively. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. The neuromuscular fatigue induced by repeated scrums generates instability that can be limited by appropriate recovery.

    PubMed

    Morel, B; Hautier, C A

    2017-02-01

    The aim of this study was to evaluate the influence of the fatigue on the machine scrum pushing sagittal forces during repeated scrums and to determine the origin of the knee extensor fatigue. Twelve elite U23 rugby union front row players performed six 6-s scrums every 30 s against a dynamic scrum machine with passive or active recovery. The peak, average, and the standard deviation of the force were measured. A neuromuscular testing procedure of the knee extensors was carried out before and immediately after the repeated scrum protocol including maximal voluntary force, evoked force, and voluntary activation. The average and peak forces did not decrease after six scrums with passive recovery. The standard deviation of the force increased by 70.2 ± 42.7% (P < 0.001). Maximal voluntary/evoked force and voluntary activation decreased (respectively 25.1 ± 7.0%, 14.6 ± 5.5%, and 24 ± 9.9%; P < 0.001). The standard deviation of the force did not increase with active recovery and was associated with lower decrease of maximal voluntary/evoked force and voluntary activation (respectively 12.8 ± 7.9%, 4.9 ± 6.5%, and 7.6 ± 4.1%; all P < 0.01). As a conclusion repeated scrummaging induced an increased machine scrum pushing instability associated with central and peripheral fatigue of the knee extensors. Active recovery seems to limit all these manifestations of fatigue. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  13. Visualizing the Sample Standard Deviation

    ERIC Educational Resources Information Center

    Sarkar, Jyotirmoy; Rashid, Mamunur

    2017-01-01

    The standard deviation (SD) of a random sample is defined as the square-root of the sample variance, which is the "mean" squared deviation of the sample observations from the sample mean. Here, we interpret the sample SD as the square-root of twice the mean square of all pairwise half deviations between any two sample observations. This…

  14. 40 CFR 60.2780 - What must I include in the deviation report?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... from the emission limitations or operating limit requirements. (b) The averaged and recorded data for those dates. (c) Duration and causes of each deviation from the emission limitations or operating limits... deviated from the emission limitations or operating limits specified in this subpart, include the six items...

  15. Multi-technique comparison of troposphere zenith delays and gradients during CONT08

    NASA Astrophysics Data System (ADS)

    Teke, Kamil; Böhm, Johannes; Nilsson, Tobias; Schuh, Harald; Steigenberger, Peter; Dach, Rolf; Heinkelmann, Robert; Willis, Pascal; Haas, Rüdiger; García-Espada, Susana; Hobiger, Thomas; Ichikawa, Ryuichi; Shimizu, Shingo

    2011-07-01

    CONT08 was a 15 days campaign of continuous Very Long Baseline Interferometry (VLBI) sessions during the second half of August 2008 carried out by the International VLBI Service for Geodesy and Astrometry (IVS). In this study, VLBI estimates of troposphere zenith total delays (ZTD) and gradients during CONT08 were compared with those derived from observations with the Global Positioning System (GPS), Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS), and water vapor radiometers (WVR) co-located with the VLBI radio telescopes. Similar geophysical models were used for the analysis of the space geodetic data, whereas the parameterization for the least-squares adjustment of the space geodetic techniques was optimized for each technique. In addition to space geodetic techniques and WVR, ZTD and gradients from numerical weather models (NWM) were used from the European Centre for Medium-Range Weather Forecasts (ECMWF) (all sites), the Japan Meteorological Agency (JMA) and Cloud Resolving Storm Simulator (CReSS) (Tsukuba), and the High Resolution Limited Area Model (HIRLAM) (European sites). Biases, standard deviations, and correlation coefficients were computed between the troposphere estimates of the various techniques for all eleven CONT08 co-located sites. ZTD from space geodetic techniques generally agree at the sub-centimetre level during CONT08, and—as expected—the best agreement is found for intra-technique comparisons: between the Vienna VLBI Software and the combined IVS solutions as well as between the Center for Orbit Determination (CODE) solution and an IGS PPP time series; both intra-technique comparisons are with standard deviations of about 3-6 mm. The best inter space geodetic technique agreement of ZTD during CONT08 is found between the combined IVS and the IGS solutions with a mean standard deviation of about 6 mm over all sites, whereas the agreement with numerical weather models is between 6 and 20 mm. The standard deviations are generally larger at low latitude sites because of higher humidity, and the latter is also the reason why the standard deviations are larger at northern hemisphere stations during CONT08 in comparison to CONT02 which was observed in October 2002. The assessment of the troposphere gradients from the different techniques is not as clear because of different time intervals, different estimation properties, or different observables. However, the best inter-technique agreement is found between the IVS combined gradients and the GPS solutions with standard deviations between 0.2 and 0.7 mm.

  16. Variation in the standard deviation of the lure rating distribution: Implications for estimates of recollection probability.

    PubMed

    Dopkins, Stephen; Varner, Kaitlin; Hoyer, Darin

    2017-10-01

    In word recognition semantic priming of test words increased the false-alarm rate and the mean of confidence ratings to lures. Such priming also increased the standard deviation of confidence ratings to lures and the slope of the z-ROC function, suggesting that the priming increased the standard deviation of the lure evidence distribution. The Unequal Variance Signal Detection (UVSD) model interpreted the priming as increasing the standard deviation of the lure evidence distribution. Without additional parameters the Dual Process Signal Detection (DPSD) model could only accommodate the results by fitting the data for related and unrelated primes separately, interpreting the priming, implausibly, as decreasing the probability of target recollection (DPSD). With an additional parameter, for the probability of false (lure) recollection the model could fit the data for related and unrelated primes together, interpreting the priming as increasing the probability of false recollection. These results suggest that DPSD estimates of target recollection probability will decrease with increases in the lure confidence/evidence standard deviation unless a parameter is included for false recollection. Unfortunately the size of a given lure confidence/evidence standard deviation relative to other possible lure confidence/evidence standard deviations is often unspecified by context. Hence the model often has no way of estimating false recollection probability and thereby correcting its estimates of target recollection probability.

  17. Down-Looking Interferometer Study II, Volume I,

    DTIC Science & Technology

    1980-03-01

    g(standard deviation of AN )(standard deviation of(3) where T’rm is the "reference spectrum", an estimate of the actual spectrum v gv T ’V Cgv . If jpj...spectrum T V . cgv . According to Eq. (2), Z is the standard deviation of the observed contrast spectral radiance AN divided by the effective rms system

  18. 40 CFR 61.207 - Radium-226 sampling and measurement procedures.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... B, Method 114. (3) Calculate the mean, x 1, and the standard deviation, s 1, of the n 1 radium-226... owner or operator of a phosphogypsum stack shall report the mean, standard deviation, 95th percentile..., Method 114. (4) Recalculate the mean and standard deviation of the entire set of n 2 radium-226...

  19. Flexner 2.0-Longitudinal Study of Student Participation in a Campus-Wide General Pathology Course for Graduate Students at The University of Arizona.

    PubMed

    Briehl, Margaret M; Nelson, Mark A; Krupinski, Elizabeth A; Erps, Kristine A; Holcomb, Michael J; Weinstein, John B; Weinstein, Ronald S

    2016-01-01

    Faculty members from the Department of Pathology at The University of Arizona College of Medicine-Tucson have offered a 4-credit course on enhanced general pathology for graduate students since 1996. The course is titled, "Mechanisms of Human Disease." Between 1997 and 2016, 270 graduate students completed Mechanisms of Human Disease. The students came from 21 programs of study. Analysis of Variance, using course grade as the dependent and degree, program, gender, and year (1997-2016) as independent variables, indicated that there was no significant difference in final grade (F = 0.112; P = .8856) as a function of degree (doctorate: mean = 89.60, standard deviation = 5.75; master's: mean = 89.34, standard deviation = 6.00; certificate program: mean = 88.64, standard deviation = 8.25), specific type of degree program (F = 2.066, P = .1316; life sciences: mean = 89.95, standard deviation = 6.40; pharmaceutical sciences: mean = 90.71, standard deviation = 4.57; physical sciences: mean = 87.79, standard deviation = 5.17), or as a function of gender (F = 2.96, P = .0865; males: mean = 88.09, standard deviation = 8.36; females: mean = 89.58, standard deviation = 5.82). Students in the physical and life sciences performed equally well. Mechanisms of Human Disease is a popular course that provides students enrolled in a variety of graduate programs with a medical school-based course on mechanisms of diseases. The addition of 2 new medically oriented Master of Science degree programs has nearly tripled enrollment. This graduate level course also potentially expands the interdisciplinary diversity of participants in our interprofessional education and collaborative practice exercises.

  20. Flexner 2.0—Longitudinal Study of Student Participation in a Campus-Wide General Pathology Course for Graduate Students at The University of Arizona

    PubMed Central

    Briehl, Margaret M.; Nelson, Mark A.; Krupinski, Elizabeth A.; Erps, Kristine A.; Holcomb, Michael J.; Weinstein, John B.

    2016-01-01

    Faculty members from the Department of Pathology at The University of Arizona College of Medicine-Tucson have offered a 4-credit course on enhanced general pathology for graduate students since 1996. The course is titled, “Mechanisms of Human Disease.” Between 1997 and 2016, 270 graduate students completed Mechanisms of Human Disease. The students came from 21 programs of study. Analysis of Variance, using course grade as the dependent and degree, program, gender, and year (1997-2016) as independent variables, indicated that there was no significant difference in final grade (F = 0.112; P = .8856) as a function of degree (doctorate: mean = 89.60, standard deviation = 5.75; master’s: mean = 89.34, standard deviation = 6.00; certificate program: mean = 88.64, standard deviation = 8.25), specific type of degree program (F = 2.066, P = .1316; life sciences: mean = 89.95, standard deviation = 6.40; pharmaceutical sciences: mean = 90.71, standard deviation = 4.57; physical sciences: mean = 87.79, standard deviation = 5.17), or as a function of gender (F = 2.96, P = .0865; males: mean = 88.09, standard deviation = 8.36; females: mean = 89.58, standard deviation = 5.82). Students in the physical and life sciences performed equally well. Mechanisms of Human Disease is a popular course that provides students enrolled in a variety of graduate programs with a medical school-based course on mechanisms of diseases. The addition of 2 new medically oriented Master of Science degree programs has nearly tripled enrollment. This graduate level course also potentially expands the interdisciplinary diversity of participants in our interprofessional education and collaborative practice exercises. PMID:28725783

  1. A method for predicting the noise levels of coannular jets with inverted velocity profiles

    NASA Technical Reports Server (NTRS)

    Russell, J. W.

    1979-01-01

    A coannular jet was equated with a single stream equivalent jet with the same mass flow, energy, and thrust. The acoustic characteristics of the coannular jet were then related to the acoustic characteristics of the single jet. Forward flight effects were included by incorporating a forward exponent, a Doppler amplification factor, and a Strouhal frequency shift. Model test data, including 48 static cases and 22 wind tunnel cases, were used to evaluate the prediction method. For the static cases and the low forward velocity wind tunnel cases, the spectral mean square pressure correlation coefficients were generally greater than 90 percent, and the spectral sound pressure level standard deviation were generally less than 3 decibels. The correlation coefficient and the standard deviation were not affected by changes in equivalent jet velocity. Limitations of the prediction method are also presented.

  2. Laser transit anemometer software development program

    NASA Technical Reports Server (NTRS)

    Abbiss, John B.

    1989-01-01

    Algorithms were developed for the extraction of two components of mean velocity, standard deviation, and the associated correlation coefficient from laser transit anemometry (LTA) data ensembles. The solution method is based on an assumed two-dimensional Gaussian probability density function (PDF) model of the flow field under investigation. The procedure consists of transforming the data ensembles from the data acquisition domain (consisting of time and angle information) to the velocity space domain (consisting of velocity component information). The mean velocity results are obtained from the data ensemble centroid. Through a least squares fitting of the transformed data to an ellipse representing the intersection of a plane with the PDF, the standard deviations and correlation coefficient are obtained. A data set simulation method is presented to test the data reduction process. Results of using the simulation system with a limited test matrix of input values is also given.

  3. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aad, G.; Abbott, B.; Abdallah, J.

    The results of a search for gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton–proton collision data at a centre-of-mass energy ofmore » $$\\sqrt{s}$$ = 13 Te V are presented. The dataset used was recorded in 2015 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 3.2 fb -1 . Six signal selections are defined that best exploit the signal characteristics. The data agree with the Standard Model background expectation in all six signal selections, and the largest deviation is a 2.1 standard deviation excess. The results are interpreted in a simplified model where pair-produced gluinos decay via the lightest chargino to the lightest neutralino. In this model, gluinos are excluded up to masses of approximately 1.6 Te V depending on the mass spectrum of the simplified model, thus surpassing the limits of previous searches.« less

  4. Capillary electrophoresis with laser-induced fluorescence detection for studying amino acid uptake by yeast during beer fermentation.

    PubMed

    Turkia, Heidi; Sirén, Heli; Penttilä, Merja; Pitkänen, Juha-Pekka

    2015-01-01

    The amino acid composition of cultivation broth is known to affect the biomass accumulation, productivity, and vitality of yeast during cultivation. A separation method based on capillary electrophoresis with laser-induced fluorescence (LIF) detection was developed for the determination of amino acid consumption by Saccharomyces cerevisiae during beer fermentation. Intraday relative standard deviations were less than 2.1% for migration times and between 2.9% and 9.9% for peak areas. Interday relative standard deviations were less than 2.5% for migration times and between 4.4% and 18.9% for peak areas. The quantification limit was even as low as 62.5 pM which equals to below attomole level detection. The method was applied to study the rate of amino acid utilization during beer fermentation. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Phase Transition in Protocols Minimizing Work Fluctuations

    NASA Astrophysics Data System (ADS)

    Solon, Alexandre P.; Horowitz, Jordan M.

    2018-05-01

    For two canonical examples of driven mesoscopic systems—a harmonically trapped Brownian particle and a quantum dot—we numerically determine the finite-time protocols that optimize the compromise between the standard deviation and the mean of the dissipated work. In the case of the oscillator, we observe a collection of protocols that smoothly trade off between average work and its fluctuations. However, for the quantum dot, we find that as we shift the weight of our optimization objective from average work to work standard deviation, there is an analog of a first-order phase transition in protocol space: two distinct protocols exchange global optimality with mixed protocols akin to phase coexistence. As a result, the two types of protocols possess qualitatively different properties and remain distinct even in the infinite duration limit: optimal-work-fluctuation protocols never coalesce with the minimal-work protocols, which therefore never become quasistatic.

  6. Tevatron constraints on models of the Higgs boson with exotic spin and parity using decays to bottom-antibottom quark pairs.

    PubMed

    Aaltonen, T; Abazov, V M; Abbott, B; Acharya, B S; Adams, M; Adams, T; Agnew, J P; Alexeev, G D; Alkhazov, G; Alton, A; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Askew, A; Atkins, S; Auerbach, B; Augsten, K; Aurisano, A; Avila, C; Azfar, F; Badaud, F; Badgett, W; Bae, T; Bagby, L; Baldin, B; Bandurin, D V; Banerjee, S; Barbaro-Galtieri, A; Barberis, E; Baringer, P; Barnes, V E; Barnett, B A; Barria, P; Bartlett, J F; Bartos, P; Bassler, U; Bauce, M; Bazterra, V; Bean, A; Bedeschi, F; Begalli, M; Behari, S; Bellantoni, L; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beri, S B; Bernardi, G; Bernhard, R; Bertram, I; Besançon, M; Beuselinck, R; Bhat, P C; Bhatia, S; Bhatnagar, V; Bhatti, A; Bland, K R; Blazey, G; Blessing, S; Bloom, K; Blumenfeld, B; Bocci, A; Bodek, A; Boehnlein, A; Boline, D; Boos, E E; Borissov, G; Bortoletto, D; Borysova, M; Boudreau, J; Boveia, A; Brandt, A; Brandt, O; Brigliadori, L; Brock, R; Bromberg, C; Bross, A; Brown, D; Brucken, E; Bu, X B; Budagov, J; Budd, H S; Buehler, M; Buescher, V; Bunichev, V; Burdin, S; Burkett, K; Busetto, G; Bussey, P; Buszello, C P; Butti, P; Buzatu, A; Calamba, A; Camacho-Pérez, E; Camarda, S; Campanelli, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Casal, B; Casarsa, M; Casey, B C K; Castilla-Valdez, H; Castro, A; Catastini, P; Caughron, S; Cauz, D; Cavaliere, V; Cerri, A; Cerrito, L; Chakrabarti, S; Chan, K M; Chandra, A; Chapon, E; Chen, G; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Cho, K; Cho, S W; Choi, S; Chokheli, D; Choudhary, B; Cihangir, S; Claes, D; Clark, A; Clarke, C; Clutter, J; Convery, M E; Conway, J; Cooke, M; Cooper, W E; Corbo, M; Corcoran, M; Cordelli, M; Couderc, F; Cousinou, M-C; Cox, C A; Cox, D J; Cremonesi, M; Cruz, D; Cuevas, J; Culbertson, R; Cutts, D; Das, A; d'Ascenzo, N; Datta, M; Davies, G; de Barbaro, P; de Jong, S J; De La Cruz-Burelo, E; Déliot, F; Demina, R; Demortier, L; Deninno, M; Denisov, D; Denisov, S P; D'Errico, M; Desai, S; Deterre, C; DeVaughan, K; Devoto, F; Di Canto, A; Di Ruzza, B; Diehl, H T; Diesburg, M; Ding, P F; Dittmann, J R; Dominguez, A; Donati, S; D'Onofrio, M; Dorigo, M; Driutti, A; Dubey, A; Dudko, L V; Duperrin, A; Dutt, S; Eads, M; Ebina, K; Edgar, R; Edmunds, D; Elagin, A; Ellison, J; Elvira, V D; Enari, Y; Erbacher, R; Errede, S; Esham, B; Evans, H; Evdokimov, V N; Farrington, S; Fauré, A; Feng, L; Ferbel, T; Fernández Ramos, J P; Fiedler, F; Field, R; Filthaut, F; Fisher, W; Fisk, H E; Flanagan, G; Forrest, R; Fortner, M; Fox, H; Franklin, M; Freeman, J C; Frisch, H; Fuess, S; Funakoshi, Y; Galloni, C; Garbincius, P H; Garcia-Bellido, A; García-González, J A; Garfinkel, A F; Garosi, P; Gavrilov, V; Geng, W; Gerber, C E; Gerberich, H; Gerchtein, E; Gershtein, Y; Giagu, S; Giakoumopoulou, V; Gibson, K; Ginsburg, C M; Ginther, G; Giokaris, N; Giromini, P; Glagolev, V; Glenzinski, D; Gogota, O; Gold, M; Goldin, D; Golossanov, A; 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Yorita, K; Yoshida, T; Youn, S W; Yu, G B; Yu, I; Yu, J M; Zanetti, A M; Zeng, Y; Zennamo, J; Zhao, T G; Zhou, B; Zhou, C; Zhu, J; Zielinski, M; Zieminska, D; Zivkovic, L; Zucchelli, S

    2015-04-17

    Combined constraints from the CDF and D0 Collaborations on models of the Higgs boson with exotic spin J and parity P are presented and compared with results obtained assuming the standard model value JP=0+. Both collaborations analyzed approximately 10  fb(-) of proton-antiproton collisions with a center-of-mass energy of 1.96 TeV collected at the Fermilab Tevatron. Two models predicting exotic Higgs bosons with JP=0- and JP=2+ are tested. The kinematic properties of exotic Higgs boson production in association with a vector boson differ from those predicted for the standard model Higgs boson. Upper limits at the 95% credibility level on the production rates of the exotic Higgs bosons, expressed as fractions of the standard model Higgs boson production rate, are set at 0.36 for both the JP=0- hypothesis and the JP=2+ hypothesis. If the production rate times the branching ratio to a bottom-antibottom pair is the same as that predicted for the standard model Higgs boson, then the exotic bosons are excluded with significances of 5.0 standard deviations and 4.9 standard deviations for the JP=0- and JP=2+ hypotheses, respectively.

  7. 40 CFR 63.8818 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... period. (4) If there are no deviations from any emission limitations (emission limit or operating limit) that applies to you, a statement that there were no deviations from the emission limitations during the reporting period. (5) For each deviation from an emission limitation that occurs, the compliance report must...

  8. A Note on Standard Deviation and Standard Error

    ERIC Educational Resources Information Center

    Hassani, Hossein; Ghodsi, Mansoureh; Howell, Gareth

    2010-01-01

    Many students confuse the standard deviation and standard error of the mean and are unsure which, if either, to use in presenting data. In this article, we endeavour to address these questions and cover some related ambiguities about these quantities.

  9. Relationship between LiDAR-derived forest canopy height and Landsat images

    Treesearch

    Cristina Pascual; Antonio Garcia-Abril; Warren B. Cohen; Susana Martin-Fernandez

    2010-01-01

    The mean and standard deviation (SD) of light detection and ranging (LiDAR)-derived canopy height are related to forest structure. However, LiDAR data typically cover a limited area and have a high economic cost compared with satellite optical imagery. Optical images may be required to extrapolate LiDAR height measurements across a broad landscape. Different spectral...

  10. Variability in Wechsler Adult Intelligence Scale-IV subtest performance across age.

    PubMed

    Wisdom, Nick M; Mignogna, Joseph; Collins, Robert L

    2012-06-01

    Normal Wechsler Adult Intelligence Scale (WAIS)-IV performance relative to average normative scores alone can be an oversimplification as this fails to recognize disparate subtest heterogeneity that occurs with increasing age. The purpose of the present study is to characterize the patterns of raw score change and associated variability on WAIS-IV subtests across age groupings. Raw WAIS-IV subtest means and standard deviations for each age group were tabulated from the WAIS-IV normative manual along with the coefficient of variation (CV), a measure of score dispersion calculated by dividing the standard deviation by the mean and multiplying by 100. The CV further informs the magnitude of variability represented by each standard deviation. Raw mean scores predictably decreased across age groups. Increased variability was noted in Perceptual Reasoning and Processing Speed Index subtests, as Block Design, Matrix Reasoning, Picture Completion, Symbol Search, and Coding had CV percentage increases ranging from 56% to 98%. In contrast, Working Memory and Verbal Comprehension subtests were more homogeneous with Digit Span, Comprehension, Information, and Similarities percentage of the mean increases ranging from 32% to 43%. Little change in the CV was noted on Cancellation, Arithmetic, Letter/Number Sequencing, Figure Weights, Visual Puzzles, and Vocabulary subtests (<14%). A thorough understanding of age-related subtest variability will help to identify test limitations as well as further our understanding of cognitive domains which remain relatively steady versus those which steadily decline.

  11. Search for resonances in diphoton events at √{s}=13 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

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C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolf, T. M. H.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zwalinski, L.

    2016-09-01

    Searches for new resonances decaying into two photons in the ATLAS experiment at the CERN Large Hadron Collider are described. The analysis is based on proton-proton collision data corresponding to an integrated luminosity of 3.2 fb-1 at √{s}=13 TeV recorded in 2015. Two searches are performed, one targeted at a spin-2 particle of mass larger than 500 GeV, using Randall-Sundrum graviton states as a benchmark model, and one optimized for a spin-0 particle of mass larger than 200 GeV. Varying both the mass and the decay width, the most significant deviation from the background-only hypothesis is observed at a diphoton invariant mass around 750 GeV with local significances of 3.8 and 3.9 standard deviations in the searches optimized for a spin-2 and spin-0 particle, respectively. The global significances are estimated to be 2.1 standard deviations for both analyses. The consistency between the data collected at 13 TeV and 8 TeV is also evaluated. Limits on the production cross section times branching ratio to two photons for the two resonance types are reported. [Figure not available: see fulltext.

  12. 14 CFR Appendix C to Part 91 - Operations in the North Atlantic (NAT) Minimum Navigation Performance Specifications (MNPS) Airspace

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... defined in section 1 of this appendix is as follows: (a) The standard deviation of lateral track errors shall be less than 6.3 NM (11.7 Km). Standard deviation is a statistical measure of data about a mean... standard deviation about the mean encompasses approximately 68 percent of the data and plus or minus 2...

  13. Repeatable source, site, and path effects on the standard deviation for empirical ground-motion prediction models

    USGS Publications Warehouse

    Lin, P.-S.; Chiou, B.; Abrahamson, N.; Walling, M.; Lee, C.-T.; Cheng, C.-T.

    2011-01-01

    In this study, we quantify the reduction in the standard deviation for empirical ground-motion prediction models by removing ergodic assumption.We partition the modeling error (residual) into five components, three of which represent the repeatable source-location-specific, site-specific, and path-specific deviations from the population mean. A variance estimation procedure of these error components is developed for use with a set of recordings from earthquakes not heavily clustered in space.With most source locations and propagation paths sampled only once, we opt to exploit the spatial correlation of residuals to estimate the variances associated with the path-specific and the source-location-specific deviations. The estimation procedure is applied to ground-motion amplitudes from 64 shallow earthquakes in Taiwan recorded at 285 sites with at least 10 recordings per site. The estimated variance components are used to quantify the reduction in aleatory variability that can be used in hazard analysis for a single site and for a single path. For peak ground acceleration and spectral accelerations at periods of 0.1, 0.3, 0.5, 1.0, and 3.0 s, we find that the singlesite standard deviations are 9%-14% smaller than the total standard deviation, whereas the single-path standard deviations are 39%-47% smaller.

  14. Determination of Trace lead (II) by Resonance Light Scattering Based on Pb (II)-KI-MG System

    NASA Astrophysics Data System (ADS)

    Chen, Ninghua; Yang, Yingchun; Hao, Shuai; Li, Yangmin

    2018-01-01

    In pH=3.0 weak acidic solution, it is found that Pb2+ can react with I-to form [PbI4]2-, and it further reacted with MG to form ion-association complex. As a result, the new spectra of RLS appeared and their intensities enhanced greatly. Accordingly, a new method developed for the determination of Pb (II).The appropriate reaction conditions were optimized through experiments. The results show that a strong and stable resonance scattering spectra emerge at the wavelength of 338 nm. The resonance light scattering strength (ΔIRLS) has good linear relationship with the concentration of Pb (II) in the range of 0.2 μg/mL ~ 1.0 μg/mL. The detection limits (LOD) is 0.0155 μg/mL. The relative standard deviation (RSD) is 3.61% (n=11) for the determination of 0.6 μg/mL Pb (II) standard solution. And this method was successfully applied to the determination of three environmental water samples (nongfu spring, tap water, laboratory wastewater). Results illustrate that the addition standard recovery are 80%~107% with relative standard deviation (RSD) between 1.8% to 4.6%.

  15. Verification of spectrophotometric method for nitrate analysis in water samples

    NASA Astrophysics Data System (ADS)

    Kurniawati, Puji; Gusrianti, Reny; Dwisiwi, Bledug Bernanti; Purbaningtias, Tri Esti; Wiyantoko, Bayu

    2017-12-01

    The aim of this research was to verify the spectrophotometric method to analyze nitrate in water samples using APHA 2012 Section 4500 NO3-B method. The verification parameters used were: linearity, method detection limit, level of quantitation, level of linearity, accuracy and precision. Linearity was obtained by using 0 to 50 mg/L nitrate standard solution and the correlation coefficient of standard calibration linear regression equation was 0.9981. The method detection limit (MDL) was defined as 0,1294 mg/L and limit of quantitation (LOQ) was 0,4117 mg/L. The result of a level of linearity (LOL) was 50 mg/L and nitrate concentration 10 to 50 mg/L was linear with a level of confidence was 99%. The accuracy was determined through recovery value was 109.1907%. The precision value was observed using % relative standard deviation (%RSD) from repeatability and its result was 1.0886%. The tested performance criteria showed that the methodology was verified under the laboratory conditions.

  16. Rapid Development and Validation of Improved Reversed-Phase High-performance Liquid Chromatography Method for the Quantification of Mangiferin, a Polyphenol Xanthone Glycoside in Mangifera indica

    PubMed Central

    Naveen, P.; Lingaraju, H. B.; Prasad, K. Shyam

    2017-01-01

    Mangiferin, a polyphenolic xanthone glycoside from Mangifera indica, is used as traditional medicine for the treatment of numerous diseases. The present study was aimed to develop and validate a reversed-phase high-performance liquid chromatography (RP-HPLC) method for the quantification of mangiferin from the bark extract of M. indica. RP-HPLC analysis was performed by isocratic elution with a low-pressure gradient using 0.1% formic acid: acetonitrile (87:13) as a mobile phase with a flow rate of 1.5 ml/min. The separation was done at 26°C using a Kinetex XB-C18 column as stationary phase and the detection wavelength at 256 nm. The proposed method was validated for linearity, precision, accuracy, limit of detection, limit of quantification, and robustness by the International Conference on Harmonisation guidelines. In linearity, the excellent correlation coefficient more than 0.999 indicated good fitting of the curve and also good linearity. The intra- and inter-day precision showed < 1% of relative standard deviation of peak area indicated high reliability and reproducibility of the method. The recovery values at three different levels (50%, 100%, and 150%) of spiked samples were found to be 100.47, 100.89, and 100.99, respectively, and low standard deviation value < 1% shows high accuracy of the method. In robustness, the results remain unaffected by small variation in the analytical parameters, which shows the robustness of the method. Liquid chromatography–mass spectrometry analysis confirmed the presence of mangiferin with M/Z value of 421. The assay developed by HPLC method is a simple, rapid, and reliable for the determination of mangiferin from M. indica. SUMMARY The present study was intended to develop and validate an RP-HPLC method for the quantification of mangiferin from the bark extract of M. indica. The developed method was validated for linearity, precision, accuracy, limit of detection, limit of quantification and robustness by International Conference on Harmonization guidelines. This study proved that the developed assay by HPLC method is a simple, rapid and reliable for the quantification of the mangiferin from M. indica. Abbreviations Used: M. indica: Mangifera indica, RP-HPLC: Reversed-phase high-performance liquid chromatography, M/Z: Mass to charge ratio, ICH: International conference on harmonization, % RSD: Percentage of relative standard deviation, ppm: Parts per million, LOD: Limit of detection, LOQ: Limit of quantification. PMID:28539748

  17. Rapid Development and Validation of Improved Reversed-Phase High-performance Liquid Chromatography Method for the Quantification of Mangiferin, a Polyphenol Xanthone Glycoside in Mangifera indica.

    PubMed

    Naveen, P; Lingaraju, H B; Prasad, K Shyam

    2017-01-01

    Mangiferin, a polyphenolic xanthone glycoside from Mangifera indica , is used as traditional medicine for the treatment of numerous diseases. The present study was aimed to develop and validate a reversed-phase high-performance liquid chromatography (RP-HPLC) method for the quantification of mangiferin from the bark extract of M. indica . RP-HPLC analysis was performed by isocratic elution with a low-pressure gradient using 0.1% formic acid: acetonitrile (87:13) as a mobile phase with a flow rate of 1.5 ml/min. The separation was done at 26°C using a Kinetex XB-C18 column as stationary phase and the detection wavelength at 256 nm. The proposed method was validated for linearity, precision, accuracy, limit of detection, limit of quantification, and robustness by the International Conference on Harmonisation guidelines. In linearity, the excellent correlation coefficient more than 0.999 indicated good fitting of the curve and also good linearity. The intra- and inter-day precision showed < 1% of relative standard deviation of peak area indicated high reliability and reproducibility of the method. The recovery values at three different levels (50%, 100%, and 150%) of spiked samples were found to be 100.47, 100.89, and 100.99, respectively, and low standard deviation value < 1% shows high accuracy of the method. In robustness, the results remain unaffected by small variation in the analytical parameters, which shows the robustness of the method. Liquid chromatography-mass spectrometry analysis confirmed the presence of mangiferin with M/Z value of 421. The assay developed by HPLC method is a simple, rapid, and reliable for the determination of mangiferin from M. indica . The present study was intended to develop and validate an RP-HPLC method for the quantification of mangiferin from the bark extract of M. indica . The developed method was validated for linearity, precision, accuracy, limit of detection, limit of quantification and robustness by International Conference on Harmonization guidelines. This study proved that the developed assay by HPLC method is a simple, rapid and reliable for the quantification of the mangiferin from M. indica . Abbreviations Used: M. indica : Mangifera indica , RP-HPLC: Reversed-phase high-performance liquid chromatography, M/Z: Mass to charge ratio, ICH: International conference on harmonization, % RSD: Percentage of relative standard deviation, ppm: Parts per million, LOD: Limit of detection, LOQ: Limit of quantification.

  18. Dispersion in Rectangular Networks: Effective Diffusivity and Large-Deviation Rate Function

    NASA Astrophysics Data System (ADS)

    Tzella, Alexandra; Vanneste, Jacques

    2016-09-01

    The dispersion of a diffusive scalar in a fluid flowing through a network has many applications including to biological flows, porous media, water supply, and urban pollution. Motivated by this, we develop a large-deviation theory that predicts the evolution of the concentration of a scalar released in a rectangular network in the limit of large time t ≫1 . This theory provides an approximation for the concentration that remains valid for large distances from the center of mass, specifically for distances up to O (t ) and thus much beyond the O (t1 /2) range where a standard Gaussian approximation holds. A byproduct of the approach is a closed-form expression for the effective diffusivity tensor that governs this Gaussian approximation. Monte Carlo simulations of Brownian particles confirm the large-deviation results and demonstrate their effectiveness in describing the scalar distribution when t is only moderately large.

  19. Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical approach in continuous time.

    PubMed

    Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

    2017-06-01

    Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provides a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to selection rules that favor the rare trajectories of interest. Such algorithms are plagued by finite simulation time and finite population size, effects that can render their use delicate. In this paper, we present a numerical approach which uses the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of rare trajectories. The method we propose allows one to extract the infinite-time and infinite-size limit of these estimators, which-as shown on the contact process-provides a significant improvement of the large deviation function estimators compared to the standard one.

  20. Validation of a quantitative NMR method for suspected counterfeit products exemplified on determination of benzethonium chloride in grapefruit seed extracts.

    PubMed

    Bekiroglu, Somer; Myrberg, Olle; Ostman, Kristina; Ek, Marianne; Arvidsson, Torbjörn; Rundlöf, Torgny; Hakkarainen, Birgit

    2008-08-05

    A 1H-nuclear magnetic resonance (NMR) spectroscopy method for quantitative determination of benzethonium chloride (BTC) as a constituent of grapefruit seed extract was developed. The method was validated, assessing its specificity, linearity, range, and precision, as well as accuracy, limit of quantification and robustness. The method includes quantification using an internal reference standard, 1,3,5-trimethoxybenzene, and regarded as simple, rapid, and easy to implement. A commercial grapefruit seed extract was studied and the experiments were performed on spectrometers operating at two different fields, 300 and 600 MHz for proton frequencies, the former with a broad band (BB) probe and the latter equipped with both a BB probe and a CryoProbe. The concentration average for the product sample was 78.0, 77.8 and 78.4 mg/ml using the 300 BB probe, the 600MHz BB probe and CryoProbe, respectively. The standard deviation and relative standard deviation (R.S.D., in parenthesis) for the average concentrations was 0.2 (0.3%), 0.3 (0.4%) and 0.3mg/ml (0.4%), respectively.

  1. Effects of handcuffs on neuropsychological testing: Implications for criminal forensic evaluations.

    PubMed

    Biddle, Christine M; Fazio, Rachel L; Dyshniku, Fiona; Denney, Robert L

    2018-01-01

    Neuropsychological evaluations are increasingly performed in forensic contexts, including in criminal settings where security sometimes cannot be compromised to facilitate evaluation according to standardized procedures. Interpretation of nonstandardized assessment results poses significant challenges for the neuropsychologist. Research is limited in regard to the validation of neuropsychological test accommodation and modification practices that deviate from standard test administration; there is no published research regarding the effects of hand restraints upon neuropsychological evaluation results. This study provides preliminary results regarding the impact of restraints on motor functioning and common neuropsychological tests with a motor component. When restrained, performance on nearly all tests utilized was significantly impacted, including Trail Making Test A/B, a coding test, and several tests of motor functioning. Significant performance decline was observed in both raw scores and normative scores. Regression models are also provided in order to help forensic neuropsychologists adjust for the effect of hand restraints on raw scores of these tests, as the hand restraints also resulted in significant differences in normative scores; in the most striking case there was nearly a full standard deviation of discrepancy.

  2. A better norm-referenced grading using the standard deviation criterion.

    PubMed

    Chan, Wing-shing

    2014-01-01

    The commonly used norm-referenced grading assigns grades to rank-ordered students in fixed percentiles. It has the disadvantage of ignoring the actual distance of scores among students. A simple norm-referenced grading via standard deviation is suggested for routine educational grading. The number of standard deviation of a student's score from the class mean was used as the common yardstick to measure achievement level. Cumulative probability of a normal distribution was referenced to help decide the amount of students included within a grade. RESULTS of the foremost 12 students from a medical examination were used for illustrating this grading method. Grading by standard deviation seemed to produce better cutoffs in allocating an appropriate grade to students more according to their differential achievements and had less chance in creating arbitrary cutoffs in between two similarly scored students than grading by fixed percentile. Grading by standard deviation has more advantages and is more flexible than grading by fixed percentile for norm-referenced grading.

  3. Personal Background Preparation Survey for early identification of nursing students at risk for attrition.

    PubMed

    Johnson, Craig W; Johnson, Ronald; Kim, Mira; McKee, John C

    2009-11-01

    During 2004 and 2005 orientations, all 187 and 188 new matriculates, respectively, in two southwestern U.S. nursing schools completed Personal Background and Preparation Surveys (PBPS) in the first predictive validity study of a diagnostic and prescriptive instrument for averting adverse academic status events (AASE) among nursing or health science professional students. One standard deviation increases in PBPS risks (p < 0.05) multiplied odds of first-year or second-year AASE by approximately 150%, controlling for school affiliation and underrepresented minority student (URMS) status. AASE odds one standard deviation above mean were 216% to 250% those one standard deviation below mean. Odds of first-year or second-year AASE for URMS one standard deviation above the 2004 PBPS mean were 587% those for non-URMS one standard deviation below mean. The PBPS consistently and significantly facilitated early identification of nursing students at risk for AASE, enabling proactive targeting of interventions for risk amelioration and AASE or attrition prevention. Copyright 2009, SLACK Incorporated.

  4. Application of Allan Deviation to Assessing Uncertainties of Continuous-measurement Instruments, and Optimizing Calibration Schemes

    NASA Astrophysics Data System (ADS)

    Jacobson, Gloria; Rella, Chris; Farinas, Alejandro

    2014-05-01

    Technological advancement of instrumentation in atmospheric and other geoscience disciplines over the past decade has lead to a shift from discrete sample analysis to continuous, in-situ monitoring. Standard error analysis used for discrete measurements is not sufficient to assess and compare the error contribution of noise and drift from continuous-measurement instruments, and a different statistical analysis approach should be applied. The Allan standard deviation analysis technique developed for atomic clock stability assessment by David W. Allan [1] can be effectively and gainfully applied to continuous measurement instruments. As an example, P. Werle et al has applied these techniques to look at signal averaging for atmospheric monitoring by Tunable Diode-Laser Absorption Spectroscopy (TDLAS) [2]. This presentation will build on, and translate prior foundational publications to provide contextual definitions and guidelines for the practical application of this analysis technique to continuous scientific measurements. The specific example of a Picarro G2401 Cavity Ringdown Spectroscopy (CRDS) analyzer used for continuous, atmospheric monitoring of CO2, CH4 and CO will be used to define the basics features the Allan deviation, assess factors affecting the analysis, and explore the time-series to Allan deviation plot translation for different types of instrument noise (white noise, linear drift, and interpolated data). In addition, the useful application of using an Allan deviation to optimize and predict the performance of different calibration schemes will be presented. Even though this presentation will use the specific example of the Picarro G2401 CRDS Analyzer for atmospheric monitoring, the objective is to present the information such that it can be successfully applied to other instrument sets and disciplines. [1] D.W. Allan, "Statistics of Atomic Frequency Standards," Proc, IEEE, vol. 54, pp 221-230, Feb 1966 [2] P. Werle, R. Miicke, F. Slemr, "The Limits of Signal Averaging in Atmospheric Trace-Gas Monitoring by Tunable Diode-Laser Absorption Spectroscopy (TDLAS)," Applied Physics, B57, pp 131-139, April 1993

  5. Demonstration of the Gore Module for Passive Ground Water Sampling

    DTIC Science & Technology

    2014-06-01

    ix ACRONYMS AND ABBREVIATIONS % RSD percent relative standard deviation 12DCA 1,2-dichloroethane 112TCA 1,1,2-trichloroethane 1122TetCA...Analysis of Variance ROD Record of Decision RSD relative standard deviation SBR Southern Bush River SVOC semi-volatile organic compound...replicate samples had a relative standard deviation ( RSD ) that was 20% or less. For the remaining analytes (PCE, cDCE, and chloroform), at least 70

  6. Impact of baseline systolic blood pressure on visit-to-visit blood pressure variability: the Kailuan study.

    PubMed

    Wang, Anxin; Li, Zhifang; Yang, Yuling; Chen, Guojuan; Wang, Chunxue; Wu, Yuntao; Ruan, Chunyu; Liu, Yan; Wang, Yilong; Wu, Shouling

    2016-01-01

    To investigate the relationship between baseline systolic blood pressure (SBP) and visit-to-visit blood pressure variability in a general population. This is a prospective longitudinal cohort study on cardiovascular risk factors and cardiovascular or cerebrovascular events. Study participants attended a face-to-face interview every 2 years. Blood pressure variability was defined using the standard deviation and coefficient of variation of all SBP values at baseline and follow-up visits. The coefficient of variation is the ratio of the standard deviation to the mean SBP. We used multivariate linear regression models to test the relationships between SBP and standard deviation, and between SBP and coefficient of variation. Approximately 43,360 participants (mean age: 48.2±11.5 years) were selected. In multivariate analysis, after adjustment for potential confounders, baseline SBPs <120 mmHg were inversely related to standard deviation (P<0.001) and coefficient of variation (P<0.001). In contrast, baseline SBPs ≥140 mmHg were significantly positively associated with standard deviation (P<0.001) and coefficient of variation (P<0.001). Baseline SBPs of 120-140 mmHg were associated with the lowest standard deviation and coefficient of variation. The associations between baseline SBP and standard deviation, and between SBP and coefficient of variation during follow-ups showed a U curve. Both lower and higher baseline SBPs were associated with increased blood pressure variability. To control blood pressure variability, a good target SBP range for a general population might be 120-139 mmHg.

  7. Flexner 3.0-Democratization of Medical Knowledge for the 21st Century: Teaching Medical Science Using K-12 General Pathology as a Gateway Course.

    PubMed

    Weinstein, Ronald S; Krupinski, Elizabeth A; Weinstein, John B; Graham, Anna R; Barker, Gail P; Erps, Kristine A; Holtrust, Angelette L; Holcomb, Michael J

    2016-01-01

    A medical school general pathology course has been reformatted into a K-12 general pathology course. This new course has been implemented at a series of 7 to 12 grade levels and the student outcomes compared. Typically, topics covered mirrored those in a medical school general pathology course serving as an introduction to the mechanisms of diseases. Assessment of student performance was based on their score on a multiple-choice final examination modeled after an examination given to medical students. Two Tucson area schools, in a charter school network, participated in the study. Statistical analysis of examination performances showed that there were no significant differences as a function of school ( F = 0.258, P = .6128), with students at school A having an average test scores of 87.03 (standard deviation = 8.99) and school B 86.00 (standard deviation = 8.18; F = 0.258, P = .6128). Analysis of variance was also conducted on the test scores as a function of gender and class grade. There were no significant differences as a function of gender ( F = 0.608, P = .4382), with females having an average score of 87.18 (standard deviation = 7.24) and males 85.61 (standard deviation = 9.85). There were also no significant differences as a function of grade level ( F = 0.627, P = .6003), with 7th graders having an average of 85.10 (standard deviation = 8.90), 8th graders 86.00 (standard deviation = 9.95), 9th graders 89.67 (standard deviation = 5.52), and 12th graders 86.90 (standard deviation = 7.52). The results demonstrated that middle and upper school students performed equally well in K-12 general pathology. Student course evaluations showed that the course met the student's expectations. One class voted K-12 general pathology their "elective course-of-the-year."

  8. Flexner 3.0—Democratization of Medical Knowledge for the 21st Century

    PubMed Central

    Krupinski, Elizabeth A.; Weinstein, John B.; Graham, Anna R.; Barker, Gail P.; Erps, Kristine A.; Holtrust, Angelette L.; Holcomb, Michael J.

    2016-01-01

    A medical school general pathology course has been reformatted into a K-12 general pathology course. This new course has been implemented at a series of 7 to 12 grade levels and the student outcomes compared. Typically, topics covered mirrored those in a medical school general pathology course serving as an introduction to the mechanisms of diseases. Assessment of student performance was based on their score on a multiple-choice final examination modeled after an examination given to medical students. Two Tucson area schools, in a charter school network, participated in the study. Statistical analysis of examination performances showed that there were no significant differences as a function of school (F = 0.258, P = .6128), with students at school A having an average test scores of 87.03 (standard deviation = 8.99) and school B 86.00 (standard deviation = 8.18; F = 0.258, P = .6128). Analysis of variance was also conducted on the test scores as a function of gender and class grade. There were no significant differences as a function of gender (F = 0.608, P = .4382), with females having an average score of 87.18 (standard deviation = 7.24) and males 85.61 (standard deviation = 9.85). There were also no significant differences as a function of grade level (F = 0.627, P = .6003), with 7th graders having an average of 85.10 (standard deviation = 8.90), 8th graders 86.00 (standard deviation = 9.95), 9th graders 89.67 (standard deviation = 5.52), and 12th graders 86.90 (standard deviation = 7.52). The results demonstrated that middle and upper school students performed equally well in K-12 general pathology. Student course evaluations showed that the course met the student’s expectations. One class voted K-12 general pathology their “elective course-of-the-year.” PMID:28725762

  9. Estimation of the neural drive to the muscle from surface electromyograms

    NASA Astrophysics Data System (ADS)

    Hofmann, David

    Muscle force is highly correlated with the standard deviation of the surface electromyogram (sEMG) produced by the active muscle. Correctly estimating this quantity of non-stationary sEMG and understanding its relation to neural drive and muscle force is of paramount importance. The single constituents of the sEMG are called motor unit action potentials whose biphasic amplitude can interfere (named amplitude cancellation), potentially affecting the standard deviation (Keenan etal. 2005). However, when certain conditions are met the Campbell-Hardy theorem suggests that amplitude cancellation does not affect the standard deviation. By simulation of the sEMG, we verify the applicability of this theorem to myoelectric signals and investigate deviations from its conditions to obtain a more realistic setting. We find no difference in estimated standard deviation with and without interference, standing in stark contrast to previous results (Keenan etal. 2008, Farina etal. 2010). Furthermore, since the theorem provides us with the functional relationship between standard deviation and neural drive we conclude that complex methods based on high density electrode arrays and blind source separation might not bear substantial advantages for neural drive estimation (Farina and Holobar 2016). Funded by NIH Grant Number 1 R01 EB022872 and NSF Grant Number 1208126.

  10. Comparison of a novel fixation device with standard suturing methods for spinal cord stimulators.

    PubMed

    Bowman, Richard G; Caraway, David; Bentley, Ishmael

    2013-01-01

    Spinal cord stimulation is a well-established treatment for chronic neuropathic pain of the trunk or limbs. Currently, the standard method of fixation is to affix the leads of the neuromodulation device to soft tissue, fascia or ligament, through the use of manually tying general suture. A novel semiautomated device is proposed that may be advantageous to the current standard. Comparison testing in an excised caprine spine and simulated bench top model was performed. Three tests were performed: 1) perpendicular pull from fascia of caprine spine; 2) axial pull from fascia of caprine spine; and 3) axial pull from Mylar film. Six samples of each configuration were tested for each scenario. Standard 2-0 Ethibond was compared with a novel semiautomated device (Anulex fiXate). Upon completion of testing statistical analysis was performed for each scenario. For perpendicular pull in the caprine spine, the failure load for standard suture was 8.95 lbs with a standard deviation of 1.39 whereas for fiXate the load was 15.93 lbs with a standard deviation of 2.09. For axial pull in the caprine spine, the failure load for standard suture was 6.79 lbs with a standard deviation of 1.55 whereas for fiXate the load was 12.31 lbs with a standard deviation of 4.26. For axial pull in Mylar film, the failure load for standard suture was 10.87 lbs with a standard deviation of 1.56 whereas for fiXate the load was 19.54 lbs with a standard deviation of 2.24. These data suggest a novel semiautomated device offers a method of fixation that may be utilized in lieu of standard suturing methods as a means of securing neuromodulation devices. Data suggest the novel semiautomated device in fact may provide a more secure fixation than standard suturing methods. © 2012 International Neuromodulation Society.

  11. Case Series Analysis of New Zealand Reports of Rapid Intense Potentiation of Warfarin by Roxithromycin.

    PubMed

    Savage, Ruth L; Tatley, Michael V

    2018-05-01

    We undertook an analysis of all the reports to the New Zealand Centre for Adverse Reactions Monitoring of a roxithromycin/warfarin interaction after two recent reports described intense rapid warfarin potentiation. The interaction was first published in 1995. Cytochrome P450 3A4 inhibition has been the proposed mechanism but has limited biologic plausibility. There are suggestions that the clinical significance of the interaction may be increased by severe illness, polypharmacy, renal dysfunction, older age and increased warfarin sensitivity. To investigate the potentiating effect of warfarin on roxithromycin in this New Zealand case series, the reports were reviewed to identify patients at risk, compare the reporting pattern with published Australian data and evaluate the appropriateness of current prescribing advice. Thirty patient reports were identified. The age range was 23-88 years, mean 66.8, median 73.0 (standard deviation 17.7) and the international normalised ratios after roxithromycin commencement ranged from 3.6 to 16.7 (mean 7.6, median 7.6, standard deviation 3.6). For eight patients with measurements on day 3, international normalised ratios were 4.3-16.7 (mean 10.4, median 8.8, standard deviation 4.4). Four patients had serious haemorrhage. Indications for roxithromycin were a range of respiratory tract infections. Anticoagulation was stable for most patients prior to acute infection. Serious infection occurred in 54.5% (12 of 22 patients with information). Polypharmacy (five or more medicines daily) was used by 36.7% of patients long term, increasing acutely to 83.3%, including additional potentially interacting medicines. Warfarin daily dose (1.5-13.0 mg, mean 4.4, median 4.0, standard deviation 2.2) was moderate to low. Pre-roxithromycin international normalised ratio values ranged from 1.4 to 3.7, mean and median 2.5, standard deviation 0.5. A high proportion of interactions were observed between warfarin and roxithromycin compared with other macrolides and compared with cytochrome P450 3A4-related macrolide interactions. The pattern was similar to published Australian data. In this case series, the high prevalence of acute polypharmacy, including potentially interacting medicines, and serious infection suggests that they may have contributed to warfarin potentiation and increased the clinical significance of a roxithromycin/warfarin interaction.

  12. Special electronic distance meter calibration for precise engineering surveying industrial applications

    NASA Astrophysics Data System (ADS)

    Braun, Jaroslav; Štroner, Martin; Urban, Rudolf

    2015-05-01

    All surveying instruments and their measurements suffer from some errors. To refine the measurement results, it is necessary to use procedures restricting influence of the instrument errors on the measured values or to implement numerical corrections. In precise engineering surveying industrial applications the accuracy of the distances usually realized on relatively short distance is a key parameter limiting the resulting accuracy of the determined values (coordinates, etc.). To determine the size of systematic and random errors of the measured distances were made test with the idea of the suppression of the random error by the averaging of the repeating measurement, and reducing systematic errors influence of by identifying their absolute size on the absolute baseline realized in geodetic laboratory at the Faculty of Civil Engineering CTU in Prague. The 16 concrete pillars with forced centerings were set up and the absolute distances between the points were determined with a standard deviation of 0.02 millimetre using a Leica Absolute Tracker AT401. For any distance measured by the calibrated instruments (up to the length of the testing baseline, i.e. 38.6 m) can now be determined the size of error correction of the distance meter in two ways: Firstly by the interpolation on the raw data, or secondly using correction function derived by previous FFT transformation usage. The quality of this calibration and correction procedure was tested on three instruments (Trimble S6 HP, Topcon GPT-7501, Trimble M3) experimentally using Leica Absolute Tracker AT401. By the correction procedure was the standard deviation of the measured distances reduced significantly to less than 0.6 mm. In case of Topcon GPT-7501 is the nominal standard deviation 2 mm, achieved (without corrections) 2.8 mm and after corrections 0.55 mm; in case of Trimble M3 is nominal standard deviation 3 mm, achieved (without corrections) 1.1 mm and after corrections 0.58 mm; and finally in case of Trimble S6 is nominal standard deviation 1 mm, achieved (without corrections) 1.2 mm and after corrections 0.51 mm. Proposed procedure of the calibration and correction is in our opinion very suitable for increasing of the accuracy of the electronic distance measurement and allows the use of the common surveying instrument to achieve uncommonly high precision.

  13. High-speed rangefinder for industrial application

    NASA Astrophysics Data System (ADS)

    Cavedo, Federico; Pesatori, Alessandro; Norgia, Michele

    2016-06-01

    The proposed work aims to improve one of the most used telemetry techniques to make absolute measurements of distance: the time of flight telemetry. The main limitation of the low-cost implementation of this technique is the low accuracy (some mm) and measurement rate (few measurements per second). In order to overcome these limits we modified the typical setup of this rangefinder exploiting low-cost telecommunication transceivers and radiofrequency synthesizers. The obtained performances are very encouraging, reaching a standard deviation of a few micrometers over the range of some meters.

  14. 40 CFR 63.490 - Batch front-end process vents-performance test methods and procedures to determine compliance.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... limitation is not dependent upon any past production or activity level. (1) If the expected mix of products... acceptable if the response from the high-level calibration gas is at least 20 times the standard deviation of..., appendix A is acceptable if the response from the high-level calibration gas is at least 20 times the...

  15. Analytical Method Development and Validation for the Simultaneous Estimation of Abacavir and Lamivudine by Reversed-phase High-performance Liquid Chromatography in Bulk and Tablet Dosage Forms.

    PubMed

    Raees Ahmad, Sufiyan Ahmad; Patil, Lalit; Mohammed Usman, Mohammed Rageeb; Imran, Mohammad; Akhtar, Rashid

    2018-01-01

    A simple rapid, accurate, precise, and reproducible validated reverse phase high performance liquid chromatography (HPLC) method was developed for the determination of Abacavir (ABAC) and Lamivudine (LAMI) in bulk and tablet dosage forms. The quantification was carried out using Symmetry Premsil C18 (250 mm × 4.6 mm, 5 μm) column run in isocratic way using mobile phase comprising methanol: water (0.05% orthophosphoric acid with pH 3) 83:17 v/v and a detection wavelength of 245 nm and injection volume of 20 μl, with a flow rate of 1 ml/min. In the developed method, the retention times of ABAC and LAMI were found to be 3.5 min and 7.4 min, respectively. The method was validated in terms of linearity, precision, accuracy, limits of detection, limits of quantitation, and robustness in accordance with the International Conference on Harmonization guidelines. The assay of the proposed method was found to be 99% - 101%. The recovery studies were also carried out and mean % recovery was found to be 99% - 101%. The % relative standard deviation from reproducibility was found to be <2%. The proposed method was statistically evaluated and can be applied for routine quality control analysis of ABAC and LAMI in bulk and in tablet dosage form. Attempts were made to develop RP-HPLC method for simultaneous estimation of Abacavir and Lamivudine for the RP-HPLC method. The developed method was validated according to the ICH guidelines. The linearity, precision, range, robustness were within the limits as specified by the ICH guidelines. Hence the method was found to be simple, accurate, precise, economic and reproducible. So the proposed methods can be used for the routine quality control analysis of Abacavir and Lamivudine in bulk drug as well as in formulations. Abbreviations Used: HPLC: High-performance liquid chromatography, UV: Ultraviolet, ICH: International Conference on Harmonization, ABAC: Abacavir, LAMI: Lamivudine, HIV: Human immunodeficiency virus, AIDS: Acquired immunodeficiency syndrome, NRTI: Nucleoside reverse transcriptase inhibitors, ARV: Antiretroviral, RSD: Relative standard deviation, RT: Retention time, SD: Standard deviation.

  16. Computer Programs for the Semantic Differential: Further Modifications.

    ERIC Educational Resources Information Center

    Lawson, Edwin D.; And Others

    The original nine programs for semantic differential analysis have been condensed into three programs which have been further refined and augmented. They yield: (1) means, standard deviations, and standard errors for each subscale on each concept; (2) Evaluation, Potency, and Activity (EPA) means, standard deviations, and standard errors; (3)…

  17. SU-F-T-564: 3 Year Experience of Treatment Plan QualityAssurance for Vero SBRT Patients

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Su, Z; Li, Z; Mamalui, M

    2016-06-15

    Purpose: To verify treatment plan monitor units from iPlan treatment planning system for Vero Stereotactic Body Radiotherapy (SBRT) treatment using both software-based and (homogeneous and heterogeneous) phantom-based approaches. Methods: Dynamic conformal arcs (DCA) were used for SBRT treatment of oligometastasis patients using Vero linear accelerator. For each plan, Monte Carlo calculated treatment plans MU (prescribed dose to water with 1% variance) is verified first by RadCalc software with 3% difference threshold. Beyond 3% differences, treatment plans were copied onto (homogeneous) Scanditronix phantom for non-lung patients and copied onto (heterogeneous) CIRS phantom for lung patients and the corresponding plan dose wasmore » measured using a cc01 ion chamber. The difference between the planed and measured dose was recorded. For the past 3 years, we have treated 180 patients with 315 targets. Out of these patients, 99 targets treatment plan RadCalc calculation exceeded 3% threshold and phantom based measurements were performed with 26 plans using Scanditronix phantom and 73 plans using CIRS phantom. Mean and standard deviation of the dose differences were obtained and presented. Results: For all patient RadCalc calculations, the mean dose difference is 0.76% with a standard deviation of 5.97%. For non-lung patient plan Scanditronix phantom measurements, the mean dose difference is 0.54% with standard deviation of 2.53%; for lung patient plan CIRS phantom measurements, the mean dose difference is −0.04% with a standard deviation of 1.09%; The maximum dose difference is 3.47% for Scanditronix phantom measurements and 3.08% for CIRS phantom measurements. Conclusion: Limitations in secondary MU check software lead to perceived large dose discrepancies for some of the lung patient SBRT treatment plans. Homogeneous and heterogeneous phantoms were used in plan quality assurance for non-lung patients and lung patients, respectively. Phantom based QA showed the relative good agreement between iPlan calculated dose and measured dose.« less

  18. A simplified physical model for assessing solar radiation over Brazil using GOES 8 visible imagery

    NASA Astrophysics Data System (ADS)

    Ceballos, Juan Carlos; Bottino, Marcus Jorge; de Souza, Jaidete Monteiro

    2004-01-01

    Solar radiation assessment by satellite is constrained by physical limitations of imagery and by the accuracy of instantaneous local atmospheric parameters, suggesting that one should use simplified but physically consistent models for operational work. Such a model is presented for use with GOES 8 imagery applied to atmospheres with low aerosol optical depth. Fundamental satellite-derived parameters are reflectance and cloud cover. A classification method applied to a set of images shows that reflectance, usually defined as upper-threshold Rmax in algorithms assessing cloud cover, would amount ˜0.465, corresponding to the transition between a cumuliform and a stratiform cloud field. Ozone absorption is limited to the stratosphere. The model considers two spectral broadband intervals for tropospheric radiative transfer: ultraviolet and visible intervals are essentially nonabsorbing and can be processed as a single interval, while near-infrared intervals have negligible atmospheric scattering and very low cloud transmittance. Typical values of CO2 and O3 content and of precipitable water are considered. A comparison of daily values of modeled mean irradiance with data of three sites (in rural, urban industrial, and urban coastal environments), September-October 2002, exhibits a bias of +5 W m-2 and a standard deviation of ˜15 W m-2 (0.4 and 1.3 MJ m-2 for daily irradiation). A comparison with monthly means from about 80 automatic weather stations (covering a large area throughout the Brazilian territory) still shows a bias generally within ±10 W m-2 and a low standard deviation (<20 W m-2), but the bias has a trend in September-December 2002, suggesting an annual cycle of local Rmax values. Systematic (mean) errors in partial cloud cover and in nearly clear-sky situations may be enhanced using regional values for atmospheric and surface parameters, such as precipitable water, Rmax, and ground reflectance. The larger errors are observed in situations of high aerosol load (especially in regions with industrial activity or forest or agricultural fires). The last case is evident when sites in the Amazonian region or São Paulo city are selected. When considering daily values averaged within 2.5° × 2.5° cells, the standard error is lower than 20 W m-2; present results suggest an annual cycle of mean bias ranging from +10 to -10 W m-2, with an amplitude of ˜10 W m-2. These values are close to the proposed requirements of 10 W m-2 for the mean deviation and 25 W m-2 for the standard deviation. It is expected that the introduction of a reference grid containing mean values of parameters within a cell could induce a decrease in the standard deviation of mean errors and the correction of their annual cycle. A model adaptation for assessing the effect of high aerosol loads is needed in order to extend improvements to the whole Brazilian area.

  19. Tevatron constraints on models of the Higgs boson with exotic spin and parity using decays to bottom-antibottom quark pairs

    DOE PAGES

    Aaltonen, T.

    2015-04-15

    In this study, combined constraints from the CDF and D0 Collaborations on models of the Higgs boson with exotic spin J and parity P are presented and compared with results obtained assuming the standard model value J P = 0 +. Both collaborations analyzed approximately 10 fb –1 of proton-antiproton collisions with a center-of-mass energy of 1.96 TeV collected at the Fermilab Tevatron. Two models predicting exotic Higgs bosons with J P = 0 – and J P = 2 + are tested. The kinematic properties of exotic Higgs boson production in association with a vector boson differ from thosemore » predicted for the standard model Higgs boson. Upper limits at the 95% credibility level on the production rates of the exotic Higgs bosons, expressed as fractions of the standard model Higgs boson production rate, are set at 0.36 for both the J P = 0 – hypothesis and the J P = 2 + hypothesis. If the production rate times the branching ratio to a bottom-antibottom pair is the same as that predicted for the standard model Higgs boson, then the exotic bosons are excluded with significances of 5.0 standard deviations and 4.9 standard deviations for the J P = 0 – and J P = 2 + hypotheses, respectively.« less

  20. Quantitative Assessment of Commutability for Clinical Viral Load Testing Using a Digital PCR-Based Reference Standard

    PubMed Central

    Tang, L.; Sun, Y.; Buelow, D.; Gu, Z.; Caliendo, A. M.; Pounds, S.

    2016-01-01

    Given recent advances in the development of quantitative standards, particularly WHO international standards, efforts to better understand the commutability of reference materials have been made. Existing approaches in evaluating commutability include prediction intervals and correspondence analysis; however, the results obtained from existing approaches may be ambiguous. We have developed a “deviation-from-ideal” (DFI) approach to evaluate commutability of standards and applied it to the assessment of Epstein-Bar virus (EBV) load testing in four quantitative PCR assays, treating digital PCR as a reference assay. We then discuss advantages and limitations of the DFI approach as well as experimental design to best evaluate the commutability of an assay in practice. PMID:27076654

  1. Effects on speed and safety of point-to-point speed enforcement systems: evaluation on the urban motorway A56 Tangenziale di Napoli.

    PubMed

    Montella, Alfonso; Imbriani, Lella Liana; Marzano, Vittorio; Mauriello, Filomena

    2015-02-01

    In this paper, we evaluated the effects on speed and safety of the point-to-point (P2P) speed enforcement system activated on the urban motorway A56 in Italy. The P2P speed enforcement is a relatively new approach to traffic law enforcement that involves the calculation of the average speed over a section. To evaluate the speed effects, we performed a before-after analysis of speed data investigating also effects on non-compliance to speed limits. To evaluate the safety effects, we carried out an empirical Bayes observational before-and-after study. The P2P system led to very positive effects on both speed and safety. As far as the effects on the section average travel speeds, the system yielded to a reduction in the mean speed, the 85th percentile speed, the standard deviation of speed, and the proportion of drivers exceeding the speed limits, exceeding the speed limits more than 10km/h, and exceeding the speed limits more than 20km/h. The best results were the decrease of the speed variability and the reduction of the excessive speeding behaviour. The decrease in the standard deviation of speed was 26% while the proportion of light and heavy vehicles exceeding the speed limits more than 20km/h was reduced respectively by 84 and 77%. As far as the safety effects, the P2P system yielded to a 32% reduction in the total crashes, with a lower 95% confidence limit of the estimate equal to 22%. The greatest crash reductions were in rainy weather (57%), on wet pavement (51%), on curves (49%), for single vehicle crashes (44%), and for injury crashes (37%). It is noteworthy that the system produced a statistically significant reduction of 21% in total crashes also in the part of the motorway where it was not activated, thus generating a significant spillover effect. The investigation of the effects of the P2P system on speed and safety over time allowed to develop crash modification functions where the relationship between crash modification factors and speed parameters (mean speed, 85th percentile speed, and standard deviation of speed) was expressed by a power function. Crash modification functions show that the effect of speed on safety is greater on curves and for injury crashes. Even though the study results show excellent outcomes, we must point out that the crash reduction effects decreased over time and speed, speed variability, and non-compliance to speed limits significantly increased over time. To maintain its effectiveness over time, P2P speed enforcement must be actively managed, i.e. constantly monitored and supported by appropriate sanctions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Complexities of follicle deviation during selection of a dominant follicle in Bos taurus heifers.

    PubMed

    Ginther, O J; Baldrighi, J M; Siddiqui, M A R; Araujo, E R

    2016-11-01

    Follicle deviation during a follicular wave is a continuation in growth rate of the dominant follicle (F1) and decreased growth rate of the largest subordinate follicle (F2). The reliability of using an F1 of 8.5 mm to represent the beginning of expected deviation for experimental purposes during waves 1 and 2 (n = 26 per wave) was studied daily in heifers. Each wave was subgrouped as follows: standard subgroup (F1 larger than F2 for 2 days preceding deviation and F2 > 7.0 mm on the day of deviation), undersized subgroup (F2 did not attain 7.0 mm by the day of deviation), and switched subgroup (F2 larger than F1 at least once on the 2 days before or on the day of deviation). For each wave, mean differences in diameter between F1 and F2 changed abruptly at expected deviation in the standard subgroup but began 1 day before expected deviation in the undersized and switched subgroups. Concentrations of FSH in the wave-stimulating FSH surge and an increase in LH centered on expected deviation did not differ among subgroups. Results for each wave indicated that (1) expected deviation (F1, 8.5 mm) was a reliable representation of actual deviation in the standard subgroup but not in the undersized and switched subgroups; (2) concentrations of the gonadotropins normalized to expected deviation were similar among the three subgroups, indicating that the day of deviation was related to diameter of F1 and not F2; and (3) defining an expected day of deviation for experimental use should consider both diameter of F1 and the characteristics of deviation. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Dynamics of the standard deviations of three wind velocity components from the data of acoustic sounding

    NASA Astrophysics Data System (ADS)

    Krasnenko, N. P.; Kapegesheva, O. F.; Shamanaeva, L. G.

    2017-11-01

    Spatiotemporal dynamics of the standard deviations of three wind velocity components measured with a mini-sodar in the atmospheric boundary layer is analyzed. During the day on September 16 and at night on September 12 values of the standard deviation changed for the x- and y-components from 0.5 to 4 m/s, and for the z-component from 0.2 to 1.2 m/s. An analysis of the vertical profiles of the standard deviations of three wind velocity components for a 6-day measurement period has shown that the increase of σx and σy with altitude is well described by a power law dependence with exponent changing from 0.22 to 1.3 depending on the time of day, and σz depends linearly on the altitude. The approximation constants have been found and their errors have been estimated. The established physical regularities and the approximation constants allow the spatiotemporal dynamics of the standard deviation of three wind velocity components in the atmospheric boundary layer to be described and can be recommended for application in ABL models.

  4. Simultaneous Determination of Multiple Ginsenosides in Panax ginseng Herbal Medicines with One Single Reference Standard.

    PubMed

    Wu, Chunwei; Guan, Qingxiao; Wang, Shumei; Rong, Yueying

    2017-01-01

    Root of Panax ginseng C. A. Mey (Renseng in Chinese) is a famous Traditional Chinese Medicine. Ginsenosides are the major bioactive components. However, the shortage and high cost of some ginsenoside reference standards make it is difficult for quality control of P. ginseng . A method, single standard for determination of multicomponents (SSDMC), was developed for the simultaneous determination of nine ginsenosides in P. ginseng (ginsenoside Rg 1 , Re, Rf, Rg 2 , Rb 1 , Rc, Rb 2 , Rb 3 , Rd). The analytes were separated on Inertsil ODS-3 C18 (250 mm × 4.6 mm, 5 μm) with gradient elution of acetonitrile and water. The flow rate was 1 mL/min and detection wavelength was set at 203 nm. The feasibility and accuracy of SSDMC were checked by the external standard method, and various high-performance liquid chromatographic (HPLC) instruments and chromatographic conditions were investigated to verify its applicability. Using ginsenoside Rg 1 as the internal reference substance, the contents of other eight ginsenosides were calculated according to conversion factors (F) by HPLC. The method was validated with linearity ( r 2 ≥ 0.9990), precision (relative standard deviation [RSD] ≤2.9%), accuracy (97.5%-100.8%, RSD ≤ 1.6%), repeatability, and stability. There was no significant difference between the SSDMC method and the external standard method. New SSDMC method could be considered as an ideal mean to analyze the components for which reference standards are not readily available. A method, single standard for determination of multicomponents (SSDMC), was established by high-performance liquid chromatography for the simultaneous determination of nine ginsenosides in Panax ginseng (ginsenoside Rg1, Re, Rf, Rg2, Rb1, Rc, Rb2, Rb3, Rd)Various chromatographic conditions were investigated to verify applicability of FsThe feasibility and accuracy of SSDMC were checked by the external standard method. Abbreviations used: DRT: Different value of retention time; F: Conversion factor; HPLC: High-performance Liquid Chromatography; LOD: Limit of detection; LOQ: Limit of quantitation; PD: Percent difference; PPD: 20(S)-protopanaxadiol; PPT: 20(S)-protopanaxatriol; RSD: Relative standard deviation; SSDMC: Single Standard for Determination of Multicomponents; TCM: Traditional Chinese Medicine.

  5. A proof for Rhiel's range estimator of the coefficient of variation for skewed distributions.

    PubMed

    Rhiel, G Steven

    2007-02-01

    In this research study is proof that the coefficient of variation (CV(high-low)) calculated from the highest and lowest values in a set of data is applicable to specific skewed distributions with varying means and standard deviations. Earlier Rhiel provided values for d(n), the standardized mean range, and a(n), an adjustment for bias in the range estimator of micro. These values are used in estimating the coefficient of variation from the range for skewed distributions. The d(n) and an values were specified for specific skewed distributions with a fixed mean and standard deviation. In this proof it is shown that the d(n) and an values are applicable for the specific skewed distributions when the mean and standard deviation can take on differing values. This will give the researcher confidence in using this statistic for skewed distributions regardless of the mean and standard deviation.

  6. Random errors in interferometry with the least-squares method

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang Qi

    2011-01-20

    This investigation analyzes random errors in interferometric surface profilers using the least-squares method when random noises are present. Two types of random noise are considered here: intensity noise and position noise. Two formulas have been derived for estimating the standard deviations of the surface height measurements: one is for estimating the standard deviation when only intensity noise is present, and the other is for estimating the standard deviation when only position noise is present. Measurements on simulated noisy interferometric data have been performed, and standard deviations of the simulated measurements have been compared with those theoretically derived. The relationships havemore » also been discussed between random error and the wavelength of the light source and between random error and the amplitude of the interference fringe.« less

  7. Search for gluinos in events with an isolated lepton, jets and missing transverse momentum at √{s} = 13 Te V with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Gonzalez, B. Alvarez; Piqueras, D. Álvarez; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Navarro, L. Barranco; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Basye, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Benitez, J.; Garcia, J. A. Benitez; Benjamin, D. P.; Bensinger, J. 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W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Araya, S. Tapia; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Kate, H. Ten; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Torres, R. E. Ticse; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tylmad, M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ueno, R.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Santurio, E. Valdes; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Vallecorsa, S.; Ferrer, J. A. Valls; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Nedden, M. zur; Zurzolo, G.; Zwalinski, L.

    2016-10-01

    The results of a search for gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a centre-of-mass energy of √{s} = 13 { Te V} are presented. The dataset used was recorded in 2015 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 3.2 fb^{-1}. Six signal selections are defined that best exploit the signal characteristics. The data agree with the Standard Model background expectation in all six signal selections, and the largest deviation is a 2.1 standard deviation excess. The results are interpreted in a simplified model where pair-produced gluinos decay via the lightest chargino to the lightest neutralino. In this model, gluinos are excluded up to masses of approximately 1.6 Te V depending on the mass spectrum of the simplified model, thus surpassing the limits of previous searches.

  8. The statistical treatment implemented to obtain the planetary protection bioburdens for the Mars Science Laboratory mission

    NASA Astrophysics Data System (ADS)

    Beaudet, Robert A.

    2013-06-01

    NASA Planetary Protection Policy requires that Category IV missions such as those going to the surface of Mars include detailed assessment and documentation of the bioburden on the spacecraft at launch. In the prior missions to Mars, the approaches used to estimate the bioburden could easily be conservative without penalizing the project because spacecraft elements such as the descent and landing stages had relatively small surface areas and volumes. With the advent of a large spacecraft such as Mars Science Laboratory (MSL), it became necessary for a modified—still conservative but more pragmatic—statistical treatment be used to obtain the standard deviations and the bioburden densities at about the 99.9% confidence limits. This article describes both the Gaussian and Poisson statistics that were implemented to analyze the bioburden data from the MSL spacecraft prior to launch. The standard deviations were weighted by the areas sampled with each swab or wipe. Some typical cases are given and discussed.

  9. Optimization of homonuclear 2D NMR for fast quantitative analysis: application to tropine-nortropine mixtures.

    PubMed

    Giraudeau, Patrick; Guignard, Nadia; Hillion, Emilie; Baguet, Evelyne; Akoka, Serge

    2007-03-12

    Quantitative analysis by (1)H NMR is often hampered by heavily overlapping signals that may occur for complex mixtures, especially those containing similar compounds. Bidimensional homonuclear NMR spectroscopy can overcome this difficulty. A thorough review of acquisition and post-processing parameters was carried out to obtain accurate and precise, quantitative 2D J-resolved and DQF-COSY spectra in a much reduced time, thus limiting the spectrometer instabilities in the course of time. The number of t(1) increments was reduced as much as possible, and standard deviation was improved by optimization of spectral width, number of transients, phase cycling and apodization function. Localized polynomial baseline corrections were applied to the relevant chemical shift areas. Our method was applied to tropine-nortropine mixtures. Quantitative J-resolved spectra were obtained in less than 3 min and quantitative DQF-COSY spectra in 12 min, with an accuracy of 3% for J-spectroscopy and 2% for DQF-COSY, and a standard deviation smaller than 1%.

  10. The production of calibration specimens for impact testing of subsize Charpy specimens

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Alexander, D.J.; Corwin, W.R.; Owings, T.D.

    1994-09-01

    Calibration specimens have been manufactured for checking the performance of a pendulum impact testing machine that has been configured for testing subsize specimens, both half-size (5.0 {times} 5.0 {times} 25.4 mm) and third-size (3.33 {times} 3.33 {times} 25.4 mm). Specimens were fabricated from quenched-and-tempered 4340 steel heat treated to produce different microstructures that would result in either high or low absorbed energy levels on testing. A large group of both half- and third-size specimens were tested at {minus}40{degrees}C. The results of the tests were analyzed for average value and standard deviation, and these values were used to establish calibration limitsmore » for the Charpy impact machine when testing subsize specimens. These average values plus or minus two standard deviations were set as the acceptable limits for the average of five tests for calibration of the impact testing machine.« less

  11. SU-F-I-47: Optimizing Protocols for Image Quality and Dose in Abdominal CT of Large Patients

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Johnson, L; Yester, M

    Purpose: Newer CT scanners are able to use scout views to adjust mA throughout the scan in order to achieve a given noise level. However, given constraints of radiologist preferences for kVp and rotation time, it may not be possible to achieve an acceptable noise level for large patients. A study was initiated to determine for which patients kVp and/or rotation time should be changed in order to achieve acceptable image quality. Methods: Patient scans were reviewed on two new Emergency Department scanners (Philips iCT) to identify patients over a large range of sizes. These iCTs were set with amore » limit of 500 mA to safeguard against a failure that might cause a CT scan to be (incorrectly) obtained at too-high mA. Scout views of these scans were assessed for both AP and LAT patient width and AP and LAT standard deviation in an ROI over the liver. Effective diameter and product of the scout standard deviations over the liver were both studied as possible metrics for identifying patients who would need kVp and/or rotation time changed. The mA used for the liver in the CT was compared to these metrics for those patients whose CT scans showed acceptable image quality. Results: Both effective diameter and product of the scout standard deviations over the liver result in similar predictions for which patients will require the kVp and/or rotation time to be changed to achieve an optimal combination of image quality and dose. Conclusion: Two mechanisms for CT technologists to determine based on scout characteristics what kVp, mA limit, and rotation time to use when DoseRight with our physicians’ preferred kVp and rotation time will not yield adequate image quality are described.« less

  12. Preparation of a novel sorptive stir bar based on vinylpyrrolidone-ethylene glycol dimethacrylate monolithic polymer for the simultaneous extraction of diazepam and nordazepam from human plasma.

    PubMed

    Torabizadeh, Mahsa; Talebpour, Zahra; Adib, Nuoshin; Aboul-Enein, Hassan Y

    2016-04-01

    A new monolithic coating based on vinylpyrrolidone-ethylene glycol dimethacrylate polymer was introduced for stir bar sorptive extraction. The polymerization step was performed using different contents of monomer, cross-linker and porogenic solvent, and the best formulation was selected. The quality of the prepared vinylpyrrolidone-ethylene glycol dimethacrylate stir bars was satisfactory, demonstrating good repeatability within batch (relative standard deviation < 3.5%) and acceptable reproducibility between batches (relative standard deviation < 6.0%). The prepared stir bar was utilized in combination with ultrasound-assisted liquid desorption, followed by high-performance liquid chromatography with ultraviolet detection for the simultaneous determination of diazepam and nordazepam in human plasma samples. To optimize the extraction step, a three-level, four-factor, three-block Box-Behnken design was applied. Under the optimum conditions, the analytical performance of the proposed method displayed excellent linear dynamic ranges for diazepam (36-1200 ng/mL) and nordazepam (25-1200 ng/mL), with correlation coefficients of 0.9986 and 0.9968 and detection limits of 12 and 10 ng/mL, respectively. The intra- and interday recovery ranged from 93 to 106%, and the relative standard deviations were less than 6%. Finally, the proposed method was successfully applied to the analysis of diazepam and nordazepam at their therapeutic levels in human plasma. The novelty of this study is the improved polarity of the stir bar coating and its application for the simultaneous extraction of diazepam and its active metabolite, nordazepam in human plasma sample. The method was more rapid than previously reported stir bar sorptive extraction techniques based on monolithic coatings, and exhibited lower detection limits in comparison with similar methods for the determination of diazepam and nordazepam in biological fluids. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Development of an accurate, sensitive, and robust isotope dilution laser ablation ICP-MS method for simultaneous multi-element analysis (chlorine, sulfur, and heavy metals) in coal samples.

    PubMed

    Boulyga, Sergei F; Heilmann, Jens; Prohaska, Thomas; Heumann, Klaus G

    2007-10-01

    A method for the direct multi-element determination of Cl, S, Hg, Pb, Cd, U, Br, Cr, Cu, Fe, and Zn in powdered coal samples has been developed by applying inductively coupled plasma isotope dilution mass spectrometry (ICP-IDMS) with laser-assisted introduction into the plasma. A sector-field ICP-MS with a mass resolution of 4,000 and a high-ablation rate laser ablation system provided significantly better sensitivity, detection limits, and accuracy compared to a conventional laser ablation system coupled with a quadrupole ICP-MS. The sensitivity ranges from about 590 cps for (35)Cl+ to more than 6 x 10(5) cps for (238)U+ for 1 microg of trace element per gram of coal sample. Detection limits vary from 450 ng g(-1) for chlorine and 18 ng g(-1) for sulfur to 9.5 pg g(-1) for mercury and 0.3 pg g(-1) for uranium. Analyses of minor and trace elements in four certified reference materials (BCR-180 Gas Coal, BCR-331 Steam Coal, SRM 1632c Trace Elements in Coal, SRM 1635 Trace Elements in Coal) yielded good agreement of usually not more than 5% deviation from the certified values and precisions of less than 10% relative standard deviation for most elements. Higher relative standard deviations were found for particular elements such as Hg and Cd caused by inhomogeneities due to associations of these elements within micro-inclusions in coal which was demonstrated for Hg in SRM 1635, SRM 1632c, and another standard reference material (SRM 2682b, Sulfur and Mercury in Coal). The developed LA-ICP-IDMS method with its simple sample pretreatment opens the possibility for accurate, fast, and highly sensitive determinations of environmentally critical contaminants in coal as well as of trace impurities in similar sample materials like graphite powder and activated charcoal on a routine basis.

  14. Longitudinal analysis on human cervical tissue using optical coherence tomography (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Gan, Yu; Yao, Wang; Myers, Kristin M.; Vink, Joy-Sarah Y.; Wapner, Ronald J.; Hendon, Christine P.

    2017-02-01

    Uterine cervical collagen fiber network is vital to the normal cervical function in pregnancy. Previously, we presented an orientation estimation method to enable dispersion analysis on a single axial slice of human cervical tissue obtained from the upper half of cervix using optical coherence tomography (OCT). How the collagen fiber network structure changes from the internal os (top of the cervix which meets the uterus) to external os (bottom of cervix which extends into the vagina), remains unknown due to depth penetration limitations of OCT. To establish a collagen fiber directionality "map" of the entire cervix, we imaged serial axial slices of human NP (n=11) and PG (n=2) cervical tissue obtained from the internal to external os using Institutional Review Board approved protocols at Columbia University Medical Center. Each slice was divided into four quadrants. In each quadrant, we stitched multiple overlapped OCT volumes and analyzed the en face images that were parallel to the surface. A pixel-wise directionality map was generated. We analyzed fiber trend by measuring the mean angles and quantified dispersion by calculating the standard deviation of the fiber direction over a region of 400 μm × 400 μm. For the initial four samples, our analysis confirms a circumferential fiber pattern in the outer region of slices at all depths. We found that the standard deviation close to internal os showed no significance to the standard deviation close to external os (p>0.05), indicating comparable dispersion.

  15. Excursions out-of-lane versus standard deviation of lateral position as outcome measure of the on-the-road driving test.

    PubMed

    Verster, Joris C; Roth, Thomas

    2014-07-01

    The traditional outcome measure of the Dutch on-the-road driving test is the standard deviation of lateral position (SDLP), the weaving of the car. This paper explores whether excursions out-of-lane are a suitable additional outcome measure to index driving impairment. A literature search was conducted to search for driving tests that used both SDLP and excursions out-of-lane as outcome measures. The analyses were limited to studies examining hypnotic drugs because several of these drugs have been shown to produce next-morning sedation. Standard deviation of lateral position was more sensitive in demonstrating driving impairment. In fact, solely relying on excursions out-of-lane as outcome measure incorrectly classifies approximately half of impaired drives as unimpaired. The frequency of excursions out-of-lane is determined by the mean lateral position within the right traffic lane. Defining driving impairment as having a ΔSDLP > 2.4 cm, half of the impaired driving tests (51.2%, 43/84) failed to produce excursions out-of-lane. Alternatively, 20.9% of driving tests with ΔSDLP < 2.4 cm (27/129) had at least one excursion out-of-lane. Excursions out-of-lane are neither a suitable measure to demonstrate driving impairment nor is this measure sufficiently sensitive to differentiate adequately between differences in magnitude of driving impairment. Copyright © 2014 John Wiley & Sons, Ltd.

  16. Task-oriented comparison of power spectral density estimation methods for quantifying acoustic attenuation in diagnostic ultrasound using a reference phantom method.

    PubMed

    Rosado-Mendez, Ivan M; Nam, Kibo; Hall, Timothy J; Zagzebski, James A

    2013-07-01

    Reported here is a phantom-based comparison of methods for determining the power spectral density (PSD) of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)= α0 f (β), was estimated using a reference phantom method. The power spectral density was estimated using the short-time Fourier transform (STFT), Welch's periodogram, and Thomson's multitaper technique, and performance was analyzed when limiting the size of the parameter-estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error (FE). For parameter estimation regions larger than ~34 pulse lengths (~1 cm for this experiment), an overall power-law FE of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here, the multitaper method reduced the standard deviation of the α0 and β estimates compared with those using the other techniques. The results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound methods.

  17. N2/O2/H2 Dual-Pump Cars: Validation Experiments

    NASA Technical Reports Server (NTRS)

    OByrne, S.; Danehy, P. M.; Cutler, A. D.

    2003-01-01

    The dual-pump coherent anti-Stokes Raman spectroscopy (CARS) method is used to measure temperature and the relative species densities of N2, O2 and H2 in two experiments. Average values and root-mean-square (RMS) deviations are determined. Mean temperature measurements in a furnace containing air between 300 and 1800 K agreed with thermocouple measurements within 26 K on average, while mean mole fractions agree to within 1.6 % of the expected value. The temperature measurement standard deviation averaged 64 K while the standard deviation of the species mole fractions averaged 7.8% for O2 and 3.8% for N2, based on 200 single-shot measurements. Preliminary measurements have also been performed in a flat-flame burner for fuel-lean and fuel-rich flames. Temperature standard deviations of 77 K were measured, and the ratios of H2 to N2 and O2 to N2 respectively had standard deviations from the mean value of 12.3% and 10% of the measured ratio.

  18. [Simultaneous determination of 15 polycyclic aromatic hydrocarbons in cigarette filter by gas chromatography-tandem mass spectrometry].

    PubMed

    Zhang, Xiaotao; Zhang, Li; Ruan, Yibin; Wang, Weiwei; Ji, Houwei; Wan, Qiang; Lin, Fucheng; Liu, Jian

    2017-10-08

    A method for the simultaneous determination of 15 polycyclic aromatic hydrocarbons in cigarette filter was developed by isotope internal standard combined with gas chromatography-tandem mass spectrometry. The cigarette filters were extracted with dichloromethane, and the extract was filtered with 0.22 μm organic phase membrane. The samples were isolated by DB-5MS column (30 m×0.25 mm, 0.25 μm) and detected using multiple reaction monitoring mode of electron impact source under positive ion mode. The linearities of the 15 polycyclic aromatic hydrocarbons (acenapthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, ben[ a ]anthracene, chrysene, benzo[ b ]fluoranthene, benzo[ k ]fluoranthene, benzo[ a ]pyrene, dibenzo[ a,h ]anthracene, benzo[ g,h,i ]perylene and indeno[1,2,3- c,d ]pyrene) were good, and the correlation coefficients ( R 2 ) ranged from 0.9914 to 0.9999. The average recoveries of the 15 polycyclic aromatic hydrocarbons were 81.6%-109.6% at low, middle and high spiked levels, and the relative standard deviations were less than 16%, except that the relative standard deviation of fluorene at the low spiked level was 19.2%. The limits of detection of the 15 polycyclic aromatic hydrocarbons were 0.02 to 0.24 ng/filter, and the limits of quantification were 0.04 to 0.80 ng/filter. The method is simple, rapid, accurate, sensitive and reproducible. It is suitable for the quantitative analysis of the 15 polycyclic aromatic hydrocarbons in cigarette filters.

  19. Determination of Wastewater Compounds in Whole Water by Continuous Liquid-Liquid Extraction and Capillary-Column Gas Chromatography/Mass Spectrometry

    USGS Publications Warehouse

    Zaugg, Steven D.; Smith, Steven G.; Schroeder, Michael P.

    2006-01-01

    A method for the determination of 69 compounds typically found in domestic and industrial wastewater is described. The method was developed in response to increasing concern over the impact of endocrine-disrupting chemicals on aquatic organisms in wastewater. This method also is useful for evaluating the effects of combined sanitary and storm-sewer overflow on the water quality of urban streams. The method focuses on the determination of compounds that are indicators of wastewater or have endocrine-disrupting potential. These compounds include the alkylphenol ethoxylate nonionic surfactants, food additives, fragrances, antioxidants, flame retardants, plasticizers, industrial solvents, disinfectants, fecal sterols, polycyclic aromatic hydrocarbons, and high-use domestic pesticides. Wastewater compounds in whole-water samples were extracted using continuous liquid-liquid extractors and methylene chloride solvent, and then determined by capillary-column gas chromatography/mass spectrometry. Recoveries in reagent-water samples fortified at 0.5 microgram per liter averaged 72 percent ? 8 percent relative standard deviation. The concentration of 21 compounds is always reported as estimated because method recovery was less than 60 percent, variability was greater than 25 percent relative standard deviation, or standard reference compounds were prepared from technical mixtures. Initial method detection limits averaged 0.18 microgram per liter. Samples were preserved by adding 60 grams of sodium chloride and stored at 4 degrees Celsius. The laboratory established a sample holding-time limit prior to sample extraction of 14 days from the date of collection.

  20. A framework for the meta-analysis of Bland-Altman studies based on a limits of agreement approach.

    PubMed

    Tipton, Elizabeth; Shuster, Jonathan

    2017-10-15

    Bland-Altman method comparison studies are common in the medical sciences and are used to compare a new measure to a gold-standard (often costlier or more invasive) measure. The distribution of these differences is summarized by two statistics, the 'bias' and standard deviation, and these measures are combined to provide estimates of the limits of agreement (LoA). When these LoA are within the bounds of clinically insignificant differences, the new non-invasive measure is preferred. Very often, multiple Bland-Altman studies have been conducted comparing the same two measures, and random-effects meta-analysis provides a means to pool these estimates. We provide a framework for the meta-analysis of Bland-Altman studies, including methods for estimating the LoA and measures of uncertainty (i.e., confidence intervals). Importantly, these LoA are likely to be wider than those typically reported in Bland-Altman meta-analyses. Frequently, Bland-Altman studies report results based on repeated measures designs but do not properly adjust for this design in the analysis. Meta-analyses of Bland-Altman studies frequently exclude these studies for this reason. We provide a meta-analytic approach that allows inclusion of estimates from these studies. This includes adjustments to the estimate of the standard deviation and a method for pooling the estimates based upon robust variance estimation. An example is included based on a previously published meta-analysis. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  1. Associations between environmental factors and hospital admissions for sickle cell disease

    PubMed Central

    Piel, Frédéric B.; Tewari, Sanjay; Brousse, Valentine; Analitis, Antonis; Font, Anna; Menzel, Stephan; Chakravorty, Subarna; Thein, Swee Lay; Inusa, Baba; Telfer, Paul; de Montalembert, Mariane; Fuller, Gary W.; Katsouyanni, Klea; Rees, David C.

    2017-01-01

    Sickle cell disease is an increasing global health burden. This inherited disease is characterized by a remarkable phenotypic heterogeneity, which can only partly be explained by genetic factors. Environmental factors are likely to play an important role but studies of their impact on disease severity are limited and their results are often inconsistent. This study investigated associations between a range of environmental factors and hospital admissions of young patients with sickle cell disease in London and in Paris between 2008 and 2012. Specific analyses were conducted for subgroups of patients with different genotypes and for the main reasons for admissions. Generalized additive models and distributed lag non-linear models were used to assess the magnitude of the associations and to calculate relative risks. Some environmental factors significantly influence the numbers of hospital admissions of children with sickle cell disease, although the associations identified are complicated. Our study suggests that meteorological factors are more likely to be associated with hospital admissions for sickle cell disease than air pollutants. It confirms previous reports of risks associated with wind speed (risk ratio: 1.06/standard deviation; 95% confidence interval: 1.00–1.12) and also with rainfall (1.06/standard deviation; 95% confidence interval: 1.01–1.12). Maximum atmospheric pressure was found to be a protective factor (0.93/standard deviation; 95% confidence interval: 0.88–0.99). Weak or no associations were found with temperature. Divergent associations were identified for different genotypes or reasons for admissions, which could partly explain the lack of consistency in earlier studies. Advice to patients with sickle cell disease usually includes avoiding a range of environmental conditions that are believed to trigger acute complications, including extreme temperatures and high altitudes. Scientific evidence to support such advice is limited and sometimes confusing. This study shows that environmental factors do explain some of the variations in rates of admission to hospital with acute symptoms in sickle cell disease, but the associations are complex, and likely to be specific to different environments and the individual’s exposure to them. Furthermore, this study highlights the need for prospective studies with large numbers of patients and standardized protocols across Europe. PMID:27909222

  2. Associations between environmental factors and hospital admissions for sickle cell disease.

    PubMed

    Piel, Frédéric B; Tewari, Sanjay; Brousse, Valentine; Analitis, Antonis; Font, Anna; Menzel, Stephan; Chakravorty, Subarna; Thein, Swee Lay; Inusa, Baba; Telfer, Paul; de Montalembert, Mariane; Fuller, Gary W; Katsouyanni, Klea; Rees, David C

    2017-04-01

    Sickle cell disease is an increasing global health burden. This inherited disease is characterized by a remarkable phenotypic heterogeneity, which can only partly be explained by genetic factors. Environmental factors are likely to play an important role but studies of their impact on disease severity are limited and their results are often inconsistent. This study investigated associations between a range of environmental factors and hospital admissions of young patients with sickle cell disease in London and in Paris between 2008 and 2012. Specific analyses were conducted for subgroups of patients with different genotypes and for the main reasons for admissions. Generalized additive models and distributed lag non-linear models were used to assess the magnitude of the associations and to calculate relative risks. Some environmental factors significantly influence the numbers of hospital admissions of children with sickle cell disease, although the associations identified are complicated. Our study suggests that meteorological factors are more likely to be associated with hospital admissions for sickle cell disease than air pollutants. It confirms previous reports of risks associated with wind speed (risk ratio: 1.06/standard deviation; 95% confidence interval: 1.00-1.12) and also with rainfall (1.06/standard deviation; 95% confidence interval: 1.01-1.12). Maximum atmospheric pressure was found to be a protective factor (0.93/standard deviation; 95% confidence interval: 0.88-0.99). Weak or no associations were found with temperature. Divergent associations were identified for different genotypes or reasons for admissions, which could partly explain the lack of consistency in earlier studies. Advice to patients with sickle cell disease usually includes avoiding a range of environmental conditions that are believed to trigger acute complications, including extreme temperatures and high altitudes. Scientific evidence to support such advice is limited and sometimes confusing. This study shows that environmental factors do explain some of the variations in rates of admission to hospital with acute symptoms in sickle cell disease, but the associations are complex, and likely to be specific to different environments and the individual's exposure to them. Furthermore, this study highlights the need for prospective studies with large numbers of patients and standardized protocols across Europe. Copyright© Ferrata Storti Foundation.

  3. Racking strength of walls : let-in corner bracing, sheet materials, and effect of loading rate

    Treesearch

    Roger L. Tuomi; David S. Gromala

    1977-01-01

    Determination of the racking strength of wails, which is a measure of a building system’s ability to resist wind loads, has generally been limited to performance testing. Although a standard test method exists, deviations have often been made in speed of testing and panel configuration. The purpose of this study was to determine the relative effect of some of these...

  4. A novel quadruplex real-time PCR method for simultaneous detection of Cry2Ae and two genetically modified cotton events (GHB119 and T304-40).

    PubMed

    Li, Xiang; Wang, Xiuxiu; Yang, Jielin; Liu, Yueming; He, Yuping; Pan, Liangwen

    2014-05-16

    To date, over 150 genetically modified (GM) crops are widely cultivated. To comply with regulations developed for genetically modified organisms (GMOs), including labeling policies, many detection methods for GMO identification and quantification have been developed. To detect the entrance and exit of unauthorized GM crop events in China, we developed a novel quadruplex real-time PCR method for simultaneous detection and quantification of GM cotton events GHB119 and T304-40 in cotton-derived products (based on the 5'-flanking sequence) and the insect-resistance gene Cry2Ae. The limit of detection was 10 copies for GHB119 and Cry2Ae and 25 copies for T304-40. The limit of quantification was 25 copies for GHB119 and Cry2Ae and 50 copies for T304-40. Moreover, low bias and acceptable standard deviation and relative standard deviation values were obtained in quantification analysis of six blind samples containing different GHB119 and T304-40 ingredients. The developed quadruplex quantitative method could be used for quantitative detection of two GM cotton events (GHB119 and T304-40) and Cry2Ae gene ingredient in cotton derived products.

  5. A novel quadruplex real-time PCR method for simultaneous detection of Cry2Ae and two genetically modified cotton events (GHB119 and T304-40)

    PubMed Central

    2014-01-01

    Background To date, over 150 genetically modified (GM) crops are widely cultivated. To comply with regulations developed for genetically modified organisms (GMOs), including labeling policies, many detection methods for GMO identification and quantification have been developed. Results To detect the entrance and exit of unauthorized GM crop events in China, we developed a novel quadruplex real-time PCR method for simultaneous detection and quantification of GM cotton events GHB119 and T304-40 in cotton-derived products (based on the 5′-flanking sequence) and the insect-resistance gene Cry2Ae. The limit of detection was 10 copies for GHB119 and Cry2Ae and 25 copies for T304-40. The limit of quantification was 25 copies for GHB119 and Cry2Ae and 50 copies for T304-40. Moreover, low bias and acceptable standard deviation and relative standard deviation values were obtained in quantification analysis of six blind samples containing different GHB119 and T304-40 ingredients. Conclusions The developed quadruplex quantitative method could be used for quantitative detection of two GM cotton events (GHB119 and T304-40) and Cry2Ae gene ingredient in cotton derived products. PMID:24884946

  6. 40 CFR 63.7190 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... period. (4) If there are no deviations from any emission limitations that apply to you, a statement that there were no deviations from the emission limitations during the reporting period and that no CMS was... malfunction. (d) For each deviation from an emission limitation that occurs at an affected source where you...

  7. 40 CFR 60.2220 - What must I include in the deviation report?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... § 60.2215, for any pollutant or parameter that deviated from the emission limitations or operating... section. (a) The calendar dates and times your unit deviated from the emission limitations or operating limit requirements. (b) The averaged and recorded data for those dates. (c) Durations and causes of each...

  8. Search for resonances in diphoton events at $$\\sqrt{s}=13 $$ TeV with the ATLAS detector

    DOE PAGES

    Aaboud, M.; Aad, G.; Abbott, B.; ...

    2016-09-01

    Searches for new resonances decaying into two photons in the ATLAS experiment at the CERN Large Hadron Collider are described. The analysis is based on proton-proton collision data corresponding to an integrated luminosity of 3.2 fb –1 at √s = 13 TeV recorded in 2015. Two searches are performed, one targeted at a spin-2 particle of mass larger than 500 GeV, using Randall-Sundrum graviton states as a benchmark model, and one optimized for a spin-0 particle of mass larger than 200 GeV. Varying both the mass and the decay width, the most significant deviation from the background-only hypothesis is observedmore » at a diphoton invariant mass around 750 GeV with local significances of 3.8 and 3.9 standard deviations in the searches optimized for a spin-2 and spin-0 particle, respectively. The global significances are estimated to be 2.1 standard deviations for both analyses. As a result, the consistency between the data collected at 13 TeV and 8 TeV is also evaluated. Limits on the production cross section times branching ratio to two photons for the two resonance types are reported.« less

  9. Comparative study of navigated versus freehand osteochondral graft transplantation of the knee.

    PubMed

    Koulalis, Dimitrios; Di Benedetto, Paolo; Citak, Mustafa; O'Loughlin, Padhraig; Pearle, Andrew D; Kendoff, Daniel O

    2009-04-01

    Osteochondral lesions are a common sports-related injury for which osteochondral grafting, including mosaicplasty, is an established treatment. Computer navigation has been gaining popularity in orthopaedic surgery to improve accuracy and precision. Navigation improves angle and depth matching during harvest and placement of osteochondral grafts compared with conventional freehand open technique. Controlled laboratory study. Three cadaveric knees were used. Reference markers were attached to the femur, tibia, and donor/recipient site guides. Fifteen osteochondral grafts were harvested and inserted into recipient sites with computer navigation, and 15 similar grafts were inserted freehand. The angles of graft removal and placement as well as surface congruity (graft depth) were calculated for each surgical group. The mean harvesting angle at the donor site using navigation was 4 degrees (standard deviation, 2.3 degrees ; range, 1 degrees -9 degrees ) versus 12 degrees (standard deviation, 5.5 degrees ; range, 5 degrees -24 degrees ) using freehand technique (P < .0001). The recipient plug removal angle using the navigated technique was 3.3 degrees (standard deviation, 2.1 degrees ; range, 0 degrees -9 degrees ) versus 10.7 degrees (standard deviation, 4.9 degrees ; range, 2 degrees -17 degrees ) in freehand (P < .0001). The mean navigated recipient plug placement angle was 3.6 degrees (standard deviation, 2.0 degrees ; range, 1 degrees -9 degrees ) versus 10.6 degrees (standard deviation, 4.4 degrees ; range, 3 degrees -17 degrees ) with freehand technique (P = .0001). The mean height of plug protrusion under navigation was 0.3 mm (standard deviation, 0.2 mm; range, 0-0.6 mm) versus 0.5 mm (standard deviation, 0.3 mm; range, 0.2-1.1 mm) using a freehand technique (P = .0034). Significantly greater accuracy and precision were observed in harvesting and placement of the osteochondral grafts in the navigated procedures. Clinical studies are needed to establish a benefit in vivo. Improvement in the osteochondral harvest and placement is desirable to optimize clinical outcomes. Navigation shows great potential to improve both harvest and placement precision and accuracy, thus optimizing ultimate surface congruity.

  10. Search for physics beyond the standard model in final states with a lepton and missing transverse energy in proton-proton collisions at $$\\sqrt{s}$$ = 8 TeV

    DOE PAGES

    Khachatryan, Vardan

    2015-05-22

    A search for new physics in proton-proton collisions having final states with an electron or muon and missing transverse energy is presented. The analysis uses data collected in 2012 with the CMS detector, at an LHC center-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of 19.7 fbmore » $$^{-1}$$. No significant deviation of the transverse mass distribution of the charged lepton-neutrino system from the standard model prediction is found. Mass exclusion limits of up to 3.28 TeV at a 95% confidence level for a W$$^{\\prime}$$ boson with the same couplings as that of the standard model W boson are determined. Results are also derived in the framework of split universal extra dimensions, and exclusion limits on Kaluza-Klein W$$^{(2)}_{{\\rm KK}}$$ states are found. The final state with large missing transverse energy also enables a search for dark matter production with a recoiling W boson, with limits set on the mass and the production cross section of potential candidates. Finally, limits are established for a model including interference between a left-handed W$$^{\\prime}$$ boson and the standard model W boson, and for a compositeness model.« less

  11. Effect of Nanoparticles on Modified Screen Printed Inhibition Superoxide Dismutase Electrodes for Aluminum

    PubMed Central

    Barquero-Quirós, Miriam; Arcos-Martínez, María Julia

    2016-01-01

    A novel amperometric biosensor for the determination of Al(III) based on the inhibition of the enzyme superoxide dismutase has been developed. The oxidation signal of epinephrine substrate was affected by the presence of Al(III) ions leading to a decrease in its amperometric current. The immobilization of the enzyme was performed with glutaraldehyde on screen-printed carbon electrodes modifiedwith tetrathiofulvalene (TTF) and different types ofnanoparticles. Nanoparticles of gold, platinum, rhodium and palladium were deposited on screen printed carbon electrodes by means of two electrochemical procedures. Nanoparticles were characterized trough scanning electronic microscopy, X-rays fluorescence, and atomic force microscopy. Palladium nanoparticles showed lower atomic force microscopy parameters and higher slope of aluminum calibration curves and were selected to perform sensor validation. The developed biosensor has a detection limit of 2.0 ± 0.2 μM for Al(III), with a reproducibility of 7.9% (n = 5). Recovery of standard reference material spiked to buffer solution was 103.8% with a relative standard deviation of 4.8% (n = 5). Recovery of tap water spiked with the standard reference material was 100.5 with a relative standard deviation of 3.4% (n = 3). The study of interfering ions has also been carried out. PMID:27681735

  12. 40 CFR 63.8693 - What reports must I submit and when?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... emission limitations (emission limit, operating limit, opacity limit, and visible emission limit) that apply to you, a statement that there were no deviations from the emission limitations during the... out-of-control during the reporting period. (d) For each deviation from an emission limitation...

  13. Matrix Summaries Improve Research Reports: Secondary Analyses Using Published Literature

    ERIC Educational Resources Information Center

    Zientek, Linda Reichwein; Thompson, Bruce

    2009-01-01

    Correlation matrices and standard deviations are the building blocks of many of the commonly conducted analyses in published research, and AERA and APA reporting standards recommend their inclusion when reporting research results. The authors argue that the inclusion of correlation/covariance matrices, standard deviations, and means can enhance…

  14. 30 CFR 74.8 - Measurement, accuracy, and reliability requirements.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... concentration, as defined by the relative standard deviation of the distribution of measurements. The relative standard deviation shall be less than 0.1275 without bias for both full-shift measurements of 8 hours or... Standards, Regulations, and Variances, 1100 Wilson Boulevard, Room 2350, Arlington, Virginia 22209-3939...

  15. Characterizing Accuracy and Precision of Glucose Sensors and Meters

    PubMed Central

    2014-01-01

    There is need for a method to describe precision and accuracy of glucose measurement as a smooth continuous function of glucose level rather than as a step function for a few discrete ranges of glucose. We propose and illustrate a method to generate a “Glucose Precision Profile” showing absolute relative deviation (ARD) and /or %CV versus glucose level to better characterize measurement errors at any glucose level. We examine the relationship between glucose measured by test and comparator methods using linear regression. We examine bias by plotting deviation = (test – comparator method) versus glucose level. We compute the deviation, absolute deviation (AD), ARD, and standard deviation (SD) for each data pair. We utilize curve smoothing procedures to minimize the effects of random sampling variability to facilitate identification and display of the underlying relationships between ARD or %CV and glucose level. AD, ARD, SD, and %CV display smooth continuous relationships versus glucose level. Estimates of MARD and %CV are subject to relatively large errors in the hypoglycemic range due in part to a markedly nonlinear relationship with glucose level and in part to the limited number of observations in the hypoglycemic range. The curvilinear relationships of ARD and %CV versus glucose level are helpful when characterizing and comparing the precision and accuracy of glucose sensors and meters. PMID:25037194

  16. 40 CFR 63.5555 - How do I demonstrate continuous compliance with the emission limits, operating limits, and work...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... periods of startup, shutdown, and malfunction. These instances are deviations from the emission limits...), deviations that occur during a period of startup, shutdown, or malfunction are not violations if you... Administrator will determine whether deviations that occur during a period you identify as a startup, shutdown...

  17. 40 CFR 63.5555 - How do I demonstrate continuous compliance with the emission limits, operating limits, and work...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... periods of startup, shutdown, and malfunction. These instances are deviations from the emission limits...), deviations that occur during a period of startup, shutdown, or malfunction are not violations if you... Administrator will determine whether deviations that occur during a period you identify as a startup, shutdown...

  18. 40 CFR 63.5555 - How do I demonstrate continuous compliance with the emission limits, operating limits, and work...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... periods of startup, shutdown, and malfunction. These instances are deviations from the emission limits...), deviations that occur during a period of startup, shutdown, or malfunction are not violations if you... Administrator will determine whether deviations that occur during a period you identify as a startup, shutdown...

  19. The effects of intranasal esketamine (84 mg) and oral mirtazapine (30 mg) on on-road driving performance: a double-blind, placebo-controlled study.

    PubMed

    van de Loo, Aurora J A E; Bervoets, Adriana C; Mooren, Loes; Bouwmeester, Noor H; Garssen, Johan; Zuiker, Rob; van Amerongen, Guido; van Gerven, Joop; Singh, Jaskaran; der Ark, Peter Van; Fedgchin, Maggie; Morrison, Randall; Wajs, Ewa; Verster, Joris C

    2017-11-01

    The purpose of this study is to evaluate the single dose effect of intranasal esketamine (84 mg) compared to placebo on on-road driving performance. Mirtazapine (oral, 30 mg) was used as a positive control, as this antidepressant drug is known to negatively affect driving performance. Twenty-six healthy volunteers aged 21 to 60 years were enrolled in this study. In the evening, 8 h after treatment administration, participants conducted the standardized 100-km on-road driving test. Primary outcome measure was the standard deviation of lateral position (SDLP), i.e., the weaving of the car. Mean lateral position, mean speed, and standard deviation of speed were secondary outcome measures. For SDLP, non-inferiority analyses were conducted, using +2.4 cm (relative to placebo) as a predefined non-inferiority margin for clinical relevant impairment. Twenty-four participants completed the study. No significant SDLP difference was found between esketamine and placebo (p = 0.7638), whereas the SDLP after mirtazapine was significantly higher when compared to placebo (p = 0.0001). The upper limit of the two-sided 95% confidence interval (CI) of the mean difference between esketamine and placebo was +0.86 cm, i.e., <+2.4 cm, thus demonstrating that esketamine was non-inferior to placebo. Non-inferiority could not be concluded for mirtazapine (+3.15 cm SDLP relative to placebo). No significant differences in mean speed, standard deviation of speed, and mean lateral position were observed between the active treatments and placebo. No significant difference in driving performance was observed 8 h after administering intranasal esketamine (84 mg) or placebo. In contrast, oral mirtazapine (30 mg) significantly impaired on road driving performance.

  20. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Khachatryan, Vardan

    A search for new physics in proton-proton collisions having final states with an electron or muon and missing transverse energy is presented. The analysis uses data collected in 2012 with the CMS detector, at an LHC center-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of 19.7 fbmore » $$^{-1}$$. No significant deviation of the transverse mass distribution of the charged lepton-neutrino system from the standard model prediction is found. Mass exclusion limits of up to 3.28 TeV at a 95% confidence level for a W$$^{\\prime}$$ boson with the same couplings as that of the standard model W boson are determined. Results are also derived in the framework of split universal extra dimensions, and exclusion limits on Kaluza-Klein W$$^{(2)}_{{\\rm KK}}$$ states are found. The final state with large missing transverse energy also enables a search for dark matter production with a recoiling W boson, with limits set on the mass and the production cross section of potential candidates. Finally, limits are established for a model including interference between a left-handed W$$^{\\prime}$$ boson and the standard model W boson, and for a compositeness model.« less

  1. The effects of auditory stimulation with music on heart rate variability in healthy women.

    PubMed

    Roque, Adriano L; Valenti, Vitor E; Guida, Heraldo L; Campos, Mônica F; Knap, André; Vanderlei, Luiz Carlos M; Ferreira, Lucas L; Ferreira, Celso; Abreu, Luiz Carlos de

    2013-07-01

    There are no data in the literature with regard to the acute effects of different styles of music on the geometric indices of heart rate variability. In this study, we evaluated the acute effects of relaxant baroque and excitatory heavy metal music on the geometric indices of heart rate variability in women. We conducted this study in 21 healthy women ranging in age from 18 to 35 years. We excluded persons with previous experience with musical instruments and persons who had an affinity for the song styles. We evaluated two groups: Group 1 (n = 21), who were exposed to relaxant classical baroque musical and excitatory heavy metal auditory stimulation; and Group 2 (n = 19), who were exposed to both styles of music and white noise auditory stimulation. Using earphones, the volunteers were exposed to baroque or heavy metal music for five minutes. After the first music exposure to baroque or heavy metal music, they remained at rest for five minutes; subsequently, they were re-exposed to the opposite music (70-80 dB). A different group of women were exposed to the same music styles plus white noise auditory stimulation (90 dB). The sequence of the songs was randomized for each individual. We analyzed the following indices: triangular index, triangular interpolation of RR intervals and Poincaré plot (standard deviation of instantaneous beat-by-beat variability, standard deviation of the long-term RR interval, standard deviation of instantaneous beat-by-beat variability and standard deviation of the long-term RR interval ratio), low frequency, high frequency, low frequency/high frequency ratio, standard deviation of all the normal RR intervals, root-mean square of differences between the adjacent normal RR intervals and the percentage of adjacent RR intervals with a difference of duration greater than 50 ms. Heart rate variability was recorded at rest for 10 minutes. The triangular index and the standard deviation of the long-term RR interval indices were reduced during exposure to both music styles in the first group and tended to decrease in the second group whereas the white noise exposure decreased the high frequency index. We observed no changes regarding the triangular interpolation of RR intervals, standard deviation of instantaneous beat-by-beat variability and standard deviation of instantaneous beat-by-beat variability/standard deviation in the long-term RR interval ratio. We suggest that relaxant baroque and excitatory heavy metal music slightly decrease global heart rate variability because of the equivalent sound level.

  2. The effects of auditory stimulation with music on heart rate variability in healthy women

    PubMed Central

    Roque, Adriano L.; Valenti, Vitor E.; Guida, Heraldo L.; Campos, Mônica F.; Knap, André; Vanderlei, Luiz Carlos M.; Ferreira, Lucas L.; Ferreira, Celso; de Abreu, Luiz Carlos

    2013-01-01

    OBJECTIVES: There are no data in the literature with regard to the acute effects of different styles of music on the geometric indices of heart rate variability. In this study, we evaluated the acute effects of relaxant baroque and excitatory heavy metal music on the geometric indices of heart rate variability in women. METHODS: We conducted this study in 21 healthy women ranging in age from 18 to 35 years. We excluded persons with previous experience with musical instruments and persons who had an affinity for the song styles. We evaluated two groups: Group 1 (n = 21), who were exposed to relaxant classical baroque musical and excitatory heavy metal auditory stimulation; and Group 2 (n = 19), who were exposed to both styles of music and white noise auditory stimulation. Using earphones, the volunteers were exposed to baroque or heavy metal music for five minutes. After the first music exposure to baroque or heavy metal music, they remained at rest for five minutes; subsequently, they were re-exposed to the opposite music (70-80 dB). A different group of women were exposed to the same music styles plus white noise auditory stimulation (90 dB). The sequence of the songs was randomized for each individual. We analyzed the following indices: triangular index, triangular interpolation of RR intervals and Poincaré plot (standard deviation of instantaneous beat-by-beat variability, standard deviation of the long-term RR interval, standard deviation of instantaneous beat-by-beat variability and standard deviation of the long-term RR interval ratio), low frequency, high frequency, low frequency/high frequency ratio, standard deviation of all the normal RR intervals, root-mean square of differences between the adjacent normal RR intervals and the percentage of adjacent RR intervals with a difference of duration greater than 50 ms. Heart rate variability was recorded at rest for 10 minutes. RESULTS: The triangular index and the standard deviation of the long-term RR interval indices were reduced during exposure to both music styles in the first group and tended to decrease in the second group whereas the white noise exposure decreased the high frequency index. We observed no changes regarding the triangular interpolation of RR intervals, standard deviation of instantaneous beat-by-beat variability and standard deviation of instantaneous beat-by-beat variability/standard deviation in the long-term RR interval ratio. CONCLUSION: We suggest that relaxant baroque and excitatory heavy metal music slightly decrease global heart rate variability because of the equivalent sound level. PMID:23917660

  3. Evaluation of scaling invariance embedded in short time series.

    PubMed

    Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

    2014-01-01

    Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length ~10(2). Calculations with specified Hurst exponent values of 0.2,0.3,...,0.9 show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias (≤0.03) and sharp confidential interval (standard deviation ≤0.05). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records.

  4. Evaluation of Scaling Invariance Embedded in Short Time Series

    PubMed Central

    Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

    2014-01-01

    Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length . Calculations with specified Hurst exponent values of show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias () and sharp confidential interval (standard deviation ). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records. PMID:25549356

  5. USL/DBMS NASA/PC R and D project C programming standards

    NASA Technical Reports Server (NTRS)

    Dominick, Wayne D. (Editor); Moreau, Dennis R.

    1984-01-01

    A set of programming standards intended to promote reliability, readability, and portability of C programs written for PC research and development projects is established. These standards must be adhered to except where reasons for deviation are clearly identified and approved by the PC team. Any approved deviation from these standards must also be clearly documented in the pertinent source code.

  6. Standard deviation index for stimulated Brillouin scattering suppression with different homogeneities.

    PubMed

    Ran, Yang; Su, Rongtao; Ma, Pengfei; Wang, Xiaolin; Zhou, Pu; Si, Lei

    2016-05-10

    We present a new quantitative index of standard deviation to measure the homogeneity of spectral lines in a fiber amplifier system so as to find the relation between the stimulated Brillouin scattering (SBS) threshold and the homogeneity of the corresponding spectral lines. A theoretical model is built and a simulation framework has been established to estimate the SBS threshold when input spectra with different homogeneities are set. In our experiment, by setting the phase modulation voltage to a constant value and the modulation frequency to different values, spectral lines with different homogeneities can be obtained. The experimental results show that the SBS threshold increases negatively with the standard deviation of the modulated spectrum, which is in good agreement with the theoretical results. When the phase modulation voltage is confined to 10 V and the modulation frequency is set to 80 MHz, the standard deviation of the modulated spectrum equals 0.0051, which is the lowest value in our experiment. Thus, at this time, the highest SBS threshold has been achieved. This standard deviation can be a good quantitative index in evaluating the power scaling potential in a fiber amplifier system, which is also a design guideline in suppressing the SBS to a better degree.

  7. Sensitive and rapid liquid chromatography/tandem mass spectrometric assay for the quantification of piperaquine in human plasma.

    PubMed

    Singhal, Puran; Gaur, Ashwani; Gautam, Anirudh; Varshney, Brijesh; Paliwal, Jyoti; Batra, Vijay

    2007-11-01

    A simple, sensitive and rapid liquid chromatography/tandem mass spectrometric (LC-MS/MS) method was developed and validated for quantification of piperaquine, an antimalarial drug, in human plasma using its structural analogue, piperazine bis chloroquinoline as internal standard (IS). The method involved a simple protein precipitation with methanol followed by rapid isocratic elution of analytes with 10mM ammonium acetate buffer/methanol/formic acid/ammonia solution (25/75/0.2/0.15, v/v) on Chromolith SpeedROD RP-18e reversed phase chromatographic column and quantification by mass spectrometry in the multiple reaction monitoring mode (MRM). The precursor to product ion transitions of m/z 535.3-->288.2 and m/z 409.1-->205.2 were used to measure the analyte and the IS, respectively. The assay exhibited a linear dynamic range of 1.0-250.2 ng/mL for piperaquine in plasma. The limit of detection (LOD) and lower limit of quantification (LLOQ) in plasma were 0.2 and 1.0 ng/mL, respectively. Acceptable precision and accuracy (+/-20% deviation for LLOQ standard and +/-15% deviation for other standards from the respective nominal concentration) were obtained for concentrations over the standard curve ranges. A run time of 2.5 min for a sample made it possible to achieve a throughput of more than 400 plasma samples analyzed per day. The validated method was successfully applied to analyze human plasma samples from phase-1 clinical studies. The mean pharmacokinetic parameters of piperaquine following 1000 mg oral dose: observed maximum plasma concentration (Cmax), time to maximum plasma concentration (Tmax) and elimination half-life (T1/2) were 46.1 ng/mL, 3.8h and 13 days, respectively.

  8. figure1.nc

    EPA Pesticide Factsheets

    NetCDF file of the SREF standard deviation of wind speed and direction that was used to inject variability in the FDDA input.variable U_NDG_OLD contains standard deviation of wind speed (m/s)variable V_NDG_OLD contains the standard deviation of wind direction (deg)This dataset is associated with the following publication:Gilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259–12,280, (2015).

  9. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aaltonen, Timo Antero

    In this study, a search for particles with the same mass and couplings as those of the standard model Higgs boson but different spin and parity quantum numbers is presented. We test two specific alternative Higgs boson hypotheses: a pseudoscalar Higgs boson with spin-parity J P = 0 – and a gravitonlike Higgs boson with J P = 2 +, assuming for both a mass of 125 GeV/c 2. We search for these exotic states produced in association with a vector boson and decaying into a bottom-antibottom quark pair. The vector boson is reconstructed through its decay into an electronmore » or muon pair, or an electron or muon and a neutrino, or it is inferred from an imbalance in total transverse momentum. We use expected kinematic differences between events containing exotic Higgs bosons and those containing standard model Higgs bosons. The data were collected by the CDF experiment at the Tevatron proton-antiproton collider, operating at a center-of-mass energy of √s = 1.96 TeV, and correspond to an integrated luminosity of 9.45 fb –1. We exclude deviations from the predictions of the standard model with a Higgs boson of mass 125 GeV/c 2 at the level of 5 standard deviations, assuming signal strengths for exotic boson production equal to the prediction for the standard model Higgs boson, and set upper limits of approximately 30% relative to the standard model rate on the possible rate of production of each exotic state.« less

  10. Probabilistic Modeling and Simulation of Metal Fatigue Life Prediction

    DTIC Science & Technology

    2002-09-01

    distribution demonstrate the central limit theorem? Obviously not! This is much the same as materials testing. If only NBA basketball stars are...60 near the exit of a NBA locker room. There would obviously be some pseudo-normal distribution with a very small standard deviation. The mean...completed, the investigators must understand how the midgets and the NBA stars will affect the total solution. D. IT IS MUCH SIMPLER TO MODEL THE

  11. 75 FR 67093 - Iceberg Water Deviating From Identity Standard; Temporary Permit for Market Testing

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-01

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2010-P-0517] Iceberg Water Deviating From Identity Standard; Temporary Permit for Market Testing AGENCY: Food and Drug... from the requirements of the standards of identity issued under section 401 of the Federal Food, Drug...

  12. 78 FR 2273 - Canned Tuna Deviating From Identity Standard; Temporary Permit for Market Testing

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-10

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2012-P-1189] Canned Tuna Deviating From Identity Standard; Temporary Permit for Market Testing AGENCY: Food and Drug... interstate shipment of experimental packs of food varying from the requirements of standards of identity...

  13. Upgraded FAA Airfield Capacity Model. Volume 2. Technical Description of Revisions

    DTIC Science & Technology

    1981-02-01

    the threshold t k a the time at which departure k is released FIGURE 3-1 TIME AXIS DIAGRAM OF SINGLE RUNWAY OPERATIONS 3-2 J"- SIGMAR the standard...standard deviation of the interarrival time. SIGMAR - the standard deviation of the arrival runway occupancy time. A-5 SINGLE - program subroutine for

  14. Methods of editing cloud and atmospheric layer affected pixels from satellite data

    NASA Technical Reports Server (NTRS)

    Nixon, P. R.; Wiegand, C. L.; Richardson, A. J.; Johnson, M. P. (Principal Investigator)

    1982-01-01

    Subvisible cirrus clouds (SCi) were easily distinguished in mid-infrared (MIR) TIROS-N daytime data from south Texas and northeast Mexico. The MIR (3.55-3.93 micrometer) pixel digital count means of the SCi affected areas were more than 3.5 standard deviations on the cold side of the scene means. (These standard deviations were made free of the effects of unusual instrument error by factoring out the Ch 3 MIR noise on the basis of detailed examination of noisy and noise-free pixels). SCi affected areas in the IR Ch 4 (10.5-11.5 micrometer) appeared cooler than the general scene, but were not as prominent as in Ch 3, being less than 2 standard deviations from the scene mean. Ch 3 and 4 standard deviations and coefficients of variation are not reliable indicators, by themselves, of the presence of SCi because land features can have similar statistical properties.

  15. 40 CFR 60.2958 - What must I include in the deviation report?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... limitations or operating limit requirements. (b) The averaged and recorded data for those dates. (c) Durations and causes of each deviation from the emission limitations or operating limits and your corrective... limitations or operating limits specified in this subpart, include the seven items described in paragraphs (a...

  16. 40 CFR 60.3053 - What must I include in the deviation report?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... limitations or operating limit requirements. (b) The averaged and recorded data for those dates. (c) Durations and causes of each deviation from the emission limitations or operating limits and your corrective... limitations or operating limits specified in this subpart, include the seven items described in paragraphs (a...

  17. A Taxonomy of Delivery and Documentation Deviations During Delivery of High-Fidelity Simulations.

    PubMed

    McIvor, William R; Banerjee, Arna; Boulet, John R; Bekhuis, Tanja; Tseytlin, Eugene; Torsher, Laurence; DeMaria, Samuel; Rask, John P; Shotwell, Matthew S; Burden, Amanda; Cooper, Jeffrey B; Gaba, David M; Levine, Adam; Park, Christine; Sinz, Elizabeth; Steadman, Randolph H; Weinger, Matthew B

    2017-02-01

    We developed a taxonomy of simulation delivery and documentation deviations noted during a multicenter, high-fidelity simulation trial that was conducted to assess practicing physicians' performance. Eight simulation centers sought to implement standardized scenarios over 2 years. Rules, guidelines, and detailed scenario scripts were established to facilitate reproducible scenario delivery; however, pilot trials revealed deviations from those rubrics. A taxonomy with hierarchically arranged terms that define a lack of standardization of simulation scenario delivery was then created to aid educators and researchers in assessing and describing their ability to reproducibly conduct simulations. Thirty-six types of delivery or documentation deviations were identified from the scenario scripts and study rules. Using a Delphi technique and open card sorting, simulation experts formulated a taxonomy of high-fidelity simulation execution and documentation deviations. The taxonomy was iteratively refined and then tested by 2 investigators not involved with its development. The taxonomy has 2 main classes, simulation center deviation and participant deviation, which are further subdivided into as many as 6 subclasses. Inter-rater classification agreement using the taxonomy was 74% or greater for each of the 7 levels of its hierarchy. Cohen kappa calculations confirmed substantial agreement beyond that expected by chance. All deviations were classified within the taxonomy. This is a useful taxonomy that standardizes terms for simulation delivery and documentation deviations, facilitates quality assurance in scenario delivery, and enables quantification of the impact of deviations upon simulation-based performance assessment.

  18. Simulation-based estimation of mean and standard deviation for meta-analysis via Approximate Bayesian Computation (ABC).

    PubMed

    Kwon, Deukwoo; Reis, Isildinha M

    2015-08-12

    When conducting a meta-analysis of a continuous outcome, estimated means and standard deviations from the selected studies are required in order to obtain an overall estimate of the mean effect and its confidence interval. If these quantities are not directly reported in the publications, they must be estimated from other reported summary statistics, such as the median, the minimum, the maximum, and quartiles. We propose a simulation-based estimation approach using the Approximate Bayesian Computation (ABC) technique for estimating mean and standard deviation based on various sets of summary statistics found in published studies. We conduct a simulation study to compare the proposed ABC method with the existing methods of Hozo et al. (2005), Bland (2015), and Wan et al. (2014). In the estimation of the standard deviation, our ABC method performs better than the other methods when data are generated from skewed or heavy-tailed distributions. The corresponding average relative error (ARE) approaches zero as sample size increases. In data generated from the normal distribution, our ABC performs well. However, the Wan et al. method is best for estimating standard deviation under normal distribution. In the estimation of the mean, our ABC method is best regardless of assumed distribution. ABC is a flexible method for estimating the study-specific mean and standard deviation for meta-analysis, especially with underlying skewed or heavy-tailed distributions. The ABC method can be applied using other reported summary statistics such as the posterior mean and 95 % credible interval when Bayesian analysis has been employed.

  19. On Teaching about the Coefficient of Variation in Introductory Statistics Courses

    ERIC Educational Resources Information Center

    Trafimow, David

    2014-01-01

    The standard deviation is related to the mean by virtue of the coefficient of variation. Teachers of statistics courses can make use of that fact to make the standard deviation more comprehensible for statistics students.

  20. INFLUENCE OF THE GALACTIC GRAVITATIONAL FIELD ON THE POSITIONAL ACCURACY OF EXTRAGALACTIC SOURCES

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Larchenkova, Tatiana I.; Lutovinov, Alexander A.; Lyskova, Natalya S.

    We investigate the influence of random variations of the Galactic gravitational field on the apparent celestial positions of extragalactic sources. The basic statistical characteristics of a stochastic process (first-order moments, an autocorrelation function and a power spectral density) are used to describe a light ray deflection in a gravitational field of randomly moving point masses as a function of the source coordinates. We map a 2D distribution of the standard deviation of the angular shifts in positions of distant sources (including reference sources of the International Celestial Reference Frame) with respect to their true positions. For different Galactic matter distributionsmore » the standard deviation of the offset angle can reach several tens of μ as (microarcsecond) toward the Galactic center, decreasing down to 4–6 μ as at high galactic latitudes. The conditional standard deviation (“jitter”) of 2.5 μ as is reached within 10 years at high galactic latitudes and within a few months toward the inner part of the Galaxy. The photometric microlensing events are not expected to be disturbed by astrometric random variations anywhere except the inner part of the Galaxy as the Einstein–Chvolson times are typically much shorter than the jittering timescale. While a jitter of a single reference source can be up to dozens of μ as over some reasonable observational time, using a sample of reference sources would reduce the error in relative astrometry. The obtained results can be used for estimating the physical upper limits on the time-dependent accuracy of astrometric measurements.« less

  1. 40 CFR 63.3120 - What reports must I submit?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... deviation. (8) Deviations: separate electrodeposition primer bake oven capture and control limitations. If you used the separate electrodeposition primer bake oven capture and control limitations in § 63.3092... dates of each month during which there was a deviation from the separate electrodeposition primer bake...

  2. 40 CFR 63.3120 - What reports must I submit?

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... deviation. (8) Deviations: separate electrodeposition primer bake oven capture and control limitations. If you used the separate electrodeposition primer bake oven capture and control limitations in § 63.3092... dates of each month during which there was a deviation from the separate electrodeposition primer bake...

  3. 40 CFR 63.3120 - What reports must I submit?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... deviation. (8) Deviations: separate electrodeposition primer bake oven capture and control limitations. If you used the separate electrodeposition primer bake oven capture and control limitations in § 63.3092... dates of each month during which there was a deviation from the separate electrodeposition primer bake...

  4. 40 CFR 63.3120 - What reports must I submit?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... deviation. (8) Deviations: separate electrodeposition primer bake oven capture and control limitations. If you used the separate electrodeposition primer bake oven capture and control limitations in § 63.3092... dates of each month during which there was a deviation from the separate electrodeposition primer bake...

  5. 40 CFR 63.3120 - What reports must I submit?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... deviation. (8) Deviations: separate electrodeposition primer bake oven capture and control limitations. If you used the separate electrodeposition primer bake oven capture and control limitations in § 63.3092... dates of each month during which there was a deviation from the separate electrodeposition primer bake...

  6. [Simultaneous determination of delta-9-tetrahydrocannabinol cannabidiol and cannabinol in edible oil using ultra performance liquid chromatography-tandem mass spectrometry].

    PubMed

    Zhang, Aizhi; Wang, Quanlin; Mo, Shijie

    2010-11-01

    A method for the simultaneous determination of delta-9-tetrahydrocannabinol (THC), cannabidiol (CBD) and cannabinol (CBN) in edible oil was developed using ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The target compounds were extracted with methanol, purified by an LC-Alumina-N solid phase extraction cartridge, separated and detected by the UPLC-MS/MS. Quantitative analysis was corrected by an isotope internal standard method using delta-9-THC-D3 as internal standard. Average recoveries for the target compounds varied from 68.0% to 101.6% with the relative standard deviations ranging from 7.0% to 20.1% at three spiked levels. The limits of detection (LOD) of the method were from 0.06-0.17 microg/kg and the limits of quantification (LOQ) were in the range of 0.20-0.52 microg/kg. The results showed that the method is able to meet the requirements for the simultaneous determination of THC, CBD and CBN in edible oil.

  7. Search for nonstandard neutrino interactions with IceCube DeepCore

    NASA Astrophysics Data System (ADS)

    Aartsen, M. G.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Ahrens, M.; Al Samarai, I.; Altmann, D.; Andeen, K.; Anderson, T.; Ansseau, I.; Anton, G.; Argüelles, C.; Auffenberg, J.; Axani, S.; Bagherpour, H.; Bai, X.; Barron, J. P.; Barwick, S. W.; Baum, V.; Bay, R.; Beatty, J. J.; Becker Tjus, J.; Becker, K.-H.; BenZvi, S.; Berley, D.; Bernardini, E.; Besson, D. Z.; Binder, G.; Bindig, D.; Blaufuss, E.; Blot, S.; Bohm, C.; Börner, M.; Bos, F.; Bose, D.; Böser, S.; Botner, O.; Bourbeau, E.; Bourbeau, J.; Bradascio, F.; Braun, J.; Brayeur, L.; Brenzke, M.; Bretz, H.-P.; Bron, S.; Brostean-Kaiser, J.; Burgman, A.; Carver, T.; Casey, J.; Casier, M.; Cheung, E.; Chirkin, D.; Christov, A.; Clark, K.; Classen, L.; Coenders, S.; Collin, G. H.; Conrad, J. M.; Cowen, D. F.; Cross, R.; Day, M.; de André, J. P. A. M.; De Clercq, C.; DeLaunay, J. J.; Dembinski, H.; De Ridder, S.; Desiati, P.; de Vries, K. D.; de Wasseige, G.; de With, M.; DeYoung, T.; Díaz-Vélez, J. C.; di Lorenzo, V.; Dujmovic, H.; Dumm, J. P.; Dunkman, M.; Dvorak, E.; Eberhardt, B.; Ehrhardt, T.; Eichmann, B.; Eller, P.; Evenson, P. A.; Fahey, S.; Fazely, A. R.; Felde, J.; Filimonov, K.; Finley, C.; Flis, S.; Franckowiak, A.; Friedman, E.; Fuchs, T.; Gaisser, T. K.; Gallagher, J.; Gerhardt, L.; Ghorbani, K.; Giang, W.; Glauch, T.; Glüsenkamp, T.; Goldschmidt, A.; Gonzalez, J. G.; Grant, D.; Griffith, Z.; Haack, C.; Hallgren, A.; Halzen, F.; Hanson, K.; Hebecker, D.; Heereman, D.; Helbing, K.; Hellauer, R.; Hickford, S.; Hignight, J.; Hill, G. C.; Hoffman, K. D.; Hoffmann, R.; Hokanson-Fasig, B.; Hoshina, K.; Huang, F.; Huber, M.; Hultqvist, K.; Hünnefeld, M.; In, S.; Ishihara, A.; Jacobi, E.; Japaridze, G. S.; Jeong, M.; Jero, K.; Jones, B. J. P.; Kalaczynski, P.; Kang, W.; Kappes, A.; Karg, T.; Karle, A.; Katz, U.; Kauer, M.; Keivani, A.; Kelley, J. L.; Kheirandish, A.; Kim, J.; Kim, M.; Kintscher, T.; Kirby, C.; Kiryluk, J.; Kittler, T.; Klein, S. R.; Kohnen, G.; Koirala, R.; Kolanoski, H.; Köpke, L.; Kopper, C.; Kopper, S.; Koschinsky, J. P.; Koskinen, D. J.; Kowalski, M.; Krings, K.; Kroll, M.; Krückl, G.; Kunnen, J.; Kunwar, S.; Kurahashi, N.; Kuwabara, T.; Kyriacou, A.; Labare, M.; Lanfranchi, J. L.; Larson, M. J.; Lauber, F.; Lennarz, D.; Lesiak-Bzdak, M.; Leuermann, M.; Liu, Q. R.; Lu, L.; Lünemann, J.; Luszczak, W.; Madsen, J.; Maggi, G.; Mahn, K. B. M.; Mancina, S.; Maruyama, R.; Mase, K.; Maunu, R.; McNally, F.; Meagher, K.; Medici, M.; Meier, M.; Menne, T.; Merino, G.; Meures, T.; Miarecki, S.; Micallef, J.; Momenté, G.; Montaruli, T.; Moore, R. W.; Moulai, M.; Nahnhauer, R.; Nakarmi, P.; Naumann, U.; Neer, G.; Niederhausen, H.; Nowicki, S. C.; Nygren, D. R.; Obertacke Pollmann, A.; Olivas, A.; O'Murchadha, A.; Palczewski, T.; Pandya, H.; Pankova, D. V.; Peiffer, P.; Pepper, J. A.; Pérez de los Heros, C.; Pieloth, D.; Pinat, E.; Plum, M.; Price, P. B.; Przybylski, G. T.; Raab, C.; Rädel, L.; Rameez, M.; Rawlins, K.; Rea, I. C.; Reimann, R.; Relethford, B.; Relich, M.; Resconi, E.; Rhode, W.; Richman, M.; Robertson, S.; Rongen, M.; Rott, C.; Ruhe, T.; Ryckbosch, D.; Rysewyk, D.; Sälzer, T.; Sanchez Herrera, S. E.; Sandrock, A.; Sandroos, J.; Santander, M.; Sarkar, S.; Sarkar, S.; Satalecka, K.; Schlunder, P.; Schmidt, T.; Schneider, A.; Schoenen, S.; Schöneberg, S.; Schumacher, L.; Seckel, D.; Seunarine, S.; Soedingrekso, J.; Soldin, D.; Song, M.; Spiczak, G. M.; Spiering, C.; Stachurska, J.; Stamatikos, M.; Stanev, T.; Stasik, A.; Stettner, J.; Steuer, A.; Stezelberger, T.; Stokstad, R. G.; Stößl, A.; Strotjohann, N. L.; Stuttard, T.; Sullivan, G. W.; Sutherland, M.; Taboada, I.; Tatar, J.; Tenholt, F.; Ter-Antonyan, S.; Terliuk, A.; Tešić, G.; Tilav, S.; Toale, P. A.; Tobin, M. N.; Toscano, S.; Tosi, D.; Tselengidou, M.; Tung, C. F.; Turcati, A.; Turley, C. F.; Ty, B.; Unger, E.; Usner, M.; Vandenbroucke, J.; Van Driessche, W.; van Eijndhoven, N.; Vanheule, S.; van Santen, J.; Vehring, M.; Vogel, E.; Vraeghe, M.; Walck, C.; Wallace, A.; Wallraff, M.; Wandler, F. D.; Wandkowsky, N.; Waza, A.; Weaver, C.; Weiss, M. J.; Wendt, C.; Werthebach, J.; Westerhoff, S.; Whelan, B. J.; Wiebe, K.; Wiebusch, C. H.; Wille, L.; Williams, D. R.; Wills, L.; Wolf, M.; Wood, J.; Wood, T. R.; Woolsey, E.; Woschnagg, K.; Xu, D. L.; Xu, X. W.; Xu, Y.; Yanez, J. P.; Yodh, G.; Yoshida, S.; Yuan, T.; Zoll, M.; IceCube Collaboration

    2018-04-01

    As atmospheric neutrinos propagate through the Earth, vacuumlike oscillations are modified by Standard Model neutral- and charged-current interactions with electrons. Theories beyond the Standard Model introduce heavy, TeV-scale bosons that can produce nonstandard neutrino interactions. These additional interactions may modify the Standard Model matter effect producing a measurable deviation from the prediction for atmospheric neutrino oscillations. The result described in this paper constrains nonstandard interaction parameters, building upon a previous analysis of atmospheric muon-neutrino disappearance with three years of IceCube DeepCore data. The best fit for the muon to tau flavor changing term is ɛμ τ=-0.0005 , with a 90% C.L. allowed range of -0.0067 <ɛμ τ<0.0081 . This result is more restrictive than recent limits from other experiments for ɛμ τ. Furthermore, our result is complementary to a recent constraint on ɛμ τ using another publicly available IceCube high-energy event selection. Together, they constitute the world's best limits on nonstandard interactions in the μ -τ sector.

  8. [Determination of trace gallium by graphite furnace atomic absorption spectrometry in urine].

    PubMed

    Zhou, L Z; Fu, S; Gao, S Q; He, G W

    2016-06-20

    To establish a method for determination trace gallium in urine by graphite furnace atomic absorption spectrometry (GFAAS). The ammonium dihydrogen phosphate was matrix modifier. The temperature effect about pyrolysis (Tpyr) and atomization temperature were optimized for determination of trace gallium. The method of technical standard about within-run, between-run and recoveries of standard were optimized. The method showed a linear relationship within the range of 0.20~80.00 μg/L (r=0.998). The within-run and between-run relative standard deviations (RSD) of repetitive measurement at 5.0, 10.0, 20.0 μg/L concentration levels were 2.1%~5.5% and 2.3%~3.0%. The detection limit was 0.06 μg/L. The recoveries of gallium were 98.2%~101.1%. This method is simple, low detection limit, accurate, reliable and reproducible. It has been applied for determination of trace gallium in urine samples those who need occupation health examination or poisoning diagnosis.

  9. SU-C-BRD-03: Analysis of Accelerator Generated Text Logs for Preemptive Maintenance

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Able, CM; Baydush, AH; Nguyen, C

    2014-06-15

    Purpose: To develop a model to analyze medical accelerator generated parameter and performance data that will provide an early warning of performance degradation and impending component failure. Methods: A robust 6 MV VMAT quality assurance treatment delivery was used to test the constancy of accelerator performance. The generated text log files were decoded and analyzed using statistical process control (SPC) methodology. The text file data is a single snapshot of energy specific and overall systems parameters. A total of 36 system parameters were monitored which include RF generation, electron gun control, energy control, beam uniformity control, DC voltage generation, andmore » cooling systems. The parameters were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and the parameter/system specification. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: the value of 1 standard deviation from the mean operating parameter of 483 TB systems, a small fraction (≤ 5%) of the operating range, or a fraction of the minor fault deviation. Results: There were 34 parameters in which synthetic errors were introduced. There were 2 parameters (radial position steering coil, and positive 24V DC) in which the errors did not exceed the limit of the I/MR chart. The I chart limit was exceeded for all of the remaining parameters (94.2%). The MR chart limit was exceeded in 29 of the 32 parameters (85.3%) in which the I chart limit was exceeded. Conclusion: Statistical process control I/MR evaluation of text log file parameters may be effective in providing an early warning of performance degradation or component failure for digital medical accelerator systems. Research is Supported by Varian Medical Systems, Inc.« less

  10. A SIMPLE METHOD FOR EVALUATING DATA FROM AN INTERLABORATORY STUDY

    EPA Science Inventory

    Large-scale laboratory-and method-performance studies involving more than about 30 laboratories may be evaluated by calculating the HORRAT ratio for each test sample (HORRAT=[experimentally found among-laboratories relative standard deviation] divided by [relative standard deviat...

  11. Limited School Drinking Water Access for Youth.

    PubMed

    Kenney, Erica L; Gortmaker, Steven L; Cohen, Juliana F W; Rimm, Eric B; Cradock, Angie L

    2016-07-01

    Providing children and youth with safe, adequate drinking water access during school is essential for health. This study used objectively measured data to investigate the extent to which schools provide drinking water access that meets state and federal policies. We visited 59 middle and high schools in Massachusetts during spring 2012. Trained research assistants documented the type, location, and working condition of all water access points throughout each school building using a standard protocol. School food service directors (FSDs) completed surveys reporting water access in cafeterias. We evaluated school compliance with state plumbing codes and federal regulations and compared FSD self-reports of water access with direct observation; data were analyzed in 2014. On average, each school had 1.5 (standard deviation: .6) water sources per 75 students; 82% (standard deviation: 20) were functioning and fewer (70%) were both clean and functioning. Less than half of the schools met the federal Healthy Hunger-Free Kids Act requirement for free water access during lunch; 18 schools (31%) provided bottled water for purchase but no free water. Slightly over half (59%) met the Massachusetts state plumbing code. FSDs overestimated free drinking water access compared to direct observation (96% FSD reported vs. 48% observed, kappa = .07, p = .17). School drinking water access may be limited. In this study, many schools did not meet state or federal policies for minimum student drinking water access. School administrative staff may not accurately report water access. Public health action is needed to increase school drinking water access. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  12. Histogram-based quantitative evaluation of endobronchial ultrasonography images of peripheral pulmonary lesion.

    PubMed

    Morikawa, Kei; Kurimoto, Noriaki; Inoue, Takeo; Mineshita, Masamichi; Miyazawa, Teruomi

    2015-01-01

    Endobronchial ultrasonography using a guide sheath (EBUS-GS) is an increasingly common bronchoscopic technique, but currently, no methods have been established to quantitatively evaluate EBUS images of peripheral pulmonary lesions. The purpose of this study was to evaluate whether histogram data collected from EBUS-GS images can contribute to the diagnosis of lung cancer. Histogram-based analyses focusing on the brightness of EBUS images were retrospectively conducted: 60 patients (38 lung cancer; 22 inflammatory diseases), with clear EBUS images were included. For each patient, a 400-pixel region of interest was selected, typically located at a 3- to 5-mm radius from the probe, from recorded EBUS images during bronchoscopy. Histogram height, width, height/width ratio, standard deviation, kurtosis and skewness were investigated as diagnostic indicators. Median histogram height, width, height/width ratio and standard deviation were significantly different between lung cancer and benign lesions (all p < 0.01). With a cutoff value for standard deviation of 10.5, lung cancer could be diagnosed with an accuracy of 81.7%. Other characteristics investigated were inferior when compared to histogram standard deviation. Histogram standard deviation appears to be the most useful characteristic for diagnosing lung cancer using EBUS images. © 2015 S. Karger AG, Basel.

  13. Statistical models for estimating daily streamflow in Michigan

    USGS Publications Warehouse

    Holtschlag, D.J.; Salehi, Habib

    1992-01-01

    Statistical models for estimating daily streamflow were analyzed for 25 pairs of streamflow-gaging stations in Michigan. Stations were paired by randomly choosing a station operated in 1989 at which 10 or more years of continuous flow data had been collected and at which flow is virtually unregulated; a nearby station was chosen where flow characteristics are similar. Streamflow data from the 25 randomly selected stations were used as the response variables; streamflow data at the nearby stations were used to generate a set of explanatory variables. Ordinary-least squares regression (OLSR) equations, autoregressive integrated moving-average (ARIMA) equations, and transfer function-noise (TFN) equations were developed to estimate the log transform of flow for the 25 randomly selected stations. The precision of each type of equation was evaluated on the basis of the standard deviation of the estimation errors. OLSR equations produce one set of estimation errors; ARIMA and TFN models each produce l sets of estimation errors corresponding to the forecast lead. The lead-l forecast is the estimate of flow l days ahead of the most recent streamflow used as a response variable in the estimation. In this analysis, the standard deviation of lead l ARIMA and TFN forecast errors were generally lower than the standard deviation of OLSR errors for l < 2 days and l < 9 days, respectively. Composite estimates were computed as a weighted average of forecasts based on TFN equations and backcasts (forecasts of the reverse-ordered series) based on ARIMA equations. The standard deviation of composite errors varied throughout the length of the estimation interval and generally was at maximum near the center of the interval. For comparison with OLSR errors, the mean standard deviation of composite errors were computed for intervals of length 1 to 40 days. The mean standard deviation of length-l composite errors were generally less than the standard deviation of the OLSR errors for l < 32 days. In addition, the composite estimates ensure a gradual transition between periods of estimated and measured flows. Model performance among stations of differing model error magnitudes were compared by computing ratios of the mean standard deviation of the length l composite errors to the standard deviation of OLSR errors. The mean error ratio for the set of 25 selected stations was less than 1 for intervals l < 32 days. Considering the frequency characteristics of the length of intervals of estimated record in Michigan, the effective mean error ratio for intervals < 30 days was 0.52. Thus, for intervals of estimation of 1 month or less, the error of the composite estimate is substantially lower than error of the OLSR estimate.

  14. Odor measurements according to EN 13725: A statistical analysis of variance components

    NASA Astrophysics Data System (ADS)

    Klarenbeek, Johannes V.; Ogink, Nico W. M.; van der Voet, Hilko

    2014-04-01

    In Europe, dynamic olfactometry, as described by the European standard EN 13725, has become the preferred method for evaluating odor emissions emanating from industrial and agricultural sources. Key elements of this standard are the quality criteria for trueness and precision (repeatability). Both are linked to standard values of n-butanol in nitrogen. It is assumed in this standard that whenever a laboratory complies with the overall sensory quality criteria for n-butanol, the quality level is transferable to other, environmental, odors. Although olfactometry is well established, little has been done to investigate inter laboratory variance (reproducibility). Therefore, the objective of this study was to estimate the reproducibility of odor laboratories complying with EN 13725 as well as to investigate the transferability of n-butanol quality criteria to other odorants. Based upon the statistical analysis of 412 odor measurements on 33 sources, distributed in 10 proficiency tests, it was established that laboratory, panel and panel session are components of variance that significantly differ between n-butanol and other odorants (α = 0.05). This finding does not support the transferability of the quality criteria, as determined on n-butanol, to other odorants and as such is a cause for reconsideration of the present single reference odorant as laid down in EN 13725. In case of non-butanol odorants, repeatability standard deviation (sr) and reproducibility standard deviation (sR) were calculated to be 0.108 and 0.282 respectively (log base-10). The latter implies that the difference between two consecutive single measurements, performed on the same testing material by two or more laboratories under reproducibility conditions, will not be larger than a factor 6.3 in 95% of cases. As far as n-butanol odorants are concerned, it was found that the present repeatability standard deviation (sr = 0.108) compares favorably to that of EN 13725 (sr = 0.172). It is therefore suggested that the repeatability limit (r), as laid down in EN 13725, can be reduced from r ≤ 0.477 to r ≤ 0.31.

  15. Search for an invisibly decaying Higgs boson or dark matter candidates produced in association with a Z boson in pp collisions at √{ s } = 13 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Bakker, P. J.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertram, I. A.; Bertsche, C.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Bethani, A.; Bethke, S.; Betti, A.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozson, A. J.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Braren, F.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Bruno, S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cai, H.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Casadei, D.; Casado, M. P.; Casha, A. F.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, Y. S.; Christodoulou, V.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Eramo, L.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vasconcelos Corga, K.; de Vivie de Regie, J. B.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Bello, F. A.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Petrillo, K. F.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Dodsworth, D.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubinin, F.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dulsen, C.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duperrin, A.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Ennis, J. S.; Epland, M. B.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giangiacomi, N.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugliarelli, G.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; Gonski, J. L.; González de La Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Grabowska-Bold, I.; Gradin, P. O. J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Grummer, A.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gurbuz, S.; Gustavino, G.; Gutelman, B. J.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Handl, D. M.; Haney, B.; Hanke, P.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrison, P. F.; Hartmann, N. M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heer, S.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herr, H.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; Hildebrand, K.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hils, M.; Hinchliffe, I.; Hirose, M.; Hirschbuehl, D.; Hiti, B.; Hladik, O.; Hlaluku, D. R.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hostiuc, A.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hrdinka, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Huhtinen, M.; Hunter, R. F. H.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Hyneman, R.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Iltzsche, F.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Isacson, M. F.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, P.; Jacobs, R. M.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. 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A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, L.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; Sottocornola, S.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Stegler, M.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, T. J.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, Dms; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeda, K.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, A. J.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Thais, S. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tian, Y.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Uno, K.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Furelos, D.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.-J.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. M.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, A.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Woods, N. L.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Xu, W.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamane, F.; Yamatani, M.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

    2018-01-01

    A search for an invisibly decaying Higgs boson or dark matter candidates produced in association with a leptonically decaying Z boson in proton-proton collisions at √{ s } = 13 TeV is presented. This search uses 36.1 fb-1 of data collected by the ATLAS experiment at the Large Hadron Collider. No significant deviation from the expectation of the Standard Model backgrounds is observed. Assuming the Standard Model ZH production cross-section, an observed (expected) upper limit of 67% (39%) at the 95% confidence level is set on the branching ratio of invisible decays of the Higgs boson with mass mH = 125 GeV. The corresponding limits on the production cross-section of the ZH process with the invisible Higgs boson decays are also presented. Furthermore, exclusion limits on the dark matter candidate and mediator masses are reported in the framework of simplified dark matter models.

  16. Determination of Minor and Trace Metals in Aluminum and Aluminum Alloys by ICP-AES; Evaluation of the Uncertainty and Limit of Quantitation from Interlaboratory Testing.

    PubMed

    Uemoto, Michihisa; Makino, Masanori; Ota, Yuji; Sakaguchi, Hiromi; Shimizu, Yukari; Sato, Kazuhiro

    2018-01-01

    Minor and trace metals in aluminum and aluminum alloys have been determined by inductively coupled plasma atomic emission spectrometry (ICP-AES) as an interlaboratory testing toward standardization. The trueness of the measured data was successfully investigated to improve the analytical protocols, using certified reference materials of aluminum. Their precision could also be evaluated, feasible to estimate the uncertainties separately. The accuracy (trueness and precision) of the data were finally in good agreement with the certified values and assigned uncertainties. Repeated measurements of aluminum solutions with different concentrations of the analytes revealed the relative standard deviations of the measurements with concentrations, thus enabling their limits of quantitation. They differed separately and also showed slightly higher values with an aluminum matrix than those without one. In addition, the upper limit of the detectable concentration of silicon with simple acid digestion was estimated to be 0.03 % in the mass fraction.

  17. Combined search for the standard model Higgs boson decaying to bb using the D0 run II data set.

    PubMed

    Abazov, V M; Abbott, B; Acharya, B S; Adams, M; Adams, T; Alexeev, G D; Alkhazov, G; Alton, A; Alverson, G; Askew, A; Atkins, S; Augsten, K; Avila, C; Badaud, F; Bagby, L; Baldin, B; Bandurin, D V; Banerjee, S; Barberis, E; Baringer, P; Bartlett, J F; Bassler, U; Bazterra, V; Bean, A; Begalli, M; Bellantoni, L; Beri, S B; Bernardi, G; Bernhard, R; Bertram, I; Besançon, M; Beuselinck, R; Bhat, P C; Bhatia, S; Bhatnagar, V; Blazey, G; Blessing, S; Bloom, K; Boehnlein, A; Boline, D; Boos, E E; Borissov, G; Bose, T; Brandt, A; Brandt, O; Brock, R; Bross, A; Brown, D; Brown, J; Bu, X B; Buehler, M; Buescher, V; Bunichev, V; Burdin, S; Buszello, C P; Camacho-Pérez, E; Casey, B C K; Castilla-Valdez, H; Caughron, S; Chakrabarti, S; Chakraborty, D; Chan, K M; Chandra, A; Chapon, E; Chen, G; Chevalier-Théry, S; Cho, D K; Cho, S W; Choi, S; Choudhary, B; Cihangir, S; Claes, D; Clutter, J; Cooke, M; Cooper, W E; Corcoran, M; Couderc, F; Cousinou, M-C; Croc, A; Cutts, D; Das, A; Davies, G; de Jong, S J; De La Cruz-Burelo, E; Déliot, F; Demina, R; Denisov, D; Denisov, S P; Desai, S; Deterre, C; Devaughan, K; Diehl, H T; Diesburg, M; Ding, P F; Dominguez, A; Dubey, A; Dudko, L V; Duggan, D; Duperrin, A; Dutt, S; Dyshkant, A; Eads, M; Edmunds, D; Ellison, J; Elvira, V D; Enari, Y; Evans, H; Evdokimov, A; Evdokimov, V N; Facini, G; Feng, L; Ferbel, T; Fiedler, F; Filthaut, F; Fisher, W; Fisk, H E; Fortner, M; Fox, H; Fuess, S; Garcia-Bellido, A; García-González, J A; García-Guerra, G A; Gavrilov, V; Gay, P; Geng, W; Gerbaudo, D; Gerber, C E; Gershtein, Y; Ginther, G; Golovanov, G; Goussiou, A; Grannis, P D; Greder, S; Greenlee, H; Grenier, G; Gris, Ph; Grivaz, J-F; Grohsjean, A; Grünendahl, S; Grünewald, M W; Guillemin, T; Gutierrez, G; Gutierrez, P; Hagopian, S; Haley, J; Han, L; Harder, K; Harel, A; Hauptman, J M; Hays, J; Head, T; Hebbeker, T; Hedin, D; Hegab, H; Heinson, A P; Heintz, U; Hensel, C; Heredia De La Cruz, I; Herner, K; Hesketh, G; Hildreth, M D; Hirosky, R; Hoang, T; Hobbs, J D; Hoeneisen, B; Hogan, J; Hohlfeld, M; Howley, I; Hubacek, Z; Hynek, V; Iashvili, I; Ilchenko, Y; Illingworth, R; Ito, A S; Jabeen, S; Jaffré, M; Jayasinghe, A; Jeong, M S; Jesik, R; Jiang, P; Johns, K; Johnson, E; Johnson, M; Jonckheere, A; Jonsson, P; Joshi, J; Jung, A W; Juste, A; Kaadze, K; Kajfasz, E; Karmanov, D; Kasper, P A; Katsanos, I; Kehoe, R; Kermiche, S; Khalatyan, N; Khanov, A; Kharchilava, A; Kharzheev, Y N; Kiselevich, I; Kohli, J M; Kozelov, A V; Kraus, J; Kulikov, S; Kumar, A; Kupco, A; Kurča, T; Kuzmin, V A; Lammers, S; Landsberg, G; Lebrun, P; Lee, H S; Lee, S W; Lee, W M; Lei, X; Lellouch, J; Li, D; Li, H; Li, L; Li, Q Z; Lim, J K; Lincoln, D; Linnemann, J; Lipaev, V V; Lipton, R; Liu, H; Liu, Y; Lobodenko, A; Lokajicek, M; Lopes de Sa, R; Lubatti, H J; Luna-Garcia, R; Lyon, A L; Maciel, A K A; Madar, R; Magaña-Villalba, R; Malik, S; Malyshev, V L; Maravin, Y; Martínez-Ortega, J; McCarthy, R; McGivern, C L; Meijer, M M; Melnitchouk, A; Menezes, D; Mercadante, P G; Merkin, M; Meyer, A; Meyer, J; Miconi, F; Mondal, N K; Mulhearn, M; Nagy, E; Naimuddin, M; Narain, M; Nayyar, R; Neal, H A; Negret, J P; Neustroev, P; Nguyen, H T; Nunnemann, T; Orduna, J; Osman, N; Osta, J; Padilla, M; Pal, A; Parashar, N; Parihar, V; Park, S K; Partridge, R; Parua, N; Patwa, A; Penning, B; Perfilov, M; Peters, Y; Petridis, K; Petrillo, G; Pétroff, P; Pleier, M-A; Podesta-Lerma, P L M; Podstavkov, V M; Popov, A V; Prewitt, M; Price, D; Prokopenko, N; Qian, J; Quadt, A; Quinn, B; Rangel, M S; Ranjan, K; Ratoff, P N; Razumov, I; Renkel, P; Ripp-Baudot, I; Rizatdinova, F; Rominsky, M; Ross, A; Royon, C; Rubinov, P; Ruchti, R; Sajot, G; Salcido, P; Sánchez-Hernández, A; Sanders, M P; Santos, A S; Savage, G; Sawyer, L; Scanlon, T; Schamberger, R D; Scheglov, Y; Schellman, H; Schlobohm, S; Schwanenberger, C; Schwienhorst, R; Sekaric, J; Severini, H; Shabalina, E; Shary, V; Shaw, S; Shchukin, A A; Shivpuri, R K; Simak, V; Skubic, P; Slattery, P; Smirnov, D; Smith, K J; Snow, G R; Snow, J; Snyder, S; Söldner-Rembold, S; Sonnenschein, L; Soustruznik, K; Stark, J; Stoyanova, D A; Strauss, M; Suter, L; Svoisky, P; Takahashi, M; Titov, M; Tokmenin, V V; Tsai, Y-T; Tschann-Grimm, K; Tsybychev, D; Tuchming, B; Tully, C; Uvarov, L; Uvarov, S; Uzunyan, S; Van Kooten, R; van Leeuwen, W M; Varelas, N; Varnes, E W; Vasilyev, I A; Verdier, P; Verkheev, A Y; Vertogradov, L S; Verzocchi, M; Vesterinen, M; Vilanova, D; Vokac, P; Wahl, H D; Wang, M H L S; Wang, R-J; Warchol, J; Watts, G; Wayne, M; Weichert, J; Welty-Rieger, L; White, A; Wicke, D; Williams, M R J; Wilson, G W; Wobisch, M; Wood, D R; Wyatt, T R; Xie, Y; Yamada, R; Yang, S; Yang, W-C; Yasuda, T; Yatsunenko, Y A; Ye, W; Ye, Z; Yin, H; Yip, K; Youn, S W; Yu, J M; Zennamo, J; Zhao, T; Zhao, T G; Zhou, B; Zhu, J; Zielinski, M; Zieminska, D; Zivkovic, L

    2012-09-21

    We present the results of the combination of searches for the standard model Higgs boson produced in association with a W or Z boson and decaying into bb using the data sample collected with the D0 detector in pp collisions at √s = 1.96 TeV at the Fermilab Tevatron Collider. We derive 95% C.L. upper limits on the Higgs boson cross section relative to the standard model prediction in the mass range 100 GeV ≤ M(H) ≤ 150 GeV, and we exclude Higgs bosons with masses smaller than 102 GeV at the 95% C.L. In the mass range 120 GeV ≤ M(H) ≤145 GeV, the data exhibit an excess above the background prediction with a global significance of 1.5 standard deviations, consistent with the expectation in the presence of a standard model Higgs boson.

  18. Inflation Accounting Methods and their Effectiveness

    DTIC Science & Technology

    1992-06-01

    security is measured by the standard deviation of its returns in the past periods and is reflected in the security’ s market price . The Capital Asset Pricing ...purchasing power should be limited to items which are used by an average consumer. Economists tend to perceive the general price level as the cost of living...accounting. Two common measures of business performance are income and rate of return on capital . Since depreciation charges for long-lived assets do

  19. Do physiotherapy staff record treatment time accurately? An observational study.

    PubMed

    Bagley, Pam; Hudson, Mary; Green, John; Forster, Anne; Young, John

    2009-09-01

    To assess the reliability of duration of treatment time measured by physiotherapy staff in early-stage stroke patients. Comparison of physiotherapy staff's recording of treatment sessions and video recording. Rehabilitation stroke unit in a general hospital. Thirty-nine stroke patients without trunk control or who were unable to stand with an erect trunk without the support of two therapists recruited to a randomized trial evaluating the Oswestry Standing Frame. Twenty-six physiotherapy staff who were involved in patient treatment. Contemporaneous recording by physiotherapy staff of treatment time (in minutes) compared with video recording. Intraclass correlation with 95% confidence interval and the Bland and Altman method for assessing agreement by calculating the mean difference (standard deviation; 95% confidence interval), reliability coefficient and 95% limits of agreement for the differences between the measurements. The mean duration (standard deviation, SD) of treatment time recorded by physiotherapy staff was 32 (11) minutes compared with 25 (9) minutes as evidenced in the video recording. The mean difference (SD) was -6 (9) minutes (95% confidence interval (CI) -9 to -3). The reliability coefficient was 18 minutes and the 95% limits of agreement were -24 to 12 minutes. Intraclass correlation coefficient for agreement between the two methods was 0.50 (95% CI 0.12 to 0.73). Physiotherapy staff's recording of duration of treatment time was not reliable and was systematically greater than the video recording.

  20. Portable device for the detection of colorimetric assays

    PubMed Central

    Nowak, E.; Kawchuk, J.; Hoorfar, M.; Najjaran, H.

    2017-01-01

    In this work, a low-cost, portable device is developed to detect colorimetric assays for in-field and point-of-care (POC) analysis. The device can rapidly detect both pH values and nitrite concentrations of five different samples, simultaneously. After mixing samples with specific reagents, a high-resolution digital camera collects a picture of the sample, and a single-board computer processes the image in real time to identify the hue–saturation–value coordinates of the image. An internal light source reduces the effect of any ambient light so the device can accurately determine the corresponding pH values or nitrite concentrations. The device was purposefully designed to be low-cost, yet versatile, and the accuracy of the results have been compared to those from a conventional method. The results obtained for pH values have a mean standard deviation of 0.03 and a correlation coefficient R2 of 0.998. The detection of nitrites is between concentrations of 0.4–1.6 mg l−1, with a low detection limit of 0.2 mg l−1, and has a mean standard deviation of 0.073 and an R2 value of 0.999. The results represent great potential of the proposed portable device as an excellent analytical tool for POC colorimetric analysis and offer broad accessibility in resource-limited settings. PMID:29291093

  1. Determination of sulfur in kerosene by combustion and molecular absorption spectrometry in the gas phase

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ruschak, M.L.; Syty, A.

    1982-08-01

    A technique of nonflame molecular adsorption in the gas phase developed for the determination of sulfite trapped in tetrachloromercurate, is described herein for application to the determination of total sulfur in kerosene. The burner head is removed from the atomic absorption spectrometer and replaced with a flow-through absorption cell. A special reaction vessel is used to evolve SO/sub 2/ from the sulfite in a precise and convenient manner. The transient absorbance caused by the SO/sub 2/, as it is carried through the absorption cell, is measured. Both spiked and unspiked samples of kerosene were analyzed, and the reproducibility of themore » repeated runs is evidenced by a relative standard deviation from the mean of 5% for the unspiked kerosene and 4% for the spiked kerosene. If the detection level is defined as that concentration of S which gives a % S twice the standard deviation from the mean yields, the detection limit for the present method is 0.002% S by weight in kerosene.« less

  2. A simplified and accurate detection of the genetically modified wheat MON71800 with one calibrator plasmid.

    PubMed

    Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Park, Sunghoon; Shin, Min-Ki; Moon, Gui Im; Hong, Jin-Hwan; Kim, Hae-Yeong

    2015-06-01

    With the increasing number of genetically modified (GM) events, unauthorized GMO releases into the food market have increased dramatically, and many countries have developed detection tools for them. This study described the qualitative and quantitative detection methods of unauthorized the GM wheat MON71800 with a reference plasmid (pGEM-M71800). The wheat acetyl-CoA carboxylase (acc) gene was used as the endogenous gene. The plasmid pGEM-M71800, which contains both the acc gene and the event-specific target MON71800, was constructed as a positive control for the qualitative and quantitative analyses. The limit of detection in the qualitative PCR assay was approximately 10 copies. In the quantitative PCR assay, the standard deviation and relative standard deviation repeatability values ranged from 0.06 to 0.25 and from 0.23% to 1.12%, respectively. This study supplies a powerful and very simple but accurate detection strategy for unauthorized GM wheat MON71800 that utilizes a single calibrator plasmid. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Microwave-assisted rapid preparation of monodisperse superhydrophilic resin microspheres as adsorbent for triazines in fruit juices.

    PubMed

    Zhou, Tianyu; Ding, Jie; Wang, Qiang; Xu, Yuan; Wang, Bo; Zhao, Li; Ding, Hong; Chen, Yanhua; Ding, Lan

    2018-03-01

    Monodisperse superhydrophilic melamine formaldehyde resorcinol resin (MFR) microspheres were prepared in 90min at 85°C via a microwave-assisted method with a yield of 60.6%. The obtained MFR microspheres exhibited narrow size distribution with the average particle size of about 2.5µm. The MFR microspheres were used as absorbents to detect triazines in juices followed by high performance liquid chromatography tandem mass spectrometry. Various factors affecting the extraction efficiency were investigated. Under the optimized conditions, the built method exhibited excellent linearity in the range of 1-250μgL -1 (R 2 ≥ 0.9994) and lower detection limits (0.3-0.65μgL -1 ). The relative standard deviations of intra- and inter-day analyses ranged from 3% to 7% and from 2% to 7%, respectively. The method was applied to determine six triazines in three juice samples. At the spiked level of 3μgL -1 , the recoveries were in the range of 90-99% with the relative standard deviations ≤ 8%. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Capillary electrophoresis with electrochemiluminescence detection for the simultaneous determination of cisatracurium besylate and its degradation products in pharmaceutical preparations.

    PubMed

    Zuo, Ming; Gao, Jieying; Zhang, Xiaoqing; Cui, Yue; Fan, Zimian; Ding, Min

    2015-07-01

    Capillary electrophoresis with electrochemiluminescence detection for the simultaneous analysis of cisatracurium besylate and its degradation products (laudanosine, quaternary monoacrylate) in pharmaceutical preparation was developed and fully validated. The significant parameters that influence capillary electrophoresis separation and electrochemiluminescence detection were optimized. The total analysis time of the analytes was 15 min. The linearities of the method were 0.1∼40.0 μg/mL for cisatracurium besylate and 0.04∼8.00 μg/mL for laudanosine, with correlation coefficients (r) of 0.999 and 0.998, respectively. The detection limits (S/N = 3) were 83.0 ng/mL for cisatracurium besylate and 32.0 ng/mL for laudanosine. The intraday relative standard deviations of the analytes were <3.0%, and the interday relative standard deviations were <8.0%. The developed method was cost-effective, sensitive, fast, and resource-saving, which was suitable for the ingredient analysis in pharmaceutical preparation. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Search for resonant production of high-mass photon pairs in proton-proton collisions at sqrt(s) = 8 and 13 TeV

    DOE PAGES

    Khachatryan, Vardan

    2016-07-28

    A search for the resonant production of high-mass photon pairs is presented. The analysis is based on samples of proton-proton collision data collected by the CMS experiment at center-of-mass energies of 8 and 13 TeV, corresponding to integrated luminosities of 19.7 and 3.3 inverse femtobarns, respectively. The search focuses on spin-0 and spin-2 resonances with masses between 0.5 and 4 TeV and with widths, relative to the mass, between 1.4E-4 and 5.6E-2. Limits are set on scalar resonances produced through gluon-gluon fusion, and on Randall--Sundrum gravitons. A modest excess of events compatible with a narrow resonance with a mass ofmore » about 750 GeV is observed. The local significance of the excess is approximately 3.4 standard deviations. The significance is reduced to 1.6 standard deviations once the effect of searching under multiple signal hypotheses is considered. More data are required to determine the origin of this excess.« less

  6. Search for gluinos in events with an isolated lepton, jets and missing transverse momentum at $$\\sqrt{s}$$ = 13 Te V with the ATLAS detector

    DOE PAGES

    Aad, G.; Abbott, B.; Abdallah, J.; ...

    2016-10-21

    The results of a search for gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton–proton collision data at a centre-of-mass energy ofmore » $$\\sqrt{s}$$ = 13 Te V are presented. The dataset used was recorded in 2015 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 3.2 fb -1 . Six signal selections are defined that best exploit the signal characteristics. The data agree with the Standard Model background expectation in all six signal selections, and the largest deviation is a 2.1 standard deviation excess. The results are interpreted in a simplified model where pair-produced gluinos decay via the lightest chargino to the lightest neutralino. In this model, gluinos are excluded up to masses of approximately 1.6 Te V depending on the mass spectrum of the simplified model, thus surpassing the limits of previous searches.« less

  7. 10 CFR 961.4 - Deviations.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Deviations. 961.4 Section 961.4 Energy DEPARTMENT OF ENERGY STANDARD CONTRACT FOR DISPOSAL OF SPENT NUCLEAR FUEL AND/OR HIGH-LEVEL RADIOACTIVE WASTE General § 961.4 Deviations. Requests for authority to deviate from this part shall be submitted in writing to...

  8. 10 CFR 961.4 - Deviations.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 4 2012-01-01 2012-01-01 false Deviations. 961.4 Section 961.4 Energy DEPARTMENT OF ENERGY STANDARD CONTRACT FOR DISPOSAL OF SPENT NUCLEAR FUEL AND/OR HIGH-LEVEL RADIOACTIVE WASTE General § 961.4 Deviations. Requests for authority to deviate from this part shall be submitted in writing to...

  9. 10 CFR 961.4 - Deviations.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 4 2014-01-01 2014-01-01 false Deviations. 961.4 Section 961.4 Energy DEPARTMENT OF ENERGY STANDARD CONTRACT FOR DISPOSAL OF SPENT NUCLEAR FUEL AND/OR HIGH-LEVEL RADIOACTIVE WASTE General § 961.4 Deviations. Requests for authority to deviate from this part shall be submitted in writing to...

  10. 10 CFR 961.4 - Deviations.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 10 Energy 4 2013-01-01 2013-01-01 false Deviations. 961.4 Section 961.4 Energy DEPARTMENT OF ENERGY STANDARD CONTRACT FOR DISPOSAL OF SPENT NUCLEAR FUEL AND/OR HIGH-LEVEL RADIOACTIVE WASTE General § 961.4 Deviations. Requests for authority to deviate from this part shall be submitted in writing to...

  11. 10 CFR 961.4 - Deviations.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 4 2011-01-01 2011-01-01 false Deviations. 961.4 Section 961.4 Energy DEPARTMENT OF ENERGY STANDARD CONTRACT FOR DISPOSAL OF SPENT NUCLEAR FUEL AND/OR HIGH-LEVEL RADIOACTIVE WASTE General § 961.4 Deviations. Requests for authority to deviate from this part shall be submitted in writing to...

  12. Do health care workforce, population, and service provision significantly contribute to the total health expenditure? An econometric analysis of Serbia.

    PubMed

    Santric-Milicevic, M; Vasic, V; Terzic-Supic, Z

    2016-08-15

    In times of austerity, the availability of econometric health knowledge assists policy-makers in understanding and balancing health expenditure with health care plans within fiscal constraints. The objective of this study is to explore whether the health workforce supply of the public health care sector, population number, and utilization of inpatient care significantly contribute to total health expenditure. The dependent variable is the total health expenditure (THE) in Serbia from the years 2003 to 2011. The independent variables are the number of health workers employed in the public health care sector, population number, and inpatient care discharges per 100 population. The statistical analyses include the quadratic interpolation method, natural logarithm and differentiation, and multiple linear regression analyses. The level of significance is set at P < 0.05. The regression model captures 90 % of all variations of observed dependent variables (adjusted R square), and the model is significant (P < 0.001). Total health expenditure increased by 1.21 standard deviations, with an increase in health workforce growth rate by 1 standard deviation. Furthermore, this rate decreased by 1.12 standard deviations, with an increase in (negative) population growth rate by 1 standard deviation. Finally, the growth rate increased by 0.38 standard deviation, with an increase of the growth rate of inpatient care discharges per 100 population by 1 standard deviation (P < 0.001). Study results demonstrate that the government has been making an effort to control strongly health budget growth. Exploring causality relationships between health expenditure and health workforce is important for countries that are trying to consolidate their public health finances and achieve universal health coverage at the same time.

  13. The truly remarkable universality of half a standard deviation: confirmation through another look.

    PubMed

    Norman, Geoffrey R; Sloan, Jeff A; Wyrwich, Kathleen W

    2004-10-01

    In this issue of Expert Review of Pharmacoeconomics and Outcomes Research, Farivar, Liu, and Hays present their findings in 'Another look at the half standard deviation estimate of the minimally important difference in health-related quality of life scores (hereafter referred to as 'Another look') . These researchers have re-examined the May 2003 Medical Care article 'Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation' (hereafter referred to as 'Remarkable') in the hope of supporting their hypothesis that the minimally important difference in health-related quality of life measures is undoubtedly closer to 0.3 standard deviations than 0.5. Nonetheless, despite their extensive wranglings with the exclusion of many articles that we included in our review; the inclusion of articles that we did not include in our review; and the recalculation of effect sizes using the absolute value of the mean differences, in our opinion, the results of the 'Another look' article confirm the same findings in the 'Remarkable' paper.

  14. Static Scene Statistical Non-Uniformity Correction

    DTIC Science & Technology

    2015-03-01

    Error NUC Non-Uniformity Correction RMSE Root Mean Squared Error RSD Relative Standard Deviation S3NUC Static Scene Statistical Non-Uniformity...Deviation ( RSD ) which normalizes the standard deviation, σ, to the mean estimated value, µ using the equation RS D = σ µ × 100. The RSD plot of the gain...estimates is shown in Figure 4.1(b). The RSD plot shows that after a sample size of approximately 10, the different photocount values and the inclusion

  15. Effect of multizone refractive multifocal contact lenses on standard automated perimetry.

    PubMed

    Madrid-Costa, David; Ruiz-Alcocer, Javier; García-Lázaro, Santiago; Albarrán-Diego, César; Ferrer-Blasco, Teresa

    2012-09-01

    The aim of this study was to evaluate whether the creation of 2 foci (distance and near) provided by multizone refractive multifocal contact lenses (CLs) for presbyopia correction affects the measurements on Humphreys 24-2 Swedish interactive threshold algorithm (SITA) standard automated perimetry (SAP). In this crossover study, 30 subjects were fitted in random order with either a multifocal CL or a monofocal CL. After 1 month, a Humphrey 24-2 SITA standard strategy was performed. The visual field global indices (the mean deviation [MD] and pattern standard deviation [PSD]), reliability indices, test duration, and number of depressed points deviating at P<5%, P<2%, P<1%, and P<0.5% on pattern deviation probability plots were determined and compared between multifocal and monofocal CLs. Thirty eyes of 30 subjects were included in this study. There were no statistically significant differences in reliability indices or test duration. There was a statistically significant reduction in the MD with the multifocal CL compared with monfocal CL (P=0.001). Differences were not found in PSD nor in the number of depressed points deviating at P<5%, P<2%, P<1%, and P<0.5% in the pattern deviation probability maps studied. The results of this study suggest that the multizone refractive lens produces a generalized depression in threshold sensitivity as measured by the Humphreys 24-2 SITA SAP.

  16. Constraints on models of the Higgs boson with exotic spin and parity using decays to bottom-antibottom quarks in the full CDF data set.

    PubMed

    Aaltonen, T; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Auerbach, B; Aurisano, A; Azfar, F; Badgett, W; Bae, T; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauce, M; Bedeschi, F; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Bland, K R; Blumenfeld, B; Bocci, A; Bodek, A; Bortoletto, D; Boudreau, J; Boveia, A; Brigliadori, L; Bromberg, C; Brucken, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Bussey, P; Butti, P; Buzatu, A; Calamba, A; Camarda, S; Campanelli, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cerri, A; Cerrito, L; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Cho, K; Chokheli, D; Clark, A; Clarke, C; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Cremonesi, M; Cruz, D; Cuevas, J; Culbertson, R; d'Ascenzo, N; Datta, M; de Barbaro, P; Demortier, L; Deninno, M; D'Errico, M; Devoto, F; Di Canto, A; Di Ruzza, B; Dittmann, J R; Donati, S; D'Onofrio, M; Dorigo, M; Driutti, A; Ebina, K; Edgar, R; Elagin, A; Erbacher, R; Errede, S; Esham, B; Farrington, S; Fernández Ramos, J P; Field, R; Flanagan, G; Forrest, R; Franklin, M; Freeman, J C; Frisch, H; Funakoshi, Y; Galloni, C; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González López, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gramellini, E; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Hahn, S R; Han, J Y; Happacher, F; Hara, K; Hare, M; Harr, R F; Harrington-Taber, T; Hatakeyama, K; Hays, C; Heinrich, J; Herndon, M; Hocker, A; Hong, Z; Hopkins, W; Hou, S; Hughes, R E; Husemann, U; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kambeitz, M; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; Keung, J; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S H; Kim, S B; Kim, Y J; Kim, Y K; Kimura, N; Kirby, M; Knoepfel, K; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Kruse, M; Kuhr, T; Kurata, M; Laasanen, A T; Lammel, S; Lancaster, M; Lannon, K; Latino, G; Lee, H S; Lee, J S; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lipeles, E; Lister, A; Liu, H; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lucà, A; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maestro, P; Malik, S; Manca, G; Manousakis-Katsikakis, A; Marchese, L; Margaroli, F; Marino, P; Matera, K; Mattson, M E; Mazzacane, A; Mazzanti, P; McNulty, R; Mehta, A; Mehtala, P; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M J; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Nigmanov, T; Nodulman, L; Noh, S Y; Norniella, O; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagliarone, C; Palencia, E; Palni, P; Papadimitriou, V; Parker, W; Pauletta, G; Paulini, M; Paus, C; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Pranko, A; Prokoshin, F; Ptohos, F; Punzi, G; Redondo Fernández, I; Renton, P; Rescigno, M; Rimondi, F; Ristori, L; Robson, A; Rodriguez, T; Rolli, S; Ronzani, M; Roser, R; Rosner, J L; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Sakumoto, W K; Sakurai, Y; Santi, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, E E; Schwarz, T; Scodellaro, L; Scuri, F; Seidel, S; Seiya, Y; Semenov, A; Sforza, F; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shochet, M; Shreyber-Tecker, I; Simonenko, A; Sliwa, K; Smith, J R; Snider, F D; Song, H; Sorin, V; St Denis, R; Stancari, M; Stentz, D; Strologas, J; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thomson, E; Thukral, V; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Ukegawa, F; Uozumi, S; Vázquez, F; Velev, G; Vellidis, C; Vernieri, C; Vidal, M; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wallny, R; Wang, S M; Waters, D; Wester, W C; Whiteson, D; Wicklund, A B; Wilbur, S; Williams, H H; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, H; Wright, T; Wu, X; Wu, Z; Yamamoto, K; Yamato, D; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Zanetti, A M; Zeng, Y; Zhou, C; Zucchelli, S

    2015-04-10

    A search for particles with the same mass and couplings as those of the standard model Higgs boson but different spin and parity quantum numbers is presented. We test two specific alternative Higgs boson hypotheses: a pseudoscalar Higgs boson with spin-parity J^{P}=0^{-} and a gravitonlike Higgs boson with J^{P}=2^{+}, assuming for both a mass of 125  GeV/c^{2}. We search for these exotic states produced in association with a vector boson and decaying into a bottom-antibottom quark pair. The vector boson is reconstructed through its decay into an electron or muon pair, or an electron or muon and a neutrino, or it is inferred from an imbalance in total transverse momentum. We use expected kinematic differences between events containing exotic Higgs bosons and those containing standard model Higgs bosons. The data were collected by the CDF experiment at the Tevatron proton-antiproton collider, operating at a center-of-mass energy of sqrt[s]=1.96  TeV, and correspond to an integrated luminosity of 9.45  fb^{-1}. We exclude deviations from the predictions of the standard model with a Higgs boson of mass 125  GeV/c^{2} at the level of 5 standard deviations, assuming signal strengths for exotic boson production equal to the prediction for the standard model Higgs boson, and set upper limits of approximately 30% relative to the standard model rate on the possible rate of production of each exotic state.

  17. Investigation of the refractive index repeatability for tantalum pentoxide coatings, prepared by physical vapor film deposition techniques.

    PubMed

    Stenzel, O; Wilbrandt, S; Wolf, J; Schürmann, M; Kaiser, N; Ristau, D; Ehlers, H; Carstens, F; Schippel, S; Mechold, L; Rauhut, R; Kennedy, M; Bischoff, M; Nowitzki, T; Zöller, A; Hagedorn, H; Reus, H; Hegemann, T; Starke, K; Harhausen, J; Foest, R; Schumacher, J

    2017-02-01

    Random effects in the repeatability of refractive index and absorption edge position of tantalum pentoxide layers prepared by plasma-ion-assisted electron-beam evaporation, ion beam sputtering, and magnetron sputtering are investigated and quantified. Standard deviations in refractive index between 4*10-4 and 4*10-3 have been obtained. Here, lowest standard deviations in refractive index close to our detection threshold could be achieved by both ion beam sputtering and plasma-ion-assisted deposition. In relation to the corresponding mean values, the standard deviations in band-edge position and refractive index are of similar order.

  18. Sample sizes needed for specified margins of relative error in the estimates of the repeatability and reproducibility standard deviations.

    PubMed

    McClure, Foster D; Lee, Jung K

    2005-01-01

    Sample size formulas are developed to estimate the repeatability and reproducibility standard deviations (Sr and S(R)) such that the actual error in (Sr and S(R)) relative to their respective true values, sigmar and sigmaR, are at predefined levels. The statistical consequences associated with AOAC INTERNATIONAL required sample size to validate an analytical method are discussed. In addition, formulas to estimate the uncertainties of (Sr and S(R)) were derived and are provided as supporting documentation. Formula for the Number of Replicates Required for a Specified Margin of Relative Error in the Estimate of the Repeatability Standard Deviation.

  19. Determination of cyflumetofen residue in water, soil, and fruits by modified quick, easy, cheap, effective, rugged, and safe method coupled to gas chromatography/tandem mass spectrometry.

    PubMed

    Li, Minmin; Liu, Xingang; Dong, Fengshou; Xu, Jun; Qin, Dongmei; Zheng, Yongquan

    2012-10-01

    A new, highly sensitive, and selective method was developed for the determination of the cyflumetofen residue in water, soil, and fruits by using gas chromatography quadruple mass spectrometry. The target compound was extracted using acetonitrile and then cleaned up using dispersive solid-phase extraction with primary and secondary amine and graphitized carbon black, and optionally by a freezing-out cleanup step. The matrix-matched standards gave satisfactory recoveries and relative standard deviation values in different matrices at three fortified levels (0.05, 0.5, and 1.0 mg kg(-1) ). The overall average recoveries for this method in water, soil, and all fruits matrix at three fortified levels ranged from 76.3 to 101.5% with relative standard deviations in the range of 1.2-11.8% (n = 5). The calculated limits of detection and quantification were typically below 0.005 and 0.015 μg kg(-1), which were much lower than the maximum residue levels established by Japanese Positive List. This study provides a theoretical basis for China to draw up maximum residue level and analytical method for cyflumetofen acaricide in different fruits. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Liquid Chromatography with Post-Column Reagent Addition of Ammonia in Methanol Coupled to Negative Ion Electrospray Ionization Tandem Mass Spectrometry for Determination of Phenoxyacid Herbicides and their Degradation Products in Surface Water

    PubMed Central

    Raina, Renata; Etter, Michele L.

    2010-01-01

    A new liquid chromatography (LC)-negative ion electrospray ionization (ESI−)–tandem mass spectrometry (MS/MS) method with post-column addition of ammonia in methanol has been developed for the analysis of acid herbicides: 2,4-dichlorophenoxy acetic acid, 4-chloro-o-tolyloxyacetic acid, 2-(2-methyl-4-chlorophenoxy)butyric acid, mecoprop, dichlorprop, 4-(2,4-dichlorophenoxy) butyric acid, 2,4,5-trichlorophenoxy propionic acid, dicamba and bromoxynil, along with their degradation products: 4-chloro-2-methylphenol, 2,4-dichlorophenol, 2,4,5-trichlorophenol and 3,5-dibromo-4-hydroxybenzoic acid. The samples were extracted from the surface water matrix using solid-phase extraction (SPE) with a polymeric sorbent and analyzed with LC ESI− with selected reaction monitoring (SRM) using a three-point confirmation approach. Chromatography was performed on a Zorbax Eclipse XDB-C18 (50 × 4.6 mm i.d., 1.8 μm) with a gradient elution using water-methanol with 2 mM ammonium acetate mobile phase at a flow rate of 0.15 mL/min. Ammonia in methanol (0.8 M) was added post-column at a flow rate of 0.05 mL/min to enhance ionization of the degradation products in the MS source. One SRM transition was used for quantitative analysis while the second SRM along with the ratio of SRM1/SRM2 within the relative standard deviation determined by standards for each individual pesticide and retention time match were used for confirmation. The standard deviation of ratio of SRM1/SRM2 obtained from standards run on the day of analysis for different phenoxyacid herbicides ranged from 3.9 to 18.5%. Limits of detection (LOD) were between 1 and 15 ng L−1 and method detection limits (MDL) with strict criteria requiring <25% deviation of peak area from best-fit line for both SRM1 and SRM2 ranged from 5 to 10 ng L−1 for acid ingredients (except dicamba at 30 ng L−1) and from 2 to 30 ng L−1 for degradation products. The SPE-LC-ESI− MS/MS method permitted low nanogram-per-liter determination of pesticides and degradation products for surface water samples. PMID:20212919

  1. Flammability of gas mixtures. Part 1: fire potential.

    PubMed

    Schröder, Volkmar; Molnarne, Maria

    2005-05-20

    International and European dangerous substances and dangerous goods regulations refer to the standard ISO 10156 (1996). This standard includes a test method and a calculation procedure for the determination of the flammability of gases and gas mixtures in air. The substance indices for the calculation, the so called "Tci values", which characterise the fire potential, are provided as well. These ISO Tci values are derived from explosion diagrams of older literature sources which do not take into account the test method and the test apparatus. However, since the explosion limits are influenced by apparatus parameters, the Tci values and lower explosion limits, given by the ISO tables, are inconsistent with those measured according to the test method of the same standard. In consequence, applying the ISO Tci values can result in wrong classifications. In this paper internationally accepted explosion limit test methods were evaluated and Tci values were derived from explosion diagrams. Therefore, an "open vessel" method with flame propagation criterion was favoured. These values were compared with the Tci values listed in ISO 10156. In most cases, significant deviations were found. A detailed study about the influence of inert gases on flammability is the objective of Part 2.

  2. Simultaneous determination of five marker constituents in Ssanghwa tang by HPLC/DAD

    PubMed Central

    Won, Jin Bae; Ma, Jin Yeul; Um, Young Ran; Ma, Choong Je

    2010-01-01

    A HPLC-DAD method was established for the simultaneous evaluation of five bioactive compounds in Ssanghwa tang (SHT) including glycyrrhizin, paeoniflorin, cinnamic acid, decursin and 6-gingerol. These compounds were separated in less than 40 min using a Dionex C18 column with a gradient elution system of water and methanol at a flow rate of 1 ml/min. Calibration curve of standard components presented excellent linear regression (R2 > 0.9903) within the test range. Limit of detection and limit of quantification varied from 0.07 to 0.46 μg/ml and 0.13 to 1.11 μg/ml, respectively. The relative standard deviations (RSDs) of data of the intraday and interday experiments were less than 3.67 and 5.73%, respectively. The accuracy of recovery test ranged from 95.98 to 105.88% with RSD values 0.10– 4.82%. PMID:20668576

  3. Measurements of the pp → Wγγ and pp → Zγγ cross sections and limits on anomalous quartic gauge couplings at √{s}=8 TeV

    NASA Astrophysics Data System (ADS)

    Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Waltenberger, W.; Wulz, C.-E.; Dvornikov, O.; Makarenko, V.; Mossolov, V.; Suarez Gonzalez, J.; Zykunov, V.; Shumeiko, N.; Alderweireldt, S.; De Wolf, E. 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L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. 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A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; El-khateeb, E.; Elgammal, S.; Mohamed, A.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Albert, A.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baur, S.; Baus, C.; Berger, J.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Freund, B.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Katkov, I.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Kousouris, K.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Triantis, F. A.; Filipovic, N.; Pasztor, G.; Bencze, G.; Hajdu, C.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Dewanjee, R. K.; Ganguly, S.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Pandey, S.; Rane, A.; Sharma, S.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Lenzi, P.; Meschini, M.; Paoletti, S.; Russo, L.; Sguazzoni, G.; Strom, D.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Brivio, F.; Ciriolo, V.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Michelotto, M.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Ventura, S.; Zanetti, M.; Zotto, P.; Braghieri, A.; Fallavollita, F.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Mariani, V.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Monteno, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, J.; Lee, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Kim, H.; Brochero Cifuentes, J. A.; Goh, J.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Lee, H.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Ali, M. A. B. Md; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Lopez-Fernandez, R.; Magaña Villalba, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Carpinteyro, S.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Calpas, B.; Di Francesco, A.; Faccioli, P.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Afanasiev, S.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Palichik, V.; Perelygin, V.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Chtchipounov, L.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Murzin, V.; Oreshkin, V.; Sulimov, V.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Bylinkin, A.; Chadeeva, M.; Rusinov, V.; Tarkovskii, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Blinov, V.; Skovpen, Y.; Shtol, D.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Barrio Luna, M.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Erice, C.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vischia, P.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Baillon, P.; Ball, A. H.; Barney, D.; Bloch, P.; Bocci, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; Chen, Y.; Cimmino, A.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Fartoukh, S.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Girone, M.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kieseler, J.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Krammer, M.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Milenovic, P.; Moortgat, F.; Morovic, S.; Mulders, M.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Sauvan, J. B.; Schäfer, C.; Schwick, C.; Seidel, M.; Selvaggi, M.; Sharma, A.; Silva, P.; Sphicas, P.; Steggemann, J.; Stoye, M.; Takahashi, Y.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Verweij, M.; Wardle, N.; Wöhri, H. K.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Bachmair, F.; Bäni, L.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Donato, S.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Seitz, C.; Yang, Y.; Zucchetta, A.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chang, Y. H.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Boran, F.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Eskut, E.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Isildak, B.; Karapinar, G.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, E. A.; Yetkin, T.; Cakir, A.; Cankocak, K.; Sen, S.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Nash, J.; Nikitenko, A.; Pela, J.; Penning, B.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Squires, M.; Stolp, D.; Tos, K.; Tripathi, M.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Weber, M.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Si, W.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Holzner, A.; Klein, D.; Krutelyov, V.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bendavid, J.; Bornheim, A.; Bunn, J.; Lawhorn, J. M.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Apresyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Wu, Y.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Low, J. F.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Bein, S.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Perry, T.; Prosper, H.; Santra, A.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Forthomme, L.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Apyan, A.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Malta Rodrigues, A.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Rupprecht, N.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Medvedeva, T.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Svyatkovskiy, A.; Tully, C.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Schulte, J. F.; Sun, J.; Wang, F.; Xie, W.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; Belknap, D. A.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

    2017-10-01

    Measurements are presented of Wγγ and Zγγ production in proton-proton collisions. Fiducial cross sections are reported based on a data sample corresponding to an integrated luminosity of 19.4 fb-1 collected with the CMS detector at a center-of-mass energy of 8 TeV. Signal is identified through the W → ℓν and Z → ℓℓ decay modes, where ℓ is a muon or an electron. The production of Wγγ and Zγγ, measured with significances of 2.6 and 5.9 standard deviations, respectively, is consistent with standard model predictions. In addition, limits on anomalous quartic gauge couplings in Wγγ production are determined in the context of a dimension-8 effective field theory. [Figure not available: see fulltext.

  4. Comparing biomarker measurements to a normal range: when to use standard error of the mean (SEM) or standard deviation (SD) confidence intervals tests.

    PubMed

    Pleil, Joachim D

    2016-01-01

    This commentary is the second of a series outlining one specific concept in interpreting biomarkers data. In the first, an observational method was presented for assessing the distribution of measurements before making parametric calculations. Here, the discussion revolves around the next step, the choice of using standard error of the mean or the calculated standard deviation to compare or predict measurement results.

  5. Introducing the Mean Absolute Deviation "Effect" Size

    ERIC Educational Resources Information Center

    Gorard, Stephen

    2015-01-01

    This paper revisits the use of effect sizes in the analysis of experimental and similar results, and reminds readers of the relative advantages of the mean absolute deviation as a measure of variation, as opposed to the more complex standard deviation. The mean absolute deviation is easier to use and understand, and more tolerant of extreme…

  6. Odds per Adjusted Standard Deviation: Comparing Strengths of Associations for Risk Factors Measured on Different Scales and Across Diseases and Populations

    PubMed Central

    Hopper, John L.

    2015-01-01

    How can the “strengths” of risk factors, in the sense of how well they discriminate cases from controls, be compared when they are measured on different scales such as continuous, binary, and integer? Given that risk estimates take into account other fitted and design-related factors—and that is how risk gradients are interpreted—so should the presentation of risk gradients. Therefore, for each risk factor X0, I propose using appropriate regression techniques to derive from appropriate population data the best fitting relationship between the mean of X0 and all the other covariates fitted in the model or adjusted for by design (X1, X2, … , Xn). The odds per adjusted standard deviation (OPERA) presents the risk association for X0 in terms of the change in risk per s = standard deviation of X0 adjusted for X1, X2, … , Xn, rather than the unadjusted standard deviation of X0 itself. If the increased risk is relative risk (RR)-fold over A adjusted standard deviations, then OPERA = exp[ln(RR)/A] = RRs. This unifying approach is illustrated by considering breast cancer and published risk estimates. OPERA estimates are by definition independent and can be used to compare the predictive strengths of risk factors across diseases and populations. PMID:26520360

  7. Selection of vegetation indices for mapping the sugarcane condition around the oil and gas field of North West Java Basin, Indonesia

    NASA Astrophysics Data System (ADS)

    Muji Susantoro, Tri; Wikantika, Ketut; Saepuloh, Asep; Handoyo Harsolumakso, Agus

    2018-05-01

    Selection of vegetation indices in plant mapping is needed to provide the best information of plant conditions. The methods used in this research are the standard deviation and the linear regression. This research tried to determine the vegetation indices used for mapping the sugarcane conditions around oil and gas fields. The data used in this study is Landsat 8 OLI/TIRS. The standard deviation analysis on the 23 vegetation indices with 27 samples has resulted in the six highest standard deviations of vegetation indices, termed as GRVI, SR, NLI, SIPI, GEMI and LAI. The standard deviation values are 0.47; 0.43; 0.30; 0.17; 0.16 and 0.13. Regression correlation analysis on the 23 vegetation indices with 280 samples has resulted in the six vegetation indices, termed as NDVI, ENDVI, GDVI, VARI, LAI and SIPI. This was performed based on regression correlation with the lowest value R2 than 0,8. The combined analysis of the standard deviation and the regression correlation has obtained the five vegetation indices, termed as NDVI, ENDVI, GDVI, LAI and SIPI. The results of the analysis of both methods show that a combination of two methods needs to be done to produce a good analysis of sugarcane conditions. It has been clarified through field surveys and showed good results for the prediction of microseepages.

  8. [Quality assurance from the viewpoint of the x-ray film industry].

    PubMed

    von Volkmann, T

    1992-08-01

    The parameters of a film-screen-combination are listed in the directive to section 16 of the german X-ray Regulation. These parameters are determined by methods described in DIN standards and published by the manufacturer. Comparable but less precise parameters are determined in the Acceptance Test. For physical reasons it is not possible to determine the speed of an X-ray film or the intensification factor of a screen separately. The films, screens and processing chemicals delivered by the members of the manufacturer association ZVEI are kept below a deviation (expressed as relative contribution to the system speed S) of +/- 10% for the majority of products, the upper limit is +/- 15%. Poor storage and transport conditions may adversely affect the quality of X-ray films. A special labeling of the film box shall serve to guarantee safe distribution channels. The processing conditions are adjusted at the Acceptance Test according to the manufacturers recommendations. The Constancy Test of film processing serves to maintain these correct conditions. Methods deviating from the DIN-method are of limited (Bayerische method) or no value (Stuttgart method).

  9. Search for dark photons from neutral meson decays in p +p and d +Au collisions at √{sN N}=200 GeV

    NASA Astrophysics Data System (ADS)

    Adare, A.; Afanasiev, S.; Aidala, C.; Ajitanand, N. N.; Akiba, Y.; Akimoto, R.; Al-Bataineh, H.; Al-Ta'Ani, H.; Alexander, J.; Alfred, M.; Andrews, K. R.; Angerami, A.; Aoki, K.; Apadula, N.; Aphecetche, L.; Appelt, E.; Aramaki, Y.; Armendariz, R.; Asai, J.; Asano, H.; Aschenauer, E. C.; Atomssa, E. T.; Averbeck, R.; Awes, T. C.; Azmoun, B.; Babintsev, V.; Bai, M.; Baksay, G.; Baksay, L.; Baldisseri, A.; Bandara, N. S.; Bannier, B.; Barish, K. N.; Barnes, P. D.; Bassalleck, B.; Basye, A. T.; Bathe, S.; Batsouli, S.; Baublis, V.; Baumann, C.; Bazilevsky, A.; Beaumier, M.; Beckman, S.; Belikov, S.; Belmont, R.; Ben-Benjamin, J.; Bennett, R.; Berdnikov, A.; Berdnikov, Y.; Bhom, J. H.; Bickley, A. A.; Black, D.; Blau, D. S.; Boissevain, J. G.; Bok, J. S.; Borel, H.; Boyle, K.; Brooks, M. L.; Broxmeyer, D.; Bryslawskyj, J.; Buesching, H.; Bumazhnov, V.; Bunce, G.; Butsyk, S.; Camacho, C. M.; Campbell, S.; Caringi, A.; Castera, P.; Chang, B. S.; Chang, W. C.; Charvet, J.-L.; Chen, C.-H.; Chernichenko, S.; Chi, C. Y.; Chiu, M.; Choi, I. J.; Choi, J. B.; Choudhury, R. K.; Christiansen, P.; Chujo, T.; Chung, P.; Churyn, A.; Chvala, O.; Cianciolo, V.; Citron, Z.; Cole, B. A.; Conesa Del Valle, Z.; Connors, M.; Constantin, P.; Csanád, M.; Csörgő, T.; Dahms, T.; Dairaku, S.; Danchev, I.; Das, K.; Datta, A.; Daugherity, M. S.; David, G.; Dayananda, M. K.; Deblasio, K.; Dehmelt, K.; Denisov, A.; D'Enterria, D.; Deshpande, A.; Desmond, E. J.; Dharmawardane, K. V.; Dietzsch, O.; Ding, L.; Dion, A.; Do, J. H.; Donadelli, M.; Drapier, O.; Drees, A.; Drees, K. A.; Dubey, A. K.; Durham, J. M.; Durum, A.; Dutta, D.; Dzhordzhadze, V.; D'Orazio, L.; Edwards, S.; Efremenko, Y. V.; Ellinghaus, F.; Engelmore, T.; Enokizono, A.; En'yo, H.; Esumi, S.; Eyser, K. O.; Fadem, B.; Feege, N.; Fields, D. E.; Finger, M.; Finger, M.; Fleuret, F.; Fokin, S. L.; Fraenkel, Z.; Frantz, J. E.; Franz, A.; Frawley, A. D.; Fujiwara, K.; Fukao, Y.; Fusayasu, T.; Gal, C.; Gallus, P.; Garg, P.; Garishvili, I.; Ge, H.; Giordano, F.; Glenn, A.; Gong, H.; Gong, X.; Gonin, M.; Gosset, J.; Goto, Y.; Granier de Cassagnac, R.; Grau, N.; Greene, S. V.; Grim, G.; Grosse Perdekamp, M.; Gu, Y.; Gunji, T.; Guo, L.; Guragain, H.; Gustafsson, H.-Å.; Hachiya, T.; Hadj Henni, A.; Haggerty, J. S.; Hahn, K. I.; Hamagaki, H.; Hamblen, J.; Han, R.; Han, S. Y.; Hanks, J.; Harper, C.; Hartouni, E. P.; Haruna, K.; Hasegawa, S.; Hashimoto, K.; Haslum, E.; Hayano, R.; He, X.; Heffner, M.; Hemmick, T. K.; Hester, T.; Hill, J. C.; Hohlmann, M.; Hollis, R. S.; Holzmann, W.; Homma, K.; Hong, B.; Horaguchi, T.; Hori, Y.; Hornback, D.; Hoshino, T.; Huang, J.; Huang, S.; Ichihara, T.; Ichimiya, R.; Iinuma, H.; Ikeda, Y.; Imai, K.; Imazu, Y.; Imrek, J.; Inaba, M.; Iordanova, A.; Isenhower, D.; Ishihara, M.; Isobe, T.; Issah, M.; Isupov, A.; Ivanischev, D.; Ivanishchev, D.; Iwanaga, Y.; Jacak, B. V.; Jeon, S. J.; Jezghani, M.; Jia, J.; Jiang, X.; Jin, J.; John, D.; Johnson, B. M.; Jones, T.; Joo, E.; Joo, K. S.; Jouan, D.; Jumper, D. S.; Kajihara, F.; Kametani, S.; Kamihara, N.; Kamin, J.; Kaneti, S.; Kang, B. H.; Kang, J. H.; Kang, J. S.; Kapustinsky, J.; Karatsu, K.; Kasai, M.; Kawall, D.; Kawashima, M.; Kazantsev, A. V.; Kempel, T.; Key, J. A.; Khachatryan, V.; Khanzadeev, A.; Kihara, K.; Kijima, K. M.; Kikuchi, J.; Kim, A.; Kim, B. I.; Kim, C.; Kim, D. H.; Kim, D. J.; Kim, E.; Kim, E.-J.; Kim, H.-J.; Kim, M.; Kim, S. H.; Kim, Y.-J.; Kim, Y. K.; Kinney, E.; Kiriluk, K.; Kiss, Á.; Kistenev, E.; Klatsky, J.; Klay, J.; Klein-Boesing, C.; Kleinjan, D.; Kline, P.; Koblesky, T.; Kochenda, L.; Kofarago, M.; Komkov, B.; Konno, M.; Koster, J.; Kotov, D.; Kozlov, A.; Král, A.; Kravitz, A.; Kunde, G. J.; Kurita, K.; Kurosawa, M.; Kweon, M. J.; Kwon, Y.; Kyle, G. S.; Lacey, R.; Lai, Y. S.; Lajoie, J. G.; Layton, D.; Lebedev, A.; Lee, D. M.; Lee, J.; Lee, K. B.; Lee, K. S.; Lee, S. H.; Lee, S. R.; Lee, T.; Leitch, M. J.; Leite, M. A. L.; Leitgab, M.; Lenzi, B.; Li, X.; Lichtenwalner, P.; Liebing, P.; Lim, S. H.; Linden Levy, L. A.; Liška, T.; Litvinenko, A.; Liu, H.; Liu, M. X.; Love, B.; Lynch, D.; Maguire, C. F.; Makdisi, Y. I.; Makek, M.; Malakhov, A.; Malik, M. D.; Manion, A.; Manko, V. I.; Mannel, E.; Mao, Y.; Mašek, L.; Masui, H.; Matathias, F.; McCumber, M.; McGaughey, P. L.; McGlinchey, D.; McKinney, C.; Means, N.; Meles, A.; Mendoza, M.; Meredith, B.; Miake, Y.; Mibe, T.; Mignerey, A. C.; Mikeš, P.; Miki, K.; Miller, A. J.; Milov, A.; Mishra, D. K.; Mishra, M.; Mitchell, J. T.; Miyachi, Y.; Miyasaka, S.; Mizuno, S.; Mohanty, A. K.; Montuenga, P.; Moon, H. J.; Moon, T.; Morino, Y.; Morreale, A.; Morrison, D. P.; Motschwiller, S.; Moukhanova, T. V.; Mukhopadhyay, D.; Murakami, T.; Murata, J.; Mwai, A.; Nagamiya, S.; Nagle, J. L.; Naglis, M.; Nagy, M. I.; Nakagawa, I.; Nakagomi, H.; Nakamiya, Y.; Nakamura, K. R.; Nakamura, T.; Nakano, K.; Nam, S.; Nattrass, C.; Netrakanti, P. K.; Newby, J.; Nguyen, M.; Nihashi, M.; Niida, T.; Nouicer, R.; Novitzky, N.; Nyanin, A. S.; Oakley, C.; O'Brien, E.; Oda, S. X.; Ogilvie, C. A.; Oka, M.; Okada, K.; Onuki, Y.; Orjuela Koop, J. D.; Oskarsson, A.; Ouchida, M.; Ozaki, H.; Ozawa, K.; Pak, R.; Palounek, A. P. T.; Pantuev, V.; Papavassiliou, V.; Park, B. H.; Park, I. H.; Park, J.; Park, S.; Park, S. K.; Park, W. J.; Pate, S. F.; Patel, L.; Patel, M.; Pei, H.; Peng, J.-C.; Pereira, H.; Perepelitsa, D. V.; Perera, G. D. N.; Peresedov, V.; Peressounko, D. Yu.; Perry, J.; Petti, R.; Pinkenburg, C.; Pinson, R.; Pisani, R. P.; Proissl, M.; Purschke, M. L.; Purwar, A. K.; Qu, H.; Rak, J.; Rakotozafindrabe, A.; Ravinovich, I.; Read, K. F.; Rembeczki, S.; Reygers, K.; Reynolds, D.; Riabov, V.; Riabov, Y.; Richardson, E.; Riveli, N.; Roach, D.; Roche, G.; Rolnick, S. D.; Rosati, M.; Rosen, C. A.; Rosendahl, S. S. E.; Rosnet, P.; Rowan, Z.; Rubin, J. G.; Rukoyatkin, P.; Ružička, P.; Rykov, V. L.; Sahlmueller, B.; Saito, N.; Sakaguchi, T.; Sakai, S.; Sakashita, K.; Sako, H.; Samsonov, V.; Sano, S.; Sarsour, M.; Sato, S.; Sato, T.; Savastio, M.; Sawada, S.; Schaefer, B.; Schmoll, B. K.; Sedgwick, K.; Seele, J.; Seidl, R.; Semenov, A. Yu.; Semenov, V.; Sen, A.; Seto, R.; Sett, P.; Sexton, A.; Sharma, D.; Shein, I.; Shibata, T.-A.; Shigaki, K.; Shim, H. H.; Shimomura, M.; Shoji, K.; Shukla, P.; Sickles, A.; Silva, C. L.; Silvermyr, D.; Silvestre, C.; Sim, K. S.; Singh, B. K.; Singh, C. P.; Singh, V.; Slunečka, M.; Sodre, T.; Soldatov, A.; Soltz, R. A.; Sondheim, W. E.; Sorensen, S. P.; Sourikova, I. V.; Staley, F.; Stankus, P. W.; Stenlund, E.; Stepanov, M.; Ster, A.; Stoll, S. P.; Sugitate, T.; Suire, C.; Sukhanov, A.; Sumita, T.; Sun, J.; Sziklai, J.; Takagui, E. M.; Takahara, A.; Taketani, A.; Tanabe, R.; Tanaka, Y.; Taneja, S.; Tanida, K.; Tannenbaum, M. J.; Tarafdar, S.; Taranenko, A.; Tarján, P.; Tennant, E.; Themann, H.; Thomas, D.; Thomas, T. L.; Timilsina, A.; Todoroki, T.; Togawa, M.; Toia, A.; Tomášek, L.; Tomášek, M.; Tomita, Y.; Torii, H.; Towell, M.; Towell, R.; Towell, R. S.; Tram, V.-N.; Tserruya, I.; Tsuchimoto, Y.; Utsunomiya, K.; Vale, C.; Valle, H.; van Hecke, H. W.; Vargyas, M.; Vazquez-Zambrano, E.; Veicht, A.; Velkovska, J.; Vértesi, R.; Vinogradov, A. A.; Virius, M.; Vossen, A.; Vrba, V.; Vznuzdaev, E.; Wang, X. R.; Watanabe, D.; Watanabe, K.; Watanabe, Y.; Watanabe, Y. S.; Wei, F.; Wei, R.; Wessels, J.; Whitaker, S.; White, S. N.; Winter, D.; Wolin, S.; Woody, C. L.; Wright, R. M.; Wysocki, M.; Xia, B.; Xie, W.; Xue, L.; Yalcin, S.; Yamaguchi, Y. L.; Yamaura, K.; Yang, R.; Yanovich, A.; Ying, J.; Yokkaichi, S.; Yoo, J. S.; Yoon, I.; You, Z.; Young, G. R.; Younus, I.; Yushmanov, I. E.; Zajc, W. A.; Zaudtke, O.; Zelenski, A.; Zhang, C.; Zhou, S.; Zolin, L.; Phenix Collaboration

    2015-03-01

    The standard model (SM) of particle physics is spectacularly successful, yet the measured value of the muon anomalous magnetic moment (g-2 ) μ deviates from SM calculations by 3.6 σ . Several theoretical models attribute this to the existence of a "dark photon," an additional U(1) gauge boson, which is weakly coupled to ordinary photons. The PHENIX experiment at the Relativistic Heavy Ion Collider has searched for a dark photon, U , in π0,η →γ e+e- decays and obtained upper limits of O (2 ×10-6) on U -γ mixing at 90% C.L. for the mass range 30

  10. Search for dark photons from neutral meson decays in p+p and d+Au collisions at √s NN = 200 GeV

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Adare, A.; Afanasiev, S.; Aidala, C.

    In this study, the standard model (SM) of particle physics is spectacularly successful, yet the measured value of the muon anomalous magnetic moment (g-2) μ deviates from SM calculations by 3.6σ. Several theoretical models attribute this to the existence of a “dark photon,” an additional U(1) gauge boson, which is weakly coupled to ordinary photons. The PHENIX experiment at the Relativistic Heavy Ion Collider has searched for a dark photon, U, in π⁰, η → γe⁺e⁻ decays and obtained upper limits of O(2×10⁻⁶) on U-γ mixing at 90% CL for the mass range 30 < m U < 90 MeV/c².more » Combined with other experimental limits, the remaining region in the U-γ mixing parameter space that can explain the (g-2) μ deviation from its SM value is nearly completely excluded at the 90% confidence level, with only a small region of 29 < m U < 32 MeV/c² remaining.« less

  11. Search for dark photons from neutral meson decays in p+p and d+Au collisions at √s NN = 200 GeV

    DOE PAGES

    Adare, A.; Afanasiev, S.; Aidala, C.; ...

    2015-03-10

    In this study, the standard model (SM) of particle physics is spectacularly successful, yet the measured value of the muon anomalous magnetic moment (g-2) μ deviates from SM calculations by 3.6σ. Several theoretical models attribute this to the existence of a “dark photon,” an additional U(1) gauge boson, which is weakly coupled to ordinary photons. The PHENIX experiment at the Relativistic Heavy Ion Collider has searched for a dark photon, U, in π⁰, η → γe⁺e⁻ decays and obtained upper limits of O(2×10⁻⁶) on U-γ mixing at 90% CL for the mass range 30 < m U < 90 MeV/c².more » Combined with other experimental limits, the remaining region in the U-γ mixing parameter space that can explain the (g-2) μ deviation from its SM value is nearly completely excluded at the 90% confidence level, with only a small region of 29 < m U < 32 MeV/c² remaining.« less

  12. Remote auditing of radiotherapy facilities using optically stimulated luminescence dosimeters

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lye, Jessica, E-mail: jessica.lye@arpansa.gov.au; Dunn, Leon; Kenny, John

    Purpose: On 1 July 2012, the Australian Clinical Dosimetry Service (ACDS) released its Optically Stimulated Luminescent Dosimeter (OSLD) Level I audit, replacing the previous TLD based audit. The aim of this work is to present the results from this new service and the complete uncertainty analysis on which the audit tolerances are based. Methods: The audit release was preceded by a rigorous evaluation of the InLight® nanoDot OSLD system from Landauer (Landauer, Inc., Glenwood, IL). Energy dependence, signal fading from multiple irradiations, batch variation, reader variation, and dose response factors were identified and quantified for each individual OSLD. The detectorsmore » are mailed to the facility in small PMMA blocks, based on the design of the existing Radiological Physics Centre audit. Modeling and measurement were used to determine a factor that could convert the dose measured in the PMMA block, to dose in water for the facility's reference conditions. This factor is dependent on the beam spectrum. The TPR{sub 20,10} was used as the beam quality index to determine the specific block factor for a beam being audited. The audit tolerance was defined using a rigorous uncertainty calculation. The audit outcome is then determined using a scientifically based two tiered action level approach. Audit outcomes within two standard deviations were defined as Pass (Optimal Level), within three standard deviations as Pass (Action Level), and outside of three standard deviations the outcome is Fail (Out of Tolerance). Results: To-date the ACDS has audited 108 photon beams with TLD and 162 photon beams with OSLD. The TLD audit results had an average deviation from ACDS of 0.0% and a standard deviation of 1.8%. The OSLD audit results had an average deviation of −0.2% and a standard deviation of 1.4%. The relative combined standard uncertainty was calculated to be 1.3% (1σ). Pass (Optimal Level) was reduced to ≤2.6% (2σ), and Fail (Out of Tolerance) was reduced to >3.9% (3σ) for the new OSLD audit. Previously with the TLD audit the Pass (Optimal Level) and Fail (Out of Tolerance) were set at ≤4.0% (2σ) and >6.0% (3σ). Conclusions: The calculated standard uncertainty of 1.3% at one standard deviation is consistent with the measured standard deviation of 1.4% from the audits and confirming the suitability of the uncertainty budget derived audit tolerances. The OSLD audit shows greater accuracy than the previous TLD audit, justifying the reduction in audit tolerances. In the TLD audit, all outcomes were Pass (Optimal Level) suggesting that the tolerances were too conservative. In the OSLD audit 94% of the audits have resulted in Pass (Optimal level) and 6% of the audits have resulted in Pass (Action Level). All Pass (Action level) results have been resolved with a repeat OSLD audit, or an on-site ion chamber measurement.« less

  13. Dental Age Estimation (DAE): Data management for tooth development stages including the third molar. Appropriate censoring of Stage H, the final stage of tooth development.

    PubMed

    Roberts, Graham J; McDonald, Fraser; Andiappan, Manoharan; Lucas, Victoria S

    2015-11-01

    The final stage of dental development of third molars is usually helpful to indicate whether or not a subject is aged over 18 years. A complexity is that the final stage of development is unlimited in its upper border. Investigators usually select an inappropriate upper age limit or censor point for this tooth development stage. The literature was searched for appropriate data sets for dental age estimation and those that provided the count (n), the mean (x¯), and the standard deviation (sd) for each of the tooth development stages. The Demirjian G and Demirjian H were used for this study. Upper and lower limits of the Stage G and Stage H data were calculated limiting the data to plus or minus three standard deviations from the mean. The upper border of Stage H was limited by appropriate censoring at the maximum value for Stage G. The maximum age at attainment from published data, for Stage H, ranged from 22.60 years to 34.50 years. These data were explored to demonstrate how censoring provides an estimate for the correct maximum age for the final stage of Stage H as 21.64 years for UK Caucasians. This study shows that confining the data array of individual tooth developments stages to ± 3sd provides a reliable and logical way of censoring the data for tooth development stages with a Normal distribution of data. For Stage H this is inappropriate as it is unbounded in its upper limit. The use of a censored data array for Stage H using Percentile values is appropriate. This increases the reliability of using third molar Stage H alone to determine whether or not an individual is over 18 years old. For Stage H, individual ancestral groups should be censored using the same technique. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  14. Global analysis of fermion mixing with exotics

    NASA Technical Reports Server (NTRS)

    Nardi, Enrico; Roulet, Esteban; Tommasini, Daniele

    1991-01-01

    The limits are analyzed on deviation of the lepton and quark weak-couplings from their standard model values in a general class of models where the known fermions are allowed to mix with new heavy particles with exotic SU(2) x U(1) quantum number assignments (left-handed singlets or right-handed doublets). These mixings appear in many extensions of the electroweak theory such as models with mirror fermions, E(sub 6) models, etc. The results update previous analyses and improve considerably the existing bounds.

  15. Normative Bilateral Brainstem Evoked Response Data for a Naval Aviation Student Population: Group Statistics

    DTIC Science & Technology

    1979-08-07

    laus levels of the present study all fall within the plus and sinus one -standard deviation boundar; limits of the composite laboratory data plotted by...to be the case in the present study in that the =pz!Aude of the contralateral response prtduced by a given stimulus level follcuzd, in general, that...equivalent Gaussian distribution was applied to Cia study data. Such an analysis, performed by Thornton (36) on the latcncy and amplitude measurements

  16. Determination of silver in irons and steels by atomic-absorption spectrometry with an induction furnace: Direct analysis of solid samples.

    PubMed

    Aziz-Alrahman, A M; Headridge, J B

    1978-07-01

    The silver contents of 17 irons and steels have been determined by dropping 0.5-20mg of millings or turnings of the metals into an induction furnace situated within an atomic-absorption spectrophotometer. The limit of detection was 0.005 mug/g and the relative standard deviations were 12% or better for silver contents of not less than 0.05 mug/g. Samples are added to the furnace at 4-5 min intervals.

  17. Spectrophotometric flow injection determination of total phosphorus in beer using on-line UV/thermal induced digestion.

    PubMed

    Fernandes, S M; Lima, J L; Rangel, A O

    2000-01-01

    A flow injection system for the automatic determination of total phosphorus in beer is described. The developed manifold uses a two-stage photooxidation/thermal digestion procedure together with oxidizing and hydrolyzing reagents to convert all forms of phosphorus compounds to orthophosphate. Polyphosphates are hydrolyzed by acid and heat, and organo-phosphates are digested by UV-catalyzed peroxodisulfate oxidation. The orthophosphate formed is then spectrophotometrically determined by the phosphomolybdenum blue reaction, using stannous chloride as reducing agent. The results obtained for a set of 19 beer samples (with concentrations from 120 to 735 mg P/L) were in good agreement with the reference method, the maximum relative deviation found being 4.7%. Relative standard deviations for ten consecutive determinations were lower than 1.5%, and a detection limit of 1 mg P/L was achieved.

  18. Collinearity in Least-Squares Analysis

    ERIC Educational Resources Information Center

    de Levie, Robert

    2012-01-01

    How useful are the standard deviations per se, and how reliable are results derived from several least-squares coefficients and their associated standard deviations? When the output parameters obtained from a least-squares analysis are mutually independent, as is often assumed, they are reliable estimators of imprecision and so are the functions…

  19. Robust Confidence Interval for a Ratio of Standard Deviations

    ERIC Educational Resources Information Center

    Bonett, Douglas G.

    2006-01-01

    Comparing variability of test scores across alternate forms, test conditions, or subpopulations is a fundamental problem in psychometrics. A confidence interval for a ratio of standard deviations is proposed that performs as well as the classic method with normal distributions and performs dramatically better with nonnormal distributions. A simple…

  20. Standard Deviation for Small Samples

    ERIC Educational Resources Information Center

    Joarder, Anwar H.; Latif, Raja M.

    2006-01-01

    Neater representations for variance are given for small sample sizes, especially for 3 and 4. With these representations, variance can be calculated without a calculator if sample sizes are small and observations are integers, and an upper bound for the standard deviation is immediate. Accessible proofs of lower and upper bounds are presented for…

  1. Estimating maize water stress by standard deviation of canopy temperature in thermal imagery

    USDA-ARS?s Scientific Manuscript database

    A new crop water stress index using standard deviation of canopy temperature as an input was developed to monitor crop water status. In this study, thermal imagery was taken from maize under various levels of deficit irrigation treatments in different crop growing stages. The Expectation-Maximizatio...

  2. Competitive separation of di- vs. mono-valent cations in electrodialysis: effects of the boundary layer properties.

    PubMed

    Kim, Younggy; Walker, W Shane; Lawler, Desmond F

    2012-05-01

    In electrodialysis desalination, the boundary layer near ion-exchange membranes is the limiting region for the overall rate of ionic separation due to concentration polarization over tens of micrometers in that layer. Under high current conditions, this sharp concentration gradient, creating substantial ionic diffusion, can drive a preferential separation for certain ions depending on their concentration and diffusivity in the solution. Thus, this study tested a hypothesis that the boundary layer affects the competitive transport between di- and mono-valent cations, which is known to be governed primarily by the partitioning with cation-exchange membranes. A laboratory-scale electrodialyzer was operated at steady state with a mixture of 10mM KCl and 10mM CaCl(2) at various flow rates. Increased flows increased the relative calcium transport. A two-dimensional model was built with analytical solutions of the Nernst-Planck equation. In the model, the boundary layer thickness was considered as a random variable defined with three statistical parameters: mean, standard deviation, and correlation coefficient between the thicknesses of the two boundary layers facing across a spacer. Model simulations with the Monte Carlo method found that a greater calcium separation was achieved with a smaller mean, greater standard deviation, or more negative correlation coefficient. The model and experimental results were compared for the cationic transport number as well as the current and potential relationship. The mean boundary layer thickness was found to decrease from 40 to less than 10 μm as the superficial water velocity increased from 1.06 to 4.24 cm/s. The standard deviation was greater than the mean thickness at slower water velocities and smaller at faster water velocities. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Evaluation of different methods for determining growing degree-day thresholds in apricot cultivars

    NASA Astrophysics Data System (ADS)

    Ruml, Mirjana; Vuković, Ana; Milatović, Dragan

    2010-07-01

    The aim of this study was to examine different methods for determining growing degree-day (GDD) threshold temperatures for two phenological stages (full bloom and harvest) and select the optimal thresholds for a greater number of apricot ( Prunus armeniaca L.) cultivars grown in the Belgrade region. A 10-year data series were used to conduct the study. Several commonly used methods to determine the threshold temperatures from field observation were evaluated: (1) the least standard deviation in GDD; (2) the least standard deviation in days; (3) the least coefficient of variation in GDD; (4) regression coefficient; (5) the least standard deviation in days with a mean temperature above the threshold; (6) the least coefficient of variation in days with a mean temperature above the threshold; and (7) the smallest root mean square error between the observed and predicted number of days. In addition, two methods for calculating daily GDD, and two methods for calculating daily mean air temperatures were tested to emphasize the differences that can arise by different interpretations of basic GDD equation. The best agreement with observations was attained by method (7). The lower threshold temperature obtained by this method differed among cultivars from -5.6 to -1.7°C for full bloom, and from -0.5 to 6.6°C for harvest. However, the “Null” method (lower threshold set to 0°C) and “Fixed Value” method (lower threshold set to -2°C for full bloom and to 3°C for harvest) gave very good results. The limitations of the widely used method (1) and methods (5) and (6), which generally performed worst, are discussed in the paper.

  4. Precision measurement of the weak charge of the proton.

    PubMed

    2018-05-01

    Large experimental programmes in the fields of nuclear and particle physics search for evidence of physics beyond that explained by current theories. The observation of the Higgs boson completed the set of particles predicted by the standard model, which currently provides the best description of fundamental particles and forces. However, this theory's limitations include a failure to predict fundamental parameters, such as the mass of the Higgs boson, and the inability to account for dark matter and energy, gravity, and the matter-antimatter asymmetry in the Universe, among other phenomena. These limitations have inspired searches for physics beyond the standard model in the post-Higgs era through the direct production of additional particles at high-energy accelerators, which have so far been unsuccessful. Examples include searches for supersymmetric particles, which connect bosons (integer-spin particles) with fermions (half-integer-spin particles), and for leptoquarks, which mix the fundamental quarks with leptons. Alternatively, indirect searches using precise measurements of well predicted standard-model observables allow highly targeted alternative tests for physics beyond the standard model because they can reach mass and energy scales beyond those directly accessible by today's high-energy accelerators. Such an indirect search aims to determine the weak charge of the proton, which defines the strength of the proton's interaction with other particles via the well known neutral electroweak force. Because parity symmetry (invariance under the spatial inversion (x, y, z) → (-x, -y, -z)) is violated only in the weak interaction, it provides a tool with which to isolate the weak interaction and thus to measure the proton's weak charge 1 . Here we report the value 0.0719 ± 0.0045, where the uncertainty is one standard deviation, derived from our measured parity-violating asymmetry in the scattering of polarized electrons on protons, which is -226.5 ± 9.3 parts per billion (the uncertainty is one standard deviation). Our value for the proton's weak charge is in excellent agreement with the standard model 2 and sets multi-teraelectronvolt-scale constraints on any semi-leptonic parity-violating physics not described within the standard model. Our results show that precision parity-violating measurements enable searches for physics beyond the standard model that can compete with direct searches at high-energy accelerators and, together with astronomical observations, can provide fertile approaches to probing higher mass scales.

  5. Qualitative computer aided evaluation of dental impressions in vivo.

    PubMed

    Luthardt, Ralph G; Koch, Rainer; Rudolph, Heike; Walter, Michael H

    2006-01-01

    Clinical investigations dealing with the precision of different impression techniques are rare. Objective of the present study was to develop and evaluate a procedure for the qualitative analysis of the three-dimensional impression precision based on an established in-vitro procedure. The zero hypothesis to be tested was that the precision of impressions does not differ depending on the impression technique used (single-step, monophase and two-step-techniques) and on clinical variables. Digital surface data of patient's teeth prepared for crowns were gathered from standardized manufactured master casts after impressions with three different techniques were taken in a randomized order. Data-sets were analyzed for each patient in comparison with the one-step impression chosen as the reference. The qualitative analysis was limited to data-points within the 99.5%-range. Based on the color-coded representation areas with maximum deviations were determined (preparation margin and the mantle and occlusal surface). To qualitatively analyze the precision of the impression techniques, the hypothesis was tested in linear models for repeated measures factors (p < 0.05). For the positive 99.5% deviations no variables with significant influence were determined in the statistical analysis. In contrast, the impression technique and the position of the preparation margin significantly influenced the negative 99.5% deviations. The influence of clinical parameter on the deviations between impression techniques can be determined reliably using the 99.5 percentile of the deviations. An analysis regarding the areas with maximum deviations showed high clinical relevance. The preparation margin was pointed out as the weak spot of impression taking.

  6. YALE NATURAL RADIOCARBON MEASUREMENTS. PART VI

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Stuiver, M.; Deevey, E.S.

    1961-01-01

    Most of the measurements made since publication of Yale V are included; some measurements, such as a series collected in Greenland, are withneld pending additional information or field work that will make better interpretations possible. In addition to radiocarbon dates of geologic and/or archaeologic interest, recent assays are given of C/sup 14/ in lake waters and other lacustrine materials, now normalized for C/sup 13/ content. The newly accepted convention is followed in expressing normalized C/sup 14/ values as DELTA = delta C/sup 14/ (2 delta C/sup 13/ + 50)STAl + ( delta C/sup 14//1000)! where DELTA is the per milmore » deviation of the C/sup 14/ if the sample from any contemporary standard (whether organic or a carbonate) after correction of sample and/or standard for real age, for the Suess effect, for normal isotopic fractionation, and for deviations of C/sup 14/ content of the age- and pollution- corrected l9th-century wood standard from that of 95% of the NBS oxalic acid standard; delta C/sup 14/ is the measured deviation from 95% of the NBS standard, and delta C/sup 13/ is the deviation from the NBS limestone standard, both in per mil. These assays are variously affected by artificial C/sup 14/ resulting from nuclear tests. (auth)« less

  7. Procedures for determination of detection limits: application to high-performance liquid chromatography analysis of fat-soluble vitamins in human serum.

    PubMed

    Browne, Richard W; Whitcomb, Brian W

    2010-07-01

    Problems in the analysis of laboratory data commonly arise in epidemiologic studies in which biomarkers subject to lower detection thresholds are used. Various thresholds exist including limit of detection (LOD), limit of quantification (LOQ), and limit of blank (LOB). Choosing appropriate strategies for dealing with data affected by such limits relies on proper understanding of the nature of the detection limit and its determination. In this paper, we demonstrate experimental and statistical procedures generally used for estimating different detection limits according to standard procedures in the context of analysis of fat-soluble vitamins and micronutrients in human serum. Fat-soluble vitamins and micronutrients were analyzed by high-performance liquid chromatography with diode array detection. A simulated serum matrix blank was repeatedly analyzed for determination of LOB parametrically by using the observed blank distribution as well as nonparametrically by using ranks. The LOD was determined by combining information regarding the LOB with data from repeated analysis of standard reference materials (SRMs), diluted to low levels; from LOB to 2-3 times LOB. The LOQ was determined experimentally by plotting the observed relative standard deviation (RSD) of SRM replicates compared with the concentration, where the LOQ is the concentration at an RSD of 20%. Experimental approaches and example statistical procedures are given for determination of LOB, LOD, and LOQ. These quantities are reported for each measured analyte. For many analyses, there is considerable information available below the LOQ. Epidemiologic studies must understand the nature of these detection limits and how they have been estimated for appropriate treatment of affected data.

  8. How Many Subjects are Needed for a Visual Field Normative Database? A Comparison of Ground Truth and Bootstrapped Statistics.

    PubMed

    Phu, Jack; Bui, Bang V; Kalloniatis, Michael; Khuu, Sieu K

    2018-03-01

    The number of subjects needed to establish the normative limits for visual field (VF) testing is not known. Using bootstrap resampling, we determined whether the ground truth mean, distribution limits, and standard deviation (SD) could be approximated using different set size ( x ) levels, in order to provide guidance for the number of healthy subjects required to obtain robust VF normative data. We analyzed the 500 Humphrey Field Analyzer (HFA) SITA-Standard results of 116 healthy subjects and 100 HFA full threshold results of 100 psychophysically experienced healthy subjects. These VFs were resampled (bootstrapped) to determine mean sensitivity, distribution limits (5th and 95th percentiles), and SD for different ' x ' and numbers of resamples. We also used the VF results of 122 glaucoma patients to determine the performance of ground truth and bootstrapped results in identifying and quantifying VF defects. An x of 150 (for SITA-Standard) and 60 (for full threshold) produced bootstrapped descriptive statistics that were no longer different to the original distribution limits and SD. Removing outliers produced similar results. Differences between original and bootstrapped limits in detecting glaucomatous defects were minimized at x = 250. Ground truth statistics of VF sensitivities could be approximated using set sizes that are significantly smaller than the original cohort. Outlier removal facilitates the use of Gaussian statistics and does not significantly affect the distribution limits. We provide guidance for choosing the cohort size for different levels of error when performing normative comparisons with glaucoma patients.

  9. Soiling of building envelope surfaces and its effect on solar reflectance – Part III: Interlaboratory study of an accelerated aging method for roofing materials

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sleiman, Mohamad; Chen, Sharon; Gilbert, Haley E.

    A laboratory method to simulate natural exposure of roofing materials has been reported in a companion article. Here in the current article, we describe the results of an international, nine-participant interlaboratory study (ILS) conducted in accordance with ASTM Standard E691-09 to establish the precision and reproducibility of this protocol. The accelerated soiling and weathering method was applied four times by each laboratory to replicate coupons of 12 products representing a wide variety of roofing categories (single-ply membrane, factory-applied coating (on metal), bare metal, field-applied coating, asphalt shingle, modified-bitumen cap sheet, clay tile, and concrete tile). Participants reported initial and laboratory-agedmore » values of solar reflectance and thermal emittance. Measured solar reflectances were consistent within and across eight of the nine participating laboratories. Measured thermal emittances reported by six participants exhibited comparable consistency. For solar reflectance, the accelerated aging method is both repeatable and reproducible within an acceptable range of standard deviations: the repeatability standard deviation sr ranged from 0.008 to 0.015 (relative standard deviation of 1.2–2.1%) and the reproducibility standard deviation sR ranged from 0.022 to 0.036 (relative standard deviation of 3.2–5.8%). The ILS confirmed that the accelerated aging method can be reproduced by multiple independent laboratories with acceptable precision. In conclusion, this study supports the adoption of the accelerated aging practice to speed the evaluation and performance rating of new cool roofing materials.« less

  10. The evaluation of relationship between vitamin D and muscle power by micro manual muscle tester in end-stage renal disease patients.

    PubMed

    Zahed, Nargesosadat; Chehrazi, Saghar; Falaknasi, Kianosh

    2014-09-01

    Muscle force of lower limb is a major factor for sustaining physical activity. Decreased muscle force can limit physical activity, which can increase mortality and morbidity in end-stage renal disease (ESRD) patients. Muscle force depends on several factors. One of the most important factors is 25-hydroxy vitamin D (25-OHD) that affects muscle function in both uremic and non-uremic patients. The aim of this study was to investigate the association between serum level of 25-OHD and muscle force of lower extremities in hemodialysis patients estimated by a Micro Manual Muscle Tester, a digital instrument that measures muscle force in kilograms This cross-sectional study was performed on 135 adult patients, 69 male (51%) and 66 female (69%) (mean: 1.4, standard deviation: 0.5), undergoing hemodialysis. Standard biochemistry parameters were measured before hemodialysis, including 25-OHD, calcium, albumin, para-hyroid hormone and C-reactive protein (CRP). Based on the result of serum level of 25-OHD, patients were classified into the following three groups: 85 patients (63%) were 25-OHD deficient (25-OHD <30), 43 patients (32%) had a normal level of 25-OHD (30-70) and seven patients (5%) had a toxic level of 25-OHD (>70) (mean: 1.42, standard deviation: 0.59). Also, based on the result of muscle force, patients were classified into the following three groups: 84/133 patients (62%) had weak muscle force (<5 kg), 46/133 patients (34%) had normal muscle force (5-10 kg) and three patients (21%) had strong muscle force (>10 kg) (mean: 1.39, standard deviation: 0.53). There was a significant relation between 25-OHD level and muscle force (P = 0.02), between age and muscle force (P = 0.002) and between gender and muscle force (P <0.001). In our opinion, 25-OHD can be a useful drug in ESRD patients to improve muscle force and physical activity.

  11. Selection and Classification Using a Forecast Applicant Pool.

    ERIC Educational Resources Information Center

    Hendrix, William H.

    The document presents a forecast model of the future Air Force applicant pool. By forecasting applicants' quality (means and standard deviations of aptitude scores) and quantity (total number of applicants), a potential enlistee could be compared to the forecasted pool. The data used to develop the model consisted of means, standard deviation, and…

  12. Test of the principle of operation of a wideband magnetic direction finder for lightning return strokes

    NASA Technical Reports Server (NTRS)

    Herrman, B. D.; Uman, M. A.; Brantley, R. D.; Krider, E. P.

    1976-01-01

    The principle of operation of a wideband crossed-loop magnetic-field direction finder is studied by comparing the bearing determined from the NS and EW magnetic fields at various times up to 155 microsec after return stroke initiation with the TV-determined lightning channel base direction. For 40 lightning strokes in the 3 to 12 km range, the difference between the bearings found from magnetic fields sampled at times between 1 and 10 microsec and the TV channel-base data has a standard deviation of 3-4 deg. Included in this standard deviation is a 2-3 deg measurement error. For fields sampled at progressively later times, both the mean and the standard deviation of the difference between the direction-finder bearing and the TV bearing increase. Near 150 microsec, means are about 35 deg and standard deviations about 60 deg. The physical reasons for the late-time inaccuracies in the wideband direction finder and the occurrence of these effects in narrow-band VLF direction finders are considered.

  13. Wavelength selection method with standard deviation: application to pulse oximetry.

    PubMed

    Vazquez-Jaccaud, Camille; Paez, Gonzalo; Strojnik, Marija

    2011-07-01

    Near-infrared spectroscopy provides useful biological information after the radiation has penetrated through the tissue, within the therapeutic window. One of the significant shortcomings of the current applications of spectroscopic techniques to a live subject is that the subject may be uncooperative and the sample undergoes significant temporal variations, due to his health status that, from radiometric point of view, introduce measurement noise. We describe a novel wavelength selection method for monitoring, based on a standard deviation map, that allows low-noise sensitivity. It may be used with spectral transillumination, transmission, or reflection signals, including those corrupted by noise and unavoidable temporal effects. We apply it to the selection of two wavelengths for the case of pulse oximetry. Using spectroscopic data, we generate a map of standard deviation that we propose as a figure-of-merit in the presence of the noise introduced by the living subject. Even in the presence of diverse sources of noise, we identify four wavelength domains with standard deviation, minimally sensitive to temporal noise, and two wavelengths domains with low sensitivity to temporal noise.

  14. How random is a random vector?

    NASA Astrophysics Data System (ADS)

    Eliazar, Iddo

    2015-12-01

    Over 80 years ago Samuel Wilks proposed that the "generalized variance" of a random vector is the determinant of its covariance matrix. To date, the notion and use of the generalized variance is confined only to very specific niches in statistics. In this paper we establish that the "Wilks standard deviation" -the square root of the generalized variance-is indeed the standard deviation of a random vector. We further establish that the "uncorrelation index" -a derivative of the Wilks standard deviation-is a measure of the overall correlation between the components of a random vector. Both the Wilks standard deviation and the uncorrelation index are, respectively, special cases of two general notions that we introduce: "randomness measures" and "independence indices" of random vectors. In turn, these general notions give rise to "randomness diagrams"-tangible planar visualizations that answer the question: How random is a random vector? The notion of "independence indices" yields a novel measure of correlation for Lévy laws. In general, the concepts and results presented in this paper are applicable to any field of science and engineering with random-vectors empirical data.

  15. Estimation of Tooth Size Discrepancies among Different Malocclusion Groups.

    PubMed

    Hasija, Narender; Bala, Madhu; Goyal, Virender

    2014-05-01

    Regards and Tribute: Late Dr Narender Hasija was a mentor and visionary in the light of knowledge and experience. We pay our regards with deepest gratitude to the departed soul to rest in peace. Bolton's ratios help in estimating overbite, overjet relationships, the effects of contemplated extractions on posterior occlusion, incisor relationships and identification of occlusal misfit produced by tooth size discrepancies. To determine any difference in tooth size discrepancy in anterior as well as overall ratio in different malocclusions and comparison with Bolton's study. After measuring the teeth on all 100 patients, Bolton's analysis was performed. Results were compared with Bolton's means and standard deviations. The results were also subjected to statistical analysis. Results show that the mean and standard deviations of ideal occlusion cases are comparable with those Bolton but, when the mean and standard deviation of malocclusion groups are compared with those of Bolton, the values of standard deviation are higher, though the mean is comparable. How to cite this article: Hasija N, Bala M, Goyal V. Estimation of Tooth Size Discrepancies among Different Malocclusion Groups. Int J Clin Pediatr Dent 2014;7(2):82-85.

  16. Association of auricular pressing and heart rate variability in pre-exam anxiety students.

    PubMed

    Wu, Wocao; Chen, Junqi; Zhen, Erchuan; Huang, Huanlin; Zhang, Pei; Wang, Jiao; Ou, Yingyi; Huang, Yong

    2013-03-25

    A total of 30 students scoring between 12 and 20 on the Test Anxiety Scale who had been exhibiting an anxious state > 24 hours, and 30 normal control students were recruited. Indices of heart rate variability were recorded using an Actiheart electrocardiogram recorder at 10 minutes before auricular pressing, in the first half of stimulation and in the second half of stimulation. The results revealed that the standard deviation of all normal to normal intervals and the root mean square of standard deviation of normal to normal intervals were significantly increased after stimulation. The heart rate variability triangular index, very-low-frequency power, low-frequency power, and the ratio of low-frequency to high-frequency power were increased to different degrees after stimulation. Compared with normal controls, the root mean square of standard deviation of normal to normal intervals was significantly increased in anxious students following auricular pressing. These results indicated that auricular pressing can elevate heart rate variability, especially the root mean square of standard deviation of normal to normal intervals in students with pre-exam anxiety.

  17. Association of auricular pressing and heart rate variability in pre-exam anxiety students

    PubMed Central

    Wu, Wocao; Chen, Junqi; Zhen, Erchuan; Huang, Huanlin; Zhang, Pei; Wang, Jiao; Ou, Yingyi; Huang, Yong

    2013-01-01

    A total of 30 students scoring between 12 and 20 on the Test Anxiety Scale who had been exhibiting an anxious state > 24 hours, and 30 normal control students were recruited. Indices of heart rate variability were recorded using an Actiheart electrocardiogram recorder at 10 minutes before auricular pressing, in the first half of stimulation and in the second half of stimulation. The results revealed that the standard deviation of all normal to normal intervals and the root mean square of standard deviation of normal to normal intervals were significantly increased after stimulation. The heart rate variability triangular index, very-low-frequency power, low-frequency power, and the ratio of low-frequency to high-frequency power were increased to different degrees after stimulation. Compared with normal controls, the root mean square of standard deviation of normal to normal intervals was significantly increased in anxious students following auricular pressing. These results indicated that auricular pressing can elevate heart rate variability, especially the root mean square of standard deviation of normal to normal intervals in students with pre-exam anxiety. PMID:25206734

  18. Offshore fatigue design turbulence

    NASA Astrophysics Data System (ADS)

    Larsen, Gunner C.

    2001-07-01

    Fatigue damage on wind turbines is mainly caused by stochastic loading originating from turbulence. While onshore sites display large differences in terrain topology, and thereby also in turbulence conditions, offshore sites are far more homogeneous, as the majority of them are likely to be associated with shallow water areas. However, despite this fact, specific recommendations on offshore turbulence intensities, applicable for fatigue design purposes, are lacking in the present IEC code. This article presents specific guidelines for such loading. These guidelines are based on the statistical analysis of a large number of wind data originating from two Danish shallow water offshore sites. The turbulence standard deviation depends on the mean wind speed, upstream conditions, measuring height and thermal convection. Defining a population of turbulence standard deviations, at a given measuring position, uniquely by the mean wind speed, variations in upstream conditions and atmospheric stability will appear as variability of the turbulence standard deviation. Distributions of such turbulence standard deviations, conditioned on the mean wind speed, are quantified by fitting the measured data to logarithmic Gaussian distributions. By combining a simple heuristic load model with the parametrized conditional probability density functions of the turbulence standard deviations, an empirical offshore design turbulence intensity is determined. For pure stochastic loading (as associated with standstill situations), the design turbulence intensity yields a fatigue damage equal to the average fatigue damage caused by the distributed turbulence intensity. If the stochastic loading is combined with a periodic deterministic loading (as in the normal operating situation), the proposed design turbulence intensity is shown to be conservative.

  19. Estimating extreme stream temperatures by the standard deviate method

    NASA Astrophysics Data System (ADS)

    Bogan, Travis; Othmer, Jonathan; Mohseni, Omid; Stefan, Heinz

    2006-02-01

    It is now widely accepted that global climate warming is taking place on the earth. Among many other effects, a rise in air temperatures is expected to increase stream temperatures indefinitely. However, due to evaporative cooling, stream temperatures do not increase linearly with increasing air temperatures indefinitely. Within the anticipated bounds of climate warming, extreme stream temperatures may therefore not rise substantially. With this concept in mind, past extreme temperatures measured at 720 USGS stream gauging stations were analyzed by the standard deviate method. In this method the highest stream temperatures are expressed as the mean temperature of a measured partial maximum stream temperature series plus its standard deviation multiplied by a factor KE (standard deviate). Various KE-values were explored; values of KE larger than 8 were found physically unreasonable. It is concluded that the value of KE should be in the range from 7 to 8. A unit error in estimating KE translates into a typical stream temperature error of about 0.5 °C. Using a logistic model for the stream temperature/air temperature relationship, a one degree error in air temperature gives a typical error of 0.16 °C in stream temperature. With a projected error in the enveloping standard deviate dKE=1.0 (range 0.5-1.5) and an error in projected high air temperature d Ta=2 °C (range 0-4 °C), the total projected stream temperature error is estimated as d Ts=0.8 °C.

  20. Herschel Extreme Lensing Line Observations: Dynamics of Two Strongly Lensed Star-Forming Galaxies near Redshift z=2*

    NASA Technical Reports Server (NTRS)

    Rhoads, James E.; Rigby, Jane Rebecca; Malhotra, Sangeeta; Allam, Sahar; Carilli, Chris; Combes, Francoise; Finkelstein, Keely; Finkelstein, Steven; Frye, Brenda; Gerin, Maryvonne; hide

    2014-01-01

    We report on two regularly rotating galaxies at redshift z approx. = 2, using high-resolution spectra of the bright [C microns] 158 micrometers emission line from the HIFI instrument on the Herschel Space Observatory. Both SDSS090122.37+181432.3 ("S0901") and SDSSJ120602.09+514229.5 ("the Clone") are strongly lensed and show the double-horned line profile that is typical of rotating gas disks. Using a parametric disk model to fit the emission line profiles, we find that S0901 has a rotation speed of v sin(i) approx. = 120 +/- 7 kms(sup -1) and a gas velocity dispersion of (standard deviation)g < 23 km s(sup -1) (1(standard deviation)). The best-fitting model for the Clone is a rotationally supported disk having v sin(i) approx. = 79 +/- 11 km s(sup -1) and (standard deviation)g 4 kms(sup -1) (1(standard deviation)). However, the Clone is also consistent with a family of dispersion-dominated models having (standard deviation)g = 92 +/- 20 km s(sup -1). Our results showcase the potential of the [C microns] line as a kinematic probe of high-redshift galaxy dynamics: [C microns] is bright, accessible to heterodyne receivers with exquisite velocity resolution, and traces dense star-forming interstellar gas. Future [C microns] line observations with ALMA would offer the further advantage of spatial resolution, allowing a clearer separation between rotation and velocity dispersion.

  1. Search for new physics in the monophoton final state in proton-proton collisions at sqrt(s) = 13 TeV

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sirunyan, Albert M; et al.

    2017-06-12

    A search is conducted for new physics in a final state containing a photon and missing transverse momentum in proton-proton collisions at sqrt(s) = 13 TeV. The data collected by the CMS experiment at the CERN LHC correspond to an integrated luminosity of 12.9 inverse-femtobarns. No deviations are observed relative to the predictions of the standard model. The results are interpreted as exclusion limits on the dark matter production cross sections and parameters in models containing extra spatial dimensions. Improved limits are set with respect to previous searches using the monophoton final state. In particular, the limits on the extramore » dimension model parameters are the most stringent to date in this channel.« less

  2. Search for new physics in the monophoton final state in proton-proton collisions at √{s}=13 TeV

    NASA Astrophysics Data System (ADS)

    Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Waltenberger, W.; Wulz, C.-E.; Dvornikov, O.; Makarenko, V.; Mossolov, V.; Suarez Gonzalez, J.; Zykunov, V.; Shumeiko, N.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Tytgat, M.; Van Driessche, W.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Ruan, M.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; El-khateeb, E.; Elgammal, S.; Mohamed, A.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Kiesel, M. 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R.; Williams, T.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Nash, J.; Nikitenko, A.; Pela, J.; Penning, B.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Squires, M.; Stolp, D.; Tos, K.; Tripathi, M.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Weber, M.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Si, W.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Holzner, A.; Klein, D.; Krutelyov, V.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bendavid, J.; Bornheim, A.; Bunn, J.; Lawhorn, J. M.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Apresyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Wu, Y.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Low, J. F.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Bein, S.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Perry, T.; Prosper, H.; Santra, A.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Forthomme, L.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Apyan, A.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Malta Rodrigues, A.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Rupprecht, N.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Medvedeva, T.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Svyatkovskiy, A.; Tully, C.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Schulte, J. F.; Sun, J.; Wang, F.; Xie, W.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; Belknap, D. A.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

    2017-10-01

    A search is conducted for new physics in a final state containing a photon and missing transverse momentum in proton-proton collisions at √{s}=13 TeV. The data collected by the CMS experiment at the CERN LHC correspond to an integrated luminosity of 12.9 fb-1. No deviations are observed relative to the predictions of the standard model. The results are interpreted as exclusion limits on the dark matter production cross sections and parameters in models containing extra spatial dimensions. Improved limits are set with respect to previous searches using the monophoton final state. In particular, the limits on the extra dimension model parameters are the most stringent to date in this channel. [Figure not available: see fulltext.

  3. Enhancement of absorption and resistance of motion utilizing a multi-channel opto-electronic sensor to effectively monitor physiological signs during sport exercise

    NASA Astrophysics Data System (ADS)

    Alzahrani, Abdullah; Hu, Sijung; Azorin-Peris, Vicente; Barrett, Laura; Esliger, Dale; Hayes, Matthew; Akbare, Shafique; Achart, Jérôme; Kuoch, Sylvain

    2015-03-01

    This study presents an effective engineering approach for human vital signs monitoring as increasingly demanded by personal healthcare. The aim of this work is to study how to capture critical physiological parameters efficiently through a well-constructed electronic system and a robust multi-channel opto-electronic patch sensor (OEPS), together with a wireless communication. A unique design comprising multi-wavelength illumination sources and a rapid response photo sensor with a 3-axis accelerometer enables to recover pulsatile features, compensate motion and increase signal-to-noise ratio. An approved protocol with designated tests was implemented at Loughborough University a UK leader in sport and exercise assessment. The results of sport physiological effects were extracted from the datasets of physical movements, i.e. sitting, standing, waking, running and cycling. t-test, Bland-Altman and correlation analysis were applied to evaluate the performance of the OEPS system against Acti-Graph and Mio-Alpha.There was no difference in heart rate measured using OEPS and both Acti-Graph and Mio-Alpha (both p<0.05). Strong correlations were observed between HR measured from the OEPS and both the Acti-graph and Mio-Alpha (r = 0.96, p<0.001). Bland-Altman analysis for the Acti-Graph and OEPS found the bias 0.85 bpm, the standard deviation 9.20 bpm, and the limits of agreement (LOA) -17.18 bpm to +18.88 bpm for lower and upper limits of agreement respectively, for the Mio-Alpha and OEPS the bias is 1.63 bpm, standard deviation SD8.62 bpm, lower and upper limits of agreement, - 15.27 bpm and +18.58 bpm respectively. The OEPS demonstrates a real time, robust and remote monitoring of cardiovascular function.

  4. Measurement of electroweak-induced production of Wγ with two jets in pp collisions at $$ \\sqrt{s}=8 $$ TeV and constraints on anomalous quartic gauge couplings

    DOE PAGES

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; ...

    2017-06-20

    A measurement of electroweak-induced production of Wγ and two jets is performed, where the W boson decays leptonically. The data used in the analysis correspond to an integrated luminosity of 19.7 fb –1 collected by the CMS experiment in √s = 8 TeV proton-proton collisions produced at the LHC. Candidate events are selected with exactly one muon or electron, missing transverse momentum, one photon, and two jets with large rapidity separation. An excess over the hypothesis of the standard model without electroweak production of Wγ with two jets is observed with a significance of 2.7 standard deviations. The crossmore » section measured in the fiducial region is 10.8 ± 4.1(stat) ± 3.4(syst) ± 0.3(lumi) fb, which is consistent with the standard model electroweak prediction. The total cross section for Wγ in association with two jets in the same fiducial region is measured to be 23.2 ± 4.3(stat) ± 1.7(syst) ± 0.6(lumi) fb, which is consistent with the standard model prediction from the combination of electroweak and quantum chromodynamics-induced processes. As a result, no deviations are observed from the standard model predictions and experimental limits on anomalous quartic gauge couplings f M,0–7/Λ 4, f T,0–2/Λ 4, and f T,5–7/Λ 4 are set at 95% confidence level.« less

  5. Measurement of electroweak-induced production of Wγ with two jets in pp collisions at $$ \\sqrt{s}=8 $$ TeV and constraints on anomalous quartic gauge couplings

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.

    A measurement of electroweak-induced production of Wγ and two jets is performed, where the W boson decays leptonically. The data used in the analysis correspond to an integrated luminosity of 19.7 fb –1 collected by the CMS experiment in √s = 8 TeV proton-proton collisions produced at the LHC. Candidate events are selected with exactly one muon or electron, missing transverse momentum, one photon, and two jets with large rapidity separation. An excess over the hypothesis of the standard model without electroweak production of Wγ with two jets is observed with a significance of 2.7 standard deviations. The crossmore » section measured in the fiducial region is 10.8 ± 4.1(stat) ± 3.4(syst) ± 0.3(lumi) fb, which is consistent with the standard model electroweak prediction. The total cross section for Wγ in association with two jets in the same fiducial region is measured to be 23.2 ± 4.3(stat) ± 1.7(syst) ± 0.6(lumi) fb, which is consistent with the standard model prediction from the combination of electroweak and quantum chromodynamics-induced processes. As a result, no deviations are observed from the standard model predictions and experimental limits on anomalous quartic gauge couplings f M,0–7/Λ 4, f T,0–2/Λ 4, and f T,5–7/Λ 4 are set at 95% confidence level.« less

  6. Simultaneous determination of airborne acetaldehyde, acetone, 2-butanone, and cyclohexanone using sampling tubes with 2,4-dinitrophenylhydrazine-coated solid sorbent.

    PubMed

    Binding, N; Schilder, K; Czeschinski, P A; Witting, U

    1998-08-01

    The 2,4-dinitrophenylhydrazine (2,4-DNPH) derivatization method mainly used for the determination of airborne formaldehyde was extended for acetaldehyde, acetone, 2-butanone, and cyclohexanone, the next four carbonyl compounds of industrial importance. Sampling devices and sampling conditions were adjusted for the respective limit value regulations. Analytical reliability criteria were established and compared to those of other recommended methods. With a minimum analytical range from one tenth to the 3-fold limit value in all cases and with relative standard deviations below 5%, the adjusted method meets all requirements for the reliable quantification of the four compounds in workplace air as well as in ambient air.

  7. Stereospecific analysis of sakuranetin by high-performance liquid chromatography: pharmacokinetic and botanical applications.

    PubMed

    Takemoto, Jody K; Remsberg, Connie M; Yáñez, Jaime A; Vega-Villa, Karina R; Davies, Neal M

    2008-11-01

    A stereospecific method for analysis of sakuranetin was developed. Separation was accomplished using a Chiralpak AD-RH column with UV (ultraviolet) detection at 288 nm. The stereospecific linear calibration curves ranged from 0.5 to 100 microg/mL. The mean extraction efficiency was >98%. Precision of the assay was <12% (relative standard deviation (R.S.D.)%), and within 10% at the limit of quantitation (0.5 microg/mL). Bias of the assay was lower than 10%, and within 5% at the limit of quantitation. The assay was applied successfully to pharmacokinetic quantification in rats, and the stereospecific quantification in oranges, grapefruit juice, and matico (Piper aduncum L.).

  8. Search for contact interactions in dimuon events from pp collisions at √s=7 TeV with the ATLAS detector

    DOE PAGES

    Aad, G.; Abbott, B.; Abdallah, J.; ...

    2011-07-01

    A search for contact interactions has been performed using dimuon events recorded with the ATLAS detector in proton-proton collisions at √s=7 TeV. The data sample corresponds to an integrated luminosity of 42 pb⁻¹. No significant deviation from the standard model is observed in the dimuon mass spectrum, allowing the following 95% C.L. limits to be set on the energy scale of contact interactions: Λ>4.9 TeV (4.5 TeV) for constructive (destructive) interference in the left-left isoscalar compositeness model. These limits are the most stringent to date for μμqq contact interactions.

  9. Search for contact interactions in dimuon events from pp collisions at s=7TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdelalim, A. A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abramowicz, H.; Abreu, H.; Acerbi, E.; Acharya, B. S.; Adams, D. L.; Addy, T. N.; Adelman, J.; Aderholz, M.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Akiyama, A.; Alam, M. S.; Alam, M. A.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Aliyev, M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alviggi, M. G.; Amako, K.; Amaral, P.; Amelung, C.; Ammosov, V. V.; Amorim, A.; Amorós, G.; Amram, N.; Anastopoulos, C.; Andeen, T.; Anders, C. F.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angerami, A.; Anghinolfi, F.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonelli, S.; Antonov, A.; Antos, J.; Anulli, F.; Aoun, S.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Archambault, J. P.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Asfandiyarov, R.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Atoian, G.; Aubert, B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Austin, N.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Bachy, G.; Backes, M.; Backhaus, M.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Baltasar Dos Santos Pedrosa, F.; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barashkou, A.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, D.; Bartsch, V.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Battistoni, G.; Bauer, F.; Bawa, H. S.; Beare, B.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Begel, M.; Behar Harpaz, S.; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Ben Ami, S.; Benary, O.; Benchekroun, D.; Benchouk, C.; Bendel, M.; Benedict, B. H.; Benekos, N.; Benhammou, Y.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernardet, K.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertin, A.; Bertinelli, F.; Bertolucci, F.; Besana, M. I.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blazek, T.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocchetta, S. S.; Bocci, A.; Boddy, C. 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M.; Sellden, B.; Sellers, G.; Seman, M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Seuster, R.; Severini, H.; Sevior, M. E.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shank, J. T.; Shao, Q. T.; Shapiro, M.; Shatalov, P. B.; Shaver, L.; Shaw, C.; Shaw, K.; Sherman, D.; Sherwood, P.; Shibata, A.; Shimizu, S.; Shimojima, M.; Shin, T.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shupe, M. A.; Sicho, P.; Sidoti, A.; Siebel, A.; Siegert, F.; Siegrist, J.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simmons, B.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skovpen, K.; Skubic, P.; Skvorodnev, N.; Slater, M.; Slavicek, T.; Sliwa, K.; Sloan, T. J.; Sloper, J.; Smakhtin, V.; Smirnov, S. Yu.; Smirnova, L. N.; Smirnova, O.; Smith, B. C.; Smith, D.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snow, S. W.; Snow, J.; Snuverink, J.; Snyder, S.; Soares, M.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E.; Soldevila, U.; Solfaroli Camillocci, E.; Solodkov, A. A.; Solovyanov, O. V.; Sondericker, J.; Soni, N.; Sopko, V.; Sopko, B.; Sorbi, M.; Sosebee, M.; Soukharev, A.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spila, F.; Spiriti, E.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R. D.; Stahl, T.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staude, A.; Stavina, P.; Stavropoulos, G.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, K.; Stewart, G. A.; Stillings, J. A.; Stockmanns, T.; Stockton, M. C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Strube, J.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Soh, D. A.; Su, D.; Subramania, Hs.; Succurro, A.; Sugaya, Y.; Sugimoto, T.; Suhr, C.; Suita, K.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Sushkov, S.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Sviridov, Yu. M.; Swedish, S.; Sykora, I.; Sykora, T.; Szeless, B.; Sánchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taga, A.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Talby, M.; Talyshev, A.; Tamsett, M. C.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanaka, Y.; Tani, K.; Tannoury, N.; Tappern, G. P.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tatarkhanov, M.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terwort, M.; Testa, M.; Teuscher, R. J.; Thadome, J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thioye, M.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomson, E.; Thomson, M.; Thun, R. P.; Tic, T.; Tikhomirov, V. O.; Tikhonov, Y. A.; Timmermans, C. J. W. P.; Tipton, P.; Tique Aires Viegas, F. J.; Tisserant, S.; Tobias, J.; Toczek, B.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokunaga, K.; Tokushuku, K.; Tollefson, K.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, G.; Tonoyan, A.; Topfel, C.; Topilin, N. D.; Torchiani, I.; Torrence, E.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Traynor, D.; Trefzger, T.; Treis, J.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Trinh, T. N.; Tripiana, M. F.; Triplett, N.; Trischuk, W.; Trivedi, A.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiakiris, M.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsung, J.-W.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tuggle, J. M.; Turala, M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Tyrvainen, H.; Tzanakos, G.; Uchida, K.; Ueda, I.; Ueno, R.; Ugland, M.; Uhlenbrock, M.; Uhrmacher, M.; Ukegawa, F.; Unal, G.; Underwood, D. G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Urkovsky, E.; Urrejola, P.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valenta, J.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; van der Graaf, H.; van der Kraaij, E.; van der Leeuw, R.; van der Poel, E.; van der Ster, D.; van Eijk, B.; van Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vandelli, W.; Vandoni, G.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Varela Rodriguez, F.; Vari, R.; Varnes, E. W.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Vegni, G.; Veillet, J. J.; Vellidis, C.; Veloso, F.; Veness, R.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Vichou, I.; Vickey, T.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinek, E.; Vinogradov, V. B.; Virchaux, M.; Viret, S.; Virzi, J.; Vitale, A.; Vitells, O.; Viti, M.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobiev, A. P.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T. T.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vukotic, I.; Wagner, W.; Wagner, P.; Wahlen, H.; Wakabayashi, J.; Walbersloh, J.; Walch, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Wang, C.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, J. C.; Wang, R.; Wang, S. M.; Warburton, A.; Ward, C. P.; Warsinsky, M.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, A. T.; Waugh, B. M.; Weber, J.; Weber, M.; Weber, M. S.; Weber, P.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P. S.; Wen, M.; Wenaus, T.; Wendler, S.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Wessels, M.; Weydert, C.; Whalen, K.; Wheeler-Ellis, S. J.; Whitaker, S. P.; White, A.; White, M. J.; White, S.; Whitehead, S. R.; Whiteson, D.; Whittington, D.; Wicek, F.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilhelm, I.; Wilkens, H. G.; Will, J. Z.; Williams, E.; Williams, H. H.; Willis, W.; Willocq, S.; Wilson, J. A.; Wilson, M. G.; Wilson, A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wolter, M. W.; Wolters, H.; Wooden, G.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wraight, K.; Wright, C.; Wrona, B.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wunstorf, R.; Wynne, B. M.; Xaplanteris, L.; Xella, S.; Xie, S.; Xie, Y.; Xu, C.; Xu, D.; Xu, G.; Yabsley, B.; Yamada, M.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U. K.; Yang, Y.; Yang, Y.; Yang, Z.; Yanush, S.; Yao, W.-M.; Yao, Y.; Yasu, Y.; Ybeles Smit, G. V.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Youssef, S.; Yu, D.; Yu, J.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zaets, V. G.; Zaidan, R.; Zaitsev, A. M.; Zajacova, Z.; Zalite, Yo. K.; Zanello, L.; Zarzhitsky, P.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zemla, A.; Zendler, C.; Zenin, A. V.; Zenin, O.; Ženiš, T.; Zenonos, Z.; Zenz, S.; Zerwas, D.; Zevi Della Porta, G.; Zhan, Z.; Zhang, D.; Zhang, H.; Zhang, J.; Zhang, X.; Zhang, Z.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zheng, S.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zieminska, D.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; Zolnierowski, Y.; Zsenei, A.; Zur Nedden, M.; Zutshi, V.; Zwalinski, L.

    2011-07-01

    A search for contact interactions has been performed using dimuon events recorded with the ATLAS detector in proton-proton collisions at s=7TeV. The data sample corresponds to an integrated luminosity of 42pb-1. No significant deviation from the standard model is observed in the dimuon mass spectrum, allowing the following 95% C.L. limits to be set on the energy scale of contact interactions: Λ>4.9TeV (4.5 TeV) for constructive (destructive) interference in the left-left isoscalar compositeness model. These limits are the most stringent to date for μμqq contact interactions.

  10. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Fried, D; Meier, J; Mawlawi, O

    Purpose: Use a NEMA-IEC PET phantom to assess the robustness of FDG-PET-based radiomics features to changes in reconstruction parameters across different scanners. Methods: We scanned a NEMA-IEC PET phantom on 3 different scanners (GE Discovery VCT, GE Discovery 710, and Siemens mCT) using a FDG source-to-background ratio of 10:1. Images were retrospectively reconstructed using different iterations (2–3), subsets (21–24), Gaussian filter widths (2, 4, 6mm), and matrix sizes (128,192,256). The 710 and mCT used time-of-flight and point-spread-functions in reconstruction. The axial-image through the center of the 6 active spheres was used for analysis. A region-of-interest containing all spheres was ablemore » to simulate a heterogeneous lesion due to partial volume effects. Maximum voxel deviations from all retrospectively reconstructed images (18 per scanner) was compared to our standard clinical protocol. PET Images from 195 non-small cell lung cancer patients were used to compare feature variation. The ratio of a feature’s standard deviation from the patient cohort versus the phantom images was calculated to assess for feature robustness. Results: Across all images, the percentage of voxels differing by <1SUV and <2SUV ranged from 61–92% and 88–99%, respectively. Voxel-voxel similarity decreased when using higher resolution image matrices (192/256 versus 128) and was comparable across scanners. Taking the ratio of patient and phantom feature standard deviation was able to identify features that were not robust to changes in reconstruction parameters (e.g. co-occurrence correlation). Metrics found to be reasonably robust (standard deviation ratios > 3) were observed for routinely used SUV metrics (e.g. SUVmean and SUVmax) as well as some radiomics features (e.g. co-occurrence contrast, co-occurrence energy, standard deviation, and uniformity). Similar standard deviation ratios were observed across scanners. Conclusions: Our method enabled a comparison of feature variability across scanners and was able to identify features that were not robust to changes in reconstruction parameters.« less

  11. Host model uncertainties in aerosol radiative forcing estimates: results from the AeroCom prescribed intercomparison study

    NASA Astrophysics Data System (ADS)

    Stier, P.; Schutgens, N. A. J.; Bian, H.; Boucher, O.; Chin, M.; Ghan, S.; Huneeus, N.; Kinne, S.; Lin, G.; Myhre, G.; Penner, J. E.; Randles, C.; Samset, B.; Schulz, M.; Yu, H.; Zhou, C.

    2012-09-01

    Simulated multi-model "diversity" in aerosol direct radiative forcing estimates is often perceived as measure of aerosol uncertainty. However, current models used for aerosol radiative forcing calculations vary considerably in model components relevant for forcing calculations and the associated "host-model uncertainties" are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in nine participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is -4.51 W m-2 and the inter-model standard deviation is 0.70 W m-2, corresponding to a relative standard deviation of 15%. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.26 W m-2, and the standard deviation increases to 1.21 W m-2, corresponding to a significant relative standard deviation of 96%. However, the top-of-atmosphere forcing variability owing to absorption is low, with relative standard deviations of 9% clear-sky and 12% all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the AeroCom Direct Effect experiment, demonstrates that host model uncertainties could explain about half of the overall sulfate forcing diversity of 0.13 W m-2 in the AeroCom Direct Radiative Effect experiment. Host model errors in aerosol radiative forcing are largest in regions of uncertain host model components, such as stratocumulus cloud decks or areas with poorly constrained surface albedos, such as sea ice. Our results demonstrate that host model uncertainties are an important component of aerosol forcing uncertainty that require further attention.

  12. Robust Alternatives to the Standard Deviation in Processing of Physics Experimental Data

    NASA Astrophysics Data System (ADS)

    Shulenin, V. P.

    2016-10-01

    Properties of robust estimations of the scale parameter are studied. It is noted that the median of absolute deviations and the modified estimation of the average Gini differences have asymptotically normal distributions and bounded influence functions, are B-robust estimations, and hence, unlike the estimation of the standard deviation, are protected from the presence of outliers in the sample. Results of comparison of estimations of the scale parameter are given for a Gaussian model with contamination. An adaptive variant of the modified estimation of the average Gini differences is considered.

  13. Validated method for quantification of genetically modified organisms in samples of maize flour.

    PubMed

    Kunert, Renate; Gach, Johannes S; Vorauer-Uhl, Karola; Engel, Edwin; Katinger, Hermann

    2006-02-08

    Sensitive and accurate testing for trace amounts of biotechnology-derived DNA from plant material is the prerequisite for detection of 1% or 0.5% genetically modified ingredients in food products or raw materials thereof. Compared to ELISA detection of expressed proteins, real-time PCR (RT-PCR) amplification has easier sample preparation and detection limits are lower. Of the different methods of DNA preparation CTAB method with high flexibility in starting material and generation of sufficient DNA with relevant quality was chosen. Previous RT-PCR data generated with the SYBR green detection method showed that the method is highly sensitive to sample matrices and genomic DNA content influencing the interpretation of results. Therefore, this paper describes a real-time DNA quantification based on the TaqMan probe method, indicating high accuracy and sensitivity with detection limits of lower than 18 copies per sample applicable and comparable to highly purified plasmid standards as well as complex matrices of genomic DNA samples. The results were evaluated with ValiData for homology of variance, linearity, accuracy of the standard curve, and standard deviation.

  14. Quantitative analysis of synthetic dyes in lipstick by micellar electrokinetic capillary chromatography.

    PubMed

    Desiderio, C; Marra, C; Fanali, S

    1998-06-01

    The separation of synthetic dyes, used as color additives in cosmetics, by micellar electrokinetic capillary chromatography (MEKC) is described in this study. The separation of seven dyes, namely eosine, erythrosine, cyanosine, rhodamine B, orange II, chromotrope FB and tartrazine has been achieved in about 3 min in an untreated fused silica capillary containing as background electrolyte a 25 mM tetraborate/phosphate buffer, pH 8.0, and 30 mM sodium dodecyl sulfate. The electrophoretic method exhibits precision and relatively high sensitivity. A detection limit (LOD, signal/noise = 3) in the range of 5-7.5 X 10(-7) M of standard compounds was recorded. Intra-day repeatability of all the studied dye determinations (8 runs) gave the following results (limit values), % standard deviation: 0.24-1.54% for migration time, 0.99-1.24% for corrected peak areas, 0.99-1.24% for corrected peak area ratio (analyte/internal standard) and 1.56-2.74% for peak areas. The optimized method was successfully applied to the analysis of a lipstick sample where eosine and cyanosine were present.

  15. Mitral stenosis and hypertrophic obstructive cardiomyopathy: An unusual combination.

    PubMed

    Hong, Joonhwa; Schaff, Hartzell V; Ommen, Steve R; Abel, Martin D; Dearani, Joseph A; Nishimura, Rick A

    2016-04-01

    Systolic anterior motion of mitral valve (MV) leaflets is a main pathophysiologic feature of left ventricular outflow tract (LVOT) obstruction in hypertrophic obstructive cardiomyopathy. Thus, restricted leaflet motion that occurs with MV stenosis might be expected to minimize outflow tract obstruction related to systolic anterior motion. From January 1993 through February 2015, we performed MV replacement and septal myectomy in 12 patients with mitral stenosis and hypertrophic obstructive cardiomyopathy at Mayo Clinic Hospital in Rochester, Minn. Preoperative data, echocardiographic images, operative records, and postoperative outcomes were reviewed. Mean (standard deviation) age was 70 (7.6) years. Preoperative mean (standard deviation) maximal LVOT pressure gradient was 75.0 (35.0) mm Hg; MV gradient was 13.7 (2.8) mm Hg. From echocardiographic images, 4 mechanisms of outflow tract obstruction were identified: systolic anterior motion without severe limitation in MV leaflet excursion, severe limitation in MV leaflet mobility with systolic anterior motion at the tip of the MV anterior leaflet, septal encroachment toward the LVOT, and MV displacement toward the LVOT by calcification. Mitral valve replacement and extended septal myectomy relieved outflow gradients in all patients, with no death or serious morbidity. Patients with mitral stenosis and hypertrophic obstructive cardiomyopathy have multiple LVOT obstruction mechanisms, and MV replacement may not be adequate treatment. We favor septal myectomy and MV replacement in this complex subset of hypertrophic obstructive cardiomyopathy. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  16. MRI-guided procedures in various regions of the body using a robotic assistance system in a closed-bore scanner: preliminary clinical experience and limitations.

    PubMed

    Moche, Michael; Zajonz, Dirk; Kahn, Thomas; Busse, Harald

    2010-04-01

    To present the clinical setup and workflow of a robotic assistance system for image-guided interventions in a conventional magnetic resonance imaging (MRI) environment and to report our preliminary clinical experience with percutaneous biopsies in various body regions. The MR-compatible, servo-pneumatically driven, robotic device (Innomotion) fits into the 60-cm bore of a standard MR scanner. The needle placement (n = 25) accuracy was estimated by measuring the 3D deviation between needle tip and prescribed target point in a phantom. Percutaneous biopsies in six patients and different body regions were planned by graphically selecting entry and target points on intraoperatively acquired roadmap MR data. For insertion depths between 29 and 95 mm, the average 3D needle deviation was 2.2 +/- 0.7 mm (range 0.9-3.8 mm). Patients with a body mass index of up to approximately 30 kg/m(2) fitted into the bore with the device. Clinical work steps and limitations are reported for the various applications. All biopsies were diagnostic and could be completed without any major complications. Median planning and intervention times were 25 (range 20-36) and 44 (36-68) minutes, respectively. Preliminary clinical results in a standard MRI environment suggest that the presented robotic device provides accurate guidance for percutaneous procedures in various body regions. Shorter procedure times may be achievable by optimizing technical and workflow aspects. (c) 2010 Wiley-Liss, Inc.

  17. Linker-assisted immunoassay and liquid chromatography/mass spectrometry for the analysis of glyphosate

    USGS Publications Warehouse

    Lee, E.A.; Zimmerman, L.R.; Bhullar, B.S.; Thurman, E.M.

    2002-01-01

    A novel, sensitive, linker-assisted enzyme-linked immunosorbent assay (L'ELISA) was compared to on-line solidphase extraction (SPE) with high-performance liquid chromatography/mass spectrometry (HPLC/MS) for the analysis of glyphosate in surface water and groundwater samples. The L'ELISA used succinic anhydride to derivatize glyphosate, which mimics the epitotic attachment of glyphosate to horseradish peroxidase hapten. Thus, L'ELISA recognized the derivatized glyphosate more effectively (detection limit of 0.1 μg/L) and with increased sensitivity (10-100 times) over conventional ELISA and showed the potential for other applications. The precision and accuracy of L'ELISA then was compared with on-line SPE/HPLC/MS, which detected glyphosate and its degradate derivatized with 9-fluorenylmethyl chloroformate using negative-ion electrospray (detection limit 0.1 μg/L, relative standard deviation ±15%). Derivatization efficiency and matrix effects were minimized by adding an isotope-labeled glyphosate (2-13C15N). The accuracy of L'ELISA gave a false positive rate of 18% between 0.1 and 1.0 μg/L and a false positive rate of only 1% above 1.0 μg/L. The relative standard deviation was ±20%. The correlation of L'ELISA and HPLC/MS for 66 surface water and groundwater samples was 0.97 with a slope of 1.28, with many detections of glyphosate and its degradate in surface water but not in groundwater.

  18. Adherence to a Videogame-Based Physical Activity Program for Older Adults with Schizophrenia.

    PubMed

    Leutwyler, Heather; Hubbard, Erin M; Dowling, Glenna A

    2014-08-01

    Adults with schizophrenia are a growing segment of the older adult population. Evidence suggests that they engage in limited physical activity. Interventions are needed that are tailored around their unique limitations. An active videogame-based physical activity program that can be offered at a treatment facility can overcome these barriers and increase motivation to engage in physical activity. The purpose of this report is to describe the adherence to a videogame-based physical activity program using the Kinect(®) for Xbox(®) 360 game system (Microsoft(®), Redmond, WA) in older adults with schizophrenia. This was a descriptive longitudinal study among 34 older adults with schizophrenia to establish the adherence to an active videogame-based physical activity program. In our ongoing program, once a week for 6 weeks, participants played an active videogame, using the Kinect for Xbox 360 game system, for 30 minutes. Adherence was measured with a count of sessions attended and with the total minutes attended out of the possible total minutes of attendance (180 minutes). Thirty-four adults with schizophrenia enrolled in the study. The mean number of groups attended was five out of six total (standard deviation=2), and the mean total minutes attended were 139 out of 180 possible (standard deviation=55). Fifty percent had perfect attendance. Older adults with schizophrenia need effective physical activity programs. Adherence to our program suggests that videogames that use the Kinect for Xbox 360 game system are an innovative way to make physical activity accessible to this population.

  19. Development of QuEChERS-based extraction and liquid chromatography-tandem mass spectrometry method for quantifying flumethasone residues in beef muscle.

    PubMed

    Park, Ki Hun; Choi, Jeong-Heui; Abd El-Aty, A M; Cho, Soon-Kil; Park, Jong-Hyouk; Kwon, Ki Sung; Park, Hee Ra; Kim, Hyung Soo; Shin, Ho-Chul; Kim, Mi Ra; Shim, Jae-Han

    2012-12-01

    A rapid, specific, and sensitive method based on liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) in the positive ion mode using multiple reaction monitoring (MRM) was developed and validated to quantify flumethasone residues in beef muscle. Methods were compared between the original as well as the EN quick, easy, cheap, effective, rugged, and safe (QuEChERS)-based extraction. Good linearity was achieved at concentration levels of 5-30 μg/kg. Estimated recovery rates at spiking levels of 5 and 10 μg/kg ranged from 72.1 to 84.6%, with relative standard deviations (RSDs)<7%. The results of the inter-day study, which was performed by fortifying beef muscle samples (n=18) on 3 separate days, showed an accuracy of 93.4-94.4%. The precision (expressed as relative standard deviation values) for the inter-day variation at two levels of fortification (10 and 20 μg/kg) was 1.9-5.2%. The limit of detection (LOD) and limit of quantitation (LOQ) were 1.7 and 5 μg/kg, at signal-to-noise ratios (S/Ns) of 3 and 10, respectively. The method was successfully applied to analyze real samples obtained from large markets throughout the Korean Peninsula. The method proved to be sensitive and reliable and, thus, rendered an appropriate means for residue analysis studies. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. A meta-analysis of the validity of FFQ targeted to adolescents.

    PubMed

    Tabacchi, Garden; Filippi, Anna Rita; Amodio, Emanuele; Jemni, Monèm; Bianco, Antonino; Firenze, Alberto; Mammina, Caterina

    2016-05-01

    The present work is aimed at meta-analysing validity studies of FFQ for adolescents, to investigate their overall accuracy and variables that can affect it negatively. A meta-analysis of sixteen original articles was performed within the ASSO Project (Adolescents and Surveillance System in the Obesity prevention). The articles assessed the validity of FFQ for adolescents, compared with food records or 24 h recalls, with regard to energy and nutrient intakes. Pearson's or Spearman's correlation coefficients, means/standard deviations, kappa agreement, percentiles and mean differences/limits of agreement (Bland-Altman method) were extracted. Pooled estimates were calculated and heterogeneity tested for correlation coefficients and means/standard deviations. A subgroup analysis assessed variables influencing FFQ accuracy. An overall fair/high correlation between FFQ and reference method was found; a good agreement, measured through the intake mean comparison for all nutrients except sugar, carotene and K, was observed. Kappa values showed fair/moderate agreement; an overall good ability to rank adolescents according to energy and nutrient intakes was evidenced by data of percentiles; absolute validity was not confirmed by mean differences/limits of agreement. Interviewer administration mode, consumption interval of the previous year/6 months and high number of food items are major contributors to heterogeneity and thus can reduce FFQ accuracy. The meta-analysis shows that FFQ are accurate tools for collecting data and could be used for ranking adolescents in terms of energy and nutrient intakes. It suggests how the design and the validation of a new FFQ should be addressed.

  1. Designing Inter-Organisational Collectivities for Dynamic Fit: Stability, maneuvrability and Application in Disaster Relief Endeavours

    DTIC Science & Technology

    2011-01-01

    changed consumer preferences . Hence, static stability limits initial performance deviation (e.g., maintaining desired airplane altitude, maintaining...by changed consumer preferences . Hence, dynamic stability limits the duration of performance deviation (e.g., maintaining desired airplane altitude...altitude from wind gust. Initial resistance to deviation in profit level from change in consumer preferences . Dynamic stability Quickness of a

  2. The performance of single and multi-collector ICP-MS instruments for fast and reliable 34S/32S isotope ratio measurements†

    PubMed Central

    Pröfrock, Daniel; Irrgeher, Johanna; Prohaska, Thomas

    2016-01-01

    The performance and validation characteristics of different single collector inductively coupled plasma mass spectrometers based on different technical principles (ICP-SFMS, ICP-QMS in reaction and collision modes, and ICP-MS/MS) were evaluated in comparison to the performance of MC ICP-MS for fast and reliable S isotope ratio measurements. The validation included the determination of LOD, BEC, measurement repeatability, within-lab reproducibility and deviation from certified values as well as a study on instrumental isotopic fractionation (IIF) and the calculation of the combined standard measurement uncertainty. Different approaches of correction for IIF applying external intra-elemental IIF correction (aka standard-sample bracketing) using certified S reference materials and internal inter-elemental IIF (aka internal standardization) correction using Si isotope ratios in MC ICP-MS are explained and compared. The resulting combined standard uncertainties of examined ICP-QMS systems were not better than 0.3–0.5% (uc,rel), which is in general insufficient to differentiate natural S isotope variations. Although the performance of the single collector ICP-SFMS is better (single measurement uc,rel = 0.08%), the measurement reproducibility (>0.2%) is the major limit of this system and leaves room for improvement. MC ICP-MS operated in the edge mass resolution mode, applying bracketing for correction of IIF, provided isotope ratio values with the highest quality (relative combined measurement uncertainty: 0.02%; deviation from the certified value: <0.002%). PMID:27812369

  3. The performance of single and multi-collector ICP-MS instruments for fast and reliable 34S/32S isotope ratio measurements.

    PubMed

    Hanousek, Ondrej; Brunner, Marion; Pröfrock, Daniel; Irrgeher, Johanna; Prohaska, Thomas

    2016-11-14

    The performance and validation characteristics of different single collector inductively coupled plasma mass spectrometers based on different technical principles (ICP-SFMS, ICP-QMS in reaction and collision modes, and ICP-MS/MS) were evaluated in comparison to the performance of MC ICP-MS for fast and reliable S isotope ratio measurements. The validation included the determination of LOD, BEC, measurement repeatability, within-lab reproducibility and deviation from certified values as well as a study on instrumental isotopic fractionation (IIF) and the calculation of the combined standard measurement uncertainty. Different approaches of correction for IIF applying external intra-elemental IIF correction (aka standard-sample bracketing) using certified S reference materials and internal inter-elemental IIF (aka internal standardization) correction using Si isotope ratios in MC ICP-MS are explained and compared. The resulting combined standard uncertainties of examined ICP-QMS systems were not better than 0.3-0.5% ( u c,rel ), which is in general insufficient to differentiate natural S isotope variations. Although the performance of the single collector ICP-SFMS is better (single measurement u c,rel = 0.08%), the measurement reproducibility (>0.2%) is the major limit of this system and leaves room for improvement. MC ICP-MS operated in the edge mass resolution mode, applying bracketing for correction of IIF, provided isotope ratio values with the highest quality (relative combined measurement uncertainty: 0.02%; deviation from the certified value: <0.002%).

  4. 40 CFR 63.8640 - What records must I keep?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... to show continuous compliance with each emission limitation that applies to you. (c) You must also... deviation of an operating limit parameter value, the date, time, and duration of the deviation, a brief...

  5. A Search for Physics Beyond the Standard Model using Like-Sign Muon Pairs in pp Collisions at Center of Mass Energy = 7 TeV with the ATLAS Detector

    NASA Astrophysics Data System (ADS)

    Skinnari, Louise Anastasia

    This dissertation presents a search for physics beyond the Standard Model using pairs of muons with equal electric charge. The search is performed in a proton-proton collision data sample collected during 2011 at s = 7 TeV by the ATLAS experiment at the Large Hadron Collider. The total data sample corresponds to an integrated luminosity of 4.7 fb -1. Events are selected by requiring pairs of prompt and isolated like-sign muons with transverse momentum greater than 20 GeV. The observed dimuon invariant mass distribution is compared to the Standard Model expectation, searching for any deviation between the observed and predicted yields. No evidence for an excess beyond the Standard Model expectation is observed. The results are interpreted as inclusive cross-section limits on the production of like-sign muon pairs from non-Standard Model sources as function of the dimuon invariant mass. The cross-section limits range between 30 fb and 1.2 fb. The data are also searched for a new narrow resonance which decays to like-sign muon pairs. No evidence for such resonant production is observed and the results are interpreted as upper limits on the mass and production cross section of doubly charged Higgs bosons. Assuming pair-production and a 100% branching ratio to muons, masses below 398 GeV (306 GeV) are excluded assuming coupling to left-handed (right-handed) fermions.

  6. Differences between dentitions with palatally and labially located maxillary canines observed in incisor width, dental morphology and space conditions.

    PubMed

    Artmann, L; Larsen, H J; Sørensen, H B; Christensen, I J; Kjaer, I

    2010-06-01

    To analyze the interrelationship between incisor width, deviations in the dentition and available space in the dental arch in palatally and labially located maxillary ectopic canine cases. Size: On dental casts from 69 patients (mean age 13 years 6 months) the mesiodistal widths of each premolar, canine and incisor were measured and compared with normal standards. Dental deviations: Based on panoramic radiographs from the same patients the dentitions were grouped accordingly: Group I: normal morphology; Group IIa: deviations in the dentition within the maxillary incisors only; Group IIb: deviations in the dentition in general. Descriptive statistics for the tooth sizes and dental deviations were presented by the mean and 95% confidence limits for the mean and the p-value for the T-statistic. Space: Space was expresses by subtracting the total tooth sizes of incisors, canines and premolars from the length of the arch segments. Size of lateral maxillary incisor: The widths of the lateral incisors were significantly different in groups I, IIa and IIb (p=0.016) and in cases with labially located ectopic canines on average 0.65 (95% CI:0.25-1.05, p=0.0019) broader than lateral incisors in cases with palatally located ectopic canines. Space: Least available space was observed in cases with labially located canines. The linear model did show a difference between palatally and labially located ectopic canines (p=0.03). Space related to deviations in the dentition: When space in the dental arch was related to dental deviations (groups I, IIa and IIb), the cases in group IIb with palatally located canines had significantly more space compared with I and IIa. Two subgroups of palatally located ectopic maxillary canine cases based on registration of space, incisor width and deviations in the morphology of the dentition were identified.

  7. Search for an invisibly decaying Higgs boson or dark matter candidates produced in association with a Z boson in pp collisions at s = 13   TeV with the ATLAS detector

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aaboud, M.; Aad, G.; Abbott, B.

    Here a search for an invisibly decaying Higgs boson or dark matter candidates produced in association with a leptonically decaying Z boson in proton–proton collisions atmore » $$\\sqrt{s}$$ 13 TeV is presented. This search uses 36.1fb -1 of data collected by the ATLAS experiment at the Large Hadron Collider. No significant deviation from the expectation of the Standard Model backgrounds is observed. Assuming the Standard Model ZH production cross-section, an observed (expected) upper limit of 67% (39%) at the 95% confidence level is set on the branching ratio of invisible decays of the Higgs boson with mass mH =125GeV. The corresponding limits on the production cross-section of the ZH process with the invisible Higgs boson decays are also presented. Furthermore, exclusion limits on the dark matter candidate and mediator masses are reported in the framework of simplified dark matter models.« less

  8. Search for an invisibly decaying Higgs boson or dark matter candidates produced in association with a Z boson in pp collisions at s = 13   TeV with the ATLAS detector

    DOE PAGES

    Aaboud, M.; Aad, G.; Abbott, B.; ...

    2017-11-26

    Here a search for an invisibly decaying Higgs boson or dark matter candidates produced in association with a leptonically decaying Z boson in proton–proton collisions atmore » $$\\sqrt{s}$$ 13 TeV is presented. This search uses 36.1fb -1 of data collected by the ATLAS experiment at the Large Hadron Collider. No significant deviation from the expectation of the Standard Model backgrounds is observed. Assuming the Standard Model ZH production cross-section, an observed (expected) upper limit of 67% (39%) at the 95% confidence level is set on the branching ratio of invisible decays of the Higgs boson with mass mH =125GeV. The corresponding limits on the production cross-section of the ZH process with the invisible Higgs boson decays are also presented. Furthermore, exclusion limits on the dark matter candidate and mediator masses are reported in the framework of simplified dark matter models.« less

  9. Water quality management using statistical analysis and time-series prediction model

    NASA Astrophysics Data System (ADS)

    Parmar, Kulwinder Singh; Bhardwaj, Rashmi

    2014-12-01

    This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

  10. [Domestic and international trends concerning allowable limits of error in external quality assessment scheme].

    PubMed

    Hosogaya, Shigemi; Ozaki, Yukio

    2005-06-01

    Many external quality assessment schemes (EQAS) are performed to support quality improvement of the services provided by participating laboratories for the benefits of patients. The EQAS organizer shall be responsible for ensuring that the method of evaluation is appropriate for maintenance of the credibility of the schemes. Procedures to evaluate each participating laboratory are gradually being standardized. In most cases of EQAS, the peer group mean is used as a target of accuracy, and the peer group standard deviation is used as a criterion for inter-laboratory variation. On the other hand, Fraser CG, et al. proposed desirable quality specifications for any imprecision and inaccuracies, which were derived from inter- and intra-biologic variations. We also proposed allowable limits of analytical error, being less than one-half of the average intra-individual variation for evaluation of imprecision, and less than one-quarter of the inter- plus intra-individual variation for evaluation of inaccuracy. When expressed in coefficient of variation terms, these allowable limits may be applied at a wide range of levels of quantity.

  11. Search for stable hadronising squarks and gluinos with the ATLAS experiment at the LHC

    NASA Astrophysics Data System (ADS)

    Aad, G.; Abbott, B.; Abdallah, J.; Abdelalim, A. A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abramowicz, H.; Abreu, H.; Acerbi, E.; Acharya, B. S.; Adams, D. L.; Addy, T. N.; Adelman, J.; Aderholz, M.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P.; Akimoto, G.; Akimov, A. V.; Alam, M. S.; Alam, M. A.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Aleppo, M.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Aliyev, M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alviggi, M. G.; Amako, K.; Amaral, P.; Amelung, C.; Ammosov, V. V.; Amorim, A.; Amorós, G.; Amram, N.; Anastopoulos, C.; Andeen, T.; Anders, C. F.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angerami, A.; Anghinolfi, F.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonelli, S.; Antos, J.; Anulli, F.; Aoun, S.; Bella, L. Aperio; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Archambault, J. P.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Asfandiyarov, R.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Atoian, G.; Aubert, B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Austin, N.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Bachy, G.; Backes, M.; Backhaus, M.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Baltasar Dos Santos Pedrosa, F.; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barashkou, A.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, D.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Battistoni, G.; Bauer, F.; Bawa, H. S.; Beare, B.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bee, C.; Begel, M.; Harpaz, S. Behar; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, G.; Bellomo, M.; Belloni, A.; Belotskiy, K.; Beltramello, O.; Ben Ami, S.; Benary, O.; Benchekroun, D.; Benchouk, C.; Bendel, M.; Benedict, B. H.; Benekos, N.; Benhammou, Y.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernardet, K.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertin, A.; Bertinelli, F.; Bertolucci, F.; Besana, M. I.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boelaert, N.; Böser, S.; Bogaerts, J. A.; Bogdanchikov, A.; Bogouch, A.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Bona, M.; Bondarenko, V. G.; Boonekamp, M.; Boorman, G.; Booth, C. N.; Booth, P.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borroni, S.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Botterill, D.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E. V.; Boulahouache, C.; Bourdarios, C.; Bousson, N.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozhko, N. I.; Bozovic-Jelisavcic, I.; Bracinik, J.; Braem, A.; Brambilla, E.; Branchini, P.; Brandenburg, G. W.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brelier, B.; Bremer, J.; Brenner, R.; Bressler, S.; Breton, D.; Brett, N. D.; Bright-Thomas, P. G.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brodbeck, T. J.; Brodet, E.; Broggi, F.; Bromberg, C.; Brooijmans, G.; Brooks, W. K.; Brown, G.; Brubaker, E.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Buanes, T.; Bucci, F.; Buchanan, J.; Buchanan, N. J.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Budick, B.; Büscher, V.; Bugge, L.; Buira-Clark, D.; Buis, E. J.; Bulekov, O.; Bunse, M.; Buran, T.; Burckhart, H.; Burdin, S.; Burgess, T.; Burke, S.; Busato, E.; Bussey, P.; Buszello, C. P.; Butin, F.; Butler, B.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Buttinger, W.; Byatt, T.; Cabrera Urbán, S.; Caccia, M.; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Caloi, R.; Calvet, D.; Calvet, S.; Camacho Toro, R.; Camard, A.; Camarri, P.; Cambiaghi, M.; Cameron, D.; Cammin, J.; Campana, S.; Campanelli, M.; Canale, V.; Canelli, F.; Canepa, A.; Cantero, J.; Capasso, L.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capriotti, D.; Capua, M.; Caputo, R.; Caramarcu, C.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, B.; Caron, S.; Carpentieri, C.; Carrillo Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Cascella, M.; Caso, C.; Castaneda Hernandez, A. M.; Castaneda-Miranda, E.; Castillo Gimenez, V.; Castro, N. F.; Cataldi, G.; Cataneo, F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cauz, D.; Cavallari, A.; Cavalleri, P.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Cazzato, A.; Ceradini, F.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cetin, S. A.; Cevenini, F.; Chafaq, A.; Chakraborty, D.; Chan, K.; Chapleau, B.; Chapman, J. D.; Chapman, J. W.; Chareyre, E.; Charlton, D. G.; Chavda, V.; Cheatham, S.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chen, H.; Chen, L.; Chen, S.; Chen, T.; Chen, X.; Cheng, S.; Cheplakov, A.; Chepurnov, V. F.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Cheung, S. L.; Chevalier, L.; Chevallier, F.; Chiefari, G.; Chikovani, L.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chizhov, M. V.; Choudalakis, G.; Chouridou, S.; Christidi, I. A.; Christov, A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Ciapetti, G.; Ciba, K.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciobotaru, M. D.; Ciocca, C.; Ciocio, A.; Cirilli, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Clifft, R. W.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coe, P.; Cogan, J. G.; Coggeshall, J.; Cogneras, E.; Cojocaru, C. D.; Colas, J.; Colijn, A. P.; Collard, C.; Collins, N. J.; Collins-Tooth, C.; Collot, J.; Colon, G.; Coluccia, R.; Comune, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Consonni, M.; Constantinescu, S.; Conta, C.; Conventi, F.; Cook, J.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Costin, T.; Côté, D.; Torres, R. Coura; Courneyea, L.; Cowan, G.; Cowden, C.; Cox, B. E.; Cranmer, K.; Cristinziani, M.; Crosetti, G.; Crupi, R.; Crépé-Renaudin, S.; Cuenca Almenar, C.; Cuhadar Donszelmann, T.; Cuneo, S.; Curatolo, M.; Curtis, C. J.; Cwetanski, P.; Czirr, H.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; D'Orazio, A.; da Rocha Gesualdi Mello, A.; da Silva, P. V. M.; da Via, C.; Dabrowski, W.; Dahlhoff, A.; Dai, T.; Dallapiccola, C.; Dallison, S. J.; Dam, M.; Dameri, M.; Damiani, D. S.; Danielsson, H. O.; Dankers, R.; Dannheim, D.; Dao, V.; Darbo, G.; Darlea, G. L.; Daum, C.; Dauvergne, J. P.; Davey, W.; Davidek, T.; Davidson, N.; Davidson, R.; Davies, M.; Davison, A. R.; Dawe, E.; Dawson, I.; Dawson, J. W.; Daya, R. K.; de, K.; de Asmundis, R.; de Castro, S.; de Castro Faria Salgado, P. E.; de Cecco, S.; de Graat, J.; de Groot, N.; de Jong, P.; de La Taille, C.; de Lotto, B.; de Mora, L.; de Nooij, L.; de Oliveira Branco, M.; de Pedis, D.; de Saintignon, P.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vivie de Regie, J. B.; Dean, S.; Dedovich, D. V.; Degenhardt, J.; Dehchar, M.; Deile, M.; Del Papa, C.; Del Peso, J.; Del Prete, T.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delpierre, P.; Delruelle, N.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demirkoz, B.; Deng, J.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Devetak, E.; Deviveiros, P. O.; Dewhurst, A.; Dewilde, B.; Dhaliwal, S.; Dhullipudi, R.; di Ciaccio, A.; di Ciaccio, L.; di Girolamo, A.; di Girolamo, B.; di Luise, S.; di Mattia, A.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; Diaz, M. A.; Diblen, F.; Diehl, E. B.; Dietl, H.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dindar Yagci, K.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djilkibaev, R.; Djobava, T.; Do Vale, M. A. B.; Do Valle Wemans, A.; Doan, T. K. O.; Dobbs, M.; Dobinson, R.; Dobos, D.; Dobson, E.; Dobson, M.; Dodd, J.; Dogan, O. B.; Doglioni, C.; Doherty, T.; Doi, Y.; Dolejsi, J.; Dolenc, I.; Dolezal, Z.; Dolgoshein, B. A.; Dohmae, T.; Donadelli, M.; Donega, M.; Donini, J.; Dopke, J.; Doria, A.; Dos Anjos, A.; Dosil, M.; Dotti, A.; Dova, M. T.; Dowell, J. D.; Doxiadis, A. D.; Doyle, A. T.; Drasal, Z.; Drees, J.; Dressnandt, N.; Drevermann, H.; Driouichi, C.; Dris, M.; Drohan, J. G.; Dubbert, J.; Dubbs, T.; Dube, S.; Duchovni, E.; Duckeck, G.; Dudarev, A.; Dudziak, F.; Dührssen, M.; Duerdoth, I. P.; Duflot, L.; Dufour, M.-A.; Dunford, M.; Yildiz, H. Duran; Duxfield, R.; Dwuznik, M.; Dydak, F.; Dzahini, D.; Düren, M.; Ebenstein, W. L.; Ebke, J.; Eckert, S.; Eckweiler, S.; Edmonds, K.; Edwards, C. A.; Efthymiopoulos, I.; Ehrenfeld, W.; Ehrich, T.; Eifert, T.; Eigen, G.; Einsweiler, K.; Eisenhandler, E.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, K.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Ely, R.; Emeliyanov, D.; Engelmann, R.; Engl, A.; Epp, B.; Eppig, A.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Escobar, C.; Espinal Curull, X.; Esposito, B.; Etienne, F.; Etienvre, A. I.; Etzion, E.; Evangelakou, D.; Evans, H.; Fabbri, L.; Fabre, C.; Facius, K.; Fakhrutdinov, R. M.; Falciano, S.; Falou, A. C.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farley, J.; Farooque, T.; Farrington, S. M.; Farthouat, P.; Fasching, D.; Fassnacht, P.; Fassouliotis, D.; Fatholahzadeh, B.; Favareto, A.; Fayard, L.; Fazio, S.; Febbraro, R.; Federic, P.; Fedin, O. L.; Fedorko, I.; Fedorko, W.; Fehling-Kaschek, M.; Feligioni, L.; Fellmann, D.; Felzmann, C. U.; Feng, C.; Feng, E. J.; Fenyuk, A. 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V.; Peng, H.; Pengo, R.; Penson, A.; Penwell, J.; Perantoni, M.; Perez, K.; Perez Cavalcanti, T.; Perez Codina, E.; Pérez García-Estañ, M. T.; Perez Reale, V.; Peric, I.; Perini, L.; Pernegger, H.; Perrino, R.; Perrodo, P.; Persembe, S.; Peshekhonov, V. D.; Peters, O.; Petersen, B. A.; Petersen, J.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petrolo, E.; Petrucci, F.; Petschull, D.; Petteni, M.; Pezoa, R.; Phan, A.; Phillips, A. W.; Phillips, P. W.; Piacquadio, G.; Piccaro, E.; Piccinini, M.; Pickford, A.; Piec, S. M.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pina, J.; Pinamonti, M.; Pinder, A.; Pinfold, J. L.; Ping, J.; Pinto, B.; Pirotte, O.; Pizio, C.; Placakyte, R.; Plamondon, M.; Plano, W. G.; Pleier, M.-A.; Pleskach, A. V.; Poblaguev, A.; Poddar, S.; Podlyski, F.; Poggioli, L.; Poghosyan, T.; Pohl, M.; Polci, F.; Polesello, G.; Policicchio, A.; Polini, A.; Poll, J.; Polychronakos, V.; Pomarede, D. M.; Pomeroy, D.; Pommès, K.; Pontecorvo, L.; Pope, B. 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G.; Searcy, J.; Sedykh, E.; Segura, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Seliverstov, D. M.; Sellden, B.; Sellers, G.; Seman, M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Seuster, R.; Severini, H.; Sevior, M. E.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shank, J. T.; Shao, Q. T.; Shapiro, M.; Shatalov, P. B.; Shaver, L.; Shaw, C.; Shaw, K.; Sherman, D.; Sherwood, P.; Shibata, A.; Shimizu, S.; Shimojima, M.; Shin, T.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shupe, M. A.; Sicho, P.; Sidoti, A.; Siebel, A.; Siegert, F.; Siegrist, J.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simmons, B.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skovpen, K.; Skubic, P.; Skvorodnev, N.; Slater, M.; Slavicek, T.; Sliwa, K.; Sloan, T. J.; Sloper, J.; Smakhtin, V.; Smirnov, S. Yu.; Smirnova, L. N.; Smirnova, O.; Smith, B. C.; Smith, D.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snow, S. W.; Snow, J.; Snuverink, J.; Snyder, S.; Soares, M.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C. A.; Solar, M.; Solc, J.; Soldevila, U.; Solfaroli Camillocci, E.; Solodkov, A. A.; Solovyanov, O. V.; Sondericker, J.; Soni, N.; Sopko, V.; Sopko, B.; Sorbi, M.; Sosebee, M.; Soukharev, A.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spila, F.; Spiriti, E.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R. D.; Stahl, T.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staude, A.; Stavina, P.; Stavropoulos, G.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, K.; Stewart, G. A.; Stillings, J. A.; Stockmanns, T.; Stockton, M. C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Strube, J.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Soh, D. A.; Su, D.; Subramania, S.; Sugaya, Y.; Sugimoto, T.; Suhr, C.; Suita, K.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Sushkov, S.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Sviridov, Yu. M.; Swedish, S.; Sykora, I.; Sykora, T.; Szeless, B.; Sánchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taga, A.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Talby, M.; Talyshev, A.; Tamsett, M. C.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanaka, Y.; Tani, K.; Tannoury, N.; Tappern, G. P.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tatarkhanov, M.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terwort, M.; Testa, M.; Teuscher, R. J.; Tevlin, C. M.; Thadome, J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thioye, M.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomson, E.; Thomson, M.; Thun, R. P.; Tic, T.; Tikhomirov, V. O.; Tikhonov, Y. A.; Timmermans, C. J. W. P.; Tipton, P.; Tique Aires Viegas, F. J.; Tisserant, S.; Tobias, J.; Toczek, B.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokunaga, K.; Tokushuku, K.; Tollefson, K.; Tomoto, M.; Tompkins, L.; Toms, K.; Tonazzo, A.; Tong, G.; Tonoyan, A.; Topfel, C.; Topilin, N. D.; Torchiani, I.; Torrence, E.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Traynor, D.; Trefzger, T.; Treis, J.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Trinh, T. N.; Tripiana, M. F.; Triplett, N.; Trischuk, W.; Trivedi, A.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiakiris, M.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsung, J.-W.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tuggle, J. M.; Turala, M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Typaldos, D.; Tyrvainen, H.; Tzanakos, G.; Uchida, K.; Ueda, I.; Ueno, R.; Ugland, M.; Uhlenbrock, M.; Uhrmacher, M.; Ukegawa, F.; Unal, G.; Underwood, D. G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Urkovsky, E.; Urquijo, P.; Urrejola, P.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valderanis, C.; Valenta, J.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; van der Graaf, H.; van der Kraaij, E.; van der Leeuw, R.; van der Poel, E.; van der Ster, D.; van Eijk, B.; van Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vandelli, W.; Vandoni, G.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Varela Rodriguez, F.; Vari, R.; Varnes, E. W.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Vegni, G.; Veillet, J. J.; Vellidis, C.; Veloso, F.; Veness, R.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Vichou, I.; Vickey, T.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinek, E.; Vinogradov, V. B.; Virchaux, M.; Viret, S.; Virzi, J.; Vitale, A.; Vitells, O.; Viti, M.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobiev, A. P.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T. T.; Vossebeld, J. H.; Vovenko, A. S.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vukotic, I.; Wagner, W.; Wagner, P.; Wahlen, H.; Wakabayashi, J.; Walbersloh, J.; Walch, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Wang, C.; Wang, H.; Wang, J.; Wang, J.; Wang, J. C.; Wang, R.; Wang, S. M.; Warburton, A.; Ward, C. P.; Warsinsky, M.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, A. T.; Waugh, B. M.; Weber, J.; Weber, M.; Weber, M. S.; Weber, P.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P. S.; Wen, M.; Wenaus, T.; Wendler, S.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Wessels, M.; Whalen, K.; Wheeler-Ellis, S. J.; Whitaker, S. P.; White, A.; White, M. J.; White, S.; Whitehead, S. R.; Whiteson, D.; Whittington, D.; Wicek, F.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilhelm, I.; Wilkens, H. G.; Will, J. Z.; Williams, E.; Williams, H. H.; Willis, W.; Willocq, S.; Wilson, J. A.; Wilson, M. G.; Wilson, A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wolter, M. W.; Wolters, H.; Wooden, G.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wraight, K.; Wright, C.; Wrona, B.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wunstorf, R.; Wynne, B. M.; Xaplanteris, L.; Xella, S.; Xie, S.; Xie, Y.; Xu, C.; Xu, D.; Xu, G.; Yabsley, B.; Yamada, M.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U. K.; Yang, Y.; Yang, Y.; Yang, Z.; Yanush, S.; Yao, W.-M.; Yao, Y.; Yasu, Y.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Youssef, S.; Yu, D.; Yu, J.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zaets, V. G.; Zaidan, R.; Zaitsev, A. M.; Zajacova, Z.; Zalite, Yo. K.; Zanello, L.; Zarzhitsky, P.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zema, P. F.; Zemla, A.; Zendler, C.; Zenin, A. V.; Zenin, O.; Ženiš, T.; Zenonos, Z.; Zenz, S.; Zerwas, D.; Zevi Della Porta, G.; Zhan, Z.; Zhang, D.; Zhang, H.; Zhang, J.; Zhang, X.; Zhang, Z.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zheng, S.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zieminska, D.; Zilka, B.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; Zolnierowski, Y.; Zsenei, A.; Zur Nedden, M.; Zutshi, V.; Zwalinski, L.; Atlas Collaboration

    2011-06-01

    Hitherto unobserved long-lived massive particles with electric and/or colour charge are predicted by a range of theories which extend the Standard Model. In this Letter a search is performed at the ATLAS experiment for slow-moving charged particles produced in proton-proton collisions at 7 TeV centre-of-mass energy at the LHC, using a data-set corresponding to an integrated luminosity of 34 pb-1. No deviations from Standard Model expectations are found. This result is interpreted in a framework of supersymmetry models in which coloured sparticles can hadronise into long-lived bound hadronic states, termed R-hadrons, and 95% CL limits are set on the production cross-sections of squarks and gluinos. The influence of R-hadron interactions in matter was studied using a number of different models, and lower mass limits for stable sbottoms and stops are found to be 294 and 309 GeV respectively. The lower mass limit for a stable gluino lies in the range from 562 to 586 GeV depending on the model assumed. Each of these constraints is the most stringent to date.

  12. Use of Standard Deviations as Predictors in Models Using Large-Scale International Data Sets

    ERIC Educational Resources Information Center

    Austin, Bruce; French, Brian; Adesope, Olusola; Gotch, Chad

    2017-01-01

    Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…

  13. Screen Twice, Cut Once: Assessing the Predictive Validity of Teacher Selection Tools

    ERIC Educational Resources Information Center

    Goldhaber, Dan; Grout, Cyrus; Huntington-Klein, Nick

    2015-01-01

    It is well documented that teachers can have profound effects on student outcomes. Empirical estimates find that a one standard deviation increase in teacher quality raises student test achievement by 10 to 25 percent of a standard deviation. More recent evidence shows that the effectiveness of teachers can affect long-term student outcomes, such…

  14. Comparing Measurement Error between Two Different Methods of Measurement of Various Magnitudes

    ERIC Educational Resources Information Center

    Zavorsky, Gerald S.

    2010-01-01

    Measurement error is a common problem in several fields of research such as medicine, physiology, and exercise science. The standard deviation of repeated measurements on the same person is the measurement error. One way of presenting measurement error is called the repeatability, which is 2.77 multiplied by the within subject standard deviation.…

  15. THE EFFECTS OF ANGULAR MOMENTUM ON HALO PROFILES

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lentz, Erik W; Rosenberg, Leslie J; Quinn, Thomas R, E-mail: lentze@phys.washington.edu, E-mail: ljrosenberg@phys.washington.edu, E-mail: trq@astro.washington.edu

    2016-05-10

    The near universality of DM halo density profiles provided by N -body simulations proved to be robust against changes in total mass density, power spectrum, and some forms of initial velocity dispersion. Here we study the effects of coherently spinning up an isolated DM-only progenitor on halo structure. Halos with spins within several standard deviations of the simulated mean ( λ ≲ 0.20) produce profiles with negligible deviations from the universal form. Only when the spin becomes quite large ( λ ≳ 0.20) do departures become evident. The angular momentum distribution also exhibits a near universal form, which is alsomore » independent of halo spin up to λ ≲ 0.20. A correlation between these epidemic profiles and the presence of a strong bar in the virialized halo is also observed. These bar structures bear resemblance to the radial orbit instability in the rotationless limit.« less

  16. Parabolic trough receiver heat loss and optical efficiency round robin 2015/2016

    NASA Astrophysics Data System (ADS)

    Pernpeintner, Johannes; Schiricke, Björn; Sallaberry, Fabienne; de Jalón, Alberto García; López-Martín, Rafael; Valenzuela, Loreto; de Luca, Antonio; Georg, Andreas

    2017-06-01

    A round robin for parabolic trough receiver heat loss and optical efficiency in the laboratory was performed between five institutions using five receivers in 2015/2016. Heat loss testing was performed at three cartridge heater test benches and one Joule heating test bench in the temperature range between 100 °C and 550 °C. Optical efficiency testing was performed with two spectrometric test bench and one calorimetric test bench. Heat loss testing results showed standard deviations at the order of 6% to 12 % for most temperatures and receivers and a standard deviation of 17 % for one receiver at 100 °C. Optical efficiency is presented normalized for laboratories showing standard deviations of 0.3 % to 1.3 % depending on the receiver.

  17. Benign positional vertigo and hyperuricaemia.

    PubMed

    Adam, A M

    2005-07-01

    To find out if there is any association between serum uric acid level and positional vertigo. A prospective, case controlled study. A private neurological clinic. All patients presenting with vertigo. Ninety patients were seen in this period with 78 males and 19 females. Mean age was 47 +/- 3 years (at 95% confidence level) with a standard deviation of 12.4. Their mean uric acid level was 442 +/- 16 (at 95% confidence level) with a standard deviation of 79.6 umol/l as compared to 291 +/- 17 (at 95% confidence level) with a standard deviation of 79.7 umol/l in the control group. The P-value was less than 0.001. That there is a significant association between high uric acid and benign positional vertigo.

  18. Palus Somni - Anomalies in the correlation of Al/Si X-ray fluorescence intensity ratios and broad-spectrum visible albedos. [lunar surface mineralogy

    NASA Technical Reports Server (NTRS)

    Clark, P. E.; Andre, C. G.; Adler, I.; Weidner, J.; Podwysocki, M.

    1976-01-01

    The positive correlation between Al/Si X-ray fluorescence intensity ratios determined during the Apollo 15 lunar mission and a broad-spectrum visible albedo of the moon is quantitatively established. Linear regression analysis performed on 246 1 degree geographic cells of X-ray fluorescence intensity and visible albedo data points produced a statistically significant correlation coefficient of .78. Three distinct distributions of data were identified as (1) within one standard deviation of the regression line, (2) greater than one standard deviation below the line, and (3) greater than one standard deviation above the line. The latter two distributions of data were found to occupy distinct geographic areas in the Palus Somni region.

  19. Screening Samples for Arsenic by Inductively Coupled Plasma-Mass Spectrometry for Treaty Samples

    DTIC Science & Technology

    2014-02-01

    2.274 3.657 10.06 14.56 30.36 35.93 % RSD : 15.87% 4.375% 2.931% 4.473% 3.349% 3.788% 2.802% 3.883% 3.449% RSD , relative standard deviation 9   Table...107.9% 106.4% Standard Deviation: 0.3171 0.3498 0.8024 2.964 4.526 10.06 13.83 16.38 11.81 % RSD : 5.657% 3.174% 3.035% 5.507% 4.332% 3.795% 2.626...119.1% 116.5% 109.4% 106.8% 105.2% 105.5% 105.8% 108.6% 107.8% Standard Deviation: 0.2379 0.5595 1.173 2.375 2.798 5.973 11.79 15.10 30.54 % RSD

  20. Comparison method for uranium determination in ore sample by inductively coupled plasma optical emission spectrometry (ICP-OES).

    PubMed

    Sert, Şenol

    2013-07-01

    A comparison method for the determination (without sample pre-concentration) of uranium in ore by inductively coupled plasma optical emission spectrometry (ICP-OES) has been performed. The experiments were conducted using three procedures: matrix matching, plasma optimization, and internal standardization for three emission lines of uranium. Three wavelengths of Sm were tested as internal standard for the internal standardization method. The robust conditions were evaluated using applied radiofrequency power, nebulizer argon gas flow rate, and sample uptake flow rate by considering the intensity ratio of the Mg(II) 280.270 nm and Mg(I) 285.213 nm lines. Analytical characterization of method was assessed by limit of detection and relative standard deviation values. The certificated reference soil sample IAEA S-8 was analyzed, and the uranium determination at 367.007 nm with internal standardization using Sm at 359.260 nm has been shown to improve accuracy compared with other methods. The developed method was used for real uranium ore sample analysis.

  1. A deviation display method for visualising data in mobile gamma-ray spectrometry.

    PubMed

    Kock, Peder; Finck, Robert R; Nilsson, Jonas M C; Ostlund, Karl; Samuelsson, Christer

    2010-09-01

    A real time visualisation method, to be used in mobile gamma-spectrometric search operations using standard detector systems is presented. The new method, called deviation display, uses a modified waterfall display to present relative changes in spectral data over energy and time. Using unshielded (137)Cs and (241)Am point sources and different natural background environments, the behaviour of the deviation displays is demonstrated and analysed for two standard detector types (NaI(Tl) and HPGe). The deviation display enhances positive significant changes while suppressing the natural background fluctuations. After an initialization time of about 10min this technique leads to a homogeneous display dominated by the background colour, where even small changes in spectral data are easy to discover. As this paper shows, the deviation display method works well for all tested gamma energies and natural background radiation levels and with both tested detector systems.

  2. Polar motion results from GEOS 3 laser ranging

    NASA Technical Reports Server (NTRS)

    Schutz, B. E.; Tapley, B. D.; Ries, J.; Eanes, R.

    1979-01-01

    The observability of polar motion from laser range data has been investigated, and the contributions from the dynamical and kinematical effects have been evaluated. Using 2-day arcs with GEOS 3 laser data, simultaneous solutions for pole position components and orbit elements have been obtained for a 2-week interval spanning August 27 to September 10, 1975, using three NASA Goddard Space Flight Center stations located at Washington, D.C., Bermuda, and Grand Turk. The results for the y-component of pole position from this limited data set differenced with the BIH linearly interpolated values yield a mean of 39 cm and a standard deviation of 1.07 m. Consideration of the variance associated with each estimate yields a mean of 20 cm and a standard deviation of 81 cm. The results for the x-component of pole position indicate that the mean value is in fair agreement with the BIH; however, the x-coordinate determination is weaker than the y-coordinate determination due to the distribution of laser sites (all three are between 77 deg W and 65 deg W) which results in greater sensitivity to the data distribution. In addition, the sensitivity of these results to various model parameters is discussed.

  3. Spectroscopy of H3+ based on a new high-accuracy global potential energy surface.

    PubMed

    Polyansky, Oleg L; Alijah, Alexander; Zobov, Nikolai F; Mizus, Irina I; Ovsyannikov, Roman I; Tennyson, Jonathan; Lodi, Lorenzo; Szidarovszky, Tamás; Császár, Attila G

    2012-11-13

    The molecular ion H(3)(+) is the simplest polyatomic and poly-electronic molecular system, and its spectrum constitutes an important benchmark for which precise answers can be obtained ab initio from the equations of quantum mechanics. Significant progress in the computation of the ro-vibrational spectrum of H(3)(+) is discussed. A new, global potential energy surface (PES) based on ab initio points computed with an average accuracy of 0.01 cm(-1) relative to the non-relativistic limit has recently been constructed. An analytical representation of these points is provided, exhibiting a standard deviation of 0.097 cm(-1). Problems with earlier fits are discussed. The new PES is used for the computation of transition frequencies. Recently measured lines at visible wavelengths combined with previously determined infrared ro-vibrational data show that an accuracy of the order of 0.1 cm(-1) is achieved by these computations. In order to achieve this degree of accuracy, relativistic, adiabatic and non-adiabatic effects must be properly accounted for. The accuracy of these calculations facilitates the reassignment of some measured lines, further reducing the standard deviation between experiment and theory.

  4. Development of a Dual-Pump CARS System for Measurements in a Supersonic Combusting Free Jet

    NASA Technical Reports Server (NTRS)

    Magnotti, Gaetano; Cutler, Andrew D.; Danehy, Paul

    2012-01-01

    This work describes the development of a dual-pump CARS system for simultaneous measurements of temperature and absolute mole fraction of N2, O2 and H2 in a laboratory scale supersonic combusting free jet. Changes to the experimental set-up and the data analysis to improve the quality of the measurements in this turbulent, high-temperature reacting flow are described. The accuracy and precision of the instrument have been determined using data collected in a Hencken burner flame. For temperature above 800 K, errors in absolute mole fraction are within 1.5, 0.5, and 1% of the total composition for N2, O2 and H2, respectively. Estimated standard deviations based on 500 single shots are between 10 and 65 K for the temperature, between 0.5 and 1.7% of the total composition for O2, and between 1.5 and 3.4% for N2. The standard deviation of H2 is 10% of the average measured mole fraction. Results obtained in the jet with and without combustion are illustrated, and the capabilities and limitations of the dual-pump CARS instrument discussed.

  5. Search for Resonant Production of High-Mass Photon Pairs in Proton-Proton Collisions at sqrt[s]=8 and 13 TeV.

    PubMed

    Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Flechl, M; Friedl, M; Frühwirth, R; Ghete, V M; Hartl, C; Hörmann, N; Hrubec, J; Jeitler, M; König, A; Krätschmer, I; Liko, D; Matsushita, T; Mikulec, I; Rabady, D; Rad, N; Rahbaran, B; Rohringer, H; Schieck, J; Strauss, J; Treberer-Treberspurg, W; Waltenberger, W; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Alderweireldt, S; De Wolf, E A; Janssen, X; Lauwers, J; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Van Spilbeeck, A; Abu Zeid, S; Blekman, F; D'Hondt, J; Daci, N; De Bruyn, I; Deroover, K; Heracleous, N; Lowette, S; Moortgat, S; Moreels, L; Olbrechts, A; Python, Q; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Parijs, I; Brun, H; Caillol, C; Clerbaux, B; De Lentdecker, G; Delannoy, H; Fasanella, G; Favart, L; Goldouzian, R; Grebenyuk, A; Karapostoli, G; Lenzi, T; Léonard, A; Luetic, J; Maerschalk, T; Marinov, A; Randle-Conde, A; Seva, T; Vander Velde, C; Vanlaer, P; Yonamine, R; Zenoni, F; Zhang, F; Cimmino, A; Cornelis, T; Dobur, D; Fagot, A; Garcia, G; Gul, M; Poyraz, D; Salva, S; Schöfbeck, R; Tytgat, M; Van Driessche, W; Yazgan, E; Zaganidis, N; Bakhshiansohi, H; Beluffi, C; Bondu, O; Brochet, S; Bruno, G; Caudron, A; De Visscher, S; Delaere, C; Delcourt, M; Francois, B; Giammanco, A; Jafari, A; Jez, P; Komm, M; Lemaitre, V; Magitteri, A; Mertens, A; Musich, M; Nuttens, C; Piotrzkowski, K; Quertenmont, L; Selvaggi, M; Vidal Marono, M; Wertz, S; Beliy, N; Aldá Júnior, W L; Alves, F L; Alves, G A; Brito, L; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; Da Silveira, G G; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Huertas Guativa, L M; Malbouisson, H; Matos Figueiredo, D; Mora Herrera, C; Mundim, L; Nogima, H; Prado Da Silva, W L; Santoro, A; Sznajder, A; Tonelli Manganote, E J; Vilela Pereira, A; Ahuja, S; Bernardes, C A; Dogra, S; Tomei, T R Fernandez Perez; Gregores, E M; Mercadante, P G; Moon, C S; Novaes, S F; Padula, Sandra S; Romero Abad, D; Ruiz Vargas, J C; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Rodozov, M; Stoykova, S; Sultanov, G; Vutova, M; Dimitrov, A; Glushkov, I; Litov, L; Pavlov, B; Petkov, P; Fang, W; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Chen, Y; Cheng, T; Jiang, C H; Leggat, D; Liu, Z; Romeo, F; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Zhang, H; Zhao, J; Ban, Y; Chen, G; Li, Q; Liu, S; Mao, Y; Qian, S J; Wang, D; Xu, Z; Avila, C; Cabrera, A; Chaparro Sierra, L F; Florez, C; Gomez, J P; González Hernández, C F; Ruiz Alvarez, J D; Sanabria, J C; Godinovic, N; Lelas, D; Puljak, I; Ribeiro Cipriano, P M; Sculac, T; Antunovic, Z; Kovac, M; Brigljevic, V; Ferencek, D; Kadija, K; Micanovic, S; Sudic, L; Susa, T; Attikis, A; Mavromanolakis, G; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Rykaczewski, H; Finger, M; Finger, M; Carrera Jarrin, E; Assran, Y; Elkafrawy, T; Mahrous, A; Calpas, B; Kadastik, M; Murumaa, M; Perrini, L; Raidal, M; Tiko, A; Veelken, C; Eerola, P; Pekkanen, J; Voutilainen, M; Härkönen, J; Karimäki, V; Kinnunen, R; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Peltola, T; Tuominiemi, J; Tuovinen, E; Wendland, L; Talvitie, J; Tuuva, T; Besancon, M; Couderc, F; Dejardin, M; Denegri, D; Fabbro, B; Faure, J L; Favaro, C; Ferri, F; Ganjour, S; Ghosh, S; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Kucher, I; Locci, E; Machet, M; Malcles, J; Rander, J; Rosowsky, A; Titov, M; Zghiche, A; Abdulsalam, A; Antropov, I; Baffioni, S; Beaudette, F; Busson, P; Cadamuro, L; Chapon, E; Charlot, C; Davignon, O; Granier de Cassagnac, R; Jo, M; Lisniak, S; Miné, P; Nguyen, M; Ochando, C; Ortona, G; Paganini, P; Pigard, P; Regnard, S; Salerno, R; Sirois, Y; Strebler, T; Yilmaz, Y; Zabi, A; Agram, J-L; Andrea, J; Aubin, A; Bloch, D; Brom, J-M; Buttignol, M; Chabert, E C; Chanon, N; Collard, C; Conte, E; Coubez, X; Fontaine, J-C; Gelé, D; Goerlach, U; Le Bihan, A-C; Merlin, J A; Skovpen, K; Van Hove, P; Gadrat, S; Beauceron, S; Bernet, C; Boudoul, G; Bouvier, E; Carrillo Montoya, C A; Chierici, R; Contardo, D; Courbon, B; Depasse, P; El Mamouni, H; Fan, J; Fay, J; Gascon, S; Gouzevitch, M; Grenier, G; Ille, B; Lagarde, F; Laktineh, I B; Lethuillier, M; Mirabito, L; Pequegnot, A L; Perries, S; Popov, A; Sabes, D; Sordini, V; Vander Donckt, M; Verdier, P; Viret, S; Toriashvili, T; Tsamalaidze, Z; Autermann, C; Beranek, S; Feld, L; Heister, A; Kiesel, M K; Klein, K; Lipinski, M; Ostapchuk, A; Preuten, M; Raupach, F; Schael, S; Schomakers, C; Schulte, J F; Schulz, J; Verlage, T; Weber, H; Zhukov, V; Brodski, M; Dietz-Laursonn, E; Duchardt, D; Endres, M; Erdmann, M; Erdweg, S; Esch, T; Fischer, R; Güth, A; Hamer, M; Hebbeker, T; Heidemann, C; Hoepfner, K; Knutzen, S; Merschmeyer, M; Meyer, A; Millet, P; Mukherjee, S; Olschewski, M; Padeken, K; Pook, T; Radziej, M; Reithler, H; Rieger, M; Scheuch, F; Sonnenschein, L; Teyssier, D; Thüer, S; Cherepanov, V; Flügge, G; Haj Ahmad, W; Hoehle, F; Kargoll, B; Kress, T; Künsken, A; Lingemann, J; Müller, T; Nehrkorn, A; Nowack, A; Nugent, I M; Pistone, C; Pooth, O; Stahl, A; Aldaya Martin, M; Asawatangtrakuldee, C; Beernaert, K; Behnke, O; Behrens, U; Bin Anuar, A A; Borras, K; Campbell, A; Connor, P; Contreras-Campana, C; Costanza, F; Diez Pardos, C; Dolinska, G; Eckerlin, G; Eckstein, D; Eren, E; Gallo, E; Garay Garcia, J; Geiser, A; Gizhko, A; Grados Luyando, J M; Gunnellini, P; Harb, A; Hauk, J; Hempel, M; Jung, H; Kalogeropoulos, A; Karacheban, O; Kasemann, M; Keaveney, J; Kieseler, J; Kleinwort, C; Korol, I; Krücker, D; Lange, W; Lelek, A; Leonard, J; Lipka, K; Lobanov, A; Lohmann, W; Mankel, R; Melzer-Pellmann, I-A; Meyer, A B; Mittag, G; Mnich, J; Mussgiller, A; Ntomari, E; Pitzl, D; Raspereza, A; Roland, B; Sahin, M Ö; Saxena, P; Schoerner-Sadenius, T; Seitz, C; Spannagel, S; Stefaniuk, N; Trippkewitz, K D; Van Onsem, G P; Walsh, R; Wissing, C; Blobel, V; Centis Vignali, M; Draeger, A R; Dreyer, T; Garutti, E; Gonzalez, D; Haller, J; Hoffmann, M; Junkes, A; Klanner, R; Kogler, R; Kovalchuk, N; Lapsien, T; Lenz, T; Marchesini, I; Marconi, D; Meyer, M; Niedziela, M; Nowatschin, D; Pantaleo, F; Peiffer, T; Perieanu, A; Poehlsen, J; Sander, C; Scharf, C; Schleper, P; Schmidt, A; Schumann, S; Schwandt, J; Stadie, H; Steinbrück, G; Stober, F M; Stöver, M; Tholen, H; Troendle, D; Usai, E; Vanelderen, L; Vanhoefer, A; Vormwald, B; Barth, C; Baus, C; Berger, J; Butz, E; Chwalek, T; Colombo, F; De Boer, W; Dierlamm, A; Fink, S; Friese, R; Giffels, M; Gilbert, A; Goldenzweig, P; Haitz, D; Hartmann, F; Heindl, S M; Husemann, U; Katkov, I; Lobelle Pardo, P; Maier, B; Mildner, H; Mozer, M U; Müller, Th; Plagge, M; Quast, G; Rabbertz, K; Röcker, S; Roscher, F; Schröder, M; Shvetsov, I; Sieber, G; Simonis, H J; Ulrich, R; Wagner-Kuhr, J; Wayand, S; Weber, M; Weiler, T; Williamson, S; Wöhrmann, C; Wolf, R; Anagnostou, G; Daskalakis, G; Geralis, T; Giakoumopoulou, V A; Kyriakis, A; Loukas, D; Topsis-Giotis, I; Agapitos, A; Kesisoglou, S; Panagiotou, A; Saoulidou, N; Tziaferi, E; Evangelou, I; Flouris, G; Foudas, C; Kokkas, P; Loukas, N; Manthos, N; Papadopoulos, I; Paradas, E; Filipovic, N; Bencze, G; Hajdu, C; Hidas, P; Horvath, D; Sikler, F; Veszpremi, V; Vesztergombi, G; Zsigmond, A J; Beni, N; Czellar, S; Karancsi, J; Makovec, A; Molnar, J; Szillasi, Z; Bartók, M; Raics, P; Trocsanyi, Z L; Ujvari, B; Bahinipati, S; Choudhury, S; Mal, P; Mandal, K; Nayak, A; Sahoo, D K; Sahoo, N; Swain, S K; Bansal, S; Beri, S B; Bhatnagar, V; Chawla, R; Bhawandeep, U; Kalsi, A K; Kaur, A; Kaur, M; Kumar, R; Mehta, A; Mittal, M; Singh, J B; Walia, G; Kumar, Ashok; Bhardwaj, A; Choudhary, B C; Garg, R B; Keshri, S; Malhotra, S; Naimuddin, M; Nishu, N; Ranjan, K; Sharma, R; Sharma, V; Bhattacharya, R; Bhattacharya, S; Chatterjee, K; Dey, S; Dutt, S; Dutta, S; Ghosh, S; Majumdar, N; Modak, A; Mondal, K; Mukhopadhyay, S; Nandan, S; Purohit, A; Roy, A; Roy, D; Roy Chowdhury, S; Sarkar, S; Sharan, M; Thakur, S; Behera, P K; Chudasama, R; Dutta, D; Jha, V; Kumar, V; Mohanty, A K; Netrakanti, P K; Pant, L M; Shukla, P; Topkar, A; Aziz, T; Dugad, S; Kole, G; Mahakud, B; Mitra, S; Mohanty, G B; Parida, B; Sur, N; Sutar, B; Banerjee, S; Bhowmik, S; Dewanjee, R K; Ganguly, S; Guchait, M; Jain, Sa; Kumar, S; Maity, M; Majumder, G; Mazumdar, K; Sarkar, T; Wickramage, N; Chauhan, S; Dube, S; Hegde, V; Kapoor, A; Kothekar, K; Rane, A; Sharma, S; Behnamian, H; Chenarani, S; Eskandari Tadavani, E; Etesami, S M; Fahim, A; Khakzad, M; Mohammadi Najafabadi, M; Naseri, M; Paktinat Mehdiabadi, S; Rezaei Hosseinabadi, F; Safarzadeh, B; Zeinali, M; Felcini, M; Grunewald, M; Abbrescia, M; Calabria, C; Caputo, C; Colaleo, A; Creanza, D; Cristella, L; De Filippis, N; De Palma, M; Fiore, L; Iaselli, G; Maggi, G; Maggi, M; Miniello, G; My, S; Nuzzo, S; Pompili, A; Pugliese, G; Radogna, R; Ranieri, A; Selvaggi, G; Silvestris, L; Venditti, R; Verwilligen, P; 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Luo, J; Marlow, D; Medvedeva, T; Mei, K; Mooney, M; Olsen, J; Palmer, C; Piroué, P; Stickland, D; Tully, C; Zuranski, A; Malik, S; Barker, A; Barnes, V E; Folgueras, S; Gutay, L; Jha, M K; Jones, M; Jung, A W; Jung, K; Miller, D H; Neumeister, N; Shi, X; Sun, J; Svyatkovskiy, A; Wang, F; Xie, W; Xu, L; Parashar, N; Stupak, J; Adair, A; Akgun, B; Chen, Z; Ecklund, K M; Geurts, F J M; Guilbaud, M; Li, W; Michlin, B; Northup, M; Padley, B P; Redjimi, R; Roberts, J; Rorie, J; Tu, Z; Zabel, J; Betchart, B; Bodek, A; de Barbaro, P; Demina, R; Duh, Y T; Ferbel, T; Galanti, M; Garcia-Bellido, A; Han, J; Hindrichs, O; Khukhunaishvili, A; Lo, K H; Tan, P; Verzetti, M; Chou, J P; Contreras-Campana, E; Gershtein, Y; Gómez Espinosa, T A; Halkiadakis, E; Heindl, M; Hidas, D; Hughes, E; Kaplan, S; Kunnawalkam Elayavalli, R; Kyriacou, S; Lath, A; Nash, K; Saka, H; Salur, S; Schnetzer, S; Sheffield, D; Somalwar, S; Stone, R; Thomas, S; Thomassen, P; Walker, M; Foerster, M; Heideman, J; Riley, G; Rose, K; Spanier, S; Thapa, K; Bouhali, O; Celik, A; Dalchenko, M; De Mattia, M; Delgado, A; Dildick, S; Eusebi, R; Gilmore, J; Huang, T; Juska, E; Kamon, T; Mueller, R; Pakhotin, Y; Patel, R; Perloff, A; Perniè, L; Rathjens, D; Rose, A; Safonov, A; Tatarinov, A; Ulmer, K A; Akchurin, N; Cowden, C; Damgov, J; Dragoiu, C; Dudero, P R; Faulkner, J; Kunori, S; Lamichhane, K; Lee, S W; Libeiro, T; Undleeb, S; Volobouev, I; Wang, Z; Delannoy, A G; Greene, S; Gurrola, A; Janjam, R; Johns, W; Maguire, C; Melo, A; Ni, H; Sheldon, P; Tuo, S; Velkovska, J; Xu, Q; Arenton, M W; Barria, P; Cox, B; Goodell, J; Hirosky, R; Ledovskoy, A; Li, H; Neu, C; Sinthuprasith, T; Wang, Y; Wolfe, E; Xia, F; Clarke, C; Harr, R; Karchin, P E; Lamichhane, P; Sturdy, J; Belknap, D A; Dasu, S; Dodd, L; Duric, S; Gomber, B; Grothe, M; Herndon, M; Hervé, A; Klabbers, P; Lanaro, A; Levine, A; Long, K; Loveless, R; Ojalvo, I; Perry, T; Pierro, G A; Polese, G; Ruggles, T; Savin, A; Sharma, A; Smith, N; Smith, W H; Taylor, D; Woods, N

    2016-07-29

    A search for the resonant production of high-mass photon pairs is presented. The analysis is based on samples of proton-proton collision data collected by the CMS experiment at center-of-mass energies of 8 and 13 TeV, corresponding to integrated luminosities of 19.7 and 3.3  fb^{-1}, respectively. The interpretation of the search results focuses on spin-0 and spin-2 resonances with masses between 0.5 and 4 TeV and with widths, relative to the mass, between 1.4×10^{-4} and 5.6×10^{-2}. Limits are set on scalar resonances produced through gluon-gluon fusion, and on Randall-Sundrum gravitons. A modest excess of events compatible with a narrow resonance with a mass of about 750 GeV is observed. The local significance of the excess is approximately 3.4 standard deviations. The significance is reduced to 1.6 standard deviations once the effect of searching under multiple signal hypotheses is considered. More data are required to determine the origin of this excess.

  6. The Portuguese adaptation of the Gudjonsson Suggestibility Scale (GSS1) in a sample of inmates.

    PubMed

    Pires, Rute; Silva, Danilo R; Ferreira, Ana Sousa

    2014-01-01

    This paper comprises two studies which address the validity of the Portuguese adaptation of the Gudjonsson Suggestibility Scale, GSS1. In study 1, the means and standard deviations for the suggestibility results of a sample of Portuguese inmates (N=40, Mage=37.5 years, SD=8.1) were compared to those of a sample of Icelandic inmates (Gudjonsson, 1997; Gudjonsson & Sigurdsson, 1996). Portuguese inmates' results were in line with the original results. In study 2, the means and standard deviations for the suggestibility results of the sample of Portuguese inmates were compared to those of a general Portuguese population sample (N=57, Mage=36.1 years, SD=12.7). The forensic sample obtained significantly higher scores in suggestibility measures than the general population sample. ANOVA confirmed that the increased suggestibility in the inmates sample was due to the limited memory capacity of this latter group. Given that the results of both studies 1 and 2 are in keeping with the author's original results (Gudjonsson, 1997), this may be regarded as a confirmation of the validity of the Portuguese GSS1. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Dispersive solid-phase extraction for the determination of trace organochlorine pesticides in apple juices using reduced graphene oxide coated with ZnO nanocomposites as sorbent.

    PubMed

    Sun, Ting; Sun, Hefeng; Zhao, Feng

    2017-09-01

    In this work, reduced graphene oxide coated with ZnO nanocomposites was used as an efficient sorbent of dispersive solid-phase extraction and successfully applied for the extraction of organochlorine pesticides from apple juice followed by gas chromatography with mass spectrometry. Several experimental parameters affecting the extraction efficiencies, including the amount of adsorbent, extraction time, and the pH of the sample solution, as well as the type and volume of eluent solvent, were investigated and optimized. Under the optimal experimental conditions, good linearity existed in the range of 1.0-200.0 ng/mL for all the analytes with the correlation coefficients (R 2 ) ranging from 0.9964 to 0.9994. The limits of detection of the method for the compounds were 0.011-0.053 ng/mL. Good reproducibilities were acquired with relative standard deviations below 8.7% for both intraday and interday precision. The recoveries of the method were in the range of 78.1-105.8% with relative standard deviations of 3.3-6.9%. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Preliminary Estimation of Deoxynivalenol Excretion through a 24 h Pilot Study

    PubMed Central

    Rodríguez-Carrasco, Yelko; Mañes, Jordi; Berrada, Houda; Font, Guillermina

    2015-01-01

    A duplicate diet study was designed to explore the occurrence of 15 Fusarium mycotoxins in the 24 h-diet consumed by one volunteer as well as the levels of mycotoxins in his 24 h-collected urine. The employed methodology involved solvent extraction at high ionic strength followed by dispersive solid phase extraction and gas chromatography determination coupled to mass spectrometry in tandem. Satisfactory results in method performance were achieved. The method’s accuracy was in a range of 68%–108%, with intra-day relative standard deviation and inter-day relative standard deviation lower than 12% and 15%, respectively. The limits of quantitation ranged from 0.1 to 8 µg/Kg. The matrix effect was evaluated and matrix-matched calibrations were used for quantitation. Only deoxynivalenol (DON) was quantified in both food and urine samples. A total DON daily intake amounted to 49.2 ± 5.6 µg whereas DON daily excretion of 35.2 ± 4.3 µg was determined. DON daily intake represented 68.3% of the established DON provisional maximum tolerable daily intake (PMTDI). Valuable preliminary information was obtained as regards DON excretion and needs to be confirmed in large-scale monitoring studies. PMID:25723325

  9. A multiresidue method for determination of trace levels of pesticides in air and water.

    PubMed

    Millet, M; Wortham, H; Sanusi, A; Mirabel, P

    1996-11-01

    A multiresidue analytical method is described for the analysis of 13 pesticides in fogwater, rainwater, gas, and particles. This method is based upon solid-liquid extraction using Sep-Pak tC18 light cartridges for aqueous samples, soxhlet for gas (adsorbed on XAD-2) and particles (on glass fiber filters), HPLC-based fractionation of the extracted residues using a silica column, and a linear gradient of n-hexane/tert butyl methyl ether followed by GC-ECD and HPLC-UV analyses of each fraction. Prior to analysis with GC-ECD, a methylation procedure using BF3/methanol was developed for the analysis of the fraction which contains chlorophenoxy acid herbicides. The recoveries of the extraction procedure of liquid samples and of the methylation were greater than 92 and 97% with a standard deviation lower than 8 and 5%, respectively. The detection limits varied between 0.1 and 0.01 microgram.ml-1 for the 13 pesticides studied with a standard deviation less than 9%. This method was used for the determination of pesticides in 18 fogwater samples (soluble + insoluble), 31 rainwater samples, and 17 air (gas + particles) samples collected between 1991 and 1993 in Colmar (east of France).

  10. Determination of rhodamine B in soft drink, waste water and lipstick samples after solid phase extraction.

    PubMed

    Soylak, Mustafa; Unsal, Yunus Emre; Yilmaz, Erkan; Tuzen, Mustafa

    2011-08-01

    A new solid phase extraction method is described for sensitive and selective determination of trace levels of rhodamine B in soft drink, food and industrial waste water samples. The method is based on the adsorption of rhodamine B on the Sepabeads SP 70 resin and its elution with 5 mL of acetonitrile in a mini chromatographic column. Rhodamine B was determined by using UV visible spectrophotometry at 556 nm. The effects of different parameters such as pH, amount of rhodamine B, flow rates of sample and eluent solutions, resin amount, and sample volume were investigated. The influences of some alkali, alkali earth and transition metals on the recoveries of rhodamine B were investigated. The preconcentration factor was found 40. The detection limit based on three times the standard deviation of the reagent blank for rhodamine B was 3.14 μg L⁻¹. The relative standard deviations of the procedure were found as 5% in 1×10⁻⁵ mol L⁻¹ rhodamine B. The presented procedure was successfully applied to real samples including soft drink, food and industrial waste water and lipstick samples. Copyright © 2011 Elsevier Ltd. All rights reserved.

  11. A randomized controlled trial investigating the effects of craniosacral therapy on pain and heart rate variability in fibromyalgia patients.

    PubMed

    Castro-Sánchez, Adelaida María; Matarán-Peñarrocha, Guillermo A; Sánchez-Labraca, Nuria; Quesada-Rubio, José Manuel; Granero-Molina, José; Moreno-Lorenzo, Carmen

    2011-01-01

    Fibromyalgia is a prevalent musculoskeletal disorder associated with widespread mechanical tenderness, fatigue, non-refreshing sleep, depressed mood and pervasive dysfunction of the autonomic nervous system: tachycardia, postural intolerance, Raynaud's phenomenon and diarrhoea. To determine the effects of craniosacral therapy on sensitive tender points and heart rate variability in patients with fibromyalgia. A randomized controlled trial. Ninety-two patients with fibromyalgia were randomly assigned to an intervention group or placebo group. Patients received treatments for 20 weeks. The intervention group underwent a craniosacral therapy protocol and the placebo group received sham treatment with disconnected magnetotherapy equipment. Pain intensity levels were determined by evaluating tender points, and heart rate variability was recorded by 24-hour Holter monitoring. After 20 weeks of treatment, the intervention group showed significant reduction in pain at 13 of the 18 tender points (P < 0.05). Significant differences in temporal standard deviation of RR segments, root mean square deviation of temporal standard deviation of RR segments and clinical global impression of improvement versus baseline values were observed in the intervention group but not in the placebo group. At two months and one year post therapy, the intervention group showed significant differences versus baseline in tender points at left occiput, left-side lower cervical, left epicondyle and left greater trochanter and significant differences in temporal standard deviation of RR segments, root mean square deviation of temporal standard deviation of RR segments and clinical global impression of improvement. Craniosacral therapy improved medium-term pain symptoms in patients with fibromyalgia.

  12. 41 CFR 102-38.30 - How does an executive agency request a deviation from the provisions of this part?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... which are distinct from the standard deviation process and specific to the requirements of the Federal... agency request a deviation from the provisions of this part? 102-38.30 Section 102-38.30 Public Contracts... executive agency request a deviation from the provisions of this part? Refer to §§ 102-2.60 through 102-2...

  13. 40 CFR 63.5555 - How do I demonstrate continuous compliance with the emission limits, operating limits, and work...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... startup, shutdown, and malfunction. These instances are deviations from the emission limits, operating... during a period of startup, shutdown, or malfunction are not violations if you demonstrate to the... determine whether deviations that occur during a period you identify as a startup, shutdown, or malfunction...

  14. 40 CFR 63.5555 - How do I demonstrate continuous compliance with the emission limits, operating limits, and work...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... startup, shutdown, and malfunction. These instances are deviations from the emission limits, operating... during a period of startup, shutdown, or malfunction are not violations if you demonstrate to the... determine whether deviations that occur during a period you identify as a startup, shutdown, or malfunction...

  15. Machine-Specific Magnetic Resonance Imaging Quality Control Procedures for Stereotactic Radiosurgery Treatment Planning

    PubMed Central

    Taghizadeh, Somayeh; Yang, Claus Chunli; R. Kanakamedala, Madhava; Morris, Bart; Vijayakumar, Srinivasan

    2017-01-01

    Purpose Magnetic resonance (MR) images are necessary for accurate contouring of intracranial targets, determination of gross target volume and evaluation of organs at risk during stereotactic radiosurgery (SRS) treatment planning procedures. Many centers use magnetic resonance imaging (MRI) simulators or regular diagnostic MRI machines for SRS treatment planning; while both types of machine require two stages of quality control (QC), both machine- and patient-specific, before use for SRS, no accepted guidelines for such QC currently exist. This article describes appropriate machine-specific QC procedures for SRS applications. Methods and materials We describe the adaptation of American College of Radiology (ACR)-recommended QC tests using an ACR MRI phantom for SRS treatment planning. In addition, commercial Quasar MRID3D and Quasar GRID3D phantoms were used to evaluate the effects of static magnetic field (B0) inhomogeneity, gradient nonlinearity, and a Leksell G frame (SRS frame) and its accessories on geometrical distortion in MR images. Results QC procedures found in-plane distortions (Maximum = 3.5 mm, Mean = 0.91 mm, Standard deviation = 0.67 mm, >2.5 mm (%) = 2) in X-direction (Maximum = 2.51 mm, Mean = 0.52 mm, Standard deviation = 0.39 mm, > 2.5 mm (%) = 0) and in Y-direction (Maximum = 13. 1 mm , Mean = 2.38 mm, Standard deviation = 2.45 mm, > 2.5 mm (%) = 34) in Z-direction and < 1 mm distortion at a head-sized region of interest. MR images acquired using a Leksell G frame and localization devices showed a mean absolute deviation of 2.3 mm from isocenter. The results of modified ACR tests were all within recommended limits, and baseline measurements have been defined for regular weekly QC tests. Conclusions With appropriate QC procedures in place, it is possible to routinely obtain clinically useful MR images suitable for SRS treatment planning purposes. MRI examination for SRS planning can benefit from the improved localization and planning possible with the superior image quality and soft tissue contrast achieved under optimal conditions. PMID:29487771

  16. Machine-Specific Magnetic Resonance Imaging Quality Control Procedures for Stereotactic Radiosurgery Treatment Planning.

    PubMed

    Fatemi, Ali; Taghizadeh, Somayeh; Yang, Claus Chunli; R Kanakamedala, Madhava; Morris, Bart; Vijayakumar, Srinivasan

    2017-12-18

    Purpose Magnetic resonance (MR) images are necessary for accurate contouring of intracranial targets, determination of gross target volume and evaluation of organs at risk during stereotactic radiosurgery (SRS) treatment planning procedures. Many centers use magnetic resonance imaging (MRI) simulators or regular diagnostic MRI machines for SRS treatment planning; while both types of machine require two stages of quality control (QC), both machine- and patient-specific, before use for SRS, no accepted guidelines for such QC currently exist. This article describes appropriate machine-specific QC procedures for SRS applications. Methods and materials We describe the adaptation of American College of Radiology (ACR)-recommended QC tests using an ACR MRI phantom for SRS treatment planning. In addition, commercial Quasar MRID 3D and Quasar GRID 3D phantoms were used to evaluate the effects of static magnetic field (B 0 ) inhomogeneity, gradient nonlinearity, and a Leksell G frame (SRS frame) and its accessories on geometrical distortion in MR images. Results QC procedures found in-plane distortions (Maximum = 3.5 mm, Mean = 0.91 mm, Standard deviation = 0.67 mm, >2.5 mm (%) = 2) in X-direction (Maximum = 2.51 mm, Mean = 0.52 mm, Standard deviation = 0.39 mm, > 2.5 mm (%) = 0) and in Y-direction (Maximum = 13. 1 mm , Mean = 2.38 mm, Standard deviation = 2.45 mm, > 2.5 mm (%) = 34) in Z-direction and < 1 mm distortion at a head-sized region of interest. MR images acquired using a Leksell G frame and localization devices showed a mean absolute deviation of 2.3 mm from isocenter. The results of modified ACR tests were all within recommended limits, and baseline measurements have been defined for regular weekly QC tests. Conclusions With appropriate QC procedures in place, it is possible to routinely obtain clinically useful MR images suitable for SRS treatment planning purposes. MRI examination for SRS planning can benefit from the improved localization and planning possible with the superior image quality and soft tissue contrast achieved under optimal conditions.

  17. Family structure and childhood anthropometry in Saint Paul, Minnesota in 1918

    PubMed Central

    Warren, John Robert

    2017-01-01

    Concern with childhood nutrition prompted numerous surveys of children’s growth in the United States after 1870. The Children’s Bureau’s 1918 “Weighing and Measuring Test” measured two million children to produce the first official American growth norms. Individual data for 14,000 children survives from the Saint Paul, Minnesota survey whose stature closely approximated national norms. As well as anthropometry the survey recorded exact ages, street address and full name. These variables allow linkage to the 1920 census to obtain demographic and socioeconomic information. We matched 72% of children to census families creating a sample of nearly 10,000 children. Children in the entire survey (linked set) averaged 0.74 (0.72) standard deviations below modern WHO height-for-age standards, and 0.48 (0.46) standard deviations below modern weight-for-age norms. Sibship size strongly influenced height-for-age, and had weaker influence on weight-for-age. Each additional child six or underreduced height-for-age scores by 0.07 standard deviations (95% CI: −0.03, 0.11). Teenage siblings had little effect on height-forage. Social class effects were substantial. Children of laborers averaged half a standard deviation shorter than children of professionals. Family structure and socio-economic status had compounding impacts on children’s stature. PMID:28943749

  18. Experimental comparison of icing cloud instruments

    NASA Technical Reports Server (NTRS)

    Olsen, W.; Takeuchi, D. M.; Adams, K.

    1983-01-01

    Icing cloud instruments were tested in the spray cloud Icing Research Tunnel (IRT) in order to determine their relative accuracy and their limitations over a broad range of conditions. It was found that the average of the readings from each of the liquid water content (LWC) instruments tested agreed closely with each other and with the IRT calibration; but all have a data scatter (+ or - one standard deviation) of about + or - 20 percent. The effect of this + or - 20 percent uncertainty is probably acceptable in aero-penalty and deicer experiments. Existing laser spectrometers proved to be too inaccurate for LWC measurements. The error due to water runoff was the same for all ice accretion LWC instruments. Any given laser spectrometer proved to be highly repeatable in its indications of volume median drop size (DVM), LWC and drop size distribution. However, there was a significant disagreement between different spectrometers of the same model, even after careful standard calibration and data analysis. The scatter about the mean of the DVM data from five Axial Scattering Spectrometer Probes was + or - 20 percent (+ or - one standard deviation) and the average was 20 percent higher than the old IRT calibration. The + or - 20 percent uncertainty in DVM can cause an unacceptable variation in the drag coefficient of an airfoil with ice; however, the variation in a deicer performance test may be acceptable.

  19. Evaluation of measurement uncertainty of glucose in clinical chemistry.

    PubMed

    Berçik Inal, B; Koldas, M; Inal, H; Coskun, C; Gümüs, A; Döventas, Y

    2007-04-01

    The definition of the uncertainty of measurement used in the International Vocabulary of Basic and General Terms in Metrology (VIM) is a parameter associated with the result of a measurement, which characterizes the dispersion of the values that could reasonably be attributed to the measurand. Uncertainty of measurement comprises many components. In addition to every parameter, the measurement uncertainty is that a value should be given by all institutions that have been accredited. This value shows reliability of the measurement. GUM, published by NIST, contains uncertainty directions. Eurachem/CITAC Guide CG4 was also published by Eurachem/CITAC Working Group in the year 2000. Both of them offer a mathematical model, for uncertainty can be calculated. There are two types of uncertainty in measurement. Type A is the evaluation of uncertainty through the statistical analysis and type B is the evaluation of uncertainty through other means, for example, certificate reference material. Eurachem Guide uses four types of distribution functions: (1) rectangular distribution that gives limits without specifying a level of confidence (u(x)=a/ radical3) to a certificate; (2) triangular distribution that values near to the same point (u(x)=a/ radical6); (3) normal distribution in which an uncertainty is given in the form of a standard deviation s, a relative standard deviation s/ radicaln, or a coefficient of variance CV% without specifying the distribution (a = certificate value, u = standard uncertainty); and (4) confidence interval.

  20. Detection limit used for early warning in public health surveillance.

    PubMed

    Kobari, Tsuyoshi; Iwaki, Kazuo; Nagashima, Tomomi; Ishii, Fumiyoshi; Hayashi, Yuzuru; Yajima, Takehiko

    2009-06-01

    A theory of detection limit, developed in analytical chemistry, is applied to public health surveillance to detect an outbreak of national emergencies such as natural disaster and bioterrorism. In this investigation, the influenza epidemic around the Tokyo area from 2003 to 2006 is taken as a model of normal and large-scale epidemics. The detection limit of the normal epidemic is used as a threshold with a specified level of significance to identify a sign of the abnormal epidemic among the daily variation in anti-influenza drug sales at community pharmacies. While auto-correlation of data is often an obstacle to an unbiased estimator of standard deviation involved in the detection limit, the analytical theory (FUMI) can successfully treat the auto-correlation of the drug sales in the same way as the auto-correlation appearing as 1/f noise in many analytical instruments.

  1. Search for new phenomena in monophoton final states in proton-proton collisions at √{ s} = 8 TeV

    NASA Astrophysics Data System (ADS)

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Ochesanu, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Mora Herrera, C.; Pol, M. 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B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Novgorodova, O.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. 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S.; Colaleo, A.; Creanza, D.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Albergo, S.; Cappello, G.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gallo, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Ferretti, R.; Ferro, F.; Lo Vetere, M.; Robutti, E.; Tosi, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Lucchini, M. T.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Galanti, M.; Gasparini, U.; Giubilato, P.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Vanini, S.; Ventura, S.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fiori, F.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Moon, C. S.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Vernieri, C.; Barone, L.; Cavallari, F.; D'imperio, G.; Del Re, D.; Diemoz, M.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Soffi, L.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Casasso, S.; Costa, M.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; Ortona, G.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Potenza, A.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Tamponi, U.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Park, H.; Sakharov, A.; Son, D. C.; Kim, T. J.; Kim, J. Y.; Song, S.; Choi, S.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K. S.; Park, S. K.; Roh, Y.; Choi, M.; Kim, J. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Md Ali, M. A. B.; Casimiro Linares, E.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. 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V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Savrin, V.; Snigirev, A.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Graziano, A.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Piedra Gomez, J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Benaglia, A.; Bendavid, J.; Benhabib, L.; Benitez, J. F.; Bernet, C.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; David, A.; De Guio, F.; De Roeck, A.; De Visscher, S.; Di Marco, E.; Dobson, M.; Dordevic, M.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Eugster, J.; Franzoni, G.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Magini, N.; Malgeri, L.; Mannelli, M.; Marrouche, J.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Musella, P.; Orsini, L.; Pape, L.; Perez, E.; Perrozzi, L.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Plagge, M.; Racz, A.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W.-S.; Kao, K. Y.; Liu, Y. F.; Lu, R.-S.; Majumder, D.; Petrakou, E.; Tzeng, Y. M.; Wilken, R.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Isildak, B.; Karapinar, G.; Ocalan, K.; Sekmen, S.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; Cankocak, K.; Vardarlı, F. I.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Senkin, S.; Smith, V. J.; Williams, T.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Krohn, M.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Skinnari, L.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kaadze, K.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P., III; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Ratnikov, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Korjenevski, S.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Vuosalo, C.; Woods, N.; CMS Collaboration

    2016-04-01

    Results are presented from a search for new physics in final states containing a photon and missing transverse momentum. The data correspond to an integrated luminosity of 19.6 fb-1 collected in proton-proton collisions at √{ s} = 8 TeV with the CMS experiment at the LHC. No deviation from the standard model predictions is observed for these final states. New, improved limits are set on dark matter production and on parameters of models with large extra dimensions. In particular, the first limits from the LHC on branon production are found and significantly extend previous limits from LEP and the Tevatron. An upper limit of 14.0 fb on the cross section is set at the 95% confidence level for events with a monophoton final state with photon transverse momentum greater than 145 GeV and missing transverse momentum greater than 140 GeV.

  2. Models of Lift and Drag Coefficients of Stalled and Unstalled Airfoils in Wind Turbines and Wind Tunnels

    NASA Technical Reports Server (NTRS)

    Spera, David A.

    2008-01-01

    Equations are developed with which to calculate lift and drag coefficients along the spans of torsionally-stiff rotating airfoils of the type used in wind turbine rotors and wind tunnel fans, at angles of attack in both the unstalled and stalled aerodynamic regimes. Explicit adjustments are made for the effects of aspect ratio (length to chord width) and airfoil thickness ratio. Calculated lift and drag parameters are compared to measured parameters for 55 airfoil data sets including 585 test points. Mean deviation was found to be -0.4 percent and standard deviation was 4.8 percent. When the proposed equations were applied to the calculation of power from a stall-controlled wind turbine tested in a NASA wind tunnel, mean deviation from 54 data points was -1.3 percent and standard deviation was 4.0 percent. Pressure-rise calculations for a large wind tunnel fan deviated by 2.7 percent (mean) and 4.4 percent (standard). The assumption that a single set of lift and drag coefficient equations can represent the stalled aerodynamic behavior of a wide variety of airfoils was found to be satisfactory.

  3. What are the bias, imprecision, and limits of agreement for finding the flexion-extension plane of the knee with five tibial reference lines?

    PubMed

    Brar, Abheetinder S; Howell, Stephen M; Hull, Maury L

    2016-06-01

    Internal-external (I-E) malrotation of the tibial component is associated with poor function after total knee arthroplasty (TKA). Kinematically aligned (KA) TKA uses a functionally defined flexion-extension (F-E) tibial reference line, which is parallel to the F-E plane of the extended knee, to set I-E rotation of the tibial component. Sixty-two, three-dimensional bone models of normal knees were analyzed. We computed the bias (mean), imprecision (±standard deviation), and limits of agreement (mean±2 standard deviations) of the angle between five anatomically defined tibial reference lines used in mechanically aligned (MA) TKA and the F-E tibial reference line (+external). The following are the bias, imprecision, and limits of agreement of the angle between the F-E tibial reference line and 1) the tibial reference lines connecting the medial border (-2°±6°, -14° to 10°), medial 1/3 (6°±6°, -6° to 18°), and the most anterior point of the tibial tubercle (9°±4°, -1° to 17°) with the center of the posterior cruciate ligament, and 2) the tibial reference lines perpendicular to the posterior condylar axis of the tibia (-3°±4°, -11° to 5°), and a line connecting the centers of the tibial condyles (1°±4°, -7° to 9°). Based on these in vitro findings, it might be prudent to reconsider setting the I-E rotation of the tibial component to tibial reference lines that have bias, imprecision, and limits of agreement that fall outside the -7° to 10° range associated with high function after KA TKA. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Measurement of the electric charge of the top quark in t t ¯ events

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Abazov, V. M.; Abbott, B.; Acharya, B. S.

    2014-09-01

    We present a measurement of the electric charge of top quarks usingmore » $$t\\bar{t}$$ events produced in $$p\\bar{p}$$ collisions at the Tevatron. The analysis is based on fully reconstructed $$t\\bar{t}$$ pairs in lepton+jets final states. Using data corresponding to 5.3 $$\\rm fb^{-1}$$ of integrated luminosity, we exclude the hypothesis that the top quark has a charge of $$Q=-4/3\\,e$$ at a significance greater than 5 standard deviations. We also place an upper limit of 0.46 on the fraction of such quarks that can be present in an admixture with the standard model top quarks ($$Q=+2/3\\,e$$) at a 95\\% confidence level.« less

  5. Spatiotemporal Parameters are not Substantially Influenced by Load Carriage or Inclination During Treadmill and Overground Walking

    PubMed Central

    Seay, Joseph F.; Gregorczyk, Karen N.; Hasselquist, Leif

    2016-01-01

    Abstract Influences of load carriage and inclination on spatiotemporal parameters were examined during treadmill and overground walking. Ten soldiers walked on a treadmill and overground with three load conditions (00 kg, 20 kg, 40 kg) during level, uphill (6% grade) and downhill (-6% grade) inclinations at self-selected speed, which was constant across conditions. Mean values and standard deviations for double support percentage, stride length and a step rate were compared across conditions. Double support percentage increased with load and inclination change from uphill to level walking, with a 0.4% stance greater increase at the 20 kg condition compared to 00 kg. As inclination changed from uphill to downhill, the step rate increased more overground (4.3 ± 3.5 steps/min) than during treadmill walking (1.7 ± 2.3 steps/min). For the 40 kg condition, the standard deviations were larger than the 00 kg condition for both the step rate and double support percentage. There was no change between modes for step rate standard deviation. For overground compared to treadmill walking, standard deviation for stride length and double support percentage increased and decreased, respectively. Changes in the load of up to 40 kg, inclination of 6% grade away from the level (i.e., uphill or downhill) and mode (treadmill and overground) produced small, yet statistically significant changes in spatiotemporal parameters. Variability, as assessed by standard deviation, was not systematically lower during treadmill walking compared to overground walking. Due to the small magnitude of changes, treadmill walking appears to replicate the spatiotemporal parameters of overground walking. PMID:28149338

  6. Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations.

    PubMed

    Hopper, John L

    2015-11-15

    How can the "strengths" of risk factors, in the sense of how well they discriminate cases from controls, be compared when they are measured on different scales such as continuous, binary, and integer? Given that risk estimates take into account other fitted and design-related factors-and that is how risk gradients are interpreted-so should the presentation of risk gradients. Therefore, for each risk factor X0, I propose using appropriate regression techniques to derive from appropriate population data the best fitting relationship between the mean of X0 and all the other covariates fitted in the model or adjusted for by design (X1, X2, … , Xn). The odds per adjusted standard deviation (OPERA) presents the risk association for X0 in terms of the change in risk per s = standard deviation of X0 adjusted for X1, X2, … , Xn, rather than the unadjusted standard deviation of X0 itself. If the increased risk is relative risk (RR)-fold over A adjusted standard deviations, then OPERA = exp[ln(RR)/A] = RR(s). This unifying approach is illustrated by considering breast cancer and published risk estimates. OPERA estimates are by definition independent and can be used to compare the predictive strengths of risk factors across diseases and populations. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. Molar heat capacity and entropy of calcium metal

    USGS Publications Warehouse

    Hemingway, B.S.; Robie, R.A.; Chase, M.W.

    1997-01-01

    The heat capacity of calcium has been measured at 85 mean temperatures between T ??? 8 K and T ??? 369 K using an adiabatically-shielded calorimeter in an intermittent heating mode. At T = 298.15 K, the recommended values for the molar heat capacity, molar entropy, and molar enthalpy increment referred to T = 0 are (25.77 ?? 0.08) J??K-1??mol-1, (42.90 ?? 0.11) J??K-1??mol-1, and (5811 ?? 12) J??mol-1, respectively. The uncertainties are twice the standard deviation of the mean. ?? 1997 Academic Press Limited.

  8. Rumsey and Walker_AMT_2016_Table 2.xlsx

    EPA Pesticide Factsheets

    Table summarizes instrument precision assessed by collocating the two sample boxes. Precision is quantified as the standard deviation of the residuals of an orthogonal least squares regression of concentrations from the two sample boxes. This allows for an estimation of gradient precision and ultimately gradient and flux detection limits. This dataset is associated with the following publication:Rumsey, I. Application of an online ion chromatography-based instrument for gradient flux measurements of speciated nitrogen and sulfur. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 9(6): 2581-2592, (2016).

  9. A flow injection chemiluminescence system for the determination of isoniazid.

    PubMed

    Huang, Y; Zhang, Z; Zhang, D; Lv, J

    2000-10-01

    A chemiluminescence (CL) flow system is described for the determination of isoniazid based on its enhancement on the chemiluminescence (CL) emission produced upon mixing a hexacyanoferrate(III) solution with an alkaline luminol solution. The system responds linearly to isoniazid concentration in the range 0-1 mg/L with a detection limit (3sigma) of 0.03 microg/L, relative standard deviation (RSD) of 1.2% for 0.1 mg/L isoniazid (n = 11). The system has been successfully applied to the determination of isoniazid in pharmaceutical preparations.

  10. The two errors of using the within-subject standard deviation (WSD) as the standard error of a reliable change index.

    PubMed

    Maassen, Gerard H

    2010-08-01

    In this Journal, Lewis and colleagues introduced a new Reliable Change Index (RCI(WSD)), which incorporated the within-subject standard deviation (WSD) of a repeated measurement design as the standard error. In this note, two opposite errors in using WSD this way are demonstrated. First, being the standard error of measurement of only a single assessment makes WSD too small when practice effects are absent. Then, too many individuals will be designated reliably changed. Second, WSD can grow unlimitedly to the extent that differential practice effects occur. This can even make RCI(WSD) unable to detect any reliable change.

  11. Measuring systems of hard to get objects: problems with analysis of measurement results

    NASA Astrophysics Data System (ADS)

    Gilewska, Grazyna

    2005-02-01

    The problem accessibility of metrological parameters features of objects appeared in many measurements. Especially if it is biological object which parameters very often determined on the basis of indirect research. Accidental component predominate in forming of measurement results with very limited access to measurement objects. Every measuring process has a lot of conditions limiting its abilities to any way processing (e.g. increase number of measurement repetition to decrease random limiting error). It may be temporal, financial limitations, or in case of biological object, small volume of sample, influence measuring tool and observers on object, or whether fatigue effects e.g. at patient. It's taken listing difficulties into consideration author worked out and checked practical application of methods outlying observation reduction and next innovative methods of elimination measured data with excess variance to decrease of mean standard deviation of measured data, with limited aomunt of data and accepted level of confidence. Elaborated methods wee verified on the basis of measurement results of knee-joint width space got from radiographs. Measurements were carried out by indirectly method on the digital images of radiographs. Results of examination confirmed legitimacy to using of elaborated methodology and measurement procedures. Such methodology has special importance when standard scientific ways didn't bring expectations effects.

  12. Gender Differences in Numeracy in Indonesia: Evidence from a Longitudinal Dataset

    ERIC Educational Resources Information Center

    Suryadarma, Daniel

    2015-01-01

    This paper uses a rich longitudinal dataset to measure the evolution of the gender differences in numeracy among school-age children in Indonesia. Girls outperformed boys by 0.08 standard deviations when the sample was around 11 years old. Seven years later, the gap has widened to 0.19 standard deviations, equivalent to around 18 months of…

  13. A Survey Data Response to the Teaching of Utility Curves and Risk Aversion

    ERIC Educational Resources Information Center

    Hobbs, Jeffrey; Sharma, Vivek

    2011-01-01

    In many finance and economics courses as well as in practice, the concept of risk aversion is reduced to the standard deviation of returns, whereby risk-averse investors prefer to minimize their portfolios' standard deviations. In reality, the concept of risk aversion is richer and more interesting than this, and can easily be conveyed through…

  14. On the Linear Relation between the Mean and the Standard Deviation of a Response Time Distribution

    ERIC Educational Resources Information Center

    Wagenmakers, Eric-Jan; Brown, Scott

    2007-01-01

    Although it is generally accepted that the spread of a response time (RT) distribution increases with the mean, the precise nature of this relation remains relatively unexplored. The authors show that in several descriptive RT distributions, the standard deviation increases linearly with the mean. Results from a wide range of tasks from different…

  15. A novel sorbent based on carbon nanotube/amino-functionalized sol-gel for the headspace solid-phase microextraction of α-bisabolol from medicinal plant samples using experimental design.

    PubMed

    Yarazavi, Mina; Noroozian, Ebrahim

    2018-02-13

    A novel sol-gel coating on a stainless-steel fiber was developed for the first time for the headspace solid-phase microextraction and determination of α-bisabolol with gas chromatography and flame ionization detection. The parameters influencing the efficiency of solid-phase microextraction process, such as extraction time and temperature, pH, and ionic strength, were optimized by the experimental design method. Under optimized conditions, the linear range was between 0.0027 and 100 μg/mL. The relative standard deviations determined at 0.01 and 1.0 μg/mL concentration levels (n = 3), respectively, were as follows: intraday relative standard deviations 3.4 and 3.3%; interday relative standard deviations 5.0 and 4.3%; and fiber-to-fiber relative standard deviations 6.0 and 3.5%. The relative recovery values were 90.3 and 101.4% at 0.01 and 1.0 μg/mL spiking levels, respectively. The proposed method was successfully applied to various real samples containing α-bisabolol. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Results of an interlaboratory method performance study for the size determination and quantification of silver nanoparticles in chicken meat by single-particle inductively coupled plasma mass spectrometry (sp-ICP-MS).

    PubMed

    Weigel, Stefan; Peters, Ruud; Loeschner, Katrin; Grombe, Ringo; Linsinger, Thomas P J

    2017-08-01

    Single-particle inductively coupled plasma mass spectrometry (sp-ICP-MS) promises fast and selective determination of nanoparticle size and number concentrations. While several studies on practical applications have been published, data on formal, especially interlaboratory validation of sp-ICP-MS, is sparse. An international interlaboratory study was organized to determine repeatability and reproducibility of the determination of the median particle size and particle number concentration of Ag nanoparticles (AgNPs) in chicken meat. Ten laboratories from the European Union, the USA, and Canada determined particle size and particle number concentration of two chicken meat homogenates spiked with polyvinylpyrrolidone (PVP)-stabilized AgNPs. For the determination of the median particle diameter, repeatability standard deviations of 2 and 5% were determined, and reproducibility standard deviations were 15 and 25%, respectively. The equivalent median diameter itself was approximately 60% larger than the diameter of the particles in the spiking solution. Determination of the particle number concentration was significantly less precise, with repeatability standard deviations of 7 and 18% and reproducibility standard deviations of 70 and 90%.

  17. Estimation of Tooth Size Discrepancies among Different Malocclusion Groups

    PubMed Central

    Bala, Madhu; Goyal, Virender

    2014-01-01

    ABSTRACT Regards and Tribute: Late Dr Narender Hasija was a mentor and visionary in the light of knowledge and experience. We pay our regards with deepest gratitude to the departed soul to rest in peace. Bolton’s ratios help in estimating overbite, overjet relationships, the effects of contemplated extractions on posterior occlusion, incisor relationships and identification of occlusal misfit produced by tooth size discrepancies. Aim: To determine any difference in tooth size discrepancy in anterior as well as overall ratio in different malocclusions and comparison with Bolton’s study. Materials and methods: After measuring the teeth on all 100 patients, Bolton’s analysis was performed. Results were compared with Bolton’s means and standard deviations. The results were also subjected to statistical analysis. Results show that the mean and standard deviations of ideal occlusion cases are comparable with those Bolton but, when the mean and standard deviation of malocclusion groups are compared with those of Bolton, the values of standard deviation are higher, though the mean is comparable. How to cite this article: Hasija N, Bala M, Goyal V. Estimation of Tooth Size Discrepancies among Different Malocclusion Groups. Int J Clin Pediatr Dent 2014;7(2):82-85. PMID:25356005

  18. Accuracy Evaluation of a Stereolithographic Surgical Template for Dental Implant Insertion Using 3D Superimposition Protocol.

    PubMed

    Cristache, Corina Marilena; Gurbanescu, Silviu

    2017-01-01

    of this study was to evaluate the accuracy of a stereolithographic template, with sleeve structure incorporated into the design, for computer-guided dental implant insertion in partially edentulous patients. Sixty-five implants were placed in twenty-five consecutive patients with a stereolithographic surgical template. After surgery, digital impression was taken and 3D inaccuracy of implants position at entry point, apex, and angle deviation was measured using an inspection tool software. Mann-Whitney U test was used to compare accuracy between maxillary and mandibular surgical guides. A p value < .05 was considered significant. Mean (and standard deviation) of 3D error at the entry point was 0.798 mm (±0.52), at the implant apex it was 1.17 mm (±0.63), and mean angular deviation was 2.34 (±0.85). A statistically significant reduced 3D error was observed at entry point p = .037, at implant apex p = .008, and also in angular deviation p = .030 in mandible when comparing to maxilla. The surgical template used has proved high accuracy for implant insertion. Within the limitations of the present study, the protocol for comparing a digital file (treatment plan) with postinsertion digital impression may be considered a useful procedure for assessing surgical template accuracy, avoiding radiation exposure, during postoperative CBCT scanning.

  19. Development and operation of a quality assurance system for deviations from standard operating procedures in a clinical cell therapy laboratory.

    PubMed

    McKenna, D; Kadidlo, D; Sumstad, D; McCullough, J

    2003-01-01

    Errors and accidents, or deviations from standard operating procedures, other policy, or regulations must be documented and reviewed, with corrective actions taken to assure quality performance in a cellular therapy laboratory. Though expectations and guidance for deviation management exist, a description of the framework for the development of such a program is lacking in the literature. Here we describe our deviation management program, which uses a Microsoft Access database and Microsoft Excel to analyze deviations and notable events, facilitating quality assurance (QA) functions and ongoing process improvement. Data is stored in a Microsoft Access database with an assignment to one of six deviation type categories. Deviation events are evaluated for potential impact on patient and product, and impact scores for each are determined using a 0- 4 grading scale. An immediate investigation occurs, and corrective actions are taken to prevent future similar events from taking place. Additionally, deviation data is collectively analyzed on a quarterly basis using Microsoft Excel, to identify recurring events or developing trends. Between January 1, 2001 and December 31, 2001 over 2500 products were processed at our laboratory. During this time period, 335 deviations and notable events occurred, affecting 385 products and/or patients. Deviations within the 'technical error' category were most common (37%). Thirteen percent of deviations had a patient and/or a product impact score > or = 2, a score indicating, at a minimum, potentially affected patient outcome or moderate effect upon product quality. Real-time analysis and quarterly review of deviations using our deviation management program allows for identification and correction of deviations. Monitoring of deviation trends allows for process improvement and overall successful functioning of the QA program in the cell therapy laboratory. Our deviation management program could serve as a model for other laboratories in need of such a program.

  20. Ku-band radar threshold analysis

    NASA Technical Reports Server (NTRS)

    Weber, C. L.; Polydoros, A.

    1979-01-01

    The statistics of the CFAR threshold for the Ku-band radar was determined. Exact analytical results were developed for both the mean and standard deviations in the designated search mode. The mean value is compared to the results of a previously reported simulation. The analytical results are more optimistic than the simulation results, for which no explanation is offered. The normalized standard deviation is shown to be very sensitive to signal-to-noise ratio and very insensitive to the noise correlation present in the range gates of the designated search mode. The substantial variation in the CFAR threshold is dominant at large values of SNR where the normalized standard deviation is greater than 0.3. Whether or not this significantly affects the resulting probability of detection is a matter which deserves additional attention.

  1. Standard deviation analysis of the mastoid fossa temperature differential reading: a potential model for objective chiropractic assessment.

    PubMed

    Hart, John

    2011-03-01

    This study describes a model for statistically analyzing follow-up numeric-based chiropractic spinal assessments for an individual patient based on his or her own baseline. Ten mastoid fossa temperature differential readings (MFTD) obtained from a chiropractic patient were used in the study. The first eight readings served as baseline and were compared to post-adjustment readings. One of the two post-adjustment MFTD readings fell outside two standard deviations of the baseline mean and therefore theoretically represents improvement according to pattern analysis theory. This study showed how standard deviation analysis may be used to identify future outliers for an individual patient based on his or her own baseline data. Copyright © 2011 National University of Health Sciences. Published by Elsevier Inc. All rights reserved.

  2. Limits of detection and decision. Part 4

    NASA Astrophysics Data System (ADS)

    Voigtman, E.

    2008-02-01

    Probability density functions (PDFs) have been derived for a number of commonly used limit of detection definitions, including several variants of the Relative Standard Deviation of the Background-Background Equivalent Concentration (RSDB-BEC) method, for a simple linear chemical measurement system (CMS) having homoscedastic, Gaussian measurement noise and using ordinary least squares (OLS) processing. All of these detection limit definitions serve as both decision and detection limits, thereby implicitly resulting in 50% rates of Type 2 errors. It has been demonstrated that these are closely related to Currie decision limits, if the coverage factor, k, is properly defined, and that all of the PDFs are scaled reciprocals of noncentral t variates. All of the detection limits have well-defined upper and lower limits, thereby resulting in finite moments and confidence limits, and the problem of estimating the noncentrality parameter has been addressed. As in Parts 1-3, extensive Monte Carlo simulations were performed and all the simulation results were found to be in excellent agreement with the derived theoretical expressions. Specific recommendations for harmonization of detection limit methodology have also been made.

  3. Cellular effects of acute exposure to high peak power microwave systems: Morphology and toxicology.

    PubMed

    Ibey, Bennett L; Roth, Caleb C; Ledwig, Patrick B; Payne, Jason A; Amato, Alayna L; Dalzell, Danielle R; Bernhard, Joshua A; Doroski, Michael W; Mylacraine, Kevin S; Seaman, Ronald L; Nelson, Gregory S; Woods, Clifford W

    2016-03-15

    Electric fields produced by advanced pulsed microwave transmitter technology now readily exceed the Institute of Electrical and Electronic Engineers (IEEE) C.95.1 peak E-field limit of 100 kV/m, highlighting a need for scientific validation of such a specific limit. Toward this goal, we exposed Jurkat Clone E-6 human lymphocyte preparations to 20 high peak power microwave (HPPM) pulses (120 ns duration) with a mean peak amplitude of 2.3 MV/m and standard deviation of 0.1 with the electric field at cells predicted to range from 0.46 to 2.7 MV/m, well in excess of current standard limit. We observed that membrane integrity and cell morphology remained unchanged 4 h after exposure and cell survival 24 h after exposure was not statistically different from sham exposure or control samples. Using flow cytometry to analyze membrane disruption and morphological changes per exposed cell, no changes were observed in HPPM-exposed samples. Current IEEE C95.1-2005 standards for pulsed radiofrequency exposure limits peak electric field to 100 kV/m for pulses shorter than 100 ms [IEEE (1995) PC95.1-Standard for Safety Levels with Respect to Human Exposure to Electric, Magnetic and Electromagnetic Fields, 0 Hz to 300 GHz, Institute of Electrical and Electronic Engineers: Piscataway, NJ, USA]. This may impose large exclusion zones that limit HPPM technology use. In this study, we offer evidence that maximum permissible exposure of 100 kV/m for peak electric field may be unnecessarily restrictive for HPPM devices. Bioelectromagnetics. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  4. Effects of Random Shadings, Phasing Errors, and Element Failures on the Beam Patterns of Linear and Planar Arrays

    DTIC Science & Technology

    1980-03-14

    failure Sigmar (Or) in line 50, the standard deviation of the relative error of the weights Sigmap (o) in line 60, the standard deviation of the phase...200, the weight structures in the x and y coordinates Q in line 210, the probability of element failure Sigmar (Or) in line 220, the standard...NUMBER OF ELEMENTS =u;2*H 120 PRINT "Pr’obability of elemenit failure al;O 130 PRINT "Standard dtvi&t ion’ oe r.1&tive ýrror of wl; Sigmar 14 0 PRINT

  5. SU-E-I-59: Investigation of the Usefulness of a Standard Deviation and Mammary Gland Density as Indexes for Mammogram Classification.

    PubMed

    Takarabe, S; Yabuuchi, H; Morishita, J

    2012-06-01

    To investigate the usefulness of the standard deviation of pixel values in a whole mammary glands region and the percentage of a high- density mammary glands region to a whole mammary glands region as features for classification of mammograms into four categories based on the ACR BI-RADS breast composition. We used 36 digital mediolateral oblique view mammograms (18 patients) approved by our IRB. These images were classified into the four categories of breast compositions by an experienced breast radiologist and the results of the classification were regarded as a gold standard. First, a whole mammary region in a breast was divided into two regions such as a high-density mammary glands region and a low/iso-density mammary glands region by using a threshold value that was obtained from the pixel values corresponding to a pectoral muscle region. Then the percentage of a high-density mammary glands region to a whole mammary glands region was calculated. In addition, as a new method, the standard deviation of pixel values in a whole mammary glands region was calculated as an index based on the intermingling of mammary glands and fats. Finally, all mammograms were classified by using the combination of the percentage of a high-density mammary glands region and the standard deviation of each image. The agreement rates of the classification between our proposed method and gold standard was 86% (31/36). This result signified that our method has the potential to classify mammograms. The combination of the standard deviation of pixel values in a whole mammary glands region and the percentage of a high-density mammary glands region to a whole mammary glands region was available as features to classify mammograms based on the ACR BI- RADS breast composition. © 2012 American Association of Physicists in Medicine.

  6. Are LOD and LOQ Reliable Parameters for Sensitivity Evaluation of Spectroscopic Methods?

    PubMed

    Ershadi, Saba; Shayanfar, Ali

    2018-03-22

    The limit of detection (LOD) and the limit of quantification (LOQ) are common parameters to assess the sensitivity of analytical methods. In this study, the LOD and LOQ of previously reported terbium sensitized analysis methods were calculated by different methods, and the results were compared with sensitivity parameters [lower limit of quantification (LLOQ)] of U.S. Food and Drug Administration guidelines. The details of the calibration curve and standard deviation of blank samples of three different terbium-sensitized luminescence methods for the quantification of mycophenolic acid, enrofloxacin, and silibinin were used for the calculation of LOD and LOQ. A comparison of LOD and LOQ values calculated by various methods and LLOQ shows a considerable difference. The significant difference of the calculated LOD and LOQ with various methods and LLOQ should be considered in the sensitivity evaluation of spectroscopic methods.

  7. Determination of the neuropharmacological drug nodakenin in rat plasma and brain tissues by liquid chromatography tandem mass spectrometry: Application to pharmacokinetic studies.

    PubMed

    Song, Yingshi; Yan, Huiyu; Xu, Jingbo; Ma, Hongxi

    2017-09-01

    A rapid and sensitive liquid chromatography tandem mass spectrometry detection using selected reaction monitoring in positive ionization mode was developed and validated for the quantification of nodakenin in rat plasma and brain. Pareruptorin A was used as internal standard. A single step liquid-liquid extraction was used for plasma and brain sample preparation. The method was validated with respect to selectivity, precision, accuracy, linearity, limit of quantification, recovery, matrix effect and stability. Lower limit of quantification of nodakenin was 2.0 ng/mL in plasma and brain tissue homogenates. Linear calibration curves were obtained over concentration ranges of 2.0-1000 ng/mL in plasma and brain tissue homogenates for nodakenin. Intra-day and inter-day precisions (relative standard deviation, RSD) were <15% in both biological media. This assay was successfully applied to plasma and brain pharmacokinetic studies of nodakenin in rats after intravenous administration. Copyright © 2017 John Wiley & Sons, Ltd.

  8. MO-F-CAMPUS-T-03: Data Driven Approaches for Determination of Treatment Table Tolerance Values for Record and Verification Systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Gupta, N; DiCostanzo, D; Fullenkamp, M

    2015-06-15

    Purpose: To determine appropriate couch tolerance values for modern radiotherapy linac R&V systems with indexed patient setup. Methods: Treatment table tolerance values have been the most difficult to lower, due to many factors including variations in patient positioning and differences in table tops between machines. We recently installed nine linacs with similar tables and started indexing every patient in our clinic. In this study we queried our R&V database and analyzed the deviation of couch position values from the acquired values at verification simulation for all patients treated with indexed positioning. Mean and standard deviations of daily setup deviations weremore » computed in the longitudinal, lateral and vertical direction for 343 patient plans. The mean, median and standard error of the standard deviations across the whole patient population and for some disease sites were computed to determine tolerance values. Results: The plot of our couch deviation values showed a gaussian distribution, with some small deviations, corresponding to setup uncertainties on non-imaging days, and SRS/SRT/SBRT patients, as well as some large deviations which were spot checked and found to be corresponding to indexing errors that were overriden. Setting our tolerance values based on the median + 1 standard error resulted in tolerance values of 1cm lateral and longitudinal, and 0.5 cm vertical for all non- SRS/SRT/SBRT cases. Re-analizing the data, we found that about 92% of the treated fractions would be within these tolerance values (ignoring the mis-indexed patients). We also analyzed data for disease site based subpopulations and found no difference in the tolerance values that needed to be used. Conclusion: With the use of automation, auto-setup and other workflow efficiency tools being introduced into radiotherapy workflow, it is very essential to set table tolerances that allow safe treatments, but flag setup errors that need to be reassessed before treatments.« less

  9. Global optimization of minority game by intelligent agents

    NASA Astrophysics Data System (ADS)

    Xie, Yan-Bo; Wang, Bing-Hong; Hu, Chin-Kun; Zhou, Tao

    2005-10-01

    We propose a new model of minority game with intelligent agents who use trail and error method to make a choice such that the standard deviation σ2 and the total loss in this model reach the theoretical minimum values in the long time limit and the global optimization of the system is reached. This suggests that the economic systems can self-organize into a highly optimized state by agents who make decisions based on inductive thinking, limited knowledge, and capabilities. When other kinds of agents are also present, the simulation results and analytic calculations show that the intelligent agent can gain profits from producers and are much more competent than the noise traders and conventional agents in original minority games proposed by Challet and Zhang.

  10. Determination of benzocaine in rainbow trout plasma

    USGS Publications Warehouse

    Bernardy, Jeffery A.; Coleman, K.S.; Stehly, G.R.; Gingerich, William H.

    1996-01-01

    A liquid chromatographic method is described for analysis of benzocaine (BZ), a proposed fish anesthetic, in rainbow trout plasma, Mean recoveries of BZ from plasma samples fortified at 44-10 100 ng/mL were 96-100%. The method detection limit is 10 ng/mL, and the limit of quantitation is 37 ng/mL. Acetylation of BZ occurs in whole blood after storage at room temperature (i.e., 21 degrees C) for 10 min. However, no acetylation of BZ was detected in plasma samples held at room temperature for 4 h, Mean method precision for plasma samples with incurred BZ residue is similar to that for fortified samples in the same concentration range (relative standard deviations of 0.9 and 1.2%, respectively).

  11. Search for WZ resonances in the fully leptonic channel using pp collisions at √s=8 TeV with the ATLAS detector

    DOE PAGES

    Aad, G.; Abbott, B.; Abdallah, J.; ...

    2014-10-07

    A search for resonant WZ production in the ℓνℓ'ℓ' (ℓ,ℓ'=e,μ) decay channel using 20.3 fb -1 of √s = 8 TeV pp collision data collected by the ATLAS experiment at LHC is presented. No significant deviation from the Standard Model prediction is observed and upper limits on the production cross sections of WZ resonances from an extended gauge model W' and from a simplified model of heavy vector triplets are derived. As a result, a corresponding observed (expected) lower mass limit of 1.52 (1.49) TeV is derived for the W' at the 95% confidence level.

  12. Extremal inversion of lunar travel time data. [seismic velocity structure

    NASA Technical Reports Server (NTRS)

    Burkhard, N.; Jackson, D. D.

    1975-01-01

    The tau method, developed by Bessonova et al. (1974), of inversion of travel times is applied to lunar P-wave travel time data to find limits on the velocity structure of the moon. Tau is the singular solution to the Clairaut equation. Models with low-velocity zones, with low-velocity zones at differing depths, and without low-velocity zones, were found to be consistent with data and within the determined limits. Models with and without a discontinuity at about 25-km depth have been found which agree with all travel time data to within two standard deviations. In other words, the existence of the discontinuity and its size and location have not been uniquely resolved. Models with low-velocity channels are also possible.

  13. Evidence for the associated production of the Higgs boson and a top quark pair with the ATLAS detector

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aaboud, M.; Aad, G.; Abbott, B.

    Here, a search for the associated production of the Higgs boson with a top quark pair (more » $$t\\bar{t}$$H) is reported. The search is performed in multilepton final states using a data set corresponding to an integrated luminosity of 36.1 fb -1 of proton-proton collision data recorded by the ATLAS experiment at a center-of-mass energy $$\\sqrt{s}$$ = 13 TeV at the Large Hadron Collider. Higgs boson decays to WW*, ττ, and ZZ* are targeted. Seven final states, categorized by the number and flavor of charged-lepton candidates, are examined for the presence of the Standard Model Higgs boson with a mass of 125 GeV and a pair of top quarks. An excess of events over the expected background from Standard Model processes is found with an observed significance of 4.1 standard deviations, compared to an expectation of 2.8 standard deviations. The best fit for the $$t\\bar{t}$$H production cross section is σ($$t\\bar{t}$$H) = $${790}_{-210}^{+230}$$ fb, in agreement with the Standard Model prediction of $${507}_{-50}^{+35}$$ fb. The combination of this result with other $$t\\bar{t}$$H searches from the ATLAS experiment using the Higgs boson decay modes to $$b\\bar{b}$$, γγ and ZZ* → 4ℓ, has an observed significance of 4.2 standard deviations, compared to an expectation of 3.8 standard deviations. This provides evidence for the $$t\\bar{t}$$H production mode.« less

  14. Evidence for the associated production of the Higgs boson and a top quark pair with the ATLAS detector

    DOE PAGES

    Aaboud, M.; Aad, G.; Abbott, B.; ...

    2018-04-09

    Here, a search for the associated production of the Higgs boson with a top quark pair (more » $$t\\bar{t}$$H) is reported. The search is performed in multilepton final states using a data set corresponding to an integrated luminosity of 36.1 fb -1 of proton-proton collision data recorded by the ATLAS experiment at a center-of-mass energy $$\\sqrt{s}$$ = 13 TeV at the Large Hadron Collider. Higgs boson decays to WW*, ττ, and ZZ* are targeted. Seven final states, categorized by the number and flavor of charged-lepton candidates, are examined for the presence of the Standard Model Higgs boson with a mass of 125 GeV and a pair of top quarks. An excess of events over the expected background from Standard Model processes is found with an observed significance of 4.1 standard deviations, compared to an expectation of 2.8 standard deviations. The best fit for the $$t\\bar{t}$$H production cross section is σ($$t\\bar{t}$$H) = $${790}_{-210}^{+230}$$ fb, in agreement with the Standard Model prediction of $${507}_{-50}^{+35}$$ fb. The combination of this result with other $$t\\bar{t}$$H searches from the ATLAS experiment using the Higgs boson decay modes to $$b\\bar{b}$$, γγ and ZZ* → 4ℓ, has an observed significance of 4.2 standard deviations, compared to an expectation of 3.8 standard deviations. This provides evidence for the $$t\\bar{t}$$H production mode.« less

  15. Evidence for the associated production of the Higgs boson and a top quark pair with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allaire, C.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Ambroz, L.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkin, R. J.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Avramidou, R.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Bakker, P. J.; Bakshi Gupta, D.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. 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A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Eramo, L.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dahbi, S.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vasconcelos Corga, K.; de Vivie de Regie, J. B.; Debenedetti, C.; Dedovich, D. 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B.; Dobre, M.; Dodsworth, D.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dreyer, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubinin, F.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dulsen, C.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duperrin, A.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Ennis, J. S.; Epland, M. B.; Erdmann, J.; Ereditato, A.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feickert, M.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, M.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores, L. M.; Flores Castillo, L. R.; Fomin, N.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Freund, W. S.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gasnikova, K.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giangiacomi, N.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugliarelli, G.; Giugni, D.; Giuli, F.; Giulini, M.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Gonella, G.; Gonella, L.; Gongadze, A.; Gonnella, F.; Gonski, J. L.; González de La Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Goy, C.; Gozani, E.; Grabowska-Bold, I.; Gradin, P. O. J.; Graham, E. C.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Grummer, A.; Guan, L.; Guan, W.; Guenther, J.; Guerguichon, A.; Guescini, F.; Guest, D.; Gueta, O.; Gugel, R.; Gui, B.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gurbuz, S.; Gustavino, G.; Gutelman, B. J.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Han, K.; Han, L.; Han, S.; Hanagaki, K.; Hance, M.; Handl, D. M.; Haney, B.; Hankache, R.; Hanke, P.; Hansen, E.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Harkusha, S.; Harrison, P. F.; Hartmann, N. M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heer, S.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herr, H.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; Hildebrand, K.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hils, M.; Hinchliffe, I.; Hirose, M.; Hirschbuehl, D.; Hiti, B.; Hladik, O.; Hlaluku, D. R.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Hohov, D.; Holmes, T. R.; Holzbock, M.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Horyn, L. A.; Hostachy, J.-Y.; Hostiuc, A.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hrdinka, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Huhtinen, M.; Hunter, R. F. H.; Huo, P.; Hupe, A. M.; Huseynov, N.; Huston, J.; Huth, J.; Hyneman, R.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iguchi, R.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Iliadis, D.; Ilic, N.; Iltzsche, F.; Introzzi, G.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Isacson, M. F.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, P.; Jacobs, R. M.; Jain, V.; Jakel, G.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javå¯Rek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. J.; Jon-And, K.; Jones, R. W. L.; Jones, S. D.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Junggeburth, J. J.; Juste Rozas, A.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanjir, L.; Kano, Y.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karpov, S. N.; Karpova, Z. M.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kay, E. F.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kellermann, E.; Kempster, J. J.; Kendrick, J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-Zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khodinov, A.; Khoo, T. 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Y.; Shen, Y.; Sherafati, N.; Sherman, A. D.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silva, M.; Silverstein, S. B.; Simic, L.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffa, A. M.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, W.; Sopczak, A.; Sopkova, F.; Sosa, D.; Sotiropoulou, C. L.; Sottocornola, S.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Stegler, M.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, T. J.; Stewart, G. A.; Stockton, M. C.; Stoicea, G.; Stolte, P.; Stonjek, S.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, D. M. S.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sydorenko, A.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeda, K.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarek Abouelfadl Mohamed, A. T.; Tarem, S.; Tarna, G.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, A. J.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Thais, S. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tian, Y.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Uno, K.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Vallier, A.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Furelos, D.; Vazquez Schroeder, T.; Veatch, J.; Vecchio, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von Buddenbrock, S. E.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Wakamiya, K.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, A. M.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.-J.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. M.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, A.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Woods, N. L.; Worm, S. D.; Wosiek, B. K.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Xu, W.; Yabsley, B.; Yacoob, S.; Yajima, K.; Yallup, D. P.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamanaka, T.; Yamane, F.; Yamatani, M.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, S.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zhulanov, V.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

    2018-04-01

    A search for the associated production of the Higgs boson with a top quark pair (t t ¯H ) is reported. The search is performed in multilepton final states using a data set corresponding to an integrated luminosity of 36.1 fb-1 of proton-proton collision data recorded by the ATLAS experiment at a center-of-mass energy √{s }=13 TeV at the Large Hadron Collider. Higgs boson decays to W W*, τ τ , and Z Z* are targeted. Seven final states, categorized by the number and flavor of charged-lepton candidates, are examined for the presence of the Standard Model Higgs boson with a mass of 125 GeV and a pair of top quarks. An excess of events over the expected background from Standard Model processes is found with an observed significance of 4.1 standard deviations, compared to an expectation of 2.8 standard deviations. The best fit for the t t ¯H production cross section is σ (t t ¯H )=79 0-210+230 fb , in agreement with the Standard Model prediction of 50 7-50+35 fb . The combination of this result with other t t ¯H searches from the ATLAS experiment using the Higgs boson decay modes to b b ¯, γ γ and Z Z*→4 ℓ, has an observed significance of 4.2 standard deviations, compared to an expectation of 3.8 standard deviations. This provides evidence for the t t ¯H production mode.

  16. Analysis of hydrazine in drinking water by isotope dilution gas chromatography/tandem mass spectrometry with derivatization and liquid-liquid extraction.

    PubMed

    Davis, William E; Li, Yongtao

    2008-07-15

    A new isotope dilution gas chromatography/chemical ionization/tandem mass spectrometric method was developed for the analysis of carcinogenic hydrazine in drinking water. The sample preparation was performed by using the optimized derivatization and multiple liquid-liquid extraction techniques. Using the direct aqueous-phase derivatization with acetone, hydrazine and isotopically labeled hydrazine-(15)N2 used as the surrogate standard formed acetone azine and acetone azine-(15)N2, respectively. These derivatives were then extracted with dichloromethane. Prior to analysis using methanol as the chemical ionization reagent gas, the extract was dried with anhydrous sodium sulfate, concentrated through evaporation, and then fortified with isotopically labeled N-nitrosodimethylamine-d6 used as the internal standard to quantify the extracted acetone azine-(15)N2. The extracted acetone azine was quantified against the extracted acetone azine-(15)N2. The isotope dilution standard calibration curve resulted in a linear regression correlation coefficient (R) of 0.999. The obtained method detection limit was 0.70 ng/L for hydrazine in reagent water samples, fortified at a concentration of 1.0 ng/L. For reagent water samples fortified at a concentration of 20.0 ng/L, the mean recoveries were 102% with a relative standard deviation of 13.7% for hydrazine and 106% with a relative standard deviation of 12.5% for hydrazine-(15)N2. Hydrazine at 0.5-2.6 ng/L was detected in 7 out of 13 chloraminated drinking water samples but was not detected in the rest of the chloraminated drinking water samples and the studied chlorinated drinking water sample.

  17. Management of obstructive sleep apnea in the indigent population: a deviation of standard of care?

    PubMed

    Hamblin, John S; Sandulache, Vlad C; Alapat, Philip M; Takashima, Masayoshi

    2014-03-01

    Comprehensive management of patients with obstructive sleep apnea (OSA) typically is managed best via a multidisciplinary approach, involving otolaryngologists, sleep psychologists/psychiatrists, pulmonologists, neurologists, oral surgeons, and sleep trained dentists. By utilizing these resources, one could fashion a treatment individualized to the patient, giving rise to the holistic phrase of "personalized medicine." Unfortunately, in situations and environments with limited resources, the treatment options in an otolaryngologist's armamentarium are restricted--typically to continuous positive airway pressure (CPAP) versus sleep surgery. However, a recent patient encounter highlighted here shows how a hospital's reimbursement policy effectively dictated a patient's medical management to sleep surgery. This occurred although the current gold standard for the initial treatment of OSA is CPAP. Changing the course of medical/surgical management by selectively restricting funding is a cause of concern, especially when it promotes patients to choose a treatment option that is not considered the current standard of care.

  18. WASP (Write a Scientific Paper) using Excel -5: Quartiles and standard deviation.

    PubMed

    Grech, Victor

    2018-03-01

    The almost inevitable descriptive statistics exercise that is undergone once data collection is complete, prior to inferential statistics, requires the acquisition of basic descriptors which may include standard deviation and quartiles. This paper provides pointers as to how to do this in Microsoft Excel™ and explains the relationship between the two. Copyright © 2018 Elsevier B.V. All rights reserved.

  19. Validation Test Report for GDEM4

    DTIC Science & Technology

    2010-08-19

    standard deviations called the Generalized Digital Environmental Model ( GDEM ). The present document describes the development and evaluation of GDEM4...the newest version of GDEM . As part of the evaluation of GDEM4, comparisons are made in this report to GDEM3 and to four other ocean climatologies...depth climatology of temperature and salinity and their standard deviations called the Generalized Digital Environmental Model ( GDEM ). The history of

  20. Tree-ring-based drought reconstruction in the Iberian Range (east of Spain) since 1694

    NASA Astrophysics Data System (ADS)

    Tejedor, Ernesto; de Luis, Martín; Cuadrat, José María; Esper, Jan; Saz, Miguel Ángel

    2016-03-01

    Droughts are a recurrent phenomenon in the Mediterranean basin with negative consequences for society, economic activities, and natural systems. Nevertheless, the study of drought recurrence and severity in Spain has been limited so far due to the relatively short instrumental period. In this work, we present a reconstruction of the standardized precipitation index (SPI) for the Iberian Range. Growth variations and climatic signals within the network are assessed developing a correlation matrix and the data combined to a single chronology integrating 336 samples from 169 trees of five different pine species distributed throughout the province of Teruel. The new chronology, calibrated against regional instrumental climatic data, shows a high and stable correlation with the July SPI integrating moisture conditions over 12 months forming the basis for a 318-year drought reconstruction. The climate signal contained in this reconstruction is highly significant ( p < 0.05) and spatially robust over the interior areas of Spain located above 1000 meters above sea level (masl). According to our SPI reconstruction, seven substantially dry and five wet periods are identified since the late seventeenth century considering ≥±1.76 standard deviations. Besides these, 36 drought and 28 pluvial years were identified. Some of these years, such as 1725, 1741, 1803, and 1879, are also revealed in other drought reconstructions in Romania and Turkey, suggesting that coherent larger-scale synoptic patterns drove these extreme deviations. Since regional drought deviations are also retained in historical documents, the tree-ring-based reconstruction presented here will allow us to cross-validate drought frequency and magnitude in a highly vulnerable region.

  1. Tree-ring-based drought reconstruction in the Iberian Range (east of Spain) since 1694.

    PubMed

    Tejedor, Ernesto; de Luis, Martín; Cuadrat, José María; Esper, Jan; Saz, Miguel Ángel

    2016-03-01

    Droughts are a recurrent phenomenon in the Mediterranean basin with negative consequences for society, economic activities, and natural systems. Nevertheless, the study of drought recurrence and severity in Spain has been limited so far due to the relatively short instrumental period. In this work, we present a reconstruction of the standardized precipitation index (SPI) for the Iberian Range. Growth variations and climatic signals within the network are assessed developing a correlation matrix and the data combined to a single chronology integrating 336 samples from 169 trees of five different pine species distributed throughout the province of Teruel. The new chronology, calibrated against regional instrumental climatic data, shows a high and stable correlation with the July SPI integrating moisture conditions over 12 months forming the basis for a 318-year drought reconstruction. The climate signal contained in this reconstruction is highly significant (p < 0.05) and spatially robust over the interior areas of Spain located above 1000 meters above sea level (masl). According to our SPI reconstruction, seven substantially dry and five wet periods are identified since the late seventeenth century considering ≥±1.76 standard deviations. Besides these, 36 drought and 28 pluvial years were identified. Some of these years, such as 1725, 1741, 1803, and 1879, are also revealed in other drought reconstructions in Romania and Turkey, suggesting that coherent larger-scale synoptic patterns drove these extreme deviations. Since regional drought deviations are also retained in historical documents, the tree-ring-based reconstruction presented here will allow us to cross-validate drought frequency and magnitude in a highly vulnerable region.

  2. When things go pear shaped: contour variations of contacts

    NASA Astrophysics Data System (ADS)

    Utzny, Clemens

    2013-04-01

    Traditional control of critical dimensions (CD) on photolithographic masks considers the CD average and a measure for the CD variation such as the CD range or the standard deviation. Also systematic CD deviations from the mean such as CD signatures are subject to the control. These measures are valid for mask quality verification as long as patterns across a mask exhibit only size variations and no shape variation. The issue of shape variations becomes especially important in the context of contact holes on EUV masks. For EUV masks the CD error budget is much smaller than for standard optical masks. This means that small deviations from the contact shape can impact EUV waver prints in the sense that contact shape deformations induce asymmetric bridging phenomena. In this paper we present a detailed study of contact shape variations based on regular product data. Two data sets are analyzed: 1) contacts of varying target size and 2) a regularly spaced field of contacts. Here, the methods of statistical shape analysis are used to analyze CD SEM generated contour data. We demonstrate that contacts on photolithographic masks do not only show size variations but exhibit also pronounced nontrivial shape variations. In our data sets we find pronounced shape variations which can be interpreted as asymmetrical shape squeezing and contact rounding. Thus we demonstrate the limitations of classic CD measures for describing the feature variations on masks. Furthermore we show how the methods of statistical shape analysis can be used for quantifying the contour variations thus paving the way to a new understanding of mask linearity and its specification.

  3. Spectral combination of spherical gravitational curvature boundary-value problems

    NASA Astrophysics Data System (ADS)

    PitoÅák, Martin; Eshagh, Mehdi; Šprlák, Michal; Tenzer, Robert; Novák, Pavel

    2018-04-01

    Four solutions of the spherical gravitational curvature boundary-value problems can be exploited for the determination of the Earth's gravitational potential. In this article we discuss the combination of simulated satellite gravitational curvatures, i.e., components of the third-order gravitational tensor, by merging these solutions using the spectral combination method. For this purpose, integral estimators of biased- and unbiased-types are derived. In numerical studies, we investigate the performance of the developed mathematical models for the gravitational field modelling in the area of Central Europe based on simulated satellite measurements. Firstly, we verify the correctness of the integral estimators for the spectral downward continuation by a closed-loop test. Estimated errors of the combined solution are about eight orders smaller than those from the individual solutions. Secondly, we perform a numerical experiment by considering the Gaussian noise with the standard deviation of 6.5× 10-17 m-1s-2 in the input data at the satellite altitude of 250 km above the mean Earth sphere. This value of standard deviation is equivalent to a signal-to-noise ratio of 10. Superior results with respect to the global geopotential model TIM-r5 are obtained by the spectral downward continuation of the vertical-vertical-vertical component with the standard deviation of 2.104 m2s-2, but the root mean square error is the largest and reaches 9.734 m2s-2. Using the spectral combination of all gravitational curvatures the root mean square error is more than 400 times smaller but the standard deviation reaches 17.234 m2s-2. The combination of more components decreases the root mean square error of the corresponding solutions while the standard deviations of the combined solutions do not improve as compared to the solution from the vertical-vertical-vertical component. The presented method represents a weight mean in the spectral domain that minimizes the root mean square error of the combined solutions and improves standard deviation of the solution based only on the least accurate components.

  4. Host model uncertainties in aerosol radiative forcing estimates: results from the AeroCom Prescribed intercomparison study

    NASA Astrophysics Data System (ADS)

    Stier, P.; Schutgens, N. A. J.; Bellouin, N.; Bian, H.; Boucher, O.; Chin, M.; Ghan, S.; Huneeus, N.; Kinne, S.; Lin, G.; Ma, X.; Myhre, G.; Penner, J. E.; Randles, C. A.; Samset, B.; Schulz, M.; Takemura, T.; Yu, F.; Yu, H.; Zhou, C.

    2013-03-01

    Simulated multi-model "diversity" in aerosol direct radiative forcing estimates is often perceived as a measure of aerosol uncertainty. However, current models used for aerosol radiative forcing calculations vary considerably in model components relevant for forcing calculations and the associated "host-model uncertainties" are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in twelve participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is -4.47 Wm-2 and the inter-model standard deviation is 0.55 Wm-2, corresponding to a relative standard deviation of 12%. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.04 Wm-2, and the standard deviation increases to 1.01 W-2, corresponding to a significant relative standard deviation of 97%. However, the top-of-atmosphere forcing variability owing to absorption (subtracting the scattering case from the case with scattering and absorption) is low, with absolute (relative) standard deviations of 0.45 Wm-2 (8%) clear-sky and 0.62 Wm-2 (11%) all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the AeroCom Direct Effect experiment demonstrates that host model uncertainties could explain about 36% of the overall sulfate forcing diversity of 0.11 Wm-2 in the AeroCom Direct Radiative Effect experiment. Host model errors in aerosol radiative forcing are largest in regions of uncertain host model components, such as stratocumulus cloud decks or areas with poorly constrained surface albedos, such as sea ice. Our results demonstrate that host model uncertainties are an important component of aerosol forcing uncertainty that require further attention.

  5. Comparison of four methods of establishing control limits for monitoring quality controls in infectious disease serology testing.

    PubMed

    Dimech, Wayne; Karakaltsas, Marina; Vincini, Giuseppe A

    2018-05-25

    A general trend towards conducting infectious disease serology testing in centralized laboratories means that quality control (QC) principles used for clinical chemistry testing are applied to infectious disease testing. However, no systematic assessment of methods used to establish QC limits has been applied to infectious disease serology testing. A total of 103 QC data sets, obtained from six different infectious disease serology analytes, were parsed through standard methods for establishing statistical control limits, including guidelines from Public Health England, USA Clinical and Laboratory Standards Institute (CLSI), German Richtlinien der Bundesärztekammer (RiliBÄK) and Australian QConnect. The percentage of QC results failing each method was compared. The percentage of data sets having more than 20% of QC results failing Westgard rules when the first 20 results were used to calculate the mean±2 standard deviation (SD) ranged from 3 (2.9%) for R4S to 66 (64.1%) for 10X rule, whereas the percentage ranged from 0 (0%) for R4S to 32 (40.5%) for 10X when the first 100 results were used to calculate the mean±2 SD. By contrast, the percentage of data sets with >20% failing the RiliBÄK control limits was 25 (24.3%). Only two data sets (1.9%) had more than 20% of results outside the QConnect Limits. The rate of failure of QCs using QConnect Limits was more applicable for monitoring infectious disease serology testing compared with UK Public Health, CLSI and RiliBÄK, as the alternatives to QConnect Limits reported an unacceptably high percentage of failures across the 103 data sets.

  6. Monitoring surgical and medical outcomes: the Bernoulli cumulative SUM chart. A novel application to assess clinical interventions

    PubMed Central

    Leandro, G; Rolando, N; Gallus, G; Rolles, K; Burroughs, A

    2005-01-01

    Background: Monitoring clinical interventions is an increasing requirement in current clinical practice. The standard CUSUM (cumulative sum) charts are used for this purpose. However, they are difficult to use in terms of identifying the point at which outcomes begin to be outside recommended limits. Objective: To assess the Bernoulli CUSUM chart that permits not only a 100% inspection rate, but also the setting of average expected outcomes, maximum deviations from these, and false positive rates for the alarm signal to trigger. Methods: As a working example this study used 674 consecutive first liver transplant recipients. The expected one year mortality set at 24% from the European Liver Transplant Registry average. A standard CUSUM was compared with Bernoulli CUSUM: the control value mortality was therefore 24%, maximum accepted mortality 30%, and average number of observations to signal was 500—that is, likelihood of false positive alarm was 1:500. Results: The standard CUSUM showed an initial descending curve (nadir at patient 215) then progressively ascended indicating better performance. The Bernoulli CUSUM gave three alarm signals initially, with easily recognised breaks in the curve. There were no alarms signals after patient 143 indicating satisfactory performance within the criteria set. Conclusions: The Bernoulli CUSUM is more easily interpretable graphically and is more suitable for monitoring outcomes than the standard CUSUM chart. It only requires three parameters to be set to monitor any clinical intervention: the average expected outcome, the maximum deviation from this, and the rate of false positive alarm triggers. PMID:16210461

  7. Scan-To Output Validation: Towards a Standardized Geometric Quality Assessment of Building Information Models Based on Point Clouds

    NASA Astrophysics Data System (ADS)

    Bonduel, M.; Bassier, M.; Vergauwen, M.; Pauwels, P.; Klein, R.

    2017-11-01

    The use of Building Information Modeling (BIM) for existing buildings based on point clouds is increasing. Standardized geometric quality assessment of the BIMs is needed to make them more reliable and thus reusable for future users. First, available literature on the subject is studied. Next, an initial proposal for a standardized geometric quality assessment is presented. Finally, this method is tested and evaluated with a case study. The number of specifications on BIM relating to existing buildings is limited. The Levels of Accuracy (LOA) specification of the USIBD provides definitions and suggestions regarding geometric model accuracy, but lacks a standardized assessment method. A deviation analysis is found to be dependent on (1) the used mathematical model, (2) the density of the point clouds and (3) the order of comparison. Results of the analysis can be graphical and numerical. An analysis on macro (building) and micro (BIM object) scale is necessary. On macro scale, the complete model is compared to the original point cloud and vice versa to get an overview of the general model quality. The graphical results show occluded zones and non-modeled objects respectively. Colored point clouds are derived from this analysis and integrated in the BIM. On micro scale, the relevant surface parts are extracted per BIM object and compared to the complete point cloud. Occluded zones are extracted based on a maximum deviation. What remains is classified according to the LOA specification. The numerical results are integrated in the BIM with the use of object parameters.

  8. Search for high-mass new phenomena in the dilepton final state using proton–proton collisions at s = 13 TeV with the ATLAS detector

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aaboud, M.; Aad, G.; Abbott, B.

    A search is conducted for both resonant and non-resonant high-mass new phenomena in dielectron and dimuon final states. The search uses 3.2 fb-1of proton–proton collision data, collected at √s = 13 TeV by the ATLAS experiment at the LHC in 2015. The dilepton invariant mass is used as the discriminating variable. No significant deviation from the Standard Model prediction is observed; therefore limits are set on the signal model parameters of interest at 95% credibility level. Upper limits are set on the cross-section times branching ratio for resonances decaying to dileptons, and the limits are converted into lower limits onmore » the resonance mass, ranging between 2.74 TeV and 3.36 TeV, depending on the model. Lower limits on the ℓℓqq contact interaction scale are set between 16.7 TeV and 25.2 TeV, also depending on the model.« less

  9. Search for high-mass new phenomena in the dilepton final state using proton-proton collisions at √{ s} = 13TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bevan, A. J.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao de Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blanco, J. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cúth, J.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, M.; Davison, P.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vivie de Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Duffield, E. M.; Duflot, L.; Duguid, L.; Dührssen, M.; Dumancic, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, G. T.; Fletcher, R. R. M.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gao, J.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gecse, Z.; Gee, C. N. P.; Geich-Gimbel, Ch.; Geisen, M.; Geisler, M. P.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; George, S.; Gerbaudo, D.; Gershon, A.; Ghasemi, S.; Ghazlane, H.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibbard, B.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Pinto Firmino da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de La Hoz, S.; Gonzalez Parra, G.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Grafström, P.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, H. M.; Graziani, E.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Grohs, J. P.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, Y.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Haefner, P.; Hageböck, S.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanisch, S.; Hanke, P.; Hanna, R.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartjes, F.; Hartmann, N. M.; Hasegawa, M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Hellman, S.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Hernández Jiménez, Y.; Herr, H.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Hickling, R.; Higón-Rodriguez, E.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hinman, R. R.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, C.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, Q.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Ince, T.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. 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C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sasaki, Y.; Sato, K.; Sauvage, G.; Sauvan, E.; Savage, G.; Savard, P.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schwegler, Ph.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Vallecorsa, S.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

    2016-10-01

    A search is conducted for both resonant and non-resonant high-mass new phenomena in dielectron and dimuon final states. The search uses 3.2fb-1 of proton-proton collision data, collected at √{ s} = 13TeV by the ATLAS experiment at the LHC in 2015. The dilepton invariant mass is used as the discriminating variable. No significant deviation from the Standard Model prediction is observed; therefore limits are set on the signal model parameters of interest at 95% credibility level. Upper limits are set on the cross-section times branching ratio for resonances decaying to dileptons, and the limits are converted into lower limits on the resonance mass, ranging between 2.74 TeV and 3.36 TeV, depending on the model. Lower limits on the ℓℓqq contact interaction scale are set between 16.7 TeV and 25.2 TeV, also depending on the model.

  10. Trace analysis of high-purity graphite by LA-ICP-MS.

    PubMed

    Pickhardt, C; Becker, J S

    2001-07-01

    Laser-ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been established as a very efficient and sensitive technique for the direct analysis of solids. In this work the capability of LA-ICP-MS was investigated for determination of trace elements in high-purity graphite. Synthetic laboratory standards with a graphite matrix were prepared for the purpose of quantifying the analytical results. Doped trace elements, concentration 0.5 microg g(-1), in a laboratory standard were determined with an accuracy of 1% to +/- 7% and a relative standard deviation (RSD) of 2-13%. Solution-based calibration was also used for quantitative analysis of high-purity graphite. It was found that such calibration led to analytical results for trace-element determination in graphite with accuracy similar to that obtained by use of synthetic laboratory standards for quantification of analytical results. Results from quantitative determination of trace impurities in a real reactor-graphite sample, using both quantification approaches, were in good agreement. Detection limits for all elements of interest were determined in the low ng g(-1) concentration range. Improvement of detection limits by a factor of 10 was achieved for analyses of high-purity graphite with LA-ICP-MS under wet plasma conditions, because the lower background signal and increased element sensitivity.

  11. Simultaneous determination of chlorantraniliprole and cyantraniliprole in fruits, vegetables and cereals using ultra-high-performance liquid chromatography-tandem mass spectrometry with the isotope-labelled internal standard method.

    PubMed

    Pan, Xinglu; Dong, Fengshou; Xu, Jun; Liu, Xingang; Chen, Zenglong; Liu, Na; Chen, Xixi; Tao, Yan; Zhang, Hongjun; Zheng, Yongquan

    2015-05-01

    A reliable and sensitive isotope-labelled internal standard method for simultaneous determination of chlorantraniliprole and cyantraniliprole in fruits (apple and grape), vegetables (cucumber and tomato) and cereals (rice and wheat) using ultra-high-performance liquid chromatography-tandem mass spectrometry was developed. Isotope-labelled internal standards were effective in compensating for the loss in the pretreatment and overcoming the matrix effect. The analytes were extracted with acetonitrile and cleaned up with different kinds of sorbents. The determination of the target compounds was achieved in less than 4 min using a T3 column combined with an electrospray ionization source in positive mode. The overall average relative recoveries in all matrices at three spiking levels (10, 20 and 50 μg kg(-1)) ranged from 95.5 to 106.2 %, with all relative standard deviations being less than 14.4 % for all analytes. The limits of detection did not exceed 0.085 μg kg(-1) and the limits of quantification were below 0.28 μg kg(-1) in all matrices. The method was demonstrated to be convenient and accurate for the routine monitoring of chlorantraniliprole and cyantraniliprole in fruits, vegetables and cereals.

  12. Medication management of febrile children: a qualitative study on pharmacy employees' experiences.

    PubMed

    Stakenborg, Jacqueline P G; de Bont, Eefje G P M; Peetoom, Kirsten K B; Nelissen-Vrancken, Marjorie H J M G; Cals, Jochen W L

    2016-10-01

    Background While fever is mostly self-limiting, antibiotic prescription rates for febrile children are high. Although every parent who receives a prescription visits a pharmacy, we have limited insight into pharmacy employees' experiences with these parents. Pharmacy employees do however exert an important role in ensuring children receive correct dosages and in advising parents on administration of antibiotics. Objective To describe pharmacists' and pharmacy assistants' experiences with parents contacting a pharmacy for their febrile child, and to identify ways of improving medication management of these children. Setting Community pharmacies in the Netherlands. Method A qualitative study including 24 Dutch pharmacy employees was conducted, performing four focus group discussions among pharmacy employees. Analysis was based on constant comparative technique using open and axial coding. Main outcome measure Pharmacy employees' experiences with parents contacting a pharmacy for their febrile child. Results Three categories were identified: (1) workload and general experience, (2) inconsistent information on antibiotic prescriptions, (3) improving communication and collaboration. Pharmacy employees experienced that dosing errors in antibiotic prescriptions occur frequently and doctors provide inconsistent information on prescriptions. Consequently, they have to contact doctors, resulting in a higher workload for both stakeholders. They believe this can be improved by providing the indication for antibiotics on prescriptions, especially when deviating from standard dosages. Conclusion Pharmacy employees experience a high amount of dosing errors in paediatric antibiotic prescriptions. Providing the indication for antibiotics in febrile children on prescriptions, especially when deviating from standard dosages, can potentially reduce dosage errors and miscommunication between doctors and pharmacy employees.

  13. Adherence to a Videogame-Based Physical Activity Program for Older Adults with Schizophrenia

    PubMed Central

    Hubbard, Erin M.; Dowling, Glenna A.

    2014-01-01

    Abstract Objectives: Adults with schizophrenia are a growing segment of the older adult population. Evidence suggests that they engage in limited physical activity. Interventions are needed that are tailored around their unique limitations. An active videogame-based physical activity program that can be offered at a treatment facility can overcome these barriers and increase motivation to engage in physical activity. The purpose of this report is to describe the adherence to a videogame-based physical activity program using the Kinect® for Xbox® 360 game system (Microsoft®, Redmond, WA) in older adults with schizophrenia. Materials and Methods: This was a descriptive longitudinal study among 34 older adults with schizophrenia to establish the adherence to an active videogame-based physical activity program. In our ongoing program, once a week for 6 weeks, participants played an active videogame, using the Kinect for Xbox 360 game system, for 30 minutes. Adherence was measured with a count of sessions attended and with the total minutes attended out of the possible total minutes of attendance (180 minutes). Results: Thirty-four adults with schizophrenia enrolled in the study. The mean number of groups attended was five out of six total (standard deviation=2), and the mean total minutes attended were 139 out of 180 possible (standard deviation=55). Fifty percent had perfect attendance. Conclusions: Older adults with schizophrenia need effective physical activity programs. Adherence to our program suggests that videogames that use the Kinect for Xbox 360 game system are an innovative way to make physical activity accessible to this population. PMID:26192371

  14. Polymeric ionic liquid based on magnetic materials fabricated through layer-by-layer assembly as adsorbents for extraction of pesticides.

    PubMed

    He, Lijun; Cui, Wenhang; Wang, Yali; Zhao, Wenjie; Xiang, Guoqiang; Jiang, Xiuming; Mao, Pu; He, Juan; Zhang, Shusheng

    2017-11-03

    In this study, layer-by-layer assembly of polyelectrolyte multilayer films on magnetic silica provided a convenient and controllable way to prepare polymeric ionic liquid-based magnetic adsorbents. The resulting particles were characterized by Fourier transform infrared spectroscopy, X-ray diffraction, transmission electron microscopy, and magnetic measurements. The data showed that the magnetic particles had more homogeneous spherical shapes with higher saturation magnetization when compared to those obtained by free radical polymerization method. This facilitated the convenient collection of magnetic particles, with higher extraction repeatability. The extraction performance of the multilayer polymeric ionic liquid-based adsorbents was evaluated by magnetic solid-phase extraction of four pesticides including quinalphos, fenthion, phoxim, and chlorpropham. The data suggested that the extraction efficiency depended on the number of layers in the film. The parameters affecting the extraction efficiency were optimized, and good linearity ranging from 2 to 250μgL -1 was obtained with correlation coefficients of 0.9994-0.9998. Moreover, the proposed method presented low limit of detection (0.5μgL -1 , S/N=3) and limit of quantification (1.5μgL -1 , S/N=10), and good repeatability expressed by the relative standard deviation (2.0%-4.6%, n=5). The extraction recoveries of four pesticides were found to range from 58.9% to 85.8%. The reliability of the proposed method was demonstrated by analyzing environmental water samples, and the results revealed satisfactory spiked recovery, relative standard deviation, and selectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. [Standard addition determination of impurities in Na2CrO4 by ICP-AES].

    PubMed

    Wang, Li-ping; Feng, Hai-tao; Dong, Ya-ping; Peng, Jiao-yu; Li, Wu; Shi, Hai-qin; Wang, Yong

    2015-02-01

    Coupled plasma atomic emission spectrometry (ICP-AES) was used to determine the trace impurities of Ca, Mg, Al, Fe and Si in industrial sodium chromate. Wavelengths of 167.079, 393.366, 259.940, 279.533 and 251.611 nm were selected as analytical lines for the determination of Al, Ca, Fe, Mg and Si, respectively. The analytical errors can be eliminated by adjusting the determined solution with high pure hydrochloric acid. Standard addition method was used to eliminate matrix effects. The linear correlation, detection limit, precision and recovery for the concerned trace impurities have been examined. The effect of standard addition method on the accuracy for the determination under the selected analytical lines has been studied in detail. The results show that the linear correlations of standard curves were very good (R2 = 0.9988 to 0.9996) under the determined conditions. Detection limits of these trace impurities were in the range of 0.0134 to 0.0280 mg x L(-1). Sample recoveries were within 97.30% to 107.50%, and relative standard deviations were lower than 5.86% for eleven repeated determinations. The detection limits and accuracies established by the experiment can meet the analytical requirements and the analytic procedure was used to determine trace impurities in sodium chromate by ion membrane electrolysis technique successfully. Due to sodium chromate can be changed into sodium dichromate and chromic acid by adding acids, the established method can be further used to monitor trace impurities in these compounds or other hexavalent chromium compounds.

  16. Local oscillator induced degradation of medium-term stability in passive atomic frequency standards

    NASA Technical Reports Server (NTRS)

    Dick, G. John; Prestage, John D.; Greenhall, Charles A.; Maleki, Lute

    1990-01-01

    As the performance of passive atomic frequency standards improves, a new limitation is encountered due to frequency fluctuations in an ancillary local oscillator (L.O.). The effect is due to time variation in the gain of the feedback which compensates L.O. frequency fluctuations. The high performance promised by new microwave and optical trapped ion standards may be severely compromised by this effect. Researchers present an analysis of this performance limitation for the case of sequentially interrogated standards. The time dependence of the sensitivity of the interrogation process to L.O. frequency fluctuations is evaluated for single-pulse and double-pulse Ramsey RF interrogation and for amplitude modulated pulses. The effect of these various time dependencies on performance of the standard is calculated for an L.O. with frequency fluctuations showing a typical 1/f spectral density. A limiting 1/sq. root gamma dependent deviation of frequency fluctuations is calculated as a function of pulse lengths, dead time, and pulse overlap. Researchers also present conceptual and hardware-oriented solutions to this problem which achieve a much more nearly constant sensitivity to L.O. fluctuations. Solutions involve use of double-pulse interrogation; alternate interrogation of multiple traps so that the dead time of one trap can be covered by operation of the other; and the use of double-pulse interrogation for two traps, so that during the time of the RF pulses, the increasing sensitivity of one trap tends to compensate for the decreasing sensitivity of the other. A solution making use of amplified-modulated pulses is also presented which shows nominally zero time variation.

  17. Size-dependent standard deviation for growth rates: Empirical results and theoretical modeling

    NASA Astrophysics Data System (ADS)

    Podobnik, Boris; Horvatic, Davor; Pammolli, Fabio; Wang, Fengzhong; Stanley, H. Eugene; Grosse, I.

    2008-05-01

    We study annual logarithmic growth rates R of various economic variables such as exports, imports, and foreign debt. For each of these variables we find that the distributions of R can be approximated by double exponential (Laplace) distributions in the central parts and power-law distributions in the tails. For each of these variables we further find a power-law dependence of the standard deviation σ(R) on the average size of the economic variable with a scaling exponent surprisingly close to that found for the gross domestic product (GDP) [Phys. Rev. Lett. 81, 3275 (1998)]. By analyzing annual logarithmic growth rates R of wages of 161 different occupations, we find a power-law dependence of the standard deviation σ(R) on the average value of the wages with a scaling exponent β≈0.14 close to those found for the growth of exports, imports, debt, and the growth of the GDP. In contrast to these findings, we observe for payroll data collected from 50 states of the USA that the standard deviation σ(R) of the annual logarithmic growth rate R increases monotonically with the average value of payroll. However, also in this case we observe a power-law dependence of σ(R) on the average payroll with a scaling exponent β≈-0.08 . Based on these observations we propose a stochastic process for multiple cross-correlated variables where for each variable (i) the distribution of logarithmic growth rates decays exponentially in the central part, (ii) the distribution of the logarithmic growth rate decays algebraically in the far tails, and (iii) the standard deviation of the logarithmic growth rate depends algebraically on the average size of the stochastic variable.

  18. Effect of extreme sea surface temperature events on the demography of an age-structured albatross population.

    PubMed

    Pardo, Deborah; Jenouvrier, Stéphanie; Weimerskirch, Henri; Barbraud, Christophe

    2017-06-19

    Climate changes include concurrent changes in environmental mean, variance and extremes, and it is challenging to understand their respective impact on wild populations, especially when contrasted age-dependent responses to climate occur. We assessed how changes in mean and standard deviation of sea surface temperature (SST), frequency and magnitude of warm SST extreme climatic events (ECE) influenced the stochastic population growth rate log( λ s ) and age structure of a black-browed albatross population. For changes in SST around historical levels observed since 1982, changes in standard deviation had a larger (threefold) and negative impact on log( λ s ) compared to changes in mean. By contrast, the mean had a positive impact on log( λ s ). The historical SST mean was lower than the optimal SST value for which log( λ s ) was maximized. Thus, a larger environmental mean increased the occurrence of SST close to this optimum that buffered the negative effect of ECE. This 'climate safety margin' (i.e. difference between optimal and historical climatic conditions) and the specific shape of the population growth rate response to climate for a species determine how ECE affect the population. For a wider range in SST, both the mean and standard deviation had negative impact on log( λ s ), with changes in the mean having a greater effect than the standard deviation. Furthermore, around SST historical levels increases in either mean or standard deviation of the SST distribution led to a younger population, with potentially important conservation implications for black-browed albatrosses.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

  19. Is standard deviation of daily PM2.5 concentration associated with respiratory mortality?

    PubMed

    Lin, Hualiang; Ma, Wenjun; Qiu, Hong; Vaughn, Michael G; Nelson, Erik J; Qian, Zhengmin; Tian, Linwei

    2016-09-01

    Studies on health effects of air pollution often use daily mean concentration to estimate exposure while ignoring daily variations. This study examined the health effects of daily variation of PM2.5. We calculated daily mean and standard deviations of PM2.5 in Hong Kong between 1998 and 2011. We used a generalized additive model to estimate the association between respiratory mortality and daily mean and variation of PM2.5, as well as their interaction. We controlled for potential confounders, including temporal trends, day of the week, meteorological factors, and gaseous air pollutants. Both daily mean and standard deviation of PM2.5 were significantly associated with mortalities from overall respiratory diseases and pneumonia. Each 10 μg/m(3) increment in daily mean concentration at lag 2 day was associated with a 0.61% (95% CI: 0.19%, 1.03%) increase in overall respiratory mortality and a 0.67% (95% CI: 0.14%, 1.21%) increase in pneumonia mortality. And a 10 μg/m(3) increase in standard deviation at lag 1 day corresponded to a 1.40% (95% CI: 0.35%, 2.46%) increase in overall respiratory mortality, and a 1.80% (95% CI: 0.46%, 3.16%) increase in pneumonia mortality. We also observed a positive but non-significant synergistic interaction between daily mean and variation on respiratory mortality and pneumonia mortality. However, we did not find any significant association with mortality from chronic obstructive pulmonary diseases. Our study suggests that, besides mean concentration, the standard deviation of PM2.5 might be one potential predictor of respiratory mortality in Hong Kong, and should be considered when assessing the respiratory effects of PM2.5. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Assessment issues in the testing of children at school entry.

    PubMed

    Rock, Donald A; Stenner, A Jackson

    2005-01-01

    The authors introduce readers to the research documenting racial and ethnic gaps in school readiness. They describe the key tests, including the Peabody Picture Vocabulary Test (PPVT), the Early Childhood Longitudinal Study (ECLS), and several intelligence tests, and describe how they have been administered to several important national samples of children. Next, the authors review the different estimates of the gaps and discuss how to interpret these differences. In interpreting test results, researchers use the statistical term "standard deviation" to compare scores across the tests. On average, the tests find a gap of about 1 standard deviation. The ECLS-K estimate is the lowest, about half a standard deviation. The PPVT estimate is the highest, sometimes more than 1 standard deviation. When researchers adjust those gaps statistically to take into account different outside factors that might affect children's test scores, such as family income or home environment, the gap narrows but does not disappear. Why such different estimates of the gap? The authors consider explanations such as differences in the samples, racial or ethnic bias in the tests, and whether the tests reflect different aspects of school "readiness," and conclude that none is likely to explain the varying estimates. Another possible explanation is the Spearman Hypothesis-that all tests are imperfect measures of a general ability construct, g; the more highly a given test correlates with g, the larger the gap will be. But the Spearman Hypothesis, too, leaves questions to be investigated. A gap of 1 standard deviation may not seem large, but the authors show clearly how it results in striking disparities in the performance of black and white students and why it should be of serious concern to policymakers.

  1. Single-Station Sigma for the Iranian Strong Motion Stations

    NASA Astrophysics Data System (ADS)

    Zafarani, H.; Soghrat, M. R.

    2017-11-01

    In development of ground motion prediction equations (GMPEs), the residuals are assumed to have a log-normal distribution with a zero mean and a standard deviation, designated as sigma. Sigma has significant effect on evaluation of seismic hazard for designing important infrastructures such as nuclear power plants and dams. Both aleatory and epistemic uncertainties are involved in the sigma parameter. However, ground-motion observations over long time periods are not available at specific sites and the GMPEs have been derived using observed data from multiple sites for a small number of well-recorded earthquakes. Therefore, sigma is dominantly related to the statistics of the spatial variability of ground motion instead of temporal variability at a single point (ergodic assumption). The main purpose of this study is to reduce the variability of the residuals so as to handle it as epistemic uncertainty. In this regard, it is tried to partially apply the non-ergodic assumption by removing repeatable site effects from total variability of six GMPEs driven from the local, Europe-Middle East and worldwide data. For this purpose, we used 1837 acceleration time histories from 374 shallow earthquakes with moment magnitudes ranging from M w 4.0 to 7.3 recorded at 370 stations with at least two recordings per station. According to estimated single-station sigma for the Iranian strong motion stations, the ratio of event-corrected single-station standard deviation ( Φ ss) to within-event standard deviation ( Φ) is about 0.75. In other words, removing the ergodic assumption on site response resulted in 25% reduction of the within-event standard deviation that reduced the total standard deviation by about 15%.

  2. Size-dependent standard deviation for growth rates: empirical results and theoretical modeling.

    PubMed

    Podobnik, Boris; Horvatic, Davor; Pammolli, Fabio; Wang, Fengzhong; Stanley, H Eugene; Grosse, I

    2008-05-01

    We study annual logarithmic growth rates R of various economic variables such as exports, imports, and foreign debt. For each of these variables we find that the distributions of R can be approximated by double exponential (Laplace) distributions in the central parts and power-law distributions in the tails. For each of these variables we further find a power-law dependence of the standard deviation sigma(R) on the average size of the economic variable with a scaling exponent surprisingly close to that found for the gross domestic product (GDP) [Phys. Rev. Lett. 81, 3275 (1998)]. By analyzing annual logarithmic growth rates R of wages of 161 different occupations, we find a power-law dependence of the standard deviation sigma(R) on the average value of the wages with a scaling exponent beta approximately 0.14 close to those found for the growth of exports, imports, debt, and the growth of the GDP. In contrast to these findings, we observe for payroll data collected from 50 states of the USA that the standard deviation sigma(R) of the annual logarithmic growth rate R increases monotonically with the average value of payroll. However, also in this case we observe a power-law dependence of sigma(R) on the average payroll with a scaling exponent beta approximately -0.08 . Based on these observations we propose a stochastic process for multiple cross-correlated variables where for each variable (i) the distribution of logarithmic growth rates decays exponentially in the central part, (ii) the distribution of the logarithmic growth rate decays algebraically in the far tails, and (iii) the standard deviation of the logarithmic growth rate depends algebraically on the average size of the stochastic variable.

  3. Validation of 10 years of SAO OMI Ozone Profiles with Ozonesonde and MLS Observations

    NASA Astrophysics Data System (ADS)

    Huang, G.; Liu, X.; Chance, K.; Bhartia, P. K.

    2015-12-01

    To evaluate the accuracy and long-term stability of the SAO OMI ozone profile product, we validate ~10 years of ozone profile product (Oct. 2004-Dec. 2014) against collocated ozonesonde and MLS data. Ozone profiles as well stratospheric, tropospheric, lower tropospheric ozone columns are compared with ozonesonde data for different latitude bands, and time periods (e.g., 2004-2008/2009-2014 for without/with row anomaly. The mean biases and their standard deviations are also assessed as a function of time to evaluate the long-term stability and bias trends. In the mid-latitude and tropical regions, OMI generally shows good agreement with ozonesonde observations. The mean ozone profile biases are generally within 6% with up to 30% standard deviations. The biases of stratospheric ozone columns (SOC) and tropospheric ozone columns (TOC) are -0.3%-2.2% and -0.2%-3%, while standard deviations are 3.9%-5.8% and 14.4%-16.0%, respectively. However, the retrievals during 2009-2014 show larger standard deviations and larger temporal variations; the standard deviations increase by ~5% in the troposphere and ~2% in the stratosphere. Retrieval biases at individual levels in the stratosphere and upper troposphere show statistically significant trends and different trends for 2004-2008 and 2009-2014 periods. The trends in integrated ozone partial columns are less significant due to cancellation from various layers, except for significant trend in tropical SOC. These results suggest the need to perform time dependent radiometric calibration to maintain the long-term stability of this product. Similarly, we are comparing the OMI stratospheric ozone profiles and SOC with collocated MLS data, and the results will be reported.

  4. [The heterogeneity of blood flow on magnetic resonance imaging: a biomarker for grading cerebral astrocytomas].

    PubMed

    Revert Ventura, A J; Sanz Requena, R; Martí-Bonmatí, L; Pallardó, Y; Jornet, J; Gaspar, C

    2014-01-01

    To study whether the histograms of quantitative parameters of perfusion in MRI obtained from tumor volume and peritumor volume make it possible to grade astrocytomas in vivo. We included 61 patients with histological diagnoses of grade II, III, or IV astrocytomas who underwent T2*-weighted perfusion MRI after intravenous contrast agent injection. We manually selected the tumor volume and peritumor volume and quantified the following perfusion parameters on a voxel-by-voxel basis: blood volume (BV), blood flow (BF), mean transit time (TTM), transfer constant (K(trans)), washout coefficient, interstitial volume, and vascular volume. For each volume, we obtained the corresponding histogram with its mean, standard deviation, and kurtosis (using the standard deviation and kurtosis as measures of heterogeneity) and we compared the differences in each parameter between different grades of tumor. We also calculated the mean and standard deviation of the highest 10% of values. Finally, we performed a multiparametric discriminant analysis to improve the classification. For tumor volume, we found statistically significant differences among the three grades of tumor for the means and standard deviations of BV, BF, and K(trans), both for the entire distribution and for the highest 10% of values. For the peritumor volume, we found no significant differences for any parameters. The discriminant analysis improved the classification slightly. The quantification of the volume parameters of the entire region of the tumor with BV, BF, and K(trans) is useful for grading astrocytomas. The heterogeneity represented by the standard deviation of BF is the most reliable diagnostic parameter for distinguishing between low grade and high grade lesions. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

  5. Relationship of Hotspots to the Distribution of Surficial Surf-Zone Sediments along the Outer Banks of North Carolina

    NASA Astrophysics Data System (ADS)

    Schupp, C. A.; McNinch, J. E.; List, J. H.; Farris, A. S.

    2002-12-01

    The formation and behavior of hotspots, or sections of the beach that exhibit markedly higher shoreline change rates than adjacent regions, are poorly understood. Several hotspots have been identified on the Outer Banks, a developed barrier island in North Carolina. To better understand hotspot dynamics and the potential relationship to the geologic framework in which they occur, the surf zone between Duck and Bodie Island was surveyed in June 2002 as part of a research effort supported by the U.S. Geological Survey and U.S. Army Corps of Engineers. Swath bathymetry, sidescan sonar, and chirp seismic were used to characterize a region 40 km long and1 km wide. Hotspot locations were pinpointed using standard deviation values for shoreline position as determined by monthly SWASH buggy surveys of the mean high water contour between October 1999 and September 2002. Observational data and sidescan images were mapped to delineate regions of surficial sediment distributions, and regions of interest were ground-truthed via grab samples or visual inspection. General kilometer-scale correlation between acoustic backscatter and high shoreline standard deviation is evident. Acoustic returns are uniform in a region of Duck where standard deviation is low, but backscatter is patchy around the Kitty Hawk hotspot, where standard deviation is higher. Based on ground-truthing of an area further north, these patches are believed to be an older ravinement surface of fine sediment. More detailed analyses of the correlation between acoustic data, standard deviation, and hotspot locations will be presented. Future work will include integration of seismic, bathymetric, and sidescan data to better understand the links between sub-bottom geology, temporal changes in surficial sediments, surf-zone sediment budgets, and short-term changes in shoreline position and morphology.

  6. Influence of eye micromotions on spatially resolved refractometry

    NASA Astrophysics Data System (ADS)

    Chyzh, Igor H.; Sokurenko, Vyacheslav M.; Osipova, Irina Y.

    2001-01-01

    The influence eye micromotions on the accuracy of estimation of Zernike coefficients form eye transverse aberration measurements was investigated. By computer modeling, the following found eye aberrations have been examined: defocusing, primary astigmatism, spherical aberration of the 3rd and the 5th orders, as well as their combinations. It was determined that the standard deviation of estimated Zernike coefficients is proportional to the standard deviation of angular eye movements. Eye micromotions cause the estimation errors of Zernike coefficients of present aberrations and produce the appearance of Zernike coefficients of aberrations, absent in the eye. When solely defocusing is present, the biggest errors, cased by eye micromotions, are obtained for aberrations like coma and astigmatism. In comparison with other aberrations, spherical aberration of the 3rd and the 5th orders evokes the greatest increase of the standard deviation of other Zernike coefficients.

  7. Search for the Standard Model Higgs Boson Produced through Vector Boson Fusion and Decaying to $$\\mathrm{b\\bar{b}}$$

    DOE PAGES

    Khachatryan, Vardan

    2015-08-27

    A first search is reported for a standard model Higgs boson (H) that is produced through vector boson fusion and decays to a bottom-quark pair. Two data samples, corresponding to integrated luminosities of 19.8 fb -1 and 18.3 fb -1 of proton-proton collisions at √s=8 TeV were selected for this channel at the CERN LHC. The observed significance in these data samples for a H→more » $$\\mathrm{b\\bar{b}}$$ signal at a mass of 125 GeV is 2.2 standard deviations, while the expected significance is 0.8 standard deviations. The fitted signal strength μ=σ/σ SM=2.8 +1.6 -1.4. The combination of this result with other CMS searches for the Higgs boson decaying to a b-quark pair yields a signal strength of 1.0±0.4, corresponding to a signal significance of 2.6 standard deviations for a Higgs boson mass of 125 GeV.« less

  8. Observation of the rare Bs0 →µ+µ- decay from the combined analysis of CMS and LHCb data

    NASA Astrophysics Data System (ADS)

    Cms Collaboration; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, S.; Cornelis, T.; de Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Ochesanu, S.; Rougny, R.; van de Klundert, M.; van Haevermaet, H.; van Mechelen, P.; van Remortel, N.; van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; van Doninck, W.; van Mulders, P.; van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; de Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Randle-Conde, A.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; McCartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; da Silveira, G. G.; Delaere, C.; Du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Mora Herrera, C.; Pol, M. E.; Rebello Teles, P.; Carvalho, W.; Chinellato, J.; Custódio, A.; da Costa, E. M.; de Jesus Damiao, D.; de Oliveira Martins, C.; Fonseca de Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado da Silva, W. L.; Santaolalla, J.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Aleksandrov, A.; Genchev, V.; Hadjiiska, R.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Tao, J.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Zou, W.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M., Jr.; Assran, Y.; Ellithi Kamel, A.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Busson, P.; Charlot, C.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Mastrolorenzo, L.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Veelken, C.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Chabert, E. C.; Collard, C.; Conte, E.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Skovpen, K.; van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Boudoul, G.; Bouvier, E.; Brochet, S.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Bontenackels, M.; Edelhoff, M.; Feld, L.; Heister, A.; Hindrichs, O.; Klein, K.; Ostapchuk, A.; Raupach, F.; Sammet, J.; Schael, S.; Schulte, J. F.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Erdmann, M.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Weber, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asin, I.; Bartosik, N.; Behr, J.; Behrens, U.; Bell, A. J.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garay Garcia, J.; Geiser, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Junkes, A.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Poehlsen, T.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; de Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Gilbert, A.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Kuznetsova, E.; Lobelle Pardo, P.; Mozer, M. U.; Müller, T.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; Röcker, S.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Makovec, A.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Sahoo, N.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; Kumar, R.; Mittal, M.; Nishu, N.; Singh, J. B.; Ashok Kumar; Arun Kumar; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Modak, A.; Mukherjee, S.; Roy, D.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kailas, S.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Goldouzian, R.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; de Filippis, N.; de Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Albergo, S.; Cappello, G.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gallo, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Ferretti, R.; Ferro, F.; Lo Vetere, M.; Robutti, E.; Tosi, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Lucchini, M. T.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; di Guida, S.; Fabozzi, F.; Iorio, A. O. 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L.; Shapoval, I.; Tellarini, G.; Tomassetti, L.; Vecchi, S.; Anderlini, L.; Bizzeti, A.; Frosini, M.; Graziani, G.; Passaleva, G.; Veltri, M.; Bencivenni, G.; Campana, P.; de Simone, P.; Lanfranchi, G.; Palutan, M.; Rama, M.; Sarti, A.; Sciascia, B.; Vazquez Gomez, R.; Cardinale, R.; Fontanelli, F.; Gambetta, S.; Patrignani, C.; Petrolini, A.; Pistone, A.; Calvi, M.; Cassina, L.; Gotti, C.; Khanji, B.; Kucharczyk, M.; Matteuzzi, C.; Fu, J.; Geraci, A.; Neri, N.; Palombo, F.; Amerio, S.; Collazuol, G.; Gallorini, S.; Gianelle, A.; Lucchesi, D.; Lupato, A.; Morandin, M.; Rotondo, M.; Sestini, L.; Simi, G.; Stroili, R.; Bedeschi, F.; Cenci, R.; Leo, S.; Marino, P.; Morello, M. J.; Punzi, G.; Stracka, S.; Walsh, J.; Carboni, G.; Furfaro, E.; Santovetti, E.; Satta, A.; Alves, A. A., Jr.; Auriemma, G.; Bocci, V.; Martellotti, G.; Penso, G.; Pinci, D.; Santacesaria, R.; Satriano, C.; Sciubba, A.; Dziurda, A.; Kucewicz, W.; Lesiak, T.; Rachwal, B.; Witek, M.; Firlej, M.; Fiutowski, T.; Idzik, M.; Morawski, P.; Moron, J.; Oblakowska-Mucha, A.; Swientek, K.; Szumlak, T.; Batozskaya, V.; Klimaszewski, K.; Kurek, K.; Szczekowski, M.; Ukleja, A.; Wislicki, W.; Cojocariu, L.; Giubega, L.; Grecu, A.; Maciuc, F.; Orlandea, M.; Popovici, B.; Stoica, S.; Straticiuc, M.; Alkhazov, G.; Bondar, N.; Dzyuba, A.; Maev, O.; Sagidova, N.; Shcheglov, Y.; Vorobyev, A.; Belogurov, S.; Belyaev, I.; Egorychev, V.; Golubkov, D.; Kvaratskheliya, T.; Machikhiliyan, I. 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    2015-06-01

    The standard model of particle physics describes the fundamental particles and their interactions via the strong, electromagnetic and weak forces. It provides precise predictions for measurable quantities that can be tested experimentally. The probabilities, or branching fractions, of the strange B meson () and the B0 meson decaying into two oppositely charged muons (μ+ and μ-) are especially interesting because of their sensitivity to theories that extend the standard model. The standard model predicts that the and decays are very rare, with about four of the former occurring for every billion mesons produced, and one of the latter occurring for every ten billion B0 mesons. A difference in the observed branching fractions with respect to the predictions of the standard model would provide a direction in which the standard model should be extended. Before the Large Hadron Collider (LHC) at CERN started operating, no evidence for either decay mode had been found. Upper limits on the branching fractions were an order of magnitude above the standard model predictions. The CMS (Compact Muon Solenoid) and LHCb (Large Hadron Collider beauty) collaborations have performed a joint analysis of the data from proton-proton collisions that they collected in 2011 at a centre-of-mass energy of seven teraelectronvolts and in 2012 at eight teraelectronvolts. Here we report the first observation of the µ+µ- decay, with a statistical significance exceeding six standard deviations, and the best measurement so far of its branching fraction. Furthermore, we obtained evidence for the µ+µ- decay with a statistical significance of three standard deviations. Both measurements are statistically compatible with standard model predictions and allow stringent constraints to be placed on theories beyond the standard model. The LHC experiments will resume taking data in 2015, recording proton-proton collisions at a centre-of-mass energy of 13 teraelectronvolts, which will approximately double the production rates of and B0 mesons and lead to further improvements in the precision of these crucial tests of the standard model.

  9. Deviation Management: Key Management Subsystem Driver of Knowledge-Based Continuous Improvement in the Henry Ford Production System.

    PubMed

    Zarbo, Richard J; Copeland, Jacqueline R; Varney, Ruan C

    2017-10-01

    To develop a business subsystem fulfilling International Organization for Standardization 15189 nonconformance management regulatory standard, facilitating employee engagement in problem identification and resolution to effect quality improvement and risk mitigation. From 2012 to 2016, the integrated laboratories of the Henry Ford Health System used a quality technical team to develop and improve a management subsystem designed to identify, track, trend, and summarize nonconformances based on frequency, risk, and root cause for elimination at the level of the work. Programmatic improvements and training resulted in markedly increased documentation culminating in 71,641 deviations in 2016 classified by a taxonomy of 281 defect types into preanalytic (74.8%), analytic (23.6%), and postanalytic (1.6%) testing phases. The top 10 deviations accounted for 55,843 (78%) of the total. Deviation management is a key subsystem of managers' standard work whereby knowledge of nonconformities assists in directing corrective actions and continuous improvements that promote consistent execution and higher levels of performance. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  10. [Determination of acetochlor and oxyfluorfen by capillary gas chromatography].

    PubMed

    Xiang, Wen-Sheng; Wang, Xiang-Jing; Wang, Jing; Wang, Qing

    2002-09-01

    A method is described for the determination of acetochlor and oxyfluorfen by capillary gas chromatography with FID and an SE-30 capillary column (60 m x 0.53 mm i. d., 1.5 microm), using dibutyl phthalate as the internal standard. The standard deviations for acetochlor and oxyfluorfen concentration(mass fraction) were 0.44% and 0.47% respectively. The relative standard deviations for acetochlor and oxyfluorfen were 0.79% and 0.88% and the average recoveries for acetochlor and oxyfluorfen were 99.3% and 101.1% respectively. The method is simple, rapid and accurate.

  11. The normalization of deviance in healthcare delivery

    PubMed Central

    Banja, John

    2009-01-01

    Many serious medical errors result from violations of recognized standards of practice. Over time, even egregious violations of standards of practice may become “normalized” in healthcare delivery systems. This article describes what leads to this normalization and explains why flagrant practice deviations can persist for years, despite the importance of the standards at issue. This article also provides recommendations to aid healthcare organizations in identifying and managing unsafe practice deviations before they become normalized and pose genuine risks to patient safety, quality care, and employee morale. PMID:20161685

  12. Observation of the Higgs boson decay to a pair of τ leptons with the CMS detector

    NASA Astrophysics Data System (ADS)

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P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Moran, D.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Álvarez Fernández, A.; de Trocóniz, J. F.; Missiroli, M.; Cuevas, J.; Erice, C.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Vischia, P.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Chazin Quero, B.; Curras, E.; Duarte Campderros, J.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Martinez Ruiz del Arbol, P.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Baillon, P.; Ball, A. H.; Barney, D.; Bianco, M.; Bloch, P.; Bocci, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; Chapon, E.; Chen, Y.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Dobson, M.; Dorney, B.; du Pree, T.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Fallavollita, F.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gilbert, A.; Gill, K.; Glege, F.; Gulhan, D.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Karacheban, O.; Kieseler, J.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Krammer, M.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Milenovic, P.; Moortgat, F.; Mulders, M.; Neugebauer, H.; Ngadiuba, J.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Selvaggi, M.; Sharma, A.; Silva, P.; Sphicas, P.; Stakia, A.; Steggemann, J.; Stoye, M.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Verweij, M.; Zeuner, W. D.; Bertl, W.; Caminada, L.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Bäni, L.; Berger, P.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Klijnsma, T.; Lustermann, W.; Mangano, B.; Marionneau, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Reichmann, M.; Schönenberger, M.; Shchutska, L.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Canelli, M. F.; De Cosa, A.; Del Burgo, R.; Donato, S.; Galloni, C.; Hreus, T.; Kilminster, B.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Seitz, C.; Takahashi, Y.; Zucchetta, A.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Paganis, E.; Psallidas, A.; Steen, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Boran, F.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Sunar Cerci, D.; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Karapinar, G.; Ocalan, K.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Grynyov, B.; Levchuk, L.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Davignon, O.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Auzinger, G.; Bainbridge, R.; Borg, J.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Elwood, A.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Palladino, V.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wardle, N.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Smith, C.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Regnard, S.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Si, W.; Wang, L.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Macneill, I.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bendavid, J.; Bornheim, A.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Alyari, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Royon, C.; Sanders, S.; Schmitz, E.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Das, S.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Schulte, J. F.; Sun, J.; Wang, F.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

    2018-04-01

    A measurement of the H → ττ signal strength is performed using events recorded in proton-proton collisions by the CMS experiment at the LHC in 2016 at a center-of-mass energy of 13TeV. The data set corresponds to an integrated luminosity of 35.9fb-1. The H → ττ signal is established with a significance of 4.9 standard deviations, to be compared to an expected significance of 4.7 standard deviations. The best fit of the product of the observed H → ττ signal production cross section and branching fraction is 1.09-0.26+0.27 times the standard model expectation. The combination with the corresponding measurement performed with data collected by the CMS experiment at center-of-mass energies of 7 and 8TeV leads to an observed significance of 5.9 standard deviations, equal to the expected significance. This is the first observation of Higgs boson decays to τ leptons by a single experiment.

  13. Employing natural reagents from turmeric and lime for acetic acid determination in vinegar sample.

    PubMed

    Supharoek, Sam-Ang; Ponhong, Kraingkrai; Siriangkhawut, Watsaka; Grudpan, Kate

    2018-04-01

    A simple, rapid and environmentally friendly sequential injection analysis system employing natural extract reagents was developed for the determination of acetic acid following an acid-base reaction in the presence of an indicator. Powdered lime and turmeric were utilized as the natural base and indicator, respectively. Mixing lime and turmeric produced an orange to reddish-brown color solution which absorbed the maximum wavelength at 455 nm, with absorbance decreasing with increasing acetic acid concentration. Influential parameters including lime and turmeric concentrations, reagent and sample aspirated volumes, mixing coil length and dispensing flow rate were investigated and optimized. A standard calibration graph was plotted for 0-5.0 mmol/L acetic acid with r 2  = 0.9925. Relative standard deviations (RSD) at 2.0 and 4.0 mmol/L acetic acid were less than 3% (n = 7), with limit of detection (LOD) and limit of quantification (LOQ) at 0.12 and 0.24 mmol/L, respectively. The method was successfully applied to assay acetic acid concentration in cooking vinegar samples. Results achieved were not significantly different from those obtained following a batchwise standard AOAC titration method. Copyright © 2017. Published by Elsevier B.V.

  14. Search for Physics Beyond the Standard Model in Events with High-Momentum Higgs Bosons and Missing Transverse Momentum in Proton-Proton Collisions at 13 TeV

    NASA Astrophysics Data System (ADS)

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S.; Lee, J.; Lee, S.; Lee, S. W.; Moon, C. S.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Kim, H.; Moon, D. H.; Oh, G.; Brochero Cifuentes, J. A.; Goh, J.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Kim, J. S.; Lee, H.; Lee, K.; Nam, K.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Choi, Y.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Reyes-Almanza, R.; Ramirez-Sanchez, G.; Duran-Osuna, M. C.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Rabadan-Trejo, R. I.; Lopez-Fernandez, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Eysermans, J.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Galinhas, B.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. 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M.; Rabady, D.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Selvaggi, M.; Sharma, A.; Silva, P.; Sphicas, P.; Stakia, A.; Steggemann, J.; Stoye, M.; Tosi, M.; Treille, D.; Tsirou, A.; Veckalns, V.; Verweij, M.; Zeuner, W. D.; Bertl, W.; Caminada, L.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Backhaus, M.; Bäni, L.; Berger, P.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dorfer, C.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Klijnsma, T.; Lustermann, W.; Marionneau, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Reichmann, M.; Sanz Becerra, D. A.; Schönenberger, M.; Shchutska, L.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Brzhechko, D.; Canelli, M. F.; De Cosa, A.; Del Burgo, R.; Donato, S.; Galloni, C.; Hreus, T.; Kilminster, B.; Neutelings, I.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Schweiger, K.; Seitz, C.; Takahashi, Y.; Zucchetta, A.; Candelise, V.; Chang, Y. H.; Cheng, K. y.; Doan, T. H.; Jain, Sh.; Khurana, R.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Paganis, E.; Psallidas, A.; Steen, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Bat, A.; Boran, F.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Sunar Cerci, D.; Tali, B.; Tok, U. G.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Karapinar, G.; Ocalan, K.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Komurcu, Y.; Grynyov, B.; Levchuk, L.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Davignon, O.; Flacher, H.; Goldstein, J.; Heath, G. P.; Heath, H. F.; Kreczko, L.; Newbold, D. M.; Paramesvaran, S.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Linacre, J.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Womersley, W. J.; Auzinger, G.; Bainbridge, R.; Bloch, P.; Borg, J.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; Della Negra, M.; Di Maria, R.; Elwood, A.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Komm, M.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Palladino, V.; Pesaresi, M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Strebler, T.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wardle, N.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Morton, A.; Reid, I. D.; Teodorescu, L.; Zahid, S.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Smith, C.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Hadley, M.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Lee, J.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Stolp, D.; Taylor, D.; Tos, K.; Tripathi, M.; Wang, Z.; Zhang, F.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Regnard, S.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Karapostoli, G.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Si, W.; Wang, L.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Gilbert, D.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Citron, M.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; Gouskos, L.; Heller, R.; Incandela, J.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bornheim, A.; Bunn, J.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T. Q.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Macdonald, E.; Mulholland, T.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chaves, J.; Cheng, Y.; Chu, J.; Datta, A.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Quach, D.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Alyari, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kortelainen, M. J.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Savoy-Navarro, A.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Wu, W.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Joshi, B. M.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Shi, K.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Dittmer, S.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Rogan, C.; Royon, C.; Sanders, S.; Schmitz, E.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Modak, A.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Rebassoo, F.; Wright, D.; Baden, A.; Baron, O.; Belloni, A.; Eno, S. C.; Feng, Y.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bauer, G.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Harris, P.; Hsu, D.; Hu, M.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Stephans, G. S. F.; Sumorok, K.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Zhaozhong, S.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Wadud, M. A.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Golf, F.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Freer, C.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Orimoto, T.; Teixeira De Lima, R.; Wamorkar, T.; Wang, B.; Wisecarver, A.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Bucci, R.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Li, W.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Siddireddy, P.; Smith, G.; Taroni, S.; Wayne, M.; Wightman, A.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Ling, T. Y.; Luo, W.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Kalogeropoulos, A.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Salfeld-Nebgen, J.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Das, S.; Gutay, L.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xiao, R.; Xie, W.; Cheng, T.; Parashar, N.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. M.; Guilbaud, M.; Kilpatrick, M.; Li, W.; Michlin, B.; Padley, B. P.; Roberts, J.; Rorie, J.; Shi, W.; Tu, Z.; Zabel, J.; Zhang, A.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Mengke, T.; Muthumuni, S.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Poudyal, N.; Sturdy, J.; Thapa, P.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Carlsmith, D.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Rekovic, V.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Woods, N.; CMS Collaboration

    2018-06-01

    A search for physics beyond the standard model in events with one or more high-momentum Higgs bosons, H , decaying to pairs of b quarks in association with missing transverse momentum is presented. The data, corresponding to an integrated luminosity of 35.9 fb-1, were collected with the CMS detector at the LHC in proton-proton collisions at the center-of-mass energy √{s }=13 TeV . The analysis utilizes a new b quark tagging technique based on jet substructure to identify jets from H →b b ¯ . Events are categorized by the multiplicity of H -tagged jets, jet mass, and the missing transverse momentum. No significant deviation from standard model expectations is observed. In the context of supersymmetry (SUSY), limits on the cross sections of pair-produced gluinos are set, assuming that gluinos decay to quark pairs, H (or Z ), and the lightest SUSY particle, LSP, through an intermediate next-to-lightest SUSY particle, NLSP. With large mass splitting between the NLSP and LSP, and 100% NLSP branching fraction to H , the lower limit on the gluino mass is found to be 2010 GeV.

  15. Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory; determination of dissolved arsenic, boron, lithium, selenium, strontium, thallium, and vanadium using inductively coupled plasma-mass spectrometry

    USGS Publications Warehouse

    Garbarino, John R.

    1999-01-01

    The inductively coupled plasma?mass spectrometric (ICP?MS) methods have been expanded to include the determination of dissolved arsenic, boron, lithium, selenium, strontium, thallium, and vanadium in filtered, acidified natural water. Method detection limits for these elements are now 10 to 200 times lower than by former U.S. Geological Survey (USGS) methods, thus providing lower variability at ambient concentrations. The bias and variability of the method was determined by using results from spike recoveries, standard reference materials, and validation samples. Spike recoveries at 5 to 10 times the method detection limit and 75 micrograms per liter in reagent-water, surface-water, and groundwater matrices averaged 93 percent for seven replicates, although selected elemental recoveries in a ground-water matrix with an extremely high iron sulfate concentration were negatively biased by 30 percent. Results for standard reference materials were within 1 standard deviation of the most probable value. Statistical analysis of the results from about 60 filtered, acidified natural-water samples indicated that there was no significant difference between ICP?MS and former USGS official methods of analysis.

  16. Passive PE Sampling in Support of In Situ Remediation of Contaminated Sediments

    DTIC Science & Technology

    2015-08-01

    control RPD relative percent difference RSD relative standard deviation SERDP Strategic Environmental Research and Development Program SOPs...sediments from 2 stations, each at 4 PCB spike levels, for four individual congeners was 22 ± 6 % relative standard deviation ( RSD ). Also, comparison of... RSD (Table 3). However, larger congeners (e.g., congeners #153 and 180) whose approach to equilibrium is less certain, based on small fractions of

  17. Thermal management optimization of an air-cooled Li-ion battery module using pin-fin heat sinks for hybrid electric vehicles

    NASA Astrophysics Data System (ADS)

    Mohammadian, Shahabeddin K.; Zhang, Yuwen

    2015-01-01

    Three dimensional transient thermal analysis of an air-cooled module that contains prismatic Li-ion cells next to a special kind of aluminum pin fin heat sink whose heights of pin fins increase linearly through the width of the channel in air flow direction was studied for thermal management of Lithium-ion battery pack. The effects of pin fins arrangements, discharge rates, inlet air flow velocities, and inlet air temperatures on the battery were investigated. The results showed that despite of heat sinks with uniform pin fin heights that increase the standard deviation of the temperature field, using this kind of pin fin heat sink compare to the heat sink without pin fins not only decreases the bulk temperature inside the battery, but also decreases the standard deviation of the temperature field inside the battery as well. Increasing the inlet air temperature leads to decreasing the standard deviation of the temperature field while increases the maximum temperature of the battery. Furthermore, increasing the inlet air velocity first increases the standard deviation of the temperature field till reaches to the maximum point, and after that decreases. Also, increasing the inlet air velocity leads to decrease in the maximum temperature of the battery.

  18. A Methodology for Protective Vibration Monitoring of Hydropower Units Based on the Mechanical Properties.

    PubMed

    Nässelqvist, Mattias; Gustavsson, Rolf; Aidanpää, Jan-Olov

    2013-07-01

    It is important to monitor the radial loads in hydropower units in order to protect the machine from harmful radial loads. Existing recommendations in the standards regarding the radial movements of the shaft and bearing housing in hydropower units, ISO-7919-5 (International Organization for Standardization, 2005, "ISO 7919-5: Mechanical Vibration-Evaluation of Machine Vibration by Measurements on Rotating Shafts-Part 5: Machine Sets in Hydraulic Power Generating and Pumping Plants," Geneva, Switzerland) and ISO-10816-5 (International Organization for Standardization, 2000, "ISO 10816-5: Mechanical Vibration-Evaluation of Machine Vibration by Measurements on Non-Rotating Parts-Part 5: Machine Sets in Hydraulic Power Generating and Pumping Plants," Geneva, Switzerland), have alarm levels based on statistical data and do not consider the mechanical properties of the machine. The synchronous speed of the unit determines the maximum recommended shaft displacement and housing acceleration, according to these standards. This paper presents a methodology for the alarm and trip levels based on the design criteria of the hydropower unit and the measured radial loads in the machine during operation. When a hydropower unit is designed, one of its design criteria is to withstand certain loads spectra without the occurrence of fatigue in the mechanical components. These calculated limits for fatigue are used to set limits for the maximum radial loads allowed in the machine before it shuts down in order to protect itself from damage due to high radial loads. Radial loads in hydropower units are caused by unbalance, shape deviations, dynamic flow properties in the turbine, etc. Standards exist for balancing and manufacturers (and power plant owners) have recommendations for maximum allowed shape deviations in generators. These standards and recommendations determine which loads, at a maximum, should be allowed before an alarm is sent that the machine needs maintenance. The radial bearing load can be determined using load cells, bearing properties multiplied by shaft displacement, or bearing bracket stiffness multiplied by housing compression or movement. Different load measurement methods should be used depending on the design of the machine and accuracy demands in the load measurement. The methodology presented in the paper is applied to a 40 MW hydropower unit; suggestions are presented for the alarm and trip levels for the machine based on the mechanical properties and radial loads.

  19. Leptoquarks and compositeness scales from a contact interaction analysis of deep inelastic e±p scattering at HERA

    NASA Astrophysics Data System (ADS)

    Aid, S.; Andreev, V.; Andrieu, B.; Appuhn, R.-D.; Arpagaus, M.; Babaev, A.; Bähr, J.; Bán, J.; Ban, Y.; Baranov, P.; Barrelet, E.; Barschke, R.; Bartel, W.; Barth, M.; Bassler, U.; Beck, H. P.; Behrend, H.-J.; Belousov, A.; Berger, Ch.; Bernardi, G.; Bernet, R.; Bertrand-Coremans, G.; Besançon, M.; Beyer, R.; Biddulph, P.; Bispham, P.; Bizot, J. C.; Blobel, V.; Borras, K.; Botterweck, F.; Boudry, V.; Braemer, A.; Brasse, F.; Braunschweig, W.; Brisson, V.; Bruncko, D.; Brune, C.; Buchholz, R.; Büngener, L.; Bürger, J.; Büsser, F. W.; Buniatian, A.; Burke, S.; Burton, M. J.; Buschhorn, G.; Campbell, A. J.; Carli, T.; Charles, F.; Charlet, M.; Clarke, D.; Clegg, A. B.; Clerbaux, B.; Contreras, J. G.; Cormack, C.; Coughlan, J. A.; Courau, A.; Coutures, Ch.; Cozzika, G.; Criegee, L.; Cussans, D. G.; Cvach, J.; Dagoret, S.; Dainton, J. B.; Dau, W. D.; Daum, K.; David, M.; Delcourt, B.; Del Buono, L.; De Roeck, A.; De Wolf, E. A.; Di Nezza, P.; Dollfus, C.; Dowell, J. D.; Dreis, H. B.; Droutskoi, A.; Duboc, J.; Düllmann, D.; Dünger, O.; Duhm, H.; Ebert, J.; Ebert, T. R.; Eckerlin, G.; Efremenko, V.; Egli, S.; Ehrlichmann, H.; Eichenberger, S.; Eichler, R.; Eisele, F.; Eisenhandler, E.; Ellison, R. J.; Elsen, E.; Erdmann, M.; Erdmann, W.; Evrard, E.; Favart, L.; Fedotov, A.; Feeken, D.; Felst, R.; Feltesse, J.; Ferencei, J.; Ferrarotto, F.; Flamm, K.; Fleischer, M.; Flieser, M.; Flügge, G.; Fomenko, A.; Fominykh, B.; Forbush, M.; Formánek, J.; Foster, J. M.; Franke, G.; Fretwurst, E.; Gabathuler, E.; Gabathuler, K.; Garvey, J.; Gayler, J.; Gebauer, M.; Gellrich, A.; Genzel, H.; Gerhards, R.; Glazov, A.; Goerlach, U.; Goerlich, L.; Gogitidze, N.; Goldberg, M.; Goldner, D.; Gonzalez-Pineiro, B.; Gorelov, I.; Goritchev, P.; Grab, C.; Grässler, H.; Grässler, R.; Greenshaw, T.; Grindhammer, G.; Gruber, A.; Gruber, C.; Haack, J.; Haidt, D.; Hajduk, L.; Hamon, O.; Hampel, M.; Hapke, M.; Haynes, W. J.; Heatherington, J.; Heinzelmann, G.; Henderson, R. C. W.; Henschel, H.; Herynek, I.; Hess, M. F.; Hildesheim, W.; Hill, P.; Hiller, K. H.; Hilton, C. D.; Hladký, J.; Hoeger, K. C.; Höppner, M.; Horisberger, R.; Hudgson, V. L.; Huet, Ph.; Hütte, M.; Hufnagel, H.; Ibbotson, M.; Itterbeck, H.; Jabiol, M.-A.; Jacholkowska, A.; Jacobsson, C.; Jaffre, M.; Janoth, J.; Jansen, T.; Jönsson, L.; Johnson, D. P.; Johnson, L.; Jung, H.; Kalmus, P. I. P.; Kant, D.; Kaschowitz, R.; Kasselmann, P.; Kathage, U.; Katzy, J.; Kaufmann, H. H.; Kazarian, S.; Kenyon, I. R.; Kermiche, S.; Keuker, C.; Kiesling, C.; Klein, M.; Kleinwort, C.; Knies, G.; Ko, W.; Köhler, T.; Köhne, J. H.; Kolanoski, H.; Kole, F.; Kolya, S. D.; Korbel, V.; Korn, M.; Kostka, P.; Kotelnikov, S. K.; Krämerkämper, T.; Krasny, M. W.; Krehbiel, H.; Krücker, D.; Krüger, U.; Krüner-Marquis, U.; Küster, H.; Kuhlen, M.; Kurča, T.; Kurzhöfer, J.; Kuznik, B.; Lacour, D.; Lamarche, F.; Lander, R.; Landon, M. P. J.; Lange, W.; Lanius, P.; Laporte, J.-F.; Lebedev, A.; Lehner, F.; Leverenz, C.; Levonian, S.; Ley, Ch.; Lindström, G.; Link, J.; Linsel, F.; Lipinski, J.; List, B.; Lobo, G.; Loch, P.; Lohmander, H.; Lomas, J. W.; Lopez, G. C.; Lubimov, V.; Lüke, D.; Magnussen, N.; Malinovski, E.; Mani, S.; Maraček, R.; Marage, P.; Marks, J.; Marshall, R.; Martens, J.; Martin, G.; Martin, R.; Martyn, H.-U.; Martyniak, J.; Masson, S.; Mavroidis, T.; Maxfield, S. J.; McMahon, S. J.; Mehta, A.; Meier, K.; Mercer, D.; Merz, T.; Meyer, A.; Meyer, C. A.; Meyer, H.; Meyer, J.; Migliori, A.; Mikocki, S.; Milstead, D.; Moreau, F.; Morris, J. V.; Mroczko, E.; Müller, G.; Müller, K.; Murín, P.; Nagovizin, V.; Nahnhauer, R.; Naroska, B.; Naumann, Th.; Newman, P. R.; Newton, D.; Neyret, D.; Nguyen, H. K.; Nicholls, T. C.; Niebergall, F.; Niebuhr, C.; Niedzballa, Ch.; Nisius, R.; Nowak, G.; Noyes, G. W.; Nyberg-Werther, M.; Oakden, M.; Oberlack, H.; Obrock, U.; Olsson, J. E.; Ozerov, D.; Panaro, E.; Panitch, A.; Pascaud, C.; Patel, G. D.; Peppel, E.; Perez, E.; Phillips, J. P.; Pichler, Ch.; Pitzl, D.; Pope, G.; Prell, S.; Prosi, R.; Rabbertz, K.; Rädel, G.; Raupach, F.; Reimer, P.; Reinshagen, S.; Ribarics, P.; Rick, H.; Riech, V.; Riedlberger, J.; Riess, S.; Rietz, M.; Rizvi, E.; Robertson, S. M.; Robmann, P.; Roloff, H. E.; Roosen, R.; Rosenbauer, K.; Rostovtsev, A.; Rouse, F.; Royon, C.; Rüter, K.; Rusakov, S.; Rybicki, K.; Rylko, R.; Sahlmann, N.; Sankey, D. P. C.; Schacht, P.; Schiek, S.; Schleif, S.; Schleper, P.; von Schlippe, W.; Schmidt, D.; Schmidt, G.; Schöning, A.; Schröder, V.; Schuhmann, E.; Schwab, B.; Sciacca, G.; Sefkow, F.; Seidel, M.; Sell, R.; Semenov, A.; Shekelyan, V.; Sheviakov, I.; Shtarkov, L. N.; Siegmon, G.; Siewert, U.; Sirois, Y.; Skillicorn, I. O.; Smirnov, P.; Smith, J. R.; Solochenko, V.; Soloviev, Y.; Spiekermann, J.; Spielman, S.; Spitzer, H.; Starosta, R.; Steenbock, M.; Steffen, P.; Steinberg, R.; Stella, B.; Stephens, K.; Stier, J.; Stiewe, J.; Stößlein, U.; Stolze, K.; Strachota, J.; Straumann, U.; Struczinski, W.; Sutton, J. P.; Tapprogge, S.; Tchernyshov, V.; Thiebaux, C.; Thompson, G.; Truöl, P.; Turnau, J.; Tutas, J.; Uelkes, P.; Usik, A.; Valkár, S.; Valkárová, A.; Vallée, C.; Vandenplas, D.; Van Esch, P.; Van Mechelen, P.; Vartapetian, A.; Vazdik, Y.; Verrecchia, P.; Villet, G.; Wacker, K.; Wagener, A.; Wagener, M.; Walther, A.; Weber, G.; Weber, M.; Wegener, D.; Wegner, A.; Wellisch, H. P.; West, L. R.; Willard, S.; Winde, M.; Winter, G.-G.; Wittek, C.; Wright, A. E.; Wünsch, E.; Wulff, N.; Yiou, T. P.; Žáček, J.; Zarbock, D.; Zhang, z.; Zhokin, A.; Zimmer, M.; Zimmermann, W.; Zomer, F.; Zuber, K.; zurNedden, M.; H1 Collaboration

    1995-02-01

    A contact interaction analysis is presented to search for new phenomena beyond the Standard Model in deep inelastic e±p → e±hadrons scattering. The data are collected with the H1 detector at HERA and correspond to integrated luminosities of 0.909 pb -1 and 2.947 pb -1 for electron and positron beams, respectively. The differential cross sections dσ/d Q2 are measured in the Q2 range between 160 GeV 2 and 20 000 GeV 2. The absence of any significant deviation from the Standard Model prediction is used to constrain the couplings and masses of new leptoquarks and to set limits on electron-quark compositeness scales and on the radius of light quarks.

  20. Heavy metal determinations in algae, mussels and clams. Their possible employment for assessing the sea water quality criteria

    NASA Astrophysics Data System (ADS)

    Locatelli, C.

    2003-05-01

    An empirical criterion for a possible classification of sea water quality is proposed. It is based on the knowledge of metal content in algae (Ulva Rigida) mussels (Mytilus Galloprovincialis) and clams (Tapes Philippinarum), three species present in marine ecosystems. The elements considered are Hg, Cu, Pb, Cd, Zn, Ni and Cr. The anatytical technique employed is Atomic Absorption Spectroscopy (AAS). The analytical procedure has been verified on three standard reference materials : Sea Water BCR-CRM 403, Ulva Lactuca BCR-CRM 279 and Mussel Tissue BCR-CRM 278. For all the elements, in addition to detection limits, accuracy and precision are given : the former, expressed as retative error (e). and the latter, expressed as relative standard deviation (sr), were in all cases lower than 6%.

  1. Determination of para red, Sudan dyes, canthaxanthin, and astaxanthin in animal feeds using UPLC.

    PubMed

    Hou, Xiaolin; Li, Yonggang; Wu, Guojuan; Wang, Lei; Hong, Miao; Wu, Yongnin

    2010-01-01

    A simple high-performance liquid chromatography method was developed for quantitative determination of para red, Sudan I, Sudan II, Sudan III, Sudan IV, canthaxanthin, and astaxanthin in feedstuff. The sample was extracted using acetonitrile and cleaned up on a C(18) SPE column. The residues were analyzed using ultra-performance liquid chromatography coupled to a diode array detector at 500 nm. The mobile phase was acetonitrile-formic acid-water with a gradient elution condition. The external standard curves were calibrated. The mean recoveries of the seven colorants were 62.7-91.0% with relative standard deviation 2.6-10.4% (intra-day) and 4.0-13.2% (inter-day). The detection limits were in the range of 0.006-0.02 mg/kg.

  2. [Determination of buprofezin, methamidophos, acephate, and triazophos residues in Chinese tea samples by gas chromatography].

    PubMed

    Zhang, Shuiba; Yi, Jun; Ye, Jianglei; Zheng, Wenhui; Cai, Xueqin; Gong, Zhenbin

    2004-03-01

    A method has been developed for the simultaneous determination of buprofezin, methamidophos, acephate and triazophos residues in Chinese tea samples. The pesticide residues were extracted from tea samples with a mixture of ethyl acetate and n-hexane (50:50, v/v) at 45 degrees C. The extracts were subsequently treated with a column packed with 40 mg of active carbon by gradient elution with ethyl acetate and n-hexane. Buprofenzin and the three organophosphorus pesticides were analyzed by gas chromatography using a DB-210 capillary column and a nitrogen-phosphorus detector. The recoveries for spiked standards were 73.4%-96.9%. The relative standard deviations were all within 4.63%. The limits of quantitation (3sigma) in the tea samples were about 7.0-12.0 microg/kg.

  3. Determination of antibacterial flomoxef in serum by capillary electrophoresis.

    PubMed

    Kitahashi, Toshihiro; Furuta, Itaru

    2003-04-01

    A determination method of flomoxef (FMOX) concentration in serum by capillary electrophoresis is developed. Serum samples are extracted with acetonitrile. After pretreatment, they are separated in a fused-silica capillary tube with a 25 mM borate buffer (pH 10.0) as a running buffer that contains 50mM sodium dodecyl sulfate. The FMOX and acetaminophen (internal standard) are detected by UV absorbance at 200 nm. Linearity (0-200 mg/L) is good, and the minimum limit of detection is 1.0 mg/L (S/N = 3). The relative standard deviations of intra- and interassay variability are 1.60-4.78% and 2.10-3.31%, respectively, and the recovery rate is 84-98%. This method can be used for determination of FMOX concentration in serum.

  4. Study of the rare decays of [Formula: see text] and [Formula: see text] into muon pairs from data collected during the LHC Run 1 with the ATLAS detector.

    PubMed

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Pallin, D; Palma, A; Panagiotopoulou, E St; Pandini, C E; Vazquez, J G Panduro; Pani, P; Panitkin, S; Pantea, D; Paolozzi, L; Papadopoulou, Th D; Papageorgiou, K; Paramonov, A; Hernandez, D Paredes; Parker, A J; Parker, M A; Parker, K A; Parodi, F; Parsons, J A; Parzefall, U; Pascuzzi, V R; Pasqualucci, E; Passaggio, S; Pastore, Fr; Pásztor, G; Pataraia, S; Pater, J R; Pauly, T; Pearce, J; Pearson, B; Pedersen, L E; Pedersen, M; Lopez, S Pedraza; Pedro, R; Peleganchuk, S V; Pelikan, D; Penc, O; Peng, C; Peng, H; Penwell, J; Peralva, B S; Perego, M M; Perepelitsa, D V; Codina, E Perez; Perini, L; Pernegger, H; Perrella, S; Peschke, R; Peshekhonov, V D; Peters, K; Peters, R F Y; Petersen, B A; Petersen, T C; Petit, E; Petridis, A; Petridou, C; Petroff, P; Petrolo, E; Petrov, M; Petrucci, F; Pettersson, N E; Peyaud, A; Pezoa, R; Phillips, P W; Piacquadio, G; Pianori, E; Picazio, A; Piccaro, E; Piccinini, M; Pickering, M A; Piegaia, R; Pilcher, J E; Pilkington, A D; Pin, A W J; Pinamonti, M; 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Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Nedden, M Zur; Zurzolo, G; Zwalinski, L

    2016-01-01

    A study of the decays [Formula: see text] and [Formula: see text] has been performed using data corresponding to an integrated luminosity of 25 fb[Formula: see text] of 7 and 8 TeV proton-proton collisions collected with the ATLAS detector during the LHC Run 1. For the [Formula: see text] dimuon decay, an upper limit on the branching fraction is set at [Formula: see text] at 95 % confidence level. For [Formula: see text], the branching fraction [Formula: see text] is measured. The results are consistent with the Standard Model expectation with a p value of 4.8 %, corresponding to 2.0 standard deviations.

  5. Identifying the independent effect of HbA1c variability on adverse health outcomes in patients with Type 2 diabetes.

    PubMed

    Prentice, J C; Pizer, S D; Conlin, P R

    2016-12-01

    To characterize the relationship between HbA 1c variability and adverse health outcomes among US military veterans with Type 2 diabetes. This retrospective cohort study used Veterans Affairs and Medicare claims for veterans with Type 2 diabetes taking metformin who initiated a second diabetes medication (n = 50 861). The main exposure of interest was HbA 1c variability during a 3-year baseline period. HbA 1c variability, categorized into quartiles, was defined as standard deviation, coefficient of variation and adjusted standard deviation, which accounted for the number and mean number of days between HbA 1c tests. Cox proportional hazard models predicted mortality, hospitalization for ambulatory care-sensitive conditions, and myocardial infarction or stroke and were controlled for mean HbA 1c levels and the direction of change in HbA 1c levels during the baseline period. Over a mean 3.3 years of follow-up, all HbA 1c variability measures significantly predicted each outcome. Using the adjusted standard deviation measure for HbA 1c variability, the hazard ratios for the third and fourth quartile predicting mortality were 1.14 (95% CI 1.04, 1.25) and 1.42 (95% CI 1.28, 1.58), for myocardial infarction and stroke they were 1.25 (95% CI 1.10, 1.41) and 1.23 (95% CI 1.07, 1.42) and for ambulatory-care sensitive condition hospitalization they were 1.10 (95% CI 1.03, 1.18) and 1.11 (95% CI 1.03, 1.20). Higher baseline HbA 1c levels independently predicted the likelihood of each outcome. In veterans with Type 2 diabetes, greater HbA 1c variability was associated with an increased risk of adverse long-term outcomes, independently of HbA 1c levels and direction of change. Limiting HbA 1c fluctuations over time may reduce complications. © 2016 Diabetes UK.

  6. High levels of ultraviolet radiation observed by ground-based instruments below the 2011 Arctic ozone hole

    NASA Astrophysics Data System (ADS)

    Bernhard, G.; Dahlback, A.; Fioletov, V.; Heikkilä, A.; Johnsen, B.; Koskela, T.; Lakkala, K.; Svendby, T.

    2013-11-01

    Greatly increased levels of ultraviolet (UV) radiation were observed at thirteen Arctic and sub-Arctic ground stations in the spring of 2011, when the ozone abundance in the Arctic stratosphere dropped to the lowest amounts on record. Measurements of the noontime UV Index (UVI) during the low-ozone episode exceeded the climatological mean by up to 77% at locations in the western Arctic (Alaska, Canada, Greenland) and by up to 161% in Scandinavia. The UVI measured at the end of March at the Scandinavian sites was comparable to that typically observed 15-60 days later in the year when solar elevations are much higher. The cumulative UV dose measured during the period of the ozone anomaly exceeded the climatological mean by more than two standard deviations at 11 sites. Enhancements beyond three standard deviations were observed at seven sites and increases beyond four standard deviations at two sites. At the western sites, the episode occurred in March, when the Sun was still low in the sky, limiting absolute UVI anomalies to less than 0.5 UVI units. At the Scandinavian sites, absolute UVI anomalies ranged between 1.0 and 2.2 UVI units. For example, at Finse, Norway, the noontime UVI on 30 March was 4.7, while the climatological UVI is 2.5. Although a UVI of 4.7 is still considered moderate, UV levels of this amount can lead to sunburn and photokeratitis during outdoor activity when radiation is reflected upward by snow towards the face of a person or animal. At the western sites, UV anomalies can be well explained with ozone anomalies of up to 41% below the climatological mean. At the Scandinavian sites, low ozone can only explain a UVI increase of 50-60%. The remaining enhancement was mainly caused by the absence of clouds during the low-ozone period.

  7. High levels of ultraviolet radiation observed by ground-based instruments below the 2011 Arctic ozone hole

    NASA Astrophysics Data System (ADS)

    Bernhard, G.; Dahlback, A.; Fioletov, V.; Heikkilä, A.; Johnsen, B.; Koskela, T.; Lakkala, K.; Svendby, T. M.

    2013-06-01

    Greatly increased levels of ultraviolet (UV) radiation were observed at thirteen Arctic and sub-Arctic ground stations in the spring of 2011 when the ozone abundance in the Arctic stratosphere dropped to the lowest amounts on record. Measurements of the noontime UV Index (UVI) during the low-ozone episode exceeded the climatological mean by up to 77% at locations in the western Arctic (Alaska, Canada, Greenland) and by up to 161% in Scandinavia. The UVI measured at the end of March at the Scandinavian sites was comparable to that typically observed 15-60 days later in the year when solar elevations are much higher. The cumulative UV dose measured during the period of the ozone anomaly exceeded the climatological mean by more than two standard deviations at 11 sites. Enhancements beyond three standard deviations were observed at seven sites and increases beyond four standard deviations at two sites. At the western sites, the episode occurred in March when the Sun was still low in the sky, limiting absolute UVI anomalies to less than 0.5 UVI units. At the Scandinavian sites, absolute UVI anomalies ranged between 1.0 and 2.2 UVI units. For example, at Finse, Norway, the noontime UVI on 30 March was 4.7 while the climatological UVI is 2.5. Although a UVI of 4.7 is still considered moderate, UV levels of this amount can lead to sunburn and photokeratitis during outdoor activity when radiation is reflected upward by snow towards the face of a person or animal. At the western sites, UV anomalies can be well explained with ozone anomalies of up to 41% below the climatological mean. At the Scandinavian sites, low ozone can only explain a UVI increase by 50-60%. The remaining enhancement was mainly caused by the absence of clouds during the low-ozone period.

  8. Relation between Birth Weight and Intraoperative Hemorrhage during Cesarean Section in Pregnancy with Placenta Previa

    PubMed Central

    Ishibashi, Hiroki; Takano, Masashi; Sasa, Hidenori; Furuya, Kenichi

    2016-01-01

    Background Placenta previa, one of the most severe obstetric complications, carries an increased risk of intraoperative massive hemorrhage. Several risk factors for intraoperative hemorrhage have been identified to date. However, the correlation between birth weight and intraoperative hemorrhage has not been investigated. Here we estimate the correlation between birth weight and the occurrence of intraoperative massive hemorrhage in placenta previa. Materials and Methods We included all 256 singleton pregnancies delivered via cesarean section at our hospital because of placenta previa between 2003 and 2015. We calculated not only measured birth weights but also standard deviation values according to the Japanese standard growth curve to adjust for differences in gestational age. We assessed the correlation between birth weight and the occurrence of intraoperative massive hemorrhage (>1500 mL blood loss). Receiver operating characteristic curves were constructed to determine the cutoff value of intraoperative massive hemorrhage. Results Of 256 pregnant women with placenta previa, 96 (38%) developed intraoperative massive hemorrhage. Receiver-operating characteristic curves revealed that the area under the curve of the combination variables between the standard deviation of birth weight and intraoperative massive hemorrhage was 0.71. The cutoff value with a sensitivity of 81.3% and specificity of 55.6% was −0.33 standard deviation. The multivariate analysis revealed that a standard deviation of >−0.33 (odds ratio, 5.88; 95% confidence interval, 3.04–12.00), need for hemostatic procedures (odds ratio, 3.31; 95% confidence interval, 1.79–6.25), and placental adhesion (odds ratio, 12.68; 95% confidence interval, 2.85–92.13) were independent risk of intraoperative massive hemorrhage. Conclusion In patients with placenta previa, a birth weight >−0.33 standard deviation was a significant risk indicator of massive hemorrhage during cesarean section. Based on this result, further studies are required to investigate whether fetal weight estimated by ultrasonography can predict hemorrhage during cesarean section in patients with placental previa. PMID:27902772

  9. Relation between Birth Weight and Intraoperative Hemorrhage during Cesarean Section in Pregnancy with Placenta Previa.

    PubMed

    Soyama, Hiroaki; Miyamoto, Morikazu; Ishibashi, Hiroki; Takano, Masashi; Sasa, Hidenori; Furuya, Kenichi

    2016-01-01

    Placenta previa, one of the most severe obstetric complications, carries an increased risk of intraoperative massive hemorrhage. Several risk factors for intraoperative hemorrhage have been identified to date. However, the correlation between birth weight and intraoperative hemorrhage has not been investigated. Here we estimate the correlation between birth weight and the occurrence of intraoperative massive hemorrhage in placenta previa. We included all 256 singleton pregnancies delivered via cesarean section at our hospital because of placenta previa between 2003 and 2015. We calculated not only measured birth weights but also standard deviation values according to the Japanese standard growth curve to adjust for differences in gestational age. We assessed the correlation between birth weight and the occurrence of intraoperative massive hemorrhage (>1500 mL blood loss). Receiver operating characteristic curves were constructed to determine the cutoff value of intraoperative massive hemorrhage. Of 256 pregnant women with placenta previa, 96 (38%) developed intraoperative massive hemorrhage. Receiver-operating characteristic curves revealed that the area under the curve of the combination variables between the standard deviation of birth weight and intraoperative massive hemorrhage was 0.71. The cutoff value with a sensitivity of 81.3% and specificity of 55.6% was -0.33 standard deviation. The multivariate analysis revealed that a standard deviation of >-0.33 (odds ratio, 5.88; 95% confidence interval, 3.04-12.00), need for hemostatic procedures (odds ratio, 3.31; 95% confidence interval, 1.79-6.25), and placental adhesion (odds ratio, 12.68; 95% confidence interval, 2.85-92.13) were independent risk of intraoperative massive hemorrhage. In patients with placenta previa, a birth weight >-0.33 standard deviation was a significant risk indicator of massive hemorrhage during cesarean section. Based on this result, further studies are required to investigate whether fetal weight estimated by ultrasonography can predict hemorrhage during cesarean section in patients with placental previa.

  10. Automating linear accelerator quality assurance.

    PubMed

    Eckhause, Tobias; Al-Hallaq, Hania; Ritter, Timothy; DeMarco, John; Farrey, Karl; Pawlicki, Todd; Kim, Gwe-Ya; Popple, Richard; Sharma, Vijeshwar; Perez, Mario; Park, SungYong; Booth, Jeremy T; Thorwarth, Ryan; Moran, Jean M

    2015-10-01

    The purpose of this study was 2-fold. One purpose was to develop an automated, streamlined quality assurance (QA) program for use by multiple centers. The second purpose was to evaluate machine performance over time for multiple centers using linear accelerator (Linac) log files and electronic portal images. The authors sought to evaluate variations in Linac performance to establish as a reference for other centers. The authors developed analytical software tools for a QA program using both log files and electronic portal imaging device (EPID) measurements. The first tool is a general analysis tool which can read and visually represent data in the log file. This tool, which can be used to automatically analyze patient treatment or QA log files, examines the files for Linac deviations which exceed thresholds. The second set of tools consists of a test suite of QA fields, a standard phantom, and software to collect information from the log files on deviations from the expected values. The test suite was designed to focus on the mechanical tests of the Linac to include jaw, MLC, and collimator positions during static, IMRT, and volumetric modulated arc therapy delivery. A consortium of eight institutions delivered the test suite at monthly or weekly intervals on each Linac using a standard phantom. The behavior of various components was analyzed for eight TrueBeam Linacs. For the EPID and trajectory log file analysis, all observed deviations which exceeded established thresholds for Linac behavior resulted in a beam hold off. In the absence of an interlock-triggering event, the maximum observed log file deviations between the expected and actual component positions (such as MLC leaves) varied from less than 1% to 26% of published tolerance thresholds. The maximum and standard deviations of the variations due to gantry sag, collimator angle, jaw position, and MLC positions are presented. Gantry sag among Linacs was 0.336 ± 0.072 mm. The standard deviation in MLC position, as determined by EPID measurements, across the consortium was 0.33 mm for IMRT fields. With respect to the log files, the deviations between expected and actual positions for parameters were small (<0.12 mm) for all Linacs. Considering both log files and EPID measurements, all parameters were well within published tolerance values. Variations in collimator angle, MLC position, and gantry sag were also evaluated for all Linacs. The performance of the TrueBeam Linac model was shown to be consistent based on automated analysis of trajectory log files and EPID images acquired during delivery of a standardized test suite. The results can be compared directly to tolerance thresholds. In addition, sharing of results from standard tests across institutions can facilitate the identification of QA process and Linac changes. These reference values are presented along with the standard deviation for common tests so that the test suite can be used by other centers to evaluate their Linac performance against those in this consortium.

  11. [Detection of methyl carbamate and ethyl carbamate in yellow rice wine by gas chromatography-mass spectrometry].

    PubMed

    Wu, Ping-gu; Ma, Bing-jie; Wang, Li-yuan; Shen, Xiang-hong; Zhang, Jing; Tan, Ying; Jiang, Wei

    2013-11-01

    To establish the method of simultaneous determination of methylcarbamate (MC) and ethylcarbamate (EC) in yellow rice wine by gas chromatography-mass spectrometry (GC/MS). MC and EC in yellow rice wine were derived by 9-xanthydrol, and then the derivants were detected by GC/MS; and quantitatively analyzed by D5-EC isotope internal standard method. The linearity of MC and EC ranged from 2.0 µg/L to 400.0 µg/L, with correlation coefficients at 0.998 and 0.999, respectively. The limits of quantitation (LOQ) and detection (LOD) were 0.67 and 2.0 µg/kg. When MC and EC were added in yellow rice wine at the range of 2.0-300.0 µg/kg, the intraday average recovery rate was 78.8%-102.3%, relative standard deviation was 3.2%-11.6%; interday average recovery rate was 75.4%-101.3%, relative standard deviation was 3.8%-13.4%. 20 samples of yellow rice wine from supermarket were detected using this method, the contents of MC were in the range of ND (no detected) to 1.2 µg/kg, the detection rate was 6% (3/20), the contents of EC in the range of 18.6 µg/kg to 432.3 µg/kg, with the average level at 135.2 µg/kg. The method is simple, rapid and useful for simultaneous determination of MC and EC in yellow rice wine.

  12. Improving the Thermal, Radial and Temporal Accuracy of the Analytical Ultracentrifuge through External References

    PubMed Central

    Ghirlando, Rodolfo; Balbo, Andrea; Piszczek, Grzegorz; Brown, Patrick H.; Lewis, Marc S.; Brautigam, Chad A.; Schuck, Peter; Zhao, Huaying

    2013-01-01

    Sedimentation velocity (SV) is a method based on first-principles that provides a precise hydrodynamic characterization of macromolecules in solution. Due to recent improvements in data analysis, the accuracy of experimental SV data emerges as a limiting factor in its interpretation. Our goal was to unravel the sources of experimental error and develop improved calibration procedures. We implemented the use of a Thermochron iButton® temperature logger to directly measure the temperature of a spinning rotor, and detected deviations that can translate into an error of as much as 10% in the sedimentation coefficient. We further designed a precision mask with equidistant markers to correct for instrumental errors in the radial calibration, which were observed to span a range of 8.6%. The need for an independent time calibration emerged with use of the current data acquisition software (Zhao et al., doi 10.1016/j.ab.2013.02.011) and we now show that smaller but significant time errors of up to 2% also occur with earlier versions. After application of these calibration corrections, the sedimentation coefficients obtained from eleven instruments displayed a significantly reduced standard deviation of ∼ 0.7 %. This study demonstrates the need for external calibration procedures and regular control experiments with a sedimentation coefficient standard. PMID:23711724

  13. Sensitivity of Runway Occupancy Time (ROT) to Various Rollout and Turnoff (ROTO) Factors. Volume 1

    NASA Technical Reports Server (NTRS)

    Goldthorpe, S. H.

    1997-01-01

    The Terminal Area Productivity (TAP) research program was initiated by NASA to increase the airport capacity for transport aircraft operations. One element of the research program is called Low Visibility Landing and Surface Operations (LVLASO). A goal of the LVLASO research is to develop transport aircraft technologies which reduce Runway Occupancy Time (ROT) so that it does not become the limiting factor in the terminal area operations that determine the capacity of a runway. Under LVLASO, the objective of this study was to determine the sensitivity of ROT to various factors associated with the Rollout and Turnoff (ROTO) operation for transport aircraft. The following operational factors were studied and are listed in the order of decreasing ROT sensitivity: ice/flood runway surface condition, exit entrance ground speed, number of exits, high-speed exit locations and spacing, aircraft type, touchdown ground speed standard deviation, reverse thrust and braking method, accurate exit prediction capability, maximum reverse thrust availability, spiral-arc vs. circle-arc exit geometry, dry/slush/wet/snow runway surface condition, maximum allowed deceleration, auto asymmetric braking on exit, do not stow reverse thrust before the exit, touchdown longitudinal location standard deviation, flap setting, anti-skid efficiency, crosswind conditions, stopping on the exit and touchdown lateral offset.

  14. Improving the thermal, radial, and temporal accuracy of the analytical ultracentrifuge through external references.

    PubMed

    Ghirlando, Rodolfo; Balbo, Andrea; Piszczek, Grzegorz; Brown, Patrick H; Lewis, Marc S; Brautigam, Chad A; Schuck, Peter; Zhao, Huaying

    2013-09-01

    Sedimentation velocity (SV) is a method based on first principles that provides a precise hydrodynamic characterization of macromolecules in solution. Due to recent improvements in data analysis, the accuracy of experimental SV data emerges as a limiting factor in its interpretation. Our goal was to unravel the sources of experimental error and develop improved calibration procedures. We implemented the use of a Thermochron iButton temperature logger to directly measure the temperature of a spinning rotor and detected deviations that can translate into an error of as much as 10% in the sedimentation coefficient. We further designed a precision mask with equidistant markers to correct for instrumental errors in the radial calibration that were observed to span a range of 8.6%. The need for an independent time calibration emerged with use of the current data acquisition software (Zhao et al., Anal. Biochem., 437 (2013) 104-108), and we now show that smaller but significant time errors of up to 2% also occur with earlier versions. After application of these calibration corrections, the sedimentation coefficients obtained from 11 instruments displayed a significantly reduced standard deviation of approximately 0.7%. This study demonstrates the need for external calibration procedures and regular control experiments with a sedimentation coefficient standard. Published by Elsevier Inc.

  15. Atmospherically deposited PBDEs, pesticides, PCBs, and PAHs in western U.S. National Park fish: Concentrations and consumption guidelines

    USGS Publications Warehouse

    Ackerman, L.K.; Schwindt, A.R.; Simonich, S.L.M.; Koch, D.C.; Blett, T.F.; Schreck, C.B.; Kent, M.L.; Landers, D.H.

    2008-01-01

    Concentrations of polybrominated diphenyl ethers (PBDEs), pesticides, polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons were measured in 136 fish from 14 remote lakes in 8 western U.S. National Parks/Preserves between 2003 and 2005 and compared to human and wildlife contaminant health thresholds. A sensitive (median detection limit, -18 pg/g wet weight), efficient (61% recovery at 8 ng/g), reproducible (4.1% relative standard deviation (RSD)), and accurate (7% deviation from standard reference material (SRM)) analytical method was developed and validated for these analyses. Concentrations of PCBs, hexachlorobenzene, hexachlorocyclohexanes, DDTs, and chlordanes in western U.S. fish were comparable to or lower than mountain fish recently collected from Europe, Canada, and Asia. Dieldrin and PBDE concentrations were higher than recent measurements in mountain fish and Pacific Ocean salmon. Concentrations of most contaminants in western U.S. fish were 1-6 orders of magnitude below calculated recreational fishing contaminant health thresholds. However, lake average contaminant concentrations in fish exceeded subsistence fishing cancer thresholds in 8 of 14 lakes and wildlife contaminant health thresholds for piscivorous birds in 1of 14 lakes. These results indicate that atmospherically deposited organic contaminants can accumulate in high elevation fish, reaching concentrations relevant to human and wildlife health. ?? 2008 American Chemical Society.

  16. Sensitivity of Runway Occupancy Time (ROT) to Various Rollout and Turnoff (ROTO) Factors. Volume 2; Complete Set of Plotted Data

    NASA Technical Reports Server (NTRS)

    Goldthorpe, S. H.

    1997-01-01

    The Terminal Area Productivity (TAP) research program was initiated by NASA to increase the airport capacity for transport aircraft operations. One element of the research program is called Low Visibility Landing and Surface Operations (LVLASO). A goal of the LVLASO research is to develop transport aircraft technologies which reduce Runway Occupancy Time (ROT) so that it does not become the limiting factor in the terminal area operations that determine the capacity of a runway. Under LVLASO, the objective of this study was to determine the sensitivity of ROT to various factors associated with the Rollout and Turnoff (ROTO) operation for transport aircraft. The following operational factors were studied and are listed in the order of decreasing ROT sensitivity: ice/flood runway surface condition, exit entrance ground speed, number of exits, high-speed exit locations and spacing, aircraft type, touchdown ground speed standard deviation, reverse thrust and braking method, accurate exit prediction capability, maximum reverse thrust availability, spiral-arc vs. circle-arc exit geometry, dry/slush/wet/snow runway surface condition, maximum allowed deceleration, auto asymmetric braking on exit, do not stow reverse thrust before the exit, touchdown longitudinal location standard deviation, flap setting, anti-skid efficiency, crosswind conditions, stopping on the exit and touchdown lateral offset.

  17. Intra-operative ultrasound-based augmented reality guidance for laparoscopic surgery.

    PubMed

    Singla, Rohit; Edgcumbe, Philip; Pratt, Philip; Nguan, Christopher; Rohling, Robert

    2017-10-01

    In laparoscopic surgery, the surgeon must operate with a limited field of view and reduced depth perception. This makes spatial understanding of critical structures difficult, such as an endophytic tumour in a partial nephrectomy. Such tumours yield a high complication rate of 47%, and excising them increases the risk of cutting into the kidney's collecting system. To overcome these challenges, an augmented reality guidance system is proposed. Using intra-operative ultrasound, a single navigation aid, and surgical instrument tracking, four augmentations of guidance information are provided during tumour excision. Qualitative and quantitative system benefits are measured in simulated robot-assisted partial nephrectomies. Robot-to-camera calibration achieved a total registration error of 1.0 ± 0.4 mm while the total system error is 2.5 ± 0.5 mm. The system significantly reduced healthy tissue excised from an average (±standard deviation) of 30.6 ± 5.5 to 17.5 ± 2.4 cm 3 ( p < 0.05) and reduced the depth from the tumor underside to cut from an average (±standard deviation) of 10.2 ± 4.1 to 3.3 ± 2.3 mm ( p < 0.05). Further evaluation is required in vivo, but the system has promising potential to reduce the amount of healthy parenchymal tissue excised.

  18. Analytical evaluation of BEA zeolite for the pre-concentration of polycyclic aromatic hydrocarbons and their subsequent chromatographic analysis in water samples.

    PubMed

    Wilson, Walter B; Costa, Andréia A; Wang, Huiyong; Dias, José A; Dias, Sílvia C L; Campiglia, Andres D

    2012-07-06

    The analytical performance of BEA - a commercial zeolite - is evaluated for the pre-concentration of fifteen Environmental Protection Agency - polycyclic aromatic hydrocarbons and their subsequent HPLC analysis in tap and lake water samples. The pre-concentration factors obtained with BEA have led to a method with excellent analytical figures of merit. One milliliter aliquots were sufficient to obtain excellent precision of measurements at the parts-per-trillion concentration level with relative standard deviations varying from 4.1% (dibenzo[a,h]anthracene) to 13.4% (pyrene). The limits of detection were excellent as well and varied between 1.1 (anthracene) and 49.9 ng L(-1) (indeno[1,2,3-cd]pyrene). The recovery values of all the studied compounds meet the criterion for regulated polycyclic aromatic hydrocarbons, which mandates relative standard deviations equal or lower than 25%. The small volume of organic solvents (100 μL per sample) and amount of BEA (2 mg per sample) makes sample pre-concentration environmentally friendly and cost effective. The extraction procedure is well suited for numerous samples as the small working volume (1 mL) facilitates the implementation of simultaneous sample extraction. These are attractive features when routine monitoring of numerous samples is contemplated. Copyright © 2012 Elsevier B.V. All rights reserved.

  19. Characterizations of particle size distribution of the droplets exhaled by sneeze

    PubMed Central

    Han, Z. Y.; Weng, W. G.; Huang, Q. Y.

    2013-01-01

    This work focuses on the size distribution of sneeze droplets exhaled immediately at mouth. Twenty healthy subjects participated in the experiment and 44 sneezes were measured by using a laser particle size analyser. Two types of distributions are observed: unimodal and bimodal. For each sneeze, the droplets exhaled at different time in the sneeze duration have the same distribution characteristics with good time stability. The volume-based size distributions of sneeze droplets can be represented by a lognormal distribution function, and the relationship between the distribution parameters and the physiological characteristics of the subjects are studied by using linear regression analysis. The geometric mean of the droplet size of all the subjects is 360.1 µm for unimodal distribution and 74.4 µm for bimodal distribution with geometric standard deviations of 1.5 and 1.7, respectively. For the two peaks of the bimodal distribution, the geometric mean (the geometric standard deviation) is 386.2 µm (1.8) for peak 1 and 72.0 µm (1.5) for peak 2. The influences of the measurement method, the limitations of the instrument, the evaporation effects of the droplets, the differences of biological dynamic mechanism and characteristics between sneeze and other respiratory activities are also discussed. PMID:24026469

  20. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ahadi, S., E-mail: su4idi@yahoo.com; Puspito, N. T.; Ibrahim, G.

    Determination of onset time precursors of strong earthquakes (Mw > 5) and distance (d < 500 km) using geomagnetic data from Geomagnetic station KTB, Sumatra and two station references DAV, Philippine and DAW, Australia. separate techniques are required in its determination. Not the same as that recorded in the kinetic wave seismograms can be determined by direct time domain. Difficulties associated with electromagnetic waves seismogenic activities require analysis of the transformed signal in the frequency domain. Determination of the frequency spectrum will determine the frequency of emissions emitted from the earthquake source. The aim is to analyze the power amplitudemore » of the ULF emissions in the horizontal component (H) and vertical component (Z). Polarization power ratio Z/H is used for determining the sign of earthquake precursors controlled by the standard deviation. The pattern recognition polarization ratio should be obtained which can differentiate emissions from seismogenic effects of geomagnetic activity. ULF emission patterns generated that seismogenic effect has duration > 5 days and the dominance of emission intensity recorded at the Z component and for the dominance of the emission intensity of geomagnetic activity recorded in the component H. The result shows that the onset time is determined when the polarization power ratio Z/H standard deviation over the limit (p ± 2 σ) which has a duration of > 5 days.« less

  1. Graphene oxide decorated with silver nanoparticles as a coating on a stainless-steel fiber for solid-phase microextraction.

    PubMed

    Wang, Licheng; Hou, Xiudan; Li, Jubai; Liu, Shujuan; Guo, Yong

    2015-07-01

    A novel graphene oxide decorated with silver nanoparticles coating on a stainless-steel fiber for solid-phase microextraction was prepared. Scanning electron microscopy and X-ray photoelectron spectroscopy were used to characterize the coating surface and showed that silver nanoparticles were dispersed on the wrinkled graphene oxide surface. Coupled to gas chromatography with flame ionization detection, the extraction abilities of the fiber for polycyclic aromatic hydrocarbons were examined in the headspace solid-phase microextraction mode. The extraction parameters including adsorption time, adsorption temperature, salt concentration, desorption time and desorption temperature were investigated. Under the optimized condition, wide linearity with low limits of detection from 2 to 10 ng/L was obtained. The relative standard deviations for single-fiber repeatability and fiber-to-fiber reproducibility were less than 10.6 and 17.5%, respectively. The enrichment factors were from 1712.5 to 4503.7, showing the fiber has good extraction abilities. Moreover, the fiber exhibited a good stability and could be reused for more than 120 times. The established method was also applied for determination of polycyclic aromatic hydrocarbons in two real water samples and the recoveries of analytes ranged from 84.4-116.3% with relative standard deviations less than 16.2%. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Determination of alkylphenols and alkylphenol mono- and diethoxylates in environmental samples by high-performance liquid chromatography

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ahel, M.; Giger, W.

    1985-07-01

    A routine method is described for the quantitative determination of 4-nonylphenol (NP) and 4-nonylphenol mono-(NP1EO) and diethoxylate (NP2EO) in samples from wastewater and sludge treatment and from the aquatic environment. An exhaustive steam-distillation/solvent-extraction procedure was employed to enrich the analytes from aqueous and solid samples. Quantitative determinations were performed by normal-phase high-performance liquid chromatography (HP-LC) using aminosilica columns. Relative standard deviations were 3.0-4.4% in a river water containing 3.9 ..mu..g/L NP, 23.4 ..mu..g/L NP1EO, and 9.4 ..mu..g/L NP2EO. A digested sewage sludge with 1.6 g of NP/kg of dry matter was analyzed with a relative standard deviation of 3.7%. Recoveriesmore » were higher than 80%, and the estimated detection limit in water samples was 0.5 ..mu..g/L. Reversed-phase HPLC on octylsilica provided complementary qualitative data, particularly on homologous alkylphenolic compounds. Good agreement was found between quantitative determinations by HPLC and by high-resolution gas chromatography with flame ionization detection and directly coupled mass spectrometry. Municipal wastewater effluents, sewage sludges, and natural waters were analyzed to demonstrate the method's broad applicability. 19 references, 4 tables, 4 figures.« less

  3. An improved analytical strategy combining microextraction by packed sorbent combined with ultra high pressure liquid chromatography for the determination of fluoxetine, clomipramine and their active metabolites in human urine.

    PubMed

    Alves, Vera; Gonçalves, João; Conceição, Carlota; Teixeira, Helena M; Câmara, José S

    2015-08-21

    A powerful and sensitive method, by microextraction packed sorbent (MEPS), and ultra-high performance liquid chromatography (UHPLC) with a photodiode array (PDA) detection, is described for the determination of fluoxetine, clomipramine and their active metabolites in human urine samples. The MEPS variables, such as sample volume, pH, number of extraction cycles (draw-eject), and desorption conditions (solvent and solvent volume of elution) were optimized. The analysis were carried out using small sample volumes (500μL) and in a short time period (5min for the entire sample preparation step). Good linearity was obtained for all antidepressants with the correlation coefficients (R(2)) above 0.9965. The limits of detection (LOD) ranged from 0.068 to 0.087μgmL(-1). The recoveries were from 93% to 98%, with relative standard deviations less than 6%. The inter-day precision, expressed as the relative standard deviation, varied between 3.8% and 8.5% while the intra-day precision between 3.0% and 7.1%. In order to evaluate the proposed method for clinical use, the MEPS/UHPLC-PDA method was applied to analysis of urine samples from depressed patients. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. An analysis of the precision and reliability of the leap motion sensor and its suitability for static and dynamic tracking.

    PubMed

    Guna, Jože; Jakus, Grega; Pogačnik, Matevž; Tomažič, Sašo; Sodnik, Jaka

    2014-02-21

    We present the results of an evaluation of the performance of the Leap Motion Controller with the aid of a professional, high-precision, fast motion tracking system. A set of static and dynamic measurements was performed with different numbers of tracking objects and configurations. For the static measurements, a plastic arm model simulating a human arm was used. A set of 37 reference locations was selected to cover the controller's sensory space. For the dynamic measurements, a special V-shaped tool, consisting of two tracking objects maintaining a constant distance between them, was created to simulate two human fingers. In the static scenario, the standard deviation was less than 0.5 mm. The linear correlation revealed a significant increase in the standard deviation when moving away from the controller. The results of the dynamic scenario revealed the inconsistent performance of the controller, with a significant drop in accuracy for samples taken more than 250 mm above the controller's surface. The Leap Motion Controller undoubtedly represents a revolutionary input device for gesture-based human-computer interaction; however, due to its rather limited sensory space and inconsistent sampling frequency, in its current configuration it cannot currently be used as a professional tracking system.

  5. An Analysis of the Precision and Reliability of the Leap Motion Sensor and Its Suitability for Static and Dynamic Tracking

    PubMed Central

    Guna, Jože; Jakus, Grega; Pogačnik, Matevž; Tomažič, Sašo; Sodnik, Jaka

    2014-01-01

    We present the results of an evaluation of the performance of the Leap Motion Controller with the aid of a professional, high-precision, fast motion tracking system. A set of static and dynamic measurements was performed with different numbers of tracking objects and configurations. For the static measurements, a plastic arm model simulating a human arm was used. A set of 37 reference locations was selected to cover the controller's sensory space. For the dynamic measurements, a special V-shaped tool, consisting of two tracking objects maintaining a constant distance between them, was created to simulate two human fingers. In the static scenario, the standard deviation was less than 0.5 mm. The linear correlation revealed a significant increase in the standard deviation when moving away from the controller. The results of the dynamic scenario revealed the inconsistent performance of the controller, with a significant drop in accuracy for samples taken more than 250 mm above the controller's surface. The Leap Motion Controller undoubtedly represents a revolutionary input device for gesture-based human-computer interaction; however, due to its rather limited sensory space and inconsistent sampling frequency, in its current configuration it cannot currently be used as a professional tracking system. PMID:24566635

  6. Search for new high-mass phenomena in the dilepton final state using 36 fb-1 of proton-proton collision data at √{s}=13 TeV with the ATLAS detector

    NASA Astrophysics Data System (ADS)

    Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, Y. S.; Christodoulou, V.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'eramo, L.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vasconcelos Corga, K.; De Vivie De Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Bello, F. A.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dreyer, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falke, P. J.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giangiacomi, N.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugliarelli, G.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de la Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Grummer, A.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartmann, N. M.; Hasegawa, M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heer, S.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herr, H.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; Hildebrand, K.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hils, M.; Hinchliffe, I.; Hirose, M.; Hirschbuehl, D.; Hiti, B.; Hladik, O.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hrdinka, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Isacson, M. F.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, P.; Jacobs, R. M.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. J.; Jon-And, K.; Jones, R. W. L.; Jones, S. D.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kay, E. F.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kellermann, E.; Kempster, J. J.; Kendrick, J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khoda, E. E.; Khodinov, A.; Khoo, T. 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E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, DMS; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. 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G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; zur Nedden, M.; Zwalinski, L.

    2017-10-01

    A search is conducted for new resonant and non-resonant high-mass phenomena in dielectron and dimuon final states. The search uses 36.1 fb-1 of proton-proton collision data, collected at √{s}=13 TeV by the ATLAS experiment at the LHC in 2015 and 2016. No significant deviation from the Standard Model prediction is observed. Upper limits at 95% credibility level are set on the cross-section times branching ratio for resonances decaying into dileptons, which are converted to lower limits on the resonance mass, up to 4.1 TeV for the E6-motivated Z χ ' . Lower limits on the qqℓℓ contact interaction scale are set between 2.4 TeV and 40 TeV, depending on the model. [Figure not available: see fulltext.

  7. Search for new high-mass phenomena in the dilepton final state using 36 fb –1 of proton-proton collision data at $$ \\sqrt{s}=13 $$ TeV with the ATLAS detector

    DOE PAGES

    Aaboud, M.; Aad, G.; Abbott, B.; ...

    2017-10-26

    A search is conducted for new resonant and non-resonant high-mass phenomena in dielectron and dimuon final states. The search uses 36.1 fb –1 of proton-proton collision data, collected at √s=13 TeV by the ATLAS experiment at the LHC in 2015 and 2016. No significant deviation from the Standard Model prediction is observed. Upper limits at 95% credibility level are set on the cross-section times branching ratio for resonances decaying into dileptons, which are converted to lower limits on the resonance mass, up to 4.1 TeV for the E6-motivated Z χ'. As a result, lower limits on the qqℓℓ contact interactionmore » scale are set between 2.4 TeV and 40 TeV, depending on the model.« less

  8. [Comparative quality measurements part 3: funnel plots].

    PubMed

    Kottner, Jan; Lahmann, Nils

    2014-02-01

    Comparative quality measurements between organisations or institutions are common. Quality measures need to be standardised and risk adjusted. Random error must also be taken adequately into account. Rankings without consideration of the precision lead to flawed interpretations and enhances "gaming". Application of confidence intervals is one possibility to take chance variation into account. Funnel plots are modified control charts based on Statistical Process Control (SPC) theory. The quality measures are plotted against their sample size. Warning and control limits that are 2 or 3 standard deviations from the center line are added. With increasing group size the precision increases and so the control limits are forming a funnel. Data points within the control limits are considered to show common cause variation; data points outside special cause variation without the focus of spurious rankings. Funnel plots offer data based information about how to evaluate institutional performance within quality management contexts.

  9. Search for Higgs boson pair production in the γγbb[over ¯] final state using pp collision data at sqrt[s]=8  TeV from the ATLAS detector.

    PubMed

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    2015-02-27

    Searches are performed for resonant and nonresonant Higgs boson pair production in the γγbb[over ¯] final state using 20  fb^{-1} of proton-proton collisions at a center-of-mass energy of 8 TeV recorded with the ATLAS detector at the CERN Large Hadron Collider. A 95% confidence level upper limit on the cross section times branching ratio of nonresonant production is set at 2.2 pb, while the expected limit is 1.0 pb. The difference derives from a modest excess of events, corresponding to 2.4 standard deviations from the background-only hypothesis. The limit observed in the search for a narrow X→hh resonance ranges between 0.7 and 3.5 pb as a function of the resonance mass.

  10. Validation of standard method EN ISO 11290-part 2 for the enumeration of Listeria monocytogenes in food.

    PubMed

    Rollier, Patricia; Lombard, Bertrand; Guillier, Laurent; François, Danièle; Romero, Karol; Pierru, Sylvie; Bouhier, Laurence; Gnanou Besse, Nathalie

    2018-05-01

    The reference method for the detection and enumeration of L. monocytogenes in food (Standards EN ISO 11290-1&2) have been validated by inter-laboratory studies in the frame of the Mandate M381 from European Commission to CEN. In this paper, the inter-laboratory studies led in 2013 on 5 matrices (cold-smoked salmon, milk powdered infant food formula, vegetables, environment, and cheese) to validate Standard EN ISO 11290-2 are reported. According to the results obtained, the method of the revised Standard EN ISO 11290-2 can be considered as a good method for the enumeration of L. monocytogenes in foods and food processing environment, in particular for the matrices included in the study. Values of repeatability and reproducibility standard deviations can be considered satisfactory for this type of method with a confirmation stage, since most of them were below 0.3 log 10 , also at low levels, close to the regulatory limit of 100 CFU/g. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. Probability Distribution Estimated From the Minimum, Maximum, and Most Likely Values: Applied to Turbine Inlet Temperature Uncertainty

    NASA Technical Reports Server (NTRS)

    Holland, Frederic A., Jr.

    2004-01-01

    Modern engineering design practices are tending more toward the treatment of design parameters as random variables as opposed to fixed, or deterministic, values. The probabilistic design approach attempts to account for the uncertainty in design parameters by representing them as a distribution of values rather than as a single value. The motivations for this effort include preventing excessive overdesign as well as assessing and assuring reliability, both of which are important for aerospace applications. However, the determination of the probability distribution is a fundamental problem in reliability analysis. A random variable is often defined by the parameters of the theoretical distribution function that gives the best fit to experimental data. In many cases the distribution must be assumed from very limited information or data. Often the types of information that are available or reasonably estimated are the minimum, maximum, and most likely values of the design parameter. For these situations the beta distribution model is very convenient because the parameters that define the distribution can be easily determined from these three pieces of information. Widely used in the field of operations research, the beta model is very flexible and is also useful for estimating the mean and standard deviation of a random variable given only the aforementioned three values. However, an assumption is required to determine the four parameters of the beta distribution from only these three pieces of information (some of the more common distributions, like the normal, lognormal, gamma, and Weibull distributions, have two or three parameters). The conventional method assumes that the standard deviation is a certain fraction of the range. The beta parameters are then determined by solving a set of equations simultaneously. A new method developed in-house at the NASA Glenn Research Center assumes a value for one of the beta shape parameters based on an analogy with the normal distribution (ref.1). This new approach allows for a very simple and direct algebraic solution without restricting the standard deviation. The beta parameters obtained by the new method are comparable to the conventional method (and identical when the distribution is symmetrical). However, the proposed method generally produces a less peaked distribution with a slightly larger standard deviation (up to 7 percent) than the conventional method in cases where the distribution is asymmetric or skewed. The beta distribution model has now been implemented into the Fast Probability Integration (FPI) module used in the NESSUS computer code for probabilistic analyses of structures (ref. 2).

  12. Lorentz Symmetry Violations from Matter-Gravity Couplings with Lunar Laser Ranging

    NASA Astrophysics Data System (ADS)

    Bourgoin, A.; Le Poncin-Lafitte, C.; Hees, A.; Bouquillon, S.; Francou, G.; Angonin, M.-C.

    2017-11-01

    The standard-model extension (SME) is an effective field theory framework aiming at parametrizing any violation to the Lorentz symmetry (LS) in all sectors of physics. In this Letter, we report the first direct experimental measurement of SME coefficients performed simultaneously within two sectors of the SME framework using lunar laser ranging observations. We consider the pure gravitational sector and the classical point-mass limit in the matter sector of the minimal SME. We report no deviation from general relativity and put new realistic stringent constraints on LS violations improving up to 3 orders of magnitude previous estimations.

  13. The muon g - 2 for low-mass pseudoscalar Higgs in the general 2HDM

    NASA Astrophysics Data System (ADS)

    Cherchiglia, Adriano; Stöckinger, Dominik; Stöckinger-Kim, Hyejung

    2018-05-01

    The two-Higgs doublet model is a simple and attractive extension of the Standard Model. It provides a possibility to explain the large deviation between theory and experiment in the muon g - 2 in an interesting parameter region: light pseudoscalar Higgs A, large Yukawa coupling to τ-leptons, and general, non-type II Yukawa couplings are preferred. This parameter region is explored, experimental limits on the relevant Yukawa couplings are obtained, and the maximum possible contributions to the muon g - 2 are discussed. Presented at Workshop on Flavour Changing and Conserving Processes (FCCP2017), September 2017

  14. Establishing Quantitative Within-Subject Confidence Limits For Clinical Stereoroentgenographs

    NASA Astrophysics Data System (ADS)

    Korn, Edward L.; Baumrind, Sheldon; Chafetz, Neil; Curry, Sean; Moffitt, Francis

    1983-07-01

    It is now quite clear that under ideal conditions, discrete points can be located on x-ray films with standard deviations of less than 50 i. However, under routine clinical conditions, such considerations as individual variation in anatomy, movement of the subject between exposures, and variations in image quality combine to produce considerable reductions in the confidence which can be placed in quantitative assessments made from stereoroentgenographic films. This paper discusses some considerations involved in designing mathematical models in such a way as to optimize the use of imperfect data in answering specific clinical questions.

  15. Retention Indices for Frequently Reported Compounds of Plant Essential Oils

    NASA Astrophysics Data System (ADS)

    Babushok, V. I.; Linstrom, P. J.; Zenkevich, I. G.

    2011-12-01

    Gas chromatographic retention indices were evaluated for 505 frequently reported plant essential oil components using a large retention index database. Retention data are presented for three types of commonly used stationary phases: dimethyl silicone (nonpolar), dimethyl silicone with 5% phenyl groups (slightly polar), and polyethylene glycol (polar) stationary phases. The evaluations are based on the treatment of multiple measurements with the number of data records ranging from about 5 to 800 per compound. Data analysis was limited to temperature programmed conditions. The data reported include the average and median values of retention index with standard deviations and confidence intervals.

  16. Real-time failure control (SAFD)

    NASA Technical Reports Server (NTRS)

    Panossian, Hagop V.; Kemp, Victoria R.; Eckerling, Sherry J.

    1990-01-01

    The Real Time Failure Control program involves development of a failure detection algorithm, referred as System for Failure and Anomaly Detection (SAFD), for the Space Shuttle Main Engine (SSME). This failure detection approach is signal-based and it entails monitoring SSME measurement signals based on predetermined and computed mean values and standard deviations. Twenty four engine measurements are included in the algorithm and provisions are made to add more parameters if needed. Six major sections of research are presented: (1) SAFD algorithm development; (2) SAFD simulations; (3) Digital Transient Model failure simulation; (4) closed-loop simulation; (5) SAFD current limitations; and (6) enhancements planned for.

  17. Validation and Recommendation of Methods to Measure Biogas Production Potential of Animal Manure

    PubMed Central

    Pham, C. H.; Triolo, J. M.; Cu, T. T. T.; Pedersen, L.; Sommer, S. G.

    2013-01-01

    In developing countries, biogas energy production is seen as a technology that can provide clean energy in poor regions and reduce pollution caused by animal manure. Laboratories in these countries have little access to advanced gas measuring equipment, which may limit research aimed at improving local adapted biogas production. They may also be unable to produce valid estimates of an international standard that can be used for articles published in international peer-reviewed science journals. This study tested and validated methods for measuring total biogas and methane (CH4) production using batch fermentation and for characterizing the biomass. The biochemical methane potential (BMP) (CH4 NL kg−1 VS) of pig manure, cow manure and cellulose determined with the Moller and VDI methods was not significantly different in this test (p>0.05). The biodegradability using a ratio of BMP and theoretical BMP (TBMP) was slightly higher using the Hansen method, but differences were not significant. Degradation rate assessed by methane formation rate showed wide variation within the batch method tested. The first-order kinetics constant k for the cumulative methane production curve was highest when two animal manures were fermented using the VDI 4630 method, indicating that this method was able to reach steady conditions in a shorter time, reducing fermentation duration. In precision tests, the repeatability of the relative standard deviation (RSDr) for all batch methods was very low (4.8 to 8.1%), while the reproducibility of the relative standard deviation (RSDR) varied widely, from 7.3 to 19.8%. In determination of biomethane concentration, the values obtained using the liquid replacement method (LRM) were comparable to those obtained using gas chromatography (GC). This indicates that the LRM method could be used to determine biomethane concentration in biogas in laboratories with limited access to GC. PMID:25049861

  18. In vivo dosimetry for external photon treatments of head and neck cancers by diodes and TLDS.

    PubMed

    Tung, C J; Wang, H C; Lo, S H; Wu, J M; Wang, C J

    2004-01-01

    In vivo dosimetry was implemented for treatments of head and neck cancers in the large fields. Diode and thermoluminescence dosemeter (TLD) measurements were carried out for the linear accelerators of 6 MV photon beams. ESTRO in vivo dosimetry protocols were followed in the determination of midline doses from measurements of entrance and exit doses. Of the fields monitored by diodes, the maximum absolute deviation of measured midline doses from planned target doses was 8%, with the mean value and the standard deviation of -1.0 and 2.7%. If planned target doses were calculated using radiological water equivalent thicknesses rather than patient geometric thicknesses, the maximum absolute deviation dropped to 4%, with the mean and the standard deviation of 0.7 and 1.8%. For in vivo dosimetry monitored by TLDs, the shift in mean dose remained small but the statistical precision became poor.

  19. A visual tristimulus projection colorimeter.

    PubMed

    Valberg, A

    1971-01-01

    Based on the optical principle of a slide projector, a visual tristimulus projection colorimeter has been developed. The calorimeter operates with easily interchangeable sets of primary color filters placed in a frame at the objective. The apparatus has proved to be fairly accurate. The reproduction of the color matches as measured by the standard deviation is equal to the visual sensitivity to color differences for each observer. Examples of deviations in the matches among individuals as well as deviations compared with the CIE 1931 Standard Observer are given. These deviations are demonstrated to be solely due to individual differences in the perception of metameric colors. Thus, taking advantage of an objective observation (allowing all adjustments to be judged by a group of impartial observers), the colorimeter provides an excellent aid in the study of discrimination, metamerism, and related effects which are of considerable interest in current research in colorimetry and in the study of color vision tests.

  20. Middle school transition and body weight outcomes: Evidence from Arkansas Public Schoolchildren.

    PubMed

    Zeng, Di; Thomsen, Michael R; Nayga, Rodolfo M; Rouse, Heather L

    2016-05-01

    There is evidence that middle school transition adversely affects educational and psychological outcomes of pre-teen children, but little is known about the impacts of middle school transition on other aspects of health. In this article, we estimate the impact of middle school transition on the body mass index (BMI) of public schoolchildren in Arkansas, United States. Using an instrumental variable approach, we find that middle school transition in grade 6 led to a moderate decrease of 0.04 standard deviations in BMI z-scores for all students. Analysis by subsample indicated that this result was driven by boys (0.06-0.07 standard deviations) and especially by non-minority boys (0.09 standard deviations). We speculate that the changing levels of physical activities associated with middle school transition provide the most reasonable explanation for this result. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Estimating active layer thickness and volumetric water content from ground penetrating radar measurements in Barrow, Alaska

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jafarov, E. E.; Parsekian, A. D.; Schaefer, K.

    Ground penetrating radar (GPR) has emerged as an effective tool for estimating active layer thickness (ALT) and volumetric water content (VWC) within the active layer. In August 2013, we conducted a series of GPR and probing surveys using a 500 MHz antenna and metallic probe around Barrow, Alaska. Here, we collected about 15 km of GPR data and 1.5 km of probing data. We describe the GPR data processing workflow from raw GPR data to the estimated ALT and VWC. We then include the corresponding uncertainties for each measured and estimated parameter. The estimated average GPR-derived ALT was 41 cm,more » with a standard deviation of 9 cm. The average probed ALT was 40 cm, with a standard deviation of 12 cm. The average GPR-derived VWC was 0.65, with a standard deviation of 0.14.« less

  2. Migration in the shearing sheet and estimates for young open cluster migration

    NASA Astrophysics Data System (ADS)

    Quillen, Alice C.; Nolting, Eric; Minchev, Ivan; De Silva, Gayandhi; Chiappini, Cristina

    2018-04-01

    Using tracer particles embedded in self-gravitating shearing sheet N-body simulations, we investigate the distance in guiding centre radius that stars or star clusters can migrate in a few orbital periods. The standard deviations of guiding centre distributions and maximum migration distances depend on the Toomre or critical wavelength and the contrast in mass surface density caused by spiral structure. Comparison between our simulations and estimated guiding radii for a few young supersolar metallicity open clusters, including NGC 6583, suggests that the contrast in mass surface density in the solar neighbourhood has standard deviation (in the surface density distribution) divided by mean of about 1/4 and larger than measured using COBE data by Drimmel and Spergel. Our estimate is consistent with a standard deviation of ˜0.07 dex in the metallicities measured from high-quality spectroscopic data for 38 young open clusters (<1 Gyr) with mean galactocentric radius 7-9 kpc.

  3. Estimating active layer thickness and volumetric water content from ground penetrating radar measurements in Barrow, Alaska

    DOE PAGES

    Jafarov, E. E.; Parsekian, A. D.; Schaefer, K.; ...

    2018-01-09

    Ground penetrating radar (GPR) has emerged as an effective tool for estimating active layer thickness (ALT) and volumetric water content (VWC) within the active layer. In August 2013, we conducted a series of GPR and probing surveys using a 500 MHz antenna and metallic probe around Barrow, Alaska. Here, we collected about 15 km of GPR data and 1.5 km of probing data. We describe the GPR data processing workflow from raw GPR data to the estimated ALT and VWC. We then include the corresponding uncertainties for each measured and estimated parameter. The estimated average GPR-derived ALT was 41 cm,more » with a standard deviation of 9 cm. The average probed ALT was 40 cm, with a standard deviation of 12 cm. The average GPR-derived VWC was 0.65, with a standard deviation of 0.14.« less

  4. The Cost of Uncertain Life Span*

    PubMed Central

    Edwards, Ryan D.

    2012-01-01

    A considerable amount of uncertainty surrounds the length of human life. The standard deviation in adult life span is about 15 years in the U.S., and theory and evidence suggest it is costly. I calibrate a utility-theoretic model of preferences over length of life and show that one fewer year in standard deviation is worth about half a mean life year. Differences in the standard deviation exacerbate cross-sectional differences in life expectancy between the U.S. and other industrialized countries, between rich and poor countries, and among poor countries. Accounting for the cost of life-span variance also appears to amplify recently discovered patterns of convergence in world average human well-being. This is partly for methodological reasons and partly because unconditional variance in human length of life, primarily the component due to infant mortality, has exhibited even more convergence than life expectancy. PMID:22368324

  5. On the linear relation between the mean and the standard deviation of a response time distribution.

    PubMed

    Wagenmakers, Eric-Jan; Brown, Scott

    2007-07-01

    Although it is generally accepted that the spread of a response time (RT) distribution increases with the mean, the precise nature of this relation remains relatively unexplored. The authors show that in several descriptive RT distributions, the standard deviation increases linearly with the mean. Results from a wide range of tasks from different experimental paradigms support a linear relation between RT mean and RT standard deviation. Both R. Ratcliff's (1978) diffusion model and G. D. Logan's (1988) instance theory of automatization provide explanations for this linear relation. The authors identify and discuss 3 specific boundary conditions for the linear law to hold. The law constrains RT models and supports the use of the coefficient of variation to (a) compare variability while controlling for differences in baseline speed of processing and (b) assess whether changes in performance with practice are due to quantitative speedup or qualitative reorganization. Copyright 2007 APA.

  6. Determination of the optimal level for combining area and yield estimates

    NASA Technical Reports Server (NTRS)

    Bauer, M. E. (Principal Investigator); Hixson, M. M.; Jobusch, C. D.

    1981-01-01

    Several levels of obtaining both area and yield estimates of corn and soybeans in Iowa were considered: county, refined strata, refined/split strata, crop reporting district, and state. Using the CCEA model form and smoothed weather data, regression coefficients at each level were derived to compute yield and its variance. Variances were also computed with stratum level. The variance of the yield estimates was largest at the state and smallest at the county level for both crops. The refined strata had somewhat larger variances than those associated with the refined/split strata and CRD. For production estimates, the difference in standard deviations among levels was not large for corn, but for soybeans the standard deviation at the state level was more than 50% greater than for the other levels. The refined strata had the smallest standard deviations. The county level was not considered in evaluation of production estimates due to lack of county area variances.

  7. Quantifying relative importance: Computing standardized effects in models with binary outcomes

    USGS Publications Warehouse

    Grace, James B.; Johnson, Darren; Lefcheck, Jonathan S.; Byrnes, Jarrett E.K.

    2018-01-01

    Results from simulation studies show that both the LT and OE methods of standardization support a similarly-broad range of coefficient comparisons. The LT method estimates effects that reflect underlying latent-linear propensities, while the OE method computes a linear approximation for the effects of predictors on binary responses. The contrast between assumptions for the two methods is reflected in persistently weaker standardized effects associated with OE standardization. Reliance on standard deviations for standardization (the traditional approach) is critically examined and shown to introduce substantial biases when predictors are non-Gaussian. The use of relevant ranges in place of standard deviations has the capacity to place LT and OE standardized coefficients on a more comparable scale. As ecologists address increasingly complex hypotheses, especially those that involve comparing the influences of different controlling factors (e.g., top-down versus bottom-up or biotic versus abiotic controls), comparable coefficients become a necessary component for evaluations.

  8. Search for physics beyond the standard model in dilepton mass spectra in proton-proton collisions at TeV

    NASA Astrophysics Data System (ADS)

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Luyckx, S.; Ochesanu, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Mora Herrera, C.; Pol, M. E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santaolalla, J.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Aleksandrov, A.; Genchev, V.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Tao, J.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Zou, W.; Avila, C.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Busson, P.; Charlot, C.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Mastrolorenzo, L.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Veelken, C.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Chabert, E. C.; Collard, C.; Conte, E.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Boudoul, G.; Bouvier, E.; Brochet, S.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Bontenackels, M.; Edelhoff, M.; Feld, L.; Hindrichs, O.; Klein, K.; Ostapchuk, A.; Perieanu, A.; Raupach, F.; Sammet, J.; Schael, S.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Erdmann, M.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Pook, T.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Weber, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Heister, A.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Perchalla, L.; Pooth, O.; Stahl, A.; Asin, I.; Bartosik, N.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bell, A. J.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garay Garcia, J.; Geiser, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Horton, D.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Krücker, D.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Novgorodova, O.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Pietsch, N.; Poehlsen, J.; Poehlsen, T.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Kuznetsova, E.; Lobelle Pardo, P.; Mozer, M. U.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Röcker, S.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; Kumar, R.; Mittal, M.; Nishu, N.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. 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S.; Colaleo, A.; Creanza, D.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Zito, G.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. 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M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Dosselli, U.; Galanti, M.; Gasparini, F.; Gasparini, U.; Giubilato, P.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fiori, F.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Moon, C. S.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Vernieri, C.; Barone, L.; Cavallari, F.; D'imperio, G.; Del Re, D.; Diemoz, M.; Grassi, M.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Soffi, L.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Casasso, S.; Costa, M.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; Ortona, G.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Potenza, A.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Tamponi, U.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Park, H.; Sakharov, A.; Son, D. C.; Kim, T. J.; Kim, J. Y.; Song, S.; Choi, S.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K. S.; Park, S. K.; Roh, Y.; Yoo, H. D.; Choi, M.; Kim, J. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Ali, M. A. B. Md; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Casimiro Linares, E.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khalid, S.; Khan, W. A.; Khurshid, T.; Shah, M. A.; Shoaib, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Brona, G.; Bunkowski, K.; Cwiok, M.; Dominik, W.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Wolszczak, W.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Lloret Iglesias, L.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Varela, J.; Vischia, P.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Konoplyanikov, V.; Kozlov, G.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Vorobyev, An.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Safronov, G.; Semenov, S.; Spiridonov, A.; Stolin, V.; Vlasov, E.; Zhokin, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Perfilov, M.; Savrin, V.; Snigirev, A.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. 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I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chang, Y. 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I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; John, J. St.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Nguyen, H.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Andrews, W.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Evans, D.; Holzner, A.; Kelley, R.; Klein, D.; Lebourgeois, M.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. 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M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kaadze, K.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Cheng, T.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Sakuma, T.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Vuosalo, C.; Woods, N.

    2015-04-01

    Dimuon and dielectron mass spectra, obtained from data resulting from proton-proton collisions at 8 TeV and recorded by the CMS experiment, are used to search for both narrow resonances and broad deviations from standard model predictions. The data correspond to an integrated luminosity of 20.6 (19.7) fb-1 for the dimuon (dielectron) channel. No evidence for non-standard-model physics is observed and 95% confidence level limits are set on parameters from a number of new physics models. The narrow resonance analyses exclude a Sequential Standard Model Z{SSM/'} resonance lighter than 2.90 TeV, a superstring-inspired Z{/ψ '} lighter than 2.57 TeV, and Randall-Sundrum Kaluza-Klein gravitons with masses below 2.73, 2.35, and 1.27 TeV for couplings of 0.10, 0.05, and 0.01, respectively. A notable feature is that the limits have been calculated in a model-independent way to enable straightforward reinterpretation in any model predicting a resonance structure. The observed events are also interpreted within the framework of two non-resonant analyses: one based on a large extra dimensions model and one based on a quark and lepton compositeness model with a left-left isoscalar contact interaction. Lower limits are established on MS, the scale characterizing the onset of quantum gravity, which range from 4.9 to 3.3 TeV, where the number of additional spatial dimensions varies from 3 to 7. Similarly, lower limits on Λ, the energy scale parameter for the contact interaction, are found to be 12.0 (15.2) TeV for destructive (constructive) interference in the dimuon channel and 13.5 (18.3) TeV in the dielectron channel. [Figure not available: see fulltext.

  9. Search for physics beyond the standard model in dilepton mass spectra in proton-proton collisions at √s = 8 TeV

    DOE PAGES

    Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; ...

    2015-04-07

    Dimuon and dielectron mass spectra, obtained from data resulting from proton-proton collisions at 8 TeV and recorded by the CMS experiment, are used to search for both narrow resonances and broad deviations from standard model predictions. The data correspond to an integrated luminosity of 20.6 (19.7) fb –1 for the dimuon (dielectron) channel. No evidence for non-standard-model physics is observed and 95% confidence level limits are set on parameters from a number of new physics models. The narrow resonance analyses exclude a Sequential Standard Model Z SSM ' resonance lighter than 2.90 TeV, a superstring-inspired Z ψ ' lighter thanmore » 2.57 TeV, and Randall-Sundrum Kaluza-Klein gravitons with masses below 2.73, 2.35, and 1.27 TeV for couplings of 0.10, 0.05, and 0.01, respectively. A notable feature is that the limits have been calculated in a model-independent way to enable straightforward reinterpretation in any model predicting a resonance structure. The observed events are also interpreted within the framework of two non-resonant analyses: one based on a large extra dimensions model and one based on a quark and lepton compositeness model with a left-left isoscalar contact interaction. Lower limits are established on MS, the scale characterizing the onset of quantum gravity, which range from 4.9 to 3.3 TeV, where the number of additional spatial dimensions varies from 3 to 7. Thus lower limits on Λ, the energy scale parameter for the contact interaction, are found to be 12.0 (15.2) TeV for destructive (constructive) interference in the dimuon channel and 13.5 (18.3) TeV in the dielectron channel.« less

  10. Defining relative humidity in terms of water activity. Part 1: definition

    NASA Astrophysics Data System (ADS)

    Feistel, Rainer; Lovell-Smith, Jeremy W.

    2017-08-01

    Relative humidity (RH) is a quantity widely used in various fields such as metrology, meteorology, climatology or engineering. However, RH is neither uniformly defined, nor do some definitions properly account for deviations from ideal-gas properties, nor is the application range of interest fully covered. In this paper, a new full-range definition of RH is proposed that is based on the thermodynamics of activities in order to include deviations from ideal-gas behaviour. Below the critical point of pure water, at pressures p  <  22.064 MPa and temperatures T  <  647.096 K, RH is rigorously defined as the relative activity (or relative fugacity) of water in humid air. For this purpose, reference states of the relative activity are specified appropriately. Asymptotically, the ideal-gas limit of the new definition is consistent with de-facto standard RH definitions published previously and recommended internationally. Virial approximations are reported for estimating small corrections to the ideal-gas equations.

  11. Polarimetric measures of selected variable stars

    NASA Astrophysics Data System (ADS)

    Elias, N. M., II; Koch, R. H.; Pfeiffer, R. J.

    2008-10-01

    Aims: The purpose of this paper is to summarize and interpret unpublished optical polarimetry for numerous program stars that were observed over the past decades at the Flower and Cook Observatory (FCO), University of Pennsylvania. We also make the individual calibrated measures available for long-term comparisons with new data. Methods: We employ three techniques to search for intrinsic variability within each dataset. First, when the observations for a given star and filter are numerous enough and when a period has been determined previously via photometry or spectroscopy, the polarimetric measures are plotted versus phase. If a statistically significant pattern appears, we attribute it to intrinsic variability. Second, we compare means of the FCO data to means from other workers. If they are statistically different, we conclude that the object exhibits long-term intrinsic variability. Third, we calculate the standard deviation for each program star and filter and compare it to the standard deviation estimated from comparable polarimetric standards. If the standard deviation of the program star is at least three times the value estimated from the polarimetric standards, the former is considered intrinsically variable. All of these statements are strengthened when variability appears in multiple filters. Results: We confirm the existence of an electron-scattering cloud at L1 in the β Per system, and find that LY Aur and HR 8281 possess scattering envelopes. Intrinsic polarization was detected for Nova Cas 1993 as early as day +3. We detected polarization variability near the primary eclipse of 32 Cyg. There is marginal evidence for polarization variability of the β Cepheid type star γ Peg. The other objects of this class exhibited no variability. All but one of the β Cepheid objects (ES Vul) fall on a tight linear relationship between linear polarization and E(B-V), in spite of the fact that the stars lay along different lines of sight. This dependence falls slightly below the classical upper limit of Serkowski, Mathewson, and Ford. The table, which contains the polarization observations of the program stars discussed in this paper, is only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/489/911

  12. Search for new phenomena in monophoton final states in proton–proton collisions at s = 8  TeV

    DOE PAGES

    Khachatryan, V.

    2016-02-01

    In this paper, results are presented from a search for new physics in final states containing a photon and missing transverse momentum. The data correspond to an integrated luminosity of 19.6 fb -1 collected in proton–proton collisions at √s = 8 TeV with the CMS experiment at the LHC. No deviation from the standard model predictions is observed for these final states. New, improved limits are set on dark matter production and on parameters of models with large extra dimensions. In particular, the first limits from the LHC on branon production are found and significantly extend previous limits from LEPmore » and the Tevatron. Finally, an upper limit of 14.0 fb on the cross section is set at the 95% confidence level for events with a monophoton final state with photon transverse momentum greater than 145 GeV and missing transverse momentum greater than 140 GeV.« less

  13. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Shekhar, R.; Karunasagar, D.; Ranjit, M.

    An open-to-air type electrolyte cathode discharge (ELCAD) has been developed with a new design. The present configuration leads to a stable plasma even at low flow rates (0.96 mL/min). Plasma fluctuations arising from the variations in the gap between solid anode and liquid cathode were eliminated by providing a V-groove to the liquid glass-capillary. Cathode (ground) connection is given to the solution at the V-groove itself. Interfaced to atomic emission spectrometry (AES), its analytical performance is evaluated. The optimized molarity of the solution is 0.2 M. The analytical response curves for Ca, Cu, Cd, Pb, Hg, Fe, and Zn demonstratedmore » good linearity. The limit of detections of Ca, Cu, Cd, Pb, Hg, Fe, and Zn are determined to be 17, 11, 5, 45, 15, 28, and 3 ng mL{sup -1}. At an integration time of 0.3 s, the relative standard deviation (RSD) values of the acid blank solutions are found to be less than 10% for the elements Ca, Cu, Cd, Hg, Fe, and Zn and 18% for Pb. The method is applied for the determination of the elemental constituents in different matrix materials such as tuna fish (IAEA-350), oyster tissue (NIST SRM 1566a), and coal fly ash (CFA SRM 1633b). The obtained results are in good agreement with the certified values. The accuracy is found to be between 7% and 0.6% for major to trace levels of constituent elements and the precision between 11% and 0.6%. For the injection of 100 {mu} L of 200 ng mL{sup -1} mercury solution at the flow rate of 0.8 mL/min, the flow injection studies resulted in the relative standard deviation (RSD) of 8%, concentration detection limit of 10 ng/mL, and mass detection limit of 1 ng for mercury.« less

  14. Method for estimating effects of unknown correlations in spectral irradiance data on uncertainties of spectrally integrated colorimetric quantities

    NASA Astrophysics Data System (ADS)

    Kärhä, Petri; Vaskuri, Anna; Mäntynen, Henrik; Mikkonen, Nikke; Ikonen, Erkki

    2017-08-01

    Spectral irradiance data are often used to calculate colorimetric properties, such as color coordinates and color temperatures of light sources by integration. The spectral data may contain unknown correlations that should be accounted for in the uncertainty estimation. We propose a new method for estimating uncertainties in such cases. The method goes through all possible scenarios of deviations using Monte Carlo analysis. Varying spectral error functions are produced by combining spectral base functions, and the distorted spectra are used to calculate the colorimetric quantities. Standard deviations of the colorimetric quantities at different scenarios give uncertainties assuming no correlations, uncertainties assuming full correlation, and uncertainties for an unfavorable case of unknown correlations, which turn out to be a significant source of uncertainty. With 1% standard uncertainty in spectral irradiance, the expanded uncertainty of the correlated color temperature of a source corresponding to the CIE Standard Illuminant A may reach as high as 37.2 K in unfavorable conditions, when calculations assuming full correlation give zero uncertainty, and calculations assuming no correlations yield the expanded uncertainties of 5.6 K and 12.1 K, with wavelength steps of 1 nm and 5 nm used in spectral integrations, respectively. We also show that there is an absolute limit of 60.2 K in the error of the correlated color temperature for Standard Illuminant A when assuming 1% standard uncertainty in the spectral irradiance. A comparison of our uncorrelated uncertainties with those obtained using analytical methods by other research groups shows good agreement. We re-estimated the uncertainties for the colorimetric properties of our 1 kW photometric standard lamps using the new method. The revised uncertainty of color temperature is a factor of 2.5 higher than the uncertainty assuming no correlations.

  15. Modeling the gas-phase thermochemistry of organosulfur compounds.

    PubMed

    Vandeputte, Aäron G; Sabbe, Maarten K; Reyniers, Marie-Françoise; Marin, Guy B

    2011-06-27

    Key to understanding the involvement of organosulfur compounds in a variety of radical chemistries, such as atmospheric chemistry, polymerization, pyrolysis, and so forth, is knowledge of their thermochemical properties. For organosulfur compounds and radicals, thermochemical data are, however, much less well documented than for hydrocarbons. The traditional recourse to the Benson group additivity method offers no solace since only a very limited number of group additivity values (GAVs) is available. In this work, CBS-QB3 calculations augmented with 1D hindered rotor corrections for 122 organosulfur compounds and 45 organosulfur radicals were used to derive 93 Benson group additivity values, 18 ring-strain corrections, 2 non-nearest-neighbor interactions, and 3 resonance corrections for standard enthalpies of formation, standard molar entropies, and heat capacities for organosulfur compounds and organosulfur radicals. The reported GAVs are consistent with previously reported GAVs for hydrocarbons and hydrocarbon radicals and include 77 contributions, among which 26 radical contributions, which, to the best of our knowledge, have not been reported before. The GAVs allow one to estimate the standard enthalpies of formation at 298 K, the standard entropies at 298 K, and standard heat capacities in the temperature range 300-1500 K for a large set of organosulfur compounds, that is, thiols, thioketons, polysulfides, alkylsulfides, thials, dithioates, and cyclic sulfur compounds. For a validation set of 26 organosulfur compounds, the mean absolute deviation between experimental and group additively modeled enthalpies of formation amounts to 1.9  kJ  mol(-1). For an additional set of 14 organosulfur compounds, it was shown that the mean absolute deviations between calculated and group additively modeled standard entropies and heat capacities are restricted to 4 and 2 J  mol(-1)  K(-1), respectively. As an alternative to Benson GAVs, 26 new hydrogen-bond increments are reported, which can also be useful for the prediction of radical thermochemistry. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Dosimetric verification of lung cancer treatment using the CBCTs estimated from limited-angle on-board projections.

    PubMed

    Zhang, You; Yin, Fang-Fang; Ren, Lei

    2015-08-01

    Lung cancer treatment is susceptible to treatment errors caused by interfractional anatomical and respirational variations of the patient. On-board treatment dose verification is especially critical for the lung stereotactic body radiation therapy due to its high fractional dose. This study investigates the feasibility of using cone-beam (CB)CT images estimated by a motion modeling and free-form deformation (MM-FD) technique for on-board dose verification. Both digital and physical phantom studies were performed. Various interfractional variations featuring patient motion pattern change, tumor size change, and tumor average position change were simulated from planning CT to on-board images. The doses calculated on the planning CT (planned doses), the on-board CBCT estimated by MM-FD (MM-FD doses), and the on-board CBCT reconstructed by the conventional Feldkamp-Davis-Kress (FDK) algorithm (FDK doses) were compared to the on-board dose calculated on the "gold-standard" on-board images (gold-standard doses). The absolute deviations of minimum dose (ΔDmin), maximum dose (ΔDmax), and mean dose (ΔDmean), and the absolute deviations of prescription dose coverage (ΔV100%) were evaluated for the planning target volume (PTV). In addition, 4D on-board treatment dose accumulations were performed using 4D-CBCT images estimated by MM-FD in the physical phantom study. The accumulated doses were compared to those measured using optically stimulated luminescence (OSL) detectors and radiochromic films. Compared with the planned doses and the FDK doses, the MM-FD doses matched much better with the gold-standard doses. For the digital phantom study, the average (± standard deviation) ΔDmin, ΔDmax, ΔDmean, and ΔV100% (values normalized by the prescription dose or the total PTV) between the planned and the gold-standard PTV doses were 32.9% (±28.6%), 3.0% (±2.9%), 3.8% (±4.0%), and 15.4% (±12.4%), respectively. The corresponding values of FDK PTV doses were 1.6% (±1.9%), 1.2% (±0.6%), 2.2% (±0.8%), and 17.4% (±15.3%), respectively. In contrast, the corresponding values of MM-FD PTV doses were 0.3% (±0.2%), 0.9% (±0.6%), 0.6% (±0.4%), and 1.0% (±0.8%), respectively. Similarly, for the physical phantom study, the average ΔDmin, ΔDmax, ΔDmean, and ΔV100% of planned PTV doses were 38.1% (±30.8%), 3.5% (±5.1%), 3.0% (±2.6%), and 8.8% (±8.0%), respectively. The corresponding values of FDK PTV doses were 5.8% (±4.5%), 1.6% (±1.6%), 2.0% (±0.9%), and 9.3% (±10.5%), respectively. In contrast, the corresponding values of MM-FD PTV doses were 0.4% (±0.8%), 0.8% (±1.0%), 0.5% (±0.4%), and 0.8% (±0.8%), respectively. For the 4D dose accumulation study, the average (± standard deviation) absolute dose deviation (normalized by local doses) between the accumulated doses and the OSL measured doses was 3.3% (±2.7%). The average gamma index (3%/3 mm) between the accumulated doses and the radiochromic film measured doses was 94.5% (±2.5%). MM-FD estimated 4D-CBCT enables accurate on-board dose calculation and accumulation for lung radiation therapy. It can potentially be valuable for treatment quality assessment and adaptive radiation therapy.

  17. The detection of problem analytes in a single proficiency test challenge in the absence of the Health Care Financing Administration rule violations.

    PubMed

    Cembrowski, G S; Hackney, J R; Carey, N

    1993-04-01

    The Clinical Laboratory Improvement Act of 1988 (CLIA 88) has dramatically changed proficiency testing (PT) practices having mandated (1) satisfactory PT for certain analytes as a condition of laboratory operation, (2) fixed PT limits for many of these "regulated" analytes, and (3) an increased number of PT specimens (n = 5) for each testing cycle. For many of these analytes, the fixed limits are much broader than the previously employed Standard Deviation Index (SDI) criteria. Paradoxically, there may be less incentive to identify and evaluate analytically significant outliers to improve the analytical process. Previously described "control rules" to evaluate these PT results are unworkable as they consider only two or three results. We used Monte Carlo simulations of Kodak Ektachem analyzers participating in PT to determine optimal control rules for the identification of PT results that are inconsistent with those from other laboratories using the same methods. The analysis of three representative analytes, potassium, creatine kinase, and iron was simulated with varying intrainstrument and interinstrument standard deviations (si and sg, respectively) obtained from the College of American Pathologists (Northfield, Ill) Quality Assurance Services data and Proficiency Test data, respectively. Analytical errors were simulated in each of the analytes and evaluated in terms of multiples of the interlaboratory SDI. Simple control rules for detecting systematic and random error were evaluated with power function graphs, graphs of probability of error detected vs magnitude of error. Based on the simulation results, we recommend screening all analytes for the occurrence of two or more observations exceeding the same +/- 1 SDI limit. For any analyte satisfying this condition, the mean of the observations should be calculated. For analytes with sg/si ratios between 1.0 and 1.5, a significant systematic error is signaled by the mean exceeding 1.0 SDI. Significant random error is signaled by one observation exceeding the +/- 3-SDI limit or the range of the observations exceeding 4 SDIs. For analytes with higher sg/si, significant systematic or random error is signaled by violation of the screening rule (having at least two observations exceeding the same +/- 1 SDI limit). Random error can also be signaled by one observation exceeding the +/- 1.5-SDI limit or the range of the observations exceeding 3 SDIs. We present a practical approach to the workup of apparent PT errors.

  18. Scanning laser polarimetry in eyes with exfoliation syndrome.

    PubMed

    Dimopoulos, Antonios T; Katsanos, Andreas; Mikropoulos, Dimitrios G; Giannopoulos, Theodoros; Empeslidis, Theodoros; Teus, Miguel A; Holló, Gábor; Konstas, Anastasios G P

    2013-01-01

    To compare retinal nerve fiber layer thickness (RNFLT) of normotensive eyes with exfoliation syndrome (XFS) and healthy eyes.
 Sixty-four consecutive individuals with XFS and normal office-time intraocular pressure (IOP) and 72 consecutive healthy controls were prospectively enrolled for a cross-sectional analysis in this hospital-based observational study. The GDx-VCC parameters (temporal-superior-nasal-inferior-temporal [TSNIT] average, superior average, inferior average, TSNIT standard deviation (SD), and nerve fiber indicator [NFI]) were compared between groups. Correlation between various clinical parameters and RNFLT parameters was investigated with Spearman coefficient. 
 The NFI, although within normal limits for both groups, was significantly greater in the XFS group compared to controls: the respective median and interquartile range (IQR) values were 25.1 (22.0-29.0) vs 15.0 (12.0-20.0), p<0.001. In the XFS group, all RNFLT values were significantly lower compared to controls (p<0.001). However, they were all within the normal clinical ranges for both groups: TSNIT average median (IQR): 52.8 (49.7-55.7) vs 56.0 (53.0-59.3) µm; superior average mean (SD): 62.3 (6.7) vs 68.8 (8.2) µm; inferior average mean (SD): 58.0 (7.2) vs 64.8 (7.7) µm, respectively. TSNIT SD was significantly lower in the XFS group, median (IQR): 18.1 (15.4-20.4) vs 21.0 (18.4-23.8), p<0.001. There was no systematic relationship between RNFLT and visual acuity, cup-to-disc ratio, IOP, central corneal thickness, Humphrey mean deviation, and pattern standard deviation in either group. 
 Compared to control eyes, polarimetry-determined RNFLT was lower in XFS eyes with normal IOP. Therefore, close monitoring of RNFLT may facilitate early identification of those XFS eyes that convert to exfoliative glaucoma.

  19. Appropriate threshold levels of cardiac beat-to-beat variation in semi-automatic analysis of equine ECG recordings.

    PubMed

    Flethøj, Mette; Kanters, Jørgen K; Pedersen, Philip J; Haugaard, Maria M; Carstensen, Helena; Olsen, Lisbeth H; Buhl, Rikke

    2016-11-28

    Although premature beats are a matter of concern in horses, the interpretation of equine ECG recordings is complicated by a lack of standardized analysis criteria and a limited knowledge of the normal beat-to-beat variation of equine cardiac rhythm. The purpose of this study was to determine the appropriate threshold levels of maximum acceptable deviation of RR intervals in equine ECG analysis, and to evaluate a novel two-step timing algorithm by quantifying the frequency of arrhythmias in a cohort of healthy adult endurance horses. Beat-to-beat variation differed considerably with heart rate (HR), and an adaptable model consisting of three different HR ranges with separate threshold levels of maximum acceptable RR deviation was consequently defined. For resting HRs <60 beats/min (bpm) the threshold level of RR deviation was set at 20%, for HRs in the intermediate range between 60 and 100 bpm the threshold was 10%, and for exercising HRs >100 bpm, the threshold level was 4%. Supraventricular premature beats represented the most prevalent arrhythmia category with varying frequencies in seven horses at rest (median 7, range 2-86) and six horses during exercise (median 2, range 1-24). Beat-to-beat variation of equine cardiac rhythm varies according to HR, and threshold levels in equine ECG analysis should be adjusted accordingly. Standardization of the analysis criteria will enable comparisons of studies and follow-up examinations of patients. A small number of supraventricular premature beats appears to be a normal finding in endurance horses. Further studies are required to validate the findings and determine the clinical significance of premature beats in horses.

  20. Ultrafast shock compression of an oxygen-balanced mixture of nitromethane and hydrogen peroxide.

    PubMed

    Armstrong, Michael R; Zaug, Joseph M; Grant, Christian D; Crowhurst, Jonathan C; Bastea, Sorin

    2014-08-14

    We apply ultrafast optical interferometry to measure the Hugoniot of an oxygen-balanced mixture of nitromethane and hydrogen peroxide (NM/HP) and compare with Hugoniot data for pure nitromethane (NM) and a 90% hydrogen peroxide/water mixture (HP), as well as theoretical predictions. We observe a 2.1% percent mean pairwise difference between the measured shockwave speed (at the measured piston speed) in unreacted NM/HP and the corresponding "universal" liquid Hugoniot, which is larger than the average standard deviation of our data, 1.4%. Unlike the Hugoniots of both HP and NM, in which measured shock speeds deviate to values greater than the unreacted Hugoniot for piston speeds larger than the respective reaction thresholds, in the NM/HP mixture we observe shock speed deviations to values lower than the unreacted Hugoniot well below the von Neumann pressure (≈28 GPa). Although the trend should reverse for high enough piston speeds, the initial behavior is unexpected. Possible explanations range from mixing effects to a complex index of refraction in the reacted solution. If this is indeed a signature of chemical initiation, it would suggest that the process may not be kinetically limited (on a ~100 ps time scale) between the initiation threshold and the von Neumann pressure.

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