Sample records for standard deviations based

  1. 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.

  2. 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.

  3. 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.

  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. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  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. 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.

  19. 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…

  20. 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.

  1. 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."

  2. 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

  3. Multi-focus image fusion based on area-based standard deviation in dual tree contourlet transform domain

    NASA Astrophysics Data System (ADS)

    Dong, Min; Dong, Chenghui; Guo, Miao; Wang, Zhe; Mu, Xiaomin

    2018-04-01

    Multiresolution-based methods, such as wavelet and Contourlet are usually used to image fusion. This work presents a new image fusion frame-work by utilizing area-based standard deviation in dual tree Contourlet trans-form domain. Firstly, the pre-registered source images are decomposed with dual tree Contourlet transform; low-pass and high-pass coefficients are obtained. Then, the low-pass bands are fused with weighted average based on area standard deviation rather than the simple "averaging" rule. While the high-pass bands are merged with the "max-absolute' fusion rule. Finally, the modified low-pass and high-pass coefficients are used to reconstruct the final fused image. The major advantage of the proposed fusion method over conventional fusion is the approximately shift invariance and multidirectional selectivity of dual tree Contourlet transform. The proposed method is compared with wavelet- , Contourletbased methods and other the state-of-the art methods on common used multi focus images. Experiments demonstrate that the proposed fusion framework is feasible and effective, and it performs better in both subjective and objective evaluation.

  4. 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

  5. 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

  6. 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.

  7. Sickle cell disease diagnosis based on spatio-temporal cell dynamics analysis using 3D printed shearing digital holographic microscopy.

    PubMed

    Javidi, Bahram; Markman, Adam; Rawat, Siddharth; O'Connor, Timothy; Anand, Arun; Andemariam, Biree

    2018-05-14

    We present a spatio-temporal analysis of cell membrane fluctuations to distinguish healthy patients from patients with sickle cell disease. A video hologram containing either healthy red blood cells (h-RBCs) or sickle cell disease red blood cells (SCD-RBCs) was recorded using a low-cost, compact, 3D printed shearing interferometer. Reconstructions were created for each hologram frame (time steps), forming a spatio-temporal data cube. Features were extracted by computing the standard deviations and the mean of the height fluctuations over time and for every location on the cell membrane, resulting in two-dimensional standard deviation and mean maps, followed by taking the standard deviations of these maps. The optical flow algorithm was used to estimate the apparent motion fields between subsequent frames (reconstructions). The standard deviation of the magnitude of the optical flow vectors across all frames was then computed. In addition, seven morphological cell (spatial) features based on optical path length were extracted from the cells to further improve the classification accuracy. A random forest classifier was trained to perform cell identification to distinguish between SCD-RBCs and h-RBCs. To the best of our knowledge, this is the first report of machine learning assisted cell identification and diagnosis of sickle cell disease based on cell membrane fluctuations and morphology using both spatio-temporal and spatial analysis.

  8. 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.

  9. 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...

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou

    PubMed Central

    Zhao, Pengxiang; Zhou, Suhong

    2018-01-01

    Traditionally, static units of analysis such as administrative units are used when studying obesity. However, using these fixed contextual units ignores environmental influences experienced by individuals in areas beyond their residential neighborhood and may render the results unreliable. This problem has been articulated as the uncertain geographic context problem (UGCoP). This study investigates the UGCoP through exploring the relationships between the built environment and obesity based on individuals’ activity space. First, a survey was conducted to collect individuals’ daily activity and weight information in Guangzhou in January 2016. Then, the data were used to calculate and compare the values of several built environment variables based on seven activity space delineations, including home buffers, workplace buffers (WPB), fitness place buffers (FPB), the standard deviational ellipse at two standard deviations (SDE2), the weighted standard deviational ellipse at two standard deviations (WSDE2), the minimum convex polygon (MCP), and road network buffers (RNB). Lastly, we conducted comparative analysis and regression analysis based on different activity space measures. The results indicate that significant differences exist between variables obtained with different activity space delineations. Further, regression analyses show that the activity space delineations used in the analysis have a significant influence on the results concerning the relationships between the built environment and obesity. The study sheds light on the UGCoP in analyzing the relationships between obesity and the built environment. PMID:29439392

  15. Combinatorial electrochemical cell array for high throughput screening of micro-fuel-cells and metal/air batteries.

    PubMed

    Jiang, Rongzhong

    2007-07-01

    An electrochemical cell array was designed that contains a common air electrode and 16 microanodes for high throughput screening of both fuel cells (based on polymer electrolyte membrane) and metal/air batteries (based on liquid electrolyte). Electrode materials can easily be coated on the anodes of the electrochemical cell array and screened by switching a graphite probe from one cell to the others. The electrochemical cell array was used to study direct methanol fuel cells (DMFCs), including high throughput screening of electrode catalysts and determination of optimum operating conditions. For screening of DMFCs, there is about 6% relative standard deviation (percentage of standard deviation versus mean value) for discharge current from 10 to 20 mAcm(2). The electrochemical cell array was also used to study tin/air batteries. The effect of Cu content in the anode electrode on the discharge performance of the tin/air battery was investigated. The relative standard deviations for screening of metal/air battery (based on zinc/air) are 2.4%, 3.6%, and 5.1% for discharge current at 50, 100, and 150 mAcm(2), respectively.

  16. 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...

  17. 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

  18. 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.

  19. 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

  20. A Priori Subgrid Scale Modeling for a Droplet Laden Temporal Mixing Layer

    NASA Technical Reports Server (NTRS)

    Okongo, Nora; Bellan, Josette

    2000-01-01

    Subgrid analysis of a transitional temporal mixing layer with evaporating droplets has been performed using a direct numerical simulation (DNS) database. The DNS is for a Reynolds number (based on initial vorticity thickness) of 600, with droplet mass loading of 0.2. The gas phase is computed using a Eulerian formulation, with Lagrangian droplet tracking. Since Large Eddy Simulation (LES) of this flow requires the computation of unfiltered gas-phase variables at droplet locations from filtered gas-phase variables at the grid points, it is proposed to model these by assuming the gas-phase variables to be given by the filtered variables plus a correction based on the filtered standard deviation, which can be computed from the sub-grid scale (SGS) standard deviation. This model predicts unfiltered variables at droplet locations better than simply interpolating the filtered variables. Three methods are investigated for modeling the SGS standard deviation: Smagorinsky, gradient and scale-similarity. When properly calibrated, the gradient and scale-similarity methods give results in excellent agreement with the DNS.

  1. Exploring local regularities for 3D object recognition

    NASA Astrophysics Data System (ADS)

    Tian, Huaiwen; Qin, Shengfeng

    2016-11-01

    In order to find better simplicity measurements for 3D object recognition, a new set of local regularities is developed and tested in a stepwise 3D reconstruction method, including localized minimizing standard deviation of angles(L-MSDA), localized minimizing standard deviation of segment magnitudes(L-MSDSM), localized minimum standard deviation of areas of child faces (L-MSDAF), localized minimum sum of segment magnitudes of common edges (L-MSSM), and localized minimum sum of areas of child face (L-MSAF). Based on their effectiveness measurements in terms of form and size distortions, it is found that when two local regularities: L-MSDA and L-MSDSM are combined together, they can produce better performance. In addition, the best weightings for them to work together are identified as 10% for L-MSDSM and 90% for L-MSDA. The test results show that the combined usage of L-MSDA and L-MSDSM with identified weightings has a potential to be applied in other optimization based 3D recognition methods to improve their efficacy and robustness.

  2. 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.

  3. 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...

  4. 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

  5. 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.

  6. 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.

  7. A natural-color mapping for single-band night-time image based on FPGA

    NASA Astrophysics Data System (ADS)

    Wang, Yilun; Qian, Yunsheng

    2018-01-01

    A natural-color mapping for single-band night-time image method based on FPGA can transmit the color of the reference image to single-band night-time image, which is consistent with human visual habits and can help observers identify the target. This paper introduces the processing of the natural-color mapping algorithm based on FPGA. Firstly, the image can be transformed based on histogram equalization, and the intensity features and standard deviation features of reference image are stored in SRAM. Then, the real-time digital images' intensity features and standard deviation features are calculated by FPGA. At last, FPGA completes the color mapping through matching pixels between images using the features in luminance channel.

  8. 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.

  9. Correlation Between Analog Noise Measurements and the Expected Bit Error Rate of a Digital Signal Propagating Through Passive Components

    NASA Technical Reports Server (NTRS)

    Warner, Joseph D.; Theofylaktos, Onoufrios

    2012-01-01

    A method of determining the bit error rate (BER) of a digital circuit from the measurement of the analog S-parameters of the circuit has been developed. The method is based on the measurement of the noise and the standard deviation of the noise in the S-parameters. Once the standard deviation and the mean of the S-parameters are known, the BER of the circuit can be calculated using the normal Gaussian function.

  10. Application of Mean of Absolute Deviation Method for the Selection of Best Nonlinear Component Based on Video Encryption

    NASA Astrophysics Data System (ADS)

    Anees, Amir; Khan, Waqar Ahmad; Gondal, Muhammad Asif; Hussain, Iqtadar

    2013-07-01

    The aim of this work is to make use of the mean of absolute deviation (MAD) method for the evaluation process of substitution boxes used in the advanced encryption standard. In this paper, we use the MAD technique to analyze some popular and prevailing substitution boxes used in encryption processes. In particular, MAD is applied to advanced encryption standard (AES), affine power affine (APA), Gray, Lui J., Residue Prime, S8 AES, SKIPJACK, and Xyi substitution boxes.

  11. 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.

  12. 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.

  13. An intelligent switch with back-propagation neural network based hybrid power system

    NASA Astrophysics Data System (ADS)

    Perdana, R. H. Y.; Fibriana, F.

    2018-03-01

    The consumption of conventional energy such as fossil fuels plays the critical role in the global warming issues. The carbon dioxide, methane, nitrous oxide, etc. could lead the greenhouse effects and change the climate pattern. In fact, 77% of the electrical energy is generated from fossil fuels combustion. Therefore, it is necessary to use the renewable energy sources for reducing the conventional energy consumption regarding electricity generation. This paper presents an intelligent switch to combine both energy resources, i.e., the solar panels as the renewable energy with the conventional energy from the State Electricity Enterprise (PLN). The artificial intelligence technology with the back-propagation neural network was designed to control the flow of energy that is distributed dynamically based on renewable energy generation. By the continuous monitoring on each load and source, the dynamic pattern of the intelligent switch was better than the conventional switching method. The first experimental results for 60 W solar panels showed the standard deviation of the trial at 0.7 and standard deviation of the experiment at 0.28. The second operation for a 900 W of solar panel obtained the standard deviation of the trial at 0.05 and 0.18 for the standard deviation of the experiment. Moreover, the accuracy reached 83% using this method. By the combination of the back-propagation neural network with the observation of energy usage of the load using wireless sensor network, each load can be evenly distributed and will impact on the reduction of conventional energy usage.

  14. 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.

  15. 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.

  16. 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.

  17. Filling the voids in the SRTM elevation model — A TIN-based delta surface approach

    NASA Astrophysics Data System (ADS)

    Luedeling, Eike; Siebert, Stefan; Buerkert, Andreas

    The Digital Elevation Model (DEM) derived from NASA's Shuttle Radar Topography Mission is the most accurate near-global elevation model that is publicly available. However, it contains many data voids, mostly in mountainous terrain. This problem is particularly severe in the rugged Oman Mountains. This study presents a method to fill these voids using a fill surface derived from Russian military maps. For this we developed a new method, which is based on Triangular Irregular Networks (TINs). For each void, we extracted points around the edge of the void from the SRTM DEM and the fill surface. TINs were calculated from these points and converted to a base surface for each dataset. The fill base surface was subtracted from the fill surface, and the result added to the SRTM base surface. The fill surface could then seamlessly be merged with the SRTM DEM. For validation, we compared the resulting DEM to the original SRTM surface, to the fill DEM and to a surface calculated by the International Center for Tropical Agriculture (CIAT) from the SRTM data. We calculated the differences between measured GPS positions and the respective surfaces for 187,500 points throughout the mountain range (ΔGPS). Comparison of the means and standard deviations of these values showed that for the void areas, the fill surface was most accurate, with a standard deviation of the ΔGPS from the mean ΔGPS of 69 m, and only little accuracy was lost by merging it to the SRTM surface (standard deviation of 76 m). The CIAT model was much less accurate in these areas (standard deviation of 128 m). The results show that our method is capable of transferring the relative vertical accuracy of a fill surface to the void areas in the SRTM model, without introducing uncertainties about the absolute elevation of the fill surface. It is well suited for datasets with varying altitude biases, which is a common problem of older topographic information.

  18. 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.

  19. 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

  20. Reliability-Based Design Optimization of a Composite Airframe Component

    NASA Technical Reports Server (NTRS)

    Pai, Shantaram S.; Coroneos, Rula; Patnaik, Surya N.

    2011-01-01

    A stochastic optimization methodology (SDO) has been developed to design airframe structural components made of metallic and composite materials. The design method accommodates uncertainties in load, strength, and material properties that are defined by distribution functions with mean values and standard deviations. A response parameter, like a failure mode, has become a function of reliability. The primitive variables like thermomechanical loads, material properties, and failure theories, as well as variables like depth of beam or thickness of a membrane, are considered random parameters with specified distribution functions defined by mean values and standard deviations.

  1. 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…

  2. Evaluation of methods for measuring particulate matter emissions from gas turbines.

    PubMed

    Petzold, Andreas; Marsh, Richard; Johnson, Mark; Miller, Michael; Sevcenco, Yura; Delhaye, David; Ibrahim, Amir; Williams, Paul; Bauer, Heidi; Crayford, Andrew; Bachalo, William D; Raper, David

    2011-04-15

    The project SAMPLE evaluated methods for measuring particle properties in the exhaust of aircraft engines with respect to the development of standardized operation procedures for particulate matter measurement in aviation industry. Filter-based off-line mass methods included gravimetry and chemical analysis of carbonaceous species by combustion methods. Online mass methods were based on light absorption measurement or used size distribution measurements obtained from an electrical mobility analyzer approach. Number concentrations were determined using different condensation particle counters (CPC). Total mass from filter-based methods balanced gravimetric mass within 8% error. Carbonaceous matter accounted for 70% of gravimetric mass while the remaining 30% were attributed to hydrated sulfate and noncarbonaceous organic matter fractions. Online methods were closely correlated over the entire range of emission levels studied in the tests. Elemental carbon from combustion methods and black carbon from optical methods deviated by maximum 5% with respect to mass for low to medium emission levels, whereas for high emission levels a systematic deviation between online methods and filter based methods was found which is attributed to sampling effects. CPC based instruments proved highly reproducible for number concentration measurements with a maximum interinstrument standard deviation of 7.5%.

  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. 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.

  5. Influence of genetic variants associated with body mass index on eating behavior in childhood

    PubMed Central

    Monnereau, Claire; Jansen, Pauline W; Tiemeier, Henning; Jaddoe, Vincent WV; Felix, Janine F

    2017-01-01

    Objective Childhood eating behaviors are associated with body mass index (BMI). Recent genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with adult and childhood BMI. We hypothesized that these SNPs also influence eating behavior. Methods In a population-based prospective cohort study among 3,179 children (mean age (standard deviation): 4.0 (0.1) years), we tested two weighted genetic risk scores, based on 15 childhood and 97 adult BMI SNPs, and ten individual appetite and/or satiety related SNPs for association with food fussiness, food responsiveness, enjoyment of food, satiety responsiveness, slowness in eating. Results The 15 SNP-based childhood BMI genetic risk score was not associated with the eating behavior subscales. The 97 SNP-based adult BMI genetic risk score was nominally associated with satiety responsiveness (β: -0.007 standard deviation, 95% confidence interval (CI) -0.013, 0.000). Of the ten individual SNPs, rs11030104 in BDNF and rs10733682 in LMX1B were nominally associated with satiety responsiveness (β: -0.057 standard deviation, 95% CI -0.112, -0.002). Conclusion Our findings do not strongly support the hypothesis that BMI associated SNPs also influence eating behavior at this age. A potential role for BMI SNPs in satiety responsiveness during childhood was observed, however, no associations with the other eating behavior subscales. PMID:28245097

  6. 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

  7. 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…

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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…

  13. 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...

  14. 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...

  15. How accurate is accident data in road safety research? An application of vehicle black box data regarding pedestrian-to-taxi accidents in Korea.

    PubMed

    Chung, Younshik; Chang, IlJoon

    2015-11-01

    Recently, the introduction of vehicle black box systems or in-vehicle video event data recorders enables the driver to use the system to collect more accurate crash information such as location, time, and situation at the pre-crash and crash moment, which can be analyzed to find the crash causal factors more accurately. This study presents the vehicle black box system in brief and its application status in Korea. Based on the crash data obtained from the vehicle black box system, this study analyzes the accuracy of the crash data collected from existing road crash data recording method, which has been recorded by police officers based on accident parties' statements or eyewitness's account. The analysis results show that the crash data observed by the existing method have an average of 84.48m of spatial difference and standard deviation of 157.75m as well as average 29.05min of temporal error and standard deviation of 19.24min. Additionally, the average and standard deviation of crash speed errors were found to be 9.03km/h and 7.21km/h, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Combined search for the standard model Higgs boson decaying to a bb pair using the full CDF data set.

    PubMed

    Aaltonen, T; Álvarez González, B; 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; Binkley, M E; Bisello, D; Bizjak, I; 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; Buzatu, A; Calamba, A; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; 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; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chung, W H; Chung, Y S; Ciocci, M A; Clark, A; Clarke, C; Compostella, G; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuevas, J; Culbertson, R; Dagenhart, D; d'Ascenzo, N; Datta, M; de Barbaro, P; Dell'Orso, M; Demortier, L; Deninno, M; Devoto, F; d'Errico, M; Di Canto, A; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, M; Dorigo, T; Ebina, K; Elagin, A; Eppig, A; Erbacher, R; Errede, S; Ershaidat, N; Eusebi, R; Farrington, S; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Funakoshi, Y; Furic, I; Gallinaro, M; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Grinstein, S; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Hahn, S R; Halkiadakis, E; Hamaguchi, A; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harr, R F; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Hewamanage, S; Hocker, A; Hopkins, W; Horn, D; Hou, S; Hughes, R E; Hurwitz, M; Husemann, U; Hussain, N; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeans, D T; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; 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; Kim, Y J; Kimura, N; Kirby, M; Klimenko, S; Knoepfel, K; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Kruse, M; Krutelyov, V; Kuhr, T; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; LeCompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lin, C-J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, H; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maeshima, K; Maestro, P; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Martínez, M; Mastrandrea, P; Matera, K; Mattson, M E; Mazzacane, A; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Noh, S Y; Norniella, O; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Paramonov, A A; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Prokoshin, F; Pranko, A; Ptohos, F; Punzi, G; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Rescigno, M; Riddick, T; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Safonov, A; Sakumoto, W K; Sakurai, Y; Santi, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schwarz, T; Scodellaro, L; Scribano, A; 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; Sinervo, P; Sliwa, K; Smith, J R; Snider, F D; Soha, A; Sorin, V; Song, H; Squillacioti, P; Stancari, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Tipton, P; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Ukegawa, F; Uozumi, S; Varganov, A; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wagner, R L; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Wester, W C; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Wick, F; 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; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zhou, C; Zucchelli, S

    2012-09-14

    We combine the results of searches for the standard model (SM) Higgs boson based on the full CDF Run II data set obtained from sqrt[s]=1.96  TeV pp collisions at the Fermilab Tevatron corresponding to an integrated luminosity of 9.45  fb(-1). The searches are conducted for Higgs bosons that are produced in association with a W or Z boson, have masses in the range 90-150  GeV/c(2), and decay into bb pairs. An excess of data is present that is inconsistent with the background prediction at the level of 2.5 standard deviations (the most significant local excess is 2.7 standard deviations).

  17. Validation of lignocellulosic biomass carbohydrates determination via acid hydrolysis.

    PubMed

    Zhou, Shengfei; Runge, Troy M

    2014-11-04

    This work studied the two-step acid hydrolysis for determining carbohydrates in lignocellulosic biomass. Estimation of sugar loss based on acid hydrolyzed sugar standards or analysis of sugar derivatives was investigated. Four model substrates (starch, holocellulose, filter paper and cotton) and three levels of acid/material ratios (7.8, 10.3 and 15.4, v/w) were studied to demonstrate the range of test artifacts. The method for carbohydrates estimation based on acid hydrolyzed sugar standards having the most satisfactory carbohydrate recovery and relative standard deviation. Raw material and the acid/material ratio both had significant effect on carbohydrate hydrolysis, suggesting the acid to have impacts beyond a catalyst in the hydrolysis. Following optimal procedures, we were able to reach a carbohydrate recovery of 96% with a relative standard deviation less than 3%. The carbohydrates recovery lower than 100% was likely due to the incomplete hydrolysis of substrates, which was supported by scanning electron microscope (SEM) images. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. Global Summary MGS TES Data and Mars-Gram Validation

    NASA Technical Reports Server (NTRS)

    Justus, C.; Johnson, D.; Parker, Nelson C. (Technical Monitor)

    2002-01-01

    Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Arizona Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topograph$ from Mars Global Surveyor Mars Orbiting Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with a global summary data set of Mars Global Surveyor Thermal Emission Spectrometer (TES) data. TES averages and standard deviations were assembled from binned TES data which covered surface to approx. 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of a Mars global dust storm). TES data were binned in 10-by-10 degree latitude-longitude bins (i.e. 36 longitude bins by 19 latitude bins), 12 seasonal bins (based on 30 degree increments of Ls angle). Bin averages and standard deviations were assembled at 23 data levels (temperature at 21 pressure levels, plus surface temperature and surface pressure). Two time-of day bins were used: local time near 2 or 14 hours local time). Two dust optical depth bins wereused: infrared optical depth either less than or greater than 0.25 (which corresponds to visible optical depth either less than or greater than about 0.5). For interests in aerocapture and precision entry and landing, comparisons focused on atmospheric density. TES densities versus height were computed from TES temperature versus pressure, using assumptions of perfect gas law and hydrostatics. Mars-GRAM validation studies used density ratio (TES/Mars-GRAM) evaluated at data bin center points in space and time. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (> 45 deg N), or at most altitudes in the southern hemisphere at Ls approx. 90 and 180deg). Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approx. 65-10.5% (varying with height) for all data, or approx. 5-12%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for local time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about the same as the standard deviation of TES data about the TES mean value at a given position and season.

  4. 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.

  5. Historical Precision of an Ozone Correction Procedure for AM0 Solar Cell Calibration

    NASA Technical Reports Server (NTRS)

    Snyder, David B.; Jenkins, Phillip; Scheiman, David

    2005-01-01

    In an effort to improve the accuracy of the high altitude aircraft method for calibration of high band-gap solar cells, the ozone correction procedure has been revisited. The new procedure adjusts the measured short circuit current, Isc, according to satellite based ozone measurements and a model of the atmospheric ozone profile then extrapolates the measurements to air mass zero, AMO. The purpose of this paper is to assess the precision of the revised procedure by applying it to historical data sets. The average Isc of a silicon cell for a flying season increased 0.5% and the standard deviation improved from 0.5% to 0.3%. The 12 year average Isc of a GaAs cell increased 1% and the standard deviation improved from 0.8% to 0.5%. The slight increase in measured Isc and improvement in standard deviation suggests that the accuracy of the aircraft method may improve from 1% to nearly 0.5%.

  6. Active laser ranging with frequency transfer using frequency comb

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

    Zhang, Hongyuan; Wei, Haoyun; Yang, Honglei

    2016-05-02

    A comb-based active laser ranging scheme is proposed for enhanced distance resolution and a common time standard for the entire system. Three frequency combs with different repetition rates are used as light sources at the two ends where the distance is measured. Pulse positions are determined through asynchronous optical sampling and type II second harmonic generation. Results show that the system achieves a maximum residual of 379.6 nm and a standard deviation of 92.9 nm with 2000 averages over 23.6 m. Moreover, as for the frequency transfer, an atom clock and an adjustable signal generator, synchronized to the atom clock, are used asmore » time standards for the two ends to appraise the frequency deviation introduced by the proposed system. The system achieves a residual fractional deviation of 1.3 × 10{sup −16} for 1 s, allowing precise frequency transfer between the two clocks at the two ends.« less

  7. 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.

  8. Computing approximate random Delta v magnitude probability densities. [for spacecraft trajectory correction

    NASA Technical Reports Server (NTRS)

    Chadwick, C.

    1984-01-01

    This paper describes the development and use of an algorithm to compute approximate statistics of the magnitude of a single random trajectory correction maneuver (TCM) Delta v vector. The TCM Delta v vector is modeled as a three component Cartesian vector each of whose components is a random variable having a normal (Gaussian) distribution with zero mean and possibly unequal standard deviations. The algorithm uses these standard deviations as input to produce approximations to (1) the mean and standard deviation of the magnitude of Delta v, (2) points of the probability density function of the magnitude of Delta v, and (3) points of the cumulative and inverse cumulative distribution functions of Delta v. The approximates are based on Monte Carlo techniques developed in a previous paper by the author and extended here. The algorithm described is expected to be useful in both pre-flight planning and in-flight analysis of maneuver propellant requirements for space missions.

  9. 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…

  10. 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.

  11. 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.

  12. 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

  13. 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...

  14. Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO)

    PubMed Central

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-01-01

    The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle’s speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles. PMID:27420073

  15. Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO).

    PubMed

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-07-13

    The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle's speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles.

  16. Longitudinal meta-analysis of NIST pH Standard Reference Materials(®): a complement to pH key comparisons.

    PubMed

    Pratt, Kenneth W

    2015-04-01

    This meta-analysis assesses the long-term (up to 70 years) within-laboratory variation of the NIST pH Standard Reference Material® (SRM) tetroxalate, phthalate, phosphate, borate, and carbonate buffers. Values of ΔpH(S), the difference between the certified pH value, pH(S), of each SRM issue and the mean of all pH(S) values for the given SRM at that Celsius temperature, t, are graphed as a function of the SRM issue and t. In most cases, |ΔpH(S)| < 0.004. Deviations from the nominal base:acid amount (mole) ratio of a buffer yield t-independent, constant shifts in ΔpH(S). The mean ΔpH(S) characterizes such deviations. The corresponding mole fraction of impurity in the conjugate buffer component is generally <0.3 %. Changes in the equipment, personnel, materials, and methodology of the pH(S) measurement yield t-dependent variations. The standard deviation of ΔpH(S) characterizes such changes. Standard deviations of ΔpH(S) are generally 0.0015 or less. The results provide a long-term, single-institution complement to the time-specific, multi-institution results of pH key comparisons administered by the Consultative Committee for Metrology in Chemistry and Biology (CCQM).

  17. Using operations research to plan improvement of the transport of critically ill patients.

    PubMed

    Chen, Jing; Awasthi, Anjali; Shechter, Steven; Atkins, Derek; Lemke, Linda; Fisher, Les; Dodek, Peter

    2013-01-01

    Operations research is the application of mathematical modeling, statistical analysis, and mathematical optimization to understand and improve processes in organizations. The objective of this study was to illustrate how the methods of operations research can be used to identify opportunities to reduce the absolute value and variability of interfacility transport intervals for critically ill patients. After linking data from two patient transport organizations in British Columbia, Canada, for all critical care transports during the calendar year 2006, the steps for transfer of critically ill patients were tabulated into a series of time intervals. Statistical modeling, root-cause analysis, Monte Carlo simulation, and sensitivity analysis were used to test the effect of changes in component intervals on overall duration and variation of transport times. Based on quality improvement principles, we focused on reducing the 75th percentile and standard deviation of these intervals. We analyzed a total of 3808 ground and air transports. Constraining time spent by transport personnel at sending and receiving hospitals was projected to reduce the total time taken by 33 minutes with as much as a 20% reduction in standard deviation of these transport intervals in 75% of ground transfers. Enforcing a policy of requiring acceptance of patients who have life- or limb-threatening conditions or organ failure was projected to reduce the standard deviation of air transport time by 63 minutes and the standard deviation of ground transport time by 68 minutes. Based on findings from our analyses, we developed recommendations for technology renovation, personnel training, system improvement, and policy enforcement. Use of the tools of operations research identifies opportunities for improvement in a complex system of critical care transport.

  18. Differential standard deviation of log-scale intensity based optical coherence tomography angiography.

    PubMed

    Shi, Weisong; Gao, Wanrong; Chen, Chaoliang; Yang, Victor X D

    2017-12-01

    In this paper, a differential standard deviation of log-scale intensity (DSDLI) based optical coherence tomography angiography (OCTA) is presented for calculating microvascular images of human skin. The DSDLI algorithm calculates the variance in difference images of two consecutive log-scale intensity based structural images from the same position along depth direction to contrast blood flow. The en face microvascular images were then generated by calculating the standard deviation of the differential log-scale intensities within the specific depth range, resulting in an improvement in spatial resolution and SNR in microvascular images compared to speckle variance OCT and power intensity differential method. The performance of DSDLI was testified by both phantom and in vivo experiments. In in vivo experiments, a self-adaptive sub-pixel image registration algorithm was performed to remove the bulk motion noise, where 2D Fourier transform was utilized to generate new images with spatial interval equal to half of the distance between two pixels in both fast-scanning and depth directions. The SNRs of signals of flowing particles are improved by 7.3 dB and 6.8 dB on average in phantom and in vivo experiments, respectively, while the average spatial resolution of images of in vivo blood vessels is increased by 21%. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Text-Based Vocabulary Intervention Training Study: Supporting Fourth Graders with Low Reading Comprehension and Learning Disabilities

    ERIC Educational Resources Information Center

    Solís, Michael; Scammacca, Nancy; Barth, Amy E.; Roberts, Garrett J.

    2017-01-01

    This experimental study examined the effectiveness of a text-based reading and vocabulary intervention with self-regulatory supports for 4th graders with low reading comprehension. Students with standard scores on the Gates MacGinitie Reading Test between 1.0 standard deviation (SD) and 0.5 SD below the normative sample were included (N=44) and…

  20. 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

  1. 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.

  2. Image contrast enhancement based on a local standard deviation model

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

    Chang, Dah-Chung; Wu, Wen-Rong

    1996-12-31

    The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. In this paper a new gain is developed based on Hunt`s Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details aremore » concentrated. We have applied the new ACE algorithm to chest x-ray images and the simulations show the effectiveness of the proposed algorithm.« less

  3. A GPS Phase-Locked Loop Performance Metric Based on the Phase Discriminator Output

    PubMed Central

    Stevanovic, Stefan; Pervan, Boris

    2018-01-01

    We propose a novel GPS phase-lock loop (PLL) performance metric based on the standard deviation of tracking error (defined as the discriminator’s estimate of the true phase error), and explain its advantages over the popular phase jitter metric using theory, numerical simulation, and experimental results. We derive an augmented GPS phase-lock loop (PLL) linear model, which includes the effect of coherent averaging, to be used in conjunction with this proposed metric. The augmented linear model allows more accurate calculation of tracking error standard deviation in the presence of additive white Gaussian noise (AWGN) as compared to traditional linear models. The standard deviation of tracking error, with a threshold corresponding to half of the arctangent discriminator pull-in region, is shown to be a more reliable/robust measure of PLL performance under interference conditions than the phase jitter metric. In addition, the augmented linear model is shown to be valid up until this threshold, which facilitates efficient performance prediction, so that time-consuming direct simulations and costly experimental testing can be reserved for PLL designs that are much more likely to be successful. The effect of varying receiver reference oscillator quality on the tracking error metric is also considered. PMID:29351250

  4. 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.

  5. Implementation of an Algorithm for Prosthetic Joint Infection: Deviations and Problems.

    PubMed

    Mühlhofer, Heinrich M L; Kanz, Karl-Georg; Pohlig, Florian; Lenze, Ulrich; Lenze, Florian; Toepfer, Andreas; von Eisenhart-Rothe, Ruediger; Schauwecker, Johannes

    The outcome of revision surgery in arthroplasty is based on a precise diagnosis. In addition, the treatment varies based on whether the prosthetic failure is caused by aseptic or septic loosening. Algorithms can help to identify periprosthetic joint infections (PJI) and standardize diagnostic steps, however, algorithms tend to oversimplify the treatment of complex cases. We conducted a process analysis during the implementation of a PJI algorithm to determine problems and deviations associated with the implementation of this algorithm. Fifty patients who were treated after implementing a standardized algorithm were monitored retrospectively. Their treatment plans and diagnostic cascades were analyzed for deviations from the implemented algorithm. Each diagnostic procedure was recorded, compared with the algorithm, and evaluated statistically. We detected 52 deviations while treating 50 patients. In 25 cases, no discrepancy was observed. Synovial fluid aspiration was not performed in 31.8% of patients (95% confidence interval [CI], 18.1%-45.6%), while white blood cell counts (WBCs) and neutrophil differentiation were assessed in 54.5% of patients (95% CI, 39.8%-69.3%). We also observed that the prolonged incubation of cultures was not requested in 13.6% of patients (95% CI, 3.5%-23.8%). In seven of 13 cases (63.6%; 95% CI, 35.2%-92.1%), arthroscopic biopsy was performed; 6 arthroscopies were performed in discordance with the algorithm (12%; 95% CI, 3%-21%). Self-critical analysis of diagnostic processes and monitoring of deviations using algorithms are important and could increase the quality of treatment by revealing recurring faults.

  6. 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.

  7. 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...

  8. 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.

  9. A Robust Interpretation of Teaching Evaluation Ratings

    ERIC Educational Resources Information Center

    Bi, Henry H.

    2018-01-01

    There are no absolute standards regarding what teaching evaluation ratings are satisfactory. It is also problematic to compare teaching evaluation ratings with the average or with a cutoff number to determine whether they are adequate. In this paper, we use average and standard deviation charts (X[overbar]-S charts), which are based on the theory…

  10. A Standardization Evaluation Potential Study of the Common Multi-Mode Radar Program.

    DTIC Science & Technology

    1979-11-01

    Radar, the RX (RF-16 etc.), Enhanced Tactical Fighter ( ETF ), and A-7. Candidate radar systems applicable to the Common Multi-Mode Radar Program...RSTC R Resupply Time to Overseas Located Bases (hours) RSTO R Depot Stock Safety Factor (standard deviations) DLY R Shipping Time to Depot from CONUS

  11. Development of a Smartphone-based reading system for lateral flow immunoassay.

    PubMed

    Lee, Sangdae; Kim, Giyoung; Moon, Jihea

    2014-11-01

    This study was conducted to develop and evaluate the performance of the Smartphone-based reading system for the lateral flow immunoassay (LFIA). Smartphone-based reading system consists of a Samsung Galaxy S2 Smartphone, Smartphone application, and a LFIA reader. LFIA reader is composed of the close-up lens with a focal length up to 30 mm, white LED light, lithium polymer battery, and main body. The Smartphone application for image acquisition and data analysis was developed on the Android platform. The standard curve was obtained by plotting the measured P(T)/P(c) or A(T)/A(c) ratio versus Salmonella standard concentration. The mean, standard deviation (SD), recovery, and relative standard deviation (RSD) were also calculated using additional experimental results. These data were compared with that obtained from the benchtop LFIA reader. The LOD in both systems was observed with 10(6) CFU/mL. The results show high accuracy and good reproducibility with a RSD less than 10% in the range of 10(6) to 10(9) CFU/mL. Due to the simple structure, good sensitivity, and high accuracy of the Smartphone-based reading system, this system can be substituted for the benchtop LFIA reader for point-of-care medical diagnostics.

  12. Validation of spectroscopic gas analyzer accuracy using gravimetric standard gas mixtures: impact of background gas composition on CO2 quantitation by cavity ring-down spectroscopy

    NASA Astrophysics Data System (ADS)

    Lim, Jeong Sik; Park, Miyeon; Lee, Jinbok; Lee, Jeongsoon

    2017-12-01

    The effect of background gas composition on the measurement of CO2 levels was investigated by wavelength-scanned cavity ring-down spectrometry (WS-CRDS) employing a spectral line centered at the R(1) of the (3 00 1)III ← (0 0 0) band. For this purpose, eight cylinders with various gas compositions were gravimetrically and volumetrically prepared within 2σ = 0.1 %, and these gas mixtures were introduced into the WS-CRDS analyzer calibrated against standards of ambient air composition. Depending on the gas composition, deviations between CRDS-determined and gravimetrically (or volumetrically) assigned CO2 concentrations ranged from -9.77 to 5.36 µmol mol-1, e.g., excess N2 exhibited a negative deviation, whereas excess Ar showed a positive one. The total pressure broadening coefficients (TPBCs) obtained from the composition of N2, O2, and Ar thoroughly corrected the deviations up to -0.5 to 0.6 µmol mol-1, while these values were -0.43 to 1.43 µmol mol-1 considering PBCs induced by only N2. The use of TPBC enhanced deviations to be corrected to ˜ 0.15 %. Furthermore, the above correction linearly shifted CRDS responses for a large extent of TPBCs ranging from 0.065 to 0.081 cm-1 atm-1. Thus, accurate measurements using optical intensity-based techniques such as WS-CRDS require TPBC-based instrument calibration or use standards prepared in the same background composition of ambient air.

  13. Tube wall thickness measurement apparatus

    DOEpatents

    Lagasse, P.R.

    1985-06-21

    An apparatus for measuring the thickness of a tube's wall for the tube's entire length and radius by determining the deviation of the tube wall thickness from the known thickness of a selected standard item. The apparatus comprises a base and a first support member having first and second ends. The first end is connected to the base and the second end is connected to a spherical element. A second support member is connected to the base and spaced apart from the first support member. A positioning element is connected to and movable relative to the second support member. An indicator is connected to the positioning element and is movable to a location proximate the spherical element. The indicator includes a contact ball for first contacting the selected standard item and holding it against the spherical element. The contact ball then contacts the tube when the tube is disposed about the spherical element. The indicator includes a dial having a rotatable needle for indicating the deviation of the tube wall thickness from the thickness of the selected standard item.

  14. Tube wall thickness measurement apparatus

    DOEpatents

    Lagasse, Paul R.

    1987-01-01

    An apparatus for measuring the thickness of a tube's wall for the tube's entire length and circumference by determining the deviation of the tube wall thickness from the known thickness of a selected standard item. The apparatus comprises a base and a first support member having first and second ends. The first end is connected to the base and the second end is connected to a spherical element. A second support member is connected to the base and spaced apart from the first support member. A positioning element is connected to and movable relative to the second support member. An indicator is connected to the positioning element and is movable to a location proximate the spherical element. The indicator includes a contact ball for first contacting the selected standard item and holding it against the spherical element. The contact ball then contacts the tube when the tube is disposed about the spherical element. The indicator includes a dial having a rotatable needle for indicating the deviation of the tube wall thickness from the thickness of the selected standard item.

  15. SU-C-207A-04: Accuracy of Acoustic-Based Proton Range Verification in Water

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

    Jones, KC; Sehgal, CM; Avery, S

    2016-06-15

    Purpose: To determine the accuracy and dose required for acoustic-based proton range verification (protoacoustics) in water. Methods: Proton pulses with 17 µs FWHM and instantaneous currents of 480 nA (5.6 × 10{sup 7} protons/pulse, 8.9 cGy/pulse) were generated by a clinical, hospital-based cyclotron at the University of Pennsylvania. The protoacoustic signal generated in a water phantom by the 190 MeV proton pulses was measured with a hydrophone placed at multiple known positions surrounding the dose deposition. The background random noise was measured. The protoacoustic signal was simulated to compare to the experiments. Results: The maximum protoacoustic signal amplitude at 5more » cm distance was 5.2 mPa per 1 × 10{sup 7} protons (1.6 cGy at the Bragg peak). The background random noise of the measurement was 27 mPa. Comparison between simulation and experiment indicates that the hydrophone introduced a delay of 2.4 µs. For acoustic data collected with a signal-to-noise ratio (SNR) of 21, deconvolution of the protoacoustic signal with the proton pulse provided the most precise time-of-flight range measurement (standard deviation of 2.0 mm), but a systematic error (−4.5 mm) was observed. Conclusion: Based on water phantom measurements at a clinical hospital-based cyclotron, protoacoustics is a potential technique for measuring the proton Bragg peak range with 2.0 mm standard deviation. Simultaneous use of multiple detectors is expected to reduce the standard deviation, but calibration is required to remove systematic error. Based on the measured background noise and protoacoustic amplitude, a SNR of 5.3 is projected for a deposited dose of 2 Gy.« less

  16. 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.

  17. 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.

  18. Holmium:YAG thermokeratoplasty: treatment parameters for the correction of astigmatism based upon enucleated human eyes using an application mask

    NASA Astrophysics Data System (ADS)

    Kriegerowski, Martin; Rassmann, Katja; Oltrup, Theo; Bende, Thomas; Jean, Benedikt J.

    1995-05-01

    The refractive outcome of thermokeratoplasty depends upon the location and angle of the coagulation spots, applied with a focusing handpiece onto the corneal surface. Accuracy can be enhanced using a specially designed application mask. An astigmatism correction was performed on 10 human donor eyes (Holmium 25, Technomed, FRG, 15 Hz, 20 mJ/pulse, 25 pulses) with an optical zone of 8.1 mm, 5 eyes received a free hand laser application (marked positions) and the other 5 eyes were treated using a suctioned metal mask with drills for the handpiece (optical zone 8.1 mm). To compare the results a silicone replica was taken and analyzed by a confocal laser microtopometer. The refractive change for the steepest meridian was 10 D with a standard deviation of +/- 3.7 D for the free hand application. Using the application mask the refractive outcome was 9.8 D with a standard deviation of only 0.8 D. Using the application mask the standard deviation for the induced refractive change decreases by a factor of five.

  19. Analysis of DGPS/INS and MLS/INS final approach navigation errors and control performance data

    NASA Technical Reports Server (NTRS)

    Hueschen, Richard M.; Spitzer, Cary R.

    1992-01-01

    Flight tests were conducted jointly by NASA Langley Research Center and Honeywell, Inc., on a B-737 research aircraft to record a data base for evaluating the performance of a differential DGPS/inertial navigation system (INS) which used GPS Course/Acquisition code receivers. Estimates from the DGPS/INS and a Microwave Landing System (MLS)/INS, and various aircraft parameter data were recorded in real time aboard the aircraft while flying along the final approach path to landing. This paper presents the mean and standard deviation of the DGPS/INS and MLS/INS navigation position errors computed relative to the laser tracker system and of the difference between the DGPS/INS and MLS/INS velocity estimates. RMS errors are presented for DGPS/INS and MLS/INS guidance errors (localizer and glideslope). The mean navigation position errors and standard deviation of the x position coordinate of the DGPS/INS and MLS/INS systems were found to be of similar magnitude while the standard deviation of the y and z position coordinate errors were significantly larger for DGPS/INS compared to MLS/INS.

  20. 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

  1. Improved Bond Strength of Cyanoacrylate Adhesives Through Nanostructured Chromium Adhesion Layers

    NASA Astrophysics Data System (ADS)

    Gobble, Kyle; Stark, Amelia; Stagon, Stephen P.

    2016-09-01

    The performance of many consumer products suffers due to weak and inconsistent bonds formed to low surface energy polymer materials, such as polyolefin-based high-density polyethylene (HDPE), with adhesives, such as cyanoacrylate. In this letter, we present an industrially relevant means of increasing bond shear strength and consistency through vacuum metallization of chromium thin films and nanorods, using HDPE as a prototype material and cyanoacrylate as a prototype adhesive. For the as received HDPE surfaces, unmodified bond shear strength is shown to be only 0.20 MPa with a standard deviation of 14 %. When Cr metallization layers are added onto the HDPE at thicknesses of 50 nm or less, nanorod-structured coatings outperform continuous films and have a maximum bond shear strength of 0.96 MPa with a standard deviation of 7 %. When the metallization layer is greater than 50 nm thick, continuous films demonstrate greater performance than nanorod coatings and have a maximum shear strength of 1.03 MPa with a standard deviation of 6 %. Further, when the combination of surface roughening with P400 grit sandpaper and metallization is used, 100-nm-thick nanorod coatings show a tenfold increase in shear strength over the baseline, reaching a maximum of 2.03 MPa with a standard deviation of only 3 %. The substantial increase in shear strength through metallization, and the combination of roughening with metallization, may have wide-reaching implications in consumer products which utilize low surface energy plastics.

  2. 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.

  3. 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.

  4. 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.

  5. Half-lives of 214Pb and 214Bi.

    PubMed

    Martz, D E; Langner, G H; Johnson, P R

    1991-10-01

    New measurements on chemically separated samples of 214Bi have yielded a mean half-life value of 19.71 +/- 0.02 min, where the error quoted is twice the standard deviation of the mean based on 23 decay runs. This result provides strong support for the historic 19.72 +/- 0.04 min half-life value and essentially excludes the 19.9-min value, both reported in previous studies. New measurements of the decay rate of 222Rn progeny activity initially in radioactive equilibrium have yielded a value of 26.89 +/- 0.03 min for the half-life of 214Pb, where the error quoted is twice the standard deviation of the mean based on 12 decay runs. This value is 0.1 min longer than the currently accepted 214Pb half-value of 26.8 min.

  6. Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis.

    PubMed

    Azami, Hamed; Fernández, Alberto; Escudero, Javier

    2017-11-01

    Multiscale entropy (MSE) has been a prevalent algorithm to quantify the complexity of biomedical time series. Recent developments in the field have tried to alleviate the problem of undefined MSE values for short signals. Moreover, there has been a recent interest in using other statistical moments than the mean, i.e., variance, in the coarse-graining step of the MSE. Building on these trends, here we introduce the so-called refined composite multiscale fuzzy entropy based on the standard deviation (RCMFE σ ) and mean (RCMFE μ ) to quantify the dynamical properties of spread and mean, respectively, over multiple time scales. We demonstrate the dependency of the RCMFE σ and RCMFE μ , in comparison with other multiscale approaches, on several straightforward signal processing concepts using a set of synthetic signals. The results evidenced that the RCMFE σ and RCMFE μ values are more stable and reliable than the classical multiscale entropy ones. We also inspect the ability of using the standard deviation as well as the mean in the coarse-graining process using magnetoencephalograms in Alzheimer's disease and publicly available electroencephalograms recorded from focal and non-focal areas in epilepsy. Our results indicated that when the RCMFE μ cannot distinguish different types of dynamics of a particular time series at some scale factors, the RCMFE σ may do so, and vice versa. The results showed that RCMFE σ -based features lead to higher classification accuracies in comparison with the RCMFE μ -based ones. We also made freely available all the Matlab codes used in this study at http://dx.doi.org/10.7488/ds/1477 .

  7. Poorer right ventricular systolic function and exercise capacity in women after repair of tetralogy of fallot: a sex comparison of standard deviation scores based on sex-specific reference values in healthy control subjects.

    PubMed

    Sarikouch, Samir; Boethig, Dietmar; Peters, Brigitte; Kropf, Siegfried; Dubowy, Karl-Otto; Lange, Peter; Kuehne, Titus; Haverich, Axel; Beerbaum, Philipp

    2013-11-01

    In repaired congenital heart disease, there is increasing evidence of sex differences in cardiac remodeling, but there is a lack of comparable data for specific congenital heart defects such as in repaired tetralogy of Fallot. In a prospective multicenter study, a cohort of 272 contemporary patients (158 men; mean age, 14.3±3.3 years [range, 8-20 years]) with repaired tetralogy of Fallot underwent cardiac magnetic resonance for ventricular function and metabolic exercise testing. All data were transformed to standard deviation scores according to the Lambda-Mu-Sigma method by relating individual values to their respective 50th percentile (standard deviation score, 0) in sex-specific healthy control subjects. No sex differences were observed in age at repair, type of repair conducted, or overall hemodynamic results. Relative to sex-specific controls, repaired tetralogy of Fallot in women had larger right ventricular end-systolic volumes (standard deviation scores: women, 4.35; men, 3.25; P=0.001), lower right ventricular ejection fraction (women, -2.83; men, -2.12; P=0.011), lower right ventricular muscle mass (women, 1.58; men 2.45; P=0.001), poorer peak oxygen uptake (women, -1.65; men, -1.14; P<0.001), higher VE/VCO2 (ventilation per unit of carbon dioxide production) slopes (women, 0.88; men 0.58; P=0.012), and reduced peak heart rate (women, -2.16; men -1.74; P=0.017). Left ventricular parameters did not differ between sexes. Relative to their respective sex-specific healthy control subjects, derived standard deviation scores in repaired tetralogy of Fallot suggest that women perform poorer than men in terms of right ventricular systolic function as tested by cardiac magnetic resonance and exercise capacity. This effect cannot be explained by selection bias. Further outcome data are required from longitudinal cohort studies.

  8. A study of respiration-correlated cone-beam CT scans to correct target positioning errors in radiotherapy of thoracic cancer

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

    Santoro, J. P.; McNamara, J.; Yorke, E.

    2012-10-15

    Purpose: There is increasingly widespread usage of cone-beam CT (CBCT) for guiding radiation treatment in advanced-stage lung tumors, but difficulties associated with daily CBCT in conventionally fractionated treatments include imaging dose to the patient, increased workload and longer treatment times. Respiration-correlated cone-beam CT (RC-CBCT) can improve localization accuracy in mobile lung tumors, but further increases the time and workload for conventionally fractionated treatments. This study investigates whether RC-CBCT-guided correction of systematic tumor deviations in standard fractionated lung tumor radiation treatments is more effective than 2D image-based correction of skeletal deviations alone. A second study goal compares respiration-correlated vs respiration-averaged imagesmore » for determining tumor deviations. Methods: Eleven stage II-IV nonsmall cell lung cancer patients are enrolled in an IRB-approved prospective off-line protocol using RC-CBCT guidance to correct for systematic errors in GTV position. Patients receive a respiration-correlated planning CT (RCCT) at simulation, daily kilovoltage RC-CBCT scans during the first week of treatment and weekly scans thereafter. Four types of correction methods are compared: (1) systematic error in gross tumor volume (GTV) position, (2) systematic error in skeletal anatomy, (3) daily skeletal corrections, and (4) weekly skeletal corrections. The comparison is in terms of weighted average of the residual GTV deviations measured from the RC-CBCT scans and representing the estimated residual deviation over the treatment course. In the second study goal, GTV deviations computed from matching RCCT and RC-CBCT are compared to deviations computed from matching respiration-averaged images consisting of a CBCT reconstructed using all projections and an average-intensity-projection CT computed from the RCCT. Results: Of the eleven patients in the GTV-based systematic correction protocol, two required no correction, seven required a single correction, one required two corrections, and one required three corrections. Mean residual GTV deviation (3D distance) following GTV-based systematic correction (mean {+-} 1 standard deviation 4.8 {+-} 1.5 mm) is significantly lower than for systematic skeletal-based (6.5 {+-} 2.9 mm, p= 0.015), and weekly skeletal-based correction (7.2 {+-} 3.0 mm, p= 0.001), but is not significantly lower than daily skeletal-based correction (5.4 {+-} 2.6 mm, p= 0.34). In two cases, first-day CBCT images reveal tumor changes-one showing tumor growth, the other showing large tumor displacement-that are not readily observed in radiographs. Differences in computed GTV deviations between respiration-correlated and respiration-averaged images are 0.2 {+-} 1.8 mm in the superior-inferior direction and are of similar magnitude in the other directions. Conclusions: An off-line protocol to correct GTV-based systematic error in locally advanced lung tumor cases can be effective at reducing tumor deviations, although the findings need confirmation with larger patient statistics. In some cases, a single cone-beam CT can be useful for assessing tumor changes early in treatment, if more than a few days elapse between simulation and the start of treatment. Tumor deviations measured with respiration-averaged CT and CBCT images are consistent with those measured with respiration-correlated images; the respiration-averaged method is more easily implemented in the clinic.« less

  9. 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)…

  10. 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.

  11. N-Terminal Pro-B-Type Natriuretic Peptide and Subclinical Brain Damage in the General Population.

    PubMed

    Zonneveld, Hazel I; Ikram, M Arfan; Hofman, Albert; Niessen, Wiro J; van der Lugt, Aad; Krestin, Gabriel P; Franco, Oscar H; Vernooij, Meike W

    2017-04-01

    Purpose To investigate the association between N-terminal pro-B-type natriuretic peptide (NT-proBNP), which is a marker of heart disease, and markers of subclinical brain damage on magnetic resonance (MR) images in community-dwelling middle-aged and elderly subjects without dementia and without a clinical diagnosis of heart disease. Materials and Methods This prospective population-based cohort study was approved by a medical ethics committee overseen by the national government, and all participants gave written informed consent. Serum levels of NT-proBNP were measured in 2397 participants without dementia or stroke (mean age, 56.6 years; age range, 45.7-87.3 years) and without clinical diagnosis of heart disease who were drawn from the population-based Rotterdam Study. All participants were examined with a 1.5-T MR imager. Multivariable linear and logistic regression analyses were used to investigate the association between NT-proBNP level and MR imaging markers of subclinical brain damage, including volumetric, focal, and microstructural markers. Results A higher NT-proBNP level was associated with smaller total brain volume (mean difference in z score per standard deviation increase in NT-proBNP level, -0.021; 95% confidence interval [CI]: -0.034, -0.007; P = .003) and was predominantly driven by gray matter volume (mean difference in z score per standard deviation increase in NT-proBNP level, -0.037; 95% CI: -0.057, -0.017; P < .001). Higher NT-proBNP level was associated with larger white matter lesion volume (mean difference in z score per standard deviation increase in NT-proBNP level, 0.090; 95% CI: 0.051, 0.129; P < .001), with lower fractional anisotropy (mean difference in z score per standard deviation increase in NT-proBNP level, -0.048; 95% CI: -0.088, -0.008; P = .019) and higher mean diffusivity (mean difference in z score per standard deviation increase in NT-proBNP level, 0.054; 95% CI: 0.018, 0.091; P = .004) of normal-appearing white matter. Conclusion In community-dwelling persons, higher serum NT-proBNP levels are associated with volumetric and microstructural MR imaging markers of subclinical brain damage. © RSNA, 2016 Online supplemental material is available for this article.

  12. Comparison of Profile Total Ozone from SBUV (v8.6) with GOME-Type and Ground-Based Total Ozone for a 16-Year Period (1996 to 2011)

    NASA Technical Reports Server (NTRS)

    Chiou, E. W.; Bhartia, P. K.; McPeters, R. D.; Loyola, D. G.; Coldewey-Egbers, M.; Fioletov, V. E.; Van Roozendael, M.; Spurr, R.; Lerot, C.; Frith, S. M.

    2014-01-01

    This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, namely, (i) Solar Backscatter Ultraviolet Instrument (SBUV) v8.6 profile total ozone, (ii) GTO (GOME-type total ozone), and (iii) ground-based total ozone data records covering the 16-year overlap period (March 1996 through June 2011). Analyses are conducted based on area-weighted zonal means for 0-30degS, 0-30degN, 50-30degS, and 30-60degN. It has been found that, on average, the differences in monthly zonal mean total ozone vary between -0.3 and 0.8% and are well within 1 %. For GTO minus SBUV, the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean total ozone vary between 0.6-0.7% and 2.8-3.8% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.4-0.6% and 2.2-3.5 %. The standard deviations and ranges of the differences ground-based minus SBUV regarding both monthly zonal means and anomalies are larger by a factor of 1.4-2.9 in comparison to GTO minus SBUV. The ground-based zonal means demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences GTO minus SBUV and ground-based minus SBUV are found to vary between -0.04 and 0.1%/yr (-0.1 and 0.3DU/yr). These negligibly small trends have provided strong evidence that there are no significant time-dependent differences among these multiyear total ozone data records. Analyses of the annual deviations from pre-1980 level indicate that, for the 15-year period of 1996 to 2010, all three data records show a gradual increase at 30-60degN from -5% in 1996 to -2% in 2010. In contrast, at 50-30degS and 30degS- 30degN there has been a leveling off in the 15 years after 1996. The deviations inferred from GTO and SBUV show agreement within 1 %, but a slight increase has been found in the differences during the period 1996-2010.

  13. Toolsets for Airborne Data - URS and New Documentation

    Atmospheric Science Data Center

    2015-03-23

    ... geolocated) files based on a user’s choice of time base. In addition, the TAD merge feature allows users to generate standard deviations ... NASA airborne missions. We are currently focused on in situ measurements and we would like to hear from you about the need for other ...

  14. Understanding Current Safety Issues for Trajectory Based Operations

    NASA Technical Reports Server (NTRS)

    Feary, Michael; Stewart, Michael

    2016-01-01

    Increases in procedural complexity were investigated as a possible contributor to flight path deviations in airline operations. Understanding current operational issues and their causes must be embraced to maintain current safety standards while increasing future functionality. ASRS data and expert narratives were used to discover factors relating to pilot deviations. Our investigation pointed to ATC intervention, automation confusion, procedure design, and mixed equipment as primary issues. Future work will need to include objective data and mitigation strategies.

  15. 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.

  16. 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.

  17. Heavy Ozone Enrichments from ATMOS Infrared Solar Spectra

    NASA Technical Reports Server (NTRS)

    Irion, F. W.; Gunson, M. R.; Rinsland, C. P.; Yung, Y. L.; Abrams, M. C.; Chang, A. Y.; Goldman, A.

    1996-01-01

    Vertical enrichment profiles of stratospheric O-16O-16O-18 and O-16O-18O-16 (hereafter referred to as (668)O3 and (686)O3 respectively) have been derived from space-based solar occultation spectra recorded at 0.01 cm(exp-1) resolution by the ATMOS (Atmospheric Trace MOlecule Spectroscopy) Fourier transform infrared (FTIR) spectrometer. The observations, made during the Spacelab 3 and ATLAS-1, -2, and -3 shuttle missions, cover polar, mid-latitude and tropical regions between 26 to 2.6 mb inclusive (approximately 25 to 41 km). Average enrichments, weighted by molecular (48)O3 density, of (15 +/- 6)% were found for (668)O3 and (10 +/- 7)% for (686)O3. Defining the mixing ratio of (50)O3 as the sum of those for (668)O3 and (686)O3, an enrichment of (13 plus or minus 5)% was found for (50)O3 (1 sigma standard deviation). No latitudinal or vertical gradients were found outside this standard deviation. From a series of ground-based measurements by the ATMOS instrument at Table Mountain, California (34.4 deg N), an average total column (668)O3 enrichment of (17 +/- 4)% (1 sigma standard deviation) was determined, with no significant seasonal variation discernable. Possible biases in the spectral intensities that affect the determination of absolute enrichments are discussed.

  18. A Priori Subgrid Analysis of Temporal Mixing Layers with Evaporating Droplets

    NASA Technical Reports Server (NTRS)

    Okongo, Nora; Bellan, Josette

    1999-01-01

    Subgrid analysis of a transitional temporal mixing layer with evaporating droplets has been performed using three sets of results from a Direct Numerical Simulation (DNS) database, with Reynolds numbers (based on initial vorticity thickness) as large as 600 and with droplet mass loadings as large as 0.5. In the DNS, the gas phase is computed using a Eulerian formulation, with Lagrangian droplet tracking. The Large Eddy Simulation (LES) equations corresponding to the DNS are first derived, and key assumptions in deriving them are first confirmed by computing the terms using the DNS database. Since LES of this flow requires the computation of unfiltered gas-phase variables at droplet locations from filtered gas-phase variables at the grid points, it is proposed to model these by assuming the gas-phase variables to be the sum of the filtered variables and a correction based on the filtered standard deviation; this correction is then computed from the Subgrid Scale (SGS) standard deviation. This model predicts the unfiltered variables at droplet locations considerably better than simply interpolating the filtered variables. Three methods are investigated for modeling the SGS standard deviation: the Smagorinsky approach, the Gradient model and the Scale-Similarity formulation. When the proportionality constant inherent in the SGS models is properly calculated, the Gradient and Scale-Similarity methods give results in excellent agreement with the DNS.

  19. 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.

  20. 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...

  1. 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

  2. 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.

  3. High-Throughput RNA Interference Screening: Tricks of the Trade

    PubMed Central

    Nebane, N. Miranda; Coric, Tatjana; Whig, Kanupriya; McKellip, Sara; Woods, LaKeisha; Sosa, Melinda; Sheppard, Russell; Rasmussen, Lynn; Bjornsti, Mary-Ann; White, E. Lucile

    2016-01-01

    The process of validating an assay for high-throughput screening (HTS) involves identifying sources of variability and developing procedures that minimize the variability at each step in the protocol. The goal is to produce a robust and reproducible assay with good metrics. In all good cell-based assays, this means coefficient of variation (CV) values of less than 10% and a signal window of fivefold or greater. HTS assays are usually evaluated using Z′ factor, which incorporates both standard deviation and signal window. A Z′ factor value of 0.5 or higher is acceptable for HTS. We used a standard HTS validation procedure in developing small interfering RNA (siRNA) screening technology at the HTS center at Southern Research. Initially, our assay performance was similar to published screens, with CV values greater than 10% and Z′ factor values of 0.51 ± 0.16 (average ± standard deviation). After optimizing the siRNA assay, we got CV values averaging 7.2% and a robust Z′ factor value of 0.78 ± 0.06 (average ± standard deviation). We present an overview of the problems encountered in developing this whole-genome siRNA screening program at Southern Research and how equipment optimization led to improved data quality. PMID:23616418

  4. 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.

  5. 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

  6. Toolsets for Airborne Data Beta Release

    Atmospheric Science Data Center

    2014-09-17

    ... create merge files based on a user’s choice of time base. In addition, the TAD merge feature allows users to generate standard deviation ... to the TAD database. We are currently focused on the in situ measurements and we want to hear from you about the need for other data ...

  7. Problem-Based Learning in a General Psychology Course.

    ERIC Educational Resources Information Center

    Willis, Sandra A.

    2002-01-01

    Describes the adoption of problem-based learning (PBL) techniques in a general psychology course. States that the instructor used a combination of techniques, including think-pair-share, lecture/discussion, and PBL. Notes means and standard deviations for graded components of PBL format versus lecture/discussion format. (Contains 18 references.)…

  8. OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics

    USGS Publications Warehouse

    Tonkin, Matthew J.; Tiedeman, Claire; Ely, D. Matthew; Hill, Mary C.

    2007-01-01

    The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added.

  9. A simulation study of nonparametric total deviation index as a measure of agreement based on quantile regression.

    PubMed

    Lin, Lawrence; Pan, Yi; Hedayat, A S; Barnhart, Huiman X; Haber, Michael

    2016-01-01

    Total deviation index (TDI) captures a prespecified quantile of the absolute deviation of paired observations from raters, observers, methods, assays, instruments, etc. We compare the performance of TDI using nonparametric quantile regression to the TDI assuming normality (Lin, 2000). This simulation study considers three distributions: normal, Poisson, and uniform at quantile levels of 0.8 and 0.9 for cases with and without contamination. Study endpoints include the bias of TDI estimates (compared with their respective theoretical values), standard error of TDI estimates (compared with their true simulated standard errors), and test size (compared with 0.05), and power. Nonparametric TDI using quantile regression, although it slightly underestimates and delivers slightly less power for data without contamination, works satisfactorily under all simulated cases even for moderate (say, ≥40) sample sizes. The performance of the TDI based on a quantile of 0.8 is in general superior to that of 0.9. The performances of nonparametric and parametric TDI methods are compared with a real data example. Nonparametric TDI can be very useful when the underlying distribution on the difference is not normal, especially when it has a heavy tail.

  10. A posteriori noise estimation in variable data sets. With applications to spectra and light curves

    NASA Astrophysics Data System (ADS)

    Czesla, S.; Molle, T.; Schmitt, J. H. M. M.

    2018-01-01

    Most physical data sets contain a stochastic contribution produced by measurement noise or other random sources along with the signal. Usually, neither the signal nor the noise are accurately known prior to the measurement so that both have to be estimated a posteriori. We have studied a procedure to estimate the standard deviation of the stochastic contribution assuming normality and independence, requiring a sufficiently well-sampled data set to yield reliable results. This procedure is based on estimating the standard deviation in a sample of weighted sums of arbitrarily sampled data points and is identical to the so-called DER_SNR algorithm for specific parameter settings. To demonstrate the applicability of our procedure, we present applications to synthetic data, high-resolution spectra, and a large sample of space-based light curves and, finally, give guidelines to apply the procedure in situation not explicitly considered here to promote its adoption in data analysis.

  11. Keratoconus: The ABCD Grading System.

    PubMed

    Belin, M W; Duncan, J K

    2016-06-01

    To propose a new keratoconus classification/staging system that utilises current tomographic data and better reflects the anatomical and functional changes seen in keratoconus. A previously published normative database was reanalysed to generate both anterior and posterior average radii of curvature (ARC and PRC) taken from a 3.0 mm optical zone centred on the thinnest point of the cornea. Mean and standard deviations were recorded and anterior data were compared to the existing Amsler-Krumeich (AK) Classification. ARC, PRC, thinnest pachymetry and distance visual acuity were then used to construct a keratoconus classification. 672 eyes of 336 patients were analysed. Anterior and posterior values were 7.65 ± 0.236 mm and 6.26 ± 0.214 mm, respectively, and thinnest pachymetry values were 534.2 ± 30.36 µm. The ARC values were 2.63, 5.47 and 6.44 standard deviations from the mean values of stages 1-3 in the AK classification, respectively. PRC staging uses the same standard deviation gates. The pachymetric values differed by 4.42 and 7.72 standard deviations for stages 2 and 3, respectively. A new keratoconus staging incorporates anterior and posterior curvature, thinnest pachymetric values, and distance visual acuity and consists of stages 0-4 (5 stages). The proposed system closely matches the existing AK classification stages 1-4 on anterior curvature. As it incorporates posterior curvature and thickness measurements based on the thinnest point, rather than apical measurements, the new staging system better reflects the anatomical changes seen in keratoconus. Georg Thieme Verlag KG Stuttgart · New York.

  12. 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.

  13. Experimental determination of the navigation error of the 4-D navigation, guidance, and control systems on the NASA B-737 airplane

    NASA Technical Reports Server (NTRS)

    Knox, C. E.

    1978-01-01

    Navigation error data from these flights are presented in a format utilizing three independent axes - horizontal, vertical, and time. The navigation position estimate error term and the autopilot flight technical error term are combined to form the total navigation error in each axis. This method of error presentation allows comparisons to be made between other 2-, 3-, or 4-D navigation systems and allows experimental or theoretical determination of the navigation error terms. Position estimate error data are presented with the navigation system position estimate based on dual DME radio updates that are smoothed with inertial velocities, dual DME radio updates that are smoothed with true airspeed and magnetic heading, and inertial velocity updates only. The normal mode of navigation with dual DME updates that are smoothed with inertial velocities resulted in a mean error of 390 m with a standard deviation of 150 m in the horizontal axis; a mean error of 1.5 m low with a standard deviation of less than 11 m in the vertical axis; and a mean error as low as 252 m with a standard deviation of 123 m in the time axis.

  14. Phase-I monitoring of standard deviations in multistage linear profiles

    NASA Astrophysics Data System (ADS)

    Kalaei, Mahdiyeh; Soleimani, Paria; Niaki, Seyed Taghi Akhavan; Atashgar, Karim

    2018-03-01

    In most modern manufacturing systems, products are often the output of some multistage processes. In these processes, the stages are dependent on each other, where the output quality of each stage depends also on the output quality of the previous stages. This property is called the cascade property. Although there are many studies in multistage process monitoring, there are fewer works on profile monitoring in multistage processes, especially on the variability monitoring of a multistage profile in Phase-I for which no research is found in the literature. In this paper, a new methodology is proposed to monitor the standard deviation involved in a simple linear profile designed in Phase I to monitor multistage processes with the cascade property. To this aim, an autoregressive correlation model between the stages is considered first. Then, the effect of the cascade property on the performances of three types of T 2 control charts in Phase I with shifts in standard deviation is investigated. As we show that this effect is significant, a U statistic is next used to remove the cascade effect, based on which the investigated control charts are modified. Simulation studies reveal good performances of the modified control charts.

  15. CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

    PubMed Central

    Peterson, Leif E

    2002-01-01

    CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

  16. Observation of t t ¯ H Production

    NASA Astrophysics Data System (ADS)

    Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Dragicevic, M.; Erö, J.; Escalante Del Valle, A.; Flechl, M.; Frühwirth, R.; Ghete, V. M.; Hrubec, J.; Jeitler, M.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Taurok, A.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Pieters, M.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Marchesini, I.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Bilin, B.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Dorney, B.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Kalsi, A. K.; Lenzi, T.; Luetic, J.; Postiau, N.; Starling, E.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Wang, Q.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Trocino, D.; Tytgat, M.; Verbeke, W.; Vermassen, B.; Vit, M.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; David, P.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Saggio, A.; Vidal Marono, M.; Wertz, S.; Zobec, J.; Alves, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Correia Silva, G.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Coelho, E.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Sanchez Rosas, L. J.; Santoro, A.; Sznajder, A.; Thiel, M.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Calligaris, L.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Marinov, A.; Misheva, M.; Rodozov, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Yuan, L.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Levin, A.; Li, J.; Li, L.; Li, Q.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Wang, Y.; Avila, C.; Cabrera, A.; Carrillo Montoya, C. A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Segura Delgado, M. A.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; Susa, T.; Ather, M. W.; Attikis, A.; Kolosova, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Ayala, E.; Carrera Jarrin, E.; Abdalla, H.; Abdelalim, A. A.; Mohamed, A.; Bhowmik, S.; Carvalho Antunes De Oliveira, A.; Dewanjee, R. K.; Ehataht, K.; Kadastik, M.; Raidal, M.; Veelken, C.; Eerola, P.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkilä, J. K.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Leloup, C.; Locci, E.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Beaudette, F.; Busson, P.; Charlot, C.; Granier de Cassagnac, R.; Kucher, I.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Pigard, P.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Stahl Leiton, A. G.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Chabert, E. C.; Cherepanov, V.; Collard, C.; Conte, E.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Jansová, M.; Le Bihan, A.-C.; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chanon, N.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lattaud, H.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Viret, S.; Zhang, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Rauch, M. P.; Schomakers, C.; Schulz, J.; Teroerde, M.; Wittmer, B.; Zhukov, V.; Albert, A.; Duchardt, D.; Endres, M.; Erdmann, M.; Esch, T.; Fischer, R.; Ghosh, S.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Keller, H.; Knutzen, S.; Mastrolorenzo, L.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Pook, T.; Radziej, M.; Rath, Y.; Reithler, H.; Rieger, M.; Scheuch, F.; Schmidt, A.; Teyssier, D.; Flügge, G.; Hlushchenko, O.; Kress, T.; Künsken, A.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Roy, D.; Sert, H.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Babounikau, I.; Beernaert, K.; Behnke, O.; Behrens, U.; Bermúdez Martínez, A.; Bertsche, D.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Danilov, V.; De Wit, A.; Defranchis, M. M.; Diez Pardos, C.; Domínguez Damiani, D.; Eckerlin, G.; Eichhorn, T.; Elwood, A.; Eren, E.; Gallo, E.; Geiser, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Guthoff, M.; Haranko, M.; Harb, A.; Hauk, J.; Jung, H.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Knolle, J.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Meyer, M.; Missiroli, M.; Mittag, G.; Mnich, J.; Myronenko, V.; Pflitsch, S. K.; Pitzl, D.; Raspereza, A.; Saibel, A.; Savitskyi, M.; Saxena, P.; Schütze, P.; Schwanenberger, C.; Shevchenko, R.; Singh, A.; Tholen, H.; Turkot, O.; Vagnerini, A.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Aggleton, R.; Bein, S.; Benato, L.; Benecke, A.; Blobel, V.; Centis Vignali, M.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Karavdina, A.; Kasieczka, G.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Kutzner, V.; Lange, J.; Marconi, D.; Multhaup, J.; Niedziela, M.; Nowatschin, D.; Perieanu, A.; Reimers, A.; Rieger, O.; Scharf, C.; Schleper, P.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Troendle, D.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baselga, M.; Baur, S.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; El Morabit, K.; Faltermann, N.; Freund, B.; Giffels, M.; Harrendorf, M. A.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Katkov, I.; Keicher, P.; Kudella, S.; Mildner, H.; Mitra, S.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Waßmer, M.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Kyriakis, A.; Loukas, D.; Paspalaki, G.; Topsis-Giotis, I.; Karathanasis, G.; Kesisoglou, S.; Kontaxakis, P.; Panagiotou, A.; Papavergou, I.; Saoulidou, N.; Tziaferi, E.; Vellidis, K.; Kousouris, K.; Papakrivopoulos, I.; Tsipolitis, G.; Evangelou, I.; Foudas, C.; Gianneios, P.; Katsoulis, P.; Kokkas, P.; Mallios, S.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Tsitsonis, D.; Bartók, M.; Csanad, M.; Filipovic, N.; Major, P.; Nagy, M. I.; Pasztor, G.; Surányi, O.; Veres, G. I.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Vámi, T. Á.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Tiwari, P. C.; Bahinipati, S.; Kar, C.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chauhan, S.; Chawla, R.; Dhingra, N.; Gupta, R.; Kaur, A.; Kaur, A.; Kaur, M.; Kaur, S.; Kumar, R.; Kumari, P.; Lohan, M.; Mehta, A.; Sandeep, K.; Sharma, S.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Gola, M.; Keshri, S.; Malhotra, S.; Naimuddin, M.; Priyanka, P.; Ranjan, K.; Sharma, R.; Bhardwaj, R.; Bharti, M.; Bhattacharya, R.; Bhattacharya, S.; Bhawandeep, U.; Bhowmik, D.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Mondal, K.; Nandan, S.; Purohit, A.; Rout, P. K.; Roy, A.; Roy Chowdhury, S.; Saha, G.; Sarkar, S.; Sharan, M.; Singh, B.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Kumar Verma, Ravindra; Aziz, T.; Bhat, M. A.; Dugad, S.; Mohanty, G. B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhattacharya, S.; Chatterjee, S.; Das, P.; Guchait, M.; Jain, Sa.; Karmakar, S.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sahoo, N.; Sarkar, T.; 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.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Di Florio, A.; Errico, F.; Fiore, L.; Gelmi, A.; Iaselli, G.; Ince, M.; Lezki, S.; 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.; Zito, G.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Borgonovi, L.; Braibant-Giacomelli, S.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Ciocca, C.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Iemmi, F.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Di Mattia, A.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Chatterjee, K.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Latino, G.; Lenzi, P.; Meschini, M.; Paoletti, S.; Russo, L.; Sguazzoni, G.; Strom, D.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Ferro, F.; Ravera, F.; Robutti, E.; Tosi, S.; Benaglia, A.; Beschi, A.; Brianza, L.; Brivio, F.; Ciriolo, V.; Di Guida, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Massironi, A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Tabarelli de Fatis, T.; Zuolo, D.; Buontempo, S.; Cavallo, N.; Di Crescenzo, A.; Fabozzi, F.; Fienga, F.; Galati, G.; Iorio, A. O. M.; Khan, W. A.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Voevodina, E.; Azzi, P.; Bacchetta, N.; Bisello, D.; Boletti, A.; Bragagnolo, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Fanzago, F.; Gasparini, U.; Gozzelino, A.; Hoh, S. Y.; Lacaprara, S.; Lujan, P.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Tiko, A.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Biasini, M.; Bilei, G. M.; Cecchi, C.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Manoni, E.; Mantovani, G.; Mariani, V.; Menichelli, M.; Rossi, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bianchini, L.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Fiori, F.; Giannini, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Manca, E.; Mandorli, G.; Messineo, A.; Palla, F.; Rizzi, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Daci, N.; Del Re, D.; Di Marco, E.; Diemoz, M.; Gelli, S.; Longo, E.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Pandolfi, F.; 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.; Cometti, S.; Costa, M.; Covarelli, R.; 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.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Soldi, D.; Staiano, A.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Vazzoler, F.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. 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.; Goh, J.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Kim, H. S.; 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.; Jeon, D.; 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.; Castaneda Hernandez, A.; Murillo Quijada, J. A.; 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.; Ramirez-Garcia, M.; 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.; Bheesette, S.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Asghar, M. I.; 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.; Traczyk, P.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Araujo, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Galinhas, B.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Nemallapudi, M. V.; Seixas, J.; Strong, G.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Afanasiev, S.; Alexakhin, V.; Bunin, P.; Gavrilenko, M.; Golunov, A.; Golutvin, I.; Gorbounov, N.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sosnov, D.; Sulimov, V.; Uvarov, L.; Vavilov, S.; 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.; Stepennov, A.; Stolin, V.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Chistov, R.; Danilov, M.; Parygin, P.; Philippov, D.; Polikarpov, S.; Tarkovskii, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Rusakov, S. V.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Klyukhin, V.; Kodolova, O.; Korneeva, N.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Perfilov, M.; Savrin, V.; Volkov, P.; Blinov, V.; Dimova, T.; Kardapoltsev, L.; Shtol, D.; Skovpen, Y.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Godizov, A.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Mandrik, P.; Petrov, V.; Ryutin, R.; Slabospitskii, S.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Babaev, A.; Baidali, S.; Okhotnikov, V.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Alcaraz Maestre, J.; Bachiller, I.; Barrio Luna, M.; Brochero Cifuentes, J. A.; Cerrada, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Moran, D.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Redondo, I.; Romero, L.; Soares, M. S.; Triossi, A.; Álvarez Fernández, A.; Albajar, C.; de Trocóniz, J. F.; Cuevas, J.; Erice, C.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Rodríguez Bouza, V.; Sanchez Cruz, S.; Vischia, P.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Chazin Quero, B.; Duarte Campderros, J.; Fernandez, M.; Fernández Manteca, P. J.; Garcia-Ferrero, J.; García Alonso, A.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Martinez Ruiz del Arbol, P.; Matorras, F.; Piedra Gomez, J.; Prieels, C.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Akgun, B.; Auffray, E.; Baillon, P.; Ball, A. H.; Barney, D.; Bendavid, J.; Bianco, M.; Bocci, A.; Botta, C.; Brondolin, E.; Camporesi, T.; Cepeda, M.; Cerminara, G.; Chapon, E.; Chen, Y.; Cucciati, G.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Roeck, A.; Deelen, N.; Dobson, M.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Fallavollita, F.; Fasanella, D.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gilbert, A.; Gill, K.; Glege, F.; Guilbaud, M.; Gulhan, D.; Hegeman, J.; Innocente, V.; Jafari, A.; Janot, P.; Karacheban, O.; Kieseler, J.; Kornmayer, A.; Krammer, M.; Lange, C.; Lecoq, P.; Lourenço, C.; Malgeri, L.; Mannelli, M.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Milenovic, P.; Moortgat, F.; Mulders, M.; Ngadiuba, J.; Orfanelli, S.; Orsini, L.; Pantaleo, F.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pitters, F. 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.; Tosi, M.; Treille, D.; Tsirou, A.; Veckalns, V.; Zeuner, W. D.; 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.; Chernyavskaya, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dorfer, C.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Klijnsma, T.; Lustermann, W.; Manzoni, R. A.; Marionneau, M.; Meinhard, M. T.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Pigazzini, S.; Quittnat, M.; Ruini, D.; 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.; 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.; Hou, W.-S.; Li, Y. y.; Liu, Y. F.; Lu, R.-S.; Paganis, E.; Psallidas, A.; Steen, A.; Asavapibhop, B.; Srimanobhas, N.; Suwonjandee, N.; Bat, A.; Boran, F.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dolek, F.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Isik, C.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Sunar Cerci, D.; Tali, B.; Tok, U. G.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Isildak, B.; Karapinar, G.; Yalvac, M.; Zeyrek, M.; Atakisi, I. O.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Komurcu, Y.; Sen, S.; 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.; Penning, B.; Sakuma, T.; Smith, D.; Smith, V. J.; Taylor, J.; Titterton, A.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; 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.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Komm, M.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Martelli, A.; 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.; Virdee, T.; Wardle, N.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Mackay, C. K.; Morton, A.; Reid, I. D.; Teodorescu, L.; Zahid, S.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Madrid, C.; Mcmaster, B.; Pastika, N.; Smith, C.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Coubez, X.; 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.; Piperov, S.; Sagir, S.; Syarif, R.; Usai, E.; 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.; Kukral, O.; Lander, R.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; 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.; 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.; Wang, S.; Yoo, J.; Anderson, D.; Bornheim, A.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T. Q.; Spiropulu, M.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Sun, M.; 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.; Lykken, J.; Maeshima, K.; 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.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Cadamuro, L.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Gleyzer, S. V.; Joshi, B. M.; Konigsberg, J.; Korytov, A.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Shi, K.; Sperka, D.; Wang, J.; Wang, S.; Joshi, Y. R.; Linn, S.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Schiber, C.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Rahmani, M.; 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.; Mills, C.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Varelas, N.; Wang, H.; Wang, X.; Wu, Z.; Zhang, J.; Alhusseini, M.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Hung, W. T.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Bylinkin, A.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Rogan, C.; Sanders, S.; Schmitz, E.; Tapia Takaki, J. D.; Wang, Q.; Duric, S.; Ivanov, A.; Kaadze, K.; Kim, D.; Maravin, Y.; Mendis, D. R.; Mitchell, T.; 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.; Wong, K.; Abercrombie, D.; Allen, B.; Azzolini, V.; 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.; 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.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kharchilava, A.; Mclean, C.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Barberis, E.; Freer, C.; Hortiangtham, 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.; Lefeld, A.; Ling, T. Y.; Luo, W.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Elmer, P.; Hardenbrook, J.; Higginbotham, S.; Kalogeropoulos, A.; Lange, D.; Lucchini, M. T.; 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.; Gutay, L.; Jones, M.; Jung, A. W.; Khatiwada, A.; Mahakud, B.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xiao, R.; Xie, W.; Cheng, T.; Dolen, J.; Parashar, N.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. 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.; Dulemba, J. L.; Fallon, C.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Taus, R.; 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.; Heideman, J.; Riley, G.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Luo, S.; Mueller, R.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; 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.; Ruiz Alvarez, J. D.; Sheldon, P.; Tuo, S.; Velkovska, J.; Verweij, M.; 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.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Long, K.; Loveless, R.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Woods, N.; CMS Collaboration

    2018-06-01

    The observation of Higgs boson production in association with a top quark-antiquark pair is reported, based on a combined analysis of proton-proton collision data at center-of-mass energies of √{s }=7 , 8, and 13 TeV, corresponding to integrated luminosities of up to 5.1, 19.7, and 35.9 fb-1, respectively. The data were collected with the CMS detector at the CERN LHC. The results of statistically independent searches for Higgs bosons produced in conjunction with a top quark-antiquark pair and decaying to pairs of W bosons, Z bosons, photons, τ leptons, or bottom quark jets are combined to maximize sensitivity. An excess of events is observed, with a significance of 5.2 standard deviations, over the expectation from the background-only hypothesis. The corresponding expected significance from the standard model for a Higgs boson mass of 125.09 GeV is 4.2 standard deviations. The combined best fit signal strength normalized to the standard model prediction is 1.26-0.26+0.31 .

  17. Observation of tt[over ¯]H Production.

    PubMed

    Sirunyan, A M; Tumasyan, A; Adam, W; Ambrogi, F; Asilar, E; Bergauer, T; Brandstetter, J; Dragicevic, M; Erö, J; Escalante Del Valle, A; Flechl, M; Frühwirth, R; Ghete, V M; Hrubec, J; Jeitler, M; Krammer, N; Krätschmer, I; Liko, D; Madlener, T; Mikulec, I; Rad, N; Rohringer, H; Schieck, J; Schöfbeck, R; Spanring, M; Spitzbart, D; Taurok, A; Waltenberger, W; Wittmann, J; Wulz, C-E; Zarucki, M; Chekhovsky, V; Mossolov, V; Suarez Gonzalez, J; De Wolf, E A; Di Croce, D; Janssen, X; Lauwers, J; Pieters, M; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Abu Zeid, S; Blekman, F; D'Hondt, J; De Bruyn, I; De Clercq, J; Deroover, K; Flouris, G; Lontkovskyi, D; Lowette, S; Marchesini, I; Moortgat, S; Moreels, L; Python, Q; Skovpen, K; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Parijs, I; Beghin, D; Bilin, B; Brun, H; Clerbaux, B; De Lentdecker, G; Delannoy, H; Dorney, B; Fasanella, G; Favart, L; Goldouzian, R; Grebenyuk, A; Kalsi, A K; Lenzi, T; Luetic, J; Postiau, N; Starling, E; Thomas, L; Vander Velde, C; Vanlaer, P; Vannerom, D; Wang, Q; Cornelis, T; Dobur, D; Fagot, A; Gul, M; Khvastunov, I; Poyraz, D; Roskas, C; Trocino, D; Tytgat, M; Verbeke, W; Vermassen, B; Vit, M; Zaganidis, N; Bakhshiansohi, H; Bondu, O; Brochet, S; Bruno, G; Caputo, C; David, P; Delaere, C; Delcourt, M; Francois, B; Giammanco, A; Krintiras, G; Lemaitre, V; Magitteri, A; Mertens, A; Musich, M; Piotrzkowski, K; Saggio, A; Vidal Marono, M; Wertz, S; Zobec, J; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Correia Silva, G; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Coelho, E; Da Costa, E M; Da Silveira, G G; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Malbouisson, H; Matos Figueiredo, D; Melo De Almeida, M; Mora Herrera, C; Mundim, L; Nogima, H; Prado Da Silva, W L; Sanchez Rosas, L J; Santoro, A; Sznajder, A; Thiel, M; Tonelli Manganote, E J; Torres Da Silva De Araujo, F; Vilela Pereira, A; Ahuja, S; Bernardes, C A; Calligaris, L; Fernandez Perez Tomei, T R; Gregores, E M; Mercadante, P G; Novaes, S F; Padula, Sandra S; Romero Abad, D; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Marinov, A; Misheva, M; Rodozov, M; Shopova, M; Sultanov, G; Dimitrov, A; Litov, L; Pavlov, B; Petkov, P; Fang, W; Gao, X; Yuan, L; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Chen, Y; Jiang, C H; Leggat, D; Liao, H; Liu, Z; Romeo, F; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Yazgan, E; Zhang, H; Zhao, J; Ban, Y; Chen, G; Levin, A; Li, J; Li, L; Li, Q; Mao, Y; Qian, S J; Wang, D; Xu, Z; Wang, Y; Avila, C; Cabrera, A; Carrillo Montoya, C A; Chaparro Sierra, L F; Florez, C; González Hernández, C F; Segura Delgado, M A; Courbon, B; Godinovic, N; Lelas, D; Puljak, I; Sculac, T; Antunovic, Z; Kovac, M; Brigljevic, V; Ferencek, D; Kadija, K; Mesic, B; Starodumov, A; Susa, T; Ather, M W; Attikis, A; Kolosova, M; Mavromanolakis, G; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Rykaczewski, H; Finger, M; Finger, M; Ayala, E; Carrera Jarrin, E; Abdalla, H; Abdelalim, A A; Mohamed, A; Bhowmik, S; Carvalho Antunes De Oliveira, A; Dewanjee, R K; Ehataht, K; Kadastik, M; Raidal, M; Veelken, C; Eerola, P; Kirschenmann, H; Pekkanen, J; Voutilainen, M; Havukainen, J; Heikkilä, J K; Järvinen, T; Karimäki, V; Kinnunen, R; Lampén, T; Lassila-Perini, K; Laurila, S; Lehti, S; Lindén, T; Luukka, P; Mäenpää, T; Siikonen, H; Tuominen, E; Tuominiemi, J; Tuuva, T; Besancon, M; Couderc, F; Dejardin, M; Denegri, D; Faure, J L; Ferri, F; Ganjour, S; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Leloup, C; Locci, E; Malcles, J; Negro, G; Rander, J; Rosowsky, A; Sahin, M Ö; Titov, M; Abdulsalam, A; Amendola, C; Antropov, I; Beaudette, F; Busson, P; Charlot, C; Granier de Cassagnac, R; Kucher, I; Lobanov, A; Martin Blanco, J; Nguyen, M; Ochando, C; Ortona, G; Pigard, P; Salerno, R; Sauvan, J B; Sirois, Y; Stahl Leiton, A G; Zabi, A; Zghiche, A; Agram, J-L; Andrea, J; Bloch, D; Brom, J-M; Chabert, E C; Cherepanov, V; Collard, C; Conte, E; Fontaine, J-C; Gelé, D; Goerlach, U; Jansová, M; Le Bihan, A-C; Tonon, N; Van Hove, P; Gadrat, S; Beauceron, S; Bernet, C; Boudoul, G; Chanon, N; Chierici, R; Contardo, D; Depasse, P; El Mamouni, H; Fay, J; Finco, L; Gascon, S; Gouzevitch, M; Grenier, G; Ille, B; Lagarde, F; Laktineh, I B; Lattaud, H; Lethuillier, M; Mirabito, L; Pequegnot, A L; Perries, S; Popov, A; Sordini, V; Vander Donckt, M; Viret, S; Zhang, S; Khvedelidze, A; Tsamalaidze, Z; Autermann, C; Feld, L; Kiesel, M K; Klein, K; Lipinski, M; Preuten, M; Rauch, M P; Schomakers, C; Schulz, J; Teroerde, M; Wittmer, B; Zhukov, V; Albert, A; Duchardt, D; Endres, M; Erdmann, M; Esch, T; Fischer, R; Ghosh, S; Güth, A; Hebbeker, T; Heidemann, C; Hoepfner, K; Keller, H; Knutzen, S; Mastrolorenzo, L; Merschmeyer, M; Meyer, A; Millet, P; Mukherjee, S; Pook, T; Radziej, M; Rath, Y; Reithler, H; Rieger, M; Scheuch, F; Schmidt, A; Teyssier, D; Flügge, G; Hlushchenko, O; Kress, T; Künsken, A; Müller, T; Nehrkorn, A; Nowack, A; Pistone, C; Pooth, O; Roy, D; Sert, H; Stahl, A; Aldaya Martin, M; Arndt, T; Asawatangtrakuldee, C; Babounikau, I; Beernaert, K; Behnke, O; Behrens, U; Bermúdez Martínez, A; Bertsche, D; Bin Anuar, A A; Borras, K; Botta, V; Campbell, A; Connor, P; Contreras-Campana, C; Costanza, F; Danilov, V; De Wit, A; Defranchis, M M; Diez Pardos, C; Domínguez Damiani, D; Eckerlin, G; Eichhorn, T; Elwood, A; Eren, E; Gallo, E; Geiser, A; Grados Luyando, J M; Grohsjean, A; Gunnellini, P; Guthoff, M; Haranko, M; Harb, A; Hauk, J; Jung, H; Kasemann, M; Keaveney, J; Kleinwort, C; Knolle, J; Krücker, D; Lange, W; Lelek, A; Lenz, T; Lipka, K; Lohmann, W; Mankel, R; Melzer-Pellmann, I-A; Meyer, A B; Meyer, M; Missiroli, M; Mittag, G; Mnich, J; Myronenko, V; Pflitsch, S K; Pitzl, D; Raspereza, A; Saibel, A; Savitskyi, M; Saxena, P; Schütze, P; Schwanenberger, C; Shevchenko, R; Singh, A; Tholen, H; Turkot, O; Vagnerini, A; Van Onsem, G P; Walsh, R; Wen, Y; Wichmann, K; Wissing, C; Zenaiev, O; Aggleton, R; Bein, S; Benato, L; Benecke, A; Blobel, V; Centis Vignali, M; Dreyer, T; Garutti, E; Gonzalez, D; Haller, J; Hinzmann, A; Karavdina, A; Kasieczka, G; Klanner, R; Kogler, R; Kovalchuk, N; Kurz, S; Kutzner, V; Lange, J; Marconi, D; Multhaup, J; Niedziela, M; Nowatschin, D; Perieanu, A; Reimers, A; Rieger, O; Scharf, C; Schleper, P; Schumann, S; Schwandt, J; Sonneveld, J; Stadie, H; Steinbrück, G; Stober, F M; Stöver, M; Troendle, D; Vanhoefer, A; Vormwald, B; Akbiyik, M; Barth, C; Baselga, M; Baur, S; Butz, E; Caspart, R; Chwalek, T; Colombo, F; De Boer, W; Dierlamm, A; El Morabit, K; Faltermann, N; Freund, B; Giffels, M; Harrendorf, M A; Hartmann, F; Heindl, S M; Husemann, U; Kassel, F; Katkov, I; Keicher, P; Kudella, S; Mildner, H; Mitra, S; Mozer, M U; Müller, Th; Plagge, M; Quast, G; Rabbertz, K; Schröder, M; Shvetsov, I; Sieber, G; Simonis, H J; Ulrich, R; Wayand, S; Waßmer, M; Weber, M; Weiler, T; Williamson, S; Wöhrmann, C; Wolf, R; Anagnostou, G; Daskalakis, G; Geralis, T; Kyriakis, A; Loukas, D; Paspalaki, G; Topsis-Giotis, I; Karathanasis, G; Kesisoglou, S; Kontaxakis, P; Panagiotou, A; Papavergou, I; Saoulidou, N; Tziaferi, E; Vellidis, K; Kousouris, K; Papakrivopoulos, I; Tsipolitis, G; Evangelou, I; Foudas, C; Gianneios, P; Katsoulis, P; Kokkas, P; Mallios, S; Manthos, N; Papadopoulos, I; Paradas, E; Strologas, J; Triantis, F A; Tsitsonis, D; Bartók, M; Csanad, M; Filipovic, N; Major, P; Nagy, M I; Pasztor, G; Surányi, O; Veres, G I; Bencze, G; Hajdu, C; Horvath, D; Hunyadi, Á; Sikler, F; Veszpremi, V; Vesztergombi, G; Vámi, T Á; Beni, N; Czellar, S; Karancsi, J; Makovec, A; Molnar, J; Szillasi, Z; Raics, P; Trocsanyi, Z L; Ujvari, B; Choudhury, S; Komaragiri, J R; Tiwari, P C; Bahinipati, S; Kar, C; Mal, P; Mandal, K; Nayak, A; Sahoo, D K; Swain, S K; Bansal, S; Beri, S B; Bhatnagar, V; Chauhan, S; Chawla, R; Dhingra, N; Gupta, R; Kaur, A; Kaur, A; Kaur, M; Kaur, S; Kumar, R; Kumari, P; Lohan, M; Mehta, A; Sandeep, K; Sharma, S; Singh, J B; Walia, G; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A; Choudhary, B C; Garg, R B; Gola, M; Keshri, S; Malhotra, S; Naimuddin, M; Priyanka, P; Ranjan, K; Sharma, R; Bhardwaj, R; Bharti, M; Bhattacharya, R; Bhattacharya, S; Bhawandeep, U; Bhowmik, D; Dey, S; Dutt, S; Dutta, S; Ghosh, S; Mondal, K; Nandan, S; Purohit, A; Rout, P K; Roy, A; Roy Chowdhury, S; Saha, G; Sarkar, S; Sharan, M; Singh, B; Thakur, S; Behera, P K; Chudasama, R; Dutta, D; Jha, V; Kumar, V; Netrakanti, P K; Pant, L M; Shukla, P; Kumar Verma, Ravindra; Aziz, T; Bhat, M A; Dugad, S; Mohanty, G B; Sur, N; Sutar, B; Banerjee, S; Bhattacharya, S; Chatterjee, S; Das, P; Guchait, M; Jain, Sa; Karmakar, S; Kumar, S; Maity, M; Majumder, G; Mazumdar, K; Sahoo, N; Sarkar, T; 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; Rezaei Hosseinabadi, F; Safarzadeh, B; Zeinali, M; Felcini, M; Grunewald, M; Abbrescia, M; Calabria, C; Colaleo, A; Creanza, D; Cristella, L; De Filippis, N; De Palma, M; Di Florio, A; Errico, F; Fiore, L; Gelmi, A; Iaselli, G; Ince, M; Lezki, S; 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; Zito, G; Abbiendi, G; Battilana, C; Bonacorsi, D; Borgonovi, L; Braibant-Giacomelli, S; Campanini, R; Capiluppi, P; Castro, A; Cavallo, F R; Chhibra, S S; Ciocca, C; Codispoti, G; Cuffiani, M; Dallavalle, G M; Fabbri, F; Fanfani, A; Giacomelli, P; Grandi, C; Guiducci, L; Iemmi, F; Marcellini, S; Masetti, G; Montanari, A; Navarria, F L; Perrotta, A; Primavera, F; Rossi, A M; Rovelli, T; Siroli, G P; Tosi, N; Albergo, S; Di Mattia, A; Potenza, R; Tricomi, A; Tuve, C; Barbagli, G; Chatterjee, K; Ciulli, V; Civinini, C; D'Alessandro, R; Focardi, E; Latino, G; Lenzi, P; Meschini, M; Paoletti, S; Russo, L; Sguazzoni, G; Strom, D; Viliani, L; Benussi, L; Bianco, S; Fabbri, F; Piccolo, D; Ferro, F; Ravera, F; Robutti, E; Tosi, S; Benaglia, A; Beschi, A; Brianza, L; Brivio, F; Ciriolo, V; Di Guida, S; Dinardo, M E; Fiorendi, S; Gennai, S; Ghezzi, A; Govoni, P; Malberti, M; Malvezzi, S; Massironi, A; Menasce, D; Moroni, L; Paganoni, M; Pedrini, D; Ragazzi, S; Tabarelli de Fatis, T; Zuolo, D; Buontempo, S; Cavallo, N; Di Crescenzo, A; Fabozzi, F; Fienga, F; Galati, G; Iorio, A O M; Khan, W A; Lista, L; Meola, S; Paolucci, P; Sciacca, C; Voevodina, E; Azzi, P; Bacchetta, N; Bisello, D; Boletti, A; Bragagnolo, A; Carlin, R; Checchia, P; Dall'Osso, M; De Castro Manzano, P; Dorigo, T; Fanzago, F; Gasparini, U; Gozzelino, A; Hoh, S Y; Lacaprara, S; Lujan, P; Margoni, M; Meneguzzo, A T; Pazzini, J; Pozzobon, N; Ronchese, P; Rossin, R; Simonetto, F; Tiko, A; Torassa, E; Zanetti, M; Zotto, P; Zumerle, G; Braghieri, A; Magnani, A; Montagna, P; Ratti, S P; Re, V; Ressegotti, M; Riccardi, C; Salvini, P; Vai, I; Vitulo, P; Alunni Solestizi, L; Biasini, M; Bilei, G M; Cecchi, C; Ciangottini, D; Fanò, L; Lariccia, P; Leonardi, R; Manoni, E; Mantovani, G; Mariani, V; Menichelli, M; Rossi, A; Santocchia, A; Spiga, D; Androsov, K; Azzurri, P; Bagliesi, G; Bianchini, L; Boccali, T; Borrello, L; Castaldi, R; Ciocci, M A; Dell'Orso, R; Fedi, G; Fiori, F; Giannini, L; Giassi, A; Grippo, M T; Ligabue, F; Manca, E; Mandorli, G; Messineo, A; Palla, F; Rizzi, A; Spagnolo, P; Tenchini, R; Tonelli, G; Venturi, A; Verdini, P G; Barone, L; Cavallari, F; Cipriani, M; Daci, N; Del Re, D; Di Marco, E; Diemoz, M; Gelli, S; Longo, E; Marzocchi, B; Meridiani, P; Organtini, G; Pandolfi, F; 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; Cometti, S; Costa, M; Covarelli, R; 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; Romero, A; Ruspa, M; Sacchi, R; Shchelina, K; Sola, V; Solano, A; Soldi, D; Staiano, A; Belforte, S; Candelise, V; Casarsa, M; Cossutti, F; Della Ricca, G; Vazzoler, F; Zanetti, A; Kim, D H; Kim, G N; Kim, M 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; Goh, J; Kim, T J; Cho, S; Choi, S; Go, Y; Gyun, D; Ha, S; Hong, B; Jo, Y; Lee, K; Lee, K S; Lee, S; Lim, J; Park, S K; Roh, Y; Kim, H S; 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; Jeon, D; 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; Castaneda Hernandez, A; Murillo Quijada, J A; 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; Ramirez-Garcia, M; 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; Bheesette, S; Butler, P H; Ahmad, A; Ahmad, M; Asghar, M I; 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; Traczyk, P; Zalewski, P; Bunkowski, K; Byszuk, A; Doroba, K; Kalinowski, A; Konecki, M; Krolikowski, J; Misiura, M; Olszewski, M; Pyskir, A; Walczak, M; Araujo, M; Bargassa, P; Beirão Da Cruz E Silva, C; Di Francesco, A; Faccioli, P; Galinhas, B; Gallinaro, M; Hollar, J; Leonardo, N; Nemallapudi, M V; Seixas, J; Strong, G; Toldaiev, O; Vadruccio, D; Varela, J; Afanasiev, S; Alexakhin, V; Bunin, P; Gavrilenko, M; Golunov, A; Golutvin, I; Gorbounov, N; Karjavin, V; Lanev, A; Malakhov, A; Matveev, V; Moisenz, P; Palichik, V; Perelygin, V; Savina, M; Shmatov, S; Smirnov, V; Voytishin, N; Zarubin, A; Golovtsov, V; Ivanov, Y; Kim, V; Kuznetsova, E; Levchenko, P; Murzin, V; Oreshkin, V; Smirnov, I; Sosnov, D; Sulimov, V; Uvarov, L; Vavilov, S; 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; Stepennov, A; Stolin, V; Toms, M; Vlasov, E; Zhokin, A; Aushev, T; Chistov, R; Danilov, M; Parygin, P; Philippov, D; Polikarpov, S; Tarkovskii, E; Andreev, V; Azarkin, M; Dremin, I; Kirakosyan, M; Rusakov, S V; Terkulov, A; Baskakov, A; Belyaev, A; Boos, E; Bunichev, V; Dubinin, M; Dudko, L; Klyukhin, V; Kodolova, O; Korneeva, N; Lokhtin, I; Miagkov, I; Obraztsov, S; Perfilov, M; Savrin, V; Volkov, P; Blinov, V; Dimova, T; Kardapoltsev, L; Shtol, D; Skovpen, Y; Azhgirey, I; Bayshev, I; Bitioukov, S; Elumakhov, D; Godizov, A; Kachanov, V; Kalinin, A; Konstantinov, D; Mandrik, P; Petrov, V; Ryutin, R; Slabospitskii, S; Sobol, A; Troshin, S; Tyurin, N; Uzunian, A; Volkov, A; Babaev, A; Baidali, S; Okhotnikov, V; Adzic, P; Cirkovic, P; Devetak, D; Dordevic, M; Milosevic, J; Alcaraz Maestre, J; Bachiller, I; Barrio Luna, M; Brochero Cifuentes, J A; Cerrada, M; Colino, N; De La Cruz, B; Delgado Peris, A; Fernandez Bedoya, C; Fernández Ramos, J P; Flix, J; Fouz, M C; Gonzalez Lopez, O; Goy Lopez, S; Hernandez, J M; Josa, M I; Moran, D; Pérez-Calero Yzquierdo, A; Puerta Pelayo, J; Redondo, I; Romero, L; Soares, M S; Triossi, A; Álvarez Fernández, A; Albajar, C; de Trocóniz, J F; Cuevas, J; Erice, C; Fernandez Menendez, J; Folgueras, S; Gonzalez Caballero, I; González Fernández, J R; Palencia Cortezon, E; Rodríguez Bouza, V; Sanchez Cruz, S; Vischia, P; Vizan Garcia, J M; Cabrillo, I J; Calderon, A; Chazin Quero, B; Duarte Campderros, J; Fernandez, M; Fernández Manteca, P J; Garcia-Ferrero, J; García Alonso, A; Gomez, G; Lopez Virto, A; Marco, J; Martinez Rivero, C; Martinez Ruiz Del Arbol, P; Matorras, F; Piedra Gomez, J; Prieels, C; Rodrigo, T; Ruiz-Jimeno, A; Scodellaro, L; Trevisani, N; Vila, I; Vilar Cortabitarte, R; Abbaneo, D; Akgun, B; Auffray, E; Baillon, P; Ball, A H; Barney, D; Bendavid, J; Bianco, M; Bocci, A; Botta, C; Brondolin, E; Camporesi, T; Cepeda, M; Cerminara, G; Chapon, E; Chen, Y; Cucciati, G; d'Enterria, D; Dabrowski, A; Daponte, V; David, A; De Roeck, A; Deelen, N; Dobson, M; Dünser, M; Dupont, N; Elliott-Peisert, A; Everaerts, P; Fallavollita, F; Fasanella, D; Franzoni, G; Fulcher, J; Funk, W; Gigi, D; Gilbert, A; Gill, K; Glege, F; Guilbaud, M; Gulhan, D; Hegeman, J; Innocente, V; Jafari, A; Janot, P; Karacheban, O; Kieseler, J; Kornmayer, A; Krammer, M; Lange, C; Lecoq, P; Lourenço, C; Malgeri, L; Mannelli, M; Meijers, F; Merlin, J A; Mersi, S; Meschi, E; Milenovic, P; Moortgat, F; Mulders, M; Ngadiuba, J; Orfanelli, S; Orsini, L; Pantaleo, F; Pape, L; Perez, E; Peruzzi, M; Petrilli, A; Petrucciani, G; Pfeiffer, A; Pierini, M; Pitters, F 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; Tosi, M; Treille, D; Tsirou, A; Veckalns, V; Zeuner, W D; 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; Chernyavskaya, N; Dissertori, G; Dittmar, M; Donegà, M; Dorfer, C; Grab, C; Heidegger, C; Hits, D; Hoss, J; Klijnsma, T; Lustermann, W; Manzoni, R A; Marionneau, M; Meinhard, M T; Micheli, F; Musella, P; Nessi-Tedaldi, F; Pata, J; Pauss, F; Perrin, G; Perrozzi, L; Pigazzini, S; Quittnat, M; Ruini, D; 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; 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; Hou, W-S; Li, Y Y; Liu, Y F; Lu, R-S; Paganis, E; Psallidas, A; Steen, A; Asavapibhop, B; Srimanobhas, N; Suwonjandee, N; Bat, A; Boran, F; Cerci, S; Damarseckin, S; Demiroglu, Z S; Dolek, F; Dozen, C; Dumanoglu, I; Girgis, S; Gokbulut, G; Guler, Y; Gurpinar, E; Hos, I; Isik, C; Kangal, E E; Kara, O; Kayis Topaksu, A; Kiminsu, U; Oglakci, M; Onengut, G; Ozdemir, K; Ozturk, S; Sunar Cerci, D; Tali, B; Tok, U G; Turkcapar, S; Zorbakir, I S; Zorbilmez, C; Isildak, B; Karapinar, G; Yalvac, M; Zeyrek, M; Atakisi, I O; Gülmez, E; Kaya, M; Kaya, O; Tekten, S; Yetkin, E A; Agaras, M N; Atay, S; Cakir, A; Cankocak, K; Komurcu, Y; Sen, S; 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; Penning, B; Sakuma, T; Smith, D; Smith, V J; Taylor, J; Titterton, A; Bell, K W; Belyaev, A; Brew, C; Brown, R M; 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; Haddad, Y; Hall, G; Iles, G; James, T; Komm, M; Laner, C; Lyons, L; Magnan, A-M; Malik, S; Martelli, A; 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; Virdee, T; Wardle, N; Winterbottom, D; Wright, J; Zenz, S C; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Mackay, C K; Morton, A; Reid, I D; Teodorescu, L; Zahid, S; Call, K; Dittmann, J; Hatakeyama, K; Liu, H; Madrid, C; Mcmaster, B; Pastika, N; Smith, C; Bartek, R; Dominguez, A; Buccilli, A; Cooper, S I; Henderson, C; Rumerio, P; West, C; Arcaro, D; Bose, T; Gastler, D; Rankin, D; Richardson, C; Rohlf, J; Sulak, L; Zou, D; Benelli, G; Coubez, X; 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; Piperov, S; Sagir, S; Syarif, R; Usai, E; 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; Kukral, O; Lander, R; Mulhearn, M; Pellett, D; Pilot, J; Shalhout, S; Shi, M; 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; 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; Wang, S; Yoo, J; Anderson, D; Bornheim, A; Lawhorn, J M; Newman, H B; Nguyen, T Q; Spiropulu, M; Vlimant, J R; Wilkinson, R; Xie, S; Zhang, Z; Zhu, R Y; Andrews, M B; Ferguson, T; Mudholkar, T; Paulini, M; Sun, M; 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; Lykken, J; Maeshima, K; 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; Acosta, D; Avery, P; Bortignon, P; Bourilkov, D; Brinkerhoff, A; Cadamuro, L; Carnes, A; Carver, M; Curry, D; Field, R D; Gleyzer, S V; Joshi, B M; Konigsberg, J; Korytov, A; Ma, P; Matchev, K; Mei, H; Mitselmakher, G; Shi, K; Sperka, D; Wang, J; Wang, S; Joshi, Y R; Linn, S; Ackert, A; Adams, T; Askew, A; Hagopian, S; Hagopian, V; Johnson, K F; Kolberg, T; Martinez, G; Perry, T; Prosper, H; Saha, A; Schiber, C; Sharma, V; Yohay, R; Baarmand, M M; Bhopatkar, V; Colafranceschi, S; Hohlmann, M; Noonan, D; Rahmani, M; 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; Mills, C; Sandoval Gonzalez, I D; Tonjes, M B; Varelas, N; Wang, H; Wang, X; Wu, Z; Zhang, J; Alhusseini, M; Bilki, B; Clarida, W; Dilsiz, K; Durgut, S; Gandrajula, R P; Haytmyradov, M; Khristenko, V; Merlo, J-P; Mestvirishvili, A; Moeller, A; Nachtman, J; Ogul, H; Onel, Y; Ozok, F; Penzo, A; Snyder, C; Tiras, E; Wetzel, J; Blumenfeld, B; Cocoros, A; Eminizer, N; Fehling, D; Feng, L; Gritsan, A V; Hung, W T; Maksimovic, P; Roskes, J; Sarica, U; Swartz, M; Xiao, M; You, C; Al-Bataineh, A; Baringer, P; Bean, A; Boren, S; Bowen, J; Bylinkin, A; Castle, J; Khalil, S; Kropivnitskaya, A; Majumder, D; Mcbrayer, W; Murray, M; Rogan, C; Sanders, S; Schmitz, E; Tapia Takaki, J D; Wang, Q; Duric, S; Ivanov, A; Kaadze, K; Kim, D; Maravin, Y; Mendis, D R; Mitchell, T; 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; Wong, K; Abercrombie, D; Allen, B; Azzolini, V; 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; 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; Godshalk, A; Harrington, C; Iashvili, I; Kharchilava, A; Mclean, C; Nguyen, D; Parker, A; Rappoccio, S; Roozbahani, B; Barberis, E; Freer, C; Hortiangtham, 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; Lefeld, A; Ling, T Y; Luo, W; Winer, B L; Wulsin, H W; Cooperstein, S; Elmer, P; Hardenbrook, J; Higginbotham, S; Kalogeropoulos, A; Lange, D; Lucchini, M T; 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; Gutay, L; Jones, M; Jung, A W; Khatiwada, A; Mahakud, B; Miller, D H; Neumeister, N; Peng, C C; Qiu, H; Schulte, J F; Sun, J; Wang, F; Xiao, R; Xie, W; Cheng, T; Dolen, J; Parashar, N; Chen, Z; Ecklund, K M; Freed, S; Geurts, F J 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; Dulemba, J L; Fallon, C; Ferbel, T; Galanti, M; Garcia-Bellido, A; Han, J; Hindrichs, O; Khukhunaishvili, A; Lo, K H; Tan, P; Taus, R; 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; Heideman, J; Riley, G; Spanier, S; Thapa, K; Bouhali, O; Celik, A; Dalchenko, M; De Mattia, M; Delgado, A; Dildick, S; Eusebi, R; Gilmore, J; Huang, T; Kamon, T; Luo, S; Mueller, R; Patel, R; Perloff, A; Perniè, L; Rathjens, D; Safonov, A; Akchurin, N; Damgov, J; De Guio, F; Dudero, P R; 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; Ruiz Alvarez, J D; Sheldon, P; Tuo, S; Velkovska, J; Verweij, M; 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; Gomber, B; Grothe, M; Herndon, M; Hervé, A; Hussain, U; Klabbers, P; Lanaro, A; Long, K; Loveless, R; Ruggles, T; Savin, A; Smith, N; Smith, W H; Woods, N

    2018-06-08

    The observation of Higgs boson production in association with a top quark-antiquark pair is reported, based on a combined analysis of proton-proton collision data at center-of-mass energies of sqrt[s]=7, 8, and 13 TeV, corresponding to integrated luminosities of up to 5.1, 19.7, and 35.9  fb^{-1}, respectively. The data were collected with the CMS detector at the CERN LHC. The results of statistically independent searches for Higgs bosons produced in conjunction with a top quark-antiquark pair and decaying to pairs of W bosons, Z bosons, photons, τ leptons, or bottom quark jets are combined to maximize sensitivity. An excess of events is observed, with a significance of 5.2 standard deviations, over the expectation from the background-only hypothesis. The corresponding expected significance from the standard model for a Higgs boson mass of 125.09 GeV is 4.2 standard deviations. The combined best fit signal strength normalized to the standard model prediction is 1.26_{-0.26}^{+0.31}.

  18. Standard deviation and standard error of the mean.

    PubMed

    Lee, Dong Kyu; In, Junyong; Lee, Sangseok

    2015-06-01

    In most clinical and experimental studies, the standard deviation (SD) and the estimated standard error of the mean (SEM) are used to present the characteristics of sample data and to explain statistical analysis results. However, some authors occasionally muddle the distinctive usage between the SD and SEM in medical literature. Because the process of calculating the SD and SEM includes different statistical inferences, each of them has its own meaning. SD is the dispersion of data in a normal distribution. In other words, SD indicates how accurately the mean represents sample data. However the meaning of SEM includes statistical inference based on the sampling distribution. SEM is the SD of the theoretical distribution of the sample means (the sampling distribution). While either SD or SEM can be applied to describe data and statistical results, one should be aware of reasonable methods with which to use SD and SEM. We aim to elucidate the distinctions between SD and SEM and to provide proper usage guidelines for both, which summarize data and describe statistical results.

  19. Standard deviation and standard error of the mean

    PubMed Central

    In, Junyong; Lee, Sangseok

    2015-01-01

    In most clinical and experimental studies, the standard deviation (SD) and the estimated standard error of the mean (SEM) are used to present the characteristics of sample data and to explain statistical analysis results. However, some authors occasionally muddle the distinctive usage between the SD and SEM in medical literature. Because the process of calculating the SD and SEM includes different statistical inferences, each of them has its own meaning. SD is the dispersion of data in a normal distribution. In other words, SD indicates how accurately the mean represents sample data. However the meaning of SEM includes statistical inference based on the sampling distribution. SEM is the SD of the theoretical distribution of the sample means (the sampling distribution). While either SD or SEM can be applied to describe data and statistical results, one should be aware of reasonable methods with which to use SD and SEM. We aim to elucidate the distinctions between SD and SEM and to provide proper usage guidelines for both, which summarize data and describe statistical results. PMID:26045923

  20. 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…

  1. 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...

  2. Panama Canal Fog Navigation Study : Candidate System Definition

    DOT National Transportation Integrated Search

    1984-01-01

    A candidate system for solving fog navigation problems in the Panama Canal is defined. The vessel monitoring subsystem is a shore-based, all-weather, precision ranging system with ranging accuracies of 9 feet (2 standard deviations, 95 percent).

  3. Impact of combustion products from Space Shuttle launches on ambient air quality

    NASA Technical Reports Server (NTRS)

    Dumbauld, R. K.; Bowers, J. F.; Cramer, H. E.

    1974-01-01

    The present work describes some multilayer diffusion models and a computer program for these models developed to predict the impact of ground clouds formed during Space Shuttle launches on ambient air quality. The diffusion models are based on the Gaussian plume equation for an instantaneous volume source. Cloud growth is estimated on the basis of measurable meteorological parameters: standard deviation of the wind azimuth angle, standard deviation of wind elevation angle, vertical wind-speed shear, vertical wind-direction shear, and depth of the surface mixing layer. Calculations using these models indicate that Space Shuttle launches under a variety of meteorological regimes at Kennedy Space Center and Vandenberg AFB are unlikely to endanger the exposure standards for HCl; similar results have been obtained for CO and Al2O3. However, the possibility that precipitation scavenging of the ground cloud might result in an acidic rain that could damage vegetation has not been investigated.

  4. A statistical analysis of energy and power demand for the tractive purposes of an electric vehicle in urban traffic - an analysis of a short and long observation period

    NASA Astrophysics Data System (ADS)

    Slaski, G.; Ohde, B.

    2016-09-01

    The article presents the results of a statistical dispersion analysis of an energy and power demand for tractive purposes of a battery electric vehicle. The authors compare data distribution for different values of an average speed in two approaches, namely a short and long period of observation. The short period of observation (generally around several hundred meters) results from a previously proposed macroscopic energy consumption model based on an average speed per road section. This approach yielded high values of standard deviation and coefficient of variation (the ratio between standard deviation and the mean) around 0.7-1.2. The long period of observation (about several kilometers long) is similar in length to standardized speed cycles used in testing a vehicle energy consumption and available range. The data were analysed to determine the impact of observation length on the energy and power demand variation. The analysis was based on a simulation of electric power and energy consumption performed with speed profiles data recorded in Poznan agglomeration.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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).

  12. 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...

  13. 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...

  14. 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

  15. Using an external gating signal to estimate noise in PET with an emphasis on tracer avid tumors

    NASA Astrophysics Data System (ADS)

    Schmidtlein, C. R.; Beattie, B. J.; Bailey, D. L.; Akhurst, T. J.; Wang, W.; Gönen, M.; Kirov, A. S.; Humm, J. L.

    2010-10-01

    The purpose of this study is to establish and validate a methodology for estimating the standard deviation of voxels with large activity concentrations within a PET image using replicate imaging that is immediately available for use in the clinic. To do this, ensembles of voxels in the averaged replicate images were compared to the corresponding ensembles in images derived from summed sinograms. In addition, the replicate imaging noise estimate was compared to a noise estimate based on an ensemble of voxels within a region. To make this comparison two phantoms were used. The first phantom was a seven-chamber phantom constructed of 1 liter plastic bottles. Each chamber of this phantom was filled with a different activity concentration relative to the lowest activity concentration with ratios of 1:1, 1:1, 2:1, 2:1, 4:1, 8:1 and 16:1. The second phantom was a GE Well-Counter phantom. These phantoms were imaged and reconstructed on a GE DSTE PET/CT scanner with 2D and 3D reprojection filtered backprojection (FBP), and with 2D- and 3D-ordered subset expectation maximization (OSEM). A series of tests were applied to the resulting images that showed that the region and replicate imaging methods for estimating standard deviation were equivalent for backprojection reconstructions. Furthermore, the noise properties of the FBP algorithms allowed scaling the replicate estimates of the standard deviation by a factor of 1/\\sqrt{N}, where N is the number of replicate images, to obtain the standard deviation of the full data image. This was not the case for OSEM image reconstruction. Due to nonlinearity of the OSEM algorithm, the noise is shown to be both position and activity concentration dependent in such a way that no simple scaling factor can be used to extrapolate noise as a function of counts. The use of the Well-Counter phantom contributed to the development of a heuristic extrapolation of the noise as a function of radius in FBP. In addition, the signal-to-noise ratio for high uptake objects was confirmed to be higher with backprojection image reconstruction methods. These techniques were applied to several patient data sets acquired in either 2D or 3D mode, with 18F (FLT and FDG). Images of the standard deviation and signal-to-noise ratios were constructed and the standard deviations of the tumors' uptake were determined. Finally, a radial noise extrapolation relationship deduced in this paper was applied to patient data.

  16. SU-F-T-547: Off-Isocenter Winston-Lutz Test for Stereotactic Radiosurgery/stereotactic Body Radiotherapy

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

    Gao, J; Liu, X

    2016-06-15

    Purpose: To perform a quantitative study to verify that the mechanical field center coincides with the radiation field center when both are off from the isocenter during the single-isocenter technique in linear accelerator-based SRS/SBRT procedure to treat multiple lesions. Methods: We developed an innovative method to measure this accuracy, called the off-isocenter Winston-Lutz test, and here we provide a practical clinical guideline to implement this technique. We used ImagePro V.6 to analyze images of a Winston-Lutz phantom obtained using a Varian 21EX linear accelerator with an electronic portal imaging device, set up as for single-isocenter SRS/SBRT for multiple lesions. Wemore » investigated asymmetry field centers that were 3 cm and 5 cm away from the isocenter, as well as performing the standard Winston-Lutz test. We used a special beam configuration to acquire images while avoiding collision, and we investigated both jaw and multileaf collimation. Results: For the jaw collimator setting, at 3 cm off-isocenter, the mechanical field deviated from the radiation field by about 2.5 mm; at 5 cm, the deviation was above 3 mm, up to 4.27 mm. For the multileaf collimator setting, at 3 cm off-isocenter, the deviation was below 1 mm; at 5 cm, the deviation was above 1 mm, up to 1.72 mm, which is 72% higher than the tolerance threshold. Conclusion: These results indicated that the further the asymmetry field center is from the machine isocenter, the larger the deviation of the mechanical field from the radiation field, and the distance between the center of the asymmetry field and the isocenter should not exceed 3 cm in of our clinic. We recommend that every clinic that uses linear accelerator, multileaf collimator-based SRS/SBRT perform the off-isocenter Winston-Lutz test in addition to the standard Winston-Lutz test and use their own deviation data to design the treatment plan.« less

  17. 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.

  18. Bias atlases for segmentation-based PET attenuation correction using PET-CT and MR.

    PubMed

    Ouyang, Jinsong; Chun, Se Young; Petibon, Yoann; Bonab, Ali A; Alpert, Nathaniel; Fakhri, Georges El

    2013-10-01

    This study was to obtain voxel-wise PET accuracy and precision using tissue-segmentation for attenuation correction. We applied multiple thresholds to the CTs of 23 patients to classify tissues. For six of the 23 patients, MR images were also acquired. The MR fat/in-phase ratio images were used for fat segmentation. Segmented tissue classes were used to create attenuation maps, which were used for attenuation correction in PET reconstruction. PET bias images were then computed using the PET reconstructed with the original CT as the reference. We registered the CTs for all the patients and transformed the corresponding bias images accordingly. We then obtained the mean and standard deviation bias atlas using all the registered bias images. Our CT-based study shows that four-class segmentation (air, lungs, fat, other tissues), which is available on most PET-MR scanners, yields 15.1%, 4.1%, 6.6%, and 12.9% RMSE bias in lungs, fat, non-fat soft-tissues, and bones, respectively. An accurate fat identification is achievable using fat/in-phase MR images. Furthermore, we have found that three-class segmentation (air, lungs, other tissues) yields less than 5% standard deviation of bias within the heart, liver, and kidneys. This implies that three-class segmentation can be sufficient to achieve small variation of bias for imaging these three organs. Finally, we have found that inter- and intra-patient lung density variations contribute almost equally to the overall standard deviation of bias within the lungs.

  19. Differences between genomic-based and pedigree-based relationships in a chicken population, as a function of quality control and pedigree links among individuals.

    PubMed

    Wang, H; Misztal, I; Legarra, A

    2014-12-01

    This work studied differences between expected (calculated from pedigree) and realized (genomic, from markers) relationships in a real population, the influence of quality control on these differences, and their fit to current theory. Data included 4940 pure line chickens across five generations genotyped for 57,636 SNP. Pedigrees (5762 animals) were available for the five generations, pedigree starting on the first one. Three levels of quality control were used. With no quality control, mean difference between realized and expected relationships for different type of relationships was ≤ 0.04 with standard deviation ≤ 0.10. With strong quality control (call rate ≥ 0.9, parent-progeny conflicts, minor allele frequency and use of only autosomal chromosomes), these numbers reduced to ≤ 0.02 and ≤ 0.04, respectively. While the maximum difference was 1.02 with the complete data, it was only 0.18 with the latest three generations of genotypes (but including all pedigrees). Variation of expected minus realized relationships agreed with theoretical developments and suggests an effective number of loci of 70 for this population. When the pedigree is complete and as deep as the genotypes, the standard deviation of difference between the expected and realized relationships is around 0.04, all categories confounded. Standard deviation of differences larger than 0.10 suggests bad quality control, mistakes in pedigree recording or genotype labelling, or insufficient depth of pedigree. © 2014 Blackwell Verlag GmbH.

  20. Measurement of top quark-antiquark pair production in association with a W or Z boson in pp collisions at √s=8 TeV

    DOE PAGES

    Khachatryan, Vardan

    2014-09-17

    The measurement of a cross section for the production of top quark–antiquark pairs (tt¯) in association with a vector boson V (W or Z) in proton-proton collisions at √s=8 TeV is presented. The results are based on a dataset corresponding to an integrated luminosity of 19.5 fb -1 recorded with the CMS detector at the LHC. The measurement is performed in three leptonic (e and μ) channels: a same-sign dilepton analysis targeting tt¯W events, and trilepton and four-lepton analyses designed for tt¯Z events. In the same-sign dilepton channel, the tt¯W cross section is measured as σ tt¯W=170 +90 -80(stat)±70(syst)fb, correspondingmore » to a significance of 1.6 standard deviations over the background-only hypothesis. Combining the trilepton and four-lepton channels, a direct measurement of the tt¯Z cross section, σ tt¯Z=200 +80 -70(stat) +40 -30(syst)fb -1, is obtained with a significance of 3.1 standard deviations. Finally, the measured cross sections are compatible with standard model predictions within their experimental uncertainties. The inclusive tt¯V process is observed with a significance of 3.7 standard deviations from the combination of all three leptonic channels.« less

  1. Mars Global Reference Atmospheric Model (Mars-GRAM) and Database for Mission Design

    NASA Technical Reports Server (NTRS)

    Justus, C. G.; Duvall, Aleta; Johnson, D. L.

    2003-01-01

    Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model, while above 80 km it is based on Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiting Laser Altimeter. Validation studies are described comparing Mars-GRAM with Mars Global Surveyor Radio Science and Thermal Emission Spectrometer data. RS data from 2480 profiles were used, covering latitudes 75 deg S to 72 deg N, surface to approximately 40 km, for seasons ranging from areocentric longitude of Sun (Ls) = 70-160 deg and 265-310 deg. RS data spanned a range of local times, mostly 0-9 hours and 18-24 hours. For interests in aerocapture and precision landing, comparisons concentrated on atmospheric density. At a fixed height of 20 km, RS density varied by about a factor of 2.5 over ranges of latitudes and Ls values observed. Evaluated at matching positions and times, these figures show average RSMars-GRAM density ratios were generally 1+/-)0.05, except at heights above approximately 25 km and latitudes above approximately 50 deg N. Average standard deviation of RSMars-GRAM density ratio was 6%. TES data were used covering surface to approximately 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of a Mars global dust storm). Depending on season, TES data covered latitudes 85 deg S to 85 deg N. Most TES data were concentrated near local times 2 hours and 14 hours. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (greater than 45 deg N), or at most altitudes in the southern hemisphere at Ls approximately 90 and 180 deg. Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approximately 2.5% for all data, or approximately 1-4%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for local time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about three times the standard deviation of TES data about the TES mean value at a given position and season.

  2. Does standard deviation matter? Using "standard deviation" to quantify security of multistage testing.

    PubMed

    Wang, Chun; Zheng, Yi; Chang, Hua-Hua

    2014-01-01

    With the advent of web-based technology, online testing is becoming a mainstream mode in large-scale educational assessments. Most online tests are administered continuously in a testing window, which may post test security problems because examinees who take the test earlier may share information with those who take the test later. Researchers have proposed various statistical indices to assess the test security, and one most often used index is the average test-overlap rate, which was further generalized to the item pooling index (Chang & Zhang, 2002, 2003). These indices, however, are all defined as the means (that is, the expected proportion of common items among examinees) and they were originally proposed for computerized adaptive testing (CAT). Recently, multistage testing (MST) has become a popular alternative to CAT. The unique features of MST make it important to report not only the mean, but also the standard deviation (SD) of test overlap rate, as we advocate in this paper. The standard deviation of test overlap rate adds important information to the test security profile, because for the same mean, a large SD reflects that certain groups of examinees share more common items than other groups. In this study, we analytically derived the lower bounds of the SD under MST, with the results under CAT as a benchmark. It is shown that when the mean overlap rate is the same between MST and CAT, the SD of test overlap tends to be larger in MST. A simulation study was conducted to provide empirical evidence. We also compared the security of MST under the single-pool versus the multiple-pool designs; both analytical and simulation studies show that the non-overlapping multiple-pool design will slightly increase the security risk.

  3. [Objective assessment of the functional impact of dry eye severity on the quality of vision by double-pass aberrometry].

    PubMed

    Habay, T; Majzoub, S; Perrault, O; Rousseau, C; Pisella, P J

    2014-03-01

    To assess the functional impact of the severity of dry eye on the quality of vision by measuring an Objective Scatter Index (OSI) using double pass aberrometry. Twenty-eight patients (56 eyes) with dry eye syndromes of varying severity participated in this study. A double-pass aberrometer was used to measure the dynamic changes in the OSI for 20 seconds. The mean and standard deviations of the OSI and the number of blinks occurring during the examination were compared as a function of the clinical severity of dry eye disease. The mean OSI increased with the severity of dry eye syndrome with a significant difference for stages 3 (P<0.01) and 4 (P<0.001) compared to stages 1 and 2, without a significant difference based on age (P>0.8) or visual acuity (P>0.2). Standard deviation of the OSI also increased with the severity of dry eye disease, with a significant difference for stages 3 (P<0.01) and 4 (P<0.0001) compared to stages 1 and 2, with no significant increase in the number of blinks (P>0.2). The values of the OSI standard deviation represented the dynamic nature of aberrometric changes related to the instability of the tear film. Quality of vision of patients deteriorated in relation to the severity of their dry eye. The analysis of OSI standard deviation appears to be an objective way to assess the intensity of subjective visual disturbances reported by patients with dry eye syndrome. It also provides a new tool to assess the severity of damage to the ocular surface. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  4. Two large earthquakes in western Switzerland in the sixteenth century: 1524 in Ardon (VS) and 1584 in Aigle (VD)

    NASA Astrophysics Data System (ADS)

    Schwarz-Zanetti, Gabriela; Fäh, Donat; Gache, Sylvain; Kästli, Philipp; Loizeau, Jeanluc; Masciadri, Virgilio; Zenhäusern, Gregor

    2018-03-01

    The Valais is the most seismically active region of Switzerland. Strong damaging events occurred in 1755, 1855, and 1946. Based on historical documents, we discuss two known damaging events in the sixteenth century: the 1524 Ardon and the 1584 Aigle earthquakes. For the 1524, a document describes damage in Ardon, Plan-Conthey, and Savièse, and a stone tablet at the new bell tower of the Ardon church confirms the reconstruction of the bell tower after the earthquake. Additionally, a significant construction activity in the Upper Valais churches during the second quarter of the sixteenth century is discussed that however cannot be clearly related to this event. The assessed moment magnitude Mw of the 1524 event is 5.8, with an error of about 0.5 units corresponding to one standard deviation. The epicenter is at 46.27 N, 7.27 E with a high uncertainty of about 50 km corresponding to one standard deviation. The assessed moment magnitude Mw of the 1584 main shock is 5.9, with an error of about 0.25 units corresponding to one standard deviation. The epicenter is at 46.33 N and 6.97 E with an uncertainty of about 25 km corresponding to one standard deviation. Exceptional movements in the Lake Geneva wreaked havoc along the shore of the Rhone delta. The large dimension of the induced damage can be explained by an expanded subaquatic slide with resultant tsunami and seiche in Lake Geneva. The strongest of the aftershocks occurred on March 14 with magnitude 5.4 and triggered a destructive landslide covering the villages Corbeyrier and Yvorne, VD.

  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. Association between Serum Uric Acid Level and Carotid Atherosclerosis in Chinese Individuals Aged 75 Years or Older: A Hospital-Based Case-Control Study.

    PubMed

    Feng, L; Hua, C; Sun, H; Qin, L-Y; Niu, P-P; Guo, Z-N; Yang, Y

    2018-01-01

    To investigate the association between serum uric acid level and the presence and progression of carotid atherosclerosis in Chinese individuals aged 75 years or older. Case-control study. In a teaching hospital. Five hundred and sixty-four elderlies (75 years or above) who underwent general health screening in our hospital were enrolled. The detailed carotid ultrasound results, physical examination information, medical history, and laboratory test results including serum uric acid level were recorded, these data were used to analyze the relationship between serum uric acid level and carotid atherosclerosis. Then, subjects who underwent the second carotid ultrasound 1.5-2 years later were further identified to analyzed the relationship between serum uric acid and the progression of carotid atherosclerosis. A total of 564 subjects were included, carotid plaque was found in 482 (85.5%) individuals. Logistic regression showed that subjects with elevated serum uric acid (expressed per 1 standard deviation change) had significantly higher incidence of carotid plaque (odds ratio, 1.37; 95% confidence interval, 1.07-1.75; P= 0.012) after controlling for other factors. A total of 236 subjects underwent the follow-up carotid ultrasound. Linear regression showed that serum uric acid level (expressed per 1 standard deviation change; 1 standard deviation = 95.5 μmol/L) was significantly associated with percentage of change of plaque score (P = 0.008). Multivariable linear regression showed that 1 standard deviation increase in serum uric acid levels was expected to increase 0.448% of plaque score (P = 0.023). The elevated serum uric acid level may be independently and significantly associated with the presence and progression of carotid atherosclerosis in Chinese individuals aged 75 years or older.

  7. Implementing lean in Malaysian universities: Lean awareness level in an engineering faculty of a local university

    NASA Astrophysics Data System (ADS)

    Azim Khairi, M.; Rahman, Mohamed Abd

    2018-01-01

    Many academic articles were published in Malaysia promoting the goodness of lean in manufacturing and industrial sectors but less attention was apparently given to the possibility of obtaining the same universal benefits when applying lean in non-manufacturing sectors especially higher education. This study aims to determine the level of lean awareness among a local university’s community taking its Faculty of Engineering (FoE) as the case study. It also seeks to identify typical FoE’s staff perception on lean regarding its benefits and the obstacles in implementing it. A web-based survey using questionnaires was carried out for 215 respondents consisting of academic and administrative staff of the faculty. Statistical Package for the Social Science (SPSS) was used to analyze the survey data collected. A total of 13.95% of respondents returned the forms. Slightly more than half of those responded (56.7%) have encountered some of the lean terms with mean 1.43 and standard deviation 0.504. However, the large amount of standard deviation somewhat indicates that the real level of lean awareness of FoE as a group was low. In terms of lean benefits, reduction of waste was favored (93.3%) by the respondents with mean 0.93 and standard deviation 0.254. For obstacles in implementing lean, lack of knowledge was selected by most respondents (86.7%) to be the major factor with mean 0.87 and standard deviation 0.346. Through the analysis done, the study may conclude that level of lean awareness among the university‘s community was low thus may hinder implementation of lean concept.

  8. Note onset deviations as musical piece signatures.

    PubMed

    Serrà, Joan; Özaslan, Tan Hakan; Arcos, Josep Lluis

    2013-01-01

    A competent interpretation of a musical composition presents several non-explicit departures from the written score. Timing variations are perhaps the most important ones: they are fundamental for expressive performance and a key ingredient for conferring a human-like quality to machine-based music renditions. However, the nature of such variations is still an open research question, with diverse theories that indicate a multi-dimensional phenomenon. In the present study, we consider event-shift timing variations and show that sequences of note onset deviations are robust and reliable predictors of the musical piece being played, irrespective of the performer. In fact, our results suggest that only a few consecutive onset deviations are already enough to identify a musical composition with statistically significant accuracy. We consider a mid-size collection of commercial recordings of classical guitar pieces and follow a quantitative approach based on the combination of standard statistical tools and machine learning techniques with the semi-automatic estimation of onset deviations. Besides the reported results, we believe that the considered materials and the methodology followed widen the testing ground for studying musical timing and could open new perspectives in related research fields.

  9. 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.

  10. Analysis of turbulence characteristics over the northern Tibetan Plateau area

    NASA Astrophysics Data System (ADS)

    Li, M. S.; Ma, Y. M.; Ma, W. Q.; Hu, Z. Y.; Ishikawa, H.; Su, Z. B.; Sun, G. L.

    2006-07-01

    Based on CATOP/Tibet [Coordinated Enhanced Observing Period (CEOP) Asia-Australia Monsoon Project (CA-IMP) on the Tibetan Plateau) turbulent data collected at the Bujiao (BJ) site of the Nagqu area, the turbulent structure and transportation characteristics in the near surface layer during summer are analyzed. The main results show that the relationship between the normalized standard deviation of 3D wind speed and stability satisfies the similarity law tinder both unstable and stable stratifications. The relations of normalized standard deviation of temperature and specific humidity to stability only obey the "-1/3 power law." tinder unstable conditions. In the case of stable stratifications, their relations to stability are dispersing. The sensible heat dominates in the dry period, while in the wet period, the latent heat is larger than the sensible heat.

  11. First flavor-tagged determination of bounds on mixing-induced CP violation in Bs0 --> J/psiphi decays.

    PubMed

    Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Behari, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; 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; 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; 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; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; 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 Lentdecker, G; De Lorenzo, G; Dell'Orso, M; Demortier, L; Deng, J; Deninno, M; De Pedis, D; 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; 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; Forrester, S; 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; Giagu, S; Giakoumopolou, 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; Hamilton, A; 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; Iyutin, B; James, E; Jayatilaka, B; Jeans, D; Jeon, E J; 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; Kerzel, U; 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; Klute, M; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraus, J; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kulkarni, N P; Kusakabe, Y; Kwang, S; Laasanen, A T; Labarga, L; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; 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, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, M; 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; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M; 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; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; 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; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, 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; Salamanna, G; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; 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; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; 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; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; 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; Sun, H; 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; Tourneur, S; Trischuk, W; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; 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; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; 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

    2008-04-25

    This Letter describes the first determination of bounds on the CP-violation parameter 2beta(s) using B(s)(0) decays in which the flavor of the bottom meson at production is identified. The result is based on approximately 2000 B(s)(0)-->J/psiphi decays reconstructed in a 1.35 fb(-1) data sample collected with the CDF II detector using pp collisions produced at the Fermilab Tevatron. We report confidence regions in the two-dimensional space of 2beta(s) and the decay-width difference DeltaGamma. Assuming the standard model predictions of 2beta(s) and DeltaGamma, the probability of a deviation as large as the level of the observed data is 15%, corresponding to 1.5 Gaussian standard deviations.

  12. [Noninvasive total hemoglobin monitoring based on multiwave spectrophotometry in obstetrics and gynecology].

    PubMed

    Pyregov, A V; Ovechkin, A Iu; Petrov, S V

    2012-01-01

    Results of prospective randomized comparative research of 2 total hemoglobin estimation methods are presented. There were laboratory tests and continuous noninvasive technique with multiwave spectrophotometry on the Masimo Rainbow SET. Research was carried out in two stages. At the 1st stage (gynecology)--67 patients were included and in second stage (obstetrics)--44 patients during and after Cesarean section. The standard deviation of noninvasive total hemoglobin estimation from absolute values (invasive) was 7.2 and 4.1%, an standard deviation in a sample--5.2 and 2.7 % in gynecologic operations and surgical delivery respectively, that confirms lack of reliable indicators differences. The method of continuous noninvasive total hemoglobin estimation with multiwave spectrophotometry on the Masimo Rainbow SET technology can be recommended for use in obstetrics and gynecology.

  13. 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...

  14. Laser frequency stabilization using a commercial wavelength meter

    NASA Astrophysics Data System (ADS)

    Couturier, Luc; Nosske, Ingo; Hu, Fachao; Tan, Canzhu; Qiao, Chang; Jiang, Y. H.; Chen, Peng; Weidemüller, Matthias

    2018-04-01

    We present the characterization of a laser frequency stabilization scheme using a state-of-the-art wavelength meter based on solid Fizeau interferometers. For a frequency-doubled Ti-sapphire laser operated at 461 nm, an absolute Allan deviation below 10-9 with a standard deviation of 1 MHz over 10 h is achieved. Using this laser for cooling and trapping of strontium atoms, the wavemeter scheme provides excellent stability in single-channel operation. Multi-channel operation with a multimode fiber switch results in fluctuations of the atomic fluorescence correlated to residual frequency excursions of the laser. The wavemeter-based frequency stabilization scheme can be applied to a wide range of atoms and molecules for laser spectroscopy, cooling, and trapping.

  15. [Method for the quality assessment of data collection processes in epidemiological studies].

    PubMed

    Schöne, G; Damerow, S; Hölling, H; Houben, R; Gabrys, L

    2017-10-01

    For a quantitative evaluation of primary data collection processes in epidemiological surveys based on accompaniments and observations (in the field), there is no description of test criteria and methodologies in relevant literature and thus no known application in practice. Therefore, methods need to be developed and existing procedures adapted. The aim was to identify quality-relevant developments within quality dimensions by means of inspection points (quality indicators) during the process of data collection. As a result we seek to implement and establish a methodology for the assessment of overall survey quality supplementary to standardized data analyses. Monitors detect deviations from standard primary data collection during site visits by applying standardized checklists. Quantitative results - overall and for each dimension - are obtained by numerical calculation of quality indicators. Score results are categorized and color coded. This visual prioritization indicates necessity for intervention. The results obtained give clues regarding the current quality of data collection. This allows for the identification of such sections where interventions for quality improvement are needed. In addition, process quality development can be shown over time on an intercomparable basis. This methodology for the evaluation of data collection quality can identify deviations from norms, focalize quality analyses and help trace causes for significant deviations.

  16. An ionization gauge for ultrahigh vacuum measurement based on a carbon nanotube cathode

    NASA Astrophysics Data System (ADS)

    Zhang, Huzhong; Cheng, Yongjun; Sun, Jian; Wang, Yongjun; Xi, Zhenhua; Dong, Meng; Li, Detian

    2017-10-01

    This work reports on the complete design and the properties of an ionization gauge based on a carbon nanotube cathode, which can measure ultrahigh vacuum without thermal effects. The gauge is composed of a pressure sensor and an electronic controller. This pressure sensor is constructed based on a hot-cathode ionization gauge, where the traditional hot filament is replaced by an electron source prepared with multi-wall nanotubes. Besides, an electronic controller was developed for bias voltage supply, low current detection, and pressure indication. The gauge was calibrated in the pressure range of 10-8 to 10-4 Pa in a XHV/UHV calibration apparatus. The gauge shows good linear characteristics in different gases. The calibrated sensitivity is 0.035 Pa-1 in N2, and the standard deviation of the sensitivity is about 1.1%. In addition, the stability of the sensitivity was learned in a long period. The standard deviation of the sensitivity factor "S" during one year is 2.0% for Ar and 1.6% for N2.

  17. Time-variant random interval natural frequency analysis of structures

    NASA Astrophysics Data System (ADS)

    Wu, Binhua; Wu, Di; Gao, Wei; Song, Chongmin

    2018-02-01

    This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

  18. Oceanographic and meteorological research based on the data products of SEASAT

    NASA Technical Reports Server (NTRS)

    Pierson, W. J. (Principal Investigator)

    1983-01-01

    De-aliased SEASAT SASS vector winds obtained during the GOASEX (Gulf of Alaska SEASAT Experiment) program were processed to obtain superobservations centered on a one degree by one degree grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. Each grid point of the synoptic field provides the mean synoptic east-west and north-south wind components plus estimates of the standard deviations of these means. These superobservations winds are then processed further to obtain synoptic scale vector winds stress fiels, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations for each grid point value. The resulting fields appear to be consistant over large distances and to agree with, for example, geostationary cloud images obtained concurrently. Their quality is far superior to that of analyses based on conventional data.

  19. Concentration sensor based on a tilted fiber Bragg grating for anions monitoring

    NASA Astrophysics Data System (ADS)

    Melo, L. B.; Rodrigues, J. M. M.; Farinha, A. S. F.; Marques, C. A.; Bilro, L.; Alberto, N.; Tomé, J. P. C.; Nogueira, R. N.

    2014-08-01

    The ubiquity and importance of anions in many crucial roles accounts for the current high interest in the design and preparation of effective sensors for these species. Therefore, a tilted fiber Bragg grating sensor was fabricated to investigate individual detection of different anion concentrations in ethyl acetate, namely acetate, fluoride and chloride. The influence of the refractive index on the transmission spectrum of a tilted fiber Bragg grating was determined by developing a new demodulation method. This is based on the calculation of the standard deviation between the cladding modes of the transmission spectrum and its smoothing function. The standard deviation method was used to monitor concentrations of different anions. The sensor resolution obtained for the anion acetate, fluoride and chloride is 79 × 10-5 mol/dm3, 119 × 10-5 mol/dm3 and 78 × 10-5 mol/dm3, respectively, within the concentration range of (39-396) × 10-5 mol/dm3.

  20. Finding new pathway-specific regulators by clustering method using threshold standard deviation based on DNA chip data of Streptomyces coelicolor.

    PubMed

    Yang, Yung-Hun; Kim, Ji-Nu; Song, Eunjung; Kim, Eunjung; Oh, Min-Kyu; Kim, Byung-Gee

    2008-09-01

    In order to identify the regulators involved in antibiotic production or time-specific cellular events, the messenger ribonucleic acid (mRNA) expression data of the two gene clusters, actinorhodin (ACT) and undecylprodigiosin (RED) biosynthetic genes, were clustered with known mRNA expression data of regulators from S. coelicolor using a filtering method based on standard deviation and clustering analysis. The result identified five regulators including two well-known regulators namely, SCO3579 (WlbA) and SCO6722 (SsgD). Using overexpression and deletion of the regulator genes, we were able to identify two regulators, i.e., SCO0608 and SCO6808, playing roles as repressors in antibiotics production and sporulation. This approach can be easily applied to mapping out new regulators related to any interesting target gene clusters showing characteristic expression patterns. The result can also be used to provide insightful information on the selection rules among a large number of regulators.

  1. Optimization of Adaptive Intraply Hybrid Fiber Composites with Reliability Considerations

    NASA Technical Reports Server (NTRS)

    Shiao, Michael C.; Chamis, Christos C.

    1994-01-01

    The reliability with bounded distribution parameters (mean, standard deviation) was maximized and the reliability-based cost was minimized for adaptive intra-ply hybrid fiber composites by using a probabilistic method. The probabilistic method accounts for all naturally occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry, and control-related parameters. Probabilistic sensitivity factors were computed and used in the optimization procedures. For actuated change in the angle of attack of an airfoil-like composite shell structure with an adaptive torque plate, the reliability was maximized to 0.9999 probability, with constraints on the mean and standard deviation of the actuation material volume ratio (percentage of actuation composite material in a ply) and the actuation strain coefficient. The reliability-based cost was minimized for an airfoil-like composite shell structure with an adaptive skin and a mean actuation material volume ratio as the design parameter. At a O.9-mean actuation material volume ratio, the minimum cost was obtained.

  2. What makes children with cerebral palsy vulnerable to malnutrition? Findings from the Bangladesh cerebral palsy register (BCPR).

    PubMed

    Jahan, Israt; Muhit, Mohammad; Karim, Tasneem; Smithers-Sheedy, Hayley; Novak, Iona; Jones, Cheryl; Badawi, Nadia; Khandaker, Gulam

    2018-04-16

    To assess the nutritional status and underlying risk factors for malnutrition among children with cerebral palsy in rural Bangladesh. We used data from the Bangladesh Cerebral Palsy Register; a prospective population based surveillance of children with cerebral palsy aged 0-18 years in a rural subdistrict of Bangladesh (i.e., Shahjadpur). Socio-demographic, clinical and anthropometric measurements were collected using Bangladesh Cerebral Palsy Register record form. Z scores were calculated using World Health Organization Anthro and World Health Organization AnthroPlus software. A total of 726 children with cerebral palsy were registered into the Bangladesh Cerebral Palsy Register (mean age 7.6 years, standard deviation 4.5, 38.1% female) between January 2015 and December 2016. More than two-third of children were underweight (70.0%) and stunted (73.1%). Mean z score for weight for age, height for age and weight for height were -2.8 (standard deviation 1.8), -3.1 (standard deviation 2.2) and -1.2 (standard deviation 2.3) respectively. Moderate to severe undernutrition (i.e., both underweight and stunting) were significantly associated with age, monthly family income, gross motor functional classification system and neurological type of cerebral palsy. The burden of undernutrition is high among children with cerebral palsy in rural Bangladesh which is augmented by both poverty and clinical severity. Enhancing clinical nutritional services for children with cerebral palsy should be a public health priority in Bangladesh. Implications for Rehabilitation Population-based surveillance data on nutritional status of children with cerebral palsy in Bangladesh indicates substantially high burden of malnutrition among children with CP in rural Bangladesh. Children with severe form of cerebral palsy, for example, higher Gross Motor Function Classification System (GMFCS) level, tri/quadriplegic cerebral palsy presents the highest proportion of severe malnutrition; hence, these vulnerable groups should be focused in designing nutrition intervention and rehabilitation programs. Disability inclusive and focused nutrition intervention programme need to be kept as priority in national nutrition policies and nutrition action plans specially in low- and middle-income countries. Community-based management of malnutrition has the potential to overcome this poor nutritional scenario of children with disability (i.e., cerebral palsy). The global leaders such as World Health Organization, national and international organizations should take this in account and conduct further research to develop nutritional guidelines for this vulnerable group of population.

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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.

  9. Accuracy of radiotherapy dose calculations based on cone-beam CT: comparison of deformable registration and image correction based methods

    NASA Astrophysics Data System (ADS)

    Marchant, T. E.; Joshi, K. D.; Moore, C. J.

    2018-03-01

    Radiotherapy dose calculations based on cone-beam CT (CBCT) images can be inaccurate due to unreliable Hounsfield units (HU) in the CBCT. Deformable image registration of planning CT images to CBCT, and direct correction of CBCT image values are two methods proposed to allow heterogeneity corrected dose calculations based on CBCT. In this paper we compare the accuracy and robustness of these two approaches. CBCT images for 44 patients were used including pelvis, lung and head & neck sites. CBCT HU were corrected using a ‘shading correction’ algorithm and via deformable registration of planning CT to CBCT using either Elastix or Niftyreg. Radiotherapy dose distributions were re-calculated with heterogeneity correction based on the corrected CBCT and several relevant dose metrics for target and OAR volumes were calculated. Accuracy of CBCT based dose metrics was determined using an ‘override ratio’ method where the ratio of the dose metric to that calculated on a bulk-density assigned version of the same image is assumed to be constant for each patient, allowing comparison to the patient’s planning CT as a gold standard. Similar performance is achieved by shading corrected CBCT and both deformable registration algorithms, with mean and standard deviation of dose metric error less than 1% for all sites studied. For lung images, use of deformed CT leads to slightly larger standard deviation of dose metric error than shading corrected CBCT with more dose metric errors greater than 2% observed (7% versus 1%).

  10. Characterizing the Spatial Density Functions of Neural Arbors

    NASA Astrophysics Data System (ADS)

    Teeter, Corinne Michelle

    Recently, it has been proposed that a universal function describes the way in which all arbors (axons and dendrites) spread their branches over space. Data from fish retinal ganglion cells as well as cortical and hippocampal arbors from mouse, rat, cat, monkey and human provide evidence that all arbor density functions (adf) can be described by a Gaussian function truncated at approximately two standard deviations. A Gaussian density function implies that there is a minimal set of parameters needed to describe an adf: two or three standard deviations (depending on the dimensionality of the arbor) and an amplitude. However, the parameters needed to completely describe an adf could be further constrained by a scaling law found between the product of the standard deviations and the amplitude of the function. In the following document, I examine the scaling law relationship in order to determine the minimal set of parameters needed to describe an adf. First, I find that the at, two-dimensional arbors of fish retinal ganglion cells require only two out of the three fundamental parameters to completely describe their density functions. Second, the three-dimensional, volume filling, cortical arbors require four fundamental parameters: three standard deviations and the total length of an arbor (which corresponds to the amplitude of the function). Next, I characterize the shape of arbors in the context of the fundamental parameters. I show that the parameter distributions of the fish retinal ganglion cells are largely homogenous. In general, axons are bigger and less dense than dendrites; however, they are similarly shaped. The parameter distributions of these two arbor types overlap and, therefore, can only be differentiated from one another probabilistically based on their adfs. Despite artifacts in the cortical arbor data, different types of arbors (apical dendrites, non-apical dendrites, and axons) can generally be differentiated based on their adfs. In addition, within arbor type, there is evidence of different neuron classes (such as interneurons and pyramidal cells). How well different types and classes of arbors can be differentiated is quantified using the Random ForestTM supervised learning algorithm.

  11. 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.

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

    Ma, Y; Lacroix, F; Lavallee, M

    Purpose: To evaluate the commercially released Collapsed Cone convolution-based(CCC) dose calculation module of the Elekta OncentraBrachy(OcB) treatment planning system(TPS). Methods: An allwater phantom was used to perform TG43 benchmarks with single source and seventeen sources, separately. Furthermore, four real-patient heterogeneous geometries (chestwall, lung, breast and prostate) were used. They were selected based on their clinical representativity of a class of clinical anatomies that pose clear challenges. The plans were used as is(no modification). For each case, TG43 and CCC calculations were performed in the OcB TPS, with TG186-recommended materials properly assigned to ROIs. For comparison, Monte Carlo simulation was runmore » for each case with the same material scheme and grid mesh as TPS calculations. Both modes of CCC (standard and high quality) were tested. Results: For the benchmark case, the CCC dose, when divided by that of TG43, yields hot-n-cold spots in a radial pattern. The pattern of the high mode is denser than that of the standard mode and is representative of angular dicretization. The total deviation ((hot-cold)/TG43) is 18% for standard mode and 11% for high mode. Seventeen dwell positions help to reduce “ray-effect”, with the total deviation to 6% (standard) and 5% (high), respectively. For the four patient cases, CCC produces, as expected, more realistic dose distributions than TG43. A close agreement was observed between CCC and MC for all isodose lines, from 20% and up; the 10% isodose line of CCC appears shifted compared to that of MC. The DVH plots show dose deviations of CCC from MC in small volume, high dose regions (>100% isodose). For patient cases, the difference between standard and high modes is almost undiscernable. Conclusion: OncentraBrachy CCC algorithm marks a significant dosimetry improvement relative to TG43 in real-patient cases. Further researches are recommended regarding the clinical implications of the above observations. Support provided by a CIHR grant and CCC system provided by Elekta-Nucletron.« less

  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. 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

  16. 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; 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; Bellato, M; Bisello, D; Carlin, R; Checchia, P; Dall'Osso, M; Dorigo, T; Galanti, M; Gasparini, F; Gasparini, U; Giubilato, P; Gozzelino, A; Kanishchev, K; Lacaprara, S; Margoni, M; Meneguzzo, A T; Pazzini, J; Pegoraro, M; 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; 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 A; Khurshid, T; 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; Afanasiev, S; Bunin, P; Gavrilenko, M; Golutvin, I; Gorbunov, I; Kamenev, A; Karjavin, V; Konoplyanikov, V; Lanev, A; Malakhov, A; Matveev, V; Moisenz, P; Palichik, V; Perelygin, V; Shmatov, 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; Pozdnyakov, I; 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; 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; Pinna, D; 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; 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; 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; Kovalskyi, D; Letts, J; Macneill, I; Olivito, D; Padhi, S; Palmer, C; Pieri, M; Sani, M; Sharma, V; Simon, S; Sudano, E; 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; Lopes De Sá, R; 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; Mei, H; 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; Berry, D; Betts, R R; Bucinskaite, I; Cavanaugh, R; Evdokimov, O; Gauthier, L; Gerber, C E; Hofman, D J; Kurt, P; Moon, D H; O'Brien, C; Sandoval Gonzalez, I D; 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; 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; 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; 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.

  17. Observation of $$\\mathrm{t\\overline{t}}$$H production

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

    Sirunyan, Albert M; et al.

    The observation of Higgs boson production in association with a top quark-antiquark pair is reported, based on a combined analysis of proton-proton collision data at center-of-mass energies ofmore » $$\\sqrt{s}=$$ 7, 8, and 13 TeV, corresponding to integrated luminosities of up to 5.1, 19.7, and 35.9 fb$$^{-1}$$, respectively. The data were collected with the CMS detector at the CERN LHC. The results of statistically independent searches for Higgs bosons produced in conjunction with a top quark-antiquark pair and decaying to pairs of W bosons, Z bosons, photons, $$\\tau$$ leptons, or bottom quark jets are combined to maximize sensitivity. An excess of events is observed, with a significance of 5.2 standard deviations, over the expectation from the background-only hypothesis. The corresponding expected significance from the standard model for a Higgs boson mass of 125.09 GeV is 4.2 standard deviations. The combined best fit signal strength normalized to the standard model prediction is 1.26$${^{+0.31}_{-0.26}}$$.« less

  18. 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.

  19. Nutrient intake values (NIVs): a recommended terminology and framework for the derivation of values.

    PubMed

    King, Janet C; Vorster, Hester H; Tome, Daniel G

    2007-03-01

    Although most countries and regions around the world set recommended nutrient intake values for their populations, there is no standardized terminology or framework for establishing these standards. Different terms used for various components of a set of dietary standards are described in this paper and a common set of terminology is proposed. The recommended terminology suggests that the set of values be called nutrient intake values (NIVs) and that the set be composed of three different values. The average nutrient requirement (ANR) reflects the median requirement for a nutrient in a specific population. The individual nutrient level (INLx) is the recommended level of nutrient intake for all healthy people in the population, which is set at a certain level x above the mean requirement. For example, a value set at 2 standard deviations above the mean requirement would cover the needs of 98% of the population and would be INL98. The third component of the NIVs is an upper nutrient level (UNL), which is the highest level of daily nutrient intake that is likely to pose no risk of adverse health effects for almost all individuals in a specified life-stage group. The proposed framework for deriving a set of NIVs is based on a statistical approach for determining the midpoint of a distribution of requirements for a set of nutrients in a population (the ANR), the standard deviation of the requirements, and an individual nutrient level that assures health at some point above the mean, e.g., 2 standard deviations. Ideally, a second set of distributions of risk of excessive intakes is used as the basis for a UNL.

  20. 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.

  1. 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.

  2. 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.

  3. 38 CFR 36.4348 - Servicer Appraisal Processing Program.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... requirement, routine reviews of SAPP cases will be made by VA staff based upon quality control procedures..., that its activities do not deviate from high standards of integrity. The quality control system must include frequent, periodic audits that specifically address the appraisal review activity. These audits...

  4. 38 CFR 36.4347 - Lender Appraisal Processing Program.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... subsequent office case review requirements, routine reviews of LAPP cases will be made by VA staff based upon..., that its activities do not deviate from high standards of integrity. The quality control system must include frequent, periodic audits that specifically address the appraisal review activity. These audits...

  5. 38 CFR 36.4348 - Servicer Appraisal Processing Program.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... requirement, routine reviews of SAPP cases will be made by VA staff based upon quality control procedures..., that its activities do not deviate from high standards of integrity. The quality control system must include frequent, periodic audits that specifically address the appraisal review activity. These audits...

  6. 38 CFR 36.4347 - Lender Appraisal Processing Program.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... subsequent office case review requirements, routine reviews of LAPP cases will be made by VA staff based upon..., that its activities do not deviate from high standards of integrity. The quality control system must include frequent, periodic audits that specifically address the appraisal review activity. These audits...

  7. 38 CFR 36.4348 - Servicer Appraisal Processing Program.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... requirement, routine reviews of SAPP cases will be made by VA staff based upon quality control procedures..., that its activities do not deviate from high standards of integrity. The quality control system must include frequent, periodic audits that specifically address the appraisal review activity. These audits...

  8. 38 CFR 36.4347 - Lender Appraisal Processing Program.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... subsequent office case review requirements, routine reviews of LAPP cases will be made by VA staff based upon..., that its activities do not deviate from high standards of integrity. The quality control system must include frequent, periodic audits that specifically address the appraisal review activity. These audits...

  9. 38 CFR 36.4348 - Servicer Appraisal Processing Program.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... requirement, routine reviews of SAPP cases will be made by VA staff based upon quality control procedures..., that its activities do not deviate from high standards of integrity. The quality control system must include frequent, periodic audits that specifically address the appraisal review activity. These audits...

  10. 38 CFR 36.4347 - Lender Appraisal Processing Program.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... subsequent office case review requirements, routine reviews of LAPP cases will be made by VA staff based upon..., that its activities do not deviate from high standards of integrity. The quality control system must include frequent, periodic audits that specifically address the appraisal review activity. These audits...

  11. A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor.

    PubMed

    Liu, Zhenwang; Xu, Jiangtao; Wang, Xinlei; Nie, Kaiming; Jin, Weimin

    2015-09-16

    In order to eliminate the fixed-pattern noise (FPN) in the output image of time-delay-integration CMOS image sensor (TDI-CIS), a FPN correction method based on gray value compensation is proposed. One hundred images are first captured under uniform illumination. Then, row FPN (RFPN) and column FPN (CFPN) are estimated based on the row-mean vector and column-mean vector of all collected images, respectively. Finally, RFPN are corrected by adding the estimated RFPN gray value to the original gray values of pixels in the corresponding row, and CFPN are corrected by subtracting the estimated CFPN gray value from the original gray values of pixels in the corresponding column. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination with the proposed method, the standard-deviation of row-mean vector decreases from 5.6798 to 0.4214 LSB, and the standard-deviation of column-mean vector decreases from 15.2080 to 13.4623 LSB. Both kinds of FPN in the real images captured by TDI-CIS are eliminated effectively with the proposed method.

  12. Sequential injection redox or acid-base titration for determination of ascorbic acid or acetic acid.

    PubMed

    Lenghor, Narong; Jakmunee, Jaroon; Vilen, Michael; Sara, Rolf; Christian, Gary D; Grudpan, Kate

    2002-12-06

    Two sequential injection titration systems with spectrophotometric detection have been developed. The first system for determination of ascorbic acid was based on redox reaction between ascorbic acid and permanganate in an acidic medium and lead to a decrease in color intensity of permanganate, monitored at 525 nm. A linear dependence of peak area obtained with ascorbic acid concentration up to 1200 mg l(-1) was achieved. The relative standard deviation for 11 replicate determinations of 400 mg l(-1) ascorbic acid was 2.9%. The second system, for acetic acid determination, was based on acid-base titration of acetic acid with sodium hydroxide using phenolphthalein as an indicator. The decrease in color intensity of the indicator was proportional to the acid content. A linear calibration graph in the range of 2-8% w v(-1) of acetic acid with a relative standard deviation of 4.8% (5.0% w v(-1) acetic acid, n=11) was obtained. Sample throughputs of 60 h(-1) were achieved for both systems. The systems were successfully applied for the assays of ascorbic acid in vitamin C tablets and acetic acid content in vinegars, respectively.

  13. 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.

  14. 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.

  15. Forty-five degree cutting septoplasty.

    PubMed

    Hsiao, Yen-Chang; Chang, Chun-Shin; Chuang, Shiow-Shuh; Kolios, Georgios; Abdelrahman, Mohamed

    2016-01-01

    The crooked nose represents a challenge for rhinoplasty surgeons, and many methods have been proposed for management; however, there is no ideal method for treatment. Accordingly, the 45° cutting septoplasty technique, which involves a 45° cut at the junction of the L-shaped strut and repositioning it to achieve a straight septum is proposed. From October 2010 to September 2014, 43 patients underwent the 45° cutting septoplasty technique. There were 28 men and 15 women, with ages ranging from 20 to 58 years (mean, 33 years). Standardized photographs were obtained at every visit. Established photogrammetric parameters were used to describe the degree of correction: Correction rate = (preoperative total deviation - postoperative residual deviation)/preoperative total deviation × 100% was proposed. The mean follow-up period for all patients was 12.3 months. The mean preoperative deviation was 64.3° and the mean postoperative deviation was 2.7°; the overall correction rate was 95.8%. One patient experienced composite implant deviation two weeks postoperatively and underwent revision rhinoplasty. There were no infections, hematomas or postoperative bleeding. Based on the clinical observation of all patients during the follow-up period, the 45° cutting septoplasty technique was shown to be effective for the treatment of crooked nose.

  16. 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…

  17. Observation and measurement of Higgs boson decays to W W * with the ATLAS detector

    DOE PAGES

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

    2015-07-16

    We report the observation of Higgs boson decays to WW * based on an excess over background of 6.1 standard deviations in the dilepton final state, where the Standard Model expectation is 5.8 standard deviations. Evidence for the vector-boson fusion (VBF) production process is obtained with a significance of 3.2 standard deviations. The results are obtained from a data sample corresponding to an integrated luminosity of 25 fb -1 from √s=7 and 8 TeV pp collisions recorded by the ATLAS detector at the LHC. For a Higgs boson mass of 125.36 GeV, the ratio of the measured value to themore » expected value of the total production cross section times branching fraction is 1.09+ 0.16 -0.15(stat) +0.17 -0.14(syst). The corresponding ratios for the gluon fusion and vector-boson fusion production mechanisms are 1.02 ± 0.19(stat) +0.22 -0.18(syst) and 1.27 +0.44 -0.40(stat) +0.30 -0.21(syst), respectively. At √s=8 TeV, the total production cross sections are measured to be σ(gg → >H → WW *)=4.6±0.9(stat) +0.8 -0.7(syst) pb and σ(VBF H →WW *)=0.51 +0.17 -0.15(stat) +0.13 -0.08(syst) pb. The fiducial cross section is determined for the gluon-fusion process in exclusive final states with 0 or one associated jet.« less

  18. 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

  19. Determination of total monomeric anthocyanin pigment content of fruit juices, beverages, natural colorants, and wines by the pH differential method: collaborative study.

    PubMed

    Lee, Jungmin; Durst, Robert W; Wrolstad, Ronald E

    2005-01-01

    This collaborative study was conducted to determine the total monomeric anthocyanin concentration by the pH differential method, which is a rapid and simple spectrophotometric method based on the anthocyanin structural transformation that occurs with a change in pH (colored at pH 1.0 and colorless at pH 4.5). Eleven collaborators representing commercial laboratories, academic institutions, and government laboratories participated. Seven Youden pair materials representing fruit juices, beverages, natural colorants, and wines were tested. The repeatability relative standard deviation (RSDr) varied from 1.06 to 4.16%. The reproducibility relative standard deviation (RSDR) ranged from 2.69 to 10.12%. The HorRat values were < or = 1.33 for all materials. The Study Director recommends that the method be adopted Official First Action.

  20. Is there another major constituent in the atmosphere of Mars?. [radiogenic argon

    NASA Technical Reports Server (NTRS)

    Wood, G. P.

    1974-01-01

    In view of the possible finding of several tens percent of inert gas in the atmosphere of Mars by an instrument on the descent module of the USSR's Mars 6 spacecraft, the likelihood of the correctness of this result was examined. The basis for the well-known fact that the most likely candidate is radiogenic argon is described. It is shown that, for the two important methods of investigating the atmosphere, earth-based CO2 is infrared absorption spectroscopy and S-band occultation, within the estimated 1 standard deviation uncertainties of these methods about 20% argon can be accommodated. Within the estimated 3 standard deviation uncertainties, more than 35% is possible. It is also stated that even with 35% argon the maximum value of heat transfer rate on the Viking 75 entry vehicle does not exceed the design value.

  1. Combustion characteristics of paper and sewage sludge in a pilot-scale fluidized bed.

    PubMed

    Yu, Yong-Ho; Chung, Jinwook

    2015-01-01

    This study characterizes the combustion of paper and sewage sludge in a pilot-scale fluidized bed. The highest temperature during combustion within the system was found at the surface of the fluidized bed. Paper sludge containing roughly 59.8% water was burned without auxiliary fuel, but auxiliary fuel was required to incinerate the sewage sludge, which contained about 79.3% water. The stability of operation was monitored based on the average pressure and the standard deviation of pressure fluctuations. The average pressure at the surface of the fluidized bed decreased as the sludge feed rate increased. However, the standard deviation of pressure fluctuations increased as the sludge feed rate increased. Finally, carbon monoxide (CO) emissions decreased as oxygen content increased in the flue gas, and nitrogen oxide (NOx) emissions were also tied with oxygen content.

  2. Quantitative angle-insensitive flow measurement using relative standard deviation OCT.

    PubMed

    Zhu, Jiang; Zhang, Buyun; Qi, Li; Wang, Ling; Yang, Qiang; Zhu, Zhuqing; Huo, Tiancheng; Chen, Zhongping

    2017-10-30

    Incorporating different data processing methods, optical coherence tomography (OCT) has the ability for high-resolution angiography and quantitative flow velocity measurements. However, OCT angiography cannot provide quantitative information of flow velocities, and the velocity measurement based on Doppler OCT requires the determination of Doppler angles, which is a challenge in a complex vascular network. In this study, we report on a relative standard deviation OCT (RSD-OCT) method which provides both vascular network mapping and quantitative information for flow velocities within a wide range of Doppler angles. The RSD values are angle-insensitive within a wide range of angles, and a nearly linear relationship was found between the RSD values and the flow velocities. The RSD-OCT measurement in a rat cortex shows that it can quantify the blood flow velocities as well as map the vascular network in vivo .

  3. Quantitative angle-insensitive flow measurement using relative standard deviation OCT

    NASA Astrophysics Data System (ADS)

    Zhu, Jiang; Zhang, Buyun; Qi, Li; Wang, Ling; Yang, Qiang; Zhu, Zhuqing; Huo, Tiancheng; Chen, Zhongping

    2017-10-01

    Incorporating different data processing methods, optical coherence tomography (OCT) has the ability for high-resolution angiography and quantitative flow velocity measurements. However, OCT angiography cannot provide quantitative information of flow velocities, and the velocity measurement based on Doppler OCT requires the determination of Doppler angles, which is a challenge in a complex vascular network. In this study, we report on a relative standard deviation OCT (RSD-OCT) method which provides both vascular network mapping and quantitative information for flow velocities within a wide range of Doppler angles. The RSD values are angle-insensitive within a wide range of angles, and a nearly linear relationship was found between the RSD values and the flow velocities. The RSD-OCT measurement in a rat cortex shows that it can quantify the blood flow velocities as well as map the vascular network in vivo.

  4. TU-G-BRD-04: A Round Robin Dosimetry Intercomparison of Gamma Stereotactic Radiosurgery Calibration Protocols

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

    Drzymala, R; Alvarez, P; Bednarz, G

    2015-06-15

    Purpose: The purpose of this multi-institutional study was to compare two new gamma stereotactic radiosurgery (GSRS) dosimetry protocols to existing calibration methods. The ultimate goal was to guide AAPM Task Group 178 in recommending a standard GSRS dosimetry protocol. Methods: Nine centers (ten GSRS units) participated in the study. Each institution made eight sets of dose rate measurements: six with two different ionization chambers in three different 160mm-diameter spherical phantoms (ABS plastic, Solid Water and liquid water), and two using the same ionization chambers with a custom in-air positioning jig. Absolute dose rates were calculated using a newly proposed formalismmore » by the IAEA working group for small and non-standard radiation fields and with a new air-kerma based protocol. The new IAEA protocol requires an in-water ionization chamber calibration and uses previously reported Monte-Carlo generated factors to account for the material composition of the phantom, the type of ionization chamber, and the unique GSRS beam configuration. Results obtained with the new dose calibration protocols were compared to dose rates determined by the AAPM TG-21 and TG-51 protocols, with TG-21 considered as the standard. Results: Averaged over all institutions, ionization chambers and phantoms, the mean dose rate determined with the new IAEA protocol relative to that determined with TG-21 in the ABS phantom was 1.000 with a standard deviation of 0.008. For TG-51, the average ratio was 0.991 with a standard deviation of 0.013, and for the new in-air formalism it was 1.008 with a standard deviation of 0.012. Conclusion: Average results with both of the new protocols agreed with TG-21 to within one standard deviation. TG-51, which does not take into account the unique GSRS beam configuration or phantom material, was not expected to perform as well as the new protocols. The new IAEA protocol showed remarkably good agreement with TG-21. Conflict of Interests: Paula Petti, Josef Novotny, Gennady Neyman and Steve Goetsch are consultants for Elekta Instrument A/B; Elekta Instrument AB, PTW Freiburg GmbH, Standard Imaging, Inc., and The Phantom Laboratory, Inc. loaned equipment for use in these experiments; The University of Wisconsin Accredited Dosimetry Calibration Laboratory provided calibration services.« less

  5. Improving student learning via mobile phone video content: Evidence from the BridgeIT India project

    NASA Astrophysics Data System (ADS)

    Wennersten, Matthew; Quraishy, Zubeeda Banu; Velamuri, Malathi

    2015-08-01

    Past efforts invested in computer-based education technology interventions have generated little evidence of affordable success at scale. This paper presents the results of a mobile phone-based intervention conducted in the Indian states of Andhra Pradesh and Tamil Nadu in 2012-13. The BridgeIT project provided a pool of audio-visual learning materials organised in accordance with a system of syllabi pacing charts. Teachers of Standard 5 and 6 English and Science classes were notified of the availability of new videos via text messages (SMS), which they downloaded onto their phones using an open-source application and showed, with suggested activities, to students on a TV screen using a TV-out cable. In their evaluation of this project, the authors of this paper found that the test scores of children who experienced the intervention improved by 0.36 standard deviations in English and 0.98 standard deviations in Science in Andhra Pradesh, relative to students in similar classrooms who did not experience the intervention. Differences between treatment and control schools in Tamil Nadu were less marked. The intervention was also cost-effective, relative to other computer-based interventions. Based on these results, the authors argue that is possible to use mobile phones to produce a strong positive and statistically significant effect in terms of teaching and learning quality across a large number of classrooms in India at a lower cost per student than past computer-based interventions.

  6. 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…

  7. 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…

  8. 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…

  9. 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...

  10. Note Onset Deviations as Musical Piece Signatures

    PubMed Central

    Serrà, Joan; Özaslan, Tan Hakan; Arcos, Josep Lluis

    2013-01-01

    A competent interpretation of a musical composition presents several non-explicit departures from the written score. Timing variations are perhaps the most important ones: they are fundamental for expressive performance and a key ingredient for conferring a human-like quality to machine-based music renditions. However, the nature of such variations is still an open research question, with diverse theories that indicate a multi-dimensional phenomenon. In the present study, we consider event-shift timing variations and show that sequences of note onset deviations are robust and reliable predictors of the musical piece being played, irrespective of the performer. In fact, our results suggest that only a few consecutive onset deviations are already enough to identify a musical composition with statistically significant accuracy. We consider a mid-size collection of commercial recordings of classical guitar pieces and follow a quantitative approach based on the combination of standard statistical tools and machine learning techniques with the semi-automatic estimation of onset deviations. Besides the reported results, we believe that the considered materials and the methodology followed widen the testing ground for studying musical timing and could open new perspectives in related research fields. PMID:23935971

  11. Test-retest reliability of computer-based video analysis of general movements in healthy term-born infants.

    PubMed

    Valle, Susanne Collier; Støen, Ragnhild; Sæther, Rannei; Jensenius, Alexander Refsum; Adde, Lars

    2015-10-01

    A computer-based video analysis has recently been presented for quantitative assessment of general movements (GMs). This method's test-retest reliability, however, has not yet been evaluated. The aim of the current study was to evaluate the test-retest reliability of computer-based video analysis of GMs, and to explore the association between computer-based video analysis and the temporal organization of fidgety movements (FMs). Test-retest reliability study. 75 healthy, term-born infants were recorded twice the same day during the FMs period using a standardized video set-up. The computer-based movement variables "quantity of motion mean" (Qmean), "quantity of motion standard deviation" (QSD) and "centroid of motion standard deviation" (CSD) were analyzed, reflecting the amount of motion and the variability of the spatial center of motion of the infant, respectively. In addition, the association between the variable CSD and the temporal organization of FMs was explored. Intraclass correlation coefficients (ICC 1.1 and ICC 3.1) were calculated to assess test-retest reliability. The ICC values for the variables CSD, Qmean and QSD were 0.80, 0.80 and 0.86 for ICC (1.1), respectively; and 0.80, 0.86 and 0.90 for ICC (3.1), respectively. There were significantly lower CSD values in the recordings with continual FMs compared to the recordings with intermittent FMs (p<0.05). This study showed high test-retest reliability of computer-based video analysis of GMs, and a significant association between our computer-based video analysis and the temporal organization of FMs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  12. Global Reference Atmosphere Model (GRAM)

    NASA Technical Reports Server (NTRS)

    Johnson, D. L.; Blocker, Rhonda; Justus, C. G.

    1993-01-01

    4D model provides atmospheric parameter values either automatically at positions along linear path or along any set of connected positions specified by user. Based on actual data, GRAM provides thermal wind shear for monthly mean winds, percent deviation from standard atmosphere, mean vertical wind, and perturbation data for each position.

  13. Plant functional traits improve diversity-based predictions of temporal stability of grassland productivity

    USDA-ARS?s Scientific Manuscript database

    Aboveground net primary productivity (ANPP) varies in response to temporal fluctuations in weather. Temporal stability (mean/standard deviation) of community ANPP may be increased, on average, by increasing plant species richness, but stability also may differ widely at a given richness level imply...

  14. Curriculum Orientations and Educational Philosophies of High School Arabic Teachers

    ERIC Educational Resources Information Center

    Alsalem, Abeer Saleh

    2018-01-01

    This study aims to investigate the curriculum orientations of High school Arabic teacher in Riyadh city and to examine the relationship between curriculum orientation and their educational philosophies. The quantitative method (descriptive study) was adopted in this questionnaire survey-based study. Mean and standard deviation for the overall of…

  15. Possibilities of inversion of satellite third-order gravitational tensor onto gravity anomalies: a case study for central Europe

    NASA Astrophysics Data System (ADS)

    Pitoňák, Martin; Šprlák, Michal; Tenzer, Robert

    2017-05-01

    We investigate a numerical performance of four different schemes applied to a regional recovery of the gravity anomalies from the third-order gravitational tensor components (assumed to be observable in the future) synthetized at the satellite altitude of 200 km above the mean sphere. The first approach is based on applying a regional inversion without modelling the far-zone contribution or long-wavelength support. In the second approach we separate integral formulas into two parts, that is, the effects of the third-order disturbing tensor data within near and far zones. Whereas the far-zone contribution is evaluated by using existing global geopotential model (GGM) with spectral weights given by truncation error coefficients, the near-zone contribution is solved by applying a regional inversion. We then extend this approach for a smoothing procedure, in which we remove the gravitational contributions of the topographic-isostatic and atmospheric masses. Finally, we apply the remove-compute-restore (r-c-r) scheme in order to reduce the far-zone contribution by subtracting the reference (long-wavelength) gravity field, which is computed for maximum degree 80. We apply these four numerical schemes to a regional recovery of the gravity anomalies from individual components of the third-order gravitational tensor as well as from their combinations, while applying two different levels of a white noise. We validated our results with respect to gravity anomalies evaluated at the mean sphere from EGM2008 up to the degree 250. Not surprisingly, better fit in terms of standard deviation (STD) was attained using lower level of noise. The worst results were gained applying classical approach, STD values of our solution from Tzzz are 1.705 mGal (noise value with a standard deviation 0.01 × 10 - 15m - 1s - 2) and 2.005 mGal (noise value with a standard deviation 0.05 × 10 - 15m - 1s - 2), while the superior from r-c-r up to the degree 80, STD fit of gravity anomalies from Tzzz with respect to the same counterpart from EGM2008 is 0.510 mGal (noise value with a standard deviation 0.01 × 10 - 15m - 1s - 2) and 1.190 mGal (noise value with a standard deviation 0.05 × 10 - 15m - 1s - 2).

  16. Mars-Gram Validation with Mars Global Surveyor Data

    NASA Technical Reports Server (NTRS)

    Justus, C. G.; Johnson, D.; Parker, Nelson C. (Technical Monitor)

    2002-01-01

    Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many b4ars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Arizona Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiting Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with Mars Global Surveyor Radio Science (RS) and Thermal Emission Spectrometer (TES) data. RS data from 2480 profiles were used, covering latitudes 75deg S to 72deg N, surface to approx. 40 km, for seasons ranging from areocentric longitude of Sun (Ls) = 70-160deg and 265-310deg. RS data spanned a range of local times, mostly 0-9 hours and 18-24 hours. For interests in aerocapture and precision landing, comparisons concentrated on atmospheric density. At a fixed height of 20 km, measured RS density varied by about a factor of 2.5 over the range of latitudes and Ls values observed. Evaluated at matching positions and times, average RS/Mars-GRAM density ratios were generally lf0.05, except at heights above approx. 25 km and latitudes above approx.50deg N. Average standard deviation of RS/Mars-GRAM density ratio was 6%. TES data were used covering surface to approx. 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of Mars global dust storm). Depending on season, TES data covered latitudes 85deg S to 85deg N. Most TES data were concentrated near local times 2 hours and 14 hours. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (> 45deg N), or at most altitudes in the southern hemisphere at Ls approx. 90 and 180deg). Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approx. 6.5-10.5% (varying with height) for all data, or approx. 5- 12%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for 1o:al time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about the same as the standard deviation of TES data about the TES mean value at a given position and season.

  17. 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

  18. 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.

  19. Accuracy of computer-aided design models of the jaws produced using ultra-low MDCT doses and ASIR and MBIR.

    PubMed

    Al-Ekrish, Asma'a A; Alfadda, Sara A; Ameen, Wadea; Hörmann, Romed; Puelacher, Wolfgang; Widmann, Gerlig

    2018-06-16

    To compare the surface of computer-aided design (CAD) models of the maxilla produced using ultra-low MDCT doses combined with filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) reconstruction techniques with that produced from a standard dose/FBP protocol. A cadaveric completely edentulous maxilla was imaged using a standard dose protocol (CTDIvol: 29.4 mGy) and FBP, in addition to 5 low dose test protocols (LD1-5) (CTDIvol: 4.19, 2.64, 0.99, 0.53, and 0.29 mGy) reconstructed with FBP, ASIR 50, ASIR 100, and MBIR. A CAD model from each test protocol was superimposed onto the reference model using the 'Best Fit Alignment' function. Differences between the test and reference models were analyzed as maximum and mean deviations, and root-mean-square of the deviations, and color-coded models were obtained which demonstrated the location, magnitude and direction of the deviations. Based upon the magnitude, size, and distribution of areas of deviations, CAD models from the following protocols were comparable to the reference model: FBP/LD1; ASIR 50/LD1 and LD2; ASIR 100/LD1, LD2, and LD3; MBIR/LD1. The following protocols demonstrated deviations mostly between 1-2 mm or under 1 mm but over large areas, and so their effect on surgical guide accuracy is questionable: FBP/LD2; MBIR/LD2, LD3, LD4, and LD5. The following protocols demonstrated large deviations over large areas and therefore were not comparable to the reference model: FBP/LD3, LD4, and LD5; ASIR 50/LD3, LD4, and LD5; ASIR 100/LD4, and LD5. When MDCT is used for CAD models of the jaws, dose reductions of 86% may be possible with FBP, 91% with ASIR 50, and 97% with ASIR 100. Analysis of the stability and accuracy of CAD/CAM surgical guides as directly related to the jaws is needed to confirm the results.

  20. A systematic review found that deviations from intention-to-treat are common in randomized trials and systematic reviews.

    PubMed

    Abraha, Iosief; Cozzolino, Francesco; Orso, Massimiliano; Marchesi, Mauro; Germani, Antonella; Lombardo, Guido; Eusebi, Paolo; De Florio, Rita; Luchetta, Maria Laura; Iorio, Alfonso; Montedori, Alessandro

    2017-04-01

    To describe the characteristics, and estimate the incidence, of trials included in systematic reviews deviating from the intention-to-treat (ITT) principle. A 5% random sample of reviews were selected (Medline 2006-2010). Trials from reviews were classified based on the ITT: (1) ITT trials (trials reporting standard ITT analyses); (2) modified ITT (mITT) trials (modified ITT; trials deviating from standard ITT); or (3) no ITT trials. Of 222 reviews, 81 (36%) included at least one mITT trial. Reviews with mITT trials were more likely to contain trials that used placebo, that investigated drugs, and that reported favorable results. The incidence of reviews with mITT trial ranged from 29% (17/58) to 48% (23/48). Of the 2,349 trials, 597 (25.4%) were classified as ITT trials, 323 (13.8%) as mITT trials, and 1,429 (60.8%) as no ITT trials. The mITT trials were more likely to have reported exclusions compared to studies classified as ITT trials and to have received funding. The reporting of the type of ITT may differ according to the clinical area and the type of intervention. Deviation from ITT in randomized controlled trials is a widespread phenomenon that significantly affects systematic reviews. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. 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

  2. Preliminary results from the White Sands Missile Range sonic boom propagation experiment

    NASA Technical Reports Server (NTRS)

    Willshire, William L., Jr.; Devilbiss, David W.

    1992-01-01

    Sonic boom bow shock amplitude and rise time statistics from a recent sonic boom propagation experiment are presented. Distributions of bow shock overpressure and rise time measured under different atmospheric turbulence conditions for the same test aircraft are quite different. The peak overpressure distributions are skewed positively, indicating a tendency for positive deviations from the mean to be larger than negative deviations. Standard deviations of overpressure distributions measured under moderate turbulence were 40 percent larger than those measured under low turbulence. As turbulence increased, the difference between the median and the mean increased, indicating increased positive overpressure deviations. The effect of turbulence was more readily seen in the rise time distributions. Under moderate turbulence conditions, the rise time distribution means were larger by a factor of 4 and the standard deviations were larger by a factor of 3 from the low turbulence values. These distribution changes resulted in a transition from a peaked appearance of the rise time distribution for the morning to a flattened appearance for the afternoon rise time distributions. The sonic boom propagation experiment consisted of flying three types of aircraft supersonically over a ground-based microphone array with concurrent measurements of turbulence and other meteorological data. The test aircraft were a T-38, an F-15, and an F-111, and they were flown at speeds of Mach 1.2 to 1.3, 30,000 feet above a 16 element, linear microphone array with an inter-element spacing of 200 ft. In two weeks of testing, 57 supersonic passes of the test aircraft were flown from early morning to late afternoon.

  3. Uncertainty of large-area estimates of indicators of forest structural gamma diversity: A study based on national forest inventory data

    Treesearch

    Susanne Winter; Andreas Böck; Ronald E. McRoberts

    2012-01-01

    Tree diameter and height are commonly measured forest structural variables, and indicators based on them are candidates for assessing forest diversity. We conducted our study on the uncertainty of estimates for mostly large geographic scales for four indicators of forest structural gamma diversity: mean tree diameter, mean tree height, and standard deviations of tree...

  4. 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…

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. Uncertainty in Vs30-based site response

    USGS Publications Warehouse

    Thompson, Eric M.; Wald, David J.

    2016-01-01

    Methods that account for site response range in complexity from simple linear categorical adjustment factors to sophisticated nonlinear constitutive models. Seismic‐hazard analysis usually relies on ground‐motion prediction equations (GMPEs); within this framework site response is modeled statistically with simplified site parameters that include the time‐averaged shear‐wave velocity to 30 m (VS30) and basin depth parameters. Because VS30 is not known in most locations, it must be interpolated or inferred through secondary information such as geology or topography. In this article, we analyze a subset of stations for which VS30 has been measured to address effects of VS30 proxies on the uncertainty in the ground motions as modeled by GMPEs. The stations we analyze also include multiple recordings, which allow us to compute the repeatable site effects (or empirical amplification factors [EAFs]) from the ground motions. Although all methods exhibit similar bias, the proxy methods only reduce the ground‐motion standard deviations at long periods when compared to GMPEs without a site term, whereas measured VS30 values reduce the standard deviations at all periods. The standard deviation of the ground motions are much lower when the EAFs are used, indicating that future refinements of the site term in GMPEs have the potential to substantially reduce the overall uncertainty in the prediction of ground motions by GMPEs.

  10. Differentiating epileptic from non-epileptic high frequency intracerebral EEG signals with measures of wavelet entropy.

    PubMed

    Mooij, Anne H; Frauscher, Birgit; Amiri, Mina; Otte, Willem M; Gotman, Jean

    2016-12-01

    To assess whether there is a difference in the background activity in the ripple band (80-200Hz) between epileptic and non-epileptic channels, and to assess whether this difference is sufficient for their reliable separation. We calculated mean and standard deviation of wavelet entropy in 303 non-epileptic and 334 epileptic channels from 50 patients with intracerebral depth electrodes and used these measures as predictors in a multivariable logistic regression model. We assessed sensitivity, positive predictive value (PPV) and negative predictive value (NPV) based on a probability threshold corresponding to 90% specificity. The probability of a channel being epileptic increased with higher mean (p=0.004) and particularly with higher standard deviation (p<0.0001). The performance of the model was however not sufficient for fully classifying the channels. With a threshold corresponding to 90% specificity, sensitivity was 37%, PPV was 80%, and NPV was 56%. A channel with a high standard deviation of entropy is likely to be epileptic; with a threshold corresponding to 90% specificity our model can reliably select a subset of epileptic channels. Most studies have concentrated on brief ripple events. We showed that background activity in the ripple band also has some ability to discriminate epileptic channels. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  11. Influence of Convective Effect of Solar Winds on the CME Transit Time

    NASA Astrophysics Data System (ADS)

    Sun, Lu-yuan

    2017-10-01

    Based on an empirical model for predicting the transit time of coronal mass ejections (CMEs) proposed by Gopalswamy, 52 CME events which are related to the geomagnetic storms of Dst < -50 nT, and 10 CME events which caused extremely strong geomagnetic storms (Dst < -200 nT) in 1996- 2007 are selected, and combined with the observational data of the interplanetary solar winds that collected by the ACE satellite at 1AU, to analyze the influence of convective effect of ambient solar winds on the prediction of the CME transit time when it arrives at a place of 1 AU. After taking the convective effect of ambient solar winds into account, the standard deviation of predictions is reduced from 16.5 to 11.4 hours for the 52 CME events, and the prediction error is less than 15 hours for 68% of these events; while the standard deviation of predictions is reduced from 10.6 to 6.5 hours for the 10 CME events that caused extremely strong geomagnetic storms, and the prediction error is less than 5 hours for 6 of the 10 events. These results show that taking the convective effect of ambient solar winds into account can reduce the standard deviation of the predicted CME transit time, hence the convective effect of solar winds plays an important role for predicting the transit times of CME events.

  12. Visualizing excipient composition and homogeneity of Compound Liquorice Tablets by near-infrared chemical imaging

    NASA Astrophysics Data System (ADS)

    Wu, Zhisheng; Tao, Ou; Cheng, Wei; Yu, Lu; Shi, Xinyuan; Qiao, Yanjiang

    2012-02-01

    This study demonstrated that near-infrared chemical imaging (NIR-CI) was a promising technology for visualizing the spatial distribution and homogeneity of Compound Liquorice Tablets. The starch distribution (indirectly, plant extraction) could be spatially determined using basic analysis of correlation between analytes (BACRA) method. The correlation coefficients between starch spectrum and spectrum of each sample were greater than 0.95. Depending on the accurate determination of starch distribution, a method to determine homogeneous distribution was proposed by histogram graph. The result demonstrated that starch distribution in sample 3 was relatively heterogeneous according to four statistical parameters. Furthermore, the agglomerates domain in each tablet was detected using score image layers of principal component analysis (PCA) method. Finally, a novel method named Standard Deviation of Macropixel Texture (SDMT) was introduced to detect agglomerates and heterogeneity based on binary image. Every binary image was divided into different sizes length of macropixel and the number of zero values in each macropixel was counted to calculate standard deviation. Additionally, a curve fitting graph was plotted on the relationship between standard deviation and the size length of macropixel. The result demonstrated the inter-tablet heterogeneity of both starch and total compounds distribution, simultaneously, the similarity of starch distribution and the inconsistency of total compounds distribution among intra-tablet were signified according to the value of slope and intercept parameters in the curve.

  13. An adaptive beamforming method for ultrasound imaging based on the mean-to-standard-deviation factor.

    PubMed

    Wang, Yuanguo; Zheng, Chichao; Peng, Hu; Chen, Qiang

    2018-06-12

    The beamforming performance has a large impact on image quality in ultrasound imaging. Previously, several adaptive weighting factors including coherence factor (CF) and generalized coherence factor (GCF) have been proposed to improved image resolution and contrast. In this paper, we propose a new adaptive weighting factor for ultrasound imaging, which is called signal mean-to-standard-deviation factor (SMSF). SMSF is defined as the mean-to-standard-deviation of the aperture data and is used to weight the output of delay-and-sum (DAS) beamformer before image formation. Moreover, we develop a robust SMSF (RSMSF) by extending the SMSF to the spatial frequency domain using an altered spectrum of the aperture data. In addition, a square neighborhood average is applied on the RSMSF to offer a more smoothed square neighborhood RSMSF (SN-RSMSF) value. We compared our methods with DAS, CF, and GCF using simulated and experimental synthetic aperture data sets. The quantitative results show that SMSF results in an 82% lower full width at half-maximum (FWHM) but a 12% lower contrast ratio (CR) compared with CF. Moreover, the SN-RSMSF leads to 15% and 10% improvement, on average, in FWHM and CR compared with GCF while maintaining the speckle quality. This demonstrates that the proposed methods can effectively improve the image resolution and contrast. Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Residual-Mean Analysis of the Air-Sea Fluxes and Associated Oceanic Meridional Overturning

    DTIC Science & Technology

    2006-12-01

    the adiabatic component of the MOC which is based entirely on the sea surface data . The coordinate system introduced in this study is somewhat...heat capacity of water. The technique utilizes the observational data based on meteorological re- analysis (density flux at the sea surface) and...Figure 8. Annual mean and temporal standard deviation of the zonally-averaged mixed- layer depth. The plotted data are based on Levitus 94 climatology

  15. Strategies to Prevent MRSA Transmission in Community-Based Nursing Homes: A Cost Analysis.

    PubMed

    Roghmann, Mary-Claire; Lydecker, Alison; Mody, Lona; Mullins, C Daniel; Onukwugha, Eberechukwu

    2016-08-01

    OBJECTIVE To estimate the costs of 3 MRSA transmission prevention scenarios compared with standard precautions in community-based nursing homes. DESIGN Cost analysis of data collected from a prospective, observational study. SETTING AND PARTICIPANTS Care activity data from 401 residents from 13 nursing homes in 2 states. METHODS Cost components included the quantities of gowns and gloves, time to don and doff gown and gloves, and unit costs. Unit costs were combined with information regarding the type and frequency of care provided over a 28-day observation period. For each scenario, the estimated costs associated with each type of care were summed across all residents to calculate an average cost and standard deviation for the full sample and for subgroups. RESULTS The average cost for standard precautions was $100 (standard deviation [SD], $77) per resident over a 28-day period. If gown and glove use for high-risk care was restricted to those with MRSA colonization or chronic skin breakdown, average costs increased to $137 (SD, $120) and $125 (SD, $109), respectively. If gowns and gloves were used for high-risk care for all residents in addition to standard precautions, the average cost per resident increased substantially to $223 (SD, $127). CONCLUSIONS The use of gowns and gloves for high-risk activities with all residents increased the estimated cost by 123% compared with standard precautions. This increase was ameliorated if specific subsets (eg, those with MRSA colonization or chronic skin breakdown) were targeted for gown and glove use for high-risk activities. Infect Control Hosp Epidemiol 2016;37:962-966.

  16. Transplant ethics under scrutiny – responsibilities of all medical professionals

    PubMed Central

    Trey, Torsten; Caplan, Arthur L.; Lavee, Jacob

    2013-01-01

    In this text, we present and elaborate ethical challenges in transplant medicine related to organ procurement and organ distribution, together with measures to solve such challenges. Based on internationally acknowledged ethical standards, we looked at cases of organ procurement and distribution practices that deviated from such ethical standards. One form of organ procurement is known as commercial organ trafficking, while in China the organ procurement is mostly based on executing prisoners, including killing of detained Falun Gong practitioners for their organs. Efforts from within the medical community as well as from governments have contributed to provide solutions to uphold ethical standards in medicine. The medical profession has the responsibility to actively promote ethical guidelines in medicine to prevent a decay of ethical standards and to ensure best medical practices. PMID:23444249

  17. Transplant ethics under scrutiny - responsibilities of all medical professionals.

    PubMed

    Trey, Torsten; Caplan, Arthur L; Lavee, Jacob

    2013-02-01

    In this text, we present and elaborate ethical challenges in transplant medicine related to organ procurement and organ distribution, together with measures to solve such challenges. Based on internationally acknowledged ethical standards, we looked at cases of organ procurement and distribution practices that deviated from such ethical standards. One form of organ procurement is known as commercial organ trafficking, while in China the organ procurement is mostly based on executing prisoners, including killing of detained Falun Gong practitioners for their organs. Efforts from within the medical community as well as from governments have contributed to provide solutions to uphold ethical standards in medicine. The medical profession has the responsibility to actively promote ethical guidelines in medicine to prevent a decay of ethical standards and to ensure best medical practices.

  18. Informative Bayesian Type A uncertainty evaluation, especially applicable to a small number of observations

    NASA Astrophysics Data System (ADS)

    Cox, M.; Shirono, K.

    2017-10-01

    A criticism levelled at the Guide to the Expression of Uncertainty in Measurement (GUM) is that it is based on a mixture of frequentist and Bayesian thinking. In particular, the GUM’s Type A (statistical) uncertainty evaluations are frequentist, whereas the Type B evaluations, using state-of-knowledge distributions, are Bayesian. In contrast, making the GUM fully Bayesian implies, among other things, that a conventional objective Bayesian approach to Type A uncertainty evaluation for a number n of observations leads to the impractical consequence that n must be at least equal to 4, thus presenting a difficulty for many metrologists. This paper presents a Bayesian analysis of Type A uncertainty evaluation that applies for all n ≥slant 2 , as in the frequentist analysis in the current GUM. The analysis is based on assuming that the observations are drawn from a normal distribution (as in the conventional objective Bayesian analysis), but uses an informative prior based on lower and upper bounds for the standard deviation of the sampling distribution for the quantity under consideration. The main outcome of the analysis is a closed-form mathematical expression for the factor by which the standard deviation of the mean observation should be multiplied to calculate the required standard uncertainty. Metrological examples are used to illustrate the approach, which is straightforward to apply using a formula or look-up table.

  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. 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.

  2. 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.

  3. Sleep Disturbances in OEF/OIF/OND Veterans: Associations with PTSD, Personality, and Coping

    PubMed Central

    Lind, Mackenzie J.; Brown, Emily; Farrell-Carnahan, Leah; Brown, Ruth C.; Hawn, Sage; Berenz, Erin; McDonald, Scott; Pickett, Treven; Danielson, Carla Kmett; Thomas, Suzanne; Amstadter, Ananda B.

    2017-01-01

    Study Objectives: Sleep disturbances are well documented in relation to trauma exposure and posttraumatic stress disorder (PTSD), but correlates of such disturbances remain understudied in veteran populations. We conducted a preliminary study of sleep disturbances in Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn veterans (n = 133; mean [standard deviation] age = 29.8 [4.7] y). Methods: Veterans were assigned to one of three groups based on responses to the Clinician Administered PTSD Scale: control (no trauma-exposure [TE] or PTSD), TE, and PTSD. Sleep disturbance was assessed using the Pittsburgh Sleep Quality Index (PSQI). Measures of resilience, trauma load, personality, coping, alcohol use, and mild traumatic brain injury were also assessed via self-report. Results: The PTSD group had significantly more disturbed sleep (PSQI global score mean = 8.94, standard deviation = 3.12) than control (mean = 5.27, standard deviation = 3.23) and TE (mean = 5.34, standard deviation = 3.17) groups, but there were no differences between TE and control. The same pattern emerged across most PSQI subscales. Results of linear regression analyses indicated that current smoking, Army (versus other military branches), neuroticism, and using substances to cope were all significant correlates of higher sleep disturbance, whereas post-deployment social support was associated with less sleep disturbance. However, when combined together into a model with PTSD status, only neuroticism and substance use coping remained significant as predictors of more disturbed sleep. Conclusions: These initial findings suggest that TE itself may not be an independent risk factor for disturbed sleep in veterans, and that neurotic personality and a tendency to cope by using substances may partially explain sleep disturbance, above and beyond a diagnosis of PTSD. Citation: Lind MJ, Brown E, Farrell-Carnahan L, Brown RC, Hawn S, Berenz E, McDonald S, Pickett T, Danielson CK, Thomas S, Amstadter AB. Sleep disturbances in OEF/OIF/OND veterans: associations with PTSD, personality and coping. J Clin Sleep Med 2017;13(2):291–299. PMID:27998375

  4. Margin selection to compensate for loss of target dose coverage due to target motion during external‐beam radiation therapy of the lung

    PubMed Central

    Osei, Ernest; Barnett, Rob

    2015-01-01

    The aim of this study is to provide guidelines for the selection of external‐beam radiation therapy target margins to compensate for target motion in the lung during treatment planning. A convolution model was employed to predict the effect of target motion on the delivered dose distribution. The accuracy of the model was confirmed with radiochromic film measurements in both static and dynamic phantom modes. 502 unique patient breathing traces were recorded and used to simulate the effect of target motion on a dose distribution. A 1D probability density function (PDF) representing the position of the target throughout the breathing cycle was generated from each breathing trace obtained during 4D CT. Changes in the target D95 (the minimum dose received by 95% of the treatment target) due to target motion were analyzed and shown to correlate with the standard deviation of the PDF. Furthermore, the amount of target D95 recovered per millimeter of increased field width was also shown to correlate with the standard deviation of the PDF. The sensitivity of changes in dose coverage with respect to target size was also determined. Margin selection recommendations that can be used to compensate for loss of target D95 were generated based on the simulation results. These results are discussed in the context of clinical plans. We conclude that, for PDF standard deviations less than 0.4 cm with target sizes greater than 5 cm, little or no additional margins are required. Targets which are smaller than 5 cm with PDF standard deviations larger than 0.4 cm are most susceptible to loss of coverage. The largest additional required margin in this study was determined to be 8 mm. PACS numbers: 87.53.Bn, 87.53.Kn, 87.55.D‐, 87.55.Gh

  5. SU-F-P-23: Setup Uncertainties for the Lung Stereotactic Body Radiation Therapy

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

    Zhang, Q; Vigneri, P; Madu, C

    2016-06-15

    Purpose: The Exactrack X-ray system with six degree-of-freedom (6DoF) adjustment ability can be used for setup of lung stereotactic body radiation therapy. The setup uncertainties from ExacTrack 6D system were analyzed. Methods: The Exactrack X-ray 6D image guided radiotherapy system is used in our clinic. The system is an integration of 2 subsystems: (1): an infrared based optical position system and (2) a radiography kV x-ray imaging system. The infrared system monitors reflective body markers on the patient’s skin to assistant in the initial setup. The radiographic kV devices were used for patient positions verification and adjustment. The position verificationmore » was made by fusing the radiographs with the digitally reconstructed radiograph (DRR) images generated by simulation CT images using 6DoF fusion algorithms. Those results were recorded in our system. Gaussian functions were used to fit the data. Results: For 37 lung SBRT patients, the image registration results for the initial setup by using surface markers and for the verifications, were measured. The results were analyzed for 143 treatments. The mean values for the lateral, longitudinal, vertical directions were 0.1, 0.3 and 0.3mm, respectively. The standard deviations for the lateral, longitudinal and vertical directions were 0.62, 0.78 and 0.75mm respectively. The mean values for the rotations around lateral, longitudinal and vertical directions were 0.1, 0.2 and 0.4 degrees respectively, with standard deviations of 0.36, 0.34, and 0.42 degrees. Conclusion: The setup uncertainties for the lung SBRT cases by using Exactrack 6D system were analyzed. The standard deviations of the setup errors were within 1mm for all three directions, and the standard deviations for rotations were within 0.5 degree.« less

  6. 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...

  7. 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.

  8. Routine sampling and the control of Legionella spp. in cooling tower water systems.

    PubMed

    Bentham, R H

    2000-10-01

    Cooling water samples from 31 cooling tower systems were cultured for Legionella over a 16-week summer period. The selected systems were known to be colonized by Legionella. Mean Legionella counts and standard deviations were calculated and time series correlograms prepared for each system. The standard deviations of Legionella counts in all the systems were very large, indicating great variability in the systems over the time period. Time series analyses demonstrated that in the majority of cases there was no significant relationship between the Legionella counts in the cooling tower at time of collection and the culture result once it was available. In the majority of systems (25/28), culture results from Legionella samples taken from the same systems 2 weeks apart were not statistically related. The data suggest that determinations of health risks from cooling towers cannot be reliably based upon single or infrequent Legionella tests.

  9. 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.

  10. The variance of length of stay and the optimal DRG outlier payments.

    PubMed

    Felder, Stefan

    2009-09-01

    Prospective payment schemes in health care often include supply-side insurance for cost outliers. In hospital reimbursement, prospective payments for patient discharges, based on their classification into diagnosis related group (DRGs), are complemented by outlier payments for long stay patients. The outlier scheme fixes the length of stay (LOS) threshold, constraining the profit risk of the hospitals. In most DRG systems, this threshold increases with the standard deviation of the LOS distribution. The present paper addresses the adequacy of this DRG outlier threshold rule for risk-averse hospitals with preferences depending on the expected value and the variance of profits. It first shows that the optimal threshold solves the hospital's tradeoff between higher profit risk and lower premium loading payments. It then demonstrates for normally distributed truncated LOS that the optimal outlier threshold indeed decreases with an increase in the standard deviation.

  11. 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.

  12. Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.

    PubMed

    Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin

    2017-09-01

    In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.

  13. Objective image characterization of a spectral CT scanner with dual-layer detector

    NASA Astrophysics Data System (ADS)

    Ozguner, Orhan; Dhanantwari, Amar; Halliburton, Sandra; Wen, Gezheng; Utrup, Steven; Jordan, David

    2018-01-01

    This work evaluated the performance of a detector-based spectral CT system by obtaining objective reference data, evaluating attenuation response of iodine and accuracy of iodine quantification, and comparing conventional CT and virtual monoenergetic images in three common phantoms. Scanning was performed using the hospital’s clinical adult body protocol. Modulation transfer function (MTF) was calculated for a tungsten wire and visual line pair targets were evaluated. Image noise power spectrum (NPS) and pixel standard deviation were calculated. MTF for monoenergetic images agreed with conventional images within 0.05 lp cm-1. NPS curves indicated that noise texture of 70 keV monoenergetic images is similar to conventional images. Standard deviation measurements showed monoenergetic images have lower noise except at 40 keV. Mean CT number and CNR agreed with conventional images at 75 keV. Measured iodine concentration agreed with true concentration within 6% for inserts at the center of the phantom. Performance of monoenergetic images at detector based spectral CT is the same as, or better than, that of conventional images. Spectral acquisition and reconstruction with a detector based platform represents the physical behaviour of iodine as expected and accurately quantifies the material concentration.

  14. Improved particle position accuracy from off-axis holograms using a Chebyshev model.

    PubMed

    Öhman, Johan; Sjödahl, Mikael

    2018-01-01

    Side scattered light from micrometer-sized particles is recorded using an off-axis digital holographic setup. From holograms, a volume is reconstructed with information about both intensity and phase. Finding particle positions is non-trivial, since poor axial resolution elongates particles in the reconstruction. To overcome this problem, the reconstructed wavefront around a particle is used to find the axial position. The method is based on the change in the sign of the curvature around the true particle position plane. The wavefront curvature is directly linked to the phase response in the reconstruction. In this paper we propose a new method of estimating the curvature based on a parametric model. The model is based on Chebyshev polynomials and is fit to the phase anomaly and compared to a plane wave in the reconstructed volume. From the model coefficients, it is possible to find particle locations. Simulated results show increased performance in the presence of noise, compared to the use of finite difference methods. The standard deviation is decreased from 3-39 μm to 6-10 μm for varying noise levels. Experimental results show a corresponding improvement where the standard deviation is decreased from 18 μm to 13 μm.

  15. Search for resonances in diphoton events at √{s}=13 TeV 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.; Barisits, M.-S.; 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.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; 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.; 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.; 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.; 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.; Cueto, A.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cúth, J.; 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.; 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.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, 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.; 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.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; 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.; Gentsos, C.; 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, R.; 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.; 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.; 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.; 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.; Herget, V.; Hernández Jiménez, Y.; 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.; 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.; 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.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, B.; Jackson, P.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansky, R.; Janssen, J.; Janus, M.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jeng, G.-Y.; Jennens, D.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Johansson, P.; Johns, K. A.; Johnson, W. J.; Jon-And, K.; Jones, G.; Jones, R. W. L.; 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.; Kaneti, S.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kapliy, A.; Kar, D.; Karakostas, K.; Karamaoun, A.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karnevskiy, M.; 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.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kempster, J. J.; Kentaro, K.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-zada, F.; Khanov, A.; Kharlamov, A. G.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; King, M.; King, S. B.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiss, F.; Kiuchi, K.; Kivernyk, O.; Kladiva, E.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klinger, J. A.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Knapik, J.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koehler, N. M.; Koffas, T.; Koffeman, E.; Koi, T.; Kolanoski, H.; Kolb, M.; Koletsou, I.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Köpke, L.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Kravchenko, A.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, A.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, A.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunigo, T.; Kupco, A.; Kurashige, H.; Kurochkin, Y. A.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; La Rosa Navarro, J. L.; La Rotonda, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; LeBlanc, M.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leisos, A.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Leontsinis, S.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Leyko, A. M.; Leyton, M.; Li, B.; Li, C.; Li, H.; Li, H. L.; Li, L.; Li, L.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, S. C.; Lin, T. H.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, H.; Liu, H.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo Sterzo, F.; Lobodzinska, E.; Loch, P.; Lockman, W. S.; Loebinger, F. K.; Loevschall-Jensen, A. E.; Loew, K. M.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopes, L.; Lopez Mateos, D.; Lopez Paredes, B.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; Macdonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A.; Magradze, E.; Mahlstedt, J.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maier, T.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandelli, B.; Mandelli, L.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchiori, G.; Marcisovsky, M.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Marti-Garcia, S.; Martin, B.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marx, M.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Mattmann, J.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; Mcfayden, J. A.; Mchedlidze, G.; McMahon, S. J.; McPherson, R. A.; Medinnis, M.; Meehan, S.; Mehlhase, S.; Mehta, A.; Meideck, T.; Meier, K.; Meineck, C.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Melo, M.; Meloni, F.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mjörnmark, J. U.; Moa, T.; Mochizuki, K.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Mortensen, S. S.; Morvaj, L.; Mosidze, M.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Mueller, T.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murillo Quijada, J. A.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Namasivayam, H.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nomachi, M.; Nomidis, I.; Nooney, T.; Norberg, S.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'grady, F.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagáčová, M.; Pagan Griso, S.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; St. Panagiotopoulou, E.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; 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.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Perez Codina, E.; 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.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reisin, H.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosenthal, O.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Salazar Loyola, J. E.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sandbach, R. L.; Sander, H. G.; Sandhoff, M.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. 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.; Savic, N.; 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.; 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.; 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.; 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, M.; 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.; Tu, Y.; 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.; Vallier, A.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; 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.; Veeraraghavan, V.; 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.; 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.

  16. Implementation of a dose gradient method into optimization of dose distribution in prostate cancer 3D-CRT plans

    PubMed Central

    Giżyńska, Marta K.; Kukołowicz, Paweł F.; Kordowski, Paweł

    2014-01-01

    Aim The aim of this work is to present a method of beam weight and wedge angle optimization for patients with prostate cancer. Background 3D-CRT is usually realized with forward planning based on a trial and error method. Several authors have published a few methods of beam weight optimization applicable to the 3D-CRT. Still, none on these methods is in common use. Materials and methods Optimization is based on the assumption that the best plan is achieved if dose gradient at ICRU point is equal to zero. Our optimization algorithm requires beam quality index, depth of maximum dose, profiles of wedged fields and maximum dose to femoral heads. The method was tested for 10 patients with prostate cancer, treated with the 3-field technique. Optimized plans were compared with plans prepared by 12 experienced planners. Dose standard deviation in target volume, and minimum and maximum doses were analyzed. Results The quality of plans obtained with the proposed optimization algorithms was comparable to that prepared by experienced planners. Mean difference in target dose standard deviation was 0.1% in favor of the plans prepared by planners for optimization of beam weights and wedge angles. Introducing a correction factor for patient body outline for dose gradient at ICRU point improved dose distribution homogeneity. On average, a 0.1% lower standard deviation was achieved with the optimization algorithm. No significant difference in mean dose–volume histogram for the rectum was observed. Conclusions Optimization shortens very much time planning. The average planning time was 5 min and less than a minute for forward and computer optimization, respectively. PMID:25337411

  17. Estimating Mixed Broadleaves Forest Stand Volume Using Dsm Extracted from Digital Aerial Images

    NASA Astrophysics Data System (ADS)

    Sohrabi, H.

    2012-07-01

    In mixed old growth broadleaves of Hyrcanian forests, it is difficult to estimate stand volume at plot level by remotely sensed data while LiDar data is absent. In this paper, a new approach has been proposed and tested for estimating stand forest volume. The approach is based on this idea that forest volume can be estimated by variation of trees height at plots. In the other word, the more the height variation in plot, the more the stand volume would be expected. For testing this idea, 120 circular 0.1 ha sample plots with systematic random design has been collected in Tonekaon forest located in Hyrcanian zone. Digital surface model (DSM) measure the height values of the first surface on the ground including terrain features, trees, building etc, which provides a topographic model of the earth's surface. The DSMs have been extracted automatically from aerial UltraCamD images so that ground pixel size for extracted DSM varied from 1 to 10 m size by 1m span. DSMs were checked manually for probable errors. Corresponded to ground samples, standard deviation and range of DSM pixels have been calculated. For modeling, non-linear regression method was used. The results showed that standard deviation of plot pixels with 5 m resolution was the most appropriate data for modeling. Relative bias and RMSE of estimation was 5.8 and 49.8 percent, respectively. Comparing to other approaches for estimating stand volume based on passive remote sensing data in mixed broadleaves forests, these results are more encouraging. One big problem in this method occurs when trees canopy cover is totally closed. In this situation, the standard deviation of height is low while stand volume is high. In future studies, applying forest stratification could be studied.

  18. A Bayesian Method for Identifying Contaminated Detectors in Low-Level Alpha Spectrometers

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

    Maclellan, Jay A.; Strom, Daniel J.; Joyce, Kevin E.

    2011-11-02

    Analyses used for radiobioassay and other radiochemical tests are normally designed to meet specified quality objectives, such relative bias, precision, and minimum detectable activity (MDA). In the case of radiobioassay analyses for alpha emitting radionuclides, a major determiner of the process MDA is the instrument background. Alpha spectrometry detectors are often restricted to only a few counts over multi-day periods in order to meet required MDAs for nuclides such as plutonium-239 and americium-241. A detector background criterion is often set empirically based on experience, or frequentist or classical statistics are applied to the calculated background count necessary to meet amore » required MDA. An acceptance criterion for the detector background is set at the multiple of the estimated background standard deviation above the assumed mean that provides an acceptably small probability of observation if the mean and standard deviation estimate are correct. The major problem with this method is that the observed background counts used to estimate the mean, and thereby the standard deviation when a Poisson distribution is assumed, are often in the range of zero to three counts. At those expected count levels it is impossible to obtain a good estimate of the true mean from a single measurement. As an alternative, Bayesian statistical methods allow calculation of the expected detector background count distribution based on historical counts from new, uncontaminated detectors. This distribution can then be used to identify detectors showing an increased probability of contamination. The effect of varying the assumed range of background counts (i.e., the prior probability distribution) from new, uncontaminated detectors will be is discussed.« less

  19. Making Meaningful Measurement in Survey Research: The Use of Person and Item Maps

    ERIC Educational Resources Information Center

    Royal, Kenneth D.

    2009-01-01

    Quality measurement is essential in every form of research, including institutional research and assessment. Unfortunately, most survey research today (both published and unpublished) is lacking with regards to quality measurement. Reporting means and standard deviations based on ordinal measures is an inappropriate, yet widespread practice in the…

  20. Luminance sticker based facial expression recognition using discrete wavelet transform for physically disabled persons.

    PubMed

    Nagarajan, R; Hariharan, M; Satiyan, M

    2012-08-01

    Developing tools to assist physically disabled and immobilized people through facial expression is a challenging area of research and has attracted many researchers recently. In this paper, luminance stickers based facial expression recognition is proposed. Recognition of facial expression is carried out by employing Discrete Wavelet Transform (DWT) as a feature extraction method. Different wavelet families with their different orders (db1 to db20, Coif1 to Coif 5 and Sym2 to Sym8) are utilized to investigate their performance in recognizing facial expression and to evaluate their computational time. Standard deviation is computed for the coefficients of first level of wavelet decomposition for every order of wavelet family. This standard deviation is used to form a set of feature vectors for classification. In this study, conventional validation and cross validation are performed to evaluate the efficiency of the suggested feature vectors. Three different classifiers namely Artificial Neural Network (ANN), k-Nearest Neighborhood (kNN) and Linear Discriminant Analysis (LDA) are used to classify a set of eight facial expressions. The experimental results demonstrate that the proposed method gives very promising classification accuracies.

  1. Accuracy of a method based on atomic absorption spectrometry to determine inorganic arsenic in food: Outcome of the collaborative trial IMEP-41.

    PubMed

    Fiamegkos, I; Cordeiro, F; Robouch, P; Vélez, D; Devesa, V; Raber, G; Sloth, J J; Rasmussen, R R; Llorente-Mirandes, T; Lopez-Sanchez, J F; Rubio, R; Cubadda, F; D'Amato, M; Feldmann, J; Raab, A; Emteborg, H; de la Calle, M B

    2016-12-15

    A collaborative trial was conducted to determine the performance characteristics of an analytical method for the quantification of inorganic arsenic (iAs) in food. The method is based on (i) solubilisation of the protein matrix with concentrated hydrochloric acid to denature proteins and allow the release of all arsenic species into solution, and (ii) subsequent extraction of the inorganic arsenic present in the acid medium using chloroform followed by back-extraction to acidic medium. The final detection and quantification is done by flow injection hydride generation atomic absorption spectrometry (FI-HG-AAS). The seven test items used in this exercise were reference materials covering a broad range of matrices: mussels, cabbage, seaweed (hijiki), fish protein, rice, wheat, mushrooms, with concentrations ranging from 0.074 to 7.55mgkg(-1). The relative standard deviation for repeatability (RSDr) ranged from 4.1 to 10.3%, while the relative standard deviation for reproducibility (RSDR) ranged from 6.1 to 22.8%. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. Monitoring the metering performance of an electronic voltage transformer on-line based on cyber-physics correlation analysis

    NASA Astrophysics Data System (ADS)

    Zhang, Zhu; Li, Hongbin; Tang, Dengping; Hu, Chen; Jiao, Yang

    2017-10-01

    Metering performance is the key parameter of an electronic voltage transformer (EVT), and it requires high accuracy. The conventional off-line calibration method using a standard voltage transformer is not suitable for the key equipment in a smart substation, which needs on-line monitoring. In this article, we propose a method for monitoring the metering performance of an EVT on-line based on cyber-physics correlation analysis. By the electrical and physical properties of a substation running in three-phase symmetry, the principal component analysis method is used to separate the metering deviation caused by the primary fluctuation and the EVT anomaly. The characteristic statistics of the measured data during operation are extracted, and the metering performance of the EVT is evaluated by analyzing the change in statistics. The experimental results show that the method successfully monitors the metering deviation of a Class 0.2 EVT accurately. The method demonstrates the accurate evaluation of on-line monitoring of the metering performance on an EVT without a standard voltage transformer.

  3. Detecting the optic disc boundary in digital fundus images using morphological, edge detection, and feature extraction techniques.

    PubMed

    Aquino, Arturo; Gegundez-Arias, Manuel Emilio; Marin, Diego

    2010-11-01

    Optic disc (OD) detection is an important step in developing systems for automated diagnosis of various serious ophthalmic pathologies. This paper presents a new template-based methodology for segmenting the OD from digital retinal images. This methodology uses morphological and edge detection techniques followed by the Circular Hough Transform to obtain a circular OD boundary approximation. It requires a pixel located within the OD as initial information. For this purpose, a location methodology based on a voting-type algorithm is also proposed. The algorithms were evaluated on the 1200 images of the publicly available MESSIDOR database. The location procedure succeeded in 99% of cases, taking an average computational time of 1.67 s. with a standard deviation of 0.14 s. On the other hand, the segmentation algorithm rendered an average common area overlapping between automated segmentations and true OD regions of 86%. The average computational time was 5.69 s with a standard deviation of 0.54 s. Moreover, a discussion on advantages and disadvantages of the models more generally used for OD segmentation is also presented in this paper.

  4. The Comparison of Iranian Normative Reference Data with Five Countries ‎Across Variables in Eight Rorschach Comprehensive System (CS) Clusters

    PubMed Central

    Hosseininasab, Abufazel; Mohammadi, Mohammadreza; Jouzi, Samira; Esmaeilinasab, Maryam; Delavar, Ali

    2016-01-01

    Objective: This study aimed to provide a normative study documenting how 114 five-seven year-old non-‎patient Iranian children respond to the Rorschach test. We compared this especial sample to ‎international normative reference values for the Comprehensive System (CS).‎ Method: One hundred fourteen 5- 7- year-old non-patient Iranian children were recruited from public ‎schools. Using five child and adolescent samples from five countries, we compared Iranian ‎Normative Reference Data- based on reference means and standard deviations for each sample.‎ Results: Findings revealed that how the scores in each sample were distributed and how the samples were ‎compared across variables in eight Rorschach Comprehensive System (CS) clusters. We reported ‎all descriptive statistics such as reference mean and standard deviation for all variables.‎ Conclusion: Iranian clinicians could rely on country specific or “local norms” when assessing children. We ‎discourage Iranian clinicians to use many CS scores to make nomothetic, score-based inferences ‎about psychopathology in children and adolescents.‎ PMID:27928247

  5. Accuracy of the HST Standard Astrometric Catalogs w.r.t. Gaia

    NASA Astrophysics Data System (ADS)

    Kozhurina-Platais, V.; Grogin, N.; Sabbi, E.

    2018-02-01

    The goal of astrometric calibration of the HST ACS/WFC and WFC3/UVIS imaging instruments is to provide a coordinate system free of distortion to the precision level of 0.1 pixel 4-5 mas or better. This astrometric calibration is based on two HST astrometric standard fields in the vicinity of the globular clusters, 47 Tuc and omega Cen, respectively. The derived calibration of the geometric distortion is assumed to be accurate down to 2-3 mas. Is this accuracy in agreement with the true value? Now, with the access to globally accurate positions from the first Gaia data release (DR1), we found that there are measurable offsets, rotation, scale and other deviations of distortion parameters in two HST standard astrometric catalogs. These deviations from the distortion-free and properly aligned coordinate system should be accounted and corrected for, so that the high precision HST positions are free of any systematic errors. We also found that the precision of the HST pixel coordinates is substantially better than the accuracy listed in the Gaia DR1. Therefore, in order to finalize the components of distortion in the HST standard catalogs, the next release of Gaia data is needed.

  6. Observation of Electroweak Production of Same-Sign W Boson Pairs in the Two Jet and Two Same-Sign Lepton Final State in Proton-Proton Collisions at √{s }=13 TeV

    NASA Astrophysics Data System (ADS)

    Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Dorney, B.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Starling, E.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; Caudron, A.; David, P.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Saggio, A.; Vidal Marono, M.; Wertz, S.; Zobec, J.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Coelho, E.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Sanchez Rosas, L. J.; Santoro, A.; Sznajder, A.; Thiel, M.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Yuan, L.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhang, S.; 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.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; 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.; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkilä, J. K.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Lindén, T.; Luukka, P.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Leloup, C.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; 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.; Jansová, M.; Le Bihan, A.-C.; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; 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.; Viret, S.; Khvedelidze, A.; Bagaturia, I.; Autermann, C.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Zhukov, V.; Albert, A.; 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.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; 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.; Bermúdez Martínez, A.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; 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.; Guthoff, M.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; 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.; Raspereza, A.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Aggleton, R.; Bein, S.; Blobel, V.; Centis Vignali, M.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Hoffmann, M.; Karavdina, 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.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baselga, M.; Baur, S.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Faltermann, N.; Freund, B.; Friese, R.; Giffels, M.; Harrendorf, M. A.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; 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.; Karathanasis, G.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Kousouris, K.; Evangelou, I.; Foudas, C.; Kokkas, P.; Mallios, S.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Csanad, M.; Filipovic, N.; Pasztor, G.; Surányi, O.; Veres, G. I.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; 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.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kaur, S.; Kumar, R.; Kumari, P.; Mehta, A.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Bhawandeep, U.; 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.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhattacharya, S.; Chatterjee, S.; Das, P.; 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.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Lezki, S.; 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.; Borgonovi, L.; Braibant-Giacomelli, S.; 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.; Chatterjee, K.; 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.; Robutti, E.; Tosi, S.; Benaglia, A.; Beschi, A.; 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.; Pauwels, K.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Khan, W. A.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Biasini, M.; Bilei, G. M.; Cecchi, C.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Manoni, E.; Mantovani, G.; Mariani, V.; Menichelli, M.; Rossi, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giannini, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Manca, E.; Mandorli, G.; 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.; Daci, N.; Del Re, D.; Di Marco, E.; 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.; Moon, C. S.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; 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.; Choi, M.; 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.; 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. V.; Seixas, J.; Strong, G.; 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.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; 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.; Stepennov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Bylinkin, A.; Chadeeva, M.; Markin, O.; Parygin, P.; Philippov, D.; Polikarpov, S.; Rusinov, V.; Zhemchugov, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; 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.; Mandrik, P.; 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.; Cerrada, 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.; 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.; Albajar, C.; 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.; Akgun, B.; Auffray, E.; Baillon, P.; Ball, A. H.; Barney, D.; Bendavid, J.; 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.; Deelen, N.; Dobson, M.; 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.; Jafari, A.; Janot, P.; Karacheban, O.; Kieseler, J.; 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.; 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.; 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.; Backhaus, M.; Bäni, L.; Berger, P.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dorfer, C.; 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.; 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.; 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.; Schweiger, K.; 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.; 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.; 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.; 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.; 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.; 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.; Garabedian, A.; 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.; 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.; 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.; 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.; 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.; 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.; 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.; 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.; Gleyzer, S. V.; Joshi, B. M.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; 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.; 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.; 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.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Hu, M.; 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.; Hiltbrand, J.; 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.; 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.; 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.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Adair, A.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. M.; Guilbaud, M.; Kilpatrick, M.; Li, W.; Michlin, B.; Northup, M.; 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.; 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.; 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.; 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.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

    2018-02-01

    The first observation of electroweak production of same-sign W boson pairs in proton-proton collisions is reported. The data sample corresponds to an integrated luminosity of 35.9 fb-1 collected at a center-of-mass energy of 13 TeV with the CMS detector at the LHC. Events are selected by requiring exactly two leptons (electrons or muons) of the same charge, moderate missing transverse momentum, and two jets with a large rapidity separation and a large dijet mass. The observed significance of the signal is 5.5 standard deviations, where a significance of 5.7 standard deviations is expected based on the standard model. The ratio of measured event yields to that expected from the standard model at leading order is 0.90 ±0.22 . A cross section measurement in a fiducial region is reported. Bounds are given on the structure of quartic vector boson interactions in the framework of dimension-8 effective field theory operators and on the production of doubly charged Higgs bosons.

  7. Virtual reality technology prevents accidents in extreme situations

    NASA Astrophysics Data System (ADS)

    Badihi, Y.; Reiff, M. N.; Beychok, S.

    2012-03-01

    This research is aimed at examining the added value of using Virtual Reality (VR) in a driving simulator to prevent road accidents, specifically by improving drivers' skills when confronted with extreme situations. In an experiment, subjects completed a driving scenario using two platforms: A 3-D Virtual Reality display system using an HMD (Head-Mounted Display), and a standard computerized display system based on a standard computer monitor. The results show that the average rate of errors (deviating from the driving path) in a VR environment is significantly lower than in the standard one. In addition, there was no compensation between speed and accuracy in completing the driving mission. On the contrary: The average speed was even slightly faster in the VR simulation than in the standard environment. Thus, generally, despite the lower rate of deviation in VR setting, it is not achieved by driving slower. When the subjects were asked about their personal experiences from the training session, most of the subjects responded that among other things, the VR session caused them to feel a higher sense of commitment to the task and their performance. Some of them even stated that the VR session gave them a real sensation of driving.

  8. Observation of Electroweak Production of Same-Sign W Boson Pairs in the Two Jet and Two Same-Sign Lepton Final State in Proton-Proton Collisions at s = 13 TeV

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

    Sirunyan, A. M.; Tumasyan, A.; Adam, W.

    The first observation of electroweak production of same-sign W boson pairs in proton-proton collisions is reported. The data sample corresponds to an integrated luminosity of 35.9 fb -1 collected at a center-of-mass energy of 13 TeV with the CMS detector at the LHC. Events are selected by requiring exactly two leptons (electrons or muons) of the same charge, moderate missing transverse momentum, and two jets with a large rapidity separation and a large dijet mass. The observed significance of the signal is 5.5 standard deviations, where a significance of 5.7 standard deviations is expected based on the standard model. The ratiomore » of measured event yields to that expected from the standard model at leading order is 0.90±0.22. A cross section measurement in a fiducial region is reported. Bounds are given on the structure of quartic vector boson interactions in the framework of dimension-8 effective field theory operators and on the production of doubly charged Higgs bosons.« less

  9. 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%.

  10. Observation of Electroweak Production of Same-Sign W Boson Pairs in the Two Jet and Two Same-Sign Lepton Final State in Proton-Proton Collisions at s = 13 TeV

    DOE PAGES

    Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...

    2018-02-22

    The first observation of electroweak production of same-sign W boson pairs in proton-proton collisions is reported. The data sample corresponds to an integrated luminosity of 35.9 fb -1 collected at a center-of-mass energy of 13 TeV with the CMS detector at the LHC. Events are selected by requiring exactly two leptons (electrons or muons) of the same charge, moderate missing transverse momentum, and two jets with a large rapidity separation and a large dijet mass. The observed significance of the signal is 5.5 standard deviations, where a significance of 5.7 standard deviations is expected based on the standard model. The ratiomore » of measured event yields to that expected from the standard model at leading order is 0.90±0.22. A cross section measurement in a fiducial region is reported. Bounds are given on the structure of quartic vector boson interactions in the framework of dimension-8 effective field theory operators and on the production of doubly charged Higgs bosons.« less

  11. Observation of Electroweak Production of Same-Sign W Boson Pairs in the Two Jet and Two Same-Sign Lepton Final State in Proton-Proton Collisions at sqrt[s]=13  TeV.

    PubMed

    Sirunyan, A M; Tumasyan, A; Adam, W; Ambrogi, F; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Flechl, M; Friedl, M; Frühwirth, R; Ghete, V M; Grossmann, J; Hrubec, J; Jeitler, M; König, A; Krammer, N; Krätschmer, I; Liko, D; Madlener, T; Mikulec, I; Pree, E; Rad, N; Rohringer, H; Schieck, J; Schöfbeck, R; Spanring, M; Spitzbart, D; Waltenberger, W; Wittmann, J; Wulz, C-E; Zarucki, M; Chekhovsky, V; Mossolov, V; Suarez Gonzalez, J; De Wolf, E A; Di Croce, D; Janssen, X; Lauwers, J; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Abu Zeid, S; Blekman, F; D'Hondt, J; De Bruyn, I; De Clercq, J; Deroover, K; Flouris, G; Lontkovskyi, D; Lowette, S; Moortgat, S; Moreels, L; Python, Q; Skovpen, K; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Parijs, I; Beghin, D; Brun, H; Clerbaux, B; De Lentdecker, G; Delannoy, H; Dorney, B; Fasanella, G; Favart, L; Goldouzian, R; Grebenyuk, A; Karapostoli, G; Lenzi, T; Luetic, J; Maerschalk, T; Marinov, A; Randle-Conde, A; Seva, T; Starling, E; Vander Velde, C; Vanlaer, P; Vannerom, D; Yonamine, R; Zenoni, F; Zhang, F; Cimmino, A; Cornelis, T; Dobur, D; Fagot, A; Gul, M; Khvastunov, I; Poyraz, D; Roskas, C; Salva, S; Tytgat, M; Verbeke, W; Zaganidis, N; Bakhshiansohi, H; Bondu, O; Brochet, S; Bruno, G; Caputo, C; Caudron, A; David, P; De Visscher, S; Delaere, C; Delcourt, M; Francois, B; Giammanco, A; Komm, M; Krintiras, G; Lemaitre, V; Magitteri, A; Mertens, A; Musich, M; Piotrzkowski, K; Quertenmont, L; Saggio, A; Vidal Marono, M; Wertz, S; Zobec, J; Beliy, N; Aldá Júnior, W L; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Coelho, E; Da Costa, E M; Da Silveira, G G; De Jesus Damiao, D; Fonseca De Souza, S; Huertas Guativa, L M; Malbouisson, H; Melo De Almeida, M; Mora Herrera, C; Mundim, L; Nogima, H; Sanchez Rosas, L J; Santoro, A; Sznajder, A; Thiel, M; Tonelli Manganote, E J; Torres Da Silva De Araujo, F; Vilela Pereira, A; Ahuja, S; Bernardes, C A; Fernandez Perez Tomei, T R; Gregores, E M; Mercadante, P G; Novaes, S F; Padula, Sandra S; Romero Abad, D; Ruiz Vargas, J C; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Misheva, M; Rodozov, M; Shopova, M; Sultanov, G; Dimitrov, A; Glushkov, I; Litov, L; Pavlov, B; Petkov, P; Fang, W; Gao, X; Yuan, L; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Chen, Y; Jiang, C H; Leggat, D; Liao, H; Liu, Z; Romeo, F; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Yazgan, E; Zhang, H; Zhang, S; 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; González Hernández, C F; Ruiz Alvarez, J D; Courbon, B; Godinovic, N; Lelas, D; Puljak, I; Ribeiro Cipriano, P M; Sculac, T; Antunovic, Z; Kovac, M; Brigljevic, V; Ferencek, D; Kadija, K; Mesic, B; Starodumov, A; 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; Abdelalim, A A; Mohammed, Y; Salama, E; Dewanjee, R K; Kadastik, M; Perrini, L; Raidal, M; Tiko, A; Veelken, C; Eerola, P; Kirschenmann, H; Pekkanen, J; Voutilainen, M; Havukainen, J; Heikkilä, J K; Järvinen, T; Karimäki, V; Kinnunen, R; Lampén, T; Lassila-Perini, K; Laurila, S; Lehti, S; Lindén, T; Luukka, P; Siikonen, H; Tuominen, E; Tuominiemi, J; Talvitie, J; Tuuva, T; Besancon, M; Couderc, F; Dejardin, M; Denegri, D; Faure, J L; Ferri, F; Ganjour, S; Ghosh, S; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Kucher, I; Leloup, C; Locci, E; Machet, M; Malcles, J; Negro, G; Rander, J; Rosowsky, A; Sahin, M Ö; Titov, M; Abdulsalam, A; Amendola, C; Antropov, I; Baffioni, S; Beaudette, F; Busson, P; Cadamuro, L; Charlot, C; Granier de Cassagnac, R; Jo, M; Lisniak, S; Lobanov, A; Martin Blanco, J; Nguyen, M; Ochando, C; Ortona, G; Paganini, P; Pigard, P; Salerno, R; Sauvan, J B; 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; Jansová, M; Le Bihan, A-C; Tonon, N; Van Hove, P; Gadrat, S; Beauceron, S; Bernet, C; Boudoul, G; Chierici, R; Contardo, D; 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; Viret, S; Khvedelidze, A; Bagaturia, I; Autermann, C; Feld, L; Kiesel, M K; Klein, K; Lipinski, M; Preuten, M; Schomakers, C; Schulz, J; Zhukov, V; Albert, A; 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; Pook, T; Radziej, M; Reithler, H; Rieger, M; Scheuch, F; Teyssier, D; Thüer, S; Flügge, G; Kargoll, B; Kress, T; Künsken, A; 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; Bermúdez Martínez, A; Bin Anuar, A A; Borras, K; Botta, V; Campbell, A; Connor, P; Contreras-Campana, C; Costanza, F; Diez Pardos, C; 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; Guthoff, M; Harb, A; Hauk, J; Hempel, M; Jung, H; Kalogeropoulos, A; 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; Raspereza, A; Savitskyi, M; Saxena, P; Shevchenko, R; Spannagel, S; Stefaniuk, N; Van Onsem, G P; Walsh, R; Wen, Y; Wichmann, K; Wissing, C; Zenaiev, O; Aggleton, R; Bein, S; Blobel, V; Centis Vignali, M; Dreyer, T; Garutti, E; Gonzalez, D; Haller, J; Hinzmann, A; Hoffmann, M; Karavdina, 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; Vanhoefer, A; Vormwald, B; Akbiyik, M; Barth, C; Baselga, M; Baur, S; Butz, E; Caspart, R; Chwalek, T; Colombo, F; De Boer, W; Dierlamm, A; Faltermann, N; Freund, B; Friese, R; Giffels, M; Harrendorf, M A; Hartmann, F; Heindl, S M; Husemann, U; Kassel, F; Kudella, S; Mildner, H; Mozer, M U; Müller, Th; Plagge, M; Quast, G; Rabbertz, K; 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; Karathanasis, G; Kesisoglou, S; Panagiotou, A; Saoulidou, N; Kousouris, K; Evangelou, I; Foudas, C; Kokkas, P; Mallios, S; Manthos, N; Papadopoulos, I; Paradas, E; Strologas, J; Triantis, F A; Csanad, M; Filipovic, N; Pasztor, G; Surányi, O; Veres, G I; Bencze, G; Hajdu, C; Horvath, D; Hunyadi, Á; Sikler, F; Veszpremi, V; 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; Dhingra, N; Kalsi, A K; Kaur, A; Kaur, M; Kaur, S; Kumar, R; Kumari, P; Mehta, A; Singh, J B; Walia, G; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A; Chauhan, S; Choudhary, B C; Garg, R B; Keshri, S; Kumar, A; Malhotra, S; Naimuddin, M; Ranjan, K; Sharma, R; Bhardwaj, R; Bhattacharya, R; Bhattacharya, S; Bhawandeep, U; 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; Mahakud, B; Mitra, S; Mohanty, G B; Sur, N; Sutar, B; Banerjee, S; Bhattacharya, S; Chatterjee, S; Das, P; 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; Colaleo, A; Creanza, D; Cristella, L; De Filippis, N; De Palma, M; Errico, F; Fiore, L; Iaselli, G; Lezki, S; 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; Borgonovi, L; Braibant-Giacomelli, S; 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; Chatterjee, K; 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; Robutti, E; Tosi, S; Benaglia, A; Beschi, A; 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; Pauwels, K; Pedrini, D; Pigazzini, S; Ragazzi, S; Redaelli, N; Tabarelli de Fatis, T; Buontempo, S; Cavallo, N; Di Guida, S; Fabozzi, F; Fienga, F; Iorio, A O M; Khan, W A; Lista, L; Meola, S; Paolucci, P; Sciacca, C; Thyssen, F; Azzi, P; Bacchetta, N; Benato, L; Bisello, D; Boletti, A; Carlin, R; Carvalho Antunes De Oliveira, A; Checchia, P; De Castro Manzano, P; Dorigo, T; Dosselli, U; Gasparini, F; Gasparini, U; Gozzelino, A; Lacaprara, S; Margoni, M; Meneguzzo, A T; Pozzobon, N; Ronchese, P; Rossin, R; Simonetto, F; Torassa, E; Zanetti, M; Zotto, P; Zumerle, G; Braghieri, A; Magnani, A; Montagna, P; Ratti, S P; Re, V; Ressegotti, M; Riccardi, C; Salvini, P; Vai, I; Vitulo, P; Alunni Solestizi, L; Biasini, M; Bilei, G M; Cecchi, C; Ciangottini, D; Fanò, L; Lariccia, P; Leonardi, R; Manoni, E; Mantovani, G; Mariani, V; Menichelli, M; Rossi, A; Santocchia, A; Spiga, D; Androsov, K; Azzurri, P; Bagliesi, G; Boccali, T; Borrello, L; Castaldi, R; Ciocci, M A; Dell'Orso, R; Fedi, G; Giannini, L; Giassi, A; Grippo, M T; Ligabue, F; Lomtadze, T; Manca, E; Mandorli, G; 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; Daci, N; Del Re, D; Di Marco, E; 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; Moon, C S; Oh, Y D; Sekmen, S; Son, D C; Yang, Y C; Lee, A; 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; Choi, M; 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; 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 V; Seixas, J; Strong, G; 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; Ivanov, Y; Kim, V; Kuznetsova, E; Levchenko, P; Murzin, V; Oreshkin, V; Smirnov, I; Sulimov, V; Uvarov, L; Vavilov, S; 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; Stepennov, A; Toms, M; Vlasov, E; Zhokin, A; Aushev, T; Bylinkin, A; Chadeeva, M; Markin, O; Parygin, P; Philippov, D; Polikarpov, S; Rusinov, V; Zhemchugov, E; Andreev, V; Azarkin, M; Dremin, I; Kirakosyan, M; Terkulov, A; Baskakov, A; Belyaev, A; Boos, E; Bunichev, V; Dubinin, M; Dudko, L; 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; Mandrik, P; 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; Cerrada, 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; 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; Albajar, C; 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; Akgun, B; Auffray, E; Baillon, P; Ball, A H; Barney, D; Bendavid, J; 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; Deelen, N; Dobson, M; 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; Jafari, A; Janot, P; Karacheban, O; Kieseler, J; 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; 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; 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; Backhaus, M; Bäni, L; Berger, P; Bianchini, L; Casal, B; Dissertori, G; Dittmar, M; Donegà, M; Dorfer, C; 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; 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; 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; Schweiger, K; 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; 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; 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; 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; 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; 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; Garabedian, A; 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; 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; 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; 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; 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; 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; 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; 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; Gleyzer, S V; Joshi, B M; Konigsberg, J; Korytov, A; Kotov, K; Ma, P; Matchev, K; Mei, H; Mitselmakher, G; Rank, D; 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; 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; 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; Bi, R; Brandt, S; Busza, W; Cali, I A; D'Alfonso, M; Demiragli, Z; Gomez Ceballos, G; Goncharov, M; Hsu, D; Hu, M; 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; Hiltbrand, J; 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; 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; 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; Qiu, H; Schulte, J F; Sun, J; Wang, F; Xie, W; Cheng, T; Parashar, N; Stupak, J; Adair, A; Chen, Z; Ecklund, K M; Freed, S; Geurts, F J M; Guilbaud, M; Kilpatrick, M; Li, W; Michlin, B; Northup, M; 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; 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; 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; 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; Polese, G; Ruggles, T; Savin, A; Smith, N; Smith, W H; Taylor, D; Woods, N

    2018-02-23

    The first observation of electroweak production of same-sign W boson pairs in proton-proton collisions is reported. The data sample corresponds to an integrated luminosity of 35.9    fb^{-1} collected at a center-of-mass energy of 13 TeV with the CMS detector at the LHC. Events are selected by requiring exactly two leptons (electrons or muons) of the same charge, moderate missing transverse momentum, and two jets with a large rapidity separation and a large dijet mass. The observed significance of the signal is 5.5 standard deviations, where a significance of 5.7 standard deviations is expected based on the standard model. The ratio of measured event yields to that expected from the standard model at leading order is 0.90±0.22. A cross section measurement in a fiducial region is reported. Bounds are given on the structure of quartic vector boson interactions in the framework of dimension-8 effective field theory operators and on the production of doubly charged Higgs bosons.

  12. 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.

  13. Particle size distributions by transmission electron microscopy: an interlaboratory comparison case study

    PubMed Central

    Rice, Stephen B; Chan, Christopher; Brown, Scott C; Eschbach, Peter; Han, Li; Ensor, David S; Stefaniak, Aleksandr B; Bonevich, John; Vladár, András E; Hight Walker, Angela R; Zheng, Jiwen; Starnes, Catherine; Stromberg, Arnold; Ye, Jia; Grulke, Eric A

    2015-01-01

    This paper reports an interlaboratory comparison that evaluated a protocol for measuring and analysing the particle size distribution of discrete, metallic, spheroidal nanoparticles using transmission electron microscopy (TEM). The study was focused on automated image capture and automated particle analysis. NIST RM8012 gold nanoparticles (30 nm nominal diameter) were measured for area-equivalent diameter distributions by eight laboratories. Statistical analysis was used to (1) assess the data quality without using size distribution reference models, (2) determine reference model parameters for different size distribution reference models and non-linear regression fitting methods and (3) assess the measurement uncertainty of a size distribution parameter by using its coefficient of variation. The interlaboratory area-equivalent diameter mean, 27.6 nm ± 2.4 nm (computed based on a normal distribution), was quite similar to the area-equivalent diameter, 27.6 nm, assigned to NIST RM8012. The lognormal reference model was the preferred choice for these particle size distributions as, for all laboratories, its parameters had lower relative standard errors (RSEs) than the other size distribution reference models tested (normal, Weibull and Rosin–Rammler–Bennett). The RSEs for the fitted standard deviations were two orders of magnitude higher than those for the fitted means, suggesting that most of the parameter estimate errors were associated with estimating the breadth of the distributions. The coefficients of variation for the interlaboratory statistics also confirmed the lognormal reference model as the preferred choice. From quasi-linear plots, the typical range for good fits between the model and cumulative number-based distributions was 1.9 fitted standard deviations less than the mean to 2.3 fitted standard deviations above the mean. Automated image capture, automated particle analysis and statistical evaluation of the data and fitting coefficients provide a framework for assessing nanoparticle size distributions using TEM for image acquisition. PMID:26361398

  14. Determination of volatile bases in seafood using the ammonia ion selective electrode: collaborative study.

    PubMed

    Ellis, P C; Pivarnik, L F; Thiam, M; Ellis, P C; Pivarnik, L F; Thiam, M

    2000-01-01

    Nine collaborating laboratories tested a combination of 23 seafood samples for volatile bases using an ammonia ion selective electrode. Results were reported as mg NH3/100 g fish, but the method reflected levels of both ammonia and trimethylamine, which permeated the ammonia membrane. The 23 samples were broken down into 8 blind duplicate pairs, 2 Youden matched pairs, and 3 single samples covering fresh to spoiled product ranging from 8 to 82 mg NH3/100 g. Seven species were evaluated: Atlantic cod, squid, Atlantic halibut, gray sole, monkfish, dogfish, and Atlantic mackerel. The ammonia electrode assay was performed on an aqueous homogenate consisting of 95 mL distilled water and 5.0 g sample tissue. Alkaline ion strength adjusting solution (2 mL) was added to the homogenate to liberate ammonia that was sensed by the ion specific electrode and measured on a precalibrated portable meter. Repeatability standard deviations (RSDr) ranged from 4.2 to 17%; reproducibility standard deviations (RSDR) ranged from 8.8 to 21%. A standard ammonium chloride solution was provided to all laboratories to spike 3 different samples at 10 mg NH3/100 g. Recoveries of added ammonia as ammonium chloride for fresh, borderline, and spoiled samples were 88.6, 107, and 128%, respectively.

  15. 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…

  16. 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.…

  17. 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.

  18. 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.

  19. 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.

  20. 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

  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. 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.

  3. 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.

  4. 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...

  5. Inter-laboratory Comparison of Three Earplug Fit-test Systems

    PubMed Central

    Byrne, David C.; Murphy, William J.; Krieg, Edward F.; Ghent, Robert M.; Michael, Kevin L.; Stefanson, Earl W.; Ahroon, William A.

    2017-01-01

    The National Institute for Occupational Safety and Health (NIOSH) sponsored tests of three earplug fit-test systems (NIOSH HPD Well-Fit™, Michael & Associates FitCheck, and Honeywell Safety Products VeriPRO®). Each system was compared to laboratory-based real-ear attenuation at threshold (REAT) measurements in a sound field according to ANSI/ASA S12.6-2008 at the NIOSH, Honeywell Safety Products, and Michael & Associates testing laboratories. An identical study was conducted independently at the U.S. Army Aeromedical Research Laboratory (USAARL), which provided their data for inclusion in this report. The Howard Leight Airsoft premolded earplug was tested with twenty subjects at each of the four participating laboratories. The occluded fit of the earplug was maintained during testing with a soundfield-based laboratory REAT system as well as all three headphone-based fit-test systems. The Michael & Associates lab had highest average A-weighted attenuations and smallest standard deviations. The NIOSH lab had the lowest average attenuations and the largest standard deviations. Differences in octave-band attenuations between each fit-test system and the American National Standards Institute (ANSI) sound field method were calculated (Attenfit-test - AttenANSI). A-weighted attenuations measured with FitCheck and HPD Well-Fit systems demonstrated approximately ±2 dB agreement with the ANSI sound field method, but A-weighted attenuations measured with the VeriPRO system underestimated the ANSI laboratory attenuations. For each of the fit-test systems, the average A-weighted attenuation across the four laboratories was not significantly greater than the average of the ANSI sound field method. Standard deviations for residual attenuation differences were about ±2 dB for FitCheck and HPD Well-Fit compared to ±4 dB for VeriPRO. Individual labs exhibited a range of agreement from less than a dB to as much as 9.4 dB difference with ANSI and REAT estimates. Factors such as the experience of study participants and test administrators, and the fit-test psychometric tasks are suggested as possible contributors to the observed results. PMID:27786602

  6. Anti-inflammatory drugs and prediction of new structures by comparative analysis.

    PubMed

    Bartzatt, Ronald

    2012-01-01

    Nonsteroidal anti-inflammatory drugs (NSAIDs) are a group of agents important for their analgesic, anti-inflammatory, and antipyretic properties. This study presents several approaches to predict and elucidate new molecular structures of NSAIDs based on 36 known and proven anti-inflammatory compounds. Based on 36 known NSAIDs the mean value of Log P is found to be 3.338 (standard deviation= 1.237), mean value of polar surface area is 63.176 Angstroms2 (standard deviation = 20.951 A2), and the mean value of molecular weight is 292.665 (standard deviation = 55.627). Nine molecular properties are determined for these 36 NSAID agents, including Log P, number of -OH and -NHn, violations of Rule of 5, number of rotatable bonds, and number of oxygens and nitrogens. Statistical analysis of these nine molecular properties provides numerical parameters to conform to in the design of novel NSAID drug candidates. Multiple regression analysis is accomplished using these properties of 36 agents followed with examples of predicted molecular weight based on minimum and maximum property values. Hierarchical cluster analysis indicated that licofelone, tolfenamic acid, meclofenamic acid, droxicam, and aspirin are substantially distinct from all remaining NSAIDs. Analysis of similarity (ANOSIM) produced R = 0.4947, which indicates low to moderate level of dissimilarity between these 36 NSAIDs. Non-hierarchical K-means cluster analysis separated the 36 NSAIDs into four groups having members of greatest similarity. Likewise, discriminant analysis divided the 36 agents into two groups indicating the greatest level of distinction (discrimination) based on nine properties. These two multivariate methods together provide investigators a means to compare and elucidate novel drug designs to 36 proven compounds and ascertain to which of those are most analogous in pharmacodynamics. In addition, artificial neural network modeling is demonstrated as an approach to predict numerous molecular properties of new drug designs that is based on neural training from 36 proven NSAIDs. Comprehensive and effective approaches are presented in this study for the design of new NSAID type agents which are so very important for inhibition of COX-2 and COX-1 isoenzymes.

  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. 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

  9. Evaluation of the MV (CAPON) Coherent Doppler Lidar Velocity Estimator

    NASA Technical Reports Server (NTRS)

    Lottman, B.; Frehlich, R.

    1997-01-01

    The performance of the CAPON velocity estimator for coherent Doppler lidar is determined for typical space-based and ground-based parameter regimes. Optimal input parameters for the algorithm were determined for each regime. For weak signals, performance is described by the standard deviation of the good estimates and the fraction of outliers. For strong signals, the fraction of outliers is zero. Numerical effort was also determined.

  10. Visualization of CDA laboratory reports and long term trends as a possible EHR application for patients and physicians.

    PubMed

    Obenaus, Manuel; Burgsteiner, Harald

    2014-01-01

    To increase the patient's acceptance of electronic health records and understanding for their laboratory findings a web application was developed which presents all parameters and possible deviations of standard values in a clear way and visualizes the time based trend of all recorded parameters graphically. Documents corresponding to the Clinical document architecture (CDA) R2 laboratory reports standard and a rapid prototyping framework called Groovy on Grails were used. This work shows, that it is possible to create a useful, standards based tool for patients and physicians with comparatively few resources - an application that could be in similar form a part of an electronic Health Record (EHR) system like the Austrian electronic Health Record (ELGA).

  11. 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.

  12. Comparison of spectral estimators for characterizing fractionated atrial electrograms

    PubMed Central

    2013-01-01

    Background Complex fractionated atrial electrograms (CFAE) acquired during atrial fibrillation (AF) are commonly assessed using the discrete Fourier transform (DFT), but this can lead to inaccuracy. In this study, spectral estimators derived by averaging the autocorrelation function at lags were compared to the DFT. Method Bipolar CFAE of at least 16 s duration were obtained from pulmonary vein ostia and left atrial free wall sites (9 paroxysmal and 10 persistent AF patients). Power spectra were computed using the DFT and three other methods: 1. a novel spectral estimator based on signal averaging (NSE), 2. the NSE with harmonic removal (NSH), and 3. the autocorrelation function average at lags (AFA). Three spectral parameters were calculated: 1. the largest fundamental spectral peak, known as the dominant frequency (DF), 2. the DF amplitude (DA), and 3. the mean spectral profile (MP), which quantifies noise floor level. For each spectral estimator and parameter, the significance of the difference between paroxysmal and persistent AF was determined. Results For all estimators, mean DA and mean DF values were higher in persistent AF, while the mean MP value was higher in paroxysmal AF. The differences in means between paroxysmals and persistents were highly significant for 3/3 NSE and NSH measurements and for 2/3 DFT and AFA measurements (p<0.001). For all estimators, the standard deviation in DA and MP values were higher in persistent AF, while the standard deviation in DF value was higher in paroxysmal AF. Differences in standard deviations between paroxysmals and persistents were highly significant in 2/3 NSE and NSH measurements, in 1/3 AFA measurements, and in 0/3 DFT measurements. Conclusions Measurements made from all four spectral estimators were in agreement as to whether the means and standard deviations in three spectral parameters were greater in CFAEs acquired from paroxysmal or in persistent AF patients. Since the measurements were consistent, use of two or more of these estimators for power spectral analysis can be assistive to evaluate CFAE more objectively and accurately, which may lead to improved clinical outcome. Since the most significant differences overall were achieved using the NSE and NSH estimators, parameters measured from their spectra will likely be the most useful for detecting and discerning electrophysiologic differences in the AF substrate based upon frequency analysis of CFAE. PMID:23855345

  13. 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.

  14. Time-dependent gravity in Southern California, May 1974 to April 1979

    NASA Technical Reports Server (NTRS)

    Whitcomb, J. H.; Franzen, W. O.; Given, J. W.; Pechmann, J. C.; Ruff, L. J.

    1980-01-01

    The Southern California gravity survey, begun in May 1974 to obtain high spatial and temporal density gravity measurements to be coordinated with long-baseline three dimensional geodetic measurements of the Astronomical Radio Interferometric Earth Surveying project, is presented. Gravity data was obtained from 28 stations located in and near the seismically active San Gabriel section of the Southern California Transverse Ranges and adjoining San Andreas Fault at intervals of one to two months using gravity meters relative to a base station standard meter. A single-reading standard deviation of 11 microGal is obtained which leads to a relative deviation of 16 microGal between stations, with data averaging reducing the standard error to 2 to 3 microGal. The largest gravity variations observed are found to correlate with nearby well water variations and smoothed rainfall levels, indicating the importance of ground water variations to gravity measurements. The largest earthquake to occur during the survey, which extended to April, 1979, is found to be accompanied in the station closest to the earthquake by the largest measured gravity changes that cannot be related to factors other than tectonic distortion.

  15. Catalytic determination of vanadium in water

    USGS Publications Warehouse

    Fishman, M. J.; Skougstad, M.W.

    1964-01-01

    A rapid, accurate, and sensitive spectrophotometric method for the quantitative determination of trace amounts of vanadium in water is based on the catalytic effect of vanadium on the rate of oxidation of gallic acid by persulfate in acid solution. Under given conditions of concentrations of reactants, temperature, and reaction time, the extent of oxidation of gallic acid is proportional to the concentration of vanadium present. Vanadium is determined by measuring the absorbance of the sample at 415 m?? and comparison with standard solutions treated in an identical manner. Concentrations in the range of from 0.1 to 8.0 ??g. per liter may be determined with a standard deviation of 0.2 or less. By reducing the reaction time, the method may be extended to cover the range from 1 to 100 ??g. with a standard deviation of 0.8 or less. Several substances interfere, including chloride above 100 p.p.m., and bromide and iodide in much lower concentrations. Interference from the halides is eliminated or minimized by the addition of mercuric nitrate solution. Most other substances do not interfere at the concentration levels at which they commonly occur in natural waters.

  16. Strong evidence for ZZ production in pp[over] collisions at sqrt[s]=1.96 TeV.

    PubMed

    Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Behari, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; 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; 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; 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; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; 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 Lentdecker, G; De Lorenzo, G; Dell'Orso, M; Demortier, L; Deng, J; Deninno, M; De Pedis, D; 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; 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; Forrester, S; 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; Giagu, S; Giakoumopolou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; 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; Hamilton, A; 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; Iyutin, B; James, E; Jayatilaka, B; Jeans, D; Jeon, E J; 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; Kerzel, U; 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; Klute, M; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraus, J; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kulkarni, N P; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; 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, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, M; 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; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M; 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; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; 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; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, 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; Salamanna, G; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; 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; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; 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; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; 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; Sun, H; 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; Tourneur, S; Trischuk, W; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; 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; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; 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; Group, R C

    2008-05-23

    We report the first evidence of Z boson pair production at a hadron collider with a significance exceeding 4 standard deviations. This result is based on a data sample corresponding to 1.9 fb(-1) of integrated luminosity from pp[over] collisions at sqrt[s]=1.96 TeV collected with the Collider Detector at Fermilab II detector. In the lll'l' channel, we observe three ZZ candidates with an expected background of 0.096(-0.063)+0.092 events. In the llnunu channel, we use a leading-order calculation of the relative ZZ and WW event probabilities to discriminate between signal and background. In the combination of lll'l' and llnunu channels, we observe an excess of events with a probability of 5.1 x 10(-6) to be due to the expected background. This corresponds to a significance of 4.4 standard deviations. The measured cross section is sigma(pp[over]-->ZZ)=1.4(-0.6)+0.7(stat+syst) pb, consistent with the standard model expectation.

  17. 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

  18. 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.

  19. 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.

  20. An algorithm for synchronizing a clock when the data are received over a network with an unstable delay

    PubMed Central

    Levine, Judah

    2016-01-01

    A method is presented for synchronizing the time of a clock to a remote time standard when the channel connecting the two has significant delay variation that can be described only statistically. The method compares the Allan deviation of the channel fluctuations to the free-running stability of the local clock, and computes the optimum interval between requests based on one of three selectable requirements: (1) choosing the highest possible accuracy, (2) choosing the best tradeoff of cost vs. accuracy, or (3) minimizing the number of requests to realize a specific accuracy. Once the interval between requests is chosen, the final step is to steer the local clock based on the received data. A typical adjustment algorithm, which supports both the statistical considerations based on the Allan deviation comparison and the timely detection of errors is included as an example. PMID:26529759

  1. 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…

  2. 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…

  3. 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…

  4. 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.

  5. 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%.

  6. 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

  7. 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.

  8. 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.

  9. Experimental verification of self-calibration radiometer based on spontaneous parametric downconversion

    NASA Astrophysics Data System (ADS)

    Gao, Dongyang; Zheng, Xiaobing; Li, Jianjun; Hu, Youbo; Xia, Maopeng; Salam, Abdul; Zhang, Peng

    2018-03-01

    Based on spontaneous parametric downconversion process, we propose a novel self-calibration radiometer scheme which can self-calibrate the degradation of its own response and ultimately monitor the fluctuation of a target radiation. Monitor results were independent of its degradation and not linked to the primary standard detector scale. The principle and feasibility of the proposed scheme were verified by observing bromine-tungsten lamp. A relative standard deviation of 0.39 % was obtained for stable bromine-tungsten lamp. Results show that the proposed scheme is advanced of its principle. The proposed scheme could make a significant breakthrough in the self-calibration issue on the space platform.

  10. Analyses of S-Box in Image Encryption Applications Based on Fuzzy Decision Making Criterion

    NASA Astrophysics Data System (ADS)

    Rehman, Inayatur; Shah, Tariq; Hussain, Iqtadar

    2014-06-01

    In this manuscript, we put forward a standard based on fuzzy decision making criterion to examine the current substitution boxes and study their strengths and weaknesses in order to decide their appropriateness in image encryption applications. The proposed standard utilizes the results of correlation analysis, entropy analysis, contrast analysis, homogeneity analysis, energy analysis, and mean of absolute deviation analysis. These analyses are applied to well-known substitution boxes. The outcome of these analyses are additional observed and a fuzzy soft set decision making criterion is used to decide the suitability of an S-box to image encryption applications.

  11. 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

  12. [Growth standardized values and curves based on weight, length/height and head circumference for Chinese children under 7 years of age].

    PubMed

    Li, Hui

    2009-03-01

    To construct the growth standardized data and curves based on weight, length/height, head circumference for Chinese children under 7 years of age. Random cluster sampling was used. The fourth national growth survey of children under 7 years in the nine cities (Beijing, Harbin, Xi'an, Shanghai, Nanjing, Wuhan, Fuzhou, Guangzhou and Kunming) of China was performed in 2005 and from this survey, data of 69 760 urban healthy boys and girls were used to set up the database for weight-for-age, height-for-age (length was measured for children under 3 years) and head circumference-for-age. Anthropometric data were ascribed to rigorous methods of data collection and standardized procedures across study sites. LMS method based on BOX-COX normal transformation and cubic splines smoothing technique was chosen for fitting the raw data according to study design and data features, and standardized values of any percentile and standard deviation were obtained by the special formulation of L, M and S parameters. Length-for-age and height-for-age standards were constructed by fitting the same model but the final curves reflected the 0.7 cm average difference between these two measurements. A set of systematic diagnostic tools was used to detect possible biases in estimated percentiles or standard deviation curves, including chi2 test, which was used for reference to evaluate to the goodness of fit. The 3rd, 10th, 25th, 50th, 75th, 90th, 97th smoothed percentiles and -3, -2, -1, 0, +1, +2, +3 SD values and curves of weight-for-age, length/height-for-age and head circumference-for-age for boys and girls aged 0-7 years were made out respectively. The Chinese child growth charts was slightly higher than the WHO child growth standards. The newly established growth charts represented the growth level of healthy and well-nourished Chinese children. The sample size was very large and national, the data were high-quality and the smoothing method was internationally accepted. The new Chinese growth charts are recommended as the Chinese child growth standards in 21st century used in China.

  13. 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...

  14. Statistical wind analysis for near-space applications

    NASA Astrophysics Data System (ADS)

    Roney, Jason A.

    2007-09-01

    Statistical wind models were developed based on the existing observational wind data for near-space altitudes between 60 000 and 100 000 ft (18 30 km) above ground level (AGL) at two locations, Akon, OH, USA, and White Sands, NM, USA. These two sites are envisioned as playing a crucial role in the first flights of high-altitude airships. The analysis shown in this paper has not been previously applied to this region of the stratosphere for such an application. Standard statistics were compiled for these data such as mean, median, maximum wind speed, and standard deviation, and the data were modeled with Weibull distributions. These statistics indicated, on a yearly average, there is a lull or a “knee” in the wind between 65 000 and 72 000 ft AGL (20 22 km). From the standard statistics, trends at both locations indicated substantial seasonal variation in the mean wind speed at these heights. The yearly and monthly statistical modeling indicated that Weibull distributions were a reasonable model for the data. Forecasts and hindcasts were done by using a Weibull model based on 2004 data and comparing the model with the 2003 and 2005 data. The 2004 distribution was also a reasonable model for these years. Lastly, the Weibull distribution and cumulative function were used to predict the 50%, 95%, and 99% winds, which are directly related to the expected power requirements of a near-space station-keeping airship. These values indicated that using only the standard deviation of the mean may underestimate the operational conditions.

  15. Acoustic Fluctuations: Guidelines for R and D Based on the Acoustic Fluctuation Workshop 22-23 February 1978

    DTIC Science & Technology

    1978-11-28

    Noise was sponsored by CNO (OP-95) and supported by Chief of Naval Research (CNR) and held at Woods Hole Oceano - graphic Institute (WHOI) in October...SURFACE ARRAY 1 Sol ’ ARRAY 2 S~BOTTOM (C) Calculate standard deviation of phase-difference fluctuations as a function of integration time, Calculate

  16. Parametric Study of Urban-Like Topographic Statistical Moments Relevant to a Priori Modelling of Bulk Aerodynamic Parameters

    NASA Astrophysics Data System (ADS)

    Zhu, Xiaowei; Iungo, G. Valerio; Leonardi, Stefano; Anderson, William

    2017-02-01

    For a horizontally homogeneous, neutrally stratified atmospheric boundary layer (ABL), aerodynamic roughness length, z_0, is the effective elevation at which the streamwise component of mean velocity is zero. A priori prediction of z_0 based on topographic attributes remains an open line of inquiry in planetary boundary-layer research. Urban topographies - the topic of this study - exhibit spatial heterogeneities associated with variability of building height, width, and proximity with adjacent buildings; such variability renders a priori, prognostic z_0 models appealing. Here, large-eddy simulation (LES) has been used in an extensive parametric study to characterize the ABL response (and z_0) to a range of synthetic, urban-like topographies wherein statistical moments of the topography have been systematically varied. Using LES results, we determined the hierarchical influence of topographic moments relevant to setting z_0. We demonstrate that standard deviation and skewness are important, while kurtosis is negligible. This finding is reconciled with a model recently proposed by Flack and Schultz (J Fluids Eng 132:041203-1-041203-10, 2010), who demonstrate that z_0 can be modelled with standard deviation and skewness, and two empirical coefficients (one for each moment). We find that the empirical coefficient related to skewness is not constant, but exhibits a dependence on standard deviation over certain ranges. For idealized, quasi-uniform cubic topographies and for complex, fully random urban-like topographies, we demonstrate strong performance of the generalized Flack and Schultz model against contemporary roughness correlations.

  17. The gait standard deviation, a single measure of kinematic variability.

    PubMed

    Sangeux, Morgan; Passmore, Elyse; Graham, H Kerr; Tirosh, Oren

    2016-05-01

    Measurement of gait kinematic variability provides relevant clinical information in certain conditions affecting the neuromotor control of movement. In this article, we present a measure of overall gait kinematic variability, GaitSD, based on combination of waveforms' standard deviation. The waveform standard deviation is the common numerator in established indices of variability such as Kadaba's coefficient of multiple correlation or Winter's waveform coefficient of variation. Gait data were collected on typically developing children aged 6-17 years. Large number of strides was captured for each child, average 45 (SD: 11) for kinematics and 19 (SD: 5) for kinetics. We used a bootstrap procedure to determine the precision of GaitSD as a function of the number of strides processed. We compared the within-subject, stride-to-stride, variability with the, between-subject, variability of the normative pattern. Finally, we investigated the correlation between age and gait kinematic, kinetic and spatio-temporal variability. In typically developing children, the relative precision of GaitSD was 10% as soon as 6 strides were captured. As a comparison, spatio-temporal parameters required 30 strides to reach the same relative precision. The ratio stride-to-stride divided by normative pattern variability was smaller in kinematic variables (the smallest for pelvic tilt, 28%) than in kinetic and spatio-temporal variables (the largest for normalised stride length, 95%). GaitSD had a strong, negative correlation with age. We show that gait consistency may stabilise only at, or after, skeletal maturity. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. 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.

  19. Photometric Selection of a Massive Galaxy Catalog with z ≥ 0.55

    NASA Astrophysics Data System (ADS)

    Núñez, Carolina; Spergel, David N.; Ho, Shirley

    2017-02-01

    We present the development of a photometrically selected massive galaxy catalog, targeting Luminous Red Galaxies (LRGs) and massive blue galaxies at redshifts of z≥slant 0.55. Massive galaxy candidates are selected using infrared/optical color-color cuts, with optical data from the Sloan Digital Sky Survey (SDSS) and infrared data from “unWISE” forced photometry derived from the Wide-field Infrared Survey Explorer (WISE). The selection method is based on previously developed techniques to select LRGs with z> 0.5, and is optimized using receiver operating characteristic curves. The catalog contains 16,191,145 objects, selected over the full SDSS DR10 footprint. The redshift distribution of the resulting catalog is estimated using spectroscopic redshifts from the DEEP2 Galaxy Redshift Survey and photometric redshifts from COSMOS. Restframe U - B colors from DEEP2 are used to estimate LRG selection efficiency. Using DEEP2, the resulting catalog has an average redshift of z = 0.65, with a standard deviation of σ =2.0, and an average restframe of U-B=1.0, with a standard deviation of σ =0.27. Using COSMOS, the resulting catalog has an average redshift of z = 0.60, with a standard deviation of σ =1.8. We estimate 34 % of the catalog to be blue galaxies with z≥slant 0.55. An estimated 9.6 % of selected objects are blue sources with redshift z< 0.55. Stellar contamination is estimated to be 1.8%.

  20. Postoperative alar base symmetry in complete unilateral cleft lip and palate:A prospective study.

    PubMed

    Vyloppilli, Suresh; Krishnakumar, K S; Sayd, Shermil; Latheef, Sameer; Narayanan, Saju V; Pati, Ajit

    2017-11-01

    In the evolution of cleft lip repair, there have been continuous attempts to minimize local trauma and to improve lip and nasal appearances. In order to obtain an aesthetically balanced development of midface, the primary surgical correction of the nasolabial area is of paramount importance. In this study, the importance of a back-cut extending cephalically above the inferior turbinate at the mucocutaneous junction which elevates the nostril floor on the cleft side for the purpose of achieving symmetry of the alar bases are analyzed by pre and postoperative photographic anthropometry. This study comprised of fifty cases of the unilateral complete cleft lip. At the time of surgery, the patient age ranged from 3-9 months. The surgeries, performed by a single surgeon, employed the standard Millard technique, incorporating Mohler modifications of lip repair. Anthropometric analysis revealed that the preoperative mean difference between the normal side and the cleft side was 0.2056 with a standard deviation of 0.133. In the postoperative analysis, the mean difference was reduced to 0.0174 with a standard deviation of 0.141. The paired t-test showed that the p-value is <0.001, indicating high statistical significance. To conclude, in complete unilateral cleft lip and palate, the geometrically placed nasal back-cut incision has a definite role in the correction of the alar base symmetry during primary surgery. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  1. 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

  2. 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

  3. 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. 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.; Barnea, R.; 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.; Bauer, K. T.; 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.; Behera, A.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; 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.; Bergsten, L. J.; 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.; 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, Dr.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; 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.; Bonilla, J. S.; 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.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; 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.; Buschmann, E.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabras, G.; Cabrera Urbán, S.; Caforio, D.; Cai, H.; Cairo, V. M. 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.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, C.; Chen, H.; Chen, J.; 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.; Cinca, D.; Cindro, V.; Cioarǎ, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Clark, A.; 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.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corrigan, E. E.; Corriveau, F.; Cortes-Gonzalez, A.; 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.; 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. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; 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 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.; Dickinson, J.; 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.; 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. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kiehn, M.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; Kirchmeier, D.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kitali, V.; Kivernyk, O.; Kladiva, E.; Klapdor-Kleingrothaus, T.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klingl, T.; Klioutchnikova, T.; Klitzner, F. F.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolb, M.; Koletsou, I.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Konya, B.; Kopeliansky, R.; Koperny, S.; Korcyl, K.; Kordas, K.; Korn, A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kourlitis, E.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Krauss, D.; Kremer, J. A.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kubota, T.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kulinich, Y. P.; Kuna, M.; Kunigo, T.; Kupco, A.; Kupfer, T.; Kuprash, O.; Kurashige, H.; Kurchaninov, L. L.; Kurochkin, Y. A.; Kurth, M. G.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; La Rosa, A.; La Rosa Navarro, J. L.; La Rotonda, L.; La Ruffa, F.; Lacasta, C.; Lacava, F.; Lacey, J.; Lack, D. P. J.; Lacker, H.; Lacour, D.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Langenberg, R. J.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Lapertosa, A.; Laplace, S.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Lau, T. S.; Laudrain, A.; Law, A. T.; Laycock, P.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; Leblanc, M.; Lecompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, G. R.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehmann Miotto, G.; Leight, W. A.; Leisos, A.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Lerner, G.; Leroy, C.; Les, R.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Li, B.; Li, C.-Q.; Li, H.; Li, L.; Li, Q.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lie, K.; Limosani, A.; Lin, C. Y.; Lin, K.; Lin, S. C.; Lin, T. H.; Linck, R. A.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, H.; Liu, H.; Liu, J. K. K.; Liu, J. B.; Liu, K.; Liu, M.; Liu, P.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo, C. Y.; Lo Sterzo, F.; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loesle, A.; Loew, K. M.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopez, J. A.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lu, Y. J.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lund-Jensen, B.; Lutz, M. S.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyu, F.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; MacDonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Mader, W. F.; Madsen, A.; Madysa, N.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A. S.; Magerl, V.; Maidantchik, C.; Maier, T.; Maio, A.; Majersky, O.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mankinen, K. H.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Marceca, G.; March, L.; Marchese, L.; Marchiori, G.; Marcisovsky, M.; Marin Tobon, C. A.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marshall, Z.; Martensson, M. U. F.; Marti-Garcia, S.; Martin, C. B.; Martin, T. A.; Martin, V. J.; Martin Dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Mason, L. H.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; McFayden, J. A.; McHedlidze, G.; McKay, M. A.; McMahon, S. J.; McNamara, P. C.; McNicol, C. J.; McPherson, R. A.; Meadows, Z. A.; Meehan, S.; Megy, T. J.; Mehlhase, S.; Mehta, A.; Meideck, T.; Meier, K.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Mellenthin, J. D.; Melo, M.; Meloni, F.; Melzer, A.; Menary, S. B.; Meng, L.; Meng, X. T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Merlassino, C.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Millar, D. A.; Miller, D. W.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mirto, A.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mkrtchyan, T.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, M.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moschovakos, P.; Mosidze, M.; Moss, H. J.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murin, P.; Murray, W. J.; Murrone, A.; Muškinja, M.; Mwewa, C.; Myagkov, A. G.; Myers, J.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, M. E.; Nemecek, S.; Nemethy, P.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Newman, P. R.; Ng, T. Y.; Ng, Y. S.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforou, N.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishu, N.; Nisius, R.; Nitsche, I.; Nitta, T.; Nobe, T.; Noguchi, Y.; Nomachi, M.; Nomidis, I.; Nomura, M. A.; Nooney, T.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Novotny, R.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'Connor, K.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Ojeda, M. L.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Oliver, J. L.; Olsson, M. J. R.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oppen, H.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orgill, E. C.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero Y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagan Griso, S.; Paganini, M.; Paige, F.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Panagiotopoulou, E. St.; Panagoulias, I.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parida, B.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasner, J. M.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearson, B.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Peri, F.; Perini, L.; Pernegger, H.; Perrella, S.; 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.; Pham, T.; Phillips, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pinamonti, M.; Pinfold, J. L.; Pitt, M.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pogrebnyak, I.; Pohl, D.; Pokharel, I.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Portillo Quintero, D. M.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potti, H.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Prell, S.; Price, D.; Primavera, M.; Prince, S.; Proklova, N.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puri, A.; Puzo, P.; Qian, J.; Qin, Y.; Quadt, A.; Queitsch-Maitland, M.; Qureshi, A.; Radeka, V.; Radhakrishnan, S. K.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rashid, T.; Raspopov, S.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravinovich, I.; Rawling, J. H.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; Rettie, S.; Reynolds, E.; Rezanova, O. L.; Reznicek, P.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; Rivera Vergara, J. C.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Roberts, R. T.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Rocco, E.; Roda, C.; Rodina, Y.; Rodriguez Bosca, S.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Rodríguez Vera, A. M.; Roe, S.; Rogan, C. S.; Røhne, O.; Röhrig, R.; Roloff, J.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossi, E.; Rossi, L. P.; Rossini, L.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Rothberg, J.; Rousseau, D.; Roy, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Rüttinger, E. M.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Salamanna, G.; Salazar Loyola, J. E.; Salek, D.; Sales de Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; Sanchez Pineda, A.; Sandaker, H.; Sander, C. O.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sano, Y.; Sansoni, A.; Santoni, C.; Santos, H.; Santoyo Castillo, I.; Sapronov, A.; Saraiva, J. G.; Sasaki, O.; Sato, K.; Sauvan, E.; Savard, P.; Savic, N.; Sawada, R.; Sawyer, C.; Sawyer, L.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaeffer, J.; Schaepe, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schenck, F.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillaci, Z. M.; Schillo, C.; Schioppa, E. J.; Schioppa, M.; Schleicher, K. E.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultz-Coulon, H.-C.; 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.; Scyboz, L. M.; 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.; Severini, H.; Šfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shahinian, J. D.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Sharma, A. S.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. 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.

  4. 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.

  5. 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

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. A population-based job exposure matrix for power-frequency magnetic fields.

    PubMed

    Bowman, Joseph D; Touchstone, Jennifer A; Yost, Michael G

    2007-09-01

    A population-based job exposure matrix (JEM) was developed to assess personal exposures to power-frequency magnetic fields (MF) for epidemiologic studies. The JEM compiled 2,317 MF measurements taken on or near workers by 10 studies in the United States, Sweden, New Zealand, Finland, and Italy. A database was assembled from the original data for six studies plus summary statistics grouped by occupation from four other published studies. The job descriptions were coded into the 1980 Standard Occupational Classification system (SOC) and then translated to the 1980 job categories of the U.S. Bureau of the Census (BOC). For each job category, the JEM database calculated the arithmetic mean, standard deviation, geometric mean, and geometric standard deviation of the workday-average MF magnitude from the combined data. Analysis of variance demonstrated that the combining of MF data from the different sources was justified, and that the homogeneity of MF exposures in the SOC occupations was comparable to JEMs for solvents and particulates. BOC occupation accounted for 30% of the MF variance (p < 10(-6)), and the contrast (ratio of the between-job variance to the total of within- and between-job variances) was 88%. Jobs lacking data had their exposures inferred from measurements on similar occupations. The JEM provided MF exposures for 97% of the person-months in a population-based case-control study and 95% of the jobs on death certificates in a registry study covering 22 states. Therefore, we expect this JEM to be useful in other population-based epidemiologic studies.

  12. Improving operating room turnover time: a systems based approach.

    PubMed

    Bhatt, Ankeet S; Carlson, Grant W; Deckers, Peter J

    2014-12-01

    Operating room (OR) turnover time (TT) has a broad and significant impact on hospital administrators, providers, staff and patients. Our objective was to identify current problems in TT management and implement a consistent, reproducible process to reduce average TT and process variability. Initial observations of TT were made to document the existing process at a 511 bed, 24 OR, academic medical center. Three control groups, including one consisting of Orthopedic and Vascular Surgery, were used to limit potential confounders such as case acuity/duration and equipment needs. A redesigned process based on observed issues, focusing on a horizontally structured, systems-based approach has three major interventions: developing consistent criteria for OR readiness, utilizing parallel processing for patient and room readiness, and enhancing perioperative communication. Process redesign was implemented in Orthopedics and Vascular Surgery. Comparisons of mean and standard deviation of TT were made using an independent 2-tailed t-test. Using all surgical specialties as controls (n = 237), mean TT (hh:mm:ss) was reduced by 0:20:48 min (95 % CI, 0:10:46-0:30:50), from 0:44:23 to 0:23:25, a 46.9 % reduction. Standard deviation of TT was reduced by 0:10:32 min, from 0:16:24 to 0:05:52 and frequency of TT≥30 min was reduced from 72.5to 11.7 %. P < 0.001 for each. Using Vascular and Orthopedic surgical specialties as controls (n = 13), mean TT was reduced by 0:15:16 min (95 % CI, 0:07:18-0:23:14), from 0:38:51 to 0:23:35, a 39.4 % reduction. Standard deviation of TT reduced by 0:08:47, from 0:14:39 to 0:05:52 and frequency of TT≥30 min reduced from 69.2 to 11.7 %. P < 0.001 for each. Reductions in mean TT present major efficiency, quality improvement, and cost-reduction opportunities. An OR redesign process focusing on parallel processing and enhanced communication resulted in greater than 35 % reduction in TT. A systems-based focus should drive OR TT design.

  13. [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.

  14. 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).

  15. 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.

  16. 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.

  17. 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%.

  18. 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.

  19. [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.

  20. A Method of Accurate Bone Tunnel Placement for Anterior Cruciate Ligament Reconstruction Based on 3-Dimensional Printing Technology: A Cadaveric Study.

    PubMed

    Ni, Jianlong; Li, Dichen; Mao, Mao; Dang, Xiaoqian; Wang, Kunzheng; He, Jiankang; Shi, Zhibin

    2018-02-01

    To explore a method of bone tunnel placement for anterior cruciate ligament (ACL) reconstruction based on 3-dimensional (3D) printing technology and to assess its accuracy. Twenty human cadaveric knees were scanned by thin-layer computed tomography (CT). To obtain data on bones used to establish a knee joint model by computer software, customized bone anchors were installed before CT. The reference point was determined at the femoral and tibial footprint areas of the ACL. The site and direction of the bone tunnels of the femur and tibia were designed and calibrated on the knee joint model according to the reference point. The resin template was designed and printed by 3D printing. Placement of the bone tunnels was accomplished by use of templates, and the cadaveric knees were scanned again to compare the concordance of the internal opening of the bone tunnels and reference points. The twenty 3D printing templates were designed and printed successfully. CT data analysis between the planned and actual drilled tunnel positions showed mean deviations of 0.57 mm (range, 0-1.5 mm; standard deviation, 0.42 mm) at the femur and 0.58 mm (range, 0-1.5 mm; standard deviation, 0.47 mm) at the tibia. The accuracy of bone tunnel placement for ACL reconstruction in cadaveric adult knees based on 3D printing technology is high. This method can improve the accuracy of bone tunnel placement for ACL reconstruction in clinical sports medicine. Copyright © 2017 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

  1. Point-based and model-based geolocation analysis of airborne laser scanning data

    NASA Astrophysics Data System (ADS)

    Sefercik, Umut Gunes; Buyuksalih, Gurcan; Jacobsen, Karsten; Alkan, Mehmet

    2017-01-01

    Airborne laser scanning (ALS) is one of the most effective remote sensing technologies providing precise three-dimensional (3-D) dense point clouds. A large-size ALS digital surface model (DSM) covering the whole Istanbul province was analyzed by point-based and model-based comprehensive statistical approaches. Point-based analysis was performed using checkpoints on flat areas. Model-based approaches were implemented in two steps as strip to strip comparing overlapping ALS DSMs individually in three subareas and comparing the merged ALS DSMs with terrestrial laser scanning (TLS) DSMs in four other subareas. In the model-based approach, the standard deviation of height and normalized median absolute deviation were used as the accuracy indicators combined with the dependency of terrain inclination. The results demonstrate that terrain roughness has a strong impact on the vertical accuracy of ALS DSMs. From the relative horizontal shifts determined and partially improved by merging the overlapping strips and comparison of the ALS, and the TLS, data were found not to be negligible. The analysis of ALS DSM in relation to TLS DSM allowed us to determine the characteristics of the DSM in detail.

  2. 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

  3. SU-F-J-177: A Novel Image Analysis Technique (center Pixel Method) to Quantify End-To-End Tests

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

    Wen, N; Chetty, I; Snyder, K

    Purpose: To implement a novel image analysis technique, “center pixel method”, to quantify end-to-end tests accuracy of a frameless, image guided stereotactic radiosurgery system. Methods: The localization accuracy was determined by delivering radiation to an end-to-end prototype phantom. The phantom was scanned with 0.8 mm slice thickness. The treatment isocenter was placed at the center of the phantom. In the treatment room, CBCT images of the phantom (kVp=77, mAs=1022, slice thickness 1 mm) were acquired to register to the reference CT images. 6D couch correction were applied based on the registration results. Electronic Portal Imaging Device (EPID)-based Winston Lutz (WL)more » tests were performed to quantify the errors of the targeting accuracy of the system at 15 combinations of gantry, collimator and couch positions. The images were analyzed using two different methods. a) The classic method. The deviation was calculated by measuring the radial distance between the center of the central BB and the full width at half maximum of the radiation field. b) The center pixel method. Since the imager projection offset from the treatment isocenter was known from the IsoCal calibration, the deviation was determined between the center of the BB and the central pixel of the imager panel. Results: Using the automatic registration method to localize the phantom and the classic method of measuring the deviation of the BB center, the mean and standard deviation of the radial distance was 0.44 ± 0.25, 0.47 ± 0.26, and 0.43 ± 0.13 mm for the jaw, MLC and cone defined field sizes respectively. When the center pixel method was used, the mean and standard deviation was 0.32 ± 0.18, 0.32 ± 0.17, and 0.32 ± 0.19 mm respectively. Conclusion: Our results demonstrated that the center pixel method accurately analyzes the WL images to evaluate the targeting accuracy of the radiosurgery system. The work was supported by a Research Scholar Grant, RSG-15-137-01-CCE from the American Cancer Society.« less

  4. Automated object-based classification of topography from SRTM data

    PubMed Central

    Drăguţ, Lucian; Eisank, Clemens

    2012-01-01

    We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble reasonably patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity. Most objects have boundaries matching natural discontinuities at regional level. The method is simple and fully automated. The input data consist of only one layer, which does not need any pre-processing. Both segmentation and classification rely on only two parameters: elevation and standard deviation of elevation. The methodology is implemented as a customized process for the eCognition® software, available as online download. The results are embedded in a web application with functionalities of visualization and download. PMID:22485060

  5. Evaluation of an attenuation correction method for PET/MR imaging of the head based on substitute CT images.

    PubMed

    Larsson, Anne; Johansson, Adam; Axelsson, Jan; Nyholm, Tufve; Asklund, Thomas; Riklund, Katrine; Karlsson, Mikael

    2013-02-01

    The aim of this study was to evaluate MR-based attenuation correction of PET emission data of the head, based on a previously described technique that calculates substitute CT (sCT) images from a set of MR images. Images from eight patients, examined with (18)F-FLT PET/CT and MRI, were included. sCT images were calculated and co-registered to the corresponding CT images, and transferred to the PET/CT scanner for reconstruction. The new reconstructions were then compared with the originals. The effect of replacing bone with soft tissue in the sCT-images was also evaluated. The average relative difference between the sCT-corrected PET images and the CT-corrected PET images was 1.6% for the head and 1.9% for the brain. The average standard deviations of the relative differences within the head were relatively high, at 13.2%, primarily because of large differences in the nasal septa region. For the brain, the average standard deviation was lower, 4.1%. The global average difference in the head when replacing bone with soft tissue was 11%. The method presented here has a high rate of accuracy, but high-precision quantitative imaging of the nasal septa region is not possible at the moment.

  6. Community covariates of malnutrition based mortality among older adults.

    PubMed

    Lee, Matthew R; Berthelot, Emily R

    2010-05-01

    The purpose of this study was to identify community level covariates of malnutrition-based mortality among older adults. A community level framework was delineated which explains rates of malnutrition-related mortality among older adults as a function of community levels of socioeconomic disadvantage, disability, and social isolation among members of this group. County level data on malnutrition mortality of people 65 years of age and older for the period 2000-2003 were drawn from the CDC WONDER system databases. County level measures of older adult socioeconomic disadvantage, disability, and social isolation were derived from the 2000 US Census of Population and Housing. Negative binomial regression models adjusting for the size of the population at risk, racial composition, urbanism, and region were estimated to assess the relationships among these indicators. Results from negative binomial regression analysis yielded the following: a standard deviation increase in socioeconomic/physical disadvantage was associated with a 12% increase in the rate of malnutrition mortality among older adults (p < 0.001), whereas a standard deviation increase in social isolation was associated with a 5% increase in malnutrition mortality among older adults (p < 0.05). Community patterns of malnutrition based mortality among older adults are partly a function of levels of socioeconomic and physical disadvantage and social isolation among older adults. 2010 Elsevier Inc. All rights reserved.

  7. Enhanced Cumulative Sum Charts for Monitoring Process Dispersion

    PubMed Central

    Abujiya, Mu’azu Ramat; Riaz, Muhammad; Lee, Muhammad Hisyam

    2015-01-01

    The cumulative sum (CUSUM) control chart is widely used in industry for the detection of small and moderate shifts in process location and dispersion. For efficient monitoring of process variability, we present several CUSUM control charts for monitoring changes in standard deviation of a normal process. The newly developed control charts based on well-structured sampling techniques - extreme ranked set sampling, extreme double ranked set sampling and double extreme ranked set sampling, have significantly enhanced CUSUM chart ability to detect a wide range of shifts in process variability. The relative performances of the proposed CUSUM scale charts are evaluated in terms of the average run length (ARL) and standard deviation of run length, for point shift in variability. Moreover, for overall performance, we implore the use of the average ratio ARL and average extra quadratic loss. A comparison of the proposed CUSUM control charts with the classical CUSUM R chart, the classical CUSUM S chart, the fast initial response (FIR) CUSUM R chart, the FIR CUSUM S chart, the ranked set sampling (RSS) based CUSUM R chart and the RSS based CUSUM S chart, among others, are presented. An illustrative example using real dataset is given to demonstrate the practicability of the application of the proposed schemes. PMID:25901356

  8. Water Level Monitoring on Tibetan Lakes Based on Icesat and Envisat Data Series

    NASA Astrophysics Data System (ADS)

    Li, H. W.; Qiao, G.; Wu, Y. J.; Cao, Y. J.; Mi, H.

    2017-09-01

    Satellite altimetry technique is an effective method to monitor the water level of lakes in a wide range, especially in sparsely populated areas, such as the Tibet Plateau (TP). To provide high quality data for time-series change detection of lake water level, an automatic and efficient algorithm for lake water footprint (LWF) detection in a wide range is used. Based on ICESat GLA14 Release634 data and ENVISat GDR 1Hz data, water level of 167 lakes were obtained from ICESat data series, and water level of 120 lakes were obtained from ENVISat data series. Among them, 67 lakes contained two data series. Mean standard deviation of all lakes is 0.088 meters (ICESat), 0.339 meters (ENVISat). Combination of multi-source altimetry data is helpful for us to get longer and more dense periods cover water level, study the lake level changes, manage water resources and understand the impacts of climate change better. In addition, the standard deviation of LWF elevation used to calculate the water level were analyzed by month. Based on lake data set for the TP from the 1960s, 2005, and 2014 in Scientific Data, it is found that the water level changes in the TP have a strong spatial correlation with the area changes.

  9. Automated object-based classification of topography from SRTM data

    NASA Astrophysics Data System (ADS)

    Drăguţ, Lucian; Eisank, Clemens

    2012-03-01

    We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble reasonably patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity. Most objects have boundaries matching natural discontinuities at regional level. The method is simple and fully automated. The input data consist of only one layer, which does not need any pre-processing. Both segmentation and classification rely on only two parameters: elevation and standard deviation of elevation. The methodology is implemented as a customized process for the eCognition® software, available as online download. The results are embedded in a web application with functionalities of visualization and download.

  10. 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.

  11. 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.

  12. 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

  13. [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.

  14. 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

  15. 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

  16. Evaluation of Remote Sensing and Hydrological Model Based Soil Moisture Datasets in Drought Perspective

    NASA Astrophysics Data System (ADS)

    Hüsami Afşar, M.; Bulut, B.; Yilmaz, M. T.

    2017-12-01

    Soil moisture is one of the fundamental parameters of the environment that plays a major role in carbon, energy, and water cycles. Spatial distribution and temporal changes of soil moisture is one of the important components in climatic, ecological and natural hazards at global, regional and local levels scales. Therefore retrieval of soil moisture datasets has a great importance in these studies. Given soil moisture can be retrieved through different platforms (i.e., in-situ measurements, numerical modeling, and remote sensing) for the same location and time period, it is often desirable to evaluate these different datasets to assign the most accurate estimates for different purposes. During last decades, efforts have been given to provide evaluations about different soil moisture products based on various statistical analysis of the soil moisture time series (i.e., comparison of correlation, bias, and their error standard deviation). On the other hand, there is still need for the comparisons of the soil moisture products in drought analysis context. In this study, LPRM and NOAH Land Surface Model soil moisture datasets are investigated in drought analysis context using station-based watershed average datasets obtained over four USDA ARS watersheds as ground truth. Here, the drought analysis are performed using the standardized soil moisture datasets (i.e., zero mean and one standard deviation) while the droughts are defined as consecutive negative anomalies less than -1 for longer than 3 months duration. Accordingly, the drought characteristics (duration and severity) and false alarm and hit/miss ratios of LPRM and NOAH datasets are validated using station-based datasets as ground truth. Results showed that although the NOAH soil moisture products have better correlations, LPRM based soil moisture retrievals show better consistency in drought analysis. This project is supported by TUBITAK Project number 114Y676.

  17. Randolph AFB, San Antonio, Texas. Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F.

    DTIC Science & Technology

    1982-02-08

    is printed in any year-month block when the extreme value Is based on an in- complete month (at least one day missing for the month). When a month has...means, standard deviations, and total number of valid observations for each month and annual (all months). An asterisk (*) is printed n each data block...becomes the extreme or monthly total in any of these tables it is printed as "TRACE." Continued on Reverse Side Values ’or means and standard

  18. Excellent reliability of the Hamilton Depression Rating Scale (HDRS-21) in Indonesia after training.

    PubMed

    Istriana, Erita; Kurnia, Ade; Weijers, Annelies; Hidayat, Teddy; Pinxten, Lucas; de Jong, Cor; Schellekens, Arnt

    2013-09-01

    The Hamilton Depression Rating Scale (HDRS) is the most widely used depression rating scale worldwide. Reliability of HDRS has been reported mainly from Western countries. The current study tested the reliability of HDRS ratings among psychiatric residents in Indonesia, before and after HDRS training. The hypotheses were that: (i) prior to the training reliability of HDRS ratings is poor; and (ii) HDRS training can improve reliability of HDRS ratings to excellent levels. Furthermore, we explored cultural validity at item level. Videotaped HDRS interviews were rated by 30 psychiatric residents before and after 1 day of HDRS training. Based on a gold standard rating, percentage correct ratings and deviation from the standard were calculated. Correct ratings increased from 83% to 99% at item level and from 70% to 100% for the total rating. The average deviation from the gold standard rating improved from 0.07 to 0.02 at item level and from 2.97 to 0.46 for the total rating. HDRS assessment by psychiatric trainees in Indonesia without prior training is unreliable. A short, evidence-based HDRS training improves reliability to near perfect levels. The outlined training program could serve as a template for HDRS trainings. HDRS items that may be less valid for assessment of depression severity in Indonesia are discussed. Copyright © 2013 Wiley Publishing Asia Pty Ltd.

  19. A Collaborative Evaluation of LC-MS/MS Based Methods for BMAA Analysis: Soluble Bound BMAA Found to Be an Important Fraction.

    PubMed

    Faassen, Elisabeth J; Antoniou, Maria G; Beekman-Lukassen, Wendy; Blahova, Lucie; Chernova, Ekaterina; Christophoridis, Christophoros; Combes, Audrey; Edwards, Christine; Fastner, Jutta; Harmsen, Joop; Hiskia, Anastasia; Ilag, Leopold L; Kaloudis, Triantafyllos; Lopicic, Srdjan; Lürling, Miquel; Mazur-Marzec, Hanna; Meriluoto, Jussi; Porojan, Cristina; Viner-Mozzini, Yehudit; Zguna, Nadezda

    2016-02-29

    Exposure to β-N-methylamino-l-alanine (BMAA) might be linked to the incidence of amyotrophic lateral sclerosis, Alzheimer's disease and Parkinson's disease. Analytical chemistry plays a crucial role in determining human BMAA exposure and the associated health risk, but the performance of various analytical methods currently employed is rarely compared. A CYANOCOST initiated workshop was organized aimed at training scientists in BMAA analysis, creating mutual understanding and paving the way towards interlaboratory comparison exercises. During this workshop, we tested different methods (extraction followed by derivatization and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis, or directly followed by LC-MS/MS analysis) for trueness and intermediate precision. We adapted three workup methods for the underivatized analysis of animal, brain and cyanobacterial samples. Based on recovery of the internal standard D₃BMAA, the underivatized methods were accurate (mean recovery 80%) and precise (mean relative standard deviation 10%), except for the cyanobacterium Leptolyngbya. However, total BMAA concentrations in the positive controls (cycad seeds) showed higher variation (relative standard deviation 21%-32%), implying that D₃BMAA was not a good indicator for the release of BMAA from bound forms. Significant losses occurred during workup for the derivatized method, resulting in low recovery (<10%). Most BMAA was found in a trichloroacetic acid soluble, bound form and we recommend including this fraction during analysis.

  20. Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation

    NASA Technical Reports Server (NTRS)

    Mandrake, Lukas

    2013-01-01

    Retrieval algorithms like that used by the Orbiting Carbon Observatory (OCO)-2 mission generate massive quantities of data of varying quality and reliability. A computationally efficient, simple method of labeling problematic datapoints or predicting soundings that will fail is required for basic operation, given that only 6% of the retrieved data may be operationally processed. This method automatically obtains a filter designed to reduce scatter based on a small number of input features. Most machine-learning filter construction algorithms attempt to predict error in the CO2 value. By using a surrogate goal of Mean Monthly STDEV, the goal is to reduce the retrieved CO2 scatter rather than solving the harder problem of reducing CO2 error. This lends itself to improved interpretability and performance. This software reduces the scatter of retrieved CO2 values globally based on a minimum number of input features. It can be used as a prefilter to reduce the number of soundings requested, or as a post-filter to label data quality. The use of the MMS (Mean Monthly Standard deviation) provides a much cleaner, clearer filter than the standard ABS(CO2-truth) metrics previously employed by competitor methods. The software's main strength lies in a clearer (i.e., fewer features required) filter that more efficiently reduces scatter in retrieved CO2 rather than focusing on the more complex (and easily removed) bias issues.

  1. Observation of the Higgs boson decay to a pair of τ leptons with the CMS detector

    NASA Astrophysics Data System (ADS)

    Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rabady, D.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; 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.; Correa Martins Junior, M.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Coelho, E.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Shopova, M.; Stoykova, S.; Sultanov, G.; 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.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhang, S.; 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.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; 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.; Assran, Y.; Elgammal, S.; Mahrous, A.; Dewanjee, R. K.; 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.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; 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.; Jansová, M.; Le Bihan, A.-C.; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; 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.; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Zhukov, V.; Albert, A.; 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.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; 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.; Bermúdez Martínez, A.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; 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.; Guthoff, M.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; 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.; Raspereza, A.; Roland, B.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Bein, S.; Blobel, V.; Centis Vignali, M.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Hoffmann, M.; Karavdina, 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.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Freund, B.; Friese, R.; Giffels, M.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; 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.; Karathanasis, G.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Kousouris, K.; Evangelou, I.; Foudas, C.; Kokkas, P.; Mallios, S.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Csanad, M.; Filipovic, N.; Pasztor, G.; Veres, G. I.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; 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.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Bhawandeep, U.; 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.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhattacharya, S.; Chatterjee, S.; Das, P.; 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.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Lezki, S.; 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.; 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.; Chatterjee, K.; 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.; Robutti, E.; Tosi, S.; Benaglia, A.; 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.; Pauwels, K.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Khan, W. A.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Bragagnolo, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Lacaprara, S.; Lujan, P.; Margoni, M.; Meneguzzo, A. T.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Ventura, S.; Zanetti, M.; Zotto, P.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Biasini, M.; Bilei, G. M.; Cecchi, C.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Manoni, E.; Mantovani, G.; Mariani, V.; Menichelli, M.; Rossi, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giannini, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Manca, E.; Mandorli, G.; 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.; Daci, N.; Del Re, D.; Di Marco, E.; 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.; Moon, C. S.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; 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.; Choi, M.; 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.; 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. V.; Seixas, J.; Strong, G.; 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.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; 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.; Stepennov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Bylinkin, A.; Chadeeva, M.; Parygin, P.; Philippov, D.; Polikarpov, S.; Popova, E.; Rusinov, V.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Blinov, V.; Skovpen, Y.; Shtol, D.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; 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.; Cerrada, 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.; 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.

  2. Birth weight standardized to gestational age and intelligence in young adulthood: a register-based birth cohort study of male siblings.

    PubMed

    Eriksen, Willy; Sundet, Jon M; Tambs, Kristian

    2010-09-01

    The authors aimed to determine the relation between birth-weight variations within the normal range and intelligence in young adulthood. A historical birth cohort study was conducted. Data from the Medical Birth Register of Norway were linked with register data from the Norwegian National Conscript Service. The sample comprised 52,408 sibships of full brothers who were born singletons at 37-41 completed weeks' gestation during 1967-1984 in Norway and were intelligence-tested at the time of mandatory military conscription. Generalized estimating equations were used to fit population-averaged panel data models. The analyses showed that in men with birth weights within the 10th-90th percentile range, a within-family difference of 1 standard deviation in birth weight standardized to gestational age was associated with a within-family difference of 0.07 standard deviation (99% confidence interval: 0.03, 0.09) in intelligence score, after adjustment for a range of background factors. There was no significant between-family association after adjustment for background factors. In Norwegian males, normal variations in intrauterine growth are associated with differences in intelligence in young adulthood. This association is probably not due to confounding by familial and parental characteristics.

  3. 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

  4. Fast high-throughput method for the determination of acidity constants by capillary electrophoresis: I. Monoprotic weak acids and bases.

    PubMed

    Fuguet, Elisabet; Ràfols, Clara; Bosch, Elisabeth; Rosés, Martí

    2009-04-24

    A new and fast method to determine acidity constants of monoprotic weak acids and bases by capillary zone electrophoresis based on the use of an internal standard (compound of similar nature and acidity constant as the analyte) has been developed. This method requires only two electrophoretic runs for the determination of an acidity constant: a first one at a pH where both analyte and internal standard are totally ionized, and a second one at another pH where both are partially ionized. Furthermore, the method is not pH dependent, so an accurate measure of the pH of the buffer solutions is not needed. The acidity constants of several phenols and amines have been measured using internal standards of known pK(a), obtaining a mean deviation of 0.05 pH units compared to the literature values.

  5. 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.

  6. Couch height–based patient setup for abdominal radiation therapy

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

    Ohira, Shingo; Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Suita; Ueda, Yoshihiro

    2016-04-01

    There are 2 methods commonly used for patient positioning in the anterior-posterior (A-P) direction: one is the skin mark patient setup method (SMPS) and the other is the couch height–based patient setup method (CHPS). This study compared the setup accuracy of these 2 methods for abdominal radiation therapy. The enrollment for this study comprised 23 patients with pancreatic cancer. For treatments (539 sessions), patients were set up by using isocenter skin marks and thereafter treatment couch was shifted so that the distance between the isocenter and the upper side of the treatment couch was equal to that indicated on themore » computed tomographic (CT) image. Setup deviation in the A-P direction for CHPS was measured by matching the spine of the digitally reconstructed radiograph (DRR) of a lateral beam at simulation with that of the corresponding time-integrated electronic portal image. For SMPS with no correction (SMPS/NC), setup deviation was calculated based on the couch-level difference between SMPS and CHPS. SMPS/NC was corrected using 2 off-line correction protocols: no action level (SMPS/NAL) and extended NAL (SMPS/eNAL) protocols. Margins to compensate for deviations were calculated using the Stroom formula. A-P deviation > 5 mm was observed in 17% of SMPS/NC, 4% of SMPS/NAL, and 4% of SMPS/eNAL sessions but only in one CHPS session. For SMPS/NC, 7 patients (30%) showed deviations at an increasing rate of > 0.1 mm/fraction, but for CHPS, no such trend was observed. The standard deviations (SDs) of systematic error (Σ) were 2.6, 1.4, 0.6, and 0.8 mm and the root mean squares of random error (σ) were 2.1, 2.6, 2.7, and 0.9 mm for SMPS/NC, SMPS/NAL, SMPS/eNAL, and CHPS, respectively. Margins to compensate for the deviations were wide for SMPS/NC (6.7 mm), smaller for SMPS/NAL (4.6 mm) and SMPS/eNAL (3.1 mm), and smallest for CHPS (2.2 mm). Achieving better setup with smaller margins, CHPS appears to be a reproducible method for abdominal patient setup.« less

  7. An Application of Extreme Value Theory to Learning Analytics: Predicting Collaboration Outcome from Eye-Tracking Data

    ERIC Educational Resources Information Center

    Sharma, Kshitij; Chavez-Demoulin, Valérie; Dillenbourg, Pierre

    2017-01-01

    The statistics used in education research are based on central trends such as the mean or standard deviation, discarding outliers. This paper adopts another viewpoint that has emerged in statistics, called extreme value theory (EVT). EVT claims that the bulk of normal distribution is comprised mainly of uninteresting variations while the most…

  8. Optimal Asset Distribution for Environmental Assessment and Forecasting Based on Observations, Adaptive Sampling, and Numerical Prediction

    DTIC Science & Technology

    2013-03-18

    Soliton Ocean Services Inc. to Steve Ramp to complete the work on the grant. Computations in support of Steve Ramp’s work were carried out by Fred...dominant term, even when averaged over the dark hours, which accounts for the large standard deviation. The net long-wave radiation was small and

  9. 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.

  10. Gauging Skills of Hospital Security Personnel: a Statistically-driven, Questionnaire-based Approach.

    PubMed

    Rinkoo, Arvind Vashishta; Mishra, Shubhra; Rahesuddin; Nabi, Tauqeer; Chandra, Vidha; Chandra, Hem

    2013-01-01

    This study aims to gauge the technical and soft skills of the hospital security personnel so as to enable prioritization of their training needs. A cross sectional questionnaire based study was conducted in December 2011. Two separate predesigned and pretested questionnaires were used for gauging soft skills and technical skills of the security personnel. Extensive statistical analysis, including Multivariate Analysis (Pillai-Bartlett trace along with Multi-factorial ANOVA) and Post-hoc Tests (Bonferroni Test) was applied. The 143 participants performed better on the soft skills front with an average score of 6.43 and standard deviation of 1.40. The average technical skills score was 5.09 with a standard deviation of 1.44. The study avowed a need for formal hands on training with greater emphasis on technical skills. Multivariate analysis of the available data further helped in identifying 20 security personnel who should be prioritized for soft skills training and a group of 36 security personnel who should receive maximum attention during technical skills training. This statistically driven approach can be used as a prototype by healthcare delivery institutions worldwide, after situation specific customizations, to identify the training needs of any category of healthcare staff.

  11. 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.

  12. Gauging Skills of Hospital Security Personnel: a Statistically-driven, Questionnaire-based Approach

    PubMed Central

    Rinkoo, Arvind Vashishta; Mishra, Shubhra; Rahesuddin; Nabi, Tauqeer; Chandra, Vidha; Chandra, Hem

    2013-01-01

    Objectives This study aims to gauge the technical and soft skills of the hospital security personnel so as to enable prioritization of their training needs. Methodology A cross sectional questionnaire based study was conducted in December 2011. Two separate predesigned and pretested questionnaires were used for gauging soft skills and technical skills of the security personnel. Extensive statistical analysis, including Multivariate Analysis (Pillai-Bartlett trace along with Multi-factorial ANOVA) and Post-hoc Tests (Bonferroni Test) was applied. Results The 143 participants performed better on the soft skills front with an average score of 6.43 and standard deviation of 1.40. The average technical skills score was 5.09 with a standard deviation of 1.44. The study avowed a need for formal hands on training with greater emphasis on technical skills. Multivariate analysis of the available data further helped in identifying 20 security personnel who should be prioritized for soft skills training and a group of 36 security personnel who should receive maximum attention during technical skills training. Conclusion This statistically driven approach can be used as a prototype by healthcare delivery institutions worldwide, after situation specific customizations, to identify the training needs of any category of healthcare staff. PMID:23559904

  13. 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).

  14. Neonatal morbidity in moderately preterm infants: a Swedish national population-based study.

    PubMed

    Altman, Maria; Vanpée, Mireille; Cnattingius, Sven; Norman, Mikael

    2011-02-01

    To determine the gestational age (GA)-specific risks for neonatal morbidity and use of interventions in infants born at 30 to 34 completed gestational weeks. A population-based Swedish study including 6674 infants born during 2004-2008. Risks for neonatal morbidity and use of interventions were investigated with respect to GA and birth weight standard deviation scores. Acute lung disorder was diagnosed in 28%, hypoglycemia in 16%, bacterial infection in 15% and hyperbilirubinemia in 59% of the infants. Thirty-eight percent had received antenatal steroid therapy, 43% nasal continuous positive airway pressure, 5.5% required mechanical ventilation, 5.2% were treated with surfactant, and 30% with antibiotic therapy. Neonatal morbidity rates increased with decreasing GA, with odds ratios for different outcomes ranging from 2.1 to 23 at 30 weeks compared with 34 weeks of GA. Low birth weight standard deviation scores was more common at lower GA and was associated with increased morbidity rates. Despite general advances in perinatal care, moderately preterm infants still have substantially increased risks for neonatal morbidity. Whereas the neonatal morbidity rate was similar to results of previous reports, management of respiratory problems differed markedly from other studies. Copyright © 2011 Mosby, Inc. All rights reserved.

  15. Tendency for interlaboratory precision in the GMO analysis method based on real-time PCR.

    PubMed

    Kodama, Takashi; Kurosawa, Yasunori; Kitta, Kazumi; Naito, Shigehiro

    2010-01-01

    The Horwitz curve estimates interlaboratory precision as a function only of concentration, and is frequently used as a method performance criterion in food analysis with chemical methods. The quantitative biochemical methods based on real-time PCR require an analogous criterion to progressively promote method validation. We analyzed the tendency of precision using a simplex real-time PCR technique in 53 collaborative studies of seven genetically modified (GM) crops. Reproducibility standard deviation (SR) and repeatability standard deviation (Sr) of the genetically modified organism (GMO) amount (%) was more or less independent of GM crops (i.e., maize, soybean, cotton, oilseed rape, potato, sugar beet, and rice) and evaluation procedure steps. Some studies evaluated whole steps consisting of DNA extraction and PCR quantitation, whereas others focused only on the PCR quantitation step by using DNA extraction solutions. Therefore, SR and Sr for GMO amount (%) are functions only of concentration similar to the Horwitz curve. We proposed S(R) = 0.1971C 0.8685 and S(r) = 0.1478C 0.8424, where C is the GMO amount (%). We also proposed a method performance index in GMO quantitative methods that is analogous to the Horwitz Ratio.

  16. 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.

  17. 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.

  18. Descriptive Statistics and Cluster Analysis for Extreme Rainfall in Java Island

    NASA Astrophysics Data System (ADS)

    E Komalasari, K.; Pawitan, H.; Faqih, A.

    2017-03-01

    This study aims to describe regional pattern of extreme rainfall based on maximum daily rainfall for period 1983 to 2012 in Java Island. Descriptive statistics analysis was performed to obtain centralization, variation and distribution of maximum precipitation data. Mean and median are utilized to measure central tendency data while Inter Quartile Range (IQR) and standard deviation are utilized to measure variation of data. In addition, skewness and kurtosis used to obtain shape the distribution of rainfall data. Cluster analysis using squared euclidean distance and ward method is applied to perform regional grouping. Result of this study show that mean (average) of maximum daily rainfall in Java Region during period 1983-2012 is around 80-181mm with median between 75-160mm and standard deviation between 17 to 82. Cluster analysis produces four clusters and show that western area of Java tent to have a higher annual maxima of daily rainfall than northern area, and have more variety of annual maximum value.

  19. Assessing the stock market volatility for different sectors in Malaysia by using standard deviation and EWMA methods

    NASA Astrophysics Data System (ADS)

    Saad, Shakila; Ahmad, Noryati; Jaffar, Maheran Mohd

    2017-11-01

    Nowadays, the study on volatility concept especially in stock market has gained so much attention from a group of people engaged in financial and economic sectors. The applications of volatility concept in financial economics can be seen in valuation of option pricing, estimation of financial derivatives, hedging the investment risk and etc. There are various ways to measure the volatility value. However for this study, two methods are used; the simple standard deviation and Exponentially Weighted Moving Average (EWMA). The focus of this study is to measure the volatility on three different sectors of business in Malaysia, called primary, secondary and tertiary by using both methods. The daily and annual volatilities of different business sector based on stock prices for the period of 1 January 2014 to December 2014 have been calculated in this study. Result shows that different patterns of the closing stock prices and return give different volatility values when calculating using simple method and EWMA method.

  20. Observation of the Decay Ξ_{b}^{-}→pK^{-}K^{-}.

    PubMed

    Aaij, R; Adeva, B; Adinolfi, M; Ajaltouni, Z; Akar, S; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves, A A; Amato, S; Amerio, S; Amhis, Y; An, L; Anderlini, L; Andreassi, G; Andreotti, M; Andrews, J E; Appleby, R B; Archilli, F; d'Argent, P; Arnau Romeu, J; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Baalouch, M; Babuschkin, I; Bachmann, S; Back, J J; Badalov, A; Baesso, C; Baker, S; Balagura, V; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Baszczyk, M; Batozskaya, V; Batsukh, B; Battista, V; Bay, A; Beaucourt, L; Beddow, J; Bedeschi, F; Bediaga, I; Bel, L J; Bellee, V; Belloli, N; Belous, K; Belyaev, I; Ben-Haim, E; Bencivenni, G; Benson, S; Berezhnoy, A; Bernet, R; Bertolin, A; Betancourt, C; Betti, F; Bettler, M-O; van Beuzekom, M; Bezshyiko, Ia; Bifani, S; Billoir, P; Bird, T; Birnkraut, A; Bitadze, A; Bizzeti, A; Blake, T; Blanc, F; Blouw, J; Blusk, S; Bocci, V; Boettcher, T; Bondar, A; Bondar, N; Bonivento, W; Bordyuzhin, I; Borgheresi, A; Borghi, S; Borisyak, M; Borsato, M; Bossu, F; Boubdir, M; Bowcock, T J V; Bowen, E; Bozzi, C; Braun, S; Britsch, M; Britton, T; Brodzicka, J; Buchanan, E; Burr, C; Bursche, A; Buytaert, J; Cadeddu, S; Calabrese, R; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Campora Perez, D H; Capriotti, L; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carniti, P; Carson, L; Carvalho Akiba, K; Casse, G; Cassina, L; Castillo Garcia, L; Cattaneo, M; Cavallero, G; Cenci, R; Chamont, D; Charles, M; Charpentier, Ph; Chatzikonstantinidis, G; Chefdeville, M; Chen, S; Cheung, S-F; Chobanova, V; Chrzaszcz, M; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coco, V; Cogan, J; Cogneras, E; Cogoni, V; Cojocariu, L; Collazuol, G; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombs, G; Coquereau, S; Corti, G; Corvo, M; Costa Sobral, C M; Couturier, B; Cowan, G A; Craik, D C; Crocombe, A; Cruz Torres, M; Cunliffe, S; Currie, R; D'Ambrosio, C; Da Cunha Marinho, F; Dall'Occo, E; Dalseno, J; David, P N Y; Davis, A; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Serio, M; De Simone, P; Dean, C-T; Decamp, D; Deckenhoff, M; Del Buono, L; Demmer, M; Dendek, A; Derkach, D; Deschamps, O; Dettori, F; Dey, B; Di Canto, A; Dijkstra, H; Dordei, F; Dorigo, M; Dosil Suárez, A; Dovbnya, A; Dreimanis, K; Dufour, L; Dujany, G; Dungs, K; Durante, P; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Déléage, N; Easo, S; Ebert, M; Egede, U; Egorychev, V; Eidelman, S; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; Ely, S; Esen, S; Evans, H M; Evans, T; Falabella, A; Farley, N; Farry, S; Fay, R; Fazzini, D; Ferguson, D; Fernandez Prieto, A; Ferrari, F; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fini, R A; Fiore, M; Fiorini, M; Firlej, M; Fitzpatrick, C; Fiutowski, T; Fleuret, F; Fohl, K; Fontana, M; Fontanelli, F; Forshaw, D C; Forty, R; Franco Lima, V; Frank, M; Frei, C; Fu, J; Funk, W; Furfaro, E; Färber, C; Gallas Torreira, A; Galli, D; Gallorini, S; Gambetta, S; Gandelman, M; Gandini, P; Gao, Y; Garcia Martin, L M; García Pardiñas, J; Garra Tico, J; Garrido, L; Garsed, P J; Gascon, D; Gaspar, C; Gavardi, L; Gazzoni, G; Gerick, D; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gianì, S; Gibson, V; Girard, O G; Giubega, L; Gizdov, K; Gligorov, V V; Golubkov, D; Golutvin, A; Gomes, A; Gorelov, I V; Gotti, C; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graverini, E; Graziani, G; Grecu, A; Griffith, P; Grillo, L; Gruberg Cazon, B R; Grünberg, O; Gushchin, E; Guz, Yu; Gys, T; Göbel, C; Hadavizadeh, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Haines, S C; Hall, S; Hamilton, B; Han, X; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Hatch, M; He, J; Head, T; Heister, A; Hennessy, K; Henrard, P; Henry, L; van Herwijnen, E; Heß, M; Hicheur, A; Hill, D; Hombach, C; Hopchev, H; Hulsbergen, W; Humair, T; Hushchyn, M; Hutchcroft, D; Idzik, M; Ilten, P; Jacobsson, R; Jaeger, A; Jalocha, J; Jans, E; Jawahery, A; Jiang, F; John, M; Johnson, D; Jones, C R; Joram, C; Jost, B; Jurik, N; Kandybei, S; Karacson, M; Kariuki, J M; Karodia, S; Kecke, M; Kelsey, M; Kenzie, M; Ketel, T; Khairullin, E; Khanji, B; Khurewathanakul, C; Kirn, T; Klaver, S; Klimaszewski, K; Koliiev, S; Kolpin, M; Komarov, I; Koopman, R F; Koppenburg, P; Kosmyntseva, A; Kozachuk, A; Kozeiha, M; Kravchuk, L; Kreplin, K; Kreps, M; Krokovny, P; Kruse, F; Krzemien, W; Kucewicz, W; Kucharczyk, M; Kudryavtsev, V; Kuonen, A K; Kurek, K; Kvaratskheliya, T; Lacarrere, D; Lafferty, G; Lai, A; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Leflat, A; Lefrançois, J; Lefèvre, R; Lemaitre, F; Lemos Cid, E; Leroy, O; Lesiak, T; Leverington, B; Li, T; Li, Y; Likhomanenko, T; Lindner, R; Linn, C; Lionetto, F; Liu, X; Loh, D; Longstaff, I; Lopes, J H; Lucchesi, D; Lucio Martinez, M; Luo, H; Lupato, A; Luppi, E; Lupton, O; Lusiani, A; Lyu, X; Machefert, F; Maciuc, F; Maev, O; Maguire, K; Malde, S; Malinin, A; Maltsev, T; Manca, G; Mancinelli, G; Manning, P; Maratas, J; Marchand, J F; Marconi, U; Marin Benito, C; Marinangeli, M; Marino, P; Marks, J; Martellotti, G; Martin, M; Martinelli, M; Martinez Santos, D; Martinez Vidal, F; Martins Tostes, D; Massacrier, L M; Massafferri, A; Matev, R; Mathad, A; Mathe, Z; Matteuzzi, C; Mauri, A; Maurice, E; Maurin, B; Mazurov, A; McCann, M; McNab, A; McNulty, R; Meadows, B; Meier, F; Meissner, M; Melnychuk, D; Merk, M; Merli, A; Michielin, E; Milanes, D A; Minard, M-N; Mitzel, D S; Mogini, A; Molina Rodriguez, J; Monroy, I A; Monteil, S; Morandin, M; Morawski, P; Mordà, A; Morello, M J; Morgunova, O; Moron, J; Morris, A B; Mountain, R; Muheim, F; Mulder, M; Mussini, M; Müller, D; Müller, J; Müller, K; Müller, V; Naik, P; Nakada, T; Nandakumar, R; Nandi, A; Nasteva, I; Needham, M; Neri, N; Neubert, S; Neufeld, N; Neuner, M; Nguyen, T D; Nguyen-Mau, C; Nieswand, S; Niet, R; Nikitin, N; Nikodem, T; Nogay, A; Novoselov, A; O'Hanlon, D P; Oblakowska-Mucha, A; Obraztsov, V; Ogilvy, S; Oldeman, R; Onderwater, C J G; Otalora Goicochea, J M; Otto, A; Owen, P; Oyanguren, A; Pais, P R; Palano, A; Palombo, F; Palutan, M; Papanestis, A; Pappagallo, M; Pappalardo, L L; Parker, W; Parkes, C; Passaleva, G; Pastore, A; Patel, G D; Patel, M; Patrignani, C; Pearce, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perret, P; Pescatore, L; Petridis, K; Petrolini, A; Petrov, A; Petruzzo, M; Picatoste Olloqui, E; Pietrzyk, B; Pikies, M; Pinci, D; Pistone, A; Piucci, A; Placinta, V; Playfer, S; Plo Casasus, M; Poikela, T; Polci, F; Poluektov, A; Polyakov, I; Polycarpo, E; Pomery, G J; Popov, A; Popov, D; Popovici, B; Poslavskii, S; Potterat, C; Price, E; Price, J D; Prisciandaro, J; Pritchard, A; Prouve, C; Pugatch, V; Puig Navarro, A; Punzi, G; Qian, W; Quagliani, R; Rachwal, B; Rademacker, J H; Rama, M; Ramos Pernas, M; Rangel, M S; Raniuk, I; Ratnikov, F; Raven, G; Redi, F; Reichert, S; Dos Reis, A C; Remon Alepuz, C; Renaudin, V; Ricciardi, S; Richards, S; Rihl, M; Rinnert, K; Rives Molina, V; Robbe, P; Rodrigues, A B; Rodrigues, E; Rodriguez Lopez, J A; Rodriguez Perez, P; Rogozhnikov, A; Roiser, S; Rollings, A; Romanovskiy, V; Romero Vidal, A; Ronayne, J W; Rotondo, M; Rudolph, M S; Ruf, T; Ruiz Valls, P; Saborido Silva, J J; Sadykhov, E; Sagidova, N; Saitta, B; Salustino Guimaraes, V; Sanchez Mayordomo, C; Sanmartin Sedes, B; Santacesaria, R; Santamarina Rios, C; Santimaria, M; Santovetti, E; Sarti, A; Satriano, C; Satta, A; Saunders, D M; Savrina, D; Schael, S; Schellenberg, M; Schiller, M; Schindler, H; Schlupp, M; Schmelling, M; Schmelzer, T; Schmidt, B; Schneider, O; Schopper, A; Schubert, K; Schubiger, M; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Semennikov, A; Sergi, A; Serra, N; Serrano, J; Sestini, L; Seyfert, P; Shapkin, M; Shapoval, I; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, V; Siddi, B G; Silva Coutinho, R; Silva de Oliveira, L; Simi, G; Simone, S; Sirendi, M; Skidmore, N; Skwarnicki, T; Smith, E; Smith, I T; Smith, J; Smith, M; Snoek, H; Soares Lavra, L; Sokoloff, M D; Soler, F J P; Souza De Paula, B; Spaan, B; Spradlin, P; Sridharan, S; Stagni, F; Stahl, M; Stahl, S; Stefko, P; Stefkova, S; Steinkamp, O; Stemmle, S; Stenyakin, O; Stevens, H; Stevenson, S; Stoica, S; Stone, S; Storaci, B; Stracka, S; Straticiuc, M; Straumann, U; Sun, L; Sutcliffe, W; Swientek, K; Syropoulos, V; Szczekowski, M; Szumlak, T; T'Jampens, S; Tayduganov, A; Tekampe, T; Tellarini, G; Teubert, F; Thomas, E; van Tilburg, J; Tilley, M J; Tisserand, V; Tobin, M; Tolk, S; Tomassetti, L; Tonelli, D; Topp-Joergensen, S; Toriello, F; Tournefier, E; Tourneur, S; Trabelsi, K; Traill, M; Tran, M T; Tresch, M; Trisovic, A; Tsaregorodtsev, A; Tsopelas, P; Tully, A; Tuning, N; Ukleja, A; Ustyuzhanin, A; Uwer, U; Vacca, C; Vagnoni, V; Valassi, A; Valat, S; Valenti, G; Vazquez Gomez, R; Vazquez Regueiro, P; Vecchi, S; van Veghel, M; Velthuis, J J; Veltri, M; Veneziano, G; Venkateswaran, A; Vernet, M; Vesterinen, M; Viana Barbosa, J V; Viaud, B; Vieira, D; Vieites Diaz, M; Viemann, H; Vilasis-Cardona, X; Vitti, M; Volkov, V; Vollhardt, A; Voneki, B; Vorobyev, A; Vorobyev, V; Voß, C; de Vries, J A; Vázquez Sierra, C; Waldi, R; Wallace, C; Wallace, R; Walsh, J; Wang, J; Ward, D R; Wark, H M; Watson, N K; Websdale, D; Weiden, A; Whitehead, M; Wicht, J; Wilkinson, G; Wilkinson, M; Williams, M; Williams, M P; Williams, M; Williams, T; Wilson, F F; Wimberley, J; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wraight, K; Wyllie, K; Xie, Y; Xing, Z; Xu, Z; Yang, Z; Yao, Y; Yin, H; Yu, J; Yuan, X; Yushchenko, O; Zarebski, K A; Zavertyaev, M; Zhang, L; Zhang, Y; Zhang, Y; Zhelezov, A; Zheng, Y; Zhu, X; Zhukov, V; Zucchelli, S

    2017-02-17

    Decays of the Ξ_{b}^{-} and Ω_{b}^{-} baryons to the charmless final states ph^{-}h^{'-}, where h^{(')} denotes a kaon or pion, are searched for with the LHCb detector. The analysis is based on a sample of proton-proton collision data collected at center-of-mass energies sqrt[s]=7 and 8 TeV, corresponding to an integrated luminosity of 3  fb^{-1}. The decay Ξ_{b}^{-}→pK^{-}K^{-} is observed with a significance of 8.7 standard deviations, and evidence at the level of 3.4 standard deviations is found for the Ξ_{b}^{-}→pK^{-}π^{-} decay. Results are reported, relative to the B^{-}→K^{+}K^{-}K^{-} normalization channel, for the products of branching fractions and b-hadron production fractions. The branching fractions of Ξ_{b}^{-}→pK^{-}π^{-} and Ξ_{b}^{-}→pπ^{-}π^{-} relative to Ξ_{b}^{-}→pK^{-}K^{-} decays are also measured.

  1. A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

    NASA Astrophysics Data System (ADS)

    Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

    2017-12-01

    Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

  2. Solid phase extraction and spectrophotometric determination of Au(III) with 5-(2-hydroxy-5-nitrophenylazo)thiorhodanine.

    PubMed

    Hu, Qiufen; Chen, Xiubin; Yang, Xiangjun; Huang, Zhangjie; Chen, Jing; Yang, Guangyu

    2006-04-01

    A new chromogenic reagent, 5-(2-hydroxy-5-nitrophenylazo)thiorhodanine (HNATR) was synthesized. A highly sensitive, selective and rapid method for the determination microg l(-1) level of Au(III) based on the rapid reaction of Au(III) with HNATR and the solid phase extraction of the colored complex with a reversed phase polymer-based C(18) cartridge have been developed. The HNATR reacted with Au(III) to form a red complex of a molar ratio 1:2 (Au(III) to HNATR) in the presence of 0.05 - 0.5 mol l(-1) of phosphoric acid solution and emulsifier-OP medium. This complex was enriched by the solid phase extraction with a polymer-based C(18) cartridge. The enrichment factor of 100 was achieved. The molar absorptivity of the complex is 1.37 x 10(5) l mol(-1) cm(-1) at 520 nm in the measured solution. The system obeys Beer's law in the range of 0.01 - 3 microg ml(-1). The relative standard deviation for eleven replicates sample of 0.5 microg l(-1) level is 2.18%. The detection limit, based on the three times of standard deviation is 0.02 microg l(-1) in the original sample. This method was applied to the determination of gold in water and ore with good results.

  3. Photoplethysmograph signal reconstruction based on a novel hybrid motion artifact detection-reduction approach. Part I: Motion and noise artifact detection.

    PubMed

    Chong, Jo Woon; Dao, Duy K; Salehizadeh, S M A; McManus, David D; Darling, Chad E; Chon, Ki H; Mendelson, Yitzhak

    2014-11-01

    Motion and noise artifacts (MNA) are a serious obstacle in utilizing photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a MNA detection method which can provide a clean vs. corrupted decision on each successive PPG segment. For motion artifact detection, we compute four time-domain parameters: (1) standard deviation of peak-to-peak intervals (2) standard deviation of peak-to-peak amplitudes (3) standard deviation of systolic and diastolic interval ratios, and (4) mean standard deviation of pulse shape. We have adopted a support vector machine (SVM) which takes these parameters from clean and corrupted PPG signals and builds a decision boundary to classify them. We apply several distinct features of the PPG data to enhance classification performance. The algorithm we developed was verified on PPG data segments recorded by simulation, laboratory-controlled and walking/stair-climbing experiments, respectively, and we compared several well-established MNA detection methods to our proposed algorithm. All compared detection algorithms were evaluated in terms of motion artifact detection accuracy, heart rate (HR) error, and oxygen saturation (SpO2) error. For laboratory controlled finger, forehead recorded PPG data and daily-activity movement data, our proposed algorithm gives 94.4, 93.4, and 93.7% accuracies, respectively. Significant reductions in HR and SpO2 errors (2.3 bpm and 2.7%) were noted when the artifacts that were identified by SVM-MNA were removed from the original signal than without (17.3 bpm and 5.4%). The accuracy and error values of our proposed method were significantly higher and lower, respectively, than all other detection methods. Another advantage of our method is its ability to provide highly accurate onset and offset detection times of MNAs. This capability is important for an automated approach to signal reconstruction of only those data points that need to be reconstructed, which is the subject of the companion paper to this article. Finally, our MNA detection algorithm is real-time realizable as the computational speed on the 7-s PPG data segment was found to be only 7 ms with a Matlab code.

  4. Trace element analysis of extraterrestrial metal samples by inductively coupled plasma mass spectrometry: the standard solutions and digesting acids.

    PubMed

    Wang, Guiqin; Wu, Yangsiqian; Lin, Yangting

    2016-02-28

    Nearly 99% of the total content of extraterrestrial metals is composed of Fe and Ni, but with greatly variable trace element contents. The accuracy obtained in the inductively coupled plasma mass spectrometry (ICP-MS) analysis of solutions of these samples can be significantly influenced by matrix contents, polyatomic ion interference, and the concentrations of external standard solutions. An ICP-MS instrument (X Series 2) was used to determine 30 standard solutions with different concentrations of trace elements, and different matrix contents. Based on these measurements, the matrix effects were determined. Three iron meteorites were dissolved separately in aqua regia and HNO3. Deviations due to variation of matrix contents in the external standard solutions were evaluated and the analysis results of the two digestion methods for iron meteorites were assessed. Our results show obvious deviations due to unmatched matrix contents in the external standard solutions. Furthermore, discrepancy in the measurement of some elements was found between the sample solutions prepared with aqua regia and HNO3, due to loss of chloride during sample preparation and/or incomplete digestion of highly siderophile elements in iron meteorites. An accurate ICP-MS analysis method for extraterrestrial metal samples has been established using external standard solutions with matched matrix contents and digesting the samples with HNO3 and aqua regia. Using the data from this work, the Mundrabilla iron meteorite previously classified as IAB-ung is reclassified as IAB-MG. Copyright © 2016 John Wiley & Sons, Ltd.

  5. Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set.

    PubMed

    Lenselink, Eelke B; Ten Dijke, Niels; Bongers, Brandon; Papadatos, George; van Vlijmen, Herman W T; Kowalczyk, Wojtek; IJzerman, Adriaan P; van Westen, Gerard J P

    2017-08-14

    The increase of publicly available bioactivity data in recent years has fueled and catalyzed research in chemogenomics, data mining, and modeling approaches. As a direct result, over the past few years a multitude of different methods have been reported and evaluated, such as target fishing, nearest neighbor similarity-based methods, and Quantitative Structure Activity Relationship (QSAR)-based protocols. However, such studies are typically conducted on different datasets, using different validation strategies, and different metrics. In this study, different methods were compared using one single standardized dataset obtained from ChEMBL, which is made available to the public, using standardized metrics (BEDROC and Matthews Correlation Coefficient). Specifically, the performance of Naïve Bayes, Random Forests, Support Vector Machines, Logistic Regression, and Deep Neural Networks was assessed using QSAR and proteochemometric (PCM) methods. All methods were validated using both a random split validation and a temporal validation, with the latter being a more realistic benchmark of expected prospective execution. Deep Neural Networks are the top performing classifiers, highlighting the added value of Deep Neural Networks over other more conventional methods. Moreover, the best method ('DNN_PCM') performed significantly better at almost one standard deviation higher than the mean performance. Furthermore, Multi-task and PCM implementations were shown to improve performance over single task Deep Neural Networks. Conversely, target prediction performed almost two standard deviations under the mean performance. Random Forests, Support Vector Machines, and Logistic Regression performed around mean performance. Finally, using an ensemble of DNNs, alongside additional tuning, enhanced the relative performance by another 27% (compared with unoptimized 'DNN_PCM'). Here, a standardized set to test and evaluate different machine learning algorithms in the context of multi-task learning is offered by providing the data and the protocols. Graphical Abstract .

  6. 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

  7. Measuring (subglacial) bedform orientation, length, and longitudinal asymmetry - Method assessment.

    PubMed

    Jorge, Marco G; Brennand, Tracy A

    2017-01-01

    Geospatial analysis software provides a range of tools that can be used to measure landform morphometry. Often, a metric can be computed with different techniques that may give different results. This study is an assessment of 5 different methods for measuring longitudinal, or streamlined, subglacial bedform morphometry: orientation, length and longitudinal asymmetry, all of which require defining a longitudinal axis. The methods use the standard deviational ellipse (not previously applied in this context), the longest straight line fitting inside the bedform footprint (2 approaches), the minimum-size footprint-bounding rectangle, and Euler's approximation. We assess how well these methods replicate morphometric data derived from a manually mapped (visually interpreted) longitudinal axis, which, though subjective, is the most typically used reference. A dataset of 100 subglacial bedforms covering the size and shape range of those in the Puget Lowland, Washington, USA is used. For bedforms with elongation > 5, deviations from the reference values are negligible for all methods but Euler's approximation (length). For bedforms with elongation < 5, most methods had small mean absolute error (MAE) and median absolute deviation (MAD) for all morphometrics and thus can be confidently used to characterize the central tendencies of their distributions. However, some methods are better than others. The least precise methods are the ones based on the longest straight line and Euler's approximation; using these for statistical dispersion analysis is discouraged. Because the standard deviational ellipse method is relatively shape invariant and closely replicates the reference values, it is the recommended method. Speculatively, this study may also apply to negative-relief, and fluvial and aeolian bedforms.

  8. The impact of the fabrication method on the three-dimensional accuracy of an implant surgery template.

    PubMed

    Matta, Ragai-Edward; Bergauer, Bastian; Adler, Werner; Wichmann, Manfred; Nickenig, Hans-Joachim

    2017-06-01

    The use of a surgical template is a well-established method in advanced implantology. In addition to conventional fabrication, computer-aided design and computer-aided manufacturing (CAD/CAM) work-flow provides an opportunity to engineer implant drilling templates via a three-dimensional printer. In order to transfer the virtual planning to the oral situation, a highly accurate surgical guide is needed. The aim of this study was to evaluate the impact of the fabrication method on the three-dimensional accuracy. The same virtual planning based on a scanned plaster model was used to fabricate a conventional thermo-formed and a three-dimensional printed surgical guide for each of 13 patients (single tooth implants). Both templates were acquired individually on the respective plaster model using an optical industrial white-light scanner (ATOS II, GOM mbh, Braunschweig, Germany), and the virtual datasets were superimposed. Using the three-dimensional geometry of the implant sleeve, the deviation between both surgical guides was evaluated. The mean discrepancy of the angle was 3.479° (standard deviation, 1.904°) based on data from 13 patients. Concerning the three-dimensional position of the implant sleeve, the highest deviation was in the Z-axis at 0.594 mm. The mean deviation of the Euclidian distance, dxyz, was 0.864 mm. Although the two different fabrication methods delivered statistically significantly different templates, the deviations ranged within a decimillimeter span. Both methods are appropriate for clinical use. Copyright © 2017 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

  9. Evaluation and validity of a LORETA normative EEG database.

    PubMed

    Thatcher, R W; North, D; Biver, C

    2005-04-01

    To evaluate the reliability and validity of a Z-score normative EEG database for Low Resolution Electromagnetic Tomography (LORETA), EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) were acquired from 106 normal subjects, and the cross-spectrum was computed and multiplied by the Key Institute's LORETA 2,394 gray matter pixel T Matrix. After a log10 transform or a Box-Cox transform the mean and standard deviation of the *.lor files were computed for each of the 2394 gray matter pixels, from 1 to 30 Hz, for each of the subjects. Tests of Gaussianity were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of a Z-score database was computed by measuring the approximation to a Gaussian distribution. The validity of the LORETA normative database was evaluated by the degree to which confirmed brain pathologies were localized using the LORETA normative database. Log10 and Box-Cox transforms approximated Gaussian distribution in the range of 95.64% to 99.75% accuracy. The percentage of normative Z-score values at 2 standard deviations ranged from 1.21% to 3.54%, and the percentage of Z-scores at 3 standard deviations ranged from 0% to 0.83%. Left temporal lobe epilepsy, right sensory motor hematoma and a right hemisphere stroke exhibited maximum Z-score deviations in the same locations as the pathologies. We conclude: (1) Adequate approximation to a Gaussian distribution can be achieved using LORETA by using a log10 transform or a Box-Cox transform and parametric statistics, (2) a Z-Score normative database is valid with adequate sensitivity when using LORETA, and (3) the Z-score LORETA normative database also consistently localized known pathologies to the expected Brodmann areas as an hypothesis test based on the surface EEG before computing LORETA.

  10. ROBUST: an interactive FORTRAN-77 package for exploratory data analysis using parametric, ROBUST and nonparametric location and scale estimates, data transformations, normality tests, and outlier assessment

    NASA Astrophysics Data System (ADS)

    Rock, N. M. S.

    ROBUST calculates 53 statistics, plus significance levels for 6 hypothesis tests, on each of up to 52 variables. These together allow the following properties of the data distribution for each variable to be examined in detail: (1) Location. Three means (arithmetic, geometric, harmonic) are calculated, together with the midrange and 19 high-performance robust L-, M-, and W-estimates of location (combined, adaptive, trimmed estimates, etc.) (2) Scale. The standard deviation is calculated along with the H-spread/2 (≈ semi-interquartile range), the mean and median absolute deviations from both mean and median, and a biweight scale estimator. The 23 location and 6 scale estimators programmed cover all possible degrees of robustness. (3) Normality: Distributions are tested against the null hypothesis that they are normal, using the 3rd (√ h1) and 4th ( b 2) moments, Geary's ratio (mean deviation/standard deviation), Filliben's probability plot correlation coefficient, and a more robust test based on the biweight scale estimator. These statistics collectively are sensitive to most usual departures from normality. (4) Presence of outliers. The maximum and minimum values are assessed individually or jointly using Grubbs' maximum Studentized residuals, Harvey's and Dixon's criteria, and the Studentized range. For a single input variable, outliers can be either winsorized or eliminated and all estimates recalculated iteratively as desired. The following data-transformations also can be applied: linear, log 10, generalized Box Cox power (including log, reciprocal, and square root), exponentiation, and standardization. For more than one variable, all results are tabulated in a single run of ROBUST. Further options are incorporated to assess ratios (of two variables) as well as discrete variables, and be concerned with missing data. Cumulative S-plots (for assessing normality graphically) also can be generated. The mutual consistency or inconsistency of all these measures helps to detect errors in data as well as to assess data-distributions themselves.

  11. Comparing language outcomes in monolingual and bilingual stroke patients

    PubMed Central

    Parker Jones, ‘Ōiwi; Grogan, Alice; Crinion, Jenny; Rae, Johanna; Ruffle, Louise; Leff, Alex P.; Seghier, Mohamed L.; Price, Cathy J.; Green, David W.

    2015-01-01

    Post-stroke prognoses are usually inductive, generalizing trends learned from one group of patients, whose outcomes are known, to make predictions for new patients. Research into the recovery of language function is almost exclusively focused on monolingual stroke patients, but bilingualism is the norm in many parts of the world. If bilingual language recruits qualitatively different networks in the brain, prognostic models developed for monolinguals might not generalize well to bilingual stroke patients. Here, we sought to establish how applicable post-stroke prognostic models, trained with monolingual patient data, are to bilingual stroke patients who had been ordinarily resident in the UK for many years. We used an algorithm to extract binary lesion images for each stroke patient, and assessed their language with a standard tool. We used feature selection and cross-validation to find ‘good’ prognostic models for each of 22 different language skills, using monolingual data only (174 patients; 112 males and 62 females; age at stroke: mean = 53.0 years, standard deviation = 12.2 years, range = 17.2–80.1 years; time post-stroke: mean = 55.6 months, standard deviation = 62.6 months, range = 3.1–431.9 months), then made predictions for both monolinguals and bilinguals (33 patients; 18 males and 15 females; age at stroke: mean = 49.0 years, standard deviation = 13.2 years, range = 23.1–77.0 years; time post-stroke: mean = 49.2 months, standard deviation = 55.8 months, range = 3.9–219.9 months) separately, after training with monolingual data only. We measured group differences by comparing prediction error distributions, and used a Bayesian test to search for group differences in terms of lesion-deficit associations in the brain. Our models distinguish better outcomes from worse outcomes equally well within each group, but tended to be over-optimistic when predicting bilingual language outcomes: our bilingual patients tended to have poorer language skills than expected, based on trends learned from monolingual data alone, and this was significant (P < 0.05, corrected for multiple comparisons) in 13/22 language tasks. Both patient groups appeared to be sensitive to damage in the same sets of regions, though the bilinguals were more sensitive than the monolinguals. PMID:25688076

  12. Improving estimates of streamflow characteristics using LANDSAT-1 (ERTS-1) imagery. [Delmarva Peninsula

    NASA Technical Reports Server (NTRS)

    Hollyday, E. F. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. Streamflow characteristics in the Delmarva Peninsula derived from the records of daily discharge of 20 gaged basins are representative of the full range in flow conditions and include all of those commonly used for design or planning purposes. They include annual flood peaks with recurrence intervals of 2, 5, 10, 25, and 50 years, mean annual discharge, standard deviation of the mean annual discharge, mean monthly discharges, standard deviation of the mean monthly discharges, low-flow characteristics, flood volume characteristics, and the discharge equalled or exceeded 50 percent of the time. Streamflow and basin characteristics were related by a technique of multiple regression using a digital computer. A control group of equations was computed using basin characteristics derived from maps and climatological records. An experimental group of equations was computed using basin characteristics derived from LANDSAT imagery as well as from maps and climatological records. Based on a reduction in standard error of estimate equal to or greater than 10 percent, the equations for 12 stream flow characteristics were substantially improved by adding to the analyses basin characteristics derived from LANDSAT imagery.

  13. The Slow Controls System of the New Muon g-2 Experiment at Fermilab

    NASA Astrophysics Data System (ADS)

    Eads, Michael; New Muon g-2 Collaboration

    2015-04-01

    The goal of the new muon g-2 experiment (E-989), currently under construction at Fermi National Accelerator Laboratory, is to measure the anomalous gyromagnetic ratio of the muon with unprecedented precision. The uncertainty goal of the experiment, 0.14ppm, represents a four-fold improvement over the current best measurement of this value and has the potential to increase the current three standard deviation disagreement with the predicted standard model value to five standard deviations. Measuring the operating conditions of the experiment will be essential to achieving these uncertainty goals. This talk will describe the design and the current status of E-989's slow controls system. This system, based on the MIDAS Slow Control Bus, will be used to measure and record currents, voltages, temperatures, humidities, pressures, flows, and other data which is collected asynchronously with the injection of the muon beam. The system consists of a variety of sensors and front-end electronics which interface to back-end data acquisition, data storage, and data monitoring systems. Parts of the system are all already operational and the full system will be completed before beam commissioning begins in 2017.

  14. Quantitative assessment of joint position sense recovery in subacute stroke patients: a pilot study.

    PubMed

    Kattenstroth, Jan-Christoph; Kalisch, Tobias; Kowalewski, Rebecca; Tegenthoff, Martin; Dinse, Hubert R

    2013-11-01

    To assess joint position sense performance in subacute stroke patients using a novel quantitative assessment. Proof-of-principle pilot study with a group of subacute stroke patients. Assessment at baseline and after 2 weeks of intervention. Additional data for a healthy age-matched control group. Ten subacute stroke patients (aged 65.41 years (standard deviation 2.5), 4 females, 2.3 weeks (standard deviation 0.2)) post-stroke receiving in-patient standard rehabilitation and repetitive electrical stimulation of the affected hand. Joint position sense was assessed based on the ability of correctly perceiving the opening angles of the finger joints. Patients had to report size differences of polystyrene balls of various sizes, whilst the balls were enclosed simultaneously by the affected and the non-affected hands. A total of 21 pairwise size comparisons was used to quantify joint position performance. After 2 weeks of therapeutic intervention a significant improvement in joint position sense performance was observed; however, the performance level was still below that of a healthy control group. The results indicate high feasibility and sensitivity of the joint position test in subacute stroke patients. Testing allowed quantification of both the deficit and the rehabilitation outcome.

  15. Vocal singing by prelingually-deafened children with cochlear implants.

    PubMed

    Xu, Li; Zhou, Ning; Chen, Xiuwu; Li, Yongxin; Schultz, Heather M; Zhao, Xiaoyan; Han, Demin

    2009-09-01

    The coarse pitch information in cochlear implants might hinder the development of singing in prelingually-deafened pediatric users. In the present study, seven prelingually-deafened children with cochlear implants (5.4-12.3 years old) sang one song that was the most familiar to him or her. The control group consisted of 14 normal-hearing children (4.1-8.0 years old). The fundamental frequencies (F0) of each note in the recorded songs were extracted. The following five metrics were computed based on the reference music scores: (1) F0 contour direction of the adjacent notes, (2) F0 compression ratio of the entire song, (3) mean deviation of the normalized F0 across the notes, (4) mean deviation of the pitch intervals, and (5) standard deviation of the note duration differences. Children with cochlear implants showed significantly poorer performance in the pitch-based assessments than the normal-hearing children. No significant differences were seen between the two groups in the rhythm-based measure. Prelingually-deafened children with cochlear implants have significant deficits in singing due to their inability to manipulate pitch in the correct directions and to produce accurate pitch height. Future studies with a large sample size are warranted in order to account for the large variability in singing performance.

  16. 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.

  17. 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.

  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. 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.

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Reproducibility of a Standardized Actigraphy Scoring Algorithm for Sleep in a US Hispanic/Latino Population

    PubMed Central

    Patel, Sanjay R.; Weng, Jia; Rueschman, Michael; Dudley, Katherine A.; Loredo, Jose S.; Mossavar-Rahmani, Yasmin; Ramirez, Maricelle; Ramos, Alberto R.; Reid, Kathryn; Seiger, Ashley N.; Sotres-Alvarez, Daniela; Zee, Phyllis C.; Wang, Rui

    2015-01-01

    Study Objectives: While actigraphy is considered objective, the process of setting rest intervals to calculate sleep variables is subjective. We sought to evaluate the reproducibility of actigraphy-derived measures of sleep using a standardized algorithm for setting rest intervals. Design: Observational study. Setting: Community-based. Participants: A random sample of 50 adults aged 18–64 years free of severe sleep apnea participating in the Sueño sleep ancillary study to the Hispanic Community Health Study/Study of Latinos. Interventions: N/A. Measurements and Results: Participants underwent 7 days of continuous wrist actigraphy and completed daily sleep diaries. Studies were scored twice by each of two scorers. Rest intervals were set using a standardized hierarchical approach based on event marker, diary, light, and activity data. Sleep/wake status was then determined for each 30-sec epoch using a validated algorithm, and this was used to generate 11 variables: mean nightly sleep duration, nap duration, 24-h sleep duration, sleep latency, sleep maintenance efficiency, sleep fragmentation index, sleep onset time, sleep offset time, sleep midpoint time, standard deviation of sleep duration, and standard deviation of sleep midpoint. Intra-scorer intraclass correlation coefficients (ICCs) were high, ranging from 0.911 to 0.995 across all 11 variables. Similarly, inter-scorer ICCs were high, also ranging from 0.911 to 0.995, and mean inter-scorer differences were small. Bland-Altman plots did not reveal any systematic disagreement in scoring. Conclusions: With use of a standardized algorithm to set rest intervals, scoring of actigraphy for the purpose of generating a wide array of sleep variables is highly reproducible. Citation: Patel SR, Weng J, Rueschman M, Dudley KA, Loredo JS, Mossavar-Rahmani Y, Ramirez M, Ramos AR, Reid K, Seiger AN, Sotres-Alvarez D, Zee PC, Wang R. Reproducibility of a standardized actigraphy scoring algorithm for sleep in a US Hispanic/Latino population. SLEEP 2015;38(9):1497–1503. PMID:25845697

  8. Windowed and Wavelet Analysis of Marine Stratocumulus Cloud Inhomogeneity

    NASA Technical Reports Server (NTRS)

    Gollmer, Steven M.; Harshvardhan; Cahalan, Robert F.; Snider, Jack B.

    1995-01-01

    To improve radiative transfer calculations for inhomogeneous clouds, a consistent means of modeling inhomogeneity is needed. One current method of modeling cloud inhomogeneity is through the use of fractal parameters. This method is based on the supposition that cloud inhomogeneity over a large range of scales is related. An analysis technique named wavelet analysis provides a means of studying the multiscale nature of cloud inhomogeneity. In this paper, the authors discuss the analysis and modeling of cloud inhomogeneity through the use of wavelet analysis. Wavelet analysis as well as other windowed analysis techniques are used to study liquid water path (LWP) measurements obtained during the marine stratocumulus phase of the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment. Statistics obtained using analysis windows, which are translated to span the LWP dataset, are used to study the local (small scale) properties of the cloud field as well as their time dependence. The LWP data are transformed onto an orthogonal wavelet basis that represents the data as a number of times series. Each of these time series lies within a frequency band and has a mean frequency that is half the frequency of the previous band. Wavelet analysis combined with translated analysis windows reveals that the local standard deviation of each frequency band is correlated with the local standard deviation of the other frequency bands. The ratio between the standard deviation of adjacent frequency bands is 0.9 and remains constant with respect to time. This ratio defined as the variance coupling parameter is applicable to all of the frequency bands studied and appears to be related to the slope of the data's power spectrum. Similar analyses are performed on two cloud inhomogeneity models, which use fractal-based concepts to introduce inhomogeneity into a uniform cloud field. The bounded cascade model does this by iteratively redistributing LWP at each scale using the value of the local mean. This model is reformulated into a wavelet multiresolution framework, thereby presenting a number of variants of the bounded cascade model. One variant introduced in this paper is the 'variance coupled model,' which redistributes LWP using the local standard deviation and the variance coupling parameter. While the bounded cascade model provides an elegant two- parameter model for generating cloud inhomogeneity, the multiresolution framework provides more flexibility at the expense of model complexity. Comparisons are made with the results from the LWP data analysis to demonstrate both the strengths and weaknesses of these models.

  9. Standardized Precipitation Index (SPI) over the Mediterranean region based on high resolution gridded data.

    NASA Astrophysics Data System (ADS)

    Polychroni, Iliana; Nastos, Panagiotis

    2017-04-01

    Mediterranean water resource system is heavily influenced by changes in climate conditions, which in turns affect significantly the socioeconomic development, specifically over coastal areas. Taking into consideration that the surface temperature is projected to rise over the 21st century and the mean precipitation is likely to decrease in mid-latitude dry regions, according to IPCC 2014, we confronted the challenge to study the drought over the Mediterranean region by means of the Standardized Precipitation Index (SPI), defined as the difference from the mean for a specified time period divided by the standard deviation, where the mean and standard deviation are determined from past records. Drought is a long-range phenomenon that affects the Mediterranean. The drought not only affects food production but also has severe environmental, economic and social impacts. The objective of this study is to assess and analyze the spatio-temporal evolution of the SPI for 3-, 6-, 9-, 12- month timescales, during the period 1950-2015. For this purpose, we processed high resolution gridded daily precipitation datasets (0.25° x 0.25°), based on the E-OBS dataset from ECA&D. Mean SPI patterns and trends for the whole examined period, as well as successive 30-year periods, were assessed by using R-project. Moreover, the influence of the well-known atmospheric circulation index of the wider region of Europe, namely the North Atlantic Oscillation Index (NAOI), on the SPI over the Mediterranean was considered necessary to evaluate, because NAOI strongly modulates precipitation over Europe and the Mediterranean.

  10. Pulse oximetry-derived respiratory rate in general care floor patients.

    PubMed

    Addison, Paul S; Watson, James N; Mestek, Michael L; Ochs, James P; Uribe, Alberto A; Bergese, Sergio D

    2015-02-01

    Respiratory rate is recognized as a clinically important parameter for monitoring respiratory status on the general care floor (GCF). Currently, intermittent manual assessment of respiratory rate is the standard of care on the GCF. This technique has several clinically-relevant shortcomings, including the following: (1) it is not a continuous measurement, (2) it is prone to observer error, and (3) it is inefficient for the clinical staff. We report here on an algorithm designed to meet clinical needs by providing respiratory rate through a standard pulse oximeter. Finger photoplethysmograms were collected from a cohort of 63 GCF patients monitored during free breathing over a 25-min period. These were processed using a novel in-house algorithm based on continuous wavelet-transform technology within an infrastructure incorporating confidence-based averaging and logical decision-making processes. The computed oximeter respiratory rates (RRoxi) were compared to an end-tidal CO2 reference rate (RRETCO2). RRETCO2 ranged from a lowest recorded value of 4.7 breaths per minute (brpm) to a highest value of 32.0 brpm. The mean respiratory rate was 16.3 brpm with standard deviation of 4.7 brpm. Excellent agreement was found between RRoxi and RRETCO2, with a mean difference of -0.48 brpm and standard deviation of 1.77 brpm. These data demonstrate that our novel respiratory rate algorithm is a potentially viable method of monitoring respiratory rate in GCF patients. This technology provides the means to facilitate continuous monitoring of respiratory rate, coupled with arterial oxygen saturation and pulse rate, using a single non-invasive sensor in low acuity settings.

  11. [5-year course of dyslexia – Persistence, sex effects, performance in reading and spelling, and school-related success].

    PubMed

    Wyschkon, Anne; Schulz, Franziska; Gallit, Finja Sunnyi; Poltz, Nadine; Kohn, Juliane; Moraske, Svenja; Bondü, Rebecca; von Aster, Michael; Esser, Günter

    2018-03-01

    The study examines the 5-year course of children with dyslexia with regard to their sex. Furthermore, the study investigates the impact of dyslexia on the performance in reading and spelling skills and school-related success. A group of 995 6- to 16-year-olds were examined at the initial assessment. Part of the initial sample was then re-examined after 43 and 63 months. The diagnosis of dyslexia was based on the double discrepancy criterion using a standard deviation of 1.5. Though they had no intellectual deficits, the children showed a considerable discrepancy between their reading or writing abilities and (1) their nonverbal intelligence and (2) the mean of their grade norm. Nearly 70 % of those examined had a persisting diagnosis of dyslexia over a period of 63 months. The 5-year course was not influenced by sex. Despite average intelligence, the performance in writing and spelling of children suffering from dyslexia was one standard deviation below a control group without dyslexia with average intelligence and 0.5 standard deviations below a group of children suffering from intellectual deficits. Furthermore, the school-related success of the dyslexics was significantly lower than those of children with average intelligence. Dyslexics showed similar school-related success rates to children suffering from intellectual deficits. Dyslexia represents a considerable developmental risk. The adverse impact of dyslexia on school-related success supports the importance of early diagnostics and intervention. It also underlines the need for reliable and general accepted diagnostic criteria. It is important to define such criteria in light of the prevalence rates.

  12. Apparent diffusion coefficient histogram metrics correlate with survival in diffuse intrinsic pontine glioma: a report from the Pediatric Brain Tumor Consortium

    PubMed Central

    Poussaint, Tina Young; Vajapeyam, Sridhar; Ricci, Kelsey I.; Panigrahy, Ashok; Kocak, Mehmet; Kun, Larry E.; Boyett, James M.; Pollack, Ian F.; Fouladi, Maryam

    2016-01-01

    Background Diffuse intrinsic pontine glioma (DIPG) is associated with poor survival regardless of therapy. We used volumetric apparent diffusion coefficient (ADC) histogram metrics to determine associations with progression-free survival (PFS) and overall survival (OS) at baseline and after radiation therapy (RT). Methods Baseline and post-RT quantitative ADC histograms were generated from fluid-attenuated inversion recovery (FLAIR) images and enhancement regions of interest. Metrics assessed included number of peaks (ie, unimodal or bimodal), mean and median ADC, standard deviation, mode, skewness, and kurtosis. Results Based on FLAIR images, the majority of tumors had unimodal peaks with significantly shorter average survival. Pre-RT FLAIR mean, mode, and median values were significantly associated with decreased risk of progression; higher pre-RT ADC values had longer PFS on average. Pre-RT FLAIR skewness and standard deviation were significantly associated with increased risk of progression; higher pre-RT FLAIR skewness and standard deviation had shorter PFS. Nonenhancing tumors at baseline showed higher ADC FLAIR mean values, lower kurtosis, and higher PFS. For enhancing tumors at baseline, bimodal enhancement histograms had much worse PFS and OS than unimodal cases and significantly lower mean peak values. Enhancement in tumors only after RT led to significantly shorter PFS and OS than in patients with baseline or no baseline enhancement. Conclusions ADC histogram metrics in DIPG demonstrate significant correlations between diffusion metrics and survival, with lower diffusion values (increased cellularity), increased skewness, and enhancement associated with shorter survival, requiring future investigations in large DIPG clinical trials. PMID:26487690

  13. The biologic error in gestational length related to the use of the first day of last menstrual period as a proxy for the start of pregnancy.

    PubMed

    Nakling, Jakob; Buhaug, Harald; Backe, Bjorn

    2005-10-01

    In a large unselected population of normal spontaneous pregnancies, to estimate the biologic variation of the interval from the first day of the last menstrual period to start of pregnancy, and the biologic variation of gestational length to delivery; and to estimate the random error of routine ultrasound assessment of gestational age in mid-second trimester. Cohort study of 11,238 singleton pregnancies, with spontaneous onset of labour and reliable last menstrual period. The day of delivery was predicted with two independent methods: According to the rule of Nägele and based on ultrasound examination in gestational weeks 17-19. For both methods, the mean difference between observed and predicted day of delivery was calculated. The variances of the differences were combined to estimate the variances of the two partitions of pregnancy. The biologic variation of the time from last menstrual period to pregnancy start was estimated to 7.0 days (standard deviation), and the standard deviation of the time to spontaneous delivery was estimated to 12.4 days. The estimate of the standard deviation of the random error of ultrasound assessed foetal age was 5.2 days. Even when the last menstrual period is reliable, the biologic variation of the time from last menstrual period to the real start of pregnancy is substantial, and must be taken into account. Reliable information about the first day of the last menstrual period is not equivalent with reliable information about the start of pregnancy.

  14. The analysis of blood lead levels changeability over the 5-year observation in workers occupationally exposed to lead.

    PubMed

    Dobrakowski, Michał; Boroń, Marta; Kasperczyk, Sławomir; Kozłowska, Agnieszka; Kasperczyk, Aleksandra; Płachetka, Anna; Pawlas, Natalia

    2017-06-01

    The aim of the present study was to compare a group of workers with stable lead levels with a group of workers with fluctuating lead levels in terms of selected hematological, biochemical, and immunological parameters. The examined group included male workers occupationally exposed to lead. Blood lead (PbB) levels were measured every 3 months during the 5-year observation. Based on standard deviation of mean PbB levels, the examined population was divided into two groups: low level of fluctuation (L-SD) and high level of fluctuation (H-SD) groups. The mean and maximal PbB levels were significantly higher in the H-SD group than in the L-SD group by 9 and 22%, respectively. At the same time, the maximal level of zinc protoporphyrin (ZPP) and standard deviation of mean ZPP level were higher in the H-SD group by 29 and 55%, respectively. The maximal level of hemoglobin and white blood cell (WBC) count as well as standard deviation of the mean hemoglobin level and WBC count were higher in the H-SD group by 2, 8, 58, and 24%, respectively. The expression of nuclear factor kappa-B1 gene and telomerase reverse transcriptase gene was significantly greater in the H-SD group than in the L-SD group by 11 and 28%, respectively. Workers occupationally exposed to lead do not represent a homogenous population. Some present stable lead levels, whereas others have fluctuating lead levels. These fluctuations are related to secondary changes in ZPP and hemoglobin levels as well as WBC count.

  15. Study of the daily and seasonal atmospheric CH4 mixing ratio variability in a rural Spanish region using 222Rn tracer

    NASA Astrophysics Data System (ADS)

    Grossi, Claudia; Vogel, Felix R.; Curcoll, Roger; Àgueda, Alba; Vargas, Arturo; Rodó, Xavier; Morguí, Josep-Anton

    2018-04-01

    The ClimaDat station at Gredos (GIC3) has been continuously measuring atmospheric (dry air) mixing ratios of carbon dioxide (CO2) and methane (CH4), as well as meteorological parameters, since November 2012. In this study we investigate the atmospheric variability of CH4 mixing ratios between 2013 and 2015 at GIC3 with the help of co-located observations of 222Rn concentrations, modelled 222Rn fluxes and modelled planetary boundary layer heights (PBLHs). Both daily and seasonal changes in atmospheric CH4 can be better understood with the help of atmospheric concentrations of 222Rn (and the corresponding fluxes). On a daily timescale, the variation in the PBLH is the main driver for 222Rn and CH4 variability while, on monthly timescales, their atmospheric variability seems to depend on emission changes. To understand (changing) CH4 emissions, nocturnal fluxes of CH4 were estimated using two methods: the radon tracer method (RTM) and a method based on the EDGARv4.2 bottom-up emission inventory, both using FLEXPARTv9.0.2 footprints. The mean value of RTM-based methane fluxes (FR_CH4) is 0.11 mg CH4 m-2 h-1 with a standard deviation of 0.09 or 0.29 mg CH4 m-2 h-1 with a standard deviation of 0.23 mg CH4 m-2 h-1 when using a rescaled 222Rn map (FR_CH4_rescale). For our observational period, the mean value of methane fluxes based on the bottom-up inventory (FE_CH4) is 0.33 mg CH4 m-2 h-1 with a standard deviation of 0.08 mg CH4 m-2 h-1. Monthly CH4 fluxes based on RTM (both FR_CH4 and FR_CH4_rescale) show a seasonality which is not observed for monthly FE_CH4 fluxes. During January-May, RTM-based CH4 fluxes present mean values 25 % lower than during June-December. This seasonal increase in methane fluxes calculated by RTM for the GIC3 area appears to coincide with the arrival of transhumant livestock at GIC3 in the second half of the year.

  16. Feature selection for elderly faller classification based on wearable sensors.

    PubMed

    Howcroft, Jennifer; Kofman, Jonathan; Lemaire, Edward D

    2017-05-30

    Wearable sensors can be used to derive numerous gait pattern features for elderly fall risk and faller classification; however, an appropriate feature set is required to avoid high computational costs and the inclusion of irrelevant features. The objectives of this study were to identify and evaluate smaller feature sets for faller classification from large feature sets derived from wearable accelerometer and pressure-sensing insole gait data. A convenience sample of 100 older adults (75.5 ± 6.7 years; 76 non-fallers, 24 fallers based on 6 month retrospective fall occurrence) walked 7.62 m while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, left and right shanks. Feature selection was performed using correlation-based feature selection (CFS), fast correlation based filter (FCBF), and Relief-F algorithms. Faller classification was performed using multi-layer perceptron neural network, naïve Bayesian, and support vector machine classifiers, with 75:25 single stratified holdout and repeated random sampling. The best performing model was a support vector machine with 78% accuracy, 26% sensitivity, 95% specificity, 0.36 F1 score, and 0.31 MCC and one posterior pelvis accelerometer input feature (left acceleration standard deviation). The second best model achieved better sensitivity (44%) and used a support vector machine with 74% accuracy, 83% specificity, 0.44 F1 score, and 0.29 MCC. This model had ten input features: maximum, mean and standard deviation posterior acceleration; maximum, mean and standard deviation anterior acceleration; mean superior acceleration; and three impulse features. The best multi-sensor model sensitivity (56%) was achieved using posterior pelvis and both shank accelerometers and a naïve Bayesian classifier. The best single-sensor model sensitivity (41%) was achieved using the posterior pelvis accelerometer and a naïve Bayesian classifier. Feature selection provided models with smaller feature sets and improved faller classification compared to faller classification without feature selection. CFS and FCBF provided the best feature subset (one posterior pelvis accelerometer feature) for faller classification. However, better sensitivity was achieved by the second best model based on a Relief-F feature subset with three pressure-sensing insole features and seven head accelerometer features. Feature selection should be considered as an important step in faller classification using wearable sensors.

  17. SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

    Andrews, M; Abazeed, M; Woody, N

    Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

  18. A hospital-based birth weight analysis using computerized perinatal data base for a Chinese population.

    PubMed

    Fu, Jing; Yu, Mei

    2011-04-01

    We aimed to construct birth weight-for-gestational age nomograms based on a computerized perinatal data base in a hospital-based Chinese population. Retrospectively collected 28,052 singleton deliveries at Women and Children's Medical Center, Guangzhou, China. Standard curves of birth weight from 27 to 43 week's gestation were computed. The nomograms included the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles and standard deviations. 79.9% pregnant women delivered between 38, 39, and 40 gestational week, and the mean birth weights are 3160, 3282, and 3388 g, respectively. Preterm birth is 5.7%. In general, male birth weights are greater than females at each gestational week. The hospital-based Chinese population birth weight is lower than that of North American and Scandinavian population. A different standard birth weight is needed for different population. A hospital-based birth weight curve by gestational week is established, which can be a useful tool to estimate intrauterine fetal growth to define SGA or LGA fetuses.

  19. Developing safety performance functions incorporating reliability-based risk measures.

    PubMed

    Ibrahim, Shewkar El-Bassiouni; Sayed, Tarek

    2011-11-01

    Current geometric design guides provide deterministic standards where the safety margin of the design output is generally unknown and there is little knowledge of the safety implications of deviating from these standards. Several studies have advocated probabilistic geometric design where reliability analysis can be used to account for the uncertainty in the design parameters and to provide a risk measure of the implication of deviation from design standards. However, there is currently no link between measures of design reliability and the quantification of safety using collision frequency. The analysis presented in this paper attempts to bridge this gap by incorporating a reliability-based quantitative risk measure such as the probability of non-compliance (P(nc)) in safety performance functions (SPFs). Establishing this link will allow admitting reliability-based design into traditional benefit-cost analysis and should lead to a wider application of the reliability technique in road design. The present application is concerned with the design of horizontal curves, where the limit state function is defined in terms of the available (supply) and stopping (demand) sight distances. A comprehensive collision and geometric design database of two-lane rural highways is used to investigate the effect of the probability of non-compliance on safety. The reliability analysis was carried out using the First Order Reliability Method (FORM). Two Negative Binomial (NB) SPFs were developed to compare models with and without the reliability-based risk measures. It was found that models incorporating the P(nc) provided a better fit to the data set than the traditional (without risk) NB SPFs for total, injury and fatality (I+F) and property damage only (PDO) collisions. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. Reliability evaluation of high-performance, low-power FinFET standard cells based on mixed RBB/FBB technique

    NASA Astrophysics Data System (ADS)

    Wang, Tian; Cui, Xiaoxin; Ni, Yewen; Liao, Kai; Liao, Nan; Yu, Dunshan; Cui, Xiaole

    2017-04-01

    With shrinking transistor feature size, the fin-type field-effect transistor (FinFET) has become the most promising option in low-power circuit design due to its superior capability to suppress leakage. To support the VLSI digital system flow based on logic synthesis, we have designed an optimized high-performance low-power FinFET standard cell library based on employing the mixed FBB/RBB technique in the existing stacked structure of each cell. This paper presents the reliability evaluation of the optimized cells under process and operating environment variations based on Monte Carlo analysis. The variations are modelled with Gaussian distribution of the device parameters and 10000 sweeps are conducted in the simulation to obtain the statistical properties of the worst-case delay and input-dependent leakage for each cell. For comparison, a set of non-optimal cells that adopt the same topology without employing the mixed biasing technique is also generated. Experimental results show that the optimized cells achieve standard deviation reduction of 39.1% and 30.7% at most in worst-case delay and input-dependent leakage respectively while the normalized deviation shrinking in worst-case delay and input-dependent leakage can be up to 98.37% and 24.13%, respectively, which demonstrates that our optimized cells are less sensitive to variability and exhibit more reliability. Project supported by the National Natural Science Foundation of China (No. 61306040), the State Key Development Program for Basic Research of China (No. 2015CB057201), the Beijing Natural Science Foundation (No. 4152020), and Natural Science Foundation of Guangdong Province, China (No. 2015A030313147).

  1. Computerized Training in Critical Thinking (CT)2: A Skill-Based Program for Army Personnel

    DTIC Science & Technology

    2008-06-01

    15-minute break, and then completed the Skill 8 posttest . After completing the Skill 8 pretest , the experimental group completed the Skill training...including pretests , training modules, and posttests for each of eight CT skills. The pretests and training modules are highly interactive, include...usability evaluations .....................................26 Table 6: Pretest and posttest means and standard deviations by group, investigation 1

  2. Asymdystopia: The Threat of Small Biases in Evaluations of Education Interventions That Need to Be Powered to Detect Small Impacts. NCEE 2018-4002

    ERIC Educational Resources Information Center

    Deke, John; Wei, Thomas; Kautz, Tim

    2017-01-01

    Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…

  3. A Maximal Graded Exercise Test to Accurately Predict VO2max in 18-65-Year-Old Adults

    ERIC Educational Resources Information Center

    George, James D.; Bradshaw, Danielle I.; Hyde, Annette; Vehrs, Pat R.; Hager, Ronald L.; Yanowitz, Frank G.

    2007-01-01

    The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO sub 2 max) based on a maximal treadmill graded exercise test (GXT; George, 1996). Participants (N = 100), ages 18-65 years, reached a maximal level of exertion (mean plus or minus standard deviation [SD]; maximal heart rate [HR sub…

  4. Selecting laser eye protectors - a helping hand

    NASA Astrophysics Data System (ADS)

    Gappenach, Catherine; Krüger, Jörg; Offenhäuser, Friedrich; Pintaske, Sabine; Krauß, Hans-Joachim

    2015-10-01

    The European laser safety standards EN 207, EN 208, and EN 12254 each contain an annex B, which serves as a guidance for the selection of products. These annexes are informative only and are therefore not binding. As there are a variety of hazard scenarios, it is not recommended to change these annexes to a normative status, through which they would become mandatory. Instead, it is recommended to allow users to apply their own skills and know-how in selecting appropriate products, justifying where and why they deviate from the guidance in the standards. This paper explains the background on which the guidance for selection in the annexes of the standards is based and shows physically meaningful leeway.

  5. A general and fast scoring function for protein-ligand interactions: a simplified potential approach.

    PubMed

    Muegge, I; Martin, Y C

    1999-03-11

    A fast, simplified potential-based approach is presented that estimates the protein-ligand binding affinity based on the given 3D structure of a protein-ligand complex. This general, knowledge-based approach exploits structural information of known protein-ligand complexes extracted from the Brookhaven Protein Data Bank and converts it into distance-dependent Helmholtz free interaction energies of protein-ligand atom pairs (potentials of mean force, PMF). The definition of an appropriate reference state and the introduction of a correction term accounting for the volume taken by the ligand were found to be crucial for deriving the relevant interaction potentials that treat solvation and entropic contributions implicitly. A significant correlation between experimental binding affinities and computed score was found for sets of diverse protein-ligand complexes and for sets of different ligands bound to the same target. For 77 protein-ligand complexes taken from the Brookhaven Protein Data Bank, the calculated score showed a standard deviation from observed binding affinities of 1.8 log Ki units and an R2 value of 0.61. The best results were obtained for the subset of 16 serine protease complexes with a standard deviation of 1.0 log Ki unit and an R2 value of 0.86. A set of 33 inhibitors modeled into a crystal structure of HIV-1 protease yielded a standard deviation of 0.8 log Ki units from measured inhibition constants and an R2 value of 0.74. In contrast to empirical scoring functions that show similar or sometimes better correlation with observed binding affinities, our method does not involve deriving specific parameters that fit the observed binding affinities of protein-ligand complexes of a given training set. We compared the performance of the PMF score, Böhm's score (LUDI), and the SMOG score for eight different test sets of protein-ligand complexes. It was found that for the majority of test sets the PMF score performs best. The strength of the new approach presented here lies in its generality as no knowledge about measured binding affinities is needed to derive atomic interaction potentials. The use of the new scoring function in docking studies is outlined.

  6. Optimizing 4DCBCT projection allocation to respiratory bins.

    PubMed

    O'Brien, Ricky T; Kipritidis, John; Shieh, Chun-Chien; Keall, Paul J

    2014-10-07

    4D cone beam computed tomography (4DCBCT) is an emerging image guidance strategy used in radiotherapy where projections acquired during a scan are sorted into respiratory bins based on the respiratory phase or displacement. 4DCBCT reduces the motion blur caused by respiratory motion but increases streaking artefacts due to projection under-sampling as a result of the irregular nature of patient breathing and the binning algorithms used. For displacement binning the streak artefacts are so severe that displacement binning is rarely used clinically. The purpose of this study is to investigate if sharing projections between respiratory bins and adjusting the location of respiratory bins in an optimal manner can reduce or eliminate streak artefacts in 4DCBCT images. We introduce a mathematical optimization framework and a heuristic solution method, which we will call the optimized projection allocation algorithm, to determine where to position the respiratory bins and which projections to source from neighbouring respiratory bins. Five 4DCBCT datasets from three patients were used to reconstruct 4DCBCT images. Projections were sorted into respiratory bins using equispaced, equal density and optimized projection allocation. The standard deviation of the angular separation between projections was used to assess streaking and the consistency of the segmented volume of a fiducial gold marker was used to assess motion blur. The standard deviation of the angular separation between projections using displacement binning and optimized projection allocation was 30%-50% smaller than conventional phase based binning and 59%-76% smaller than conventional displacement binning indicating more uniformly spaced projections and fewer streaking artefacts. The standard deviation in the marker volume was 20%-90% smaller when using optimized projection allocation than using conventional phase based binning suggesting more uniform marker segmentation and less motion blur. Images reconstructed using displacement binning and the optimized projection allocation algorithm were clearer, contained visibly fewer streak artefacts and produced more consistent marker segmentation than those reconstructed with either equispaced or equal-density binning. The optimized projection allocation algorithm significantly improves image quality in 4DCBCT images and provides, for the first time, a method to consistently generate high quality displacement binned 4DCBCT images in clinical applications.

  7. A method to estimate statistical errors of properties derived from charge-density modelling

    PubMed Central

    Lecomte, Claude

    2018-01-01

    Estimating uncertainties of property values derived from a charge-density model is not straightforward. A methodology, based on calculation of sample standard deviations (SSD) of properties using randomly deviating charge-density models, is proposed with the MoPro software. The parameter shifts applied in the deviating models are generated in order to respect the variance–covariance matrix issued from the least-squares refinement. This ‘SSD methodology’ procedure can be applied to estimate uncertainties of any property related to a charge-density model obtained by least-squares fitting. This includes topological properties such as critical point coordinates, electron density, Laplacian and ellipticity at critical points and charges integrated over atomic basins. Errors on electrostatic potentials and interaction energies are also available now through this procedure. The method is exemplified with the charge density of compound (E)-5-phenylpent-1-enylboronic acid, refined at 0.45 Å resolution. The procedure is implemented in the freely available MoPro program dedicated to charge-density refinement and modelling. PMID:29724964

  8. Determining the Equation of State (EoS) Parameters for Ballistic Gelatin

    DTIC Science & Technology

    2015-09-01

    standard deviation. The specific heat measured at room temperature reported in (Winter 1975) is approximately 1.13 cal/g/°C (= 4.73 J /g/K). Fig. 4...Piatt 2010) Table 3 Specific heat capacity, average heat capacity, and standard deviation Temperature (°C) Cp [ J /(g·K)] Cp Cp Cp Average Cp...density amorphous ice and their implications on pressure induced amorphization. J Chem Physics. 2005;122:124710. Appleby-Thomas GJ, Hazell PJ

  9. Precision Geolocation of Active Electromagnetic Sensors Using Stationary Magnetic Sensors

    DTIC Science & Technology

    2009-09-01

    0.0003, 0.0003 ] m TiltMeter Mean Pitch: -1.71576990 and Roll: 0.92591697 LSQ Moment Pitch: 0.00576850 and Roll: -0.35543026 Run #5...Standard deviation of optimized solution: [ 0.0028, 0.0014, 0.0012 ] m TiltMeter Mean Pitch: -1.08757549 and Roll: 1.09065730 LSQ Moment...0.00, 0.00, -434.95 ] Standard deviation of optimized solution: [ 0.0051, 0.0031, 0.0035 ] m TiltMeter Mean Pitch: 0.05301905

  10. Coherent and Semiclassical States of a Charged Particle in a Constant Electric Field

    NASA Astrophysics Data System (ADS)

    Adorno, T. C.; Pereira, A. S.

    2018-05-01

    The method of integrals of motion is used to construct families of generalized coherent states of a nonrelativistic spinless charged particle in a constant electric field. Families of states, differing in the values of their standard deviations at the initial time, are obtained. Depending on the initial values of the standard deviations, and also on the electric field, it turns out to be possible to identify some families with semiclassical states.

  11. An estimator for the standard deviation of a natural frequency. I.

    NASA Technical Reports Server (NTRS)

    Schiff, A. J.; Bogdanoff, J. L.

    1971-01-01

    A brief review of mean-square approximate systems is given. The case in which the masses are deterministic is considered first in the derivation of an estimator for the upper bound of the standard deviation of a natural frequency. Two examples presented include a two-degree-of-freedom system and a case in which the disorder in the springs is perfectly correlated. For purposes of comparison, a Monte Carlo simulation was done on a digital computer.

  12. Statistical characteristics of cloud variability. Part 1: Retrieved cloud liquid water path at three ARM sites

    NASA Astrophysics Data System (ADS)

    Huang, Dong; Campos, Edwin; Liu, Yangang

    2014-09-01

    Statistical characteristics of cloud variability are examined for their dependence on averaging scales and best representation of probability density function with the decade-long retrieval products of cloud liquid water path (LWP) from the tropical western Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy's Atmospheric Radiation Measurement Program. The statistical moments of LWP show some seasonal variation at the SGP and NSA sites but not much at the TWP site. It is found that the standard deviation, relative dispersion (the ratio of the standard deviation to the mean), and skewness all quickly increase with the averaging window size when the window size is small and become more or less flat when the window size exceeds 12 h. On average, the cloud LWP at the TWP site has the largest values of standard deviation, relative dispersion, and skewness, whereas the NSA site exhibits the least. Correlation analysis shows that there is a positive correlation between the mean LWP and the standard deviation. The skewness is found to be closely related to the relative dispersion with a correlation coefficient of 0.6. The comparison further shows that the lognormal, Weibull, and gamma distributions reasonably explain the observed relationship between skewness and relative dispersion over a wide range of scales.

  13. Statistical characteristics of cloud variability. Part 1: Retrieved cloud liquid water path at three ARM sites: Observed cloud variability at ARM sites

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

    Huang, Dong; Campos, Edwin; Liu, Yangang

    2014-09-17

    Statistical characteristics of cloud variability are examined for their dependence on averaging scales and best representation of probability density function with the decade-long retrieval products of cloud liquid water path (LWP) from the tropical western Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy’s Atmospheric Radiation Measurement Program. The statistical moments of LWP show some seasonal variation at the SGP and NSA sites but not much at the TWP site. It is found that the standard deviation, relative dispersion (the ratio of the standard deviation to the mean), and skewness allmore » quickly increase with the averaging window size when the window size is small and become more or less flat when the window size exceeds 12 h. On average, the cloud LWP at the TWP site has the largest values of standard deviation, relative dispersion, and skewness, whereas the NSA site exhibits the least. Correlation analysis shows that there is a positive correlation between the mean LWP and the standard deviation. The skewness is found to be closely related to the relative dispersion with a correlation coefficient of 0.6. The comparison further shows that the log normal, Weibull, and gamma distributions reasonably explain the observed relationship between skewness and relative dispersion over a wide range of scales.« less

  14. Measurements of leakage from Lake Michigan through three control structures near Chicago, Illinois, April-October 1993

    USGS Publications Warehouse

    Oberg, K.A.; Schmidt, A.R.

    1994-01-01

    A total of 213 measurements of leakage were made at three control structures near Chicago, Ill.--the Chicago River Controlling Works (CRCW), Thomas J. O'Brien Lock and Dam (O'Brien), and Wilmette Pumping Station (Wilmette)--using acoustic Doppler current profilers (ADCP's) and dye-dilution techniques. The CRCW consists of the Chicago Lock and two sets of sluice gates connected by a network of harbor walls. Leakage measurements were made in April, May, July, September, and October 1993 using an ADCP. The mean and standard deviation of leakage measured by the ADCP for the Chicago Lock river gate were 133 and 39 cubic feet per second, respectively. The mean and standard deviation of the leakage measurements at CRCW were 204 and 70 cubic feet per second, respectively. The mean and standard deviation of leakage measurements at O'Brien on September 17, 1993, were 21 and 10 cubic feet per second, respectively. The mean and standard deviation leakage measured at Wilmette using the ADCP were 59 and 8 cubic feet per second, respectively, in April 1993. After the pump bays at Wilmette were sealed in July 1993, the leakage dropped to less than 15 cubic feet per second in September 1993. Discharge estimated by dye-dilution at the Chicago Lock on July 15, 1993, was 160 cubic feet per second, or within 8 percent of the discharge measured with the ADCP. (USGS)

  15. Reductions in the variations of respiration signals for respiratory-gated radiotherapy when using the video-coaching respiration guiding system

    NASA Astrophysics Data System (ADS)

    Lee, Hyun Jeong; Yea, Ji Woon; Oh, Se An

    2015-07-01

    Respiratory-gated radiation therapy (RGRT) has been used to minimize the dose to normal tissue in lung-cancer radiotherapy. The present research aims to improve the regularity of respiration in RGRT by using a video-coached respiration guiding system. In the study, 16 patients with lung cancer were evaluated. The respiration signals of the patients were measured by using a realtime position management (RPM) respiratory gating system (Varian, USA), and the patients were trained using the video-coaching respiration guiding system. The patients performed free breathing and guided breathing, and the respiratory cycles were acquired for ~5 min. Then, Microsoft Excel 2010 software was used to calculate the mean and the standard deviation for each phase. The standard deviation was computed in order to analyze the improvement in the respiratory regularity with respect to the period and the displacement. The standard deviation of the guided breathing decreased to 48.8% in the inhale peak and 24.2% in the exhale peak compared with the values for the free breathing of patient 6. The standard deviation of the respiratory cycle was found to be decreased when using the respiratory guiding system. The respiratory regularity was significantly improved when using the video-coaching respiration guiding system. Therefore, the system is useful for improving the accuracy and the efficiency of RGRT.

  16. [Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm].

    PubMed

    Liang, Xue; Ji, Hai-yan; Wang, Peng-xin; Rao, Zhen-hong; Shen, Bing-hui

    2010-01-01

    Preprocess method of multiplicative scatter correction (MSC) was used to reject noises in the original spectra produced by the environmental physical factor effectively, then the principal components of near-infrared spectroscopy were calculated by nonlinear iterative partial least squares (NIPALS) before building the back propagation artificial neural networks method (BP-ANN), and the numbers of principal components were calculated by the method of cross validation. The calculated principal components were used as the inputs of the artificial neural networks model, and the artificial neural networks model was used to find the relation between chlorophyll in winter wheat and reflective spectrum, which can predict the content of chlorophyll in winter wheat. The correlation coefficient (r) of calibration set was 0.9604, while the standard deviation (SD) and relative standard deviation (RSD) was 0.187 and 5.18% respectively. The correlation coefficient (r) of predicted set was 0.9600, and the standard deviation (SD) and relative standard deviation (RSD) was 0.145 and 4.21% respectively. It means that the MSC-ANN algorithm can reject noises in the original spectra produced by the environmental physical factor effectively and set up an exact model to predict the contents of chlorophyll in living leaves veraciously to replace the classical method and meet the needs of fast analysis of agricultural products.

  17. Professionalism in medical students at a private medical college in Karachi, Pakistan.

    PubMed

    Sobani, Zain-ul-abedeen; Mohyuddin, Muhammad Masaud; Farooq, Fahd; Qaiser, Kanza Noor; Gani, Faiz; Bham, Nida Shahab; Raheem, Ahmed; Mehraj, Vikram; Saeed, Syed Abdul; Sharif, Hasanat; Sheerani, Mughis; Zuberi, Rukhsana Wamiq; Beg, Mohamamd Asim

    2013-07-01

    To determine levels of professionalism in undergraduate medical students at a private medical college and assess how changes emerge during their training. The study was conducted at Aga Khan University, a tertiary care teaching hospital, during November and December 2011. Freshmen, Year 3 and Year 5 students were requested to fill out a questionnaire. It was designed to assess the participants' levels of professionalism and how they perceived the professional environment around them by incorporating previously described scales. The questionnaire was re-validated on a random sample of practising clinicians at the same hospital. SPSS 17 was used for statistical analysis. The study sample comprised 204 participants. The mean score for level of individual professionalism was 7.72+/-3.43. Only 13 (6.4%) students had a score one standard deviation above the faculty mean. About 24 (11.8%) were one standard deviation and 35 (17.2%) were 2 standard deviations below the faculty mean. The remaining 130 (63.7%) were >2 standard deviations below the faculty mean. Considering the level of education, the mean score for level of professionalism was 8.00+/-3.39 for freshmen, 6.85+/-3.41 for year 3 students, and 8.40+/-3.34 for year 5 students. The currently employed teaching practices inculcating the values of professionalism in medical students are serving as a buffer to maintain the pre-training levels of professionalism from declining.

  18. How to model moon signals using 2-dimensional Gaussian function: Classroom activity for measuring nighttime cloud cover

    NASA Astrophysics Data System (ADS)

    Gacal, G. F. B.; Lagrosas, N.

    2016-12-01

    Nowadays, cameras are commonly used by students. In this study, we use this instrument to look at moon signals and relate these signals to Gaussian functions. To implement this as a classroom activity, students need computers, computer software to visualize signals, and moon images. A normalized Gaussian function is often used to represent probability density functions of normal distribution. It is described by its mean m and standard deviation s. The smaller standard deviation implies less spread from the mean. For the 2-dimensional Gaussian function, the mean can be described by coordinates (x0, y0), while the standard deviations can be described by sx and sy. In modelling moon signals obtained from sky-cameras, the position of the mean (x0, y0) is solved by locating the coordinates of the maximum signal of the moon. The two standard deviations are the mean square weighted deviation based from the sum of total pixel values of all rows/columns. If visualized in three dimensions, the 2D Gaussian function appears as a 3D bell surface (Fig. 1a). This shape is similar to the pixel value distribution of moon signals as captured by a sky-camera. An example of this is illustrated in Fig 1b taken around 22:20 (local time) of January 31, 2015. The local time is 8 hours ahead of coordinated universal time (UTC). This image is produced by a commercial camera (Canon Powershot A2300) with 1s exposure time, f-stop of f/2.8, and 5mm focal length. One has to chose a camera with high sensitivity when operated at nighttime to effectively detect these signals. Fig. 1b is obtained by converting the red-green-blue (RGB) photo to grayscale values. The grayscale values are then converted to a double data type matrix. The last conversion process is implemented for the purpose of having the same scales for both Gaussian model and pixel distribution of raw signals. Subtraction of the Gaussian model from the raw data produces a moonless image as shown in Fig. 1c. This moonless image can be used for quantifying cloud cover as captured by ordinary cameras (Gacal et al, 2016). Cloud cover can be defined as the ratio of number of pixels whose values exceeds 0.07 and the total number of pixels. In this particular image, cloud cover value is 0.67.

  19. RE-PERG, a new procedure for electrophysiologic diagnosis of glaucoma that may improve PERG specificity.

    PubMed

    Mavilio, Alberto; Sisto, Dario; Ferreri, Paolo; Cardascia, Nicola; Alessio, Giovanni

    2017-01-01

    A significant variability of the second harmonic (2ndH) phase of steady-state pattern electroretinogram (SS-PERG) in intrasession retest has been recently described in glaucoma patients (GP), which has not been found in healthy subjects. To evaluate the reliability of phase variability in retest (a procedure called RE-PERG or REPERG) in the presence of cataract, which is known to affect standard PERG, we tested this procedure in GP, normal controls (NC), and cataract patients (CP). The procedure was performed on 50 GP, 35 NC, and 27 CP. All subjects were examined with RE-PERG and SS-PERG and also with spectral domain optical coherence tomography and standard automated perimetry. Standard deviation of phase and amplitude value of 2ndH were correlated by means of one-way analysis of variance and Pearson correlation, with the mean deviation and pattern standard deviation assessed by standard automated perimetry and retinal nerve fiber layer and the ganglion cell complex thickness assessed by spectral domain optical coherence tomography. Receiver operating characteristics were calculated in cohort populations with and without cataract. Standard deviation of phase of 2ndH was significantly higher in GP with respect to NC ( P <0.001) and CP ( P <0.001), and it correlated with retinal nerve fiber layer ( r =-0.5, P <0.001) and ganglion cell complex ( r =-0.6, P <0.001) defects in GP. Receiver operating characteristic evaluation showed higher specificity of RE-PERG (86.4%; area under the curve 0.93) with respect to SS-PERG (54.5%; area under the curve 0.68) in CP. RE-PERG may improve the specificity of SS-PERG in clinical practice in the discrimination of GP.

  20. Inter-Labeler and Intra-Labeler Variability of Condition Severity Classification Models Using Active and Passive Learning Methods

    PubMed Central

    Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

    2018-01-01

    Background and Objectives Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers’ learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. Methods We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven labelers. We also compared the performance of the passive and active learning models when using the consensus label. Results The AL methods produced, for the models induced from each labeler, smoother Intra-labeler learning curves during the training phase, compared to the models produced when using the passive learning method. The mean standard deviation of the learning curves of the three AL methods over all labelers (mean: 0.0379; range: [0.0182 to 0.0496]), was significantly lower (p = 0.049) than the Intra-labeler standard deviation when using the passive learning method (mean: 0.0484; range: [0.0275 to 0.0724). Using the AL methods resulted in a lower mean Inter-labeler AUC standard deviation among the AUC values of the labelers’ different models during the training phase, compared to the variance of the induced models’ AUC values when using passive learning. The Inter-labeler AUC standard deviation, using the passive learning method (0.039), was almost twice as high as the Inter-labeler standard deviation using our two new AL methods (0.02 and 0.019, respectively). The SVM-Margin AL method resulted in an Inter-labeler standard deviation (0.029) that was higher by almost 50% than that of our two AL methods. The difference in the inter-labeler standard deviation between the passive learning method and the SVM-Margin learning method was significant (p = 0.042). The difference between the SVM-Margin and Exploitation method was insignificant (p = 0.29), as was the difference between the Combination_XA and Exploitation methods (p = 0.67). Finally, using the consensus label led to a learning curve that had a higher mean intra-labeler variance, but resulted eventually in an AUC that was at least as high as the AUC achieved using the gold standard label and that was always higher than the expected mean AUC of a randomly selected labeler, regardless of the choice of learning method (including a passive learning method). Using a paired t-test, the difference between the intra-labeler AUC standard deviation when using the consensus label, versus that value when using the other two labeling strategies, was significant only when using the passive learning method (p = 0.014), but not when using any of the three AL methods. Conclusions The use of AL methods, (a) reduces intra-labeler variability in the performance of the induced models during the training phase, and thus reduces the risk of halting the process at a local minimum that is significantly different in performance from the rest of the learned models; and (b) reduces Inter-labeler performance variance, and thus reduces the dependence on the use of a particular labeler. In addition, the use of a consensus label, agreed upon by a rather uneven group of labelers, might be at least as good as using the gold standard labeler, who might not be available, and certainly better than randomly selecting one of the group’s individual labelers. Finally, using the AL methods when provided by the consensus label reduced the intra-labeler AUC variance during the learning phase, compared to using passive learning. PMID:28456512

  1. Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

    PubMed

    Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

    2017-09-01

    Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers' learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven labelers. We also compared the performance of the passive and active learning models when using the consensus label. The AL methods: produced, for the models induced from each labeler, smoother Intra-labeler learning curves during the training phase, compared to the models produced when using the passive learning method. The mean standard deviation of the learning curves of the three AL methods over all labelers (mean: 0.0379; range: [0.0182 to 0.0496]), was significantly lower (p=0.049) than the Intra-labeler standard deviation when using the passive learning method (mean: 0.0484; range: [0.0275-0.0724). Using the AL methods resulted in a lower mean Inter-labeler AUC standard deviation among the AUC values of the labelers' different models during the training phase, compared to the variance of the induced models' AUC values when using passive learning. The Inter-labeler AUC standard deviation, using the passive learning method (0.039), was almost twice as high as the Inter-labeler standard deviation using our two new AL methods (0.02 and 0.019, respectively). The SVM-Margin AL method resulted in an Inter-labeler standard deviation (0.029) that was higher by almost 50% than that of our two AL methods The difference in the inter-labeler standard deviation between the passive learning method and the SVM-Margin learning method was significant (p=0.042). The difference between the SVM-Margin and Exploitation method was insignificant (p=0.29), as was the difference between the Combination_XA and Exploitation methods (p=0.67). Finally, using the consensus label led to a learning curve that had a higher mean intra-labeler variance, but resulted eventually in an AUC that was at least as high as the AUC achieved using the gold standard label and that was always higher than the expected mean AUC of a randomly selected labeler, regardless of the choice of learning method (including a passive learning method). Using a paired t-test, the difference between the intra-labeler AUC standard deviation when using the consensus label, versus that value when using the other two labeling strategies, was significant only when using the passive learning method (p=0.014), but not when using any of the three AL methods. The use of AL methods, (a) reduces intra-labeler variability in the performance of the induced models during the training phase, and thus reduces the risk of halting the process at a local minimum that is significantly different in performance from the rest of the learned models; and (b) reduces Inter-labeler performance variance, and thus reduces the dependence on the use of a particular labeler. In addition, the use of a consensus label, agreed upon by a rather uneven group of labelers, might be at least as good as using the gold standard labeler, who might not be available, and certainly better than randomly selecting one of the group's individual labelers. Finally, using the AL methods: when provided by the consensus label reduced the intra-labeler AUC variance during the learning phase, compared to using passive learning. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. SU-E-T-469: A Practical Approach for the Determination of Small Field Output Factors Using Published Monte Carlo Derived Correction Factors

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

    Calderon, E; Siergiej, D

    2014-06-01

    Purpose: Output factor determination for small fields (less than 20 mm) presents significant challenges due to ion chamber volume averaging and diode over-response. Measured output factor values between detectors are known to have large deviations as field sizes are decreased. No set standard to resolve this difference in measurement exists. We observed differences between measured output factors of up to 14% using two different detectors. Published Monte Carlo derived correction factors were used to address this challenge and decrease the output factor deviation between detectors. Methods: Output factors for Elekta's linac-based stereotactic cone system were measured using the EDGE detectormore » (Sun Nuclear) and the A16 ion chamber (Standard Imaging). Measurements conditions were 100 cm SSD (source to surface distance) and 1.5 cm depth. Output factors were first normalized to a 10.4 cm × 10.4 cm field size using a daisy-chaining technique to minimize the dependence of field size on detector response. An equation expressing the relation between published Monte Carlo correction factors as a function of field size for each detector was derived. The measured output factors were then multiplied by the calculated correction factors. EBT3 gafchromic film dosimetry was used to independently validate the corrected output factors. Results: Without correction, the deviation in output factors between the EDGE and A16 detectors ranged from 1.3 to 14.8%, depending on cone size. After applying the calculated correction factors, this deviation fell to 0 to 3.4%. Output factors determined with film agree within 3.5% of the corrected output factors. Conclusion: We present a practical approach to applying published Monte Carlo derived correction factors to measured small field output factors for the EDGE and A16 detectors. Using this method, we were able to decrease the percent deviation between both detectors from 14.8% to 3.4% agreement.« less

  3. On the Distribution of Protein Refractive Index Increments

    PubMed Central

    Zhao, Huaying; Brown, Patrick H.; Schuck, Peter

    2011-01-01

    The protein refractive index increment, dn/dc, is an important parameter underlying the concentration determination and the biophysical characterization of proteins and protein complexes in many techniques. In this study, we examine the widely used assumption that most proteins have dn/dc values in a very narrow range, and reappraise the prediction of dn/dc of unmodified proteins based on their amino acid composition. Applying this approach in large scale to the entire set of known and predicted human proteins, we obtain, for the first time, to our knowledge, an estimate of the full distribution of protein dn/dc values. The distribution is close to Gaussian with a mean of 0.190 ml/g (for unmodified proteins at 589 nm) and a standard deviation of 0.003 ml/g. However, small proteins <10 kDa exhibit a larger spread, and almost 3000 proteins have values deviating by more than two standard deviations from the mean. Due to the widespread availability of protein sequences and the potential for outliers, the compositional prediction should be convenient and provide greater accuracy than an average consensus value for all proteins. We discuss how this approach should be particularly valuable for certain protein classes where a high dn/dc is coincidental to structural features, or may be functionally relevant such as in proteins of the eye. PMID:21539801

  4. On the distribution of protein refractive index increments.

    PubMed

    Zhao, Huaying; Brown, Patrick H; Schuck, Peter

    2011-05-04

    The protein refractive index increment, dn/dc, is an important parameter underlying the concentration determination and the biophysical characterization of proteins and protein complexes in many techniques. In this study, we examine the widely used assumption that most proteins have dn/dc values in a very narrow range, and reappraise the prediction of dn/dc of unmodified proteins based on their amino acid composition. Applying this approach in large scale to the entire set of known and predicted human proteins, we obtain, for the first time, to our knowledge, an estimate of the full distribution of protein dn/dc values. The distribution is close to Gaussian with a mean of 0.190 ml/g (for unmodified proteins at 589 nm) and a standard deviation of 0.003 ml/g. However, small proteins <10 kDa exhibit a larger spread, and almost 3000 proteins have values deviating by more than two standard deviations from the mean. Due to the widespread availability of protein sequences and the potential for outliers, the compositional prediction should be convenient and provide greater accuracy than an average consensus value for all proteins. We discuss how this approach should be particularly valuable for certain protein classes where a high dn/dc is coincidental to structural features, or may be functionally relevant such as in proteins of the eye. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  5. Associations between Changes in City and Address Specific Temperature and QT Interval - The VA Normative Aging Study

    PubMed Central

    Mehta, Amar J.; Kloog, Itai; Zanobetti, Antonella; Coull, Brent A.; Sparrow, David; Vokonas, Pantel; Schwartz, Joel

    2014-01-01

    Background The underlying mechanisms of the association between ambient temperature and cardiovascular morbidity and mortality are not well understood, particularly for daily temperature variability. We evaluated if daily mean temperature and standard deviation of temperature was associated with heart rate-corrected QT interval (QTc) duration, a marker of ventricular repolarization in a prospective cohort of older men. Methods This longitudinal analysis included 487 older men participating in the VA Normative Aging Study with up to three visits between 2000–2008 (n = 743). We analyzed associations between QTc and moving averages (1–7, 14, 21, and 28 days) of the 24-hour mean and standard deviation of temperature as measured from a local weather monitor, and the 24-hour mean temperature estimated from a spatiotemporal prediction model, in time-varying linear mixed-effect regression. Effect modification by season, diabetes, coronary heart disease, obesity, and age was also evaluated. Results Higher mean temperature as measured from the local monitor, and estimated from the prediction model, was associated with longer QTc at moving averages of 21 and 28 days. Increased 24-hr standard deviation of temperature was associated with longer QTc at moving averages from 4 and up to 28 days; a 1.9°C interquartile range increase in 4-day moving average standard deviation of temperature was associated with a 2.8 msec (95%CI: 0.4, 5.2) longer QTc. Associations between 24-hr standard deviation of temperature and QTc were stronger in colder months, and in participants with diabetes and coronary heart disease. Conclusion/Significance In this sample of older men, elevated mean temperature was associated with longer QTc, and increased variability of temperature was associated with longer QTc, particularly during colder months and among individuals with diabetes and coronary heart disease. These findings may offer insight of an important underlying mechanism of temperature-related cardiovascular morbidity and mortality in an older population. PMID:25238150

  6. Updated U.S. population standard for the Veterans RAND 12-item Health Survey (VR-12).

    PubMed

    Selim, Alfredo J; Rogers, William; Fleishman, John A; Qian, Shirley X; Fincke, Benjamin G; Rothendler, James A; Kazis, Lewis E

    2009-02-01

    The purpose of this project was to develop an updated U.S. population standard for the Veterans RAND 12-item Health Survey (VR-12). We used a well-defined and nationally representative sample of the U.S. population from 52,425 responses to the Medical Expenditure Panel Survey (MEPS) collected between 2000 and 2002. We applied modified regression estimates to update the non-proprietary 1990 scoring algorithms. We applied the updated standard to the Medicare Health Outcomes Survey (HOS) to compute the VR-12 physical (PCS((MEPS standard))) and mental (MCS((MEPS standard))) component summaries based on the MEPS. We compared these scores to PCS and MCS based on the 1990 U.S. population standard. Using the updated U.S. population standard, the average VR-12 PCS((MEPS standard)) and MCS((MEPS standard)) scores in the Medicare HOS were 39.82 (standard deviation [SD] = 12.2) and 50.08 (SD = 11.4), respectively. For the same Medicare HOS, the average PCS and MCS scores based on the 1990 standard were 1.40 points higher and 0.99 points lower in comparison to VR-12 PCS and MCS, respectively. Changes in the U.S. population between 1990 and today make the old standard obsolete for the VR-12, so the updated standard developed here is widely available to serve as such a contemporary standard for future applications for health-related quality of life (HRQoL) assessments.

  7. Public healthcare interests require strict competition enforcement.

    PubMed

    Loozen, Edith M H

    2015-07-01

    Several countries have introduced competition in their health systems in order to maintain the supply of high quality health care in a cost-effective manner. The introduction of competition triggers competition enforcement. Since healthcare is characterized by specific market failures, many favor healthcare-specific competition enforcement in order not only to account for the competition interest, but also for the healthcare interests. The question is whether healthcare systems based on competition can succeed when competition enforcement deviates from standard practice. This paper analyzes whether healthcare-specific competition enforcement is theoretically sound and practically effective. This is exemplified by the Dutch system that is based on regulated competition and thus crucially depends on getting competition enforcement right. Governments are responsible for correcting market failures. Markets are responsible for maximizing the public healthcare interests. By securing sufficient competitive pressure, competition enforcement makes sure they do. When interpreted according to welfare-economics, competition law takes into account both costs and benefits specific market behavior may have for healthcare. Competition agencies and judiciary are not legitimized to deviate from standard evidentiary requirements. Dutch case law shows that healthcare-specific enforcement favors the healthcare undertakings concerned, but to the detriment of public health care. Healthcare-specific competition enforcement is conceptually flawed and counterproductive. In order for healthcare systems based on competition to succeed, competition enforcement should be strict. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  8. Robust regression for large-scale neuroimaging studies.

    PubMed

    Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand

    2015-05-01

    Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Model and parametric uncertainty in source-based kinematic models of earthquake ground motion

    USGS Publications Warehouse

    Hartzell, Stephen; Frankel, Arthur; Liu, Pengcheng; Zeng, Yuehua; Rahman, Shariftur

    2011-01-01

    Four independent ground-motion simulation codes are used to model the strong ground motion for three earthquakes: 1994 Mw 6.7 Northridge, 1989 Mw 6.9 Loma Prieta, and 1999 Mw 7.5 Izmit. These 12 sets of synthetics are used to make estimates of the variability in ground-motion predictions. In addition, ground-motion predictions over a grid of sites are used to estimate parametric uncertainty for changes in rupture velocity. We find that the combined model uncertainty and random variability of the simulations is in the same range as the variability of regional empirical ground-motion data sets. The majority of the standard deviations lie between 0.5 and 0.7 natural-log units for response spectra and 0.5 and 0.8 for Fourier spectra. The estimate of model epistemic uncertainty, based on the different model predictions, lies between 0.2 and 0.4, which is about one-half of the estimates for the standard deviation of the combined model uncertainty and random variability. Parametric uncertainty, based on variation of just the average rupture velocity, is shown to be consistent in amplitude with previous estimates, showing percentage changes in ground motion from 50% to 300% when rupture velocity changes from 2.5 to 2.9 km/s. In addition, there is some evidence that mean biases can be reduced by averaging ground-motion estimates from different methods.

  10. Inverse associations between cord vitamin D and attention deficit hyperactivity disorder symptoms: A child cohort study.

    PubMed

    Mossin, Mats H; Aaby, Jens B; Dalgård, Christine; Lykkedegn, Sine; Christesen, Henrik T; Bilenberg, Niels

    2017-07-01

    To examine the association between cord 25-hydroxyvitamin D 2+3 (25(OH)D) and attention deficit hyperactivity disorder symptoms in toddlers, using Child Behaviour Checklist for ages 1.5-5. In a population-based birth cohort, a Child Behaviour Checklist for ages 1.5-5 questionnaire was returned from parents of 1233 infants with mean age 2.7 (standard deviation 0.6) years. Adjusted associations between cord 25(OH)D and Child Behaviour Checklist-based attention deficit hyperactivity disorder problems were analysed by multiple regression. Results The median cord 25(OH)D was 44.1 (range: 1.5-127.1) nmol/L. Mean attention deficit hyperactivity disorder problem score was 2.7 (standard deviation 2.1). In adjusted analyses, cord 25(OH)D levels >25 nmol/L and >30 nmol/L were associated with lower attention deficit hyperactivity disorder scores compared to levels ⩽25 nmol/L ( p = 0.035) and ⩽30 nmol/L ( p = 0.043), respectively. The adjusted odds of scoring above the 90th percentile on the Child Behaviour Checklist-based attention deficit hyperactivity disorder problem scale decreased by 11% per 10 nmol/L increase in cord 25(OH)D. An inverse association between cord 25(OH)D and attention deficit hyperactivity disorder symptoms in toddlers was found, suggesting a protective effect of prenatal vitamin D.

  11. A Collaborative Evaluation of LC-MS/MS Based Methods for BMAA Analysis: Soluble Bound BMAA Found to Be an Important Fraction

    PubMed Central

    Faassen, Elisabeth J.; Antoniou, Maria G.; Beekman-Lukassen, Wendy; Blahova, Lucie; Chernova, Ekaterina; Christophoridis, Christophoros; Combes, Audrey; Edwards, Christine; Fastner, Jutta; Harmsen, Joop; Hiskia, Anastasia; Ilag, Leopold L.; Kaloudis, Triantafyllos; Lopicic, Srdjan; Lürling, Miquel; Mazur-Marzec, Hanna; Meriluoto, Jussi; Porojan, Cristina; Viner-Mozzini, Yehudit; Zguna, Nadezda

    2016-01-01

    Exposure to β-N-methylamino-l-alanine (BMAA) might be linked to the incidence of amyotrophic lateral sclerosis, Alzheimer’s disease and Parkinson’s disease. Analytical chemistry plays a crucial role in determining human BMAA exposure and the associated health risk, but the performance of various analytical methods currently employed is rarely compared. A CYANOCOST initiated workshop was organized aimed at training scientists in BMAA analysis, creating mutual understanding and paving the way towards interlaboratory comparison exercises. During this workshop, we tested different methods (extraction followed by derivatization and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis, or directly followed by LC-MS/MS analysis) for trueness and intermediate precision. We adapted three workup methods for the underivatized analysis of animal, brain and cyanobacterial samples. Based on recovery of the internal standard D3BMAA, the underivatized methods were accurate (mean recovery 80%) and precise (mean relative standard deviation 10%), except for the cyanobacterium Leptolyngbya. However, total BMAA concentrations in the positive controls (cycad seeds) showed higher variation (relative standard deviation 21%–32%), implying that D3BMAA was not a good indicator for the release of BMAA from bound forms. Significant losses occurred during workup for the derivatized method, resulting in low recovery (<10%). Most BMAA was found in a trichloroacetic acid soluble, bound form and we recommend including this fraction during analysis. PMID:26938542

  12. Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle.

    PubMed

    Rönnegård, L; Felleki, M; Fikse, W F; Mulder, H A; Strandberg, E

    2013-04-01

    Trait uniformity, or micro-environmental sensitivity, may be studied through individual differences in residual variance. These differences appear to be heritable, and the need exists, therefore, to fit models to predict breeding values explaining differences in residual variance. The aim of this paper is to estimate breeding values for micro-environmental sensitivity (vEBV) in milk yield and somatic cell score, and their associated variance components, on a large dairy cattle data set having more than 1.6 million records. Estimation of variance components, ordinary breeding values, and vEBV was performed using standard variance component estimation software (ASReml), applying the methodology for double hierarchical generalized linear models. Estimation using ASReml took less than 7 d on a Linux server. The genetic standard deviations for residual variance were 0.21 and 0.22 for somatic cell score and milk yield, respectively, which indicate moderate genetic variance for residual variance and imply that a standard deviation change in vEBV for one of these traits would alter the residual variance by 20%. This study shows that estimation of variance components, estimated breeding values and vEBV, is feasible for large dairy cattle data sets using standard variance component estimation software. The possibility to select for uniformity in Holstein dairy cattle based on these estimates is discussed. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  13. Validation of the RisingSun RS-651 Blood Pressure Monitor Based on Auscultation in Adults According to the ANSI/AAMI/ISO 81060-2:2013 Standard.

    PubMed

    She, Jin; Guan, Xizhou; Liu, Yanyong; Xiang, Haiyan

    2016-12-01

    This study validated the RisingSun RS-651 blood pressure (BP) monitor based on auscultation in adults according to the American National Standards Institute/Association for the Advancement of Medical Instrumentation/International Organization for Standardization (ANSI/AAMI/ISO) 81060-2:2013 standard. The RS-651 device was evaluated in a study of 97 participants. The same arm simultaneous method, as defined in the ANSI/AAMI/ISO standard, was used. The mean differences±standard deviation for criterion 1 were 0.8±2.3 mm Hg for systolic BP (SBP) and -0.1±2.9 mm Hg for diastolic BP (DBP). Analysis for criterion 2 resulted in values of 0.8±1.5 mm Hg for SBP and -0.1±2.1 mm Hg for DBP. All of the data fulfilled the ANSI/AAMI/ISO 81060-2:2013 standard requirements to pass the validation. The RisingSun RS-651 device can be recommended for both clinical and self/home use in adults according to the ANSI/AAMI/ISO 81060-2:2013 standard. © 2016 The Authors. The Journal of Clinical Hypertension Published by Wiley Periodicals, Inc.

  14. Analysis of measurement deviations for the patient-specific quality assurance using intensity-modulated spot-scanning particle beams

    NASA Astrophysics Data System (ADS)

    Li, Yongqiang; Hsi, Wen C.

    2017-04-01

    To analyze measurement deviations of patient-specific quality assurance (QA) using intensity-modulated spot-scanning particle beams, a commercial radiation dosimeter using 24 pinpoint ionization chambers was utilized. Before the clinical trial, validations of the radiation dosimeter and treatment planning system were conducted. During the clinical trial 165 measurements were performed on 36 enrolled patients. Two or three fields of particle beam were used for each patient. Measurements were typically performed with the dosimeter placed at special regions of dose distribution along depth and lateral profiles. In order to investigate the dosimeter accuracy, repeated measurements with uniform dose irradiations were also carried out. A two-step approach was proposed to analyze 24 sampling points over a 3D treatment volume. The mean value and the standard deviation of each measurement did not exceed 5% for all measurements performed on patients with various diseases. According to the defined intervention thresholds of mean deviation and the distance-to-agreement concept with a Gamma index analysis using criteria of 3.0% and 2 mm, a decision could be made regarding whether the dose distribution was acceptable for the patient. Based measurement results, deviation analysis was carried out. In this study, the dosimeter was used for dose verification and provided a safety guard to assure precise dose delivery of highly modulated particle therapy. Patient-specific QA will be investigated in future clinical operations.

  15. 22st Annual National Test and Evaluation Conference

    DTIC Science & Technology

    2006-03-09

    B1 B2 y ii) Factor B affects the standard deviation C2 C1 y iii) Factor C affects the average and the standard deviation D1 = D2 y iv) Factor D has...22303 UNITED STATES (P) (703)862-0908 (F) (703)970-5700 poole_grady@emc.com Mr. Josh Pressnell RTI 8306 Rugby Rd. Manassas, VA 20111...Ricciardi RTI 8306 Rugby Rd. Manassas, VA 20111-1912 UNITED STATES (P) (703)365-9662 (F) (703)365-9818 michael.ricciardi@rti-world.com Mr

  16. Characterization of solar cells for space applications. Volume 5: Electrical characteristics of OCLI 225-micron MLAR wraparound cells as a function of intensity, temperature, and irradiation

    NASA Technical Reports Server (NTRS)

    Anspaugh, B. E.; Miyahira, T. F.; Weiss, R. S.

    1979-01-01

    Computed statistical averages and standard deviations with respect to the measured cells for each intensity temperature measurement condition are presented. Display averages and standard deviations of the cell characteristics in a two dimensional array format are shown: one dimension representing incoming light intensity, and another, the cell temperature. Programs for calculating the temperature coefficients of the pertinent cell electrical parameters are presented, and postirradiation data are summarized.

  17. Evaluation of Acoustic Doppler Current Profiler measurements of river discharge

    USGS Publications Warehouse

    Morlock, S.E.

    1996-01-01

    The standard deviations of the ADCP measurements ranged from approximately 1 to 6 percent and were generally higher than the measurement errors predicted by error-propagation analysis of ADCP instrument performance. These error-prediction methods assume that the largest component of ADCP discharge measurement error is instrument related. The larger standard deviations indicate that substantial portions of measurement error may be attributable to sources unrelated to ADCP electronics or signal processing and are functions of the field environment.

  18. Threshold and variability properties of matrix frequency-doubling technology and standard automated perimetry in glaucoma.

    PubMed

    Artes, Paul H; Hutchison, Donna M; Nicolela, Marcelo T; LeBlanc, Raymond P; Chauhan, Balwantray C

    2005-07-01

    To compare test results from second-generation Frequency-Doubling Technology perimetry (FDT2, Humphrey Matrix; Carl-Zeiss Meditec, Dublin, CA) and standard automated perimetry (SAP) in patients with glaucoma. Specifically, to examine the relationship between visual field sensitivity and test-retest variability and to compare total and pattern deviation probability maps between both techniques. Fifteen patients with glaucoma who had early to moderately advanced visual field loss with SAP (mean MD, -4.0 dB; range, +0.2 to -16.1) were enrolled in the study. Patients attended three sessions. During each session, one eye was examined twice with FDT2 (24-2 threshold test) and twice with SAP (Swedish Interactive Threshold Algorithm [SITA] Standard 24-2 test), in random order. We compared threshold values between FDT2 and SAP at test locations with similar visual field coordinates. Test-retest variability, established in terms of test-retest intervals and standard deviations (SDs), was investigated as a function of visual field sensitivity (estimated by baseline threshold and mean threshold, respectively). The magnitude of visual field defects apparent in total and pattern deviation probability maps were compared between both techniques by ordinal scoring. The global visual field indices mean deviation (MD) and pattern standard deviation (PSD) of FDT2 and SAP correlated highly (r > 0.8; P < 0.001). At test locations with high sensitivity (>25 dB with SAP), threshold estimates from FDT2 and SAP exhibited a close, linear relationship, with a slope of approximately 2.0. However, at test locations with lower sensitivity, the relationship was much weaker and ceased to be linear. In comparison with FDT2, SAP showed a slightly larger proportion of test locations with absolute defects (3.0% vs. 2.2% with SAP and FDT2, respectively, P < 0.001). Whereas SAP showed a significant increase in test-retest variability at test locations with lower sensitivity (P < 0.001), there was no relationship between variability and sensitivity with FDT2 (P = 0.46). In comparison with SAP, FDT2 exhibited narrower test-retest intervals at test locations with lower sensitivity (SAP thresholds <25 dB). A comparison of the total and pattern deviation maps between both techniques showed that the total deviation analyses of FDT2 may slightly underestimate the visual field loss apparent with SAP. However, the pattern-deviation maps of both instruments agreed well with each other. The test-retest variability of FDT2 is uniform over the measurement range of the instrument. These properties may provide advantages for the monitoring of patients with glaucoma that should be investigated in longitudinal studies.

  19. 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.

  20. 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.

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