Inverse modeling with RZWQM2 to predict water quality

USGS Publications Warehouse

Nolan, Bernard T.; Malone, Robert W.; Ma, Liwang; Green, Christopher T.; Fienen, Michael N.; Jaynes, Dan B.

2011-01-01

This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST in both parameter estimation and predictive analysis modes. The goal of parameter estimation is to identify a unique set of parameters that minimize a weighted least squares objective function, and the goal of predictive analysis is to construct a nonlinear confidence interval for a prediction of interest by finding a set of parameters that maximizes or minimizes the prediction while maintaining the model in a calibrated state. We also describe PEST utilities (PAR2PAR, TSPROC) for maintaining ordered relations among model parameters (e.g., soil root growth factor) and for post-processing of RZWQM2 outputs representing different cropping practices at the Iowa site. Inverse modeling provided reasonable fits to observed water and N fluxes and directly benefitted the modeling through: (i) simultaneous adjustment of multiple parameters versus one-at-a-time adjustment in manual approaches; (ii) clear indication by convergence criteria of when calibration is complete; (iii) straightforward detection of nonunique and insensitive parameters, which can affect the stability of PEST and RZWQM2; and (iv) generation of confidence intervals for uncertainty analysis of parameters and model predictions. Composite scaled sensitivities, which reflect the total information provided by the observations for a parameter, indicated that most of the RZWQM2 parameters at the California study site (CA) and Iowa study site (IA) could be reliably estimated by regression. Correlations obtained in the CA case indicated that all model parameters could be uniquely estimated by inverse modeling. Although water content at field capacity was highly correlated with bulk density (−0.94), the correlation is less than the threshold for nonuniqueness (0.95, absolute value basis). Additionally, we used truncated singular value decomposition (SVD) at CA to mitigate potential problems with highly correlated and insensitive parameters. Singular value decomposition estimates linear combinations (eigenvectors) of the original process-model parameters. Parameter confidence intervals (CIs) at CA indicated that parameters were reliably estimated with the possible exception of an organic pool transfer coefficient (R45), which had a comparatively wide CI. However, the 95% confidence interval for R45 (0.03–0.35) is mostly within the range of values reported for this parameter. Predictive analysis at CA generated confidence intervals that were compared with independently measured annual water flux (groundwater recharge) and median nitrate concentration in a collocated monitoring well as part of model evaluation. Both the observed recharge (42.3 cm yr−1) and nitrate concentration (24.3 mg L−1) were within their respective 90% confidence intervals, indicating that overall model error was within acceptable limits.

Combining benefits of an adrenergic and a muscarinic blocker in a single formulation - a pharmacokinetic evaluation.

PubMed

Nazarudheen, Shabana; Dey, Surajit; Kandhwal, Kirti; Arora, Rachna; Reyar, Simrit; Khuroo, Arshad H; Monif, Tausif; Madan, Sumit; Arora, Vinod

2013-11-01

A pharmacokinetic bioequivalence study was conducted in Asian subjects, to compare a fixed dose combination capsule single oral dose of alpha adrenoceptor blocker-Alfuzosin hydrochloride 10mg extended release and muscarinic antagonists-Solifenacin succinate 5mg against individually administered Xatral XL 10mg tablets (Alfuzosin) of Sanofi Synthelabo Limited, United Kingdom (UK) and Vesicare 5mg tablets (Solifenacin) of Astellas Pharma Limited, UK under fed conditions. Blood samples were collected pre-dose up to 72 h post dose for determination of plasma Alfuzosin and Solifenacin concentrations and calculation of the pharmacokinetic parameters. ANOVA was performed on the log (natural)-transformed pharmacokinetic parameters. A 90% confidence interval for the ratios of the test and reference product averages (least square means) were calculated for alfuzosin and solifenacin. The 90% confidence intervals obtained for alfuzosin for Cmax, AUC0-t and AUC0-∞ were 102.74-122.75%, 95.84-116.96% and 95.82-116.76%, respectively. The 90% confidence intervals obtained for Solifenacin for Cmax, and AUC0-72 were 89.55-97.91% and 90.47-99.38%, respectively. Based on the results, the fixed dose combination was concluded to be bioequivalent to individually administered products. Copyright © 2013 Elsevier Inc. All rights reserved.

Neonatal stretched penile length: relationship with gestational maturity and anthropometric parameters at birth.

PubMed

Bhakhri, Bhanu Kiran; Meena, Shyam Sundar; Rawat, Mayank; Datta, Vikram

2015-02-01

It is inappropriate to use universal cut-off points to interpret stretched penile length (SPL) measurements in newborns with variable body dimensions. To assess neonatal SPL on the basis of gestational maturity and anthropometric parameters at birth. A cross-sectional observational study of SPL was conducted on stable newborns at a referral teaching hospital in north India between January and June 2012. Gestational maturity, SPL and anthropometric parameters (weight, length, head circumference and foot length) were recorded within 24 hours of birth. Variation of SPL in relation to gestational age and anthropometric parameters were evaluated using multiple linear regression models. The equation using lower confidence limits of 95% confidence intervals for the correlation coefficients provides cut-off points to define a small penis. Data from 1249 newborns demonstrated that penile growth follows the pattern of increase in body dimensions in newborns. SPL can be predicted best in relation to body and foot length taken together. SPL should be interpreted in relation to anthropometric parameters in newborns, particularly body and foot length.

Impact of age-related macular degeneration in patients with glaucoma: understanding the patients' perspective.

PubMed

Skalicky, Simon E; Fenwick, Eva; Martin, Keith R; Crowston, Jonathan; Goldberg, Ivan; McCluskey, Peter

2016-07-01

The aim of the study is to measure the impact of age-related macular degeneration on vision-related activity limitation and preference-based status for glaucoma patients. This was a cross-sectional study. Two-hundred glaucoma patients of whom 73 had age-related macular degeneration were included in the research. Sociodemographic information, visual field parameters and visual acuity were collected. Age-related macular degeneration was scored using the Age-Related Eye Disease Study system. The Rasch-analysed Glaucoma Activity Limitation-9 and the Visual Function Questionnaire Utility Index measured vision-related activity limitation and preference-based status, respectively. Regression models determined factors predictive of vision-related activity limitation and preference-based status. Differential item functioning compared Glaucoma Activity Limitation-9 item difficulty for those with and without age-related macular degeneration. Mean age was 73.7 (±10.1) years. Lower better eye mean deviation (β: 1.42, 95% confidence interval: 1.24-1.63, P < 0.001) and age-related macular degeneration (β: 1.26 95% confidence interval: 1.10-1.44, P = 0.001) were independently associated with worse vision-related activity limitation. Worse eye visual acuity (β: 0.978, 95% confidence interval: 0.961-0.996, P = 0.018), high risk age-related macular degeneration (β: 0.981, 95% confidence interval: 0.965-0.998, P = 0.028) and severe glaucoma (β: 0.982, 95% confidence interval: 0.966-0.998, P = 0.032) were independently associated with worse preference-based status. Glaucoma patients with age-related macular degeneration found using stairs, walking on uneven ground and judging distances of foot to step/curb significantly more difficult than those without age-related macular degeneration. Vision-related activity limitation and preference-based status are negatively impacted by severe glaucoma and age-related macular degeneration. Patients with both conditions perceive increased difficulty walking safely compared with patients with glaucoma alone. © 2015 Royal Australian and New Zealand College of Ophthalmologists.

The Sense of Confidence during Probabilistic Learning: A Normative Account.

PubMed

Meyniel, Florent; Schlunegger, Daniel; Dehaene, Stanislas

2015-06-01

Learning in a stochastic environment consists of estimating a model from a limited amount of noisy data, and is therefore inherently uncertain. However, many classical models reduce the learning process to the updating of parameter estimates and neglect the fact that learning is also frequently accompanied by a variable "feeling of knowing" or confidence. The characteristics and the origin of these subjective confidence estimates thus remain largely unknown. Here we investigate whether, during learning, humans not only infer a model of their environment, but also derive an accurate sense of confidence from their inferences. In our experiment, humans estimated the transition probabilities between two visual or auditory stimuli in a changing environment, and reported their mean estimate and their confidence in this report. To formalize the link between both kinds of estimate and assess their accuracy in comparison to a normative reference, we derive the optimal inference strategy for our task. Our results indicate that subjects accurately track the likelihood that their inferences are correct. Learning and estimating confidence in what has been learned appear to be two intimately related abilities, suggesting that they arise from a single inference process. We show that human performance matches several properties of the optimal probabilistic inference. In particular, subjective confidence is impacted by environmental uncertainty, both at the first level (uncertainty in stimulus occurrence given the inferred stochastic characteristics) and at the second level (uncertainty due to unexpected changes in these stochastic characteristics). Confidence also increases appropriately with the number of observations within stable periods. Our results support the idea that humans possess a quantitative sense of confidence in their inferences about abstract non-sensory parameters of the environment. This ability cannot be reduced to simple heuristics, it seems instead a core property of the learning process.

The Sense of Confidence during Probabilistic Learning: A Normative Account

PubMed Central

Meyniel, Florent; Schlunegger, Daniel; Dehaene, Stanislas

2015-01-01

Learning in a stochastic environment consists of estimating a model from a limited amount of noisy data, and is therefore inherently uncertain. However, many classical models reduce the learning process to the updating of parameter estimates and neglect the fact that learning is also frequently accompanied by a variable “feeling of knowing” or confidence. The characteristics and the origin of these subjective confidence estimates thus remain largely unknown. Here we investigate whether, during learning, humans not only infer a model of their environment, but also derive an accurate sense of confidence from their inferences. In our experiment, humans estimated the transition probabilities between two visual or auditory stimuli in a changing environment, and reported their mean estimate and their confidence in this report. To formalize the link between both kinds of estimate and assess their accuracy in comparison to a normative reference, we derive the optimal inference strategy for our task. Our results indicate that subjects accurately track the likelihood that their inferences are correct. Learning and estimating confidence in what has been learned appear to be two intimately related abilities, suggesting that they arise from a single inference process. We show that human performance matches several properties of the optimal probabilistic inference. In particular, subjective confidence is impacted by environmental uncertainty, both at the first level (uncertainty in stimulus occurrence given the inferred stochastic characteristics) and at the second level (uncertainty due to unexpected changes in these stochastic characteristics). Confidence also increases appropriately with the number of observations within stable periods. Our results support the idea that humans possess a quantitative sense of confidence in their inferences about abstract non-sensory parameters of the environment. This ability cannot be reduced to simple heuristics, it seems instead a core property of the learning process. PMID:26076466

A hierarchical Bayesian GEV model for improving local and regional flood quantile estimates

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; Lall, Upmanu; Troy, Tara; Devineni, Naresh

2016-10-01

We estimate local and regional Generalized Extreme Value (GEV) distribution parameters for flood frequency analysis in a multilevel, hierarchical Bayesian framework, to explicitly model and reduce uncertainties. As prior information for the model, we assume that the GEV location and scale parameters for each site come from independent log-normal distributions, whose mean parameter scales with the drainage area. From empirical and theoretical arguments, the shape parameter for each site is shrunk towards a common mean. Non-informative prior distributions are assumed for the hyperparameters and the MCMC method is used to sample from the joint posterior distribution. The model is tested using annual maximum series from 20 streamflow gauges located in an 83,000 km2 flood prone basin in Southeast Brazil. The results show a significant reduction of uncertainty estimates of flood quantile estimates over the traditional GEV model, particularly for sites with shorter records. For return periods within the range of the data (around 50 years), the Bayesian credible intervals for the flood quantiles tend to be narrower than the classical confidence limits based on the delta method. As the return period increases beyond the range of the data, the confidence limits from the delta method become unreliable and the Bayesian credible intervals provide a way to estimate satisfactory confidence bands for the flood quantiles considering parameter uncertainties and regional information. In order to evaluate the applicability of the proposed hierarchical Bayesian model for regional flood frequency analysis, we estimate flood quantiles for three randomly chosen out-of-sample sites and compare with classical estimates using the index flood method. The posterior distributions of the scaling law coefficients are used to define the predictive distributions of the GEV location and scale parameters for the out-of-sample sites given only their drainage areas and the posterior distribution of the average shape parameter is taken as the regional predictive distribution for this parameter. While the index flood method does not provide a straightforward way to consider the uncertainties in the index flood and in the regional parameters, the results obtained here show that the proposed Bayesian method is able to produce adequate credible intervals for flood quantiles that are in accordance with empirical estimates.

Evaluation of confidence intervals for a steady-state leaky aquifer model

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

1999-01-01

The fact that dependent variables of groundwater models are generally nonlinear functions of model parameters is shown to be a potentially significant factor in calculating accurate confidence intervals for both model parameters and functions of the parameters, such as the values of dependent variables calculated by the model. The Lagrangian method of Vecchia and Cooley [Vecchia, A.V. and Cooley, R.L., Water Resources Research, 1987, 23(7), 1237-1250] was used to calculate nonlinear Scheffe-type confidence intervals for the parameters and the simulated heads of a steady-state groundwater flow model covering 450 km2 of a leaky aquifer. The nonlinear confidence intervals are compared to corresponding linear intervals. As suggested by the significant nonlinearity of the regression model, linear confidence intervals are often not accurate. The commonly made assumption that widths of linear confidence intervals always underestimate the actual (nonlinear) widths was not correct. Results show that nonlinear effects can cause the nonlinear intervals to be asymmetric and either larger or smaller than the linear approximations. Prior information on transmissivities helps reduce the size of the confidence intervals, with the most notable effects occurring for the parameters on which there is prior information and for head values in parameter zones for which there is prior information on the parameters.The fact that dependent variables of groundwater models are generally nonlinear functions of model parameters is shown to be a potentially significant factor in calculating accurate confidence intervals for both model parameters and functions of the parameters, such as the values of dependent variables calculated by the model. The Lagrangian method of Vecchia and Cooley was used to calculate nonlinear Scheffe-type confidence intervals for the parameters and the simulated heads of a steady-state groundwater flow model covering 450 km2 of a leaky aquifer. The nonlinear confidence intervals are compared to corresponding linear intervals. As suggested by the significant nonlinearity of the regression model, linear confidence intervals are often not accurate. The commonly made assumption that widths of linear confidence intervals always underestimate the actual (nonlinear) widths was not correct. Results show that nonlinear effects can cause the nonlinear intervals to be asymmetric and either larger or smaller than the linear approximations. Prior information on transmissivities helps reduce the size of the confidence intervals, with the most notable effects occurring for the parameters on which there is prior information and for head values in parameter zones for which there is prior information on the parameters.

Constraints on the double-parton scattering cross section from same-sign W boson pair production in proton-proton collisions at √{s}=8 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.; 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 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.; 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.; 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.; 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.; Mahmoud, M. A.; Mahrous, A.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; 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.; 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.; Toriashvili, T.; 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. 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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.; 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.; 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.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2018-02-01

A first search for same-sign WW production via double-parton scattering is performed based on proton-proton collision data at a center-of-mass energy of 8 TeV using dimuon and electron-muon final states. The search is based on the analysis of data corresponding to an integrated luminosity of 19.7 fb-1. No significant excess of events is observed above the expected single-parton scattering yields. A 95% confidence level upper limit of 0.32 pb is set on the inclusive cross section for same-sign WW production via the double-parton scattering process. This upper limit is used to place a 95% confidence level lower limit of 12.2 mb on the effective double-parton cross section parameter, closely related to the transverse distribution of partons in the proton. This limit on the effective cross section is consistent with previous measurements as well as with Monte Carlo event generator predictions.

Improved central confidence intervals for the ratio of Poisson means

NASA Astrophysics Data System (ADS)

Cousins, R. D.

The problem of confidence intervals for the ratio of two unknown Poisson means was "solved" decades ago, but a closer examination reveals that the standard solution is far from optimal from the frequentist point of view. We construct a more powerful set of central confidence intervals, each of which is a (typically proper) subinterval of the corresponding standard interval. They also provide upper and lower confidence limits which are more restrictive than the standard limits. The construction follows Neyman's original prescription, though discreteness of the Poisson distribution and the presence of a nuisance parameter (one of the unknown means) lead to slightly conservative intervals. Philosophically, the issue of the appropriateness of the construction method is similar to the issue of conditioning on the margins in 2×2 contingency tables. From a frequentist point of view, the new set maintains (over) coverage of the unknown true value of the ratio of means at each stated confidence level, even though the new intervals are shorter than the old intervals by any measure (except for two cases where they are identical). As an example, when the number 2 is drawn from each Poisson population, the 90% CL central confidence interval on the ratio of means is (0.169, 5.196), rather than (0.108, 9.245). In the cited literature, such confidence intervals have applications in numerous branches of pure and applied science, including agriculture, wildlife studies, manufacturing, medicine, reliability theory, and elementary particle physics.

Exact Scheffé-type confidence intervals for output from groundwater flow models: 2. Combined use of hydrogeologic information and calibration data

USGS Publications Warehouse

Cooley, Richard L.

1993-01-01

Calibration data (observed values corresponding to model-computed values of dependent variables) are incorporated into a general method of computing exact Scheffé-type confidence intervals analogous to the confidence intervals developed in part 1 (Cooley, this issue) for a function of parameters derived from a groundwater flow model. Parameter uncertainty is specified by a distribution of parameters conditioned on the calibration data. This distribution was obtained as a posterior distribution by applying Bayes' theorem to the hydrogeologically derived prior distribution of parameters from part 1 and a distribution of differences between the calibration data and corresponding model-computed dependent variables. Tests show that the new confidence intervals can be much smaller than the intervals of part 1 because the prior parameter variance-covariance structure is altered so that combinations of parameters that give poor model fit to the data are unlikely. The confidence intervals of part 1 and the new confidence intervals can be effectively employed in a sequential method of model construction whereby new information is used to reduce confidence interval widths at each stage.

A multiple reader scoring system for Nasal Potential Difference parameters.

PubMed

Solomon, George M; Liu, Bo; Sermet-Gaudelus, Isabelle; Fajac, Isabelle; Wilschanski, Michael; Vermeulen, Francois; Rowe, Steven M

2017-09-01

Nasal Potential Difference (NPD) is a biomarker of CFTR activity used to diagnose CF and monitor experimental therapies. Limited studies have been performed to assess agreement between expert readers of NPD interpretation using a scoring algorithm. We developed a standardized scoring algorithm for "interpretability" and "confidence" for PD (potential difference) measures, and sought to determine the degree of agreement on NPD parameters between trained readers. There was excellent agreement for interpretability between NPD readers for CF and fair agreement for normal tracings but slight agreement of interpretability in indeterminate tracings. Amongst interpretable tracings, excellent correlation of mean scores for Ringer's Baseline PD, Δ amiloride , and Δ Cl-free+Isoproterenol was observed. There was slight agreement regarding confidence of the interpretable PD tracings, resulting in divergence of the Ringers and Δ amiloride , and ΔCl -free+Isoproterenol PDs between "high" and "low" confidence CF tracings. A multi-reader process with adjudication is important for scoring NPDs for diagnosis and in monitoring of CF clinical trials. Copyright © 2017 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

Inverse models: A necessary next step in ground-water modeling

USGS Publications Warehouse

Poeter, E.P.; Hill, M.C.

1997-01-01

Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares repression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares regression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.

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

Shaffer, Richard, E-mail: rickyshaffer@yahoo.co.u; Department of Clinical Oncology, Imperial College London National Health Service Trust, London; Pickles, Tom

Purpose: Prior studies have derived low values of alpha-beta ratio (a/ss) for prostate cancer of approximately 1-2 Gy. These studies used poorly matched groups, differing definitions of biochemical failure, and insufficient follow-up. Methods and Materials: National Comprehensive Cancer Network low- or low-intermediate risk prostate cancer patients, treated with external beam radiotherapy or permanent prostate brachytherapy, were matched for prostate-specific antigen, Gleason score, T-stage, percentage of positive cores, androgen deprivation therapy, and era, yielding 118 patient pairs. The Phoenix definition of biochemical failure was used. The best-fitting value for a/ss was found for up to 90-month follow-up using maximum likelihood analysis,more » and the 95% confidence interval using the profile likelihood method. Linear quadratic formalism was applied with the radiobiological parameters of relative biological effectiveness = 1.0, potential doubling time = 45 days, and repair half-time = 1 hour. Bootstrap analysis was performed to estimate uncertainties in outcomes, and hence in a/ss. Sensitivity analysis was performed by varying the values of the radiobiological parameters to extreme values. Results: The value of a/ss best fitting the outcomes data was >30 Gy, with lower 95% confidence limit of 5.2 Gy. This was confirmed on bootstrap analysis. Varying parameters to extreme values still yielded best-fit a/ss of >30 Gy, although the lower 95% confidence interval limit was reduced to 0.6 Gy. Conclusions: Using carefully matched groups, long follow-up, the Phoenix definition of biochemical failure, and well-established statistical methods, the best estimate of a/ss for low and low-tier intermediate-risk prostate cancer is likely to be higher than that of normal tissues, although a low value cannot be excluded.« less

Estimation of αL, velocity, Kd and confidence limits from tracer injection test data

USGS Publications Warehouse

Broermann, James; Bassett, R.L.; Weeks, Edwin P.; Borgstrom, Mark

1997-01-01

Bromide and boron were used as tracers during an injection experiment conducted at an artificial recharge facility near Stanton, Texas. The Ogallala aquifer at the Stanton site represents a heterogeneous alluvial environment and provides the opportunity to report scale dependent dispersivities at observation distances of 2 to 15 m in this setting. Values of longitudinal dispersivities are compared with other published values. Water samples were collected at selected depths both from piezometers and from fully screened observation wells at radii of 2, 5, 10 and 15 m. An exact analytical solution is used to simulate the concentration breakthrough curves and estimate longitudinal dispersivities and velocity parameters. Greater confidence can be placed on these data because the estimated parameters are error bounded using the bootstrap method. The non-conservative behavior of boron transport in clay rich sections of the aquifer were quantified with distribution coefficients by using bromide as a conservative reference tracer.

Estimation of αL, velocity, Kd, and confidence limits from tracer injection data

USGS Publications Warehouse

Broermann, James; Bassett, R.L.; Weeks, Edwin P.; Borgstrom, Mark

1997-01-01

Bromide and boron were used as tracers during an injection experiment conducted at an artificial recharge facility near Stanton, Texas. The Ogallala aquifer at the Stanton site represents a heterogeneous alluvial environment and provides the opportunity to report scale dependent dispersivities at observation distances of 2 to 15 m in this setting. Values of longitudinal dispersivities are compared with other published values. Water samples were collected at selected depths both from piezometers and from fully screened observation wells at radii of 2, 5, 10 and 15 m. An exact analytical solution is used to simulate the concentration breakthrough curves and estimate longitudinal dispersivities and velocity parameters. Greater confidence can be placed on these data because the estimated parameters are error bounded using the bootstrap method. The non-conservative behavior of boron transport in clay rich sections of the aquifer were quantified with distribution coefficients by using bromide as a conservative reference tracer.

Probabilistic Analysis for Comparing Fatigue Data Based on Johnson-Weibull Parameters

NASA Technical Reports Server (NTRS)

Vlcek, Brian L.; Hendricks, Robert C.; Zaretsky, Erwin V.

2013-01-01

Leonard Johnson published a methodology for establishing the confidence that two populations of data are different. Johnson's methodology is dependent on limited combinations of test parameters (Weibull slope, mean life ratio, and degrees of freedom) and a set of complex mathematical equations. In this report, a simplified algebraic equation for confidence numbers is derived based on the original work of Johnson. The confidence numbers calculated with this equation are compared to those obtained graphically by Johnson. Using the ratios of mean life, the resultant values of confidence numbers at the 99 percent level deviate less than 1 percent from those of Johnson. At a 90 percent confidence level, the calculated values differ between +2 and 4 percent. The simplified equation is used to rank the experimental lives of three aluminum alloys (AL 2024, AL 6061, and AL 7075), each tested at three stress levels in rotating beam fatigue, analyzed using the Johnson- Weibull method, and compared to the ASTM Standard (E739 91) method of comparison. The ASTM Standard did not statistically distinguish between AL 6061 and AL 7075. However, it is possible to rank the fatigue lives of different materials with a reasonable degree of statistical certainty based on combined confidence numbers using the Johnson- Weibull analysis. AL 2024 was found to have the longest fatigue life, followed by AL 7075, and then AL 6061. The ASTM Standard and the Johnson-Weibull analysis result in the same stress-life exponent p for each of the three aluminum alloys at the median, or L(sub 50), lives

An ultraviolet-spectrophotometric method for the determination of glimepiride in solid dosage forms.

PubMed

Afieroho, Ozadheoghene E; Okorie, Ogbonna; Okonkwo, Tochukwu J N

2011-06-01

Considering the cost of acquiring a liquid chromatographic instrument in underdeveloped economies, the rising incidence of diabetes mellitus, the need to evaluate the quality performance of glimepiride generics, and the need for less toxic processes, this research is an imperative. The method was validated for linearity, recovery accuracy, intra- and inter-day precision, specificity in the presence of excipients, and inter-day stability under laboratory conditions. Student's t test at the 95% confidence limit was used for statistics. Using 96% ethanol as solvent, a less toxic and cost-effective spectrophotometric method for the determination of glimepiride in solid dosage forms was developed and validated. The results of the validated parameters showed a λ(max) of 231 nm, linearity range of 0.5-22 μg/mL, precision with relative SD of <1.0%, recovery accuracy of 100.8%, regression equation of y = 45.741x + 0.0202, R(2) = 0.999, limit of detection of 0.35 μg/mL, and negligible interference from common excipients and colorants. The method was found to be accurate at the 95% confidence limit compared with the standard liquid chromatographic method with comparable reproducibility when used to assay the formulated products Amaryl(®) (sanofi-aventis, Paris, France) and Mepyril(®) (May & Baker Nigeria PLC, Ikeja, Nigeria). The results obtained for the validated parameters were within allowable limits. This method is recommended for routine quality control analysis.

Point and interval estimation of pollinator importance: a study using pollination data of Silene caroliniana.

PubMed

Reynolds, Richard J; Fenster, Charles B

2008-05-01

Pollinator importance, the product of visitation rate and pollinator effectiveness, is a descriptive parameter of the ecology and evolution of plant-pollinator interactions. Naturally, sources of its variation should be investigated, but the SE of pollinator importance has never been properly reported. Here, a Monte Carlo simulation study and a result from mathematical statistics on the variance of the product of two random variables are used to estimate the mean and confidence limits of pollinator importance for three visitor species of the wildflower, Silene caroliniana. Both methods provided similar estimates of mean pollinator importance and its interval if the sample size of the visitation and effectiveness datasets were comparatively large. These approaches allowed us to determine that bumblebee importance was significantly greater than clearwing hawkmoth, which was significantly greater than beefly. The methods could be used to statistically quantify temporal and spatial variation in pollinator importance of particular visitor species. The approaches may be extended for estimating the variance of more than two random variables. However, unless the distribution function of the resulting statistic is known, the simulation approach is preferable for calculating the parameter's confidence limits.

Constraints on the double-parton scattering cross section from same-sign W boson pair production in proton-proton collisions at $$ \\sqrt{s}=8 $$ TeV

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

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

A first search for same-sign WW production via double-parton scattering is performed based on proton-proton collision data at a center-of-mass energy of 8 TeV using dimuon and electron-muon final states. The search is based on the analysis of data corresponding to an integrated luminosity of 19.7 fb –1. No significant excess of events is observed above the expected single-parton scattering yields. A 95% confidence level upper limit of 0.32 pb is set on the inclusive cross section for same-sign WW production via the double-parton scattering process. This upper limit is used to place a 95% confidence level lower limit ofmore » 12.2 mb on the effective double-parton cross section parameter, closely related to the transverse distribution of partons in the proton. As a result, this limit on the effective cross section is consistent with previous measurements as well as with Monte Carlo event generator predictions.« less

Constraints on the double-parton scattering cross section from same-sign W boson pair production in proton-proton collisions at $$ \\sqrt{s}=8 $$ TeV

DOE PAGES

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

2018-02-06

A first search for same-sign WW production via double-parton scattering is performed based on proton-proton collision data at a center-of-mass energy of 8 TeV using dimuon and electron-muon final states. The search is based on the analysis of data corresponding to an integrated luminosity of 19.7 fb –1. No significant excess of events is observed above the expected single-parton scattering yields. A 95% confidence level upper limit of 0.32 pb is set on the inclusive cross section for same-sign WW production via the double-parton scattering process. This upper limit is used to place a 95% confidence level lower limit ofmore » 12.2 mb on the effective double-parton cross section parameter, closely related to the transverse distribution of partons in the proton. As a result, this limit on the effective cross section is consistent with previous measurements as well as with Monte Carlo event generator predictions.« less

Search for high-mass resonances in dilepton final states in proton-proton collisions at $$\\sqrt{s}=$$ 13 TeV

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

Sirunyan, Albert M; et al.

A search is presented for new high-mass resonances decaying into electron or muon pairs. The search uses proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the CMS experiment at the LHC in 2016, corresponding to an integrated luminosity of 36 fbmore » $$^{-1}$$. Observations are in agreement with standard model expectations. Upper limits on the product of a new resonance production cross section and branching fraction to dileptons are calculated in a model-independent manner. This permits the interpretation of the limits in models predicting a narrow dielectron or dimuon resonance. A scan of different intrinsic width hypotheses is performed. Limits are set on the masses of various hypothetical particles. For the Z$$'_\\mathrm{SSM}$$ (Z$$'_{\\psi}$$) particle, which arises in the sequential standard model (superstring-inspired model), a lower mass limit of 4.50 (3.90) TeV is set at 95% confidence level. The lightest Kaluza-Klein graviton arising in the Randall-Sundrum model of extra dimensions, with coupling parameters $$k/\\overline{M}_\\mathrm{Pl}$$ of 0.01, 0.05, and 0.10, is excluded at 95% confidence level below 2.10 , 3.65 , and 4.25 TeV, respectively. In a simplified model of dark matter production via a vector or axial vector mediator, limits at 95% confidence level are obtained on the masses of the dark matter particle and its mediator.« less

Uncertainties in Galactic Chemical Evolution Models

DOE PAGES

Cote, Benoit; Ritter, Christian; Oshea, Brian W.; ...

2016-06-15

Here we use a simple one-zone galactic chemical evolution model to quantify the uncertainties generated by the input parameters in numerical predictions for a galaxy with properties similar to those of the Milky Way. We compiled several studies from the literature to gather the current constraints for our simulations regarding the typical value and uncertainty of the following seven basic parameters: the lower and upper mass limits of the stellar initial mass function (IMF), the slope of the high-mass end of the stellar IMF, the slope of the delay-time distribution function of Type Ia supernovae (SNe Ia), the number ofmore » SNe Ia per M ⊙ formed, the total stellar mass formed, and the final mass of gas. We derived a probability distribution function to express the range of likely values for every parameter, which were then included in a Monte Carlo code to run several hundred simulations with randomly selected input parameters. This approach enables us to analyze the predicted chemical evolution of 16 elements in a statistical manner by identifying the most probable solutions along with their 68% and 95% confidence levels. Our results show that the overall uncertainties are shaped by several input parameters that individually contribute at different metallicities, and thus at different galactic ages. The level of uncertainty then depends on the metallicity and is different from one element to another. Among the seven input parameters considered in this work, the slope of the IMF and the number of SNe Ia are currently the two main sources of uncertainty. The thicknesses of the uncertainty bands bounded by the 68% and 95% confidence levels are generally within 0.3 and 0.6 dex, respectively. When looking at the evolution of individual elements as a function of galactic age instead of metallicity, those same thicknesses range from 0.1 to 0.6 dex for the 68% confidence levels and from 0.3 to 1.0 dex for the 95% confidence levels. The uncertainty in our chemical evolution model does not include uncertainties relating to stellar yields, star formation and merger histories, and modeling assumptions.« less

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

Cote, Benoit; Ritter, Christian; Oshea, Brian W.

Here we use a simple one-zone galactic chemical evolution model to quantify the uncertainties generated by the input parameters in numerical predictions for a galaxy with properties similar to those of the Milky Way. We compiled several studies from the literature to gather the current constraints for our simulations regarding the typical value and uncertainty of the following seven basic parameters: the lower and upper mass limits of the stellar initial mass function (IMF), the slope of the high-mass end of the stellar IMF, the slope of the delay-time distribution function of Type Ia supernovae (SNe Ia), the number ofmore » SNe Ia per M ⊙ formed, the total stellar mass formed, and the final mass of gas. We derived a probability distribution function to express the range of likely values for every parameter, which were then included in a Monte Carlo code to run several hundred simulations with randomly selected input parameters. This approach enables us to analyze the predicted chemical evolution of 16 elements in a statistical manner by identifying the most probable solutions along with their 68% and 95% confidence levels. Our results show that the overall uncertainties are shaped by several input parameters that individually contribute at different metallicities, and thus at different galactic ages. The level of uncertainty then depends on the metallicity and is different from one element to another. Among the seven input parameters considered in this work, the slope of the IMF and the number of SNe Ia are currently the two main sources of uncertainty. The thicknesses of the uncertainty bands bounded by the 68% and 95% confidence levels are generally within 0.3 and 0.6 dex, respectively. When looking at the evolution of individual elements as a function of galactic age instead of metallicity, those same thicknesses range from 0.1 to 0.6 dex for the 68% confidence levels and from 0.3 to 1.0 dex for the 95% confidence levels. The uncertainty in our chemical evolution model does not include uncertainties relating to stellar yields, star formation and merger histories, and modeling assumptions.« less

Simplifying Chandra aperture photometry with srcflux

NASA Astrophysics Data System (ADS)

Glotfelty, Kenny

2014-11-01

This poster will highlight some of the features of the srcflux script in CIAO. This script combines many threads and tools together to compute photometric properties for sources: counts, rates, various fluxes, and confidence intervals or upper limits. Beginning and casual X-ray astronomers greatly benefit from the simple interface: just specify the event file and a celestial location, while power-users and X-ray astronomy experts can take advantage of the all the parameters to automatically produce catalogs for entire fields. Current limitations and future enhancements of the script will also be presented.

Measurement of the cosmic microwave background spectrum by the COBE FIRAS instrument

NASA Technical Reports Server (NTRS)

Mather, J. C.; Cheng, E. S.; Cottingham, D. A.; Eplee, R. E., Jr.; Fixsen, D. J.; Hewagama, T.; Isaacman, R. B.; Jensen, K. A.; Meyer, S. S.; Noerdlinger, P. D.

1994-01-01

The cosmic microwave background radiation (CMBR) has a blackbody spectrum within 3.4 x 10(exp -8) ergs/sq cm/s/sr cm over the frequency range from 2 to 20/cm (5-0.5 mm). These measurements, derived from the Far-Infrared Absolute Spectrophotomer (FIRAS) instrument on the Cosmic Background Explorer (COBE) satellite, imply stringent limits on energy release in the early universe after t approximately 1 year and redshift z approximately 3 x 10(exp 6). The deviations are less than 0.30% of the peak brightness, with an rms value of 0.01%, and the dimensionless cosmological distortion parameters are limited to the absolute value of y is less than 2.5 x 10(exp -5) and the absolute value of mu is less than 3.3 x 10(exp -4) (95% confidence level). The temperature of the CMBR is 2.726 +/- 0.010 K (95% confidence level systematic).

Search for WWγ and WZγ production and constraints on anomalous quartic gauge couplings in pp collisions at √s =8 TeV

NASA Astrophysics Data System (ADS)

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Luyckx, S.; Ochesanu, S.; Roland, B.; Rougny, R.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Heracleous, N.; Kalogeropoulos, A.; Keaveney, J.; Kim, T. 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.; Favart, L.; Gay, A. P. R.; Léonard, A.; Marage, P. E.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Garcia, G.; Klein, B.; Lellouch, J.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Walsh, S.; 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.; Jez, P.; Komm, M.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; 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.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Pol, M. E.; Rebello Teles, P.; Aldá Júnior, W. L.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Malek, M.; 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.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Du, R.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Plestina, R.; Tao, J.; Wang, X.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, Y.; Li, Q.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Yang, D.; Zhang, L.; Zou, W.; Avila, C.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Morovic, S.; Tikvica, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Mahmoud, M. A.; Mahrous, A.; Radi, A.; Kadastik, M.; Müntel, 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.; 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.; Nayak, A.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Busson, P.; Charlot, C.; Daci, N.; 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.; Sabes, D.; Salerno, R.; Sauvan, J. b.; Sirois, Y.; Veelken, C.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Chabert, E. C.; Collard, C.; Conte, E.; Drouhin, F.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Juillot, P.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Boudoul, G.; 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.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Rurua, L.; Autermann, C.; Beranek, S.; Bontenackels, M.; Calpas, B.; Edelhoff, M.; Feld, L.; Hindrichs, O.; Klein, K.; Ostapchuk, A.; Perieanu, A.; Raupach, F.; Sammet, J.; Schael, S.; Sprenger, D.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Caudron, J.; 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.; 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.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Perchalla, L.; Pooth, O.; Stahl, A.; Asin, I.; Bartosik, N.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bell, A. J.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garay Garcia, J.; Geiser, A.; Grebenyuk, A.; Gunnellini, P.; Habib, S.; Hauk, J.; Hellwig, G.; Hempel, M.; Horton, D.; Jung, H.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Krämer, M.; Krücker, D.; Lange, W.; Leonard, J.; Lipka, K.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Novgorodova, O.; Nowak, F.; Ntomari, E.; Perrey, H.; Petrukhin, A.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Riedl, C.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Stein, M.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; Enderle, H.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Gosselink, M.; Haller, J.; Höing, R. S.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Pietsch, N.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sibille, J.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Guthoff, M.; Hartmann, F.; Hauth, T.; Held, H.; Hoffmann, K. H.; Husemann, U.; Katkov, I.; Kornmayer, A.; Kuznetsova, E.; Lobelle Pardo, P.; Martschei, D.; Mozer, M. U.; Müller, Th.; Niegel, M.; Nürnberg, A.; Oberst, O.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Röcker, S.; Schilling, F.-P.; Schott, G.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Zeise, M.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kesisoglou, S.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Gouskos, L.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Jones, J.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Dhingra, N.; Gupta, R.; Kalsi, A. K.; Kaur, M.; Mittal, M.; Nishu, N.; Sharma, A.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Shivpuri, R. K.; 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.; Singh, A. P.; Abdulsalam, A.; Dutta, D.; Kailas, S.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Chatterjee, R. M.; 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.; Banerjee, S.; Dewanjee, R. K.; Dugad, S.; Arfaei, H.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Jafari, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Safarzadeh, B.; Zeinali, M.; Grunewald, M.; Abbrescia, M.; Barbone, L.; 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.; Pacifico, N.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Silvestris, L.; Singh, G.; Venditti, R.; Verwilligen, P.; Zito, G.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Meneghelli, M.; Montanari, A.; Navarria, F. L.; Odorici, F.; 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.; Fabbricatore, P.; Ferro, F.; Lo Vetere, M.; Musenich, R.; Robutti, E.; Tosi, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Lucchini, M. T.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dorigo, T.; Galanti, M.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Lazzizzera, I.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Sgaravatto, M.; Simonetto, F.; Torassa, E.; Tosi, M.; Triossi, A.; Ventura, S.; Zotto, P.; Zucchetta, A.; Gabusi, M.; Ratti, S. P.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Romeo, F.; 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.; Kraan, A.; 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.; Del Re, D.; Diemoz, M.; Grassi, M.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Rovelli, C.; 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.; Montanino, D.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kim, T. Y.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, J. E.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Park, H.; Sakharov, A.; Son, D. C.; Kim, J. Y.; Kim, Zero J.; 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, C.; Park, I. C.; Park, S.; Ryu, G.; Choi, Y.; Choi, Y. K.; Goh, J.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Lopez-Fernandez, R.; Martínez-Ortega, J.; Sanchez-Hernandez, A.; Villasenor-Cendejas, L. M.; Carrillo Moreno, S.; Vazquez Valencia, F.; Salazar Ibarguen, H. A.; Casimiro Linares, E.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Doesburg, R.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Asghar, M. I.; Butt, J.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Khurshid, T.; Qazi, S.; Shah, M. A.; Shoaib, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Wrochna, G.; Zalewski, P.; Brona, G.; Bunkowski, K.; Cwiok, M.; Dominik, W.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Wolszczak, W.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Varela, J.; Vischia, P.; Golutvin, I.; Gorbunov, I.; Karjavin, V.; Konoplyanikov, V.; Korenkov, V.; Kozlov, G.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Vorobyev, An.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Safronov, G.; Semenov, S.; Spiridonov, A.; Stolin, V.; Vlasov, E.; Zhokin, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Petrushanko, 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.; Djordjevic, M.; Ekmedzic, M.; Milosevic, J.; Aguilar-Benitez, M.; 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.; Ferrando, A.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Merino, G.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Willmott, C.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Lloret Iglesias, L.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Gonzalez Sanchez, J.; 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.; Bianchi, G.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Christiansen, T.; Coarasa Perez, J. A.; Colafranceschi, S.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; David, A.; De Guio, F.; De Roeck, A.; De Visscher, S.; Dobson, M.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Eugster, J.; Franzoni, G.; Funk, W.; Giffels, M.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Giunta, M.; Glege, F.; Gomez-Reino Garrido, R.; Gowdy, S.; Guida, R.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Karavakis, E.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Magini, N.; Malgeri, L.; Mannelli, M.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Mulders, M.; Musella, P.; Orsini, L.; Palencia Cortezon, E.; Pape, L.; Perez, E.; Perrozzi, L.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Plagge, M.; Racz, A.; Reece, W.; Rolandi, G.; Rovere, M.; Sakulin, H.; Santanastasio, F.; Schäfer, C.; Schwick, C.; Sekmen, S.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Treille, D.; Tsirou, A.; Veres, G. I.; Vlimant, J. R.; Wöhri, H. K.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; König, S.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Bortignon, P.; Buchmann, M. A.; Casal, B.; Chanon, N.; Deisher, A.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Meister, D.; Mohr, N.; Nägeli, C.; Nef, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Ronga, F. J.; 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.; Ivova Rikova, M.; Kilminster, B.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Snoek, H.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Li, S. W.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Bartalini, P.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W.-S.; Hsiung, Y.; Kao, K. Y.; Lei, Y. J.; Liu, Y. F.; Lu, R.-S.; Majumder, D.; Petrakou, E.; Shi, X.; Shiu, J. G.; Tzeng, Y. M.; Wang, M.; Wilken, R.; Asavapibhop, B.; Simili, E.; 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.; Sogut, K.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Aliev, T.; Bilin, B.; Bilmis, S.; Deniz, M.; Gamsizkan, H.; Guler, A. M.; Karapinar, G.; Ocalan, K.; Ozpineci, A.; Serin, M.; Sever, R.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Isildak, B.; Kaya, M.; Kaya, O.; Ozkorucuklu, S.; Bahtiyar, H.; Barlas, E.; Cankocak, K.; Günaydin, Y. O.; Vardarlı, F. I.; Yücel, M.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Frazier, R.; 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.; 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.; Ilic, J.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Ferguson, W.; Fulcher, J.; Futyan, D.; Gilbert, A.; Guneratne Bryer, A.; Hall, G.; Hatherell, Z.; Hays, J.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Marrouche, J.; Mathias, B.; Nandi, R.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Pioppi, M.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Sparrow, A.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Wakefield, S.; Wardle, N.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Heister, A.; Lawson, P.; Lazic, D.; Richardson, C.; Rohlf, J.; Sperka, D.; St. John, J.; Sulak, L.; Alimena, J.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Jabeen, S.; 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.; Kopecky, A.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Rutherford, B.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Tripathi, M.; Wilbur, S.; Yohay, R.; Andreev, V.; Cline, D.; Cousins, R.; Erhan, S.; Everaerts, P.; Farrell, C.; Felcini, M.; Hauser, J.; Ignatenko, M.; Jarvis, C.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Babb, J.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Jandir, P.; Lacroix, F.; Liu, H.; Long, O. R.; Luthra, A.; Malberti, M.; Nguyen, H.; Shrinivas, A.; Sturdy, J.; Sumowidagdo, S.; Wimpenny, S.; Andrews, W.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Evans, D.; Holzner, A.; Kelley, R.; Kovalskyi, D.; Lebourgeois, M.; Letts, J.; Macneill, I.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Wasserbaech, S.; Würthwein, F.; Yagil, A.; Yoo, J.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Incandela, J.; Justus, C.; Magaña Villalba, R.; Mccoll, N.; Pavlunin, V.; Richman, J.; Rossin, R.; Stuart, D.; To, W.; West, C.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Di Marco, E.; Duarte, J.; Kcira, D.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carroll, R.; Ferguson, T.; Iiyama, Y.; Jang, D. W.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Drell, B. R.; Ford, W. T.; Gaz, A.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chu, J.; Eggert, N.; Gibbons, L. K.; Hopkins, W.; Khukhunaishvili, A.; Kreis, B.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; 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.; Burkett, K.; Butler, J. N.; Chetluru, V.; 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.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Ratnikova, N.; 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.; Wu, W.; Yang, F.; Yun, J. C.; Acosta, D.; Avery, P.; Bourilkov, D.; Cheng, T.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Dobur, D.; Field, R. D.; Fisher, M.; Fu, Y.; Furic, I. K.; Hugon, J.; Kim, B.; Konigsberg, J.; Korytov, A.; Kropivnitskaya, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Skhirtladze, N.; Snowball, M.; Yelton, J.; Zakaria, M.; Gaultney, V.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Chen, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Dorney, B.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Akgun, U.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Gray, J.; Kenny, R. P.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Barfuss, A. F.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, 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.; Temple, J.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Dutta, V.; 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.; Yoon, A. S.; Zanetti, M.; Zhukova, V.; Dahmes, B.; De Benedetti, A.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Cremaldi, L. M.; Kroeger, R.; Oliveros, S.; Perera, L.; Sanders, D. A.; Summers, D.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Dolen, J.; Godshalk, A.; Iashvili, I.; Jain, S.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Nash, D.; Orimoto, T.; Trocino, D.; Wood, D.; Zhang, J.; Anastassov, A.; Hahn, K. A.; Kubik, A.; Lusito, L.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Berry, D.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Kolb, J.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Morse, D. M.; Pearson, T.; Planer, M.; Ruchti, R.; Slaunwhite, J.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Vuosalo, C.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Berry, E.; Elmer, P.; Halyo, V.; Hebda, P.; Hunt, A.; Jindal, P.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Raval, A.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zenz, S. C.; Zuranski, A.; Brownson, E.; Lopez, A.; Mendez, H.; Ramirez Vargas, J. E.; Alagoz, E.; Barnes, V. E.; Benedetti, D.; Bolla, G.; Bortoletto, D.; De Mattia, M.; Everett, A.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Merkel, P.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; 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.; Miner, D. C.; Petrillo, G.; Vishnevskiy, D.; Zielinski, M.; Bhatti, A.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Malik, S.; 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.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Rekovic, V.; Robles, J.; Salur, S.; Schnetzer, S.; Seitz, C.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; Yang, Z. C.; York, A.; Bouhali, O.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Sakuma, T.; Suarez, I.; Tatarinov, A.; Toback, D.; 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.; Gollapinni, S.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Belknap, D. A.; Borrello, L.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Duric, S.; Friis, E.; Grothe, M.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Klukas, J.; 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.; Woods, N.; CMS Collaboration

2014-08-01

A search for WVγ triple vector boson production is presented based on events containing a W boson decaying to a muon or an electron and a neutrino, a second V (W or Z) boson, and a photon. The data correspond to an integrated luminosity of 19.3 fb-1 collected in 2012 with the CMS detector at the LHC in pp collisions at √s =8 TeV. An upper limit of 311 fb on the cross section for the WVγ production process is obtained at 95% confidence level for photons with a transverse energy above 30 GeV and with an absolute value of pseudorapidity of less than 1.44. This limit is approximately a factor of 3.4 larger than the standard model predictions that are based on next-to-leading order QCD calculations. Since no evidence of anomalous WWγγ or WWZγ quartic gauge boson couplings is found, this paper presents the first experimental limits on the dimension-eight parameter fT,0 and the CP-conserving WWZγ parameters κ0W and κCW. Limits are also obtained for the WWγγ parameters a0W and aCW.

Accuracy in parameter estimation for targeted effects in structural equation modeling: sample size planning for narrow confidence intervals.

PubMed

Lai, Keke; Kelley, Ken

2011-06-01

In addition to evaluating a structural equation model (SEM) as a whole, often the model parameters are of interest and confidence intervals for those parameters are formed. Given a model with a good overall fit, it is entirely possible for the targeted effects of interest to have very wide confidence intervals, thus giving little information about the magnitude of the population targeted effects. With the goal of obtaining sufficiently narrow confidence intervals for the model parameters of interest, sample size planning methods for SEM are developed from the accuracy in parameter estimation approach. One method plans for the sample size so that the expected confidence interval width is sufficiently narrow. An extended procedure ensures that the obtained confidence interval will be no wider than desired, with some specified degree of assurance. A Monte Carlo simulation study was conducted that verified the effectiveness of the procedures in realistic situations. The methods developed have been implemented in the MBESS package in R so that they can be easily applied by researchers. © 2011 American Psychological Association

Implicit assimilation for marine ecological models

NASA Astrophysics Data System (ADS)

Weir, B.; Miller, R.; Spitz, Y. H.

2012-12-01

We use a new data assimilation method to estimate the parameters of a marine ecological model. At a given point in the ocean, the estimated values of the parameters determine the behaviors of the modeled planktonic groups, and thus indicate which species are dominant. To begin, we assimilate in situ observations, e.g., the Bermuda Atlantic Time-series Study, the Hawaii Ocean Time-series, and Ocean Weather Station Papa. From there, we estimate the parameters at surrounding points in space based on satellite observations of ocean color. Given the variation of the estimated parameters, we divide the ocean into regions meant to represent distinct ecosystems. An important feature of the data assimilation approach is that it refines the confidence limits of the optimal Gaussian approximation to the distribution of the parameters. This enables us to determine the ecological divisions with greater accuracy.

Sample variance in weak lensing: How many simulations are required?

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

Petri, Andrea; May, Morgan; Haiman, Zoltan

Constraining cosmology using weak gravitational lensing consists of comparing a measured feature vector of dimension N b with its simulated counterpart. An accurate estimate of the N b × N b feature covariance matrix C is essential to obtain accurate parameter confidence intervals. When C is measured from a set of simulations, an important question is how large this set should be. To answer this question, we construct different ensembles of N r realizations of the shear field, using a common randomization procedure that recycles the outputs from a smaller number N s ≤ N r of independent ray-tracing N-bodymore » simulations. We study parameter confidence intervals as a function of (N s, N r) in the range 1 ≤ N s ≤ 200 and 1 ≤ N r ≲ 105. Previous work [S. Dodelson and M. D. Schneider, Phys. Rev. D 88, 063537 (2013)] has shown that Gaussian noise in the feature vectors (from which the covariance is estimated) lead, at quadratic order, to an O(1/N r) degradation of the parameter confidence intervals. Using a variety of lensing features measured in our simulations, including shear-shear power spectra and peak counts, we show that cubic and quartic covariance fluctuations lead to additional O(1/N 2 r) error degradation that is not negligible when N r is only a factor of few larger than N b. We study the large N r limit, and find that a single, 240 Mpc/h sized 512 3-particle N-body simulation (N s = 1) can be repeatedly recycled to produce as many as N r = few × 10 4 shear maps whose power spectra and high-significance peak counts can be treated as statistically independent. Lastly, a small number of simulations (N s = 1 or 2) is sufficient to forecast parameter confidence intervals at percent accuracy.« less

Sample variance in weak lensing: How many simulations are required?

DOE PAGES

Petri, Andrea; May, Morgan; Haiman, Zoltan

2016-03-24

Constraining cosmology using weak gravitational lensing consists of comparing a measured feature vector of dimension N b with its simulated counterpart. An accurate estimate of the N b × N b feature covariance matrix C is essential to obtain accurate parameter confidence intervals. When C is measured from a set of simulations, an important question is how large this set should be. To answer this question, we construct different ensembles of N r realizations of the shear field, using a common randomization procedure that recycles the outputs from a smaller number N s ≤ N r of independent ray-tracing N-bodymore » simulations. We study parameter confidence intervals as a function of (N s, N r) in the range 1 ≤ N s ≤ 200 and 1 ≤ N r ≲ 105. Previous work [S. Dodelson and M. D. Schneider, Phys. Rev. D 88, 063537 (2013)] has shown that Gaussian noise in the feature vectors (from which the covariance is estimated) lead, at quadratic order, to an O(1/N r) degradation of the parameter confidence intervals. Using a variety of lensing features measured in our simulations, including shear-shear power spectra and peak counts, we show that cubic and quartic covariance fluctuations lead to additional O(1/N 2 r) error degradation that is not negligible when N r is only a factor of few larger than N b. We study the large N r limit, and find that a single, 240 Mpc/h sized 512 3-particle N-body simulation (N s = 1) can be repeatedly recycled to produce as many as N r = few × 10 4 shear maps whose power spectra and high-significance peak counts can be treated as statistically independent. Lastly, a small number of simulations (N s = 1 or 2) is sufficient to forecast parameter confidence intervals at percent accuracy.« less

The massive halos of spiral galaxies

NASA Technical Reports Server (NTRS)

Zaritsky, Dennis; White, Simon D. M.

1994-01-01

We use a sample of satellite galaxies to demonstrate the existence of extended massive dark halos around spiral galaxies. Isolated spirals with rotation velocities near 250 km/s have a typical halo mass within 200 kpc of 1.5-2.6 x 10(exp 12) solar mass (90% confidence range for H(sub 0) = 75 km/s/Mpc). This result is most easily derived using standard mass estimator techniques, but such techniques do not account for the strong observational selection effects in the sample, nor for the extended mass distributions that the data imply. These complications can be addressed using scale-free models similar to those previously employed to study binary galaxies. When satellite velocities are assumed isotropic, both methods imply massive and extended halos. However, the derived masses depend sensitively on the assumed shape of satellite orbits. Furthermore, both methods ignore the fact that many of the satellites in the sample have orbital periods comparable to the Hubble time. The orbital phases of such satellites cannot be random, and their distribution in radius cannot be freely adjusted; rather these properties reflect ongoing infall onto the outer halos of their primaries. We use detailed dynamical models for halo formation to evaluate these problems, and we devise a maximum likelihood technique for estimating the parameters of such models from the data. The most strongly constrained parameter is the mass within 200-300 kpc, giving the confidence limits quoted above. The eccentricity, e, of satellite orbits is also strongly constrained, 0.50 less than e less than 0.88 at 90% confidence, implying a near-isotropic distribution of satellite velocities. The cosmic density parameter in the vicinity of our isolated halos exceeds 0.13 at 90% confidence, with preferred values exceeding 0.3.

CALCULATION OF NONLINEAR CONFIDENCE AND PREDICTION INTERVALS FOR GROUND-WATER FLOW MODELS.

USGS Publications Warehouse

Cooley, Richard L.; Vecchia, Aldo V.

1987-01-01

A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. Application of the method to a hypothetical example showed that inclusion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals.

Studies of cluster X-ray sources, energy spectra for the Perseus, Virgo, and Coma clusters

NASA Technical Reports Server (NTRS)

Kellogg, E.; Baldwin, J. R.; Koch, D.

1975-01-01

Final Uhuru X-ray differential-energy spectra are presented for the Perseus, Virgo, and Coma clusters. Power-law and isothermal bremsstrahlung model spectra with low-energy cutoffs are given, and the energy-dependent Gaunt factor is calculated for the bremsstrahlung. The spectra, which are best fits to the Uhuru data between 2 and 10 keV, are compared with previous observations of these sources in the energy range from 0.1 to 100 keV. The problem of parameter estimation is discussed, error bars with 68% confidence are given for the independently determined slope and cutoff parameters, and the 68% confidence limits are plotted for the fitted spectral functions. The data for Perseus above 20 keV marginally favor the bremsstrahlung fit, those for Virgo between 0.25 and 1.0 keV clearly favor that curve, and those for Coma indicate a low-energy turnover or cutoff. Implications of such a cutoff are briefly discussed.

Cosmological constraints on Brans-Dicke theory.

PubMed

Avilez, A; Skordis, C

2014-07-04

We report strong cosmological constraints on the Brans-Dicke (BD) theory of gravity using cosmic microwave background data from Planck. We consider two types of models. First, the initial condition of the scalar field is fixed to give the same effective gravitational strength Geff today as the one measured on Earth, GN. In this case, the BD parameter ω is constrained to ω>692 at the 99% confidence level, an order of magnitude improvement over previous constraints. In the second type, the initial condition for the scalar is a free parameter leading to a somewhat stronger constraint of ω>890, while Geff is constrained to 0.981

Search for Higgs boson pair production in events with two bottom quarks and two tau leptons in proton-proton collisions at √{ s } = 13TeV

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.; Strauss, J.; 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.; Olbrechts, A.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; 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.; 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.; 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.; 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.; El-khateeb, E.; Elgammal, S.; Mohamed, 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.; Regnard, S.; 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.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Albert, A.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; 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.; 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.; Placakyte, R.; 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.; Gilbert, A.; 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.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; 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.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Bhawandeep, U.; 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.; Sharma, V.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; 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.; Caputo, 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.; 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.; 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.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Fantinel, S.; Fanzago, F.; Gozzelino, A.; Lacaprara, S.; Lujan, P.; Margoni, M.; Meneguzzo, A. T.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Fallavollita, F.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; 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.; Bernardini, J.; 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.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Monteno, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, J.; Lee, S.; Lee, S. W.; 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.; Ryu, G.; 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.; Duran-Osuna, M. C.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Lopez-Fernandez, R.; Mejia Guisao, J.; Rabadán-Trejo, R. I.; Ramirez-Sanchez, G.; Reyes-Almanza, R.; 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.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Calpas, B.; Di Francesco, A.; Faccioli, P.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. 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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.; Das, S.; 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.; 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.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; 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.; Alyari, M.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; 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.; Benaglia, A.; 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.; 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.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; 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

2018-03-01

A search for the production of Higgs boson pairs in proton-proton collisions at a centre-of-mass energy of 13 TeV is presented, using a data sample corresponding to an integrated luminosity of 35.9fb-1 collected with the CMS detector at the LHC. Events with one Higgs boson decaying into two bottom quarks and the other decaying into two τ leptons are explored to investigate both resonant and nonresonant production mechanisms. The data are found to be consistent, within uncertainties, with the standard model background predictions. For resonant production, upper limits at the 95% confidence level are set on the production cross section for Higgs boson pairs as a function of the hypothesized resonance mass and are interpreted in the context of the minimal supersymmetric standard model. For nonresonant production, upper limits on the production cross section constrain the parameter space for anomalous Higgs boson couplings. The observed (expected) upper limit at 95% confidence level corresponds to about 30 (25) times the prediction of the standard model.

Measurement of neutrino and antineutrino oscillations by the T2K experiment including a new additional sample of νe interactions at the far detector

NASA Astrophysics Data System (ADS)

Abe, K.; Amey, J.; Andreopoulos, C.; Antonova, M.; Aoki, S.; Ariga, A.; Ashida, Y.; Ban, S.; Barbi, M.; Barker, G. J.; Barr, G.; Barry, C.; Batkiewicz, M.; Berardi, V.; Berkman, S.; Bhadra, S.; Bienstock, S.; Blondel, A.; Bolognesi, S.; Bordoni, S.; Boyd, S. B.; Brailsford, D.; Bravar, A.; Bronner, C.; Buizza Avanzini, M.; Calland, R. G.; Campbell, T.; Cao, S.; Cartwright, S. L.; Catanesi, M. G.; Cervera, A.; Chappell, A.; Checchia, C.; Cherdack, D.; Chikuma, N.; Christodoulou, G.; Coleman, J.; Collazuol, G.; Coplowe, D.; Cudd, A.; Dabrowska, A.; De Rosa, G.; Dealtry, T.; Denner, P. F.; Dennis, S. R.; Densham, C.; Di Lodovico, F.; Dolan, S.; Drapier, O.; Duffy, K. E.; Dumarchez, J.; Dunne, P.; Emery-Schrenk, S.; Ereditato, A.; Feusels, T.; Finch, A. J.; Fiorentini, G. A.; Fiorillo, G.; Friend, M.; Fujii, Y.; Fukuda, D.; Fukuda, Y.; Garcia, A.; Giganti, C.; Gizzarelli, F.; Golan, T.; Gonin, M.; Hadley, D. R.; Haegel, L.; Haigh, J. T.; Hansen, D.; Harada, J.; Hartz, M.; Hasegawa, T.; Hastings, N. C.; Hayashino, T.; Hayato, Y.; Hillairet, A.; Hiraki, T.; Hiramoto, A.; Hirota, S.; Hogan, M.; Holeczek, J.; Hosomi, F.; Huang, K.; Ichikawa, A. K.; Ikeda, M.; Imber, J.; Insler, J.; Intonti, R. A.; Ishida, T.; Ishii, T.; Iwai, E.; Iwamoto, K.; Izmaylov, A.; Jamieson, B.; Jiang, M.; Johnson, S.; Jonsson, P.; Jung, C. K.; Kabirnezhad, M.; Kaboth, A. C.; Kajita, T.; Kakuno, H.; Kameda, J.; Karlen, D.; Katori, T.; Kearns, E.; Khabibullin, M.; Khotjantsev, A.; Kim, H.; Kim, J.; King, S.; Kisiel, J.; Knight, A.; Knox, A.; Kobayashi, T.; Koch, L.; Koga, T.; Koller, P. P.; Konaka, A.; Kormos, L. L.; Koshio, Y.; Kowalik, K.; Kudenko, Y.; Kurjata, R.; Kutter, T.; Lagoda, J.; Lamont, I.; Lamoureux, M.; Lasorak, P.; Laveder, M.; Lawe, M.; Licciardi, M.; Lindner, T.; Liptak, Z. J.; Litchfield, R. P.; Li, X.; Longhin, A.; Lopez, J. P.; Lou, T.; Ludovici, L.; Lu, X.; Magaletti, L.; Mahn, K.; Malek, M.; Manly, S.; Maret, L.; Marino, A. D.; Martin, J. F.; Martins, P.; Martynenko, S.; Maruyama, T.; Matveev, V.; Mavrokoridis, K.; Ma, W. Y.; Mazzucato, E.; McCarthy, M.; McCauley, N.; McFarland, K. S.; McGrew, C.; Mefodiev, A.; Metelko, C.; Mezzetto, M.; Minamino, A.; Mineev, O.; Mine, S.; Missert, A.; Miura, M.; Moriyama, S.; Morrison, J.; Mueller, Th. A.; Nakadaira, T.; Nakahata, M.; Nakamura, K. G.; Nakamura, K.; Nakamura, K. D.; Nakanishi, Y.; Nakayama, S.; Nakaya, T.; Nakayoshi, K.; Nantais, C.; Nielsen, C.; Nishikawa, K.; Nishimura, Y.; Novella, P.; Nowak, J.; O'Keeffe, H. M.; Okumura, K.; Okusawa, T.; Oryszczak, W.; Oser, S. M.; Ovsyannikova, T.; Owen, R. A.; Oyama, Y.; Palladino, V.; Palomino, J. L.; Paolone, V.; Patel, N. D.; Paudyal, P.; Pavin, M.; Payne, D.; Petrov, Y.; Pickering, L.; Pinzon Guerra, E. S.; Pistillo, C.; Popov, B.; Posiadala-Zezula, M.; Poutissou, J.-M.; Pritchard, A.; Przewlocki, P.; Quilain, B.; Radermacher, T.; Radicioni, E.; Ratoff, P. N.; Rayner, M. A.; Reinherz-Aronis, E.; Riccio, C.; Rodrigues, P. A.; Rondio, E.; Rossi, B.; Roth, S.; Ruggeri, A. C.; Rychter, A.; Sakashita, K.; Sánchez, F.; Scantamburlo, E.; Scholberg, K.; Schwehr, J.; Scott, M.; Seiya, Y.; Sekiguchi, T.; Sekiya, H.; Sgalaberna, D.; Shah, R.; Shaikhiev, A.; Shaker, F.; Shaw, D.; Shiozawa, M.; Shirahige, T.; Smy, M.; Sobczyk, J. T.; Sobel, H.; Steinmann, J.; Stewart, T.; Stowell, P.; Suda, Y.; Suvorov, S.; Suzuki, A.; Suzuki, S. Y.; Suzuki, Y.; Tacik, R.; Tada, M.; Takeda, A.; Takeuchi, Y.; Tamura, R.; Tanaka, H. K.; Tanaka, H. A.; Thakore, T.; Thompson, L. F.; Tobayama, S.; Toki, W.; Tomura, T.; Tsukamoto, T.; Tzanov, M.; Vagins, M.; Vallari, Z.; Vasseur, G.; Vilela, C.; Vladisavljevic, T.; Wachala, T.; Walter, C. W.; Wark, D.; Wascko, M. O.; Weber, A.; Wendell, R.; Wilking, M. J.; Wilkinson, C.; Wilson, J. R.; Wilson, R. J.; Wret, C.; Yamada, Y.; Yamamoto, K.; Yanagisawa, C.; Yano, T.; Yen, S.; Yershov, N.; Yokoyama, M.; Yu, M.; Zalewska, A.; Zalipska, J.; Zambelli, L.; Zaremba, K.; Ziembicki, M.; Zimmerman, E. D.; Zito, M.; T2K Collaboration

2017-11-01

The T2K experiment reports an updated analysis of neutrino and antineutrino oscillations in appearance and disappearance channels. A sample of electron neutrino candidates at Super-Kamiokande in which a pion decay has been tagged is added to the four single-ring samples used in previous T2K oscillation analyses. Through combined analyses of these five samples, simultaneous measurements of four oscillation parameters, |Δ m322 |, sin2θ23, sin2θ13, and δCP and of the mass ordering are made. A set of studies of simulated data indicates that the sensitivity to the oscillation parameters is not limited by neutrino interaction model uncertainty. Multiple oscillation analyses are performed, and frequentist and Bayesian intervals are presented for combinations of the oscillation parameters with and without the inclusion of reactor constraints on sin2θ13. When combined with reactor measurements, the hypothesis of C P conservation (δCP=0 or π ) is excluded at 90% confidence level. The 90% confidence region for δCP is [-2.95 ,-0.44 ] ([-1.47 ,-1.27 ] ) for normal (inverted) ordering. The central values and 68% confidence intervals for the other oscillation parameters for normal (inverted) ordering are Δ m322=2.54 ±0.08 (2.51 ±0.08 )×10-3 eV2/c4 and sin2θ23 =0.5 5-0.09+0.05 (0.5 5-0.08+0.05), compatible with maximal mixing. In the Bayesian analysis, the data weakly prefer normal ordering (Bayes factor 3.7) and the upper octant for sin2θ23 (Bayes factor 2.4).

Towards Limits on Neutrino Mixing Parameters from Nucleosynthesis in the Big Bang and Supernovae

NASA Astrophysics Data System (ADS)

Cardall, Christian Young

1997-11-01

Astrophysical environments can often provide stricter limits on neutrino mass and mixing parameters than terrestrial experiments. However, before firm limits can be found, there must be confidence in the understanding of the astrophysical environment being used to make these limits. In this dissertation, progress towards limits on neutrino mixing parameters from big bang nucleosynthesis and supernova r-process nucleosynthesis is sought. By way of assessment of current knowledge of neutrino oscillation parameters, we examine the potential for a 'natural' three-neutrino mixing scheme (one without sterile neutrinos) to satisfy available data and astrophysical arguments. A small parameter space currently exists for a natural three-neutrino oscillation solution meeting known constraints. If such a solution is ruled out, and current hints about neutrino oscillations are confirmed, mixing between active and sterile neutrinos will probably be required. Because mixing between active and sterile neutrinos with parameters appropriate for the atmospheric or solar neutrino problems increases the primordial 4He abundance, big bang nucleosynthesis considerations can place limits on such mixing. In the present work the overall consistency of standard big bang nucleosynthesis is discussed in light of recent discordant determinations of the primordial deuterium abundance. Cosmological considerations favor a larger baryon density, which supports the lower reported value of D/H. Studies of limits on active-sterile neutrino mixing derived from big bang nucleosynthesis considerations are here extended to consider the dependance of these constraints on the primordial deuterium abundance. If the neutrino-heated ejecta in the post-core-bounce supernova environment is the site of r-process nucleosynthesis, limits can be placed on mixing between νe, and νsbμ, or νsbτ. Refined limits will require a better understanding of this r-process environment, since current supernova models do not show a completely successful r-process. In this work it is shown that general relativistic effects associated with a more compact supernova core can provide more suitable conditions for the r-process. As a step towards analyzing the effects of neutrino mixing in such a relativistic environment, neutrino oscillations in curved spacetime are studied.

Reporting Confidence Intervals and Effect Sizes: Collecting the Evidence

ERIC Educational Resources Information Center

Zientek, Linda Reichwein; Ozel, Z. Ebrar Yetkiner; Ozel, Serkan; Allen, Jeff

2012-01-01

Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…

Quality Management and Calibration

NASA Astrophysics Data System (ADS)

Merkus, Henk G.

Good specification of a product’s performance requires adequate characterization of relevant properties. Particulate products are usually characterized by some PSD, shape or porosity parameter(s). For proper characterization, adequate sampling, dispersion, and measurement procedures should be available or developed and skilful personnel should use appropriate, well-calibrated/qualified equipment. The characterization should be executed, in agreement with customers, in a wellorganized laboratory. All related aspects should be laid down in a quality handbook. The laboratory should provide proof for its capability to perform the characterization of stated products and/or reference materials within stated confidence limits. This can be done either by internal validation and audits or by external GLP accreditation.

A comparison of statistical methods for evaluating matching performance of a biometric identification device: a preliminary report

NASA Astrophysics Data System (ADS)

Schuckers, Michael E.; Hawley, Anne; Livingstone, Katie; Mramba, Nona

2004-08-01

Confidence intervals are an important way to assess and estimate a parameter. In the case of biometric identification devices, several approaches to confidence intervals for an error rate have been proposed. Here we evaluate six of these methods. To complete this evaluation, we simulate data from a wide variety of parameter values. This data are simulated via a correlated binary distribution. We then determine how well these methods do at what they say they do: capturing the parameter inside the confidence interval. In addition, the average widths of the various confidence intervals are recorded for each set of parameters. The complete results of this simulation are presented graphically for easy comparison. We conclude by making a recommendation regarding which method performs best.

An Analysis of Recent Measurements of the Temperature of the Cosmic Microwave Background Radiation

DOE R&D Accomplishments Database

Smoot, G.; Levin, S. M.; Witebsky, C.; De Amici, G.; Rephaeli, Y.

1987-07-01

This paper presents an analysis of the results of recent temperature measurements of the cosmic microwave background radiation (CMBR). The observations for wavelengths longer than 0.1 cum are well fit by a blackbody spectrum at 2.74{+ or -}0.0w K; however, including the new data of Matsumoto et al. (1987) the result is no longer consistent with a Planckian spectrum. The data are described by a Thomson-distortion parameter u=0.021{+ or -}0.002 and temperature 2.823{+ or -}0.010 K at the 68% confidence level. Fitting the low-frequency data to a Bose-Einstein spectral distortion yields a 95% confidence level upper limit of 1.4 x 10{sup -2} on the chemical potential mu{sub 0}. These limits on spectral distortions place restrictions on a number of potentially interesting sources of energy release to the CMBR, including the hot intergalactic medium proposed as the source of the X-ray background.

Searches for Sterile Neutrinos with the IceCube Detector

NASA Astrophysics Data System (ADS)

Aartsen, M. G.; Abraham, K.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Ahrens, M.; Altmann, D.; Andeen, K.; Anderson, T.; Ansseau, I.; Anton, G.; Archinger, M.; Argüelles, C.; Arlen, T. C.; Auffenberg, J.; Axani, S.; Bai, X.; Barwick, S. W.; Baum, V.; Bay, R.; Beatty, J. J.; Becker Tjus, J.; Becker, K.-H.; BenZvi, S.; Berghaus, P.; Berley, D.; Bernardini, E.; Bernhard, A.; Besson, D. Z.; Binder, G.; Bindig, D.; Blaufuss, E.; Blot, S.; Boersma, D. J.; Bohm, C.; Börner, M.; Bos, F.; Bose, D.; Böser, S.; Botner, O.; Braun, J.; Brayeur, L.; Bretz, H.-P.; Burgman, A.; Casey, J.; Casier, M.; Cheung, E.; Chirkin, D.; Christov, A.; Clark, K.; Classen, L.; Coenders, S.; Collin, G. H.; Conrad, J. M.; Cowen, D. F.; Cruz Silva, A. H.; Daughhetee, J.; Davis, J. C.; Day, M.; de André, J. P. A. M.; De Clercq, C.; del Pino Rosendo, E.; Dembinski, H.; De Ridder, S.; Desiati, P.; de Vries, K. D.; de Wasseige, G.; de With, M.; DeYoung, T.; Díaz-Vélez, J. C.; di Lorenzo, V.; Dujmovic, H.; Dumm, J. P.; Dunkman, M.; Eberhardt, B.; Ehrhardt, T.; Eichmann, B.; Euler, S.; Evenson, P. A.; Fahey, S.; Fazely, A. R.; Feintzeig, J.; Felde, J.; Filimonov, K.; Finley, C.; Flis, S.; Fösig, C.-C.; Fuchs, T.; Gaisser, T. K.; Gaior, R.; Gallagher, J.; Gerhardt, L.; Ghorbani, K.; Giang, W.; Gladstone, L.; Glüsenkamp, T.; Goldschmidt, A.; Golup, G.; Gonzalez, J. G.; Góra, D.; Grant, D.; Griffith, Z.; Haj Ismail, A.; Hallgren, A.; Halzen, F.; Hansen, E.; Hanson, K.; Hebecker, D.; Heereman, D.; Helbing, K.; Hellauer, R.; Hickford, S.; Hignight, J.; Hill, G. C.; Hoffman, K. D.; Hoffmann, R.; Holzapfel, K.; Homeier, A.; Hoshina, K.; Huang, F.; Huber, M.; Huelsnitz, W.; Hultqvist, K.; In, S.; Ishihara, A.; Jacobi, E.; Japaridze, G. S.; Jeong, M.; Jero, K.; Jones, B. J. P.; Jurkovic, M.; Kappes, A.; Karg, T.; Karle, A.; Katz, U.; Kauer, M.; Keivani, A.; Kelley, J. L.; Kheirandish, A.; Kim, M.; Kintscher, T.; Kiryluk, J.; Kittler, T.; Klein, S. R.; Kohnen, G.; Koirala, R.; Kolanoski, H.; Köpke, L.; Kopper, C.; Kopper, S.; Koskinen, D. J.; Kowalski, M.; Krings, K.; Kroll, M.; Krückl, G.; Krüger, C.; Kunnen, J.; Kunwar, S.; Kurahashi, N.; Kuwabara, T.; Labare, M.; Lanfranchi, J. L.; Larson, M. J.; Lennarz, D.; Lesiak-Bzdak, M.; Leuermann, M.; Lu, L.; Lünemann, J.; Madsen, J.; Maggi, G.; Mahn, K. B. M.; Mancina, S.; Mandelartz, M.; Maruyama, R.; Mase, K.; Maunu, R.; McNally, F.; Meagher, K.; Medici, M.; Meier, M.; Meli, A.; Menne, T.; Merino, G.; Meures, T.; Miarecki, S.; Middell, E.; Mohrmann, L.; Montaruli, T.; Moulai, M.; Nahnhauer, R.; Naumann, U.; Neer, G.; Niederhausen, H.; Nowicki, S. C.; Nygren, D. R.; Obertacke Pollmann, A.; Olivas, A.; Omairat, A.; O'Murchadha, A.; Palczewski, T.; Pandya, H.; Pankova, D. V.; Pepper, J. A.; Pérez de los Heros, C.; Pfendner, C.; Pieloth, D.; Pinat, E.; Posselt, J.; Price, P. B.; Przybylski, G. T.; Quinnan, M.; Raab, C.; Rameez, M.; Rawlins, K.; Relich, M.; Resconi, E.; Rhode, W.; Richman, M.; Riedel, B.; Robertson, S.; Rott, C.; Ruhe, T.; Ryckbosch, D.; Rysewyk, D.; Sabbatini, L.; Salvado, J.; Sanchez Herrera, S. E.; Sandrock, A.; Sandroos, J.; Sarkar, S.; Satalecka, K.; Schlunder, P.; Schmidt, T.; Schöneberg, S.; Schönwald, A.; Seckel, D.; Seunarine, S.; Soldin, D.; Song, M.; Spiczak, G. M.; Spiering, C.; Stamatikos, M.; Stanev, T.; Stasik, A.; Steuer, A.; Stezelberger, T.; Stokstad, R. G.; Stößl, A.; Ström, R.; Strotjohann, N. L.; Sullivan, G. W.; Sutherland, M.; Taavola, H.; Taboada, I.; Tatar, J.; Ter-Antonyan, S.; Terliuk, A.; Tešić, G.; Tilav, S.; Toale, P. A.; Tobin, M. N.; Toscano, S.; Tosi, D.; Tselengidou, M.; Turcati, A.; Unger, E.; Usner, M.; Vallecorsa, S.; Vandenbroucke, J.; van Eijndhoven, N.; Vanheule, S.; van Rossem, M.; van Santen, J.; Veenkamp, J.; Voge, M.; Vraeghe, M.; Walck, C.; Wallace, A.; Wandkowsky, N.; Weaver, Ch.; Wendt, C.; Westerhoff, S.; Whelan, B. J.; Wiebe, K.; Wille, L.; Williams, D. R.; Wills, L.; Wissing, H.; Wolf, M.; Wood, T. R.; Woolsey, E.; Woschnagg, K.; Xu, D. L.; Xu, X. W.; Xu, Y.; Yanez, J. P.; Yodh, G.; Yoshida, S.; Zoll, M.; IceCube Collaboration

2016-08-01

The IceCube neutrino telescope at the South Pole has measured the atmospheric muon neutrino spectrum as a function of zenith angle and energy in the approximate 320 GeV to 20 TeV range, to search for the oscillation signatures of light sterile neutrinos. No evidence for anomalous νμ or ν¯μ disappearance is observed in either of two independently developed analyses, each using one year of atmospheric neutrino data. New exclusion limits are placed on the parameter space of the 3 +1 model, in which muon antineutrinos experience a strong Mikheyev-Smirnov-Wolfenstein-resonant oscillation. The exclusion limits extend to sin22 θ24≤0.02 at Δ m2˜0.3 eV2 at the 90% confidence level. The allowed region from global analysis of appearance experiments, including LSND and MiniBooNE, is excluded at approximately the 99% confidence level for the global best-fit value of |Ue 4 |2 .

Searches for Sterile Neutrinos with the IceCube Detector.

PubMed

Aartsen, M G; Abraham, K; Ackermann, M; Adams, J; Aguilar, J A; Ahlers, M; Ahrens, M; Altmann, D; Andeen, K; Anderson, T; Ansseau, I; Anton, G; Archinger, M; Argüelles, C; Arlen, T C; Auffenberg, J; Axani, S; Bai, X; Barwick, S W; Baum, V; Bay, R; Beatty, J J; Becker Tjus, J; Becker, K-H; BenZvi, S; Berghaus, P; Berley, D; Bernardini, E; Bernhard, A; Besson, D Z; Binder, G; Bindig, D; Blaufuss, E; Blot, S; Boersma, D J; Bohm, C; Börner, M; Bos, F; Bose, D; Böser, S; Botner, O; Braun, J; Brayeur, L; Bretz, H-P; Burgman, A; Casey, J; Casier, M; Cheung, E; Chirkin, D; Christov, A; Clark, K; Classen, L; Coenders, S; Collin, G H; Conrad, J M; Cowen, D F; Cruz Silva, A H; Daughhetee, J; Davis, J C; Day, M; de André, J P A M; De Clercq, C; Del Pino Rosendo, E; Dembinski, H; De Ridder, S; Desiati, P; de Vries, K D; de Wasseige, G; de With, M; DeYoung, T; Díaz-Vélez, J C; di Lorenzo, V; Dujmovic, H; Dumm, J P; Dunkman, M; Eberhardt, B; Ehrhardt, T; Eichmann, B; Euler, S; Evenson, P A; Fahey, S; Fazely, A R; Feintzeig, J; Felde, J; Filimonov, K; Finley, C; Flis, S; Fösig, C-C; Fuchs, T; Gaisser, T K; Gaior, R; Gallagher, J; Gerhardt, L; Ghorbani, K; Giang, W; Gladstone, L; Glüsenkamp, T; Goldschmidt, A; Golup, G; Gonzalez, J G; Góra, D; Grant, D; Griffith, Z; Haj Ismail, A; Hallgren, A; Halzen, F; Hansen, E; Hanson, K; Hebecker, D; Heereman, D; Helbing, K; Hellauer, R; Hickford, S; Hignight, J; Hill, G C; Hoffman, K D; Hoffmann, R; Holzapfel, K; Homeier, A; Hoshina, K; Huang, F; Huber, M; Huelsnitz, W; Hultqvist, K; In, S; Ishihara, A; Jacobi, E; Japaridze, G S; Jeong, M; Jero, K; Jones, B J P; Jurkovic, M; Kappes, A; Karg, T; Karle, A; Katz, U; Kauer, M; Keivani, A; Kelley, J L; Kheirandish, A; Kim, M; Kintscher, T; Kiryluk, J; Kittler, T; Klein, S R; Kohnen, G; Koirala, R; Kolanoski, H; Köpke, L; Kopper, C; Kopper, S; Koskinen, D J; Kowalski, M; Krings, K; Kroll, M; Krückl, G; Krüger, C; Kunnen, J; Kunwar, S; Kurahashi, N; Kuwabara, T; Labare, M; Lanfranchi, J L; Larson, M J; Lennarz, D; Lesiak-Bzdak, M; Leuermann, M; Lu, L; Lünemann, J; Madsen, J; Maggi, G; Mahn, K B M; Mancina, S; Mandelartz, M; Maruyama, R; Mase, K; Maunu, R; McNally, F; Meagher, K; Medici, M; Meier, M; Meli, A; Menne, T; Merino, G; Meures, T; Miarecki, S; Middell, E; Mohrmann, L; Montaruli, T; Moulai, M; Nahnhauer, R; Naumann, U; Neer, G; Niederhausen, H; Nowicki, S C; Nygren, D R; Obertacke Pollmann, A; Olivas, A; Omairat, A; O'Murchadha, A; Palczewski, T; Pandya, H; Pankova, D V; Pepper, J A; Pérez de Los Heros, C; Pfendner, C; Pieloth, D; Pinat, E; Posselt, J; Price, P B; Przybylski, G T; Quinnan, M; Raab, C; Rameez, M; Rawlins, K; Relich, M; Resconi, E; Rhode, W; Richman, M; Riedel, B; Robertson, S; Rott, C; Ruhe, T; Ryckbosch, D; Rysewyk, D; Sabbatini, L; Salvado, J; Sanchez Herrera, S E; Sandrock, A; Sandroos, J; Sarkar, S; Satalecka, K; Schlunder, P; Schmidt, T; Schöneberg, S; Schönwald, A; Seckel, D; Seunarine, S; Soldin, D; Song, M; Spiczak, G M; Spiering, C; Stamatikos, M; Stanev, T; Stasik, A; Steuer, A; Stezelberger, T; Stokstad, R G; Stößl, A; Ström, R; Strotjohann, N L; Sullivan, G W; Sutherland, M; Taavola, H; Taboada, I; Tatar, J; Ter-Antonyan, S; Terliuk, A; Tešić, G; Tilav, S; Toale, P A; Tobin, M N; Toscano, S; Tosi, D; Tselengidou, M; Turcati, A; Unger, E; Usner, M; Vallecorsa, S; Vandenbroucke, J; van Eijndhoven, N; Vanheule, S; van Rossem, M; van Santen, J; Veenkamp, J; Voge, M; Vraeghe, M; Walck, C; Wallace, A; Wandkowsky, N; Weaver, Ch; Wendt, C; Westerhoff, S; Whelan, B J; Wiebe, K; Wille, L; Williams, D R; Wills, L; Wissing, H; Wolf, M; Wood, T R; Woolsey, E; Woschnagg, K; Xu, D L; Xu, X W; Xu, Y; Yanez, J P; Yodh, G; Yoshida, S; Zoll, M

2016-08-12

The IceCube neutrino telescope at the South Pole has measured the atmospheric muon neutrino spectrum as a function of zenith angle and energy in the approximate 320 GeV to 20 TeV range, to search for the oscillation signatures of light sterile neutrinos. No evidence for anomalous ν_{μ} or ν[over ¯]_{μ} disappearance is observed in either of two independently developed analyses, each using one year of atmospheric neutrino data. New exclusion limits are placed on the parameter space of the 3+1 model, in which muon antineutrinos experience a strong Mikheyev-Smirnov-Wolfenstein-resonant oscillation. The exclusion limits extend to sin^{2}2θ_{24}≤0.02 at Δm^{2}∼0.3  eV^{2} at the 90% confidence level. The allowed region from global analysis of appearance experiments, including LSND and MiniBooNE, is excluded at approximately the 99% confidence level for the global best-fit value of |U_{e4}|^{2}.

Evaluation of the biophysical limitations on photosynthesis of four varietals of Brassica rapa

NASA Astrophysics Data System (ADS)

Pleban, J. R.; Mackay, D. S.; Aston, T.; Ewers, B.; Weinig, C.

2014-12-01

Evaluating performance of agricultural varietals can support the identification of genotypes that will increase yield and can inform management practices. The biophysical limitations of photosynthesis are amongst the key factors that necessitate evaluation. This study evaluated how four biophysical limitations on photosynthesis, stomatal response to vapor pressure deficit, maximum carboxylation rate by Rubisco (Ac), rate of photosynthetic electron transport (Aj) and triose phosphate use (At) vary between four Brassica rapa genotypes. Leaf gas exchange data was used in an ecophysiological process model to conduct this evaluation. The Terrestrial Regional Ecosystem Exchange Simulator (TREES) integrates the carbon uptake and utilization rate limiting factors for plant growth. A Bayesian framework integrated in TREES here used net A as the target to estimate the four limiting factors for each genotype. As a first step the Bayesian framework was used for outlier detection, with data points outside the 95% confidence interval of model estimation eliminated. Next parameter estimation facilitated the evaluation of how the limiting factors on A different between genotypes. Parameters evaluated included maximum carboxylation rate (Vcmax), quantum yield (ϕJ), the ratio between Vc-max and electron transport rate (J), and trios phosphate utilization (TPU). Finally, as trios phosphate utilization has been shown to not play major role in the limiting A in many plants, the inclusion of At in models was evaluated using deviance information criteria (DIC). The outlier detection resulted in a narrowing in the estimated parameter distributions allowing for greater differentiation of genotypes. Results show genotypes vary in the how limitations shape assimilation. The range in Vc-max , a key parameter in Ac, was 203.2 - 223.9 umol m-2 s-1 while the range in ϕJ, a key parameter in AJ, was 0.463 - 0.497 umol m-2 s-1. The added complexity of the TPU limitation did not improve model performance in the genotypes assessed based on DIC. By identifying how varietals differ in their biophysical limitations on photosynthesis genotype selection can be informed for agricultural goals. Further work aims at applying this approach to a fifth limiting factor on photosynthesis, mesophyll conductance.

Application of continuous normal-lognormal bivariate density functions in a sensitivity analysis of municipal solid waste landfill.

PubMed

Petrovic, Igor; Hip, Ivan; Fredlund, Murray D

2016-09-01

The variability of untreated municipal solid waste (MSW) shear strength parameters, namely cohesion and shear friction angle, with respect to waste stability problems, is of primary concern due to the strong heterogeneity of MSW. A large number of municipal solid waste (MSW) shear strength parameters (friction angle and cohesion) were collected from published literature and analyzed. The basic statistical analysis has shown that the central tendency of both shear strength parameters fits reasonably well within the ranges of recommended values proposed by different authors. In addition, it was established that the correlation between shear friction angle and cohesion is not strong but it still remained significant. Through use of a distribution fitting method it was found that the shear friction angle could be adjusted to a normal probability density function while cohesion follows the log-normal density function. The continuous normal-lognormal bivariate density function was therefore selected as an adequate model to ascertain rational boundary values ("confidence interval") for MSW shear strength parameters. It was concluded that a curve with a 70% confidence level generates a "confidence interval" within the reasonable limits. With respect to the decomposition stage of the waste material, three different ranges of appropriate shear strength parameters were indicated. Defined parameters were then used as input parameters for an Alternative Point Estimated Method (APEM) stability analysis on a real case scenario of the Jakusevec landfill. The Jakusevec landfill is the disposal site of the capital of Croatia - Zagreb. The analysis shows that in the case of a dry landfill the most significant factor influencing the safety factor was the shear friction angle of old, decomposed waste material, while in the case of a landfill with significant leachate level the most significant factor influencing the safety factor was the cohesion of old, decomposed waste material. The analysis also showed that a satisfactory level of performance with a small probability of failure was produced for the standard practice design of waste landfills as well as an analysis scenario immediately after the landfill closure. Copyright © 2015 Elsevier Ltd. All rights reserved.

Knowledge Confidence and Desire for Further Diabetes-Management Education among Nurses and Personal Support Workers in Long-Term Care.

PubMed

Vincent, Corita; Hall, Peter; Ebsary, Sally; Hannay, Scott; Hayes-Cardinal, Lynn; Husein, Nadira

2016-06-01

Diabetes care in the long-term care (LTC) setting is complicated by increased prevalence of comorbidities, age-related changes in medication tolerance, frailty and limited resources. Registered nurses (RNs), registered practical nurses (RPNs) and personal support workers (PSWs) are responsible for front-line diabetes care; however, there is limited formal diabetes education in this setting. The current study aimed to assess the knowledge confidence and desire for additional diabetes education among nurses and PSWs in the LTC setting. We studied 89 RNs, RPNs and PSWs (Mage=43.6, 94.3% female) in 2 LTC facilities in the Kitchener-Waterloo area who participated in an online survey assessing knowledge and confidence in 6 key areas of diabetes care (nutrition, insulin, oral medications, hypoglycemia, hyperglycemia and sick-day management). Interest in further diabetes education was also explored. Self-rated knowledge and confidence were generally moderate to high, ranging from 46% to 79% being moderately to very knowledgeable and from 61% to 74% being moderately to very confident. Knowledge and confidence was highest for nutrition and management of hypo- and hyperglycemia and lower for sick-day management, oral medications and insulin. There were significant differences between clinicians such that PSWs reported less knowledge and confidence than RNs and RPNs on most parameters. Among the whole sample, 85% wanted education about diabetes, and this rate did not vary by occupation. The most commonly reported areas for additional education concerning diabetes were for management of hypo- and hyperglycemia (30% to 31%) and insulin (31%). Overall, the findings indicate moderate levels of self-rated knowledge across diabetes care areas; however, most clinicians feel there is room for more diabetes-care education, particularly regarding insulin and management of hypo- and hyperglycemia. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Limits on cold dark matter cosmologies from new anisotropy bounds on the cosmic microwave background

NASA Technical Reports Server (NTRS)

Vittorio, Nicola; Meinhold, Peter; Lubin, Philip; Muciaccia, Pio Francesco; Silk, Joseph

1991-01-01

A self-consistent method is presented for comparing theoretical predictions of and observational upper limits on CMB anisotropy. New bounds on CDM cosmologies set by the UCSB South Pole experiment on the 1 deg angular scale are presented. An upper limit of 4.0 x 10 to the -5th is placed on the rms differential temperature anisotropy to a 95 percent confidence level and a power of the test beta = 55 percent. A lower limit of about 0.6/b is placed on the density parameter of cold dark matter universes with greater than about 3 percent baryon abundance and a Hubble constant of 50 km/s/Mpc, where b is the bias factor, equal to unity only if light traces mass.

Heterogeneity, histological features and DNA ploidy in oral carcinoma by image-based analysis.

PubMed

Diwakar, N; Sperandio, M; Sherriff, M; Brown, A; Odell, E W

2005-04-01

Oral squamous carcinomas appear heterogeneous on DNA ploidy analysis. However, this may be partly a result of sample dilution or the detection limit of techniques. The aim of this study was to determine whether oral squamous carcinomas are heterogeneous for ploidy status using image-based ploidy analysis and to determine whether ploidy status correlates with histological parameters. Multiple samples from 42 oral squamous carcinomas were analysed for DNA ploidy using an image-based system and scored for histological parameters. 22 were uniformly aneuploid, 1 uniformly tetraploid and 3 uniformly diploid. 16 appeared heterogeneous but only 8 appeared to be genuinely heterogeneous when minor ploidy histogram peaks were taken into account. Ploidy was closely related to nuclear pleomorphism but not differentiation. Sample variation, detection limits and diagnostic criteria account for much of the ploidy heterogeneity observed. Confident diagnosis of diploid status in an oral squamous cell carcinoma requires a minimum of 5 samples.

Revisiting CMB constraints on warm inflation

NASA Astrophysics Data System (ADS)

Arya, Richa; Dasgupta, Arnab; Goswami, Gaurav; Prasad, Jayanti; Rangarajan, Raghavan

2018-02-01

We revisit the constraints that Planck 2015 temperature, polarization and lensing data impose on the parameters of warm inflation. To this end, we study warm inflation driven by a single scalar field with a quartic self interaction potential in the weak dissipative regime. We analyse the effect of the parameters of warm inflation, namely, the inflaton self coupling λ and the inflaton dissipation parameter QP on the CMB angular power spectrum. We constrain λ and QP for 50 and 60 number of e-foldings with the full Planck 2015 data (TT, TE, EE + lowP and lensing) by performing a Markov-Chain Monte Carlo analysis using the publicly available code CosmoMC and obtain the joint as well as marginalized distributions of those parameters. We present our results in the form of mean and 68 % confidence limits on the parameters and also highlight the degeneracy between λ and QP in our analysis. From this analysis we show how warm inflation parameters can be well constrained using the Planck 2015 data.

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

Dale, R.; Sáez, D., E-mail: rdale@umh.es, E-mail: diego.saez@uv.es

The vector-tensor (VT) theory of gravitation revisited in this article was studied in previous papers, where it was proved that VT works and deserves attention. New observational data and numerical codes have motivated further development which is presented here. New research has been planed with the essential aim of proving that current cosmological observations, including Planck data, baryon acoustic oscillations (BAO), and so on, may be explained with VT, a theory which accounts for a kind of dark energy which has the same equation of state as vacuum. New versions of the codes CAMB and COSMOMC have been designed formore » applications to VT, and the resulting versions have been used to get the cosmological parameters of the VT model at suitable confidence levels. The parameters to be estimated are the same as in general relativity (GR), plus a new parameter D . For D = 0, VT linear cosmological perturbations reduces to those of GR, but the VT background may explain dark energy. The fits between observations and VT predictions lead to non vanishing | D | upper limits at the 1σ confidence level. The value D = 0 is admissible at this level, but this value is not that of the best fit in any case. Results strongly suggest that VT may explain current observations, at least, as well as GR; with the advantage that, as it is proved in this paper, VT has an additional parameter which facilitates adjustments to current observational data.« less

Search for high-mass diphoton states and limits on Randall-Sundrum gravitons at CDF.

PubMed

Aaltonen, T; Abulencia, A; Adelman, J; Affolder, T; Akimoto, T; Albrow, M G; Amerio, S; Amidei, D; Anastassov, A; Anikeev, K; Annovi, A; Antos, J; Aoki, M; Apollinari, G; 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; 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; 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; Carrillo, S; Carlsmith, D; Carosi, R; 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, I; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Cilijak, M; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Coca, M; 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; DaRonco, S; Datta, M; D'Auria, S; Davies, T; Dagenhart, D; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; De Lorenzo, G; Dell'Orso, M; Delli Paoli, F; 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; Dörr, C; 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, I; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Forrest, R; Forrester, S; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garcia, J E; Garberson, F; Garfinkel, A F; Gay, C; Gerberich, H; Gerdes, D; Giagu, S; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Goldstein, J; 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; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Holloway, 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; Jang, D; 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; Karchin, P E; Kato, Y; Kemp, 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; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraan, A C; 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; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lu, R-S; Lucchesi, D; 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; Marginean, R; Marino, C; Marino, C P; Martin, A; Martin, M; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Matsunaga, H; Mattson, M E; Mazini, R; 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; Miyamoto, A; Moed, S; Moggi, N; Mohr, B; Moon, C S; Moore, R; Morello, M; Fernandez, P Movilla; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; 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; Savard, P; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; 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; Staveris-Polykalas, A; 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; 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; Tsuno, S; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vazquez, F; Velev, G; Vellidis, C; Veramendi, G; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Vollrath, I; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner, J; Wagner, W; 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; Zhou, J; Zucchelli, S

2007-10-26

We have performed a search for new particles which decay to two photons using 1.2 fb(-1) of integrated luminosity from pp[over] collisions at square root s = 1.96 TeV collected using the CDF II detector at the Fermilab Tevatron. We find the diphoton mass spectrum to be in agreement with the standard model expectation, and set limits on the cross section times branching ratio for the Randall-Sundrum graviton, as a function of diphoton mass. We subsequently derive lower limits for the graviton mass of 230 GeV/c(2) and 850 GeV/c(2), at the 95% confidence level, for coupling parameters (k/M[over](Pl)) of 0.01 and 0.1, respectively.

A lower limit on the age of the universe

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

Chaboyer, B.; Demarque, P.; Kernan, P.J.

1996-02-16

A detailed numerical study was designed and conducted to estimate the absolute age and the uncertainty in age (with confidence limits) of the oldest globular clusters in our galaxy, and hence to put a robust lower bound on the age of the universe. Estimates of the uncertainty range and distribution in the input parameters of stellar evolution codes were used to produce 1000 Monte Carlo realizations of stellar isochrones, which were then used to derive ages for the 17 oldest globular clusters. A probability distribution for the mean age of these systems was derived by incorporating the observational uncertainties inmore » chrones. The dominant contribution to the width of the distribution (approximately {sup +}{sub -}5) magnitudes. Subdominant contributions came from the choice of the color table used to translate theoretical luminosities and temperatures to observed magnitudes and colors, as well as from theoretical uncertainties in heavy element abundances and mixing length. The one-sided 95 percent confidence limit lower bound for this distribution occurs at an age of 12.07 X 10{sup 9} years, and the median age for the distribution is 14.56 X 10{sup 9} years. These age limits, when compared with the Hubble age estimate, put powerful constraints on cosmology. 41 refs., 2 figs.« less

Hematology and biochemistry reference intervals for Ontario commercial nursing pigs close to the time of weaning

PubMed Central

Perri, Amanda M.; O’Sullivan, Terri L.; Harding, John C.S.; Wood, R. Darren; Friendship, Robert M.

2017-01-01

The evaluation of pig hematology and biochemistry parameters is rarely done largely due to the costs associated with laboratory testing and labor, and the limited availability of reference intervals needed for interpretation. Within-herd and between-herd biological variation of these values also make it difficult to establish reference intervals. Regardless, baseline reference intervals are important to aid veterinarians in the interpretation of blood parameters for the diagnosis and treatment of diseased swine. The objective of this research was to provide reference intervals for hematology and biochemistry parameters of 3-week-old commercial nursing piglets in Ontario. A total of 1032 pigs lacking clinical signs of disease from 20 swine farms were sampled for hematology and iron panel evaluation, with biochemistry analysis performed on a subset of 189 randomly selected pigs. The 95% reference interval, mean, median, range, and 90% confidence intervals were calculated for each parameter. PMID:28373729

Search for Higgs boson pair production in events with two bottom quarks and two tau leptons in proton–proton collisions at s = 13 TeV

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

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

A search for the production of Higgs boson pairs in proton–proton collisions at a centre-of-mass energy of 13 TeV is presented, using a data sample corresponding to an integrated luminosity of 35.9 fb -1 collected with the CMS detector at the LHC. Events with one Higgs boson decaying into two bottom quarks and the other decaying into two τ leptons are explored to investigate both resonant and nonresonant production mechanisms. The data are found to be consistent, within uncertainties, with the standard model background predictions. For resonant production, upper limits at the 95% confidence level are set on the productionmore » cross section for Higgs boson pairs as a function of the hypothesized resonance mass and are interpreted in the context of the minimal supersymmetric standard model. For nonresonant production, upper limits on the production cross section constrain the parameter space for anomalous Higgs boson couplings. The observed (expected) upper limit at 95% confidence level corresponds to about 30 (25) times the prediction of the standard model.« less

Search for Higgs boson pair production in events with two bottom quarks and two tau leptons in proton–proton collisions at s = 13 TeV

DOE PAGES

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

2018-03-01

A search for the production of Higgs boson pairs in proton–proton collisions at a centre-of-mass energy of 13 TeV is presented, using a data sample corresponding to an integrated luminosity of 35.9 fb -1 collected with the CMS detector at the LHC. Events with one Higgs boson decaying into two bottom quarks and the other decaying into two τ leptons are explored to investigate both resonant and nonresonant production mechanisms. The data are found to be consistent, within uncertainties, with the standard model background predictions. For resonant production, upper limits at the 95% confidence level are set on the productionmore » cross section for Higgs boson pairs as a function of the hypothesized resonance mass and are interpreted in the context of the minimal supersymmetric standard model. For nonresonant production, upper limits on the production cross section constrain the parameter space for anomalous Higgs boson couplings. The observed (expected) upper limit at 95% confidence level corresponds to about 30 (25) times the prediction of the standard model.« less

[Establishment of the mathematic model of total quantum statistical moment standard similarity for application to medical theoretical research].

PubMed

He, Fu-yuan; Deng, Kai-wen; Huang, Sheng; Liu, Wen-long; Shi, Ji-lian

2013-09-01

The paper aims to elucidate and establish a new mathematic model: the total quantum statistical moment standard similarity (TQSMSS) on the base of the original total quantum statistical moment model and to illustrate the application of the model to medical theoretical research. The model was established combined with the statistical moment principle and the normal distribution probability density function properties, then validated and illustrated by the pharmacokinetics of three ingredients in Buyanghuanwu decoction and of three data analytical method for them, and by analysis of chromatographic fingerprint for various extracts with different solubility parameter solvents dissolving the Buyanghanwu-decoction extract. The established model consists of four mainly parameters: (1) total quantum statistical moment similarity as ST, an overlapped area by two normal distribution probability density curves in conversion of the two TQSM parameters; (2) total variability as DT, a confidence limit of standard normal accumulation probability which is equal to the absolute difference value between the two normal accumulation probabilities within integration of their curve nodical; (3) total variable probability as 1-Ss, standard normal distribution probability within interval of D(T); (4) total variable probability (1-beta)alpha and (5) stable confident probability beta(1-alpha): the correct probability to make positive and negative conclusions under confident coefficient alpha. With the model, we had analyzed the TQSMS similarities of pharmacokinetics of three ingredients in Buyanghuanwu decoction and of three data analytical methods for them were at range of 0.3852-0.9875 that illuminated different pharmacokinetic behaviors of each other; and the TQSMS similarities (ST) of chromatographic fingerprint for various extracts with different solubility parameter solvents dissolving Buyanghuanwu-decoction-extract were at range of 0.6842-0.999 2 that showed different constituents with various solvent extracts. The TQSMSS can characterize the sample similarity, by which we can quantitate the correct probability with the test of power under to make positive and negative conclusions no matter the samples come from same population under confident coefficient a or not, by which we can realize an analysis at both macroscopic and microcosmic levels, as an important similar analytical method for medical theoretical research.

Data assimilation method based on the constraints of confidence region

NASA Astrophysics Data System (ADS)

Li, Yong; Li, Siming; Sheng, Yao; Wang, Luheng

2018-03-01

The ensemble Kalman filter (EnKF) is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence. Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called EnCR, to estimate the inflation parameter of the forecast error variance of the EnKF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.

Application of iterative robust model-based optimal experimental design for the calibration of biocatalytic models.

PubMed

Van Daele, Timothy; Gernaey, Krist V; Ringborg, Rolf H; Börner, Tim; Heintz, Søren; Van Hauwermeiren, Daan; Grey, Carl; Krühne, Ulrich; Adlercreutz, Patrick; Nopens, Ingmar

2017-09-01

The aim of model calibration is to estimate unique parameter values from available experimental data, here applied to a biocatalytic process. The traditional approach of first gathering data followed by performing a model calibration is inefficient, since the information gathered during experimentation is not actively used to optimize the experimental design. By applying an iterative robust model-based optimal experimental design, the limited amount of data collected is used to design additional informative experiments. The algorithm is used here to calibrate the initial reaction rate of an ω-transaminase catalyzed reaction in a more accurate way. The parameter confidence region estimated from the Fisher Information Matrix is compared with the likelihood confidence region, which is not only more accurate but also a computationally more expensive method. As a result, an important deviation between both approaches is found, confirming that linearization methods should be applied with care for nonlinear models. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1278-1293, 2017. © 2017 American Institute of Chemical Engineers.

Statistical, time series, and fractal analysis of full stretch of river Yamuna (India) for water quality management.

PubMed

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2015-01-01

River water is a major resource of drinking water on earth. Management of river water is highly needed for surviving. Yamuna is the main river of India, and monthly variation of water quality of river Yamuna, using statistical methods have been compared at different sites for each water parameters. Regression, correlation coefficient, autoregressive integrated moving average (ARIMA), box-Jenkins, residual autocorrelation function (ACF), residual partial autocorrelation function (PACF), lag, fractal, Hurst exponent, and predictability index have been estimated to analyze trend and prediction of water quality. Predictive model is useful at 95% confidence limits and all water parameters reveal platykurtic curve. Brownian motion (true random walk) behavior exists at different sites for BOD, AMM, and total Kjeldahl nitrogen (TKN). Quality of Yamuna River water at Hathnikund is good, declines at Nizamuddin, Mazawali, Agra D/S, and regains good quality again at Juhikha. For all sites, almost all parameters except potential of hydrogen (pH), water temperature (WT) crosses the prescribed limits of World Health Organization (WHO)/United States Environmental Protection Agency (EPA).

XENON100 exclusion limit without considering Leff as a nuisance parameter

NASA Astrophysics Data System (ADS)

Davis, Jonathan H.; Bœhm, Céline; Oppermann, Niels; Ensslin, Torsten; Lacroix, Thomas

2012-07-01

In 2011, the XENON100 experiment has set unprecedented constraints on dark matter-nucleon interactions, excluding dark matter candidates with masses down to 6 GeV if the corresponding cross section is larger than 10-39cm2. The dependence of the exclusion limit in terms of the scintillation efficiency (Leff) has been debated at length. To overcome possible criticisms XENON100 performed an analysis in which Leff was considered as a nuisance parameter and its uncertainties were profiled out by using a Gaussian likelihood in which the mean value corresponds to the best fit Leff value (smoothly extrapolated to 0 below 3 keVnr). Although such a method seems fairly robust, it does not account for more extreme types of extrapolation nor does it enable us to anticipate how much the exclusion limit would vary if new data were to support a flat behavior for Leff below 3 keVnr, for example. Yet, such a question is crucial for light dark matter models which are close to the published XENON100 limit. To answer this issue, we use a maximum likelihood ratio analysis, as done by the XENON100 Collaboration, but do not consider Leff as a nuisance parameter. Instead, Leff is obtained directly from the fits to the data. This enables us to define frequentist confidence intervals by marginalizing over Leff.

Reducing the width of confidence intervals for the difference between two population means by inverting adaptive tests.

PubMed

O'Gorman, Thomas W

2018-05-01

In the last decade, it has been shown that an adaptive testing method could be used, along with the Robbins-Monro search procedure, to obtain confidence intervals that are often narrower than traditional confidence intervals. However, these confidence interval limits require a great deal of computation and some familiarity with stochastic search methods. We propose a method for estimating the limits of confidence intervals that uses only a few tests of significance. We compare these limits to those obtained by a lengthy Robbins-Monro stochastic search and find that the proposed method is nearly as accurate as the Robbins-Monro search. Adaptive confidence intervals that are produced by the proposed method are often narrower than traditional confidence intervals when the distributions are long-tailed, skewed, or bimodal. Moreover, the proposed method of estimating confidence interval limits is easy to understand, because it is based solely on the p-values from a few tests of significance.

Software thresholds alter the bias of actigraphy for monitoring sleep in team-sport athletes.

PubMed

Fuller, Kate L; Juliff, Laura; Gore, Christopher J; Peiffer, Jeremiah J; Halson, Shona L

2017-08-01

Actical ® actigraphy is commonly used to monitor athlete sleep. The proprietary software, called Actiware ® , processes data with three different sleep-wake thresholds (Low, Medium or High), but there is no standardisation regarding their use. The purpose of this study was to examine validity and bias of the sleep-wake thresholds for processing Actical ® sleep data in team sport athletes. Validation study comparing actigraph against accepted gold standard polysomnography (PSG). Sixty seven nights of sleep were recorded simultaneously with polysomnography and Actical ® devices. Individual night data was compared across five sleep measures for each sleep-wake threshold using Actiware ® software. Accuracy of each sleep-wake threshold compared with PSG was evaluated from mean bias with 95% confidence limits, Pearson moment-product correlation and associated standard error of estimate. The Medium threshold generated the smallest mean bias compared with polysomnography for total sleep time (8.5min), sleep efficiency (1.8%) and wake after sleep onset (-4.1min); whereas the Low threshold had the smallest bias (7.5min) for wake bouts. Bias in sleep onset latency was the same across thresholds (-9.5min). The standard error of the estimate was similar across all thresholds; total sleep time ∼25min, sleep efficiency ∼4.5%, wake after sleep onset ∼21min, and wake bouts ∼8 counts. Sleep parameters measured by the Actical ® device are greatly influenced by the sleep-wake threshold applied. In the present study the Medium threshold produced the smallest bias for most parameters compared with PSG. Given the magnitude of measurement variability, confidence limits should be employed when interpreting changes in sleep parameters. Copyright © 2017 Sports Medicine Australia. All rights reserved.

Estimating effects of limiting factors with regression quantiles

USGS Publications Warehouse

Cade, B.S.; Terrell, J.W.; Schroeder, R.L.

1999-01-01

In a recent Concepts paper in Ecology, Thomson et al. emphasized that assumptions of conventional correlation and regression analyses fundamentally conflict with the ecological concept of limiting factors, and they called for new statistical procedures to address this problem. The analytical issue is that unmeasured factors may be the active limiting constraint and may induce a pattern of unequal variation in the biological response variable through an interaction with the measured factors. Consequently, changes near the maxima, rather than at the center of response distributions, are better estimates of the effects expected when the observed factor is the active limiting constraint. Regression quantiles provide estimates for linear models fit to any part of a response distribution, including near the upper bounds, and require minimal assumptions about the form of the error distribution. Regression quantiles extend the concept of one-sample quantiles to the linear model by solving an optimization problem of minimizing an asymmetric function of absolute errors. Rank-score tests for regression quantiles provide tests of hypotheses and confidence intervals for parameters in linear models with heteroscedastic errors, conditions likely to occur in models of limiting ecological relations. We used selected regression quantiles (e.g., 5th, 10th, ..., 95th) and confidence intervals to test hypotheses that parameters equal zero for estimated changes in average annual acorn biomass due to forest canopy cover of oak (Quercus spp.) and oak species diversity. Regression quantiles also were used to estimate changes in glacier lily (Erythronium grandiflorum) seedling numbers as a function of lily flower numbers, rockiness, and pocket gopher (Thomomys talpoides fossor) activity, data that motivated the query by Thomson et al. for new statistical procedures. Both example applications showed that effects of limiting factors estimated by changes in some upper regression quantile (e.g., 90-95th) were greater than if effects were estimated by changes in the means from standard linear model procedures. Estimating a range of regression quantiles (e.g., 5-95th) provides a comprehensive description of biological response patterns for exploratory and inferential analyses in observational studies of limiting factors, especially when sampling large spatial and temporal scales.

Search for anomalous production of multilepton events in pp collisions at sqrt s=1.96 TeV.

PubMed

Abulencia, A; Adelman, J; Affolder, T; Akimoto, T; Albrow, M G; Ambrose, D; Amerio, S; Amidei, D; Anastassov, A; Anikeev, K; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Arguin, J-F; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, 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; Bedeschi, F; Behari, S; Belforte, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; 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; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Budroni, S; Burkett, K; Busetto, G; Bussey, P; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carillo, S; Carlsmith, D; Carosi, R; 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, I; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciljak, M; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Coca, M; 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; Cyr, D; DaRonco, S; Datta, M; D'Auria, S; Davies, T; D'Onofrio, M; Dagenhart, D; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; Dell'Orso, M; Delli Paoli, F; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; DiTuro, P; Dörr, C; Donati, S; Donega, M; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, I; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Foland, A; Forrester, S; Foster, G W; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garcia, J E; Garberson, F; Garfinkel, A F; Gay, C; Gerberich, H; Gerdes, D; Giagu, S; Giannetti, P; Gibson, A; Gibson, K; Gimmell, J L; Ginsburg, C; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Goldstein, J; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Griffiths, M; 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, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Holloway, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ishizawa, Y; Ivanov, A; Iyutin, B; James, E; Jang, D; Jayatilaka, B; Jeans, D; Jensen, H; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Karchin, P E; Kato, Y; Kemp, 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; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kovalev, A; Kraan, A C; Kraus, J; Kravchenko, I; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; 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; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Loverre, P; Lu, R-S; Lucchesi, D; 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; Manca, G; Margaroli, F; Marginean, R; Marino, C; Marino, C P; Martin, A; Martin, M; Martin, V; Martínez, M; Maruyama, T; Mastrandrea, P; Masubuchi, T; Matsunaga, H; Mattson, M E; Mazini, R; 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; Miyamoto, A; Moed, S; Moggi, N; Mohr, B; Moore, R; Morello, M; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Nachtman, J; Nagano, A; Naganoma, J; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nigmanov, T; Nodulman, L; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Pagliarone, C; Palencia, E; Papadimitriou, V; 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; Ranjan, N; Rappoccio, S; 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; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Sabik, S; Safonov, A; Sakumoto, W K; Salamanna, G; Saltó, O; Saltzberg, D; Sánchez, C; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savard, P; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; 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; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Sjolin, J; 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; Staveris-Polykalas, A; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sun, H; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Takikawa, K; Tanaka, M; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; 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; Tsuchiya, R; Tsuno, S; Turini, N; Ukegawa, F; Unverhau, T; Uozumi, S; Usynin, D; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Veramendi, G; Veszpremi, V; Vidal, R; Vila, I; Vilar, R; Vine, T; Vollrath, I; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner, J; Wagner, W; Wallny, R; Wang, S M; Warburton, A; Waschke, S; Waters, D; Weinberger, M; Wester Iii, 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; Zhou, J; Zucchelli, S

2007-03-30

We report a search for the anomalous production of events with multiple charged leptons in pp[over] collisions at sqrt[s]=1.96 TeV using a data sample corresponding to an integrated luminosity of 346 pb(-1) collected by the CDF II detector at the Fermilab Tevatron. The search is divided into three-lepton and four-or-more-lepton data samples. We observe six events in the three-lepton sample and zero events in the > or =4-lepton sample. Both numbers of events are consistent with standard model background expectations. Within the framework of an R-parity-violating supergravity model, the results are interpreted as mass limits on the lightest neutralino (chi[over](1)(0)) and chargino (chi[over](1+/-) particles. For one particular choice of model parameters, the limits are M(chi[over](1)(0)>110 GeV/c2 and M(chi[over](1+/-)>203 GeV/c2 at 95% confidence level; the variation of these mass limits with model parameters is presented.

Analysis of adverse events of renal impairment related to platinum-based compounds using the Japanese Adverse Drug Event Report database.

PubMed

Naganuma, Misa; Motooka, Yumi; Sasaoka, Sayaka; Hatahira, Haruna; Hasegawa, Shiori; Fukuda, Akiho; Nakao, Satoshi; Shimada, Kazuyo; Hirade, Koseki; Mori, Takayuki; Yoshimura, Tomoaki; Kato, Takeshi; Nakamura, Mitsuhiro

2018-01-01

Platinum compounds cause several adverse events, such as nephrotoxicity, gastrointestinal toxicity, myelosuppression, ototoxicity, and neurotoxicity. We evaluated the incidence of renal impairment as adverse events are related to the administration of platinum compounds using the Japanese Adverse Drug Event Report database. We analyzed adverse events associated with the use of platinum compounds reported from April 2004 to November 2016. The reporting odds ratio at 95% confidence interval was used to detect the signal for each renal impairment incidence. We evaluated the time-to-onset profile of renal impairment and assessed the hazard type using Weibull shape parameter and used the applied association rule mining technique to discover undetected relationships such as possible risk factor. In total, 430,587 reports in the Japanese Adverse Drug Event Report database were analyzed. The reporting odds ratios (95% confidence interval) for renal impairment resulting from the use of cisplatin, oxaliplatin, carboplatin, and nedaplatin were 2.7 (2.5-3.0), 0.6 (0.5-0.7), 0.8 (0.7-1.0), and 1.3 (0.8-2.1), respectively. The lower limit of the reporting odds ratio (95% confidence interval) for cisplatin was >1. The median (lower-upper quartile) onset time of renal impairment following the use of platinum-based compounds was 6.0-8.0 days. The Weibull shape parameter β and 95% confidence interval upper limit of oxaliplatin were <1. In the association rule mining, the score of lift for patients who were treated with cisplatin and co-administered furosemide, loxoprofen, or pemetrexed was high. Similarly, the scores for patients with hypertension or diabetes mellitus were high. Our findings suggest a potential risk of renal impairment during cisplatin use in real-world setting. The present findings demonstrate that the incidence of renal impairment following cisplatin use should be closely monitored when patients are hypertensive or diabetic, or when they are co-administered furosemide, loxoprofen, or pemetrexed. In addition, healthcare professionals should closely assess a patient's background prior to treatment.

Search for dark matter and unparticles produced in association with a Z boson in proton-proton collisions at s = 8 TeV

DOE PAGES

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

2016-03-22

In this study, a search for evidence of particle dark matter (DM) and unparticle production at the LHC has been performed using events containing two charged leptons, consistent with the decay of a Z boson, and large missing transverse momentum. This study is based on data collected with the CMS detector corresponding to an integrated luminosity of 19.7 fb –1 of pp collisions at the LHC at a center-of-mass energy of 8 TeV. No significant excess of events is observed above the number expected from the standard model contributions. The results are interpreted in terms of 90% confidence level limitsmore » on the DM-nucleon scattering cross section, as a function of the DM particle mass, for both spin-dependent and spin-independent scenarios. Limits are set on the effective cutoff scale Lambda, and on the annihilation rate for DM particles, assuming that their branching fraction to quarks is 100%. Additionally, the most stringent 95% confidence level limits to date on the unparticle model parameters are obtained.« less

Measuring systems of hard to get objects: problems with analysis of measurement results

NASA Astrophysics Data System (ADS)

Gilewska, Grazyna

2005-02-01

The problem accessibility of metrological parameters features of objects appeared in many measurements. Especially if it is biological object which parameters very often determined on the basis of indirect research. Accidental component predominate in forming of measurement results with very limited access to measurement objects. Every measuring process has a lot of conditions limiting its abilities to any way processing (e.g. increase number of measurement repetition to decrease random limiting error). It may be temporal, financial limitations, or in case of biological object, small volume of sample, influence measuring tool and observers on object, or whether fatigue effects e.g. at patient. It's taken listing difficulties into consideration author worked out and checked practical application of methods outlying observation reduction and next innovative methods of elimination measured data with excess variance to decrease of mean standard deviation of measured data, with limited aomunt of data and accepted level of confidence. Elaborated methods wee verified on the basis of measurement results of knee-joint width space got from radiographs. Measurements were carried out by indirectly method on the digital images of radiographs. Results of examination confirmed legitimacy to using of elaborated methodology and measurement procedures. Such methodology has special importance when standard scientific ways didn't bring expectations effects.

Sampling Theory and Confidence Intervals for Effect Sizes: Using ESCI To Illustrate "Bouncing"; Confidence Intervals.

ERIC Educational Resources Information Center

Du, Yunfei

This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes. Sampling error affects the location and precision of confidence intervals. Meta-analytic resampling demonstrates that confidence intervals can haphazardly bounce around the true population parameter. Special software with graphical…

Recent results on search for new physics at BaBar

NASA Astrophysics Data System (ADS)

Oberhof, Benjamin

2017-04-01

We present some recent measurements for the search of New Physics using 514 fb-1 of e+e- collisions collected with the BaBar detector at the PEP-II e+e- collider at SLAC. First we present a search for the decay ϒ (1S) → γA0, A0 → cc¯, where A0 is a candidate for the CP-odd Higgs boson of the next-to-minimal supersymmetric standard model. No significant signal is observed and we set 90% confidence-level upper limits on B(ϒ(1S ) → γA0) × B(A0 → cc¯). We report the search for a light non-Standard Model gauge boson Z' coupling only to the second and third lepton families. Our results significantly improve current limits and further constrain the remaining region of the allowed parameter space. Finally, we present a search for a long-lived particle L that is produced in e+e- annihilations and decays into two oppositely charged tracks. We do not observe a significant signal and we and set 90% confidence level upper limits on the product of the L production cross section, branching fraction, and reconstruction efficiency as a function of the L mass. In addition, upper limits are provided on the branching fraction B(B → XsL), where Xs is an hadronic system with strangeness -1.

Sensor fusion for antipersonnel landmine detection: a case study

NASA Astrophysics Data System (ADS)

den Breejen, Eric; Schutte, Klamer; Cremer, Frank

1999-08-01

In this paper the multi sensor fusion results obtained within the European research project GEODE are presented. The layout of the test lane and the individual sensors used are described. The implementation of the SCOOP algorithm improves the ROC curves, as the false alarm surface and the number of false alarms both are taken into account. The confidence grids, as produced by the sensor manufacturers, of the sensors are used as input for the different sensor fusion methods implemented. The multisensor fusion methods implemented are Bayes, Dempster-Shafer, fuzzy probabilities and rules. The mapping of the confidence grids to the input parameters for fusion methods is an important step. Due to limited amount of the available data the entire test lane is used for training and evaluation. All four sensor fusion methods provide better detection results than the individual sensors.

Effects of aerodynamic heating and TPS thermal performance uncertainties on the Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Goodrich, W. D.; Derry, S. M.; Maraia, R. J.

1980-01-01

A procedure for estimating uncertainties in the aerodynamic-heating and thermal protection system (TPS) thermal-performance methodologies developed for the Shuttle Orbiter is presented. This procedure is used in predicting uncertainty bands around expected or nominal TPS thermal responses for the Orbiter during entry. Individual flowfield and TPS parameters that make major contributions to these uncertainty bands are identified and, by statistical considerations, combined in a manner suitable for making engineering estimates of the TPS thermal confidence intervals and temperature margins relative to design limits. Thus, for a fixed TPS design, entry trajectories for future Orbiter missions can be shaped subject to both the thermal-margin and confidence-interval requirements. This procedure is illustrated by assessing the thermal margins offered by selected areas of the existing Orbiter TPS design for an entry trajectory typifying early flight test missions.

Profile-likelihood Confidence Intervals in Item Response Theory Models.

PubMed

Chalmers, R Philip; Pek, Jolynn; Liu, Yang

2017-01-01

Confidence intervals (CIs) are fundamental inferential devices which quantify the sampling variability of parameter estimates. In item response theory, CIs have been primarily obtained from large-sample Wald-type approaches based on standard error estimates, derived from the observed or expected information matrix, after parameters have been estimated via maximum likelihood. An alternative approach to constructing CIs is to quantify sampling variability directly from the likelihood function with a technique known as profile-likelihood confidence intervals (PL CIs). In this article, we introduce PL CIs for item response theory models, compare PL CIs to classical large-sample Wald-type CIs, and demonstrate important distinctions among these CIs. CIs are then constructed for parameters directly estimated in the specified model and for transformed parameters which are often obtained post-estimation. Monte Carlo simulation results suggest that PL CIs perform consistently better than Wald-type CIs for both non-transformed and transformed parameters.

Application of Non-Deterministic Methods to Assess Modeling Uncertainties for Reinforced Carbon-Carbon Debris Impacts

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Fasanella, Edwin L.; Melis, Matthew; Carney, Kelly; Gabrys, Jonathan

2004-01-01

The Space Shuttle Columbia Accident Investigation Board (CAIB) made several recommendations for improving the NASA Space Shuttle Program. An extensive experimental and analytical program has been developed to address two recommendations related to structural impact analysis. The objective of the present work is to demonstrate the application of probabilistic analysis to assess the effect of uncertainties on debris impacts on Space Shuttle Reinforced Carbon-Carbon (RCC) panels. The probabilistic analysis is used to identify the material modeling parameters controlling the uncertainty. A comparison of the finite element results with limited experimental data provided confidence that the simulations were adequately representing the global response of the material. Five input parameters were identified as significantly controlling the response.

Search for new phenomena in monophoton final states in proton-proton collisions at √{ s} = 8 TeV

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Ochesanu, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Mora Herrera, C.; Pol, M. 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.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Neveu, 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.; Rurua, L.; 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. 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B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Novgorodova, O.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; 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, 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. 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M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Galanti, M.; Gasparini, U.; Giubilato, P.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Vanini, S.; Ventura, S.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fiori, F.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Moon, C. S.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Vernieri, C.; Barone, L.; Cavallari, F.; D'imperio, G.; Del Re, D.; Diemoz, M.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Soffi, L.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Casasso, S.; Costa, M.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; Ortona, G.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Potenza, A.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Tamponi, U.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Park, H.; Sakharov, A.; Son, D. C.; Kim, T. J.; Kim, J. Y.; Song, S.; Choi, S.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K. S.; Park, S. K.; Roh, Y.; Choi, M.; Kim, J. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Md Ali, M. A. B.; Casimiro Linares, E.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. 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G.; Gallinaro, M.; Lloret Iglesias, L.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Varela, J.; Vischia, P.; Afanasiev, S.; Bunin, P.; Golutvin, I.; Karjavin, V.; Konoplyanikov, V.; Kozlov, G.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Vorobyev, An.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; 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. 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F.; Missiroli, M.; Moran, D.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Graziano, A.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Piedra Gomez, J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Benaglia, A.; Bendavid, J.; Benhabib, L.; Benitez, J. F.; Bernet, C.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; David, A.; De Guio, F.; De Roeck, A.; De Visscher, S.; Di Marco, E.; Dobson, M.; Dordevic, M.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Eugster, J.; Franzoni, G.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Magini, N.; Malgeri, L.; Mannelli, M.; Marrouche, J.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Musella, P.; Orsini, L.; Pape, L.; Perez, E.; Perrozzi, L.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Plagge, M.; Racz, A.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W.-S.; Kao, K. Y.; Liu, Y. F.; Lu, R.-S.; Majumder, D.; Petrakou, E.; Tzeng, Y. M.; Wilken, R.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Isildak, B.; Karapinar, G.; Ocalan, K.; Sekmen, S.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; Cankocak, K.; Vardarlı, F. I.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Senkin, S.; Smith, V. J.; Williams, T.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Krohn, M.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Skinnari, L.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kaadze, K.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P., III; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Ratnikov, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Korjenevski, S.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Vuosalo, C.; Woods, N.; CMS Collaboration

2016-04-01

Results are presented from a search for new physics in final states containing a photon and missing transverse momentum. The data correspond to an integrated luminosity of 19.6 fb-1 collected in proton-proton collisions at √{ s} = 8 TeV with the CMS experiment at the LHC. No deviation from the standard model predictions is observed for these final states. New, improved limits are set on dark matter production and on parameters of models with large extra dimensions. In particular, the first limits from the LHC on branon production are found and significantly extend previous limits from LEP and the Tevatron. An upper limit of 14.0 fb on the cross section is set at the 95% confidence level for events with a monophoton final state with photon transverse momentum greater than 145 GeV and missing transverse momentum greater than 140 GeV.

Retrospective analysis of the incidence of epidural haematoma in patients with epidural catheters and abnormal coagulation parameters.

PubMed

Gulur, P; Tsui, B; Pathak, R; Koury, K M; Lee, H

2015-05-01

Epidural haematoma is a rare but potentially catastrophic complication associated with epidural catheterization. The times of insertion and removal of epidural catheters are high-risk periods for epidural haematoma formation, especially with abnormal coagulation parameters. There is a lack of data on the incidence of epidural haematoma in patients with abnormal coagulation parameters. A retrospective analysis was undertaken from 2002 to 2009 on patients with an epidural catheter. Queries were performed on the coagulation parameters for the dates of placement and removal of the catheters and on all documented epidural haematoma cases. During the study period, 11 600 epidural catheters were placed. In the setting of abnormal coagulation parameters, 278 (2.4%) epidural catheters were placed and 351 (3%) were removed. Two epidural haematomas occurred; both patients had epidural catheters and spinal drains placed for vascular procedures with abnormal coagulation parameters after operatation. The haematomas occurred after removal of the catheters. Based on our study, the incidence of epidural haematoma in patients with abnormal coagulation parameters is 1 in 315 patients, with the lower limit of the 95% confidence interval at 87 and the upper limit at 2597. The risk of epidural haematoma is clearly elevated with abnormal coagulation parameters. Our data suggest that as the incidence of epidural haematoma with neuraxial access in patients with abnormal coagulation is not 100%, individual risk-benefit evaluations are warranted. © The Author 2015. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Search for displaced supersymmetry in events with an electron and a muon with large impact parameters

DOE PAGES

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

2015-02-13

A search for new long-lived particles decaying to leptons is presented using proton-proton collisions produced by the LHC at √s=8 TeV. Data used for the analysis were collected by the CMS detector and correspond to an integrated luminosity of 19.7 fb -1. Events are selected with an electron and muon with opposite charges that both have transverse impact parameter values between 0.02 and 2 cm. The search has been designed to be sensitive to a wide range of models with nonprompt e-μ final states. Limits are set on the “displaced supersymmetry” model, with pair production of top squarks decaying intomore » an e-μ final state via R-parity-violating interactions. Lastly, the results are the most restrictive to date on this model, with the most stringent limit being obtained for a top squark lifetime corresponding to cτ=2 cm, excluding masses below 790 GeV at 95% confidence level.« less

A search for squarks of Rp-violating SUSY at HERA

NASA Astrophysics Data System (ADS)

Aid, S.; Andreev, V.; Andrieu, B.; Appuhn, R. D.; Arpagaus, M.; Babaev, A.; Bähr, J.; Bán, J.; Ban, Y.; Baranov, P.; Barrelet, E.; Barschke, R.; Bartel, W.; Barth, M.; Bassler, U.; Beck, H. P.; Behrend, H. J.; Belousov, A.; Berger, Ch.; Bernardi, G.; Bernet, R.; Bertrand-Coremans, G.; Besançon, M.; Beyer, R.; Biddulph, P.; Bispham, P.; Bizot, J. C.; Blobel, V.; Borras, K.; Botterweck, F.; Boudry, V.; Braemer, A.; Braunschweig, W.; Brisson, V.; Bruel, P.; Bruncko, D.; Brune, C.; Buchholz, R.; Büngener, L.; Bürger, J.; Büsser, F. W.; Buniatian, A.; Burke, S.; Burton, M. J.; Buschhorn, G.; Campbell, A. J.; Carli, T.; Charles, F.; Charlet, M.; Clarke, D.; Clegg, A. B.; Clerbaux, B.; Cocks, S.; Contreras, J. G.; Cormack, C.; Coughlan, J. A.; Courau, A.; Cousinou, M. C.; Cozzika, G.; Criegee, L.; Cussans, D. G.; Cvach, J.; Dagoret, S.; Dainton, J. B.; Dau, W. D.; Daum, K.; David, M.; Davis, C. L.; Delcourt, B.; de Roeck, A.; de Wolf, E. A.; Dirkmann, M.; Dixon, P.; di Nezza, P.; Dlugosz, W.; Dollfus, C.; Dowell, J. D.; Dreis, H. B.; Droutskoi, A.; Düllmann, D.; Dünger, O.; Duhm, H.; Ebert, J.; Ebert, T. R.; Eckerlin, G.; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Eisenhandler, E.; Ellison, R. J.; Elsen, E.; Erdmann, M.; Erdmann, W.; Evrard, E.; Fahr, A. B.; Favart, L.; Fedotov, A.; Feeken, D.; Felst, R.; Feltesse, J.; Ferencei, J.; Ferrarotto, F.; Flamm, K.; Fleischer, M.; Flieser, M.; Flügge, G.; Fomenko, A.; Fominykh, B.; Formánek, J.; Foster, J. M.; Franke, G.; Fretwurst, E.; Gabathuler, E.; Gabathuler, K.; Gaede, F.; Garvey, J.; Gayler, J.; Gebauer, M.; Gellrich, A.; Genzel, H.; Gerhards, R.; Glazov, A.; Goerlach, U.; Goerlich, L.; Gogitidze, N.; Goldberg, M.; Goldner, D.; Golec-Biernat, K.; Gonzalez-Pineiro, B.; Gorelov, I.; Grab, C.; Grässler, H.; Grässler, R.; Greenshaw, T.; Griffiths, R.; Grindhammer, G.; Gruber, A.; Gruber, C.; Haack, J.; Haidt, D.; Hajduk, L.; Hampel, M.; Haynes, W. J.; Heinzelmann, G.; Henderson, R. C. W.; Henschel, H.; Herynek, I.; Hess, M. F.; Hildesheim, W.; Hiller, K. H.; Hilton, C. D.; Hladky, J.; Hoeger, K. C.; Höppner, M.; Hoffmann, D.; Holtom, T.; Horisberger, R.; Hudgson, V. L.; Hütte, M.; Hufnagel, H.; Ibbotson, M.; Itterbeck, H.; Jacholkowska, A.; Jacobsson, C.; Jaffre, M.; Janoth, J.; Jansen, T.; Jönsson, L.; Johannsen, K.; Johnson, D. P.; Johnson, L.; Jung, H.; Kalmus, P. I. P.; Kander, M.; Kant, D.; Kaschowitz, R.; Kathage, U.; Katzy, J.; Kaufmann, H. H.; Kaufmann, O.; Kazarian, S.; Kenyon, I. R.; Kermiche, S.; Keuker, C.; Kiesling, C.; Klein, M.; Kleinwort, C.; Knies, G.; Köhler, T.; Köhne, J. H.; Kolanoski, H.; Kole, F.; Kolya, S. D.; Korbel, V.; Korn, M.; Kostka, P.; Kotelnikov, S. K.; Krämerkämper, T.; Krasny, M. W.; Krehbiel, H.; Krücker, D.; Krüger, U.; Krüner-Marquis, U.; Küster, H.; Kuhlen, M.; Kurča, T.; Kurzhöfer, J.; Lacour, D.; Laforge, B.; Lander, R.; Landon, M. P. J.; Lange, W.; Langenegger, U.; Laporte, J. F.; Lebedev, A.; Lehner, F.; Leverenz, C.; Levonian, S.; Ley, Ch.; Lindström, G.; Lindstroem, M.; Link, J.; Linsel, F.; Lipinski, J.; List, B.; Lobo, G.; Lohmander, H.; Lomas, J. W.; Lopez, G. C.; Lubimov, V.; Lüke, D.; Magnussen, N.; Malinovski, E.; Mani, S.; Maraček, R.; Marage, P.; Marks, J.; Marshall, R.; Martens, J.; Martin, G.; Martin, R.; Martyn, H. U.; Martyniak, J.; Mavroidis, T.; Maxfield, S. J.; McMahon, S. J.; Mehta, A.; Meier, K.; Merz, T.; Meyer, A.; Meyer, A.; Meyer, H.; Meyer, J.; Meyer, P. O.; Migliori, A.; Mikocki, S.; Milstead, D.; Moeck, J.; Moreau, F.; Morris, J. V.; Mroczko, E.; Müller, D.; Müller, G.; Müller, K.; Murín, P.; Nagovizin, V.; Nahnhauer, R.; Naroska, B.; Naumann, Th.; Newman, P. R.; Newton, D.; Neyret, D.; Nguyen, H. K.; Nicholls, T. C.; Niebergall, F.; Niebuhr, C.; Niedzballa, Ch.; Niggli, H.; Nisius, R.; Nowak, G.; Noyes, G. W.; Nyberg-Werther, M.; Oakden, M.; Oberlack, H.; Obrock, U.; Olsson, J. E.; Ozerov, D.; Palmen, P.; Panaro, E.; Panitch, A.; Pascaud, C.; Patel, G. D.; Pawletta, H.; Peppel, E.; Perez, E.; Phillips, J. P.; Pieuchot, A.; Pitzl, D.; Pope, G.; Prell, S.; Prosi, R.; Rabbertz, K.; Rädel, G.; Raupach, F.; Reimer, P.; Reinshagen, S.; Rick, H.; Riech, V.; Riedlberger, J.; Riepenhausen, F.; Riess, S.; Rizvi, E.; Robertson, S. M.; Robmann, P.; Roloff, H. E.; Roosen, R.; Rosenbauer, K.; Rostovtsev, A.; Rouse, F.; Royon, C.; Rüter, K.; Rusakov, S.; Rybicki, K.; Sahlmann, N.; Sankey, D. P. C.; Schacht, P.; Schiek, S.; Schleif, S.; Schleper, P.; von Schlippe, W.; Schmidt, D.; Schmidt, G.; Schöning, A.; Schröder, V.; Schuhmann, E.; Schwab, B.; Sefkow, F.; Seidel, M.; Sell, R.; Semenov, A.; Shekelyan, V.; Sheviakov, I.; Shtarkov, L. N.; Siegmon, G.; Siewert, U.; Sirois, Y.; Skillicorn, I. O.; Smirnov, P.; Smith, J. R.; Solochenko, V.; Soloviev, Y.; Specka, A.; Spiekermann, J.; Spielman, S.; Spitzer, H.; Squinabol, F.; Starosta, R.; Steenbock, M.; Steffen, P.; Steinberg, R.; Steiner, H.; Stella, B.; Stellberger, A.; Stier, J.; Stiewe, J.; Stößlein, U.; Stolze, K.; Straumann, U.; Struczinski, W.; Sutton, J. P.; Tapprogge, S.; Taševský, M.; Tchernyshov, V.; Tchetchelnitski, S.; Theissen, J.; Thiebaux, C.; Thompson, G.; Truöl, P.; Turnau, J.; Tutas, J.; Uelkes, P.; Usik, A.; Valkár, S.; Valkárová, A.; Vallée, C.; Vandenplas, D.; van Esch, P.; van Mechelen, P.; Vazdik, Y.; Verrecchia, P.; Villet, G.; Wacker, K.; Wagener, A.; Wagener, M.; Walther, A.; Waugh, B.; Weber, G.; Weber, M.; Wegener, D.; Wegner, A.; Wengler, T.; Werner, M.; West, L. R.; Wilksen, T.; Willard, S.; Winde, M.; Winter, G. G.; Wittek, C.; Wünsch, E.; Žáček, J.; Zarbock, D.; Zhang, Z.; Zhokin, A.; Zimmer, M.; Zomer, F.; Zsembery, J.; Zuber, K.; Zurnedden, M.

1996-03-01

A search for squarks of R-parity violating supersymmetry is performed in ep collisions at HERA using H1 1994 e + data. Direct single production of squarks of each generation by e +-quark fusion via a Yukawa coupling λ' is considered. All possible R-parity violating decays and gauge decays of the squarks are taken into account. No significant deviation from the Standard Model predictions is found in the various multi-lepton and multi-jet final states studied and exclusion limits are derived. At 95% confidence level, the existence of first generation squarks is excluded for masses up to 240 GeV for coupling values λ'≳√4 πα em. The limits obtained are shown to be only weakly dependent on the free parameters of the Minimal Supersymmetric Standard Model. Stop squarks are excluded for masses up to 138 GeV for coupling λ'×cos θ t to e +d pairs ≳0.1×√4 πα em, where θ t is the mass mixing angle. Light stop squarks are furthermore searched for through pair production in γ-gluon fusion processes. No signal is observed and exclusion limits are derived. Masses in the range 9 to 24.4 GeV are excluded at 95% confidence level for λ'×cos θ t>10-4.

Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

PubMed Central

Lubin, Jay H.; Colt, Joanne S.; Camann, David; Davis, Scott; Cerhan, James R.; Severson, Richard K.; Bernstein, Leslie; Hartge, Patricia

2004-01-01

Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma. PMID:15579415

Limits of detection and decision. Part 4

NASA Astrophysics Data System (ADS)

Voigtman, E.

2008-02-01

Probability density functions (PDFs) have been derived for a number of commonly used limit of detection definitions, including several variants of the Relative Standard Deviation of the Background-Background Equivalent Concentration (RSDB-BEC) method, for a simple linear chemical measurement system (CMS) having homoscedastic, Gaussian measurement noise and using ordinary least squares (OLS) processing. All of these detection limit definitions serve as both decision and detection limits, thereby implicitly resulting in 50% rates of Type 2 errors. It has been demonstrated that these are closely related to Currie decision limits, if the coverage factor, k, is properly defined, and that all of the PDFs are scaled reciprocals of noncentral t variates. All of the detection limits have well-defined upper and lower limits, thereby resulting in finite moments and confidence limits, and the problem of estimating the noncentrality parameter has been addressed. As in Parts 1-3, extensive Monte Carlo simulations were performed and all the simulation results were found to be in excellent agreement with the derived theoretical expressions. Specific recommendations for harmonization of detection limit methodology have also been made.

Precise Measurement of the Neutrino Mixing Parameter θ23 from Muon Neutrino Disappearance in an Off-Axis Beam

NASA Astrophysics Data System (ADS)

Abe, K.; Adam, J.; Aihara, H.; Akiri, T.; Andreopoulos, C.; Aoki, S.; Ariga, A.; Ariga, T.; Assylbekov, S.; Autiero, D.; Barbi, M.; Barker, G. J.; Barr, G.; Bass, M.; Batkiewicz, M.; Bay, F.; Bentham, S. W.; Berardi, V.; Berger, B. E.; Berkman, S.; Bertram, I.; Bhadra, S.; Blaszczyk, F. d. M.; Blondel, A.; Bojechko, C.; Bordoni, S.; Boyd, S. B.; Brailsford, D.; Bravar, A.; Bronner, C.; Buchanan, N.; Calland, R. G.; Caravaca Rodríguez, J.; Cartwright, S. L.; Castillo, R.; Catanesi, M. G.; Cervera, A.; Cherdack, D.; Christodoulou, G.; Clifton, A.; Coleman, J.; Coleman, S. J.; Collazuol, G.; Connolly, K.; Cremonesi, L.; Dabrowska, A.; Danko, I.; Das, R.; Davis, S.; de Perio, P.; De Rosa, G.; Dealtry, T.; Dennis, S. R.; Densham, C.; Di Lodovico, F.; Di Luise, S.; Drapier, O.; Duboyski, T.; Duffy, K.; Dufour, F.; Dumarchez, J.; Dytman, S.; Dziewiecki, M.; Emery, S.; Ereditato, A.; Escudero, L.; Finch, A. J.; Floetotto, L.; Friend, M.; Fujii, Y.; Fukuda, Y.; Furmanski, A. P.; Galymov, V.; Giffin, S.; Giganti, C.; Gilje, K.; Goeldi, D.; Golan, T.; Gonin, M.; Grant, N.; Gudin, D.; Hadley, D. R.; Haesler, A.; Haigh, M. D.; Hamilton, P.; Hansen, D.; Hara, T.; Hartz, M.; Hasegawa, T.; Hastings, N. C.; Hayato, Y.; Hearty, C.; Helmer, R. L.; Hierholzer, M.; Hignight, J.; Hillairet, A.; Himmel, A.; Hiraki, T.; Hirota, S.; Holeczek, J.; Horikawa, S.; Huang, K.; Ichikawa, A. K.; Ieki, K.; Ieva, M.; Ikeda, M.; Imber, J.; Insler, J.; Irvine, T. J.; Ishida, T.; Ishii, T.; Ives, S. J.; Iwai, E.; Iyogi, K.; Izmaylov, A.; Jacob, A.; Jamieson, B.; Johnson, R. A.; Jo, J. H.; Jonsson, P.; Jung, C. K.; Kabirnezhad, M.; Kaboth, A. C.; Kajita, T.; Kakuno, H.; Kameda, J.; Kanazawa, Y.; Karlen, D.; Karpikov, I.; Kearns, E.; Khabibullin, M.; Khotjantsev, A.; Kielczewska, D.; Kikawa, T.; Kilinski, A.; Kim, J.; Kisiel, J.; Kitching, P.; Kobayashi, T.; Koch, L.; Kolaceke, A.; Konaka, A.; Kormos, L. L.; Korzenev, A.; Koseki, K.; Koshio, Y.; Kreslo, I.; Kropp, W.; Kubo, H.; Kudenko, Y.; Kumaratunga, S.; Kurjata, R.; Kutter, T.; Lagoda, J.; Laihem, K.; Lamont, I.; Laveder, M.; Lawe, M.; Lazos, M.; Lee, K. P.; Lindner, T.; Lister, C.; Litchfield, R. P.; Longhin, A.; Ludovici, L.; Macaire, M.; Magaletti, L.; Mahn, K.; Malek, M.; Manly, S.; Marino, A. D.; Marteau, J.; Martin, J. F.; Maruyama, T.; Marzec, J.; Mathie, E. L.; Matveev, V.; Mavrokoridis, K.; Mazzucato, E.; McCarthy, M.; McCauley, N.; McFarland, K. S.; McGrew, C.; Metelko, C.; Mezzetto, M.; Mijakowski, P.; Miller, C. A.; Minamino, A.; Mineev, O.; Mine, S.; Missert, A.; Miura, M.; Monfregola, L.; Moriyama, S.; Mueller, Th. A.; Murakami, A.; Murdoch, M.; Murphy, S.; Myslik, J.; Nagasaki, T.; Nakadaira, T.; Nakahata, M.; Nakai, T.; Nakamura, K.; Nakayama, S.; Nakaya, T.; Nakayoshi, K.; Naples, D.; Nielsen, C.; Nirkko, M.; Nishikawa, K.; Nishimura, Y.; O'Keeffe, H. M.; Ohta, R.; Okumura, K.; Okusawa, T.; Oryszczak, W.; Oser, S. M.; Owen, R. A.; Oyama, Y.; Palladino, V.; Palomino, J.; Paolone, V.; Payne, D.; Perevozchikov, O.; Perkin, J. D.; Petrov, Y.; Pickard, L.; Pinzon Guerra, E. S.; Pistillo, C.; Plonski, P.; Poplawska, E.; Popov, B.; Posiadala, M.; Poutissou, J.-M.; Poutissou, R.; Przewlocki, P.; Quilain, B.; Radicioni, E.; Ratoff, P. N.; Ravonel, M.; Rayner, M. A. M.; Redij, A.; Reeves, M.; Reinherz-Aronis, E.; Retiere, F.; Robert, A.; Rodrigues, P. A.; Rojas, P.; Rondio, E.; Roth, S.; Rubbia, A.; Ruterbories, D.; Sacco, R.; Sakashita, K.; Sánchez, F.; Sato, F.; Scantamburlo, E.; Scholberg, K.; Schoppmann, S.; Schwehr, J.; Scott, M.; Seiya, Y.; Sekiguchi, T.; Sekiya, H.; Sgalaberna, D.; Shiozawa, M.; Short, S.; Shustrov, Y.; Sinclair, P.; Smith, B.; Smith, R. J.; Smy, M.; Sobczyk, J. T.; Sobel, H.; Sorel, M.; Southwell, L.; Stamoulis, P.; Steinmann, J.; Still, B.; Suda, Y.; Suzuki, A.; Suzuki, K.; Suzuki, S. Y.; Suzuki, Y.; Szeglowski, T.; Tacik, R.; Tada, M.; Takahashi, S.; Takeda, A.; Takeuchi, Y.; Tanaka, H. K.; Tanaka, H. A.; Tanaka, M. M.; Terhorst, D.; Terri, R.; Thompson, L. F.; Thorley, A.; Tobayama, S.; Toki, W.; Tomura, T.; Totsuka, Y.; Touramanis, C.; Tsukamoto, T.; Tzanov, M.; Uchida, Y.; Ueno, K.; Vacheret, A.; Vagins, M.; Vasseur, G.; Wachala, T.; Waldron, A. V.; Walter, C. W.; Wark, D.; Wascko, M. O.; Weber, A.; Wendell, R.; Wilkes, R. J.; Wilking, M. J.; Wilkinson, C.; Williamson, Z.; Wilson, J. R.; Wilson, R. J.; Wongjirad, T.; Yamada, Y.; Yamamoto, K.; Yanagisawa, C.; Yen, S.; Yershov, N.; Yokoyama, M.; Yuan, T.; Yu, M.; Zalewska, A.; Zalipska, J.; Zambelli, L.; Zaremba, K.; Ziembicki, M.; Zimmerman, E. D.; Zito, M.; Żmuda, J.; T2K Collaboration

2014-05-01

New data from the T2K neutrino oscillation experiment produce the most precise measurement of the neutrino mixing parameter θ23. Using an off-axis neutrino beam with a peak energy of 0.6 GeV and a data set corresponding to 6.57×1020 protons on target, T2K has fit the energy-dependent νμ oscillation probability to determine oscillation parameters. The 68% confidence limit on sin2(θ23) is 0.514-0.056+0.055 (0.511±0.055), assuming normal (inverted) mass hierarchy. The best-fit mass-squared splitting for normal hierarchy is Δm322=(2.51±0.10)×10-3 eV2/c4 (inverted hierarchy: Δm132=(2.48±0.10)×10-3 eV2/c4). Adding a model of multinucleon interactions that affect neutrino energy reconstruction is found to produce only small biases in neutrino oscillation parameter extraction at current levels of statistical uncertainty.

Prevalence of shigellosis in the U.S.: consistency with dose-response information.

PubMed

Crockett, C S; Haas, C N; Fazil, A; Rose, J B; Gerba, C P

1996-06-01

Every year there are estimated 300000 cases of Shigella in the United States (Bennett et al., 1987, Am. J. Prev. Med. 3, 102-114). A beta-poisson model was fit to human dose-response information on pathogenic Shigella using the Maximum Likelihood Estimation technique (Haas, 1983, Am. J. Epidemiol. 118, 573-582). Pooled and separate data sets for the Shigella species were fit to the beta-Poisson model and 95% confidence limits and regions were calculated. Shigella dysentariae and Shigella flexneri confidence regions and limits overlapped with each other and with the pooled data set, suggesting that this model can describe Shigella in general. The pooled Shigella model as well as the upper and lower confidence limits of the three data sets showed average exposures based on the estimated U.S. caseload of pathogenic Shigella of 0.01 to 0.014 organisms (confidence limits 0.001-0.05) for a 7-day per annum period of exposure and ranges from 0.07 to 0.1 organisms (confidence limits 0.006-0.4). for a 1-day per annum period of exposure. The plausibility of the pooled dose-response model was then evaluated by comparison with two known cruise ship outbreaks. The pooled model estimated that the two outbreaks studied could have been due to ingestion of 344 (confidence limits 72-915) Shigella cells per meal and 10.5-12 (confidence limits 1-44) Shigella cells per glass of water by passengers.

Method and system for assigning a confidence metric for automated determination of optic disc location

DOEpatents

Karnowski, Thomas P [Knoxville, TN; Tobin, Jr., Kenneth W.; Muthusamy Govindasamy, Vijaya Priya [Knoxville, TN; Chaum, Edward [Memphis, TN

2012-07-10

A method for assigning a confidence metric for automated determination of optic disc location that includes analyzing a retinal image and determining at least two sets of coordinates locating an optic disc in the retinal image. The sets of coordinates can be determined using first and second image analysis techniques that are different from one another. An accuracy parameter can be calculated and compared to a primary risk cut-off value. A high confidence level can be assigned to the retinal image if the accuracy parameter is less than the primary risk cut-off value and a low confidence level can be assigned to the retinal image if the accuracy parameter is greater than the primary risk cut-off value. The primary risk cut-off value being selected to represent an acceptable risk of misdiagnosis of a disease having retinal manifestations by the automated technique.

A Monte Carlo Technique Suitable for Obtaining Complex Space System Reliability Confidence Limits from Component Test Data with Three Unknown Parameters.

DTIC Science & Technology

1982-12-01

093 .031 .026 E 116,292 56,424 44,906 12,354 L.L.S. c 2280 802 351 OW Average k .360 .074* .022* .009* Slope f 116,892 51,187 35,276 8,318 Modified c...LE.O.)THEN gELY =1. RGE1=RGE 1.1 ELS E X (CT-C) /THETA)**KI IF(XeLTo20.)THE4. RErLY=EXP(-X) ELSE RELY=O. END IF E"’D IF RETURN EN) 66 I APPENDIX B

40 CFR Appendix A to Subpart Kk of... - Data Quality Objective and Lower Confidence Limit Approaches for Alternative Capture Efficiency...

Code of Federal Regulations, 2013 CFR

2013-07-01

... approach follows: 4.3A source conducts an initial series of at least three runs. The owner or operator may... Confidence Limit Approaches for Alternative Capture Efficiency Protocols and Test Methods A Appendix A to... to Subpart KK of Part 63—Data Quality Objective and Lower Confidence Limit Approaches for Alternative...

40 CFR Appendix A to Subpart Kk of... - Data Quality Objective and Lower Confidence Limit Approaches for Alternative Capture Efficiency...

Code of Federal Regulations, 2010 CFR

2010-07-01

... approach follows: 4.3A source conducts an initial series of at least three runs. The owner or operator may... Confidence Limit Approaches for Alternative Capture Efficiency Protocols and Test Methods A Appendix A to... to Subpart KK of Part 63—Data Quality Objective and Lower Confidence Limit Approaches for Alternative...

40 CFR Appendix A to Subpart Kk of... - Data Quality Objective and Lower Confidence Limit Approaches for Alternative Capture Efficiency...

Code of Federal Regulations, 2014 CFR

2014-07-01

... of the LCL approach follows: 4.3A source conducts an initial series of at least three runs. The owner... Confidence Limit Approaches for Alternative Capture Efficiency Protocols and Test Methods A Appendix A to... to Subpart KK of Part 63—Data Quality Objective and Lower Confidence Limit Approaches for Alternative...

40 CFR Appendix A to Subpart Kk of... - Data Quality Objective and Lower Confidence Limit Approaches for Alternative Capture Efficiency...

Code of Federal Regulations, 2012 CFR

2012-07-01

... approach follows: 4.3A source conducts an initial series of at least three runs. The owner or operator may... Confidence Limit Approaches for Alternative Capture Efficiency Protocols and Test Methods A Appendix A to... to Subpart KK of Part 63—Data Quality Objective and Lower Confidence Limit Approaches for Alternative...

Developing Confidence Limits For Reliability Of Software

NASA Technical Reports Server (NTRS)

Hayhurst, Kelly J.

1991-01-01

Technique developed for estimating reliability of software by use of Moranda geometric de-eutrophication model. Pivotal method enables straightforward construction of exact bounds with associated degree of statistical confidence about reliability of software. Confidence limits thus derived provide precise means of assessing quality of software. Limits take into account number of bugs found while testing and effects of sampling variation associated with random order of discovering bugs.

Cosmological parameter estimation from CMB and X-ray cluster after Planck

NASA Astrophysics Data System (ADS)

Hu, Jian-Wei; Cai, Rong-Gen; Guo, Zong-Kuan; Hu, Bin

2014-05-01

We investigate constraints on cosmological parameters in three 8-parameter models with the summed neutrino mass as a free parameter, by a joint analysis of CCCP X-ray cluster data, the newly released Planck CMB data as well as some external data sets including baryon acoustic oscillation measurements from the 6dFGS, SDSS DR7 and BOSS DR9 surveys, and Hubble Space Telescope H0 measurement. We find that the combined data strongly favor a non-zero neutrino masses at more than 3σ confidence level in these non-vanilla models. Allowing the CMB lensing amplitude AL to vary, we find AL > 1 at 3σ confidence level. For dark energy with a constant equation of state w, we obtain w < -1 at 3σ confidence level. The estimate of the matter power spectrum amplitude σ8 is discrepant with the Planck value at 2σ confidence level, which reflects some tension between X-ray cluster data and Planck data in these non-vanilla models. The tension can be alleviated by adding a 9% systematic shift in the cluster mass function.

Model structures amplify uncertainty in predicted soil carbon responses to climate change.

PubMed

Shi, Zheng; Crowell, Sean; Luo, Yiqi; Moore, Berrien

2018-06-04

Large model uncertainty in projected future soil carbon (C) dynamics has been well documented. However, our understanding of the sources of this uncertainty is limited. Here we quantify the uncertainties arising from model parameters, structures and their interactions, and how those uncertainties propagate through different models to projections of future soil carbon stocks. Both the vertically resolved model and the microbial explicit model project much greater uncertainties to climate change than the conventional soil C model, with both positive and negative C-climate feedbacks, whereas the conventional model consistently predicts positive soil C-climate feedback. Our findings suggest that diverse model structures are necessary to increase confidence in soil C projection. However, the larger uncertainty in the complex models also suggests that we need to strike a balance between model complexity and the need to include diverse model structures in order to forecast soil C dynamics with high confidence and low uncertainty.

Search for anomalous production of multi-lepton events in p anti-p collisions at s**(1/2) = 1.96-TeV

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

Abulencia, A.; Adelman, Jahred A.; Affolder, T.

2007-01-01

The authors report a search for the anomalous production of events with multiple charged leptons in p{bar p} collisions at {radical}s = 1.96 TeV using a data sample corresponding to an integrated luminosity of 346 pb{sup -1} collected by the CDF II detector at the Fermilab Tevatron. The search is divided into three-lepton and four-or-more-lepton data samples. They observe six events in the three-lepton sample and zero events in the {ge}4-lepton sample. Both numbers of events are consistent with standard model background expectations. Within the framework of an R-parity violating supergravity model, the results are interpreted as mass limits onmore » the lightest neutralino ({bar {chi}}{sub 1}{sup 0}) and chargino ({bar {chi}}{sub 1}{sup {+-}}) particles. For one particular choice of model parameters, the limits are M({bar {chi}}{sub 1}{sup 0}) > 110 GeV/c{sup 2} and M({bar {chi}}{sub 1}{sup {+-}}) > 203 GeV/c{sup 2} at 95% confidence level; the variation of these mass limits with model parameters is presented.« less

Undersampling power-law size distributions: effect on the assessment of extreme natural hazards

USGS Publications Warehouse

Geist, Eric L.; Parsons, Thomas E.

2014-01-01

The effect of undersampling on estimating the size of extreme natural hazards from historical data is examined. Tests using synthetic catalogs indicate that the tail of an empirical size distribution sampled from a pure Pareto probability distribution can range from having one-to-several unusually large events to appearing depleted, relative to the parent distribution. Both of these effects are artifacts caused by limited catalog length. It is more difficult to diagnose the artificially depleted empirical distributions, since one expects that a pure Pareto distribution is physically limited in some way. Using maximum likelihood methods and the method of moments, we estimate the power-law exponent and the corner size parameter of tapered Pareto distributions for several natural hazard examples: tsunamis, floods, and earthquakes. Each of these examples has varying catalog lengths and measurement thresholds, relative to the largest event sizes. In many cases where there are only several orders of magnitude between the measurement threshold and the largest events, joint two-parameter estimation techniques are necessary to account for estimation dependence between the power-law scaling exponent and the corner size parameter. Results indicate that whereas the corner size parameter of a tapered Pareto distribution can be estimated, its upper confidence bound cannot be determined and the estimate itself is often unstable with time. Correspondingly, one cannot statistically reject a pure Pareto null hypothesis using natural hazard catalog data. Although physical limits to the hazard source size and by attenuation mechanisms from source to site constrain the maximum hazard size, historical data alone often cannot reliably determine the corner size parameter. Probabilistic assessments incorporating theoretical constraints on source size and propagation effects are preferred over deterministic assessments of extreme natural hazards based on historic data.

rFRET: A comprehensive, Matlab-based program for analyzing intensity-based ratiometric microscopic FRET experiments.

PubMed

Nagy, Peter; Szabó, Ágnes; Váradi, Tímea; Kovács, Tamás; Batta, Gyula; Szöllősi, János

2016-04-01

Fluorescence or Förster resonance energy transfer (FRET) remains one of the most widely used methods for assessing protein clustering and conformation. Although it is a method with solid physical foundations, many applications of FRET fall short of providing quantitative results due to inappropriate calibration and controls. This shortcoming is especially valid for microscopy where currently available tools have limited or no capability at all to display parameter distributions or to perform gating. Since users of multiparameter flow cytometry usually apply these tools, the absence of these features in applications developed for microscopic FRET analysis is a significant limitation. Therefore, we developed a graphical user interface-controlled Matlab application for the evaluation of ratiometric, intensity-based microscopic FRET measurements. The program can calculate all the necessary overspill and spectroscopic correction factors and the FRET efficiency and it displays the results on histograms and dot plots. Gating on plots and mask images can be used to limit the calculation to certain parts of the image. It is an important feature of the program that the calculated parameters can be determined by regression methods, maximum likelihood estimation (MLE) and from summed intensities in addition to pixel-by-pixel evaluation. The confidence interval of calculated parameters can be estimated using parameter simulations if the approximate average number of detected photons is known. The program is not only user-friendly, but it provides rich output, it gives the user freedom to choose from different calculation modes and it gives insight into the reliability and distribution of the calculated parameters. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Comparison of three-parameter kinetic model analysis to standard Patlak's analysis in 18F-FDG PET imaging of lung cancer patients.

PubMed

Laffon, E; Calcagni, M L; Galli, G; Giordano, A; Capotosti, A; Marthan, R; Indovina, L

2018-03-27

Patlak's graphical analysis can provide tracer net influx constant (Ki) with limitation of assuming irreversible tracer trapping, that is, release rate constant (k b ) set to zero. We compared linear Patlak's analysis to non-linear three-compartment three-parameter kinetic model analysis (3P-KMA) providing Ki, k b , and fraction of free 18 F-FDG in blood and interstitial volume (V b ). Dynamic PET data of 21 lung cancer patients were retrospectively analyzed, yielding for each patient an 18 F-FDG input function (IF) and a tissue time-activity curve. The former was fitted with a three-exponentially decreasing function, and the latter was fitted with an analytical formula involving the fitted IF data (11 data points, ranging 7.5-57.5 min post-injection). Bland-Altman analysis was used for Ki comparison between Patlak's analysis and 3P-KMA. Additionally, a three-compartment five-parameter KMA (5P-KMA) was implemented for comparison with Patlak's analysis and 3P-KMA. We found that 3P-KMA Ki was significantly greater than Patlak's Ki over the whole patient series, + 6.0% on average, with limits of agreement of ± 17.1% (95% confidence). Excluding 8 out of 21 patients with k b  > 0 deleted this difference. A strong correlation was found between Ki ratio (=3P-KMA/Patlak) and k b (R = 0.801; P < 0.001). No significant difference in Ki was found between 3P-KMA versus 5P-KMA, and between 5P-KMA versus Patlak's analysis, with limits of agreement of ± 23.0 and ± 31.7% (95% confidence), respectively. Comparison between 3P-KMA and Patlak's analysis significantly showed that the latter underestimates Ki because it arbitrarily set k b to zero: the greater the k b value, the greater the Ki underestimation. This underestimation was not revealed when comparing 5P-KMA and Patlak's analysis. We suggest that further studies are warranted to investigate the 3P-KMA efficiency in various tissues showing greater 18 F-FDG trapping reversibility than lung cancer lesions.

Optimal and Most Exact Confidence Intervals for Person Parameters in Item Response Theory Models

ERIC Educational Resources Information Center

Doebler, Anna; Doebler, Philipp; Holling, Heinz

2013-01-01

The common way to calculate confidence intervals for item response theory models is to assume that the standardized maximum likelihood estimator for the person parameter [theta] is normally distributed. However, this approximation is often inadequate for short and medium test lengths. As a result, the coverage probabilities fall below the given…

Program for Weibull Analysis of Fatigue Data

NASA Technical Reports Server (NTRS)

Krantz, Timothy L.

2005-01-01

A Fortran computer program has been written for performing statistical analyses of fatigue-test data that are assumed to be adequately represented by a two-parameter Weibull distribution. This program calculates the following: (1) Maximum-likelihood estimates of the Weibull distribution; (2) Data for contour plots of relative likelihood for two parameters; (3) Data for contour plots of joint confidence regions; (4) Data for the profile likelihood of the Weibull-distribution parameters; (5) Data for the profile likelihood of any percentile of the distribution; and (6) Likelihood-based confidence intervals for parameters and/or percentiles of the distribution. The program can account for tests that are suspended without failure (the statistical term for such suspension of tests is "censoring"). The analytical approach followed in this program for the software is valid for type-I censoring, which is the removal of unfailed units at pre-specified times. Confidence regions and intervals are calculated by use of the likelihood-ratio method.

A framework for streamflow prediction in the world's most severely data-limited regions: Test of applicability and performance in a poorly-gauged region of China

NASA Astrophysics Data System (ADS)

Alipour, M. H.; Kibler, Kelly M.

2018-02-01

A framework methodology is proposed for streamflow prediction in poorly-gauged rivers located within large-scale regions of sparse hydrometeorologic observation. A multi-criteria model evaluation is developed to select models that balance runoff efficiency with selection of accurate parameter values. Sparse observed data are supplemented by uncertain or low-resolution information, incorporated as 'soft' data, to estimate parameter values a priori. Model performance is tested in two catchments within a data-poor region of southwestern China, and results are compared to models selected using alternative calibration methods. While all models perform consistently with respect to runoff efficiency (NSE range of 0.67-0.78), models selected using the proposed multi-objective method may incorporate more representative parameter values than those selected by traditional calibration. Notably, parameter values estimated by the proposed method resonate with direct estimates of catchment subsurface storage capacity (parameter residuals of 20 and 61 mm for maximum soil moisture capacity (Cmax), and 0.91 and 0.48 for soil moisture distribution shape factor (B); where a parameter residual is equal to the centroid of a soft parameter value minus the calibrated parameter value). A model more traditionally calibrated to observed data only (single-objective model) estimates a much lower soil moisture capacity (residuals of Cmax = 475 and 518 mm and B = 1.24 and 0.7). A constrained single-objective model also underestimates maximum soil moisture capacity relative to a priori estimates (residuals of Cmax = 246 and 289 mm). The proposed method may allow managers to more confidently transfer calibrated models to ungauged catchments for streamflow predictions, even in the world's most data-limited regions.

Introduction to Sample Size Choice for Confidence Intervals Based on "t" Statistics

ERIC Educational Resources Information Center

Liu, Xiaofeng Steven; Loudermilk, Brandon; Simpson, Thomas

2014-01-01

Sample size can be chosen to achieve a specified width in a confidence interval. The probability of obtaining a narrow width given that the confidence interval includes the population parameter is defined as the power of the confidence interval, a concept unfamiliar to many practitioners. This article shows how to utilize the Statistical Analysis…

TARGETED SEQUENTIAL DESIGN FOR TARGETED LEARNING INFERENCE OF THE OPTIMAL TREATMENT RULE AND ITS MEAN REWARD.

PubMed

Chambaz, Antoine; Zheng, Wenjing; van der Laan, Mark J

2017-01-01

This article studies the targeted sequential inference of an optimal treatment rule (TR) and its mean reward in the non-exceptional case, i.e. , assuming that there is no stratum of the baseline covariates where treatment is neither beneficial nor harmful, and under a companion margin assumption. Our pivotal estimator, whose definition hinges on the targeted minimum loss estimation (TMLE) principle, actually infers the mean reward under the current estimate of the optimal TR. This data-adaptive statistical parameter is worthy of interest on its own. Our main result is a central limit theorem which enables the construction of confidence intervals on both mean rewards under the current estimate of the optimal TR and under the optimal TR itself. The asymptotic variance of the estimator takes the form of the variance of an efficient influence curve at a limiting distribution, allowing to discuss the efficiency of inference. As a by product, we also derive confidence intervals on two cumulated pseudo-regrets, a key notion in the study of bandits problems. A simulation study illustrates the procedure. One of the corner-stones of the theoretical study is a new maximal inequality for martingales with respect to the uniform entropy integral.

Confidence Sharing: An Economic Strategy for Efficient Information Flows in Animal Groups

PubMed Central

Korman, Amos; Greenwald, Efrat; Feinerman, Ofer

2014-01-01

Social animals may share information to obtain a more complete and accurate picture of their surroundings. However, physical constraints on communication limit the flow of information between interacting individuals in a way that can cause an accumulation of errors and deteriorated collective behaviors. Here, we theoretically study a general model of information sharing within animal groups. We take an algorithmic perspective to identify efficient communication schemes that are, nevertheless, economic in terms of communication, memory and individual internal computation. We present a simple and natural algorithm in which each agent compresses all information it has gathered into a single parameter that represents its confidence in its behavior. Confidence is communicated between agents by means of active signaling. We motivate this model by novel and existing empirical evidences for confidence sharing in animal groups. We rigorously show that this algorithm competes extremely well with the best possible algorithm that operates without any computational constraints. We also show that this algorithm is minimal, in the sense that further reduction in communication may significantly reduce performances. Our proofs rely on the Cramér-Rao bound and on our definition of a Fisher Channel Capacity. We use these concepts to quantify information flows within the group which are then used to obtain lower bounds on collective performance. The abstract nature of our model makes it rigorously solvable and its conclusions highly general. Indeed, our results suggest confidence sharing as a central notion in the context of animal communication. PMID:25275649

Confidence sharing: an economic strategy for efficient information flows in animal groups.

PubMed

Korman, Amos; Greenwald, Efrat; Feinerman, Ofer

2014-10-01

Social animals may share information to obtain a more complete and accurate picture of their surroundings. However, physical constraints on communication limit the flow of information between interacting individuals in a way that can cause an accumulation of errors and deteriorated collective behaviors. Here, we theoretically study a general model of information sharing within animal groups. We take an algorithmic perspective to identify efficient communication schemes that are, nevertheless, economic in terms of communication, memory and individual internal computation. We present a simple and natural algorithm in which each agent compresses all information it has gathered into a single parameter that represents its confidence in its behavior. Confidence is communicated between agents by means of active signaling. We motivate this model by novel and existing empirical evidences for confidence sharing in animal groups. We rigorously show that this algorithm competes extremely well with the best possible algorithm that operates without any computational constraints. We also show that this algorithm is minimal, in the sense that further reduction in communication may significantly reduce performances. Our proofs rely on the Cramér-Rao bound and on our definition of a Fisher Channel Capacity. We use these concepts to quantify information flows within the group which are then used to obtain lower bounds on collective performance. The abstract nature of our model makes it rigorously solvable and its conclusions highly general. Indeed, our results suggest confidence sharing as a central notion in the context of animal communication.

Two Decades of WRF/CMAQ simulations over the continental United States: New approaches for performing dynamic model evaluation and determining confidence limits for ozone exceedances

EPA Science Inventory

Confidence in the application of models for forecasting and regulatory assessments is furthered by conducting four types of model evaluation: operational, dynamic, diagnostic, and probabilistic. Operational model evaluation alone does not reveal the confidence limits that can be ...

Statistical analysis of radioimmunoassay. In comparison with bioassay (in Japanese)

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

Nakano, R.

1973-01-01

Using the data of RIA (radioimmunoassay), statistical procedures for dealing with two problems of the linearization of dose response curve and calculation of relative potency were described. There were three methods for linearization of dose response curve of RIA. In each method, the following parameters were shown on the horizontal and vertical axis: dose x, (B/T)/sup -1/; c/x + c, B/T (C: dose which makes B/T 50%); log x, logit B/T. Among them, the last method seems to be most practical. The statistical procedures for bioassay were employed for calculating the relative potency of unknown samples compared to the standardmore » samples from dose response curves of standand and unknown samples using regression coefficient. It is desirable that relative potency is calculated by plotting more than 5 points in the standard curve and plotting more than 2 points in unknow samples. For examining the statistical limit of precision of measuremert, LH activity of gonadotropin in urine was measured and relative potency, precision coefficient and the upper and lower limits of relative potency at 95% confidence limit were calculated. On the other hand, bioassay (by the ovarian ascorbic acid reduction method and anteriol lobe of prostate weighing method) was done in the same samples, and the precision was compared with that of RIA. In these examinations, the upper and lower limits of the relative potency at 95% confidence limit were near each other, while in bioassay, a considerable difference was observed between the upper and lower limits. The necessity of standardization and systematization of the statistical procedures for increasing the precision of RIA was pointed out. (JA)« less

Monte Carlo simulation of parameter confidence intervals for non-linear regression analysis of biological data using Microsoft Excel.

PubMed

Lambert, Ronald J W; Mytilinaios, Ioannis; Maitland, Luke; Brown, Angus M

2012-08-01

This study describes a method to obtain parameter confidence intervals from the fitting of non-linear functions to experimental data, using the SOLVER and Analysis ToolPaK Add-In of the Microsoft Excel spreadsheet. Previously we have shown that Excel can fit complex multiple functions to biological data, obtaining values equivalent to those returned by more specialized statistical or mathematical software. However, a disadvantage of using the Excel method was the inability to return confidence intervals for the computed parameters or the correlations between them. Using a simple Monte-Carlo procedure within the Excel spreadsheet (without recourse to programming), SOLVER can provide parameter estimates (up to 200 at a time) for multiple 'virtual' data sets, from which the required confidence intervals and correlation coefficients can be obtained. The general utility of the method is exemplified by applying it to the analysis of the growth of Listeria monocytogenes, the growth inhibition of Pseudomonas aeruginosa by chlorhexidine and the further analysis of the electrophysiological data from the compound action potential of the rodent optic nerve. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Cosmological parameter estimation from CMB and X-ray cluster after Planck

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

Hu, Jian-Wei; Cai, Rong-Gen; Guo, Zong-Kuan

We investigate constraints on cosmological parameters in three 8-parameter models with the summed neutrino mass as a free parameter, by a joint analysis of CCCP X-ray cluster data, the newly released Planck CMB data as well as some external data sets including baryon acoustic oscillation measurements from the 6dFGS, SDSS DR7 and BOSS DR9 surveys, and Hubble Space Telescope H{sub 0} measurement. We find that the combined data strongly favor a non-zero neutrino masses at more than 3σ confidence level in these non-vanilla models. Allowing the CMB lensing amplitude A{sub L} to vary, we find A{sub L} > 1 atmore » 3σ confidence level. For dark energy with a constant equation of state w, we obtain w < −1 at 3σ confidence level. The estimate of the matter power spectrum amplitude σ{sub 8} is discrepant with the Planck value at 2σ confidence level, which reflects some tension between X-ray cluster data and Planck data in these non-vanilla models. The tension can be alleviated by adding a 9% systematic shift in the cluster mass function.« less

The climate of HD 189733b from fourteen transits and eclipses measured by Spitzer

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

Agol, E.; /Washington U., Seattle, Astron. Dept. /Santa Barbara, KITP /UC, Santa Barbara; Cowan, Nicolas B.

We present observations of six transits and six eclipses of the transiting planet system HD 189733 taken with the Spitzer Space Telescope IRAC camera at 8 microns, as well as a re-analysis of previously published data. We use several novel techniques in our data analysis, the most important of which is a new correction for the detector 'ramp' variation with a double-exponential function which performs better and is a better physical model for this detector variation. Our main scientific findings are: (1) an upper limit on the variability of the day-side planet flux of 2.7% (68% confidence); (2) the mostmore » precise set of transit times measured for a transiting planet, with an average accuracy of 3 seconds; (3) a lack of transit-timing variations, excluding the presence of second planets in this system above 20% of the mass of Mars in low-order mean-motion resonance at 95% confidence; (4) a confirmation of the planet's phase variation, finding the night side is 64% as bright as the day side, as well as an upper limit on the night-side variability of 17% (68% confidence); (5) a better correction for stellar variability at 8 micron causing the phase function to peak 3.5 hours before secondary eclipse, confirming that the advection and radiation timescales are comparable at the 8 micron photosphere; (6) variation in the depth of transit, which possibly implies variations in the surface brightness of the portion of the star occulted by the planet, posing a fundamental limit on non-simultaneous multi-wavelength transit absorption measurements of planet atmospheres; (7) a measurement of the infrared limb-darkening of the star, which is in good agreement with stellar atmosphere models; (8) an offset in the times of secondary eclipse of 69 seconds, which is mostly accounted for by a 31 second light travel time delay and 33 second delay due to the shift of ingress and egress by the planet hot spot; this confirms that the phase variation is due to an offset hot spot on the planet; (9) a retraction of the claimed eccentricity of this system due to the offset of secondary eclipse, which is now just an upper limit; and (10) high precision measurements of the parameters of this system. These results were enabled by the exquisite photometric precision of the Spitzer IRAC camera; for repeat observations the scatter is less than 0.35 mmag over the 590 day time scale of our observations after decorrelating with detector parameters.« less

Using the Nintendo Wii Fit and body weight support to improve aerobic capacity, balance, gait ability, and fear of falling: two case reports.

PubMed

Miller, Carol A; Hayes, Dawn M; Dye, Kelli; Johnson, Courtney; Meyers, Jennifer

2012-01-01

Lower limb amputation in older adults has a significant impact on balance, gait, and cardiovascular fitness, resulting in diminished community participation. The purpose of this case study was to describe the effects of a balance training program utilizing the Nintendo Wii™ Fit (Nintendo of America, Inc, Redmond, Washington) balance board and body-weight supported gait training on aerobic capacity, balance, gait, and fear of falling in two persons with transfemoral amputation. Participant A, a 62 year-old male 32 months post traumatic transfemoral amputation, reported fear of falling and restrictions in community activity. Participant B, a 58 year-old male 9 years post transfemoral amputation, reported limited energy and balance deficits during advanced gait activities. 6-weeks, 2 supervised sessions per week included 20 minutes of Nintendo™ Wii Fit Balance gaming and 20 minutes of gait training using Body Weight Support. Measures included oxygen uptake efficiency slope (OUES), economy of movement, dynamic balance (Biodex platform system), Activities-Specific Balance Confidence (ABC) Scale, and spatial-temporal parameters of gait (GAITRite). Both participants demonstrated improvement in dynamic balance, balance confidence, economy of movement, and spatial-temporal parameters of gait. Participant A reduced the need for an assistive device during community ambulation. Participant B improved his aerobic capacity, indicated by an increase in OUES. This case study illustrated that the use of Nintendo Wii™ Fit training and Body Weight Support were effective interventions to achieve functional goals for improving balance confidence, reducing use of assistive devices, and increasing energy efficiency when ambulating with a transfemoral prosthesis.

Quantile regression models of animal habitat relationships

USGS Publications Warehouse

Cade, Brian S.

2003-01-01

Typically, all factors that limit an organism are not measured and included in statistical models used to investigate relationships with their environment. If important unmeasured variables interact multiplicatively with the measured variables, the statistical models often will have heterogeneous response distributions with unequal variances. Quantile regression is an approach for estimating the conditional quantiles of a response variable distribution in the linear model, providing a more complete view of possible causal relationships between variables in ecological processes. Chapter 1 introduces quantile regression and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of estimates for homogeneous and heterogeneous regression models. Chapter 2 evaluates performance of quantile rankscore tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). A permutation F test maintained better Type I errors than the Chi-square T test for models with smaller n, greater number of parameters p, and more extreme quantiles τ. Both versions of the test required weighting to maintain correct Type I errors when there was heterogeneity under the alternative model. An example application related trout densities to stream channel width:depth. Chapter 3 evaluates a drop in dispersion, F-ratio like permutation test for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). Chapter 4 simulates from a large (N = 10,000) finite population representing grid areas on a landscape to demonstrate various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable (spatially and not spatially structured). Depending on whether interactions of the measured habitat and unmeasured variable were negative (interference interactions) or positive (facilitation interactions), either upper (τ > 0.5) or lower (τ < 0.5) quantile regression parameters were less biased than mean rate parameters. Sampling (n = 20 - 300) simulations demonstrated that confidence intervals constructed by inverting rankscore tests provided valid coverage of these biased parameters. Quantile regression was used to estimate effects of physical habitat resources on a bivalve mussel (Macomona liliana) in a New Zealand harbor by modeling the spatial trend surface as a cubic polynomial of location coordinates.

Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models.

PubMed

Cotten, Cameron; Reed, Jennifer L

2013-01-30

Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets.

Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models

PubMed Central

2013-01-01

Background Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. Results In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. Conclusions This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets. PMID:23360254

Search for new phenomena in monophoton final states in proton–proton collisions at s = 8  TeV

DOE PAGES

Khachatryan, V.

2016-02-01

In this paper, results are presented from a search for new physics in final states containing a photon and missing transverse momentum. The data correspond to an integrated luminosity of 19.6 fb -1 collected in proton–proton collisions at √s = 8 TeV with the CMS experiment at the LHC. No deviation from the standard model predictions is observed for these final states. New, improved limits are set on dark matter production and on parameters of models with large extra dimensions. In particular, the first limits from the LHC on branon production are found and significantly extend previous limits from LEPmore » and the Tevatron. Finally, an upper limit of 14.0 fb on the cross section is set at the 95% confidence level for events with a monophoton final state with photon transverse momentum greater than 145 GeV and missing transverse momentum greater than 140 GeV.« less

CalFitter: a web server for analysis of protein thermal denaturation data.

PubMed

Mazurenko, Stanislav; Stourac, Jan; Kunka, Antonin; Nedeljkovic, Sava; Bednar, David; Prokop, Zbynek; Damborsky, Jiri

2018-05-14

Despite significant advances in the understanding of protein structure-function relationships, revealing protein folding pathways still poses a challenge due to a limited number of relevant experimental tools. Widely-used experimental techniques, such as calorimetry or spectroscopy, critically depend on a proper data analysis. Currently, there are only separate data analysis tools available for each type of experiment with a limited model selection. To address this problem, we have developed the CalFitter web server to be a unified platform for comprehensive data fitting and analysis of protein thermal denaturation data. The server allows simultaneous global data fitting using any combination of input data types and offers 12 protein unfolding pathway models for selection, including irreversible transitions often missing from other tools. The data fitting produces optimal parameter values, their confidence intervals, and statistical information to define unfolding pathways. The server provides an interactive and easy-to-use interface that allows users to directly analyse input datasets and simulate modelled output based on the model parameters. CalFitter web server is available free at https://loschmidt.chemi.muni.cz/calfitter/.

Search for the neutral MSSM Higgs bosons in the ditau decay channels at CDF Run II

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

Almenar, Cristobal Cuenca

2008-04-01

This thesis presents the results on a search for the neutral MSSM Higgs bosons decaying to tau pairs, with least one of these taus decays leptonically. The search was performed with a sample of 1.8 fb -1 of proton-antiproton collisions at √s = 1.96 TeV provided by the Tevatron and collected by CDF Run II. No significant excess over the Standard Model prediction was found and a 95% confidence level exclusion limit have been set on the cross section times branching ratio as a function of the Higgs boson mass. This limit has been translated into the MSSM Higgs sectormore » parameter plane, tanβ vs. M A, for the four different benchmark scenarios.« less

First LIGO search for gravitational wave bursts from cosmic (super)strings

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Adhikari, R.; Ajith, P.; Allen, B.; Allen, G.; Amin, R. S.; Anderson, S. B.; Anderson, W. G.; Arain, M. A.; Araya, M.; Armandula, H.; Armor, P.; Aso, Y.; Aston, S.; Aufmuth, P.; Aulbert, C.; Babak, S.; Baker, P.; Ballmer, S.; Barker, C.; Barker, D.; Barr, B.; Barriga, P.; Barsotti, L.; Barton, M. A.; Bartos, I.; Bassiri, R.; Bastarrika, M.; Behnke, B.; Benacquista, M.; Betzwieser, J.; Beyersdorf, P. T.; Bilenko, I. A.; Billingsley, G.; Biswas, R.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Bland, B.; Bodiya, T. P.; Bogue, L.; Bork, R.; Boschi, V.; Bose, S.; Brady, P. R.; Braginsky, V. B.; Brau, J. E.; Bridges, D. O.; Brinkmann, M.; Brooks, A. F.; Brown, D. A.; Brummit, A.; Brunet, G.; Bullington, A.; Buonanno, A.; Burmeister, O.; Byer, R. L.; Cadonati, L.; Camp, J. B.; Cannizzo, J.; Cannon, K. C.; Cao, J.; Cardenas, L.; Caride, S.; Castaldi, G.; Caudill, S.; Cavaglià, M.; Cepeda, C.; Chalermsongsak, T.; Chalkley, E.; Charlton, P.; Chatterji, S.; Chelkowski, S.; Chen, Y.; Christensen, N.; Chung, C. T. Y.; Clark, D.; Clark, J.; Clayton, J. H.; Cokelaer, T.; Colacino, C. N.; Conte, R.; Cook, D.; Corbitt, T. R. C.; Cornish, N.; Coward, D.; Coyne, D. C.; Creighton, J. D. E.; Creighton, T. D.; Cruise, A. M.; Culter, R. M.; Cumming, A.; Cunningham, L.; Danilishin, S. L.; Danzmann, K.; Daudert, B.; Davies, G.; Daw, E. J.; Debra, D.; Degallaix, J.; Dergachev, V.; Desai, S.; Desalvo, R.; Dhurandhar, S.; Díaz, M.; Dietz, A.; Donovan, F.; Dooley, K. L.; Doomes, E. E.; Drever, R. W. P.; Dueck, J.; Duke, I.; Dumas, J.-C.; Dwyer, J. G.; Echols, C.; Edgar, M.; Effler, A.; Ehrens, P.; Espinoza, E.; Etzel, T.; Evans, M.; Evans, T.; Fairhurst, S.; Faltas, Y.; Fan, Y.; Fazi, D.; Fehrmann, H.; Finn, L. S.; Flasch, K.; Foley, S.; Forrest, C.; Fotopoulos, N.; Franzen, A.; Frede, M.; Frei, M.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T.; Fritschel, P.; Frolov, V. V.; Fyffe, M.; Galdi, V.; Garofoli, J. A.; Gholami, I.; Giaime, J. A.; Giampanis, S.; Giardina, K. D.; Goda, K.; Goetz, E.; Goggin, L. M.; González, G.; Gorodetsky, M. L.; Goßler, S.; Gouaty, R.; Grant, A.; Gras, S.; Gray, C.; Gray, M.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Grimaldi, F.; Grosso, R.; Grote, H.; Grunewald, S.; Guenther, M.; Gustafson, E. K.; Gustafson, R.; Hage, B.; Hallam, J. M.; Hammer, D.; Hammond, G. D.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Haughian, K.; Hayama, K.; Heefner, J.; Heng, I. S.; Heptonstall, A.; Hewitson, M.; Hild, S.; Hirose, E.; Hoak, D.; Hodge, K. A.; Holt, K.; Hosken, D. J.; Hough, J.; Hoyland, D.; Hughey, B.; Huttner, S. H.; Ingram, D. R.; Isogai, T.; Ito, M.; Ivanov, A.; Johnson, B.; Johnson, W. W.; Jones, D. I.; Jones, G.; Jones, R.; Ju, L.; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kanner, J.; Kasprzyk, D.; Katsavounidis, E.; Kawabe, K.; Kawamura, S.; Kawazoe, F.; Kells, W.; Keppel, D. G.; Khalaidovski, A.; Khalili, F. Y.; Khan, R.; Khazanov, E.; King, P.; Kissel, J. S.; Klimenko, S.; Kokeyama, K.; Kondrashov, V.; Kopparapu, R.; Koranda, S.; Kozak, D.; Krishnan, B.; Kumar, R.; Kwee, P.; Lam, P. K.; Landry, M.; Lantz, B.; Lazzarini, A.; Lei, H.; Lei, M.; Leindecker, N.; Leonor, I.; Li, C.; Lin, H.; Lindquist, P. E.; Littenberg, T. B.; Lockerbie, N. A.; Lodhia, D.; Longo, M.; Lormand, M.; Lu, P.; Lubiński, M.; Lucianetti, A.; Lück, H.; Machenschalk, B.; Macinnis, M.; Mageswaran, M.; Mailand, K.; Mandel, I.; Mandic, V.; Márka, S.; Márka, Z.; Markosyan, A.; Markowitz, J.; Maros, E.; Martin, I. W.; Martin, R. M.; Marx, J. N.; Mason, K.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McHugh, M.; McIntyre, G.; McKechan, D. J. A.; McKenzie, K.; Mehmet, M.; Melatos, A.; Melissinos, A. C.; Menéndez, D. F.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyer, M. S.; Miller, J.; Minelli, J.; Mino, Y.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Miyakawa, O.; Moe, B.; Mohanty, S. D.; Mohapatra, S. R. P.; Moreno, G.; Morioka, T.; Mors, K.; Mossavi, K.; Mowlowry, C.; Mueller, G.; Müller-Ebhardt, H.; Muhammad, D.; Mukherjee, S.; Mukhopadhyay, H.; Mullavey, A.; Munch, J.; Murray, P. G.; Myers, E.; Myers, J.; Nash, T.; Nelson, J.; Newton, G.; Nishizawa, A.; Numata, K.; O'Dell, J.; O'Reilly, B.; O'Shaughnessy, R.; Ochsner, E.; Ogin, G. H.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pan, Y.; Pankow, C.; Papa, M. A.; Parameshwaraiah, V.; Patel, P.; Pedraza, M.; Penn, S.; Perreca, A.; Pierro, V.; Pinto, I. M.; Pitkin, M.; Pletsch, H. J.; Plissi, M. V.; Postiglione, F.; Principe, M.; Prix, R.; Prokhorov, L.; Punken, O.; Quetschke, V.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raics, Z.; Rainer, N.; Rakhmanov, M.; Raymond, V.; Reed, C. M.; Reed, T.; Rehbein, H.; Reid, S.; Reitze, D. H.; Riesen, R.; Riles, K.; Rivera, B.; Roberts, P.; Robertson, N. A.; Robinson, C.; Robinson, E. L.; Roddy, S.; Röver, C.; Rollins, J.; Romano, J. D.; Romie, J. H.; Rowan, S.; Rüdiger, A.; Russell, P.; Ryan, K.; Sakata, S.; Sancho de La Jordana, L.; Sandberg, V.; Sannibale, V.; Santamaría, L.; Saraf, S.; Sarin, P.; Sathyaprakash, B. S.; Sato, S.; Satterthwaite, M.; Saulson, P. R.; Savage, R.; Savov, P.; Scanlan, M.; Schilling, R.; Schnabel, R.; Schofield, R.; Schulz, B.; Schutz, B. F.; Schwinberg, P.; Scott, J.; Scott, S. M.; Searle, A. C.; Sears, B.; Seifert, F.; Sellers, D.; Sengupta, A. S.; Sergeev, A.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sibley, A.; Siemens, X.; Sigg, D.; Sinha, S.; Sintes, A. M.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M. R.; Smith, N. D.; Somiya, K.; Sorazu, B.; Stein, A.; Stein, L. C.; Steplewski, S.; Stochino, A.; Stone, R.; Strain, K. A.; Strigin, S.; Stroeer, A.; Stuver, A. L.; Summerscales, T. Z.; Sun, K.-X.; Sung, M.; Sutton, P. J.; Szokoly, G. P.; Talukder, D.; Tang, L.; Tanner, D. B.; Tarabrin, S. P.; Taylor, J. R.; Taylor, R.; Thacker, J.; Thorne, K. A.; Thorne, K. S.; Thüring, A.; Tokmakov, K. V.; Torres, C.; Torrie, C.; Traylor, G.; Trias, M.; Ugolini, D.; Ulmen, J.; Urbanek, K.; Vahlbruch, H.; Vallisneri, M.; van den Broeck, C.; van der Sluys, M. V.; van Veggel, A. A.; Vass, S.; Vaulin, R.; Vecchio, A.; Veitch, J.; Veitch, P.; Veltkamp, C.; Villar, A.; Vorvick, C.; Vyachanin, S. P.; Waldman, S. J.; Wallace, L.; Ward, R. L.; Weidner, A.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wen, S.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; Whiting, B. F.; Wilkinson, C.; Willems, P. A.; Williams, H. R.; Williams, L.; Willke, B.; Wilmut, I.; Winkelmann, L.; Winkler, W.; Wipf, C. C.; Wiseman, A. G.; Woan, G.; Wooley, R.; Worden, J.; Wu, W.; Yakushin, I.; Yamamoto, H.; Yan, Z.; Yoshida, S.; Zanolin, M.; Zhang, J.; Zhang, L.; Zhao, C.; Zotov, N.; Zucker, M. E.; Zur Mühlen, H.; Zweizig, J.; Robinet, F.

2009-09-01

We report on a matched-filter search for gravitational wave bursts from cosmic string cusps using LIGO data from the fourth science run (S4) which took place in February and March 2005. No gravitational waves were detected in 14.9 days of data from times when all three LIGO detectors were operating. We interpret the result in terms of a frequentist upper limit on the rate of gravitational wave bursts and use the limits on the rate to constrain the parameter space (string tension, reconnection probability, and loop sizes) of cosmic string models. Many grand unified theory-scale models (with string tension Gμ/c2≈10-6) can be ruled out at 90% confidence for reconnection probabilities p≤10-3 if loop sizes are set by gravitational back reaction.

VizieR Online Data Catalog: Stellar and planet properties for K2 candidates (Montet+, 2015)

NASA Astrophysics Data System (ADS)

Montet, B. T.; Morton, T. D.; Foreman-Mackey, D.; Johnson, J. A.; Hogg, D. W.; Bowler, B. P.; Latham, D. W.; Bieryla, A.; Mann, A. W.

2017-09-01

In this paper, we present stellar and planetary parameters for each system. We also analyze the false positive probability (FPP) of each system using vespa, a new publicly available, general-purpose implementation of the Morton (2012ApJ...761....6M) procedure to calculate FPPs for transiting planets. Through this analysis, as well as archival imaging, ground-based seeing-limited survey data, and adaptive optics imaging, we are able to confirm 21 of these systems as transiting planets at the 99% confidence level. Additionally, we identify six systems as false positives. (5 data files).

Development of welding emission factors for Cr and Cr(VI) with a confidence level.

PubMed

Serageldin, Mohamed; Reeves, David W

2009-05-01

Knowledge of the emission rate and release characteristics is necessary for estimating pollutant fate and transport. Because emission measurements at a facility's fence line are generally not readily available, environmental agencies in many countries are using emission factors (EFs) to indicate the quantity of certain pollutants released into the atmosphere from operations such as welding. The amount of fumes and metals generated from a welding process is dependent on many parameters, such as electrode composition, voltage, and current. Because test reports on fume generation provide different levels of detail, a common approach was used to give a test report a quality rating on the basis of several highly subjective criteria; however, weighted average EFs generated in this way are not meant to reflect data precision or to be used for a refined risk analysis. The 95% upper confidence limit (UCL) of the unknown population mean was used in this study to account for the uncertainty in the EF test data. Several parametric UCLs were computed and compared for multiple welding EFs associated with several mild, stainless, and alloy steels. Also, several nonparametric statistical methods, including several bootstrap procedures, were used to compute 95% UCLs. For the nonparametric methods, a distribution for calculating the mean, standard deviation, and other statistical parameters for a dataset does not need to be assumed. There were instances when the sample size was small and instances when EFs for an electrode/process combination were not found. Those two points are addressed in this paper. Finally, this paper is an attempt to deal with the uncertainty in the value of a mean EF for an electrode/process combination that is based on test data from several laboratories. Welding EFs developed with a defined level of confidence may be used as input parameters for risk assessment.

APOSTLE: 11 TRANSIT OBSERVATIONS OF TrES-3b

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

Kundurthy, P.; Becker, A. C.; Agol, E.

2013-02-10

The Apache Point Survey of Transit Lightcurves of Exoplanets (APOSTLE) observed 11 transits of TrES-3b over two years in order to constrain system parameters and look for transit timing and depth variations. We describe an updated analysis protocol for APOSTLE data, including the reduction pipeline, transit model, and Markov Chain Monte Carlo analyzer. Our estimates of the system parameters for TrES-3b are consistent with previous estimates to within the 2{sigma} confidence level. We improved the errors (by 10%-30%) on system parameters such as the orbital inclination (i {sub orb}), impact parameter (b), and stellar density ({rho}{sub *}) compared to previousmore » measurements. The near-grazing nature of the system, and incomplete sampling of some transits, limited our ability to place reliable uncertainties on individual transit depths and hence we do not report strong evidence for variability. Our analysis of the transit timing data shows no evidence for transit timing variations and our timing measurements are able to rule out super-Earth and gas giant companions in low-order mean motion resonance with TrES-3b.« less

Synchrony in Joint Action Is Directed by Each Participant’s Motor Control System

PubMed Central

Noy, Lior; Weiser, Netta; Friedman, Jason

2017-01-01

In this work, we ask how the probability of achieving synchrony in joint action is affected by the choice of motion parameters of each individual. We use the mirror game paradigm to study how changes in leader’s motion parameters, specifically frequency and peak velocity, affect the probability of entering the state of co-confidence (CC) motion: a dyadic state of synchronized, smooth and co-predictive motions. In order to systematically study this question, we used a one-person version of the mirror game, where the participant mirrored piece-wise rhythmic movements produced by a computer on a graphics tablet. We systematically varied the frequency and peak velocity of the movements to determine how these parameters affect the likelihood of synchronized joint action. To assess synchrony in the mirror game we used the previously developed marker of co-confident (CC) motions: smooth, jitter-less and synchronized motions indicative of co-predicative control. We found that when mirroring movements with low frequencies (i.e., long duration movements), the participants never showed CC, and as the frequency of the stimuli increased, the probability of observing CC also increased. This finding is discussed in the framework of motor control studies showing an upper limit on the duration of smooth motion. We confirmed the relationship between motion parameters and the probability to perform CC with three sets of data of open-ended two-player mirror games. These findings demonstrate that when performing movements together, there are optimal movement frequencies to use in order to maximize the possibility of entering a state of synchronized joint action. It also shows that the ability to perform synchronized joint action is constrained by the properties of our motor control systems. PMID:28443047

A perturbative solution to metadynamics ordinary differential equation

NASA Astrophysics Data System (ADS)

Tiwary, Pratyush; Dama, James F.; Parrinello, Michele

2015-12-01

Metadynamics is a popular enhanced sampling scheme wherein by periodic application of a repulsive bias, one can surmount high free energy barriers and explore complex landscapes. Recently, metadynamics was shown to be mathematically well founded, in the sense that the biasing procedure is guaranteed to converge to the true free energy surface in the long time limit irrespective of the precise choice of biasing parameters. A differential equation governing the post-transient convergence behavior of metadynamics was also derived. In this short communication, we revisit this differential equation, expressing it in a convenient and elegant Riccati-like form. A perturbative solution scheme is then developed for solving this differential equation, which is valid for any generic biasing kernel. The solution clearly demonstrates the robustness of metadynamics to choice of biasing parameters and gives further confidence in the widely used method.

A perturbative solution to metadynamics ordinary differential equation.

PubMed

Tiwary, Pratyush; Dama, James F; Parrinello, Michele

2015-12-21

Metadynamics is a popular enhanced sampling scheme wherein by periodic application of a repulsive bias, one can surmount high free energy barriers and explore complex landscapes. Recently, metadynamics was shown to be mathematically well founded, in the sense that the biasing procedure is guaranteed to converge to the true free energy surface in the long time limit irrespective of the precise choice of biasing parameters. A differential equation governing the post-transient convergence behavior of metadynamics was also derived. In this short communication, we revisit this differential equation, expressing it in a convenient and elegant Riccati-like form. A perturbative solution scheme is then developed for solving this differential equation, which is valid for any generic biasing kernel. The solution clearly demonstrates the robustness of metadynamics to choice of biasing parameters and gives further confidence in the widely used method.

Development of confidence limits by pivotal functions for estimating software reliability

NASA Technical Reports Server (NTRS)

Dotson, Kelly J.

1987-01-01

The utility of pivotal functions is established for assessing software reliability. Based on the Moranda geometric de-eutrophication model of reliability growth, confidence limits for attained reliability and prediction limits for the time to the next failure are derived using a pivotal function approach. Asymptotic approximations to the confidence and prediction limits are considered and are shown to be inadequate in cases where only a few bugs are found in the software. Departures from the assumed exponentially distributed interfailure times in the model are also investigated. The effect of these departures is discussed relative to restricting the use of the Moranda model.

A study of the reaction e +e -→ γγ at LEP

NASA Astrophysics Data System (ADS)

Akrawy, M. Z.; Alexander, G.; Allison, J.; Allport, P. P.; Anderson, K. J.; Armitage, J. C.; Arnison, G. T. J.; Ashton, P.; Azuelos, G.; Baines, J. T. M.; Ball, A. H.; Banks, J.; Barker, G. J.; Barlow, R. J.; Batley, J. R.; Becker, J.; Behnke, T.; Bell, K. W.; Bella, G.; Bethke, S.; Biebel, O.; Binder, U.; Bloodworth, I. J.; Bock, P.; Breuker, H.; Brown, R. M.; Brun, R.; Buijs, A.; Burckhart, H. J.; Capiluppi, P.; Carnegie, R. K.; Carter, A. A.; Carter, J. R.; Chang, C. Y.; Charlton, D. G.; Chrin, J. T. M.; Cohen, I.; Collins, W. J.; Conboy, J. E.; Couch, M.; Coupland, M.; Cuffiani, M.; Dado, S.; Dallavalle, G. M.; Deninno, M. M.; Dieckmann, A.; Dittmar, M.; Dixit, M. S.; Duchovni, E.; Duerdoth, I. P.; Dumas, D.; El Mamouni, H.; Elcombe, P. A.; Estabrooks, P. G.; Etzion, E.; Fabbri, F.; Farthouat, P.; Fischer, H. M.; Fong, D. G.; French, M. T.; Fukunaga, C.; Gandois, B.; Ganel, O.; Gary, J. W.; Gascon, J.; Geddes, N. I.; Gee, C. N. P.; Geich-Gimbel, C.; Gensler, S. W.; Gentit, F. X.; Giacomelli, G.; Gibson, V.; Gibson, W. R.; Gillies, J. D.; Goldberg, J.; Goodrick, M. J.; Gorn, W.; Granite, D.; Gross, E.; Grosse-Wiesmann, P.; Grunhaus, J.; Hagedorn, H.; Hagemann, J.; Hansroul, M.; Hargrove, C. K.; Hart, J.; Hattersley, P. M.; Hauschild, M.; Hawkes, C. M.; Heflin, E.; Hemingway, R. J.; Heuer, R. D.; Hill, J. C.; Hillier, S. J.; Ho, C.; Hobbs, J. D.; Hobson, P. R.; Hochman, D.; Holl, B.; Homer, R. J.; Hou, S. R.; Howarth, C. P.; Hughes-Jones, R. E.; Igo-Kemenes, P.; Ihssen, H.; Imrie, D. C.; Jawahery, A.; Jeffreys, P. W.; Jeremie, H.; Jimack, M.; Jobes, M.; Jones, R. W. L.; Jovanovic, P.; Karlen, D.; Kawagoe, K.; Kawamoto, T.; Kellogg, R. G.; Kennedy, B. W.; Kleinwort, C.; Klem, D. E.; Knop, G.; Kobayashi, T.; Kokott, T. P.; Köpke, L.; Kowalewski, R.; Kreutzmann, H.; Kroll, J.; Kuwano, M.; Kyberd, P.; Lafferty, G. D.; Lamarche, F.; Larson, W. J.; Lasota, M. M. B.; Layter, J. G.; Le Du, P.; Leblanc, P.; Lee, A. M.; Lellouch, D.; Lennert, P.; Lessard, L.; Levinson, L.; Lloyd, S. L.; Loebinger, F. K.; Lorah, J. M.; Lorazo, B.; Losty, M. J.; Ludwig, J.; Lupu, N.; Ma, J.; Macbeth, A. A.; Mannelli, M.; Marcellini, S.; Maringer, G.; Martin, A. J.; Martin, J. P.; Mashimo, T.; Mättig, P.; Maur, U.; McMahon, T. J.; McPherson, A. C.; Meijers, F.; Menszner, D.; Merritt, F. S.; Mes, H.; Michelini, A.; Middleton, R. P.; Mikenberg, G.; Miller, D. J.; Milstene, C.; Minowa, M.; Mohr, W.; Montanari, A.; Mori, T.; Moss, M. W.; Muller, A.; Murphy, P. G.; Murray, W. J.; Nellen, B.; Nguyen, H. H.; Nozaki, M.; O'Dowd, A. J. P.; O'Neale, S. W.; O'Neill, B. P.; Oakham, F. G.; Odorici, F.; Ogg, M.; Oh, H.; Oreglia, M. J.; Orito, S.; Patrick, G. N.; Pawley, S. J.; Pfister, P.; Pilcher, J. E.; Pinfold, J. L.; Plane, D. E.; Poli, B.; Pouladdej, A.; Pritchard, T. W.; Quast, G.; Raab, J.; Redmond, M. W.; Rees, D. L.; Regimbald, M.; Riles, K.; Roach, C. M.; Robins, S. A.; Rollnik, A.; Roney, J. M.; Rossberg, S.; Rossi, A. M.; Routenburg, P.; Runge, K.; Runolfsson, O.; Sanghera, S.; Sansum, R. A.; Sasaki, M.; Saunders, B. J.; Schaile, A. D.; Schaile, O.; Schappert, W.; Scharff-Hansen, P.; Schreiber, S.; Schwarz, J.; Shapira, A.; Shen, B. C.; Sherwood, P.; Simon, A.; Siroli, G. P.; Skuja, A.; Smith, A. M.; Smith, T. J.; Snow, G. A.; Spreadbury, E. J.; Springer, R. W.; Sproston, M.; Stephens, K.; Stier, H. E.; Ströhmer, R.; Strom, D.; Takeda, H.; Takeshita, T.; Tsukomoto, T.; Turner, M. F.; Tysarczyk-Niemeyer, G.; Van Den Plas, D.; Vandalen, G. J.; Virtue, C. J.; Von Der Schmitt, H.; Von Krogh, J.; Wagner, A.; Wahl, C.; Ward, C. P.; Ward, D. R.; Waterhouse, J.; Watkins, P. M.; Watson, A. T.; Watson, N. K.; Weber, M.; Weisz, S.; Wermes, N.; Weymann, M.; Wilson, G. W.; Wilson, J. A.; Wingerter, I.; Winterer, V.-H.; Wood, N. C.; Wotton, S.; Wuensch, B.; Wyatt, T. R.; Yaari, R.; Yang, Y.; Yekutieli, G.; Yoshida, T.; Zeuner, W.; Zorn, G. T.; Zylberajch, S.; OPAL Collaboration

1990-05-01

The pure QED reaction e +e -→ γγ has been studied at centre of mass energies around the mass of the Z 0 boson using data recorded by the OPAL detector at LEP. The results are in good agreement with the QED prediction. Lower limits on the cutoff parameters of the modified electron propagator are found to be Λ +>89 GeV and Λ. The lower limit on the mass of an excited electron is 82 GeV assuming the coupling constant λ=1. Upper limits on the branching ratios of Z 0→ γγ, Z 0→ π0γ and Z 0→ ηγ are set at 3.7×10 -4, 3.9×10 -4 and 5.8×10 -4 respectively. Two events from the reaction e +e -→ γγγ have been observed, consistent with the QED prediction. An upper limit on the branching ratio of Z 0→ γγγ is set at 2.8×10 -4. All the limits are given at 95% confidence level.

A Comparison of Various Stress Rupture Life Models for Orbiter Composite Pressure Vessels and Confidence Intervals

NASA Technical Reports Server (NTRS)

Grimes-Ledesma, Lorie; Murthy, Pappu L. N.; Phoenix, S. Leigh; Glaser, Ronald

2007-01-01

In conjunction with a recent NASA Engineering and Safety Center (NESC) investigation of flight worthiness of Kevlar Overwrapped Composite Pressure Vessels (COPVs) on board the Orbiter, two stress rupture life prediction models were proposed independently by Phoenix and by Glaser. In this paper, the use of these models to determine the system reliability of 24 COPVs currently in service on board the Orbiter is discussed. The models are briefly described, compared to each other, and model parameters and parameter uncertainties are also reviewed to understand confidence in reliability estimation as well as the sensitivities of these parameters in influencing overall predicted reliability levels. Differences and similarities in the various models will be compared via stress rupture reliability curves (stress ratio vs. lifetime plots). Also outlined will be the differences in the underlying model premises, and predictive outcomes. Sources of error and sensitivities in the models will be examined and discussed based on sensitivity analysis and confidence interval determination. Confidence interval results and their implications will be discussed for the models by Phoenix and Glaser.

Testing the Performance and Accuracy of the RELXILL Model for the Relativistic X-Ray Reflection from Accretion Disks

NASA Astrophysics Data System (ADS)

Choudhury, Kishalay; García, Javier A.; Steiner, James F.; Bambi, Cosimo

2017-12-01

The reflection spectroscopic model RELXILL is commonly implemented in studying relativistic X-ray reflection from accretion disks around black holes. We present a systematic study of the model’s capability to constrain the dimensionless spin and ionization parameters from ∼6000 Nuclear Spectroscopic Telescope Array (NuSTAR) simulations of a bright X-ray source employing the lamp-post geometry. We employ high-count spectra to show the limitations in the model without being confused with limitations in signal-to-noise. We find that both parameters are well-recovered at 90% confidence with improving constraints at higher reflection fraction, high spin, and low source height. We test spectra across a broad range—first at 106–107 and then ∼105 total source counts across the effective 3–79 keV band of NuSTAR, and discover a strong dependence of the results on how fits are performed around the starting parameters, owing to the complexity of the model itself. A blind fit chosen over an approach that carries some estimates of the actual parameter values can lead to significantly worse recovery of model parameters. We further stress the importance to span the space of nonlinear-behaving parameters like {log} ξ carefully and thoroughly for the model to avoid misleading results. In light of selecting fitting procedures, we recall the necessity to pay attention to the choice of data binning and fit statistics used to test the goodness of fit by demonstrating the effect on the photon index Γ. We re-emphasize and implore the need to account for the detector resolution while binning X-ray data and using Poisson fit statistics instead while analyzing Poissonian data.

Inappropriate use of the quasi-reversible electrode kinetic model in simulation-experiment comparisons of voltammetric processes that approach the reversible limit.

PubMed

Simonov, Alexandr N; Morris, Graham P; Mashkina, Elena A; Bethwaite, Blair; Gillow, Kathryn; Baker, Ruth E; Gavaghan, David J; Bond, Alan M

2014-08-19

Many electrode processes that approach the "reversible" (infinitely fast) limit under voltammetric conditions have been inappropriately analyzed by comparison of experimental data and theory derived from the "quasi-reversible" model. Simulations based on "reversible" and "quasi-reversible" models have been fitted to an extensive series of a.c. voltammetric experiments undertaken at macrodisk glassy carbon (GC) electrodes for oxidation of ferrocene (Fc(0/+)) in CH3CN (0.10 M (n-Bu)4NPF6) and reduction of [Ru(NH3)6](3+) and [Fe(CN)6](3-) in 1 M KCl aqueous electrolyte. The confidence with which parameters such as standard formal potential (E(0)), heterogeneous electron transfer rate constant at E(0) (k(0)), charge transfer coefficient (α), uncompensated resistance (Ru), and double layer capacitance (CDL) can be reported using the "quasi-reversible" model has been assessed using bootstrapping and parameter sweep (contour plot) techniques. Underparameterization, such as that which occurs when modeling CDL with a potential independent value, results in a less than optimal level of experiment-theory agreement. Overparameterization may improve the agreement but easily results in generation of physically meaningful but incorrect values of the recovered parameters, as is the case with the very fast Fc(0/+) and [Ru(NH3)6](3+/2+) processes. In summary, for fast electrode kinetics approaching the "reversible" limit, it is recommended that the "reversible" model be used for theory-experiment comparisons with only E(0), Ru, and CDL being quantified and a lower limit of k(0) being reported; e.g., k(0) ≥ 9 cm s(-1) for the Fc(0/+) process.

Cosmological Parameters from the QUAD CMB Polarization Experiment

NASA Astrophysics Data System (ADS)

Castro, P. G.; Ade, P.; Bock, J.; Bowden, M.; Brown, M. L.; Cahill, G.; Church, S.; Culverhouse, T.; Friedman, R. B.; Ganga, K.; Gear, W. K.; Gupta, S.; Hinderks, J.; Kovac, J.; Lange, A. E.; Leitch, E.; Melhuish, S. J.; Memari, Y.; Murphy, J. A.; Orlando, A.; Pryke, C.; Schwarz, R.; O'Sullivan, C.; Piccirillo, L.; Rajguru, N.; Rusholme, B.; Taylor, A. N.; Thompson, K. L.; Turner, A. H.; Wu, E. Y. S.; Zemcov, M.; QUa D Collaboration

2009-08-01

In this paper, we present a parameter estimation analysis of the polarization and temperature power spectra from the second and third season of observations with the QUaD experiment. QUaD has for the first time detected multiple acoustic peaks in the E-mode polarization spectrum with high significance. Although QUaD-only parameter constraints are not competitive with previous results for the standard six-parameter ΛCDM cosmology, they do allow meaningful polarization-only parameter analyses for the first time. In a standard six-parameter ΛCDM analysis, we find the QUaD TT power spectrum to be in good agreement with previous results. However, the QUaD polarization data show some tension with ΛCDM. The origin of this 1σ-2σ tension remains unclear, and may point to new physics, residual systematics, or simple random chance. We also combine QUaD with the five-year WMAP data set and the SDSS luminous red galaxies 4th data release power spectrum, and extend our analysis to constrain individual isocurvature mode fractions, constraining cold dark matter density, αcdmi < 0.11 (95% confidence limit (CL)), neutrino density, αndi < 0.26 (95% CL), and neutrino velocity, αnvi < 0.23 (95% CL), modes. Our analysis sets a benchmark for future polarization experiments.

On the modeling of breath-by-breath oxygen uptake kinetics at the onset of high-intensity exercises: simulated annealing vs. GRG2 method.

PubMed

Bernard, Olivier; Alata, Olivier; Francaux, Marc

2006-03-01

Modeling in the time domain, the non-steady-state O2 uptake on-kinetics of high-intensity exercises with empirical models is commonly performed with gradient-descent-based methods. However, these procedures may impair the confidence of the parameter estimation when the modeling functions are not continuously differentiable and when the estimation corresponds to an ill-posed problem. To cope with these problems, an implementation of simulated annealing (SA) methods was compared with the GRG2 algorithm (a gradient-descent method known for its robustness). Forty simulated Vo2 on-responses were generated to mimic the real time course for transitions from light- to high-intensity exercises, with a signal-to-noise ratio equal to 20 dB. They were modeled twice with a discontinuous double-exponential function using both estimation methods. GRG2 significantly biased two estimated kinetic parameters of the first exponential (the time delay td1 and the time constant tau1) and impaired the precision (i.e., standard deviation) of the baseline A0, td1, and tau1 compared with SA. SA significantly improved the precision of the three parameters of the second exponential (the asymptotic increment A2, the time delay td2, and the time constant tau2). Nevertheless, td2 was significantly biased by both procedures, and the large confidence intervals of the whole second component parameters limit their interpretation. To compare both algorithms on experimental data, 26 subjects each performed two transitions from 80 W to 80% maximal O2 uptake on a cycle ergometer and O2 uptake was measured breath by breath. More than 88% of the kinetic parameter estimations done with the SA algorithm produced the lowest residual sum of squares between the experimental data points and the model. Repeatability coefficients were better with GRG2 for A1 although better with SA for A2 and tau2. Our results demonstrate that the implementation of SA improves significantly the estimation of most of these kinetic parameters, but a large inaccuracy remains in estimating the parameter values of the second exponential.

Planck intermediate results. XVI. Profile likelihoods for cosmological parameters

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Battaner, E.; Benabed, K.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bonaldi, A.; Bond, J. R.; Bouchet, F. R.; Burigana, C.; Cardoso, J.-F.; Catalano, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Couchot, F.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Dupac, X.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lawrence, C. R.; Leonardi, R.; Liddle, A.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Maino, D.; Mandolesi, N.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Mazzotta, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski∗, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rouillé d'Orfeuil, B.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Savelainen, M.; Savini, G.; Spencer, L. D.; Spinelli, M.; Starck, J.-L.; Sureau, F.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; White, M.; Yvon, D.; Zacchei, A.; Zonca, A.

2014-06-01

We explore the 2013 Planck likelihood function with a high-precision multi-dimensional minimizer (Minuit). This allows a refinement of the ΛCDM best-fit solution with respect to previously-released results, and the construction of frequentist confidence intervals using profile likelihoods. The agreement with the cosmological results from the Bayesian framework is excellent, demonstrating the robustness of the Planck results to the statistical methodology. We investigate the inclusion of neutrino masses, where more significant differences may appear due to the non-Gaussian nature of the posterior mass distribution. By applying the Feldman-Cousins prescription, we again obtain results very similar to those of the Bayesian methodology. However, the profile-likelihood analysis of the cosmic microwave background (CMB) combination (Planck+WP+highL) reveals a minimum well within the unphysical negative-mass region. We show that inclusion of the Planck CMB-lensing information regularizes this issue, and provide a robust frequentist upper limit ∑ mν ≤ 0.26 eV (95% confidence) from the CMB+lensing+BAO data combination.

Confidence limit variation for a single IMRT system following the TG119 protocol.

PubMed

Gordon, J D; Krafft, S P; Jang, S; Smith-Raymond, L; Stevie, M Y; Hamilton, R J

2011-03-01

To evaluate the robustness of TG119-based quality assurance metrics for an IMRT system. Four planners constructed treatment plans for the five IMRT test cases described in TG119. All plans were delivered to a 30 cm x 30 cm x 15 cm solid water phantom in one treatment session in order to minimize session-dependent variation from phantom setup, film quality, machine performance, etc. Composite measurements utilized film and an ionization chamber. Per-field measurements were collected using a diode array device at an effective depth of 5 cm. All data collected were analyzed using the TG119 specifications to determine the confidence limit values for each planner separately and then compared. The mean variance of ion chamber measurements for each planner was within 1.7% of the planned dose. The resulting confidence limits were 3.13%, 1.98%, 3.65%, and 4.39%. Confidence limit values determined by composite film analysis were 8.06%, 13.4%, 9.30%, and 16.5%. Confidence limits from per-field measurements were 1.55%, 0.00%, 0.00%, and 2.89%. For a single IMRT system, the accuracy assessment provided by TG119-based quality assurance metrics showed significant variations in the confidence limits between planners across all composite and per-field evaluations. This observed variation is likely due to the different levels of modulation between each planner's set of plans. Performing the TG119 evaluation using plans produced by a single planner may not provide an adequate estimation of IMRT system accuracy.

Confidence in Altman-Bland plots: a critical review of the method of differences.

PubMed

Ludbrook, John

2010-02-01

1. Altman and Bland argue that the virtue of plotting differences against averages in method-comparison studies is that 95% confidence limits for the differences can be constructed. These allow authors and readers to judge whether one method of measurement could be substituted for another. 2. The technique is often misused. So I have set out, by statistical argument and worked examples, to advise pharmacologists and physiologists how best to construct these limits. 3. First, construct a scattergram of differences on averages, then calculate the line of best fit for the linear regression of differences on averages. If the slope of the regression is shown to differ from zero, there is proportional bias. 4. If there is no proportional bias and if the scatter of differences is uniform (homoscedasticity), construct 'classical' 95% confidence limits. 5. If there is proportional bias yet homoscedasticity, construct hyperbolic 95% confidence limits (prediction interval) around the line of best fit. 6. If there is proportional bias and the scatter of values for differences increases progressively as the average values increase (heteroscedasticity), log-transform the raw values from the two methods and replot differences against averages. If this eliminates proportional bias and heteroscedasticity, construct 'classical' 95% confidence limits. Otherwise, construct horizontal V-shaped 95% confidence limits around the line of best fit of differences on averages or around the weighted least products line of best fit to the original data. 7. In designing a method-comparison study, consult a qualified biostatistician, obey the rules of randomization and make replicate observations.

Search for Diphoton Resonances in the Mass Range from 150 to 850 GeV in pp Collisions at $$\\sqrt{s}$$ = 8 TeV

DOE PAGES

Khachatryan, V.

2015-09-30

Results are presented of a search for heavy particles decaying into two photons. The analysis is based on a 19.7fb -1 sample of proton–proton collisions atmore » $$\\sqrt{s}$$ = 8 TeV collected with the CMS detector at the CERN LHC. The diphoton mass spectrum from 150 to 850 GeV is used to search for an excess of events over the background. The search is extended to new resonances with natural widths of up to 10% of the mass value. No evidence for new particle production is observed and limits at 95% confidence level on the production cross section times branching fraction to diphotons are determined. These limits are interpreted in terms of two-Higgs-doublet model parameters.« less

Search for Supersymmetry Using Final States with One Lepton, Jets, and Missing Transverse Momentum with the ATLAS Detector in √s=7 TeV pp Collisions

DOE PAGES

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

2011-03-28

This Letter presents the first search for supersymmetry in final states containing one isolated electron or muon, jets, and missing transverse momentum from √s=7 TeV proton-proton collisions at the LHC. The data were recorded by the ATLAS experiment during 2010 and correspond to a total integrated luminosity of 35 pb⁻¹. No excess above the standard model background expectation is observed. Limits are set on the parameters of the minimal supergravity framework, extending previous limits. Within this framework, for A 0=0 GeV, tanβ=3, and μ>0 and for equal squark and gluino masses, gluino masses below 700 GeV are excluded at 95%more » confidence level.« less

Diagnostic capability of spectral-domain optical coherence tomography for glaucoma.

PubMed

Wu, Huijuan; de Boer, Johannes F; Chen, Teresa C

2012-05-01

To determine the diagnostic capability of spectral-domain optical coherence tomography in glaucoma patients with visual field defects. Prospective, cross-sectional study. Participants were recruited from a university hospital clinic. One eye of 85 normal subjects and 61 glaucoma patients with average visual field mean deviation of -9.61 ± 8.76 dB was selected randomly for the study. A subgroup of the glaucoma patients with early visual field defects was calculated separately. Spectralis optical coherence tomography (Heidelberg Engineering, Inc) circular scans were performed to obtain peripapillary retinal nerve fiber layer (RNFL) thicknesses. The RNFL diagnostic parameters based on the normative database were used alone or in combination for identifying glaucomatous RNFL thinning. To evaluate diagnostic performance, calculations included areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio. Overall RNFL thickness had the highest area under the receiver operating characteristic curve values: 0.952 for all patients and 0.895 for the early glaucoma subgroup. For all patients, the highest sensitivity (98.4%; 95% confidence interval, 96.3% to 100%) was achieved by using 2 criteria: ≥ 1 RNFL sectors being abnormal at the < 5% level and overall classification of borderline or outside normal limits, with specificities of 88.9% (95% confidence interval, 84.0% to 94.0%) and 87.1% (95% confidence interval, 81.6% to 92.5%), respectively, for these 2 criteria. Statistical parameters for evaluating the diagnostic performance of the Spectralis spectral-domain optical coherence tomography were good for early perimetric glaucoma and were excellent for moderately advanced perimetric glaucoma. Copyright © 2012 Elsevier Inc. All rights reserved.

Limits, discovery and cut optimization for a Poisson process with uncertainty in background and signal efficiency: TRolke 2.0

NASA Astrophysics Data System (ADS)

Lundberg, J.; Conrad, J.; Rolke, W.; Lopez, A.

2010-03-01

A C++ class was written for the calculation of frequentist confidence intervals using the profile likelihood method. Seven combinations of Binomial, Gaussian, Poissonian and Binomial uncertainties are implemented. The package provides routines for the calculation of upper and lower limits, sensitivity and related properties. It also supports hypothesis tests which take uncertainties into account. It can be used in compiled C++ code, in Python or interactively via the ROOT analysis framework. Program summaryProgram title: TRolke version 2.0 Catalogue identifier: AEFT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: MIT license No. of lines in distributed program, including test data, etc.: 3431 No. of bytes in distributed program, including test data, etc.: 21 789 Distribution format: tar.gz Programming language: ISO C++. Computer: Unix, GNU/Linux, Mac. Operating system: Linux 2.6 (Scientific Linux 4 and 5, Ubuntu 8.10), Darwin 9.0 (Mac-OS X 10.5.8). RAM:˜20 MB Classification: 14.13. External routines: ROOT ( http://root.cern.ch/drupal/) Nature of problem: The problem is to calculate a frequentist confidence interval on the parameter of a Poisson process with statistical or systematic uncertainties in signal efficiency or background. Solution method: Profile likelihood method, Analytical Running time:<10 seconds per extracted limit.

A confidence metric for using neurobiological feedback in actor-critic reinforcement learning based brain-machine interfaces

PubMed Central

Prins, Noeline W.; Sanchez, Justin C.; Prasad, Abhishek

2014-01-01

Brain-Machine Interfaces (BMIs) can be used to restore function in people living with paralysis. Current BMIs require extensive calibration that increase the set-up times and external inputs for decoder training that may be difficult to produce in paralyzed individuals. Both these factors have presented challenges in transitioning the technology from research environments to activities of daily living (ADL). For BMIs to be seamlessly used in ADL, these issues should be handled with minimal external input thus reducing the need for a technician/caregiver to calibrate the system. Reinforcement Learning (RL) based BMIs are a good tool to be used when there is no external training signal and can provide an adaptive modality to train BMI decoders. However, RL based BMIs are sensitive to the feedback provided to adapt the BMI. In actor-critic BMIs, this feedback is provided by the critic and the overall system performance is limited by the critic accuracy. In this work, we developed an adaptive BMI that could handle inaccuracies in the critic feedback in an effort to produce more accurate RL based BMIs. We developed a confidence measure, which indicated how appropriate the feedback is for updating the decoding parameters of the actor. The results show that with the new update formulation, the critic accuracy is no longer a limiting factor for the overall performance. We tested and validated the system onthree different data sets: synthetic data generated by an Izhikevich neural spiking model, synthetic data with a Gaussian noise distribution, and data collected from a non-human primate engaged in a reaching task. All results indicated that the system with the critic confidence built in always outperformed the system without the critic confidence. Results of this study suggest the potential application of the technique in developing an autonomous BMI that does not need an external signal for training or extensive calibration. PMID:24904257

Can 3-dimensional power Doppler indices improve the prenatal diagnosis of a potentially morbidly adherent placenta in patients with placenta previa?

PubMed

Haidar, Ziad A; Papanna, Ramesha; Sibai, Baha M; Tatevian, Nina; Viteri, Oscar A; Vowels, Patricia C; Blackwell, Sean C; Moise, Kenneth J

2017-08-01

Traditionally, 2-dimensional ultrasound parameters have been used for the diagnosis of a suspected morbidly adherent placenta previa. More objective techniques have not been well studied yet. The objective of the study was to determine the ability of prenatal 3-dimensional power Doppler analysis of flow and vascular indices to predict the morbidly adherent placenta objectively. A prospective cohort study was performed in women between 28 and 32 gestational weeks with known placenta previa. Patients underwent a two-dimensional gray-scale ultrasound that determined management decisions. 3-Dimensional power Doppler volumes were obtained during the same examination and vascular, flow, and vascular flow indices were calculated after manual tracing of the viewed placenta in the sweep; data were blinded to obstetricians. Morbidly adherent placenta was confirmed by histology. Severe morbidly adherent placenta was defined as increta/percreta on histology, blood loss >2000 mL, and >2 units of PRBC transfused. Sensitivities, specificities, predictive values, and likelihood ratios were calculated. Student t and χ 2 tests, logistic regression, receiver-operating characteristic curves, and intra- and interrater agreements using Kappa statistics were performed. The following results were found: (1) 50 women were studied: 23 had morbidly adherent placenta, of which 12 (52.2%) were severe morbidly adherent placenta; (2) 2-dimensional parameters diagnosed morbidly adherent placenta with a sensitivity of 82.6% (95% confidence interval, 60.4-94.2), a specificity of 88.9% (95% confidence interval, 69.7-97.1), a positive predictive value of 86.3% (95% confidence interval, 64.0-96.4), a negative predictive value of 85.7% (95% confidence interval, 66.4-95.3), a positive likelihood ratio of 7.4 (95% confidence interval, 2.5-21.9), and a negative likelihood ratio of 0.2 (95% confidence interval, 0.08-0.48); (3) mean values of the vascular index (32.8 ± 7.4) and the vascular flow index (14.2 ± 3.8) were higher in morbidly adherent placenta (P < .001); (4) area under the receiver-operating characteristic curve for the vascular and vascular flow indices were 0.99 and 0.97, respectively; (5) the vascular index ≥21 predicted morbidly adherent placenta with a sensitivity and a specificity of 95% (95% confidence interval, 88.2-96.9) and 91%, respectively (95% confidence interval, 87.5-92.4), 92% positive predictive value (95% confidence interval, 85.5-94.3), 90% negative predictive value (95% confidence interval, 79.9-95.3), positive likelihood ratio of 10.55 (95% confidence interval, 7.06-12.75), and negative likelihood ratio of 0.05 (95% confidence interval, 0.03-0.13); and (6) for the severe morbidly adherent placenta, 2-dimensional ultrasound had a sensitivity of 33.3% (95% confidence interval, 11.3-64.6), a specificity of 81.8% (95% confidence interval, 47.8-96.8), a positive predictive value of 66.7% (95% confidence interval, 24.1-94.1), a negative predictive value of 52.9% (95% confidence interval, 28.5-76.1), a positive likelihood ratio of 1.83 (95% confidence interval, 0.41-8.11), and a negative likelihood ratio of 0.81 (95% confidence interval, 0.52-1.26). A vascular index ≥31 predicted the diagnosis of a severe morbidly adherent placenta with a 100% sensitivity (95% confidence interval, 72-100), a 90% specificity (95% confidence interval, 81.7-93.8), an 88% positive predictive value (95% confidence interval, 55.0-91.3), a 100% negative predictive value (95% confidence interval, 90.9-100), a positive likelihood ratio of 10.0 (95% confidence interval, 3.93-16.13), and a negative likelihood ratio of 0 (95% confidence interval, 0-0.34). Intrarater and interrater agreements were 94% (P < .001) and 93% (P < .001), respectively. The vascular index accurately predicts the morbidly adherent placenta in patients with placenta previa. In addition, 3-dimensional power Doppler vascular and vascular flow indices were more predictive of severe cases of morbidly adherent placenta compared with 2-dimensional ultrasound. This objective technique may limit the variations in diagnosing morbidly adherent placenta because of the subjectivity of 2-dimensional ultrasound interpretations. Copyright © 2017 Elsevier Inc. All rights reserved.

Mathematical estimation of the level of microbial contamination on spacecraft surfaces by volumetric air sampling

NASA Technical Reports Server (NTRS)

Oxborrow, G. S.; Roark, A. L.; Fields, N. D.; Puleo, J. R.

1974-01-01

Microbiological sampling methods presently used for enumeration of microorganisms on spacecraft surfaces require contact with easily damaged components. Estimation of viable particles on surfaces using air sampling methods in conjunction with a mathematical model would be desirable. Parameters necessary for the mathematical model are the effect of angled surfaces on viable particle collection and the number of viable cells per viable particle. Deposition of viable particles on angled surfaces closely followed a cosine function, and the number of viable cells per viable particle was consistent with a Poisson distribution. Other parameters considered by the mathematical model included deposition rate and fractional removal per unit time. A close nonlinear correlation between volumetric air sampling and airborne fallout on surfaces was established with all fallout data points falling within the 95% confidence limits as determined by the mathematical model.

Fetal growth and perinatal outcome of pregnancies continuing after threatened abortion.

PubMed

Das, A G; Gopalan, S; Dhaliwal, L K

1996-05-01

The present study was conducted with the aim to find out the effect of threatened abortion in the current pregnancy on the subsequent perinatal outcome and follow the growth pattern of the fetuses of such complicated pregnancies. The study group consisted of 55 women with threatened abortion and 55 women with normal pregnancies formed the control group. Most of the patients presented at 6-12 weeks' gestation. The fetal growth was monitored by both clinical as well as ultrasound (USG) parameters. The mean growth rates were almost identical throughout gestation. The mean values of each parameter of the study group were found lying with 95% confidence limit values of their control group. The apparent increased incidence of low lying placenta in early pregnancy probably contributed to threatened abortion. There was no significant difference in preterm delivery, low birth-weight and overall perinatal outcome.

Detecting Dark Photons with Reactor Neutrino Experiments

NASA Astrophysics Data System (ADS)

Park, H. K.

2017-08-01

We propose to search for light U (1 ) dark photons, A', produced via kinetically mixing with ordinary photons via the Compton-like process, γ e-→A'e-, in a nuclear reactor and detected by their interactions with the material in the active volumes of reactor neutrino experiments. We derive 95% confidence-level upper limits on ɛ , the A'-γ mixing parameter, ɛ , for dark-photon masses below 1 MeV of ɛ <1.3 ×10-5 and ɛ <2.1 ×10-5, from NEOS and TEXONO experimental data, respectively. This study demonstrates the applicability of nuclear reactors as potential sources of intense fluxes of low-mass dark photons.

Narrow-band search of continuous gravitational-wave signals from Crab and Vela pulsars in Virgo VSR4 data

NASA Astrophysics Data System (ADS)

Aasi, J.; Abbott, B. P.; Abbott, R.; Abbott, T.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Ain, A.; Ajith, P.; Alemic, A.; Allen, B.; Allocca, A.; Amariutei, D.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C.; Areeda, J. S.; Ashton, G.; Ast, S.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Aylott, B. E.; Babak, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barbet, M.; Barclay, S.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Bartlett, J.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Bauer, Th. S.; Baune, C.; Bavigadda, V.; Behnke, B.; Bejger, M.; Belczynski, C.; Bell, A. S.; Bell, C.; Benacquista, M.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biscans, S.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackburn, L.; Blair, C. D.; Blair, D.; Bloemen, S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bojtos, P.; Bond, C.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, Sukanta; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Buchman, S.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Cadonati, L.; Cagnoli, G.; Calderón Bustillo, J.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Carbognani, F.; Caride, S.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C.; Colombini, M.; Cominsky, L.; Constancio, M.; Conte, A.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M. W.; Coulon, J.-P.; Countryman, S.; Couvares, P.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Cutler, C.; Dahl, K.; Canton, T. Dal; Damjanic, M.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dartez, L.; Dattilo, V.; Dave, I.; Daveloza, H.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Dhurandhar, S.; Díaz, M.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Dominguez, E.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S.; Eberle, T.; Edo, T.; Edwards, M.; Edwards, M.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Essick, R.; Etzel, T.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Feldbaum, D.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fuentes-Tapia, S.; Fulda, P.; Fyffe, M.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S.; Garufi, F.; Gatto, A.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; Gergely, L. Á.; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gleason, J.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gordon, N.; Gorodetsky, M. L.; Gossan, S.; Goßler, S.; Gouaty, R.; Gräf, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guido, C. J.; Guo, X.; Gushwa, K.; Gustafson, E. K.; Gustafson, R.; Hacker, J.; Hall, E. D.; Hammond, G.; Hanke, M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Hee, S.; Heidmann, A.; Heintze, M.; Heinzel, G.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Heptonstall, A. W.; Heurs, M.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E.; Howell, E. J.; Hu, Y. M.; Huerta, E.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh, M.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Islas, G.; Isler, J. C.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacobson, M.; Jang, H.; Jaranowski, P.; Jawahar, S.; Ji, Y.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Keiser, G. M.; Keitel, D.; Kelley, D. B.; Kells, W.; Keppel, D. G.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, C.; Kim, K.; Kim, N. G.; Kim, N.; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kline, J.; Koehlenbeck, S.; Kokeyama, K.; Kondrashov, V.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, A.; Kumar, P.; Kuo, L.; Kutynia, A.; Landry, M.; Lantz, B.; Larson, S.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Lazzaro, C.; Le, J.; Leaci, P.; Leavey, S.; Lebigot, E.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B.; Lewis, J.; Li, T. G. F.; Libbrecht, K.; Libson, A.; Lin, A. C.; Littenberg, T. B.; Lockerbie, N. A.; Lockett, V.; Logue, J.; Lombardi, A. L.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Lubinski, M. J.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macarthur, J.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Magee, R.; Mageswaran, M.; Maglione, C.; Mailand, K.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mangano, V.; Mansell, G. L.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McLin, K.; McWilliams, S.; Meacher, D.; Meadors, G. D.; Meidam, J.; Meinders, M.; Melatos, A.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moe, B.; Moggi, A.; Mohan, M.; Mohanty, S. D.; Mohapatra, S. R. P.; Moore, B.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nagy, M. F.; Nardecchia, I.; Nash, T.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Neri, I.; Neri, M.; Newton, G.; Nguyen, T.; Nielsen, A. B.; Nissanke, S.; Nitz, A. H.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oppermann, P.; Oram, R.; O'Reilly, B.; Ortega, W.; O'Shaughnessy, R.; Osthelder, C.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Padilla, C.; Pai, A.; Pai, S.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Papa, M. A.; Paris, H.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patrick, Z.; Pedraza, M.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poeld, J.; Poggiani, R.; Post, A.; Poteomkin, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qin, J.; Quetschke, V.; Quintero, E.; Quiroga, G.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Raja, S.; Rajalakshmi, G.; Rakhmanov, M.; Ramirez, K.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Reula, O.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Saleem, M.; Salemi, F.; Sammut, L.; Sandberg, V.; Sanders, J. R.; Sannibale, V.; Santiago-Prieto, I.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Savage, R.; Sawadsky, A.; Scheuer, J.; Schilling, R.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Serafinelli, R.; Sergeev, A.; Serna, G.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sidery, T. L.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, A. D.; Simakov, D.; Singer, A.; Singer, L.; Singh, R.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, J. R.; Smith, M. R.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Son, E. J.; Sorazu, B.; Souradeep, T.; Staley, A.; Stebbins, J.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Steplewski, S.; Stevenson, S.; Stone, R.; Strain, K. A.; Straniero, N.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sutton, P. J.; Swinkels, B.; Szczepanczyk, M.; Szeifert, G.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Tellez, G.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Travasso, F.; Traylor, G.; Tse, M.; Tshilumba, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Vajente, G.; Valdes, G.; Vallisneri, M.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; van den Broeck, C.; van der Sluys, M. V.; van Heijningen, J.; van Veggel, A. A.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vincent-Finley, R.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, H.; Wang, M.; Wang, X.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wessels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Wilkinson, C.; Williams, L.; Williams, R.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Xie, S.; Yablon, J.; Yakushin, I.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yang, Q.; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, Fan; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhu, X. J.; Zucker, M. E.; Zuraw, S.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2015-01-01

In this paper we present the results of a coherent narrow-band search for continuous gravitational-wave signals from the Crab and Vela pulsars conducted on Virgo VSR4 data. In order to take into account a possible small mismatch between the gravitational-wave frequency and two times the star rotation frequency, inferred from measurement of the electromagnetic pulse rate, a range of 0.02 Hz around two times the star rotational frequency has been searched for both the pulsars. No evidence for a signal has been found and 95% confidence level upper limits have been computed assuming both that polarization parameters are completely unknown and that they are known with some uncertainty, as derived from x-ray observations of the pulsar wind torii. For Vela the upper limits are comparable to the spin-down limit, computed assuming that all the observed spin-down is due to the emission of gravitational waves. For Crab the upper limits are about a factor of 2 below the spin-down limit, and represent a significant improvement with respect to past analysis. This is the first time the spin-down limit is significantly overcome in a narrow-band search.

Narrow-Band Search of Continuous Gravitational-Wave Signals from Crab and Vela Pulsars in Virgo VSR4 Data

NASA Technical Reports Server (NTRS)

Aasi, J.; Abbott, B. P.; Abbott, R.; Abbott, T.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Adams, T.;

The estimation of parameter compaction values for pavement subgrade stabilized with lime

NASA Astrophysics Data System (ADS)

Lubis, A. S.; Muis, Z. A.; Simbolon, C. A.

2018-02-01

The type of soil material, field control, maintenance and availability of funds are several factors that must be considered in compaction of the pavement subgrade. In determining the compaction parameters in laboratory desperately requires considerable materials, time and funds, and reliable laboratory operators. If the result of soil classification values can be used to estimate the compaction parameters of a subgrade material, so it would save time, energy, materials and cost on the execution of this work. This is also a clarification (cross check) of the work that has been done by technicians in the laboratory. The study aims to estimate the compaction parameter values ie. maximum dry unit weight (γdmax) and optimum water content (Wopt) of the soil subgrade that stabilized with lime. The tests that conducted in the laboratory of soil mechanics were to determine the index properties (Fines and Liquid Limit/LL) and Standard Compaction Test. Soil samples that have Plasticity Index (PI) > 10% were made with additional 3% lime for 30 samples. By using the Goswami equation, the compaction parameter values can be estimated by equation γd max # = -0,1686 Log G + 1,8434 and Wopt # = 2,9178 log G + 17,086. From the validation calculation, there was a significant positive correlation between the compaction parameter values laboratory and the compaction parameter values estimated, with a 95% confidence interval as a strong relationship.

Determination of confidence limits for experiments with low numbers of counts. [Poisson-distributed photon counts from astrophysical sources

NASA Technical Reports Server (NTRS)

Kraft, Ralph P.; Burrows, David N.; Nousek, John A.

1991-01-01

Two different methods, classical and Bayesian, for determining confidence intervals involving Poisson-distributed data are compared. Particular consideration is given to cases where the number of counts observed is small and is comparable to the mean number of background counts. Reasons for preferring the Bayesian over the classical method are given. Tables of confidence limits calculated by the Bayesian method are provided for quick reference.

Constraints on the unified dark energy dark matter model from latest observational data

NASA Astrophysics Data System (ADS)

Wu, Puxun; Yu, Hongwei

2007-03-01

The generalized Chaplygin gas (GCG) is studied in this paper by using the latest observational data including 182 gold sample type Ia supernovae (Sne Ia) data, the ESSENCE Sne Ia data, the distance ratio from z = 0.35 to 1089 (the redshift of decoupling), the cosmic microwave background shift parameter and the Hubble parameter data. Our results rule out the standard Chaplygin gas model (α = 1) at the 99.7% confidence level, but allow for the λCDM model (α = 0) at the 68.3% confidence level. At a 95.4% confidence level, we obtain w = -0.74-0.09+0.10 and α = -0.14-0.19+0.30. In addition, we find that the phase transition from deceleration to acceleration occurs at redshift zq = 0~0.78-0.89 at a 1σ confidence level for the GCG model.

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics.

PubMed

Prins, Noeline W; Sanchez, Justin C; Prasad, Abhishek

2017-06-01

For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance. Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor's weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the 'ambiguous' region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture. In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold. The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics

NASA Astrophysics Data System (ADS)

Prins, Noeline W.; Sanchez, Justin C.; Prasad, Abhishek

2017-06-01

Objective. For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance. Approach. Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor’s weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the ‘ambiguous’ region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture. Main results. In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold. Significance: The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Search for contact interactions in μ⁺μ⁺ events in pp collisions at √s=7 TeV

DOE PAGES

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; ...

2013-02-01

Results are reported from a search for the effects of contact interactions using events with a high-mass, oppositely charged muon pair. The events are collected in proton-proton collisions at s√=7 TeV using the Compact Muon Solenoid detector at the Large Hadron Collider. The data sample corresponds to an integrated luminosity of 5.3 fb⁻¹. The observed dimuon mass spectrum is consistent with that expected from the standard model. The data are interpreted in the context of a quark- and muon-compositeness model with a left-handed isoscalar current and an energy scale parameter Λ. The 95% confidence level lower limit on Λ ismore » 9.5 TeV under the assumption of destructive interference between the standard model and contact-interaction amplitudes. For constructive interference, the limit is 13.1 TeV. These limits are comparable to the most stringent ones reported to date.« less

Search for supersymmetry in events with large missing transverse momentum, jets, and at least one tau lepton in 7 TeV proton-proton collision data with the ATLAS detector

DOE PAGES

Aad, G.; Abajyan, T.; Abbott, B.; ...

2012-11-20

A search for supersymmetry (SUSY) in events with large missing transverse momentum, jets, and at least one hadronically decaying τ lepton, with zero or one additional light lepton (e/μ), has been performed using 4.7 fb -1 of proton-proton collision data at √s = 7 TeV recorded with the ATLAS detector at the Large Hadron Collider. No excess above the Standard Model background expectation is observed and a 95 % confidence level visible cross-section upper limit for new phenomena is set. In the framework of gauge-mediated SUSY-breaking models, lower limits on the mass scale Λ are set at 54 TeV inmore » the regions where the τ 1 is the next-to-lightest SUSY particle (tanβ > 20). These limits provide the most stringent tests to date of GMSB models in a large part of the parameter space considered.« less

No tension between assembly models of super massive black hole binaries and pulsar observations.

PubMed

Middleton, Hannah; Chen, Siyuan; Del Pozzo, Walter; Sesana, Alberto; Vecchio, Alberto

2018-02-08

Pulsar timing arrays are presently the only means to search for the gravitational wave stochastic background from super massive black hole binary populations, considered to be within the grasp of current or near-future observations. The stringent upper limit from the Parkes Pulsar Timing Array has been interpreted as excluding (>90% confidence) the current paradigm of binary assembly through galaxy mergers and hardening via stellar interaction, suggesting evolution is accelerated or stalled. Using Bayesian hierarchical modelling we consider implications of this upper limit for a range of astrophysical scenarios, without invoking stalling, nor more exotic physical processes. All scenarios are fully consistent with the upper limit, but (weak) bounds on population parameters can be inferred. Recent upward revisions of the black hole-galaxy bulge mass relation are disfavoured at 1.6σ against lighter models. Once sensitivity improves by an order of magnitude, a non-detection will disfavour the most optimistic scenarios at 3.9σ.

Verification of spectrophotometric method for nitrate analysis in water samples

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Search for contact interactions in μ⁺μ⁺ events in pp collisions at √s=7 TeV

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

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

Results are reported from a search for the effects of contact interactions using events with a high-mass, oppositely charged muon pair. The events are collected in proton-proton collisions at s√=7 TeV using the Compact Muon Solenoid detector at the Large Hadron Collider. The data sample corresponds to an integrated luminosity of 5.3 fb⁻¹. The observed dimuon mass spectrum is consistent with that expected from the standard model. The data are interpreted in the context of a quark- and muon-compositeness model with a left-handed isoscalar current and an energy scale parameter Λ. The 95% confidence level lower limit on Λ ismore » 9.5 TeV under the assumption of destructive interference between the standard model and contact-interaction amplitudes. For constructive interference, the limit is 13.1 TeV. These limits are comparable to the most stringent ones reported to date.« less

Current and Future Constraints on Primordial Magnetic Fields

NASA Astrophysics Data System (ADS)

Sutton, Dylan R.; Feng, Chang; Reichardt, Christian L.

2017-09-01

We present new limits on the amplitude of potential primordial magnetic fields (PMFs) using temperature and polarization measurements of the cosmic microwave background (CMB) from Planck, the BICEP2/Keck Array, Polarbear, and SPTpol. We reduce twofold the 95% confidence upper limit on the CMB anisotropy power due to a nearly scale-invariant PMF, with an allowed B-mode power at ℓ = 1500 of {D}{\\ell =1500}{BB}< 0.071 μ {K}2 for Planck versus {D}{\\ell =1500}{BB}< 0.034 μ {K}2 for the combined data set. We also forecast the expected limits from soon-to-deploy CMB experiments (like SPT-3G, Adv. ACTpol, or the Simons Array) and the proposed CMB-S4 experiment. Future CMB experiments should dramatically reduce the current uncertainties by one order of magnitude for the near-term experiments and two orders of magnitude for the CMB-S4 experiment. The constraints from CMB-S4 have the potential to rule out much of the parameter space for PMFs.

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.

Sample size planning for composite reliability coefficients: accuracy in parameter estimation via narrow confidence intervals.

PubMed

Terry, Leann; Kelley, Ken

2012-11-01

Composite measures play an important role in psychology and related disciplines. Composite measures almost always have error. Correspondingly, it is important to understand the reliability of the scores from any particular composite measure. However, the point estimates of the reliability of composite measures are fallible and thus all such point estimates should be accompanied by a confidence interval. When confidence intervals are wide, there is much uncertainty in the population value of the reliability coefficient. Given the importance of reporting confidence intervals for estimates of reliability, coupled with the undesirability of wide confidence intervals, we develop methods that allow researchers to plan sample size in order to obtain narrow confidence intervals for population reliability coefficients. We first discuss composite reliability coefficients and then provide a discussion on confidence interval formation for the corresponding population value. Using the accuracy in parameter estimation approach, we develop two methods to obtain accurate estimates of reliability by planning sample size. The first method provides a way to plan sample size so that the expected confidence interval width for the population reliability coefficient is sufficiently narrow. The second method ensures that the confidence interval width will be sufficiently narrow with some desired degree of assurance (e.g., 99% assurance that the 95% confidence interval for the population reliability coefficient will be less than W units wide). The effectiveness of our methods was verified with Monte Carlo simulation studies. We demonstrate how to easily implement the methods with easy-to-use and freely available software. ©2011 The British Psychological Society.

Constraints on Black Hole Spin in a Sample of Broad Iron Line AGN

NASA Technical Reports Server (NTRS)

Brenneman, Laura W.; Reynolds, Christopher S.

2008-01-01

We present a uniform X-ray spectral analysis of nine type-1 active galactic nuclei (AGN) that have been previously found to harbor relativistically broadened iron emission lines. We show that the need for relativistic effects in the spectrum is robust even when one includes continuum "reflection" from the accretion disk. We then proceed to model these relativistic effects in order to constrain the spin of the supermassive black holes in these AGN. Our principal assumption, supported by recent simulations of geometrically-thin accretion disks, is that no iron line emission (or any associated Xray reflection features) can originate from the disk within the innermost stable circular orbit. Under this assumption, which tends to lead to constraints in the form of lower limits on the spin parameter, we obtain non-trivial spin constraints on five AGN. The spin parameters of these sources range from moderate (a approximates 0.6) to high (a > 0.96). Our results allow, for the first time, an observational constraint on the spin distribution function of local supermassive black holes. Parameterizing this as a power-law in dimensionless spin parameter (f(a) varies as absolute value of (a) exp zeta), we present the probability distribution for zeta implied by our results. Our results suggest 90% and 95% confidence limits of zeta > -0.09 and zeta > -0.3 respectively.

Improvements in absolute seismometer sensitivity calibration using local earth gravity measurements

USGS Publications Warehouse

Anthony, Robert E.; Ringler, Adam; Wilson, David

2018-01-01

The ability to determine both absolute and relative seismic amplitudes is fundamentally limited by the accuracy and precision with which scientists are able to calibrate seismometer sensitivities and characterize their response. Currently, across the Global Seismic Network (GSN), errors in midband sensitivity exceed 3% at the 95% confidence interval and are the least‐constrained response parameter in seismic recording systems. We explore a new methodology utilizing precise absolute Earth gravity measurements to determine the midband sensitivity of seismic instruments. We first determine the absolute sensitivity of Kinemetrics EpiSensor accelerometers to 0.06% at the 99% confidence interval by inverting them in a known gravity field at the Albuquerque Seismological Laboratory (ASL). After the accelerometer is calibrated, we install it in its normal configuration next to broadband seismometers and subject the sensors to identical ground motions to perform relative calibrations of the broadband sensors. Using this technique, we are able to determine the absolute midband sensitivity of the vertical components of Nanometrics Trillium Compact seismometers to within 0.11% and Streckeisen STS‐2 seismometers to within 0.14% at the 99% confidence interval. The technique enables absolute calibrations from first principles that are traceable to National Institute of Standards and Technology (NIST) measurements while providing nearly an order of magnitude more precision than step‐table calibrations.

Confidence assignment for mass spectrometry based peptide identifications via the extreme value distribution.

PubMed

Alves, Gelio; Yu, Yi-Kuo

2016-09-01

There is a growing trend for biomedical researchers to extract evidence and draw conclusions from mass spectrometry based proteomics experiments, the cornerstone of which is peptide identification. Inaccurate assignments of peptide identification confidence thus may have far-reaching and adverse consequences. Although some peptide identification methods report accurate statistics, they have been limited to certain types of scoring function. The extreme value statistics based method, while more general in the scoring functions it allows, demands accurate parameter estimates and requires, at least in its original design, excessive computational resources. Improving the parameter estimate accuracy and reducing the computational cost for this method has two advantages: it provides another feasible route to accurate significance assessment, and it could provide reliable statistics for scoring functions yet to be developed. We have formulated and implemented an efficient algorithm for calculating the extreme value statistics for peptide identification applicable to various scoring functions, bypassing the need for searching large random databases. The source code, implemented in C ++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit yyu@ncbi.nlm.nih.gov Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

Evaluation of measurement uncertainty of glucose in clinical chemistry.

PubMed

Berçik Inal, B; Koldas, M; Inal, H; Coskun, C; Gümüs, A; Döventas, Y

2007-04-01

The definition of the uncertainty of measurement used in the International Vocabulary of Basic and General Terms in Metrology (VIM) is a parameter associated with the result of a measurement, which characterizes the dispersion of the values that could reasonably be attributed to the measurand. Uncertainty of measurement comprises many components. In addition to every parameter, the measurement uncertainty is that a value should be given by all institutions that have been accredited. This value shows reliability of the measurement. GUM, published by NIST, contains uncertainty directions. Eurachem/CITAC Guide CG4 was also published by Eurachem/CITAC Working Group in the year 2000. Both of them offer a mathematical model, for uncertainty can be calculated. There are two types of uncertainty in measurement. Type A is the evaluation of uncertainty through the statistical analysis and type B is the evaluation of uncertainty through other means, for example, certificate reference material. Eurachem Guide uses four types of distribution functions: (1) rectangular distribution that gives limits without specifying a level of confidence (u(x)=a/ radical3) to a certificate; (2) triangular distribution that values near to the same point (u(x)=a/ radical6); (3) normal distribution in which an uncertainty is given in the form of a standard deviation s, a relative standard deviation s/ radicaln, or a coefficient of variance CV% without specifying the distribution (a = certificate value, u = standard uncertainty); and (4) confidence interval.

Measurement of the cross sections of the reactions e +e - → γγ and e +e - → γγγ at LEP

NASA Astrophysics Data System (ADS)

Akwawy, M. Z.; Alexander, G.; Allison, J.; Allport, P. P.; Anderson, K. J.; Armitage, J. C.; Arnison, G. T. J.; Ashton, P.; Azuelos, G.; Baines, J. T. M.; Ball, A. H.; Banks, J.; Barker, G. J.; Barlow, R. J.; Batley, J. R.; Beaudoin, G.; Beck, A.; Becker, J.; Behnke, T.; Bell, K. W.; Bella, G.; Bethke, S.; Biebel, O.; Binder, U.; Bloodworth, I. J.; Bock, P.; Breuker, H.; Brown, R. M.; Brun, R.; Buijs, A.; Burckhart, H. J.; Capiluppi, P.; Carnegie, R. K.; Carter, A. A.; Carter, J. R.; Chang, C. Y.; Charlton, D. G.; Chrin, J. T. M.; Clarke, P. E. L.; Cohen, I.; Collins, W. J.; Conboy, J. E.; Couch, M.; Coupland, M.; Cuffiani, M.; Dado, S.; Dallavalle, G. M.; De Jong, S.; Debu, P.; Deninno, M. M.; Dieckmann, A.; Dittmar, M.; Dixit, M. S.; Duchovni, E.; Duerdoth, I. P.; Dumas, D. J. P.; Elcombe, P. A.; Estabrooks, P. G.; Etzion, E.; Fabbri, F.; Farthouat, P.; Fischer, H. M.; Fong, D. G.; French, M. T.; Fukunaga, C.; Gaidot, A.; Ganel, O.; Gary, J. W.; Gascon, J.; Geddes, N. I.; Gee, C. N. P.; Geich-Gimbel, C.; Gensler, S. W.; Gentit, F. X.; Giacomelli, G.; Gibson, V.; Gibson, W. R.; Gillies, J. D.; Goldberg, J.; Goodrick, M. J.; Gorn, W.; Granite, D.; Gross, E.; Grunhaus, J.; Hagedorn, H.; Hagemann, J.; Hansroul, M.; Hargrove, C. K.; Harrus, I.; Hart, J.; Hattersley, P. M.; Hauschild, M.; Hawkes, C. M.; Heflin, E.; Hemingway, R. J.; Heuer, R. D.; Hill, J. C.; Hillier, S. J.; Hinshaw, D. A.; Ho, C.; Hobbs, J. D.; Hobson, P. R.; Hochman, D.; Holl, B.; Homer, R. J.; Hou, S. R.; Howarth, C. P.; Hughes-Jones, R. E.; Humbert, R.; Igo-Kemenes, P.; Ihssen, H.; Imrie, D. C.; Janissen, L.; Jawahery, A.; Jeffreys, P. W.; Jeremie, H.; Jimack, M.; Jobes, M.; Jones, R. W. L.; Jovanovic, P.; Karlen, D.; Kawagoe, K.; Kawamoto, T.; Kellogg, R. G.; Kennedy, B. W.; Kleinwort, C.; Klem, D. E.; Knop, G.; Kobayashi, T.; Kokott, T. P.; Köpke, L.; Kowalewski, R.; Kreutzmann, H.; Kroll, J.; Kuwano, M.; Kyberd, P.; Lafferty, G. D.; Lamarche, F.; Larson, W. J.; Layter, J. G.; Le Du, P.; Leblanc, P.; Lee, A. M.; Lehto, M. H.; Lellouch, D.; Lennert, P.; Leroy, C.; Lessard, L.; Levegrün, S.; Levinson, L.; Lloyd, S. L.; Loebinger, F. K.; Lorah, J. M.; Lorazo, B.; Losty, M. J.; Ludwig, J.; Ma, J.; Macbeth, A. A.; Mannelli, M.; Marcellini, S.; Maringer, G.; Martin, A. J.; Martin, J. P.; Mashimo, T.; Mättig, P.; Maur, U.; McMahon, T. J.; McNutt, J. R.; Meijers, F.; Menszner, D.; Merritt, F. S.; Mes, H.; Michelini, A.; Middleton, R. P.; Mikenberg, G.; Mildenberger, J.; Miller, D. J.; Milstene, C.; Minowa, M.; Mohr, W.; Moisan, C.; Montanari, A.; Mori, T.; Moss, M. W.; Murphy, P. G.; Murray, W. J.; Nellen, B.; Nguyen, H. H.; Nozaki, M.; O'Dowd, A. J. P.; O'Neale, S. W.; O'Neill, B. P.; Oakham, F. G.; Odorici, F.; Ogg, M.; Oh, H.; Oreglia, M. J.; Orito, S.; Pansart, J. P.; Patrick, G. N.; Pawley, S. J.; Pfister, P.; Pilcher, J. E.; Pinfold, J. L.; Plane, D. E.; Poli, B.; Pouladdej, A.; Prebys, E.; Pritchard, T. W.; Przysiezniak, H.; Quast, G.; Redmond, M. W.; Rees, D. L.; Regimbald, M.; Riles, K.; Roach, C. M.; Robins, S. A.; Rollnik, A.; Roney, J. M.; Rossberg, S.; Rossi, A. M.; Routenburg, P.; Runge, K.; Runolfsson, O.; Sanghera, S.; Sansum, R. A.; Sasaki, M.; Saunders, B. J.; Schaile, A. D.; Schaile, O.; Schappert, W.; Scharff-Hansen, P.; Schreiber, S.; Schwarz, J.; Shapira, A.; Shen, B. C.; Sherwood, P.; Simon, A.; Singh, P.; Siroli, G. P.; Skuja, A.; Smith, A. M.; Smith, T. J.; Snow, G. A.; Springer, R. W.; Sproston, M.; Stephens, K.; Stier, H. E.; Stroehmer, R.; Strom, D.; Takeda, H.; Takeshita, T.; Taras, P.; Thackray, N. J.; Tsukamoto, T.; Turner, M. F.; Tysarczyk-Niemeyer, G.; Van den plas, D.; Van Kooten, R.; VanDalen, G. J.; Vasseur, G.; Virtue, C. J.; von der Schmitt, H.; von Krogh, J.; Wagner, A.; Wahl, C.; Walker, J. P.; Ward, C. P.; Ward, D. R.; Watkins, P. M.; Watson, A. T.; Watson, N. K.; Weber, M.; Weisz, S.; Wells, P. S.; Wermes, N.; Weymann, M.; Wilson, G. W.; Wilson, J. A.; Wingerter, I.; Winterer, V.-H.; Wood, N. C.; Wotton, S.; Wyatt, T. R.; Yaari, R.; Yang, Y.; Yekutieli, G.; Yoshida, T.; Zeuner, W.; Zorn, G. T.; OPAL Collaboration

1991-03-01

The cross section of the pure QED process e +e -→ γγ has been measured using data accumulated during the 1989 and 1990 scans of the Z 0 resonance at LEP. Both the energy dependence and the angular distribution are in good agreement with the QED prediction. Upper limits on the branching ratios of Z 0→ γγ, Z 0→ π0γ and Z 0→ ηγ have been set at 1.4×10 -4, 1.4×10 -4 and 2.0×10 -4 respectively. Lower limits on the cutoff parameters of the modified electron propagator have been found to be Λ+ > 117 GeV and Λ- > 110 GeV. The reaction e +e - → γγγ has also been studied and was found to be consistent with the QED prediction. An upper limit on the branching ratio of Z 0→ γγγ has been set at 6.6 × 10 -5. All the limits are given at 95% confidence level.

Assessing the limitations of the Banister model in monitoring training

PubMed Central

Hellard, Philippe; Avalos, Marta; Lacoste, Lucien; Barale, Frédéric; Chatard, Jean-Claude; Millet, Grégoire P.

2006-01-01

The aim of this study was to carry out a statistical analysis of the Banister model to verify how useful it is in monitoring the training programmes of elite swimmers. The accuracy, the ill-conditioning and the stability of this model were thus investigated. Training loads of nine elite swimmers, measured over one season, were related to performances with the Banister model. Firstly, to assess accuracy, the 95% bootstrap confidence interval (95% CI) of parameter estimates and modelled performances were calculated. Secondly, to study ill-conditioning, the correlation matrix of parameter estimates was computed. Finally, to analyse stability, iterative computation was performed with the same data but minus one performance, chosen randomly. Performances were significantly related to training loads in all subjects (R2= 0.79 ± 0.13, P < 0.05) and the estimation procedure seemed to be stable. Nevertheless, the 95% CI of the most useful parameters for monitoring training were wide τa =38 (17, 59), τf =19 (6, 32), tn =19 (7, 35), tg =43 (25, 61). Furthermore, some parameters were highly correlated making their interpretation worthless. The study suggested possible ways to deal with these problems and reviewed alternative methods to model the training-performance relationships. PMID:16608765

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

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

The electroweak production and subsequent decay of single top quarks is determined by the properties of the Wtb vertex. This vertex can be described by the complex parameters of an effective Lagrangian. An analysis of angular distributions of the decay products of single top quarks produced in the t -channel constrains these parameters simultaneously. The analysis described in this paper uses 4.6 fb -1 of proton-proton collision data at √s=7 TeV collected with the ATLAS detector at the LHC. Two parameters are measured simultaneously in this analysis. The fraction f 1 of decays containing transversely polarised W bosons is measuredmore » to be 0.37 ± 0.07 (stat.⊕syst.). The phase δ - between amplitudes for transversely and longitudinally polarised W bosons recoiling against left-handed b-quarks is measured to be -0.014π ± 0.036π (stat.⊕syst.). The correlation in the measurement of these parameters is 0.15. These values result in two-dimensional limits at the 95% confidence level on the ratio of the complex coupling parameters g R and V L, yielding Re[g R /V L] ϵ [-0.36, 0.10] and Im[g R /V L] ϵ [-0.17, 0.23] with a correlation of 0.11. We find the results are in good agreement with the predictions of the Standard Model.« less

Computational tools for fitting the Hill equation to dose-response curves.

PubMed

Gadagkar, Sudhindra R; Call, Gerald B

2015-01-01

Many biological response curves commonly assume a sigmoidal shape that can be approximated well by means of the 4-parameter nonlinear logistic equation, also called the Hill equation. However, estimation of the Hill equation parameters requires access to commercial software or the ability to write computer code. Here we present two user-friendly and freely available computer programs to fit the Hill equation - a Solver-based Microsoft Excel template and a stand-alone GUI-based "point and click" program, called HEPB. Both computer programs use the iterative method to estimate two of the Hill equation parameters (EC50 and the Hill slope), while constraining the values of the other two parameters (the minimum and maximum asymptotes of the response variable) to fit the Hill equation to the data. In addition, HEPB draws the prediction band at a user-defined confidence level, and determines the EC50 value for each of the limits of this band to give boundary values that help objectively delineate sensitive, normal and resistant responses to the drug being tested. Both programs were tested by analyzing twelve datasets that varied widely in data values, sample size and slope, and were found to yield estimates of the Hill equation parameters that were essentially identical to those provided by commercial software such as GraphPad Prism and nls, the statistical package in the programming language R. The Excel template provides a means to estimate the parameters of the Hill equation and plot the regression line in a familiar Microsoft Office environment. HEPB, in addition to providing the above results, also computes the prediction band for the data at a user-defined level of confidence, and determines objective cut-off values to distinguish among response types (sensitive, normal and resistant). Both programs are found to yield estimated values that are essentially the same as those from standard software such as GraphPad Prism and the R-based nls. Furthermore, HEPB also has the option to simulate 500 response values based on the range of values of the dose variable in the original data and the fit of the Hill equation to that data. Copyright © 2014. Published by Elsevier Inc.

Probabilistic migration modelling focused on functional barrier efficiency and low migration concepts in support of risk assessment.

PubMed

Brandsch, Rainer

2017-10-01

Migration modelling provides reliable migration estimates from food-contact materials (FCM) to food or food simulants based on mass-transfer parameters like diffusion and partition coefficients related to individual materials. In most cases, mass-transfer parameters are not readily available from the literature and for this reason are estimated with a given uncertainty. Historically, uncertainty was accounted for by introducing upper limit concepts first, turning out to be of limited applicability due to highly overestimated migration results. Probabilistic migration modelling gives the possibility to consider uncertainty of the mass-transfer parameters as well as other model inputs. With respect to a functional barrier, the most important parameters among others are the diffusion properties of the functional barrier and its thickness. A software tool that accepts distribution as inputs and is capable of applying Monte Carlo methods, i.e., random sampling from the input distributions of the relevant parameters (i.e., diffusion coefficient and layer thickness), predicts migration results with related uncertainty and confidence intervals. The capabilities of probabilistic migration modelling are presented in the view of three case studies (1) sensitivity analysis, (2) functional barrier efficiency and (3) validation by experimental testing. Based on the predicted migration by probabilistic migration modelling and related exposure estimates, safety evaluation of new materials in the context of existing or new packaging concepts is possible. Identifying associated migration risk and potential safety concerns in the early stage of packaging development is possible. Furthermore, dedicated material selection exhibiting required functional barrier efficiency under application conditions becomes feasible. Validation of the migration risk assessment by probabilistic migration modelling through a minimum of dedicated experimental testing is strongly recommended.

Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

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

Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin

Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

DOE PAGES

Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin; ...

2016-04-04

Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

Data on electrical energy conservation using high efficiency motors for the confidence bounds using statistical techniques.

PubMed

Shaikh, Muhammad Mujtaba; Memon, Abdul Jabbar; Hussain, Manzoor

2016-09-01

In this article, we describe details of the data used in the research paper "Confidence bounds for energy conservation in electric motors: An economical solution using statistical techniques" [1]. The data presented in this paper is intended to show benefits of high efficiency electric motors over the standard efficiency motors of similar rating in the industrial sector of Pakistan. We explain how the data was collected and then processed by means of formulas to show cost effectiveness of energy efficient motors in terms of three important parameters: annual energy saving, cost saving and payback periods. This data can be further used to construct confidence bounds for the parameters using statistical techniques as described in [1].

Inverse modeling with RZWQM2 to predict water quality

USDA-ARS?s Scientific Manuscript database

Agricultural systems models such as RZWQM2 are complex and have numerous parameters that are unknown and difficult to estimate. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals...

Search for W‧ decaying to tau lepton and neutrino in proton-proton collisions at √{ s} = 8 TeV

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Knünz, V.; König, A.; Krammer, M.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, 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.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; de Bruyn, I.; Deroover, K.; Heracleous, N.; Keaveney, J.; Lowette, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; van Doninck, W.; van Mulders, P.; van Onsem, G. P.; van Parijs, I.; Barria, P.; Caillol, C.; Clerbaux, B.; de Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Lenzi, T.; Léonard, A.; Maerschalk, T.; Marinov, A.; Perniè, L.; Randle-Conde, A.; Reis, T.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Beernaert, K.; Benucci, L.; Cimmino, A.; Crucy, S.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; McCartin, J.; Ocampo Rios, A. A.; Poyraz, D.; Ryckbosch, D.; Salva, S.; Sigamani, M.; Strobbe, N.; Tytgat, M.; van Driessche, W.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; da Silveira, G. G.; Delaere, C.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Mertens, A.; Nuttens, C.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Beliy, N.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hensel, C.; Mora Herrera, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; da Costa, E. M.; de Jesus Damiao, D.; de Oliveira Martins, C.; Fonseca de Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; de Souza Santos, A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Genchev, V.; Hadjiiska, R.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Shaheen, S. M.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Zou, W.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Micanovic, S.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Mahmoud, M. A.; Calpas, B.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; 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.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Dahms, T.; Davignon, O.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Lisniak, S.; Mastrolorenzo, L.; Miné, P.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Merlin, J. A.; Skovpen, K.; van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Edelhoff, M.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schulte, J. F.; Verlage, T.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Edelhäuser, L.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knochel, A.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asin, I.; Bartosik, N.; Behnke, O.; Behrens, U.; Bell, A. J.; 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.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Korol, I.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; 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.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Trippkewitz, K. D.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Gonzalez, D.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Junkes, A.; Klanner, R.; Kogler, R.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Nowatschin, D.; Ott, J.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Schwandt, J.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Akbiyik, M.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; Colombo, F.; de Boer, W.; Descroix, A.; Dierlamm, A.; Fink, S.; Frensch, F.; Giffels, M.; Gilbert, A.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Katkov, I.; Kornmayer, A.; Lobelle Pardo, P.; Maier, B.; Mildner, H.; Mozer, M. U.; Müller, T.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weber, M.; Weiler, T.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Bencze, G.; Hajdu, C.; Hazi, A.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Szillasi, Z.; Bartók, M.; Makovec, A.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Mal, P.; Mandal, K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Kumar, Arun; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Nishu, N.; Ranjan, K.; Sharma, R.; Sharma, V.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutta, S.; Jain, Sa.; Majumdar, N.; Modak, A.; Mondal, K.; Mukherjee, S.; Mukhopadhyay, S.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Chudasama, R.; Dutta, D.; Jha, V.; 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.; Mahakud, B.; Maity, M.; Majumder, G.; Mazumdar, K.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sarkar, T.; Sudhakar, K.; Sur, N.; Sutar, B.; Wickramage, N.; Chauhan, S.; Dube, S.; Sharma, S.; 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.; Caputo, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; Cristella, L.; de Filippis, N.; de Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; 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.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; 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.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Malvezzi, S.; Manzoni, R. 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.; Esposito, M.; Fabozzi, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Montecassiano, F.; Passaseo, M.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; 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.; Fedi, G.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; D'Imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Costa, M.; Covarelli, R.; de Remigis, P.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Musich, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; 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.; Sakharov, A.; Son, D. C.; Brochero Cifuentes, J. A.; Kim, H.; Kim, T. J.; Ryu, M. S.; Song, S.; Choi, S.; Go, Y.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K.; Lee, K. S.; Lee, S.; Park, S. K.; Roh, Y.; Yoo, H. D.; Choi, M.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Yu, I.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Komaragiri, J. R.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; 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.; Carpinteyro, S.; 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.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Walczak, M.; Bargassa, P.; Beirão da Cruz E Silva, C.; di Francesco, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Leonardo, N.; Lloret Iglesias, L.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; 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.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; 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.; Vlasov, E.; Zhokin, A.; Bylinkin, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Myagkov, I.; Obraztsov, S.; Perfilov, M.; Savrin, V.; 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.; 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.; Palencia Cortezon, E.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Castiñeiras de Saa, J. R.; de Castro Manzano, P.; 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.; Berruti, G. M.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D'Alfonso, M.; D'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; de Gruttola, M.; de Guio, F.; de Roeck, A.; de Visscher, S.; di Marco, E.; Dobson, M.; Dordevic, M.; Du Pree, T.; Dupont, N.; Elliott-Peisert, A.; 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.; Kirschenmann, H.; Kortelainen, M. J.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Magini, N.; Malgeri, L.; Mannelli, M.; Martelli, A.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Nemallapudi, M. V.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Piparo, D.; Racz, A.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Triossi, A.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lustermann, W.; Mangano, B.; Marini, A. C.; Marionneau, M.; Martinez Ruiz Del Arbol, P.; Masciovecchio, M.; Meister, D.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrozzi, L.; Peruzzi, M.; Quittnat, M.; Rossini, M.; Starodumov, A.; Takahashi, M.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; Chiochia, V.; de Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Ngadiuba, J.; Pinna, D.; Robmann, P.; Ronga, F. J.; Salerno, D.; Yang, Y.; Cardaci, M.; Chen, K. H.; Doan, T. H.; Ferro, C.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Bartek, R.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Fiori, F.; Grundler, U.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Petrakou, E.; Tsai, J. F.; Tzeng, Y. M.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; Vergili, M.; Zorbilmez, C.; Akin, I. V.; Bilin, B.; Bilmis, S.; Isildak, B.; Karapinar, G.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; Cankocak, K.; Sen, S.; Vardarlı, F. I.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; 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.; Seif El Nasr-Storey, S.; Senkin, S.; Smith, D.; Smith, V. J.; 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.; Thomas, L.; Tomalin, I. R.; Williams, T.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Cripps, N.; Dauncey, P.; Davies, G.; de Wit, A.; Della Negra, M.; Dunne, P.; Elwood, A.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Richards, A.; Rose, A.; Seez, C.; Tapper, A.; Uchida, K.; 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.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Gastler, D.; Lawson, P.; Rankin, D.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Zou, D.; Alimena, J.; Berry, E.; Bhattacharya, S.; Cutts, D.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Sagir, S.; Sinthuprasith, T.; 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.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Saltzberg, D.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Paneva, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Wei, H.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; MacNeill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Incandela, J.; Justus, C.; McColl, N.; Mullin, S. D.; Richman, J.; Stuart, D.; Suarez, I.; To, W.; West, C.; Yoo, J.; Anderson, D.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Pierini, M.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Sun, W.; Tan, S. M.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Wittich, P.; 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.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Hu, Z.; Jindariani, S.; Johnson, M.; Joshi, U.; Jung, A. W.; Klima, B.; Kreis, B.; Kwan, S.; Lammel, 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.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Weber, H. A.; Whitbeck, A.; Yang, F.; Yin, H.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Low, J. F.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rank, D.; Rossin, R.; Shchutska, L.; Snowball, M.; Sperka, D.; Wang, J.; Wang, S.; Yelton, J.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Bhopatkar, V.; Hohlmann, M.; Kalakhety, H.; Mareskas-Palcek, D.; Roy, T.; 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.; O'Brien, C.; Sandoval Gonzalez, I. D.; Silkworth, C.; Turner, P.; Varelas, N.; Wu, Z.; Zakaria, M.; 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.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Barnett, B. A.; Blumenfeld, B.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Nash, K.; Osherson, M.; Swartz, M.; Xiao, M.; Xin, Y.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Gray, J.; Kenny, R. P., III; Majumder, D.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Svintradze, I.; Toda, S.; Lange, D.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Baty, A.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; McGinn, C.; Mironov, C.; Niu, X.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Dahmes, B.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Meier, F.; Monroy, J.; Ratnikov, F.; Siado, J. E.; Snow, G. R.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira de Lima, R.; 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.; Trovato, M.; Velasco, M.; Won, S.; Brinkerhoff, A.; Dev, N.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Lynch, S.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Pearson, T.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; 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.; Liu, B.; Luo, W.; Puigh, D.; Rodenburg, M.; Winer, B. L.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Malik, S.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Miller, D. H.; Neumeister, N.; Primavera, F.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Zablocki, J.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Hindrichs, O.; Khukhunaishvili, A.; Petrillo, G.; Verzetti, M.; Demortier, L.; 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.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Lath, A.; Panwalkar, S.; Park, M.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Riley, G.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Dalchenko, M.; de Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Krutelyov, V.; Montalvo, R.; Mueller, R.; Osipenkov, I.; Pakhotin, Y.; Patel, R.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wolfe, E.; Wood, J.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Christian, A.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Gomber, B.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Ruggles, T.; Sarangi, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; Cms Collaboration

2016-04-01

The first search for a heavy charged vector boson in the final state with a tau lepton and a neutrino is reported, using 19.7 fb-1 of LHC data at √{ s} = 8 TeV. A signal would appear as an excess of events with high transverse mass, where the standard model background is low. No excess is observed. Limits are set on a model in which the W‧ decays preferentially to fermions of the third generation. These results substantially extend previous constraints on this model. Masses below 2.0 to 2.7 TeV are excluded, depending on the model parameters. In addition, the existence of a W‧ boson with universal fermion couplings is excluded at 95% confidence level, for W‧ masses below 2.7 TeV. For further reinterpretation a model-independent limit on potential signals for various transverse mass thresholds is also presented.

Search for new resonances decaying via WZ to leptons in proton–proton collisions at $$\\sqrt s =$$ 8 TeV

DOE PAGES

Khachatryan, V.

2014-11-18

A search is performed in proton–proton collisions at √s=8 TeV for exotic particles decaying via WZ to fully leptonic final states with electrons, muons, and neutrinos. The data set corresponds to an integrated luminosity of 19.5 fb -1. No significant excess is observed above the expected standard model background. Upper bounds at 95% confidence level are set on the production cross section of a W' boson as predicted by an extended gauge model, and on the W'WZ coupling. The expected and observed mass limits for a W' boson, as predicted by this model, are 1.55 and 1.47 TeV, respectively. Stringentmore » limits are also set in the context of low-scale technicolor models under a range of assumptions for the model parameters.« less

Search for low-scale gravity signatures in multi-jet final states with the ATLAS detector at $$\\sqrt{s}=8 $$ TeV

DOE PAGES

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

2015-07-07

A search for evidence of physics beyond the Standard Model in final states with multiple high-transverse-momentum jets is performed using 20.3 fb -1 of proton-proton collision data at √s = 8 TeV recorded by the ATLAS detector at the LHC. No significant excess of events beyond Standard Model expectations is observed, and upper limits on the visible cross sections for non-Standard Model production of multi-jet final states are set. A wide variety of models for black hole and string ball production and decay are considered, and the upper limit on the cross section times acceptance is as low as 0.16more » fb at the 95% confidence level. For these models, excluded regions are also given as function of the main model parameters.« less

Directed search for continuous gravitational waves from the Galactic center

NASA Astrophysics Data System (ADS)

Aasi, J.; Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T.; Abernathy, M. R.; Accadia, T.; Acernese, F.; Adams, C.; Adams, T.; Adhikari, R. X.; Affeldt, C.; Agathos, M.; Aggarwal, N.; Aguiar, O. D.; Ajith, P.; Allen, B.; Allocca, A.; Amador Ceron, E.; Amariutei, D.; Anderson, R. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C.; Areeda, J.; Ast, S.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Austin, L.; Aylott, B. E.; Babak, S.; Baker, P. T.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barker, D.; Barnum, S. H.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J.; Bauchrowitz, J.; Bauer, Th. S.; Bebronne, M.; Behnke, B.; Bejger, M.; Beker, M. G.; Bell, A. S.; Bell, C.; Belopolski, I.; Bergmann, G.; Berliner, J. M.; Bertolini, A.; Bessis, D.; Betzwieser, J.; Beyersdorf, P. T.; Bhadbhade, T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Blom, M.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogan, C.; Bond, C.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Bose, S.; Bosi, L.; Bowers, J.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brannen, C. A.; Brau, J. E.; Breyer, J.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Britzger, M.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brückner, F.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Calderón Bustillo, J.; Calloni, E.; Camp, J. B.; Campsie, P.; Cannon, K. C.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Castiglia, A.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J.; Christensen, N.; Chu, Q.; Chua, S. S. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, D. E.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Colombini, M.; Constancio, M., Jr.; Conte, A.; Conte, R.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M. W.; Coulon, J.-P.; Countryman, S.; Couvares, P.; Coward, D. M.; Cowart, M.; Coyne, D. C.; Craig, K.; Creighton, J. D. E.; Creighton, T. D.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dahl, K.; Dal Canton, T.; Damjanic, M.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daudert, B.; Daveloza, H.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; Dayanga, T.; De Rosa, R.; Debreczeni, G.; Degallaix, J.; Del Pozzo, W.; Deleeuw, E.; Deléglise, S.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; DeRosa, R.; DeSalvo, R.; Dhurandhar, S.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Virgilio, A.; Díaz, M.; Dietz, A.; Dmitry, K.; Donovan, F.; Dooley, K. L.; Doravari, S.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dumas, J.-C.; Dwyer, S.; Eberle, T.; Edwards, M.; Effler, A.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Endrőczi, G.; Essick, R.; Etzel, T.; Evans, K.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fang, Q.; Farr, B.; Farr, W.; Favata, M.; Fazi, D.; Fehrmann, H.; Feldbaum, D.; Ferrante, I.; Ferrini, F.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R.; Flaminio, R.; Foley, E.; Foley, S.; Forsi, E.; Forte, L. A.; Fotopoulos, N.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, M.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fujimoto, M.-K.; Fulda, P.; Fyffe, M.; Gair, J.; Gammaitoni, L.; Garcia, J.; Garufi, F.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; Gergely, L.; Ghosh, S.; Giaime, J. A.; Giampanis, S.; Giardina, K. D.; Giazotto, A.; Gil-Casanova, S.; Gill, C.; Gleason, J.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gordon, N.; Gorodetsky, M. L.; Gossan, S.; Goßler, S.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Griffo, C.; Grote, H.; Grover, K.; Grunewald, S.; Guidi, G. M.; Guido, C.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, B.; Hall, E.; Hammer, D.; Hammond, G.; Hanke, M.; Hanks, J.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hartman, M. T.; Haughian, K.; Hayama, K.; Heefner, J.; Heidmann, A.; Heintze, M.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Holtrop, M.; Hong, T.; Hooper, S.; Horrom, T.; Hosken, D. J.; Hough, J.; Howell, E. J.; Hu, Y.; Hua, Z.; Huang, V.; Huerta, E. A.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh, M.; Huynh-Dinh, T.; Iafrate, J.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Iyer, B. R.; Izumi, K.; Jacobson, M.; James, E.; Jang, H.; Jang, Y. J.; Jaranowski, P.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; K, Haris; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kasprzack, M.; Kasturi, R.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kaufman, K.; Kawabe, K.; Kawamura, S.; Kawazoe, F.; Kéfélian, F.; Keitel, D.; Kelley, D. B.; Kells, W.; Keppel, D. G.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, B. K.; Kim, C.; Kim, K.; Kim, N.; Kim, W.; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kline, J.; Koehlenbeck, S.; Kokeyama, K.; Kondrashov, V.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D.; Kremin, A.; Kringel, V.; Krishnan, B.; Królak, A.; Kucharczyk, C.; Kudla, S.; Kuehn, G.; Kumar, A.; Kumar, P.; Kumar, R.; Kurdyumov, R.; Kwee, P.; Landry, M.; Lantz, B.; Larson, S.; Lasky, P. D.; Lawrie, C.; Lazzarini, A.; Le Roux, A.; Leaci, P.; Lebigot, E. O.; Lee, C.-H.; Lee, H. K.; Lee, H. M.; Lee, J.; Lee, J.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levine, B.; Lewis, J. B.; Lhuillier, V.; Li, T. G. F.; Lin, A. C.; Littenberg, T. B.; Litvine, V.; Liu, F.; Liu, H.; Liu, Y.; Liu, Z.; Lloyd, D.; Lockerbie, N. A.; Lockett, V.; Lodhia, D.; Loew, K.; Logue, J.; Lombardi, A. L.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Luan, J.; Lubinski, M. J.; Lück, H.; Lundgren, A. P.; Macarthur, J.; Macdonald, E.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Mageswaran, M.; Mailand, K.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Manca, G. M.; Mandel, I.; Mandic, V.; Mangano, V.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martin, I. W.; Martin, R. M.; Martinelli, L.; Martynov, D.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; May, G.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; Meacher, D.; Meadors, G. D.; Mehmet, M.; Meidam, J.; Meier, T.; Melatos, A.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyer, M. S.; Miao, H.; Michel, C.; Mikhailov, E. E.; Milano, L.; Miller, J.; Minenkov, Y.; Mingarelli, C. M. F.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moe, B.; Mohan, M.; Mohapatra, S. R. P.; Mokler, F.; Moraru, D.; Moreno, G.; Morgado, N.; Mori, T.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nagy, M. F.; Nanda Kumar, D.; Nardecchia, I.; Nash, T.; Naticchioni, L.; Nayak, R.; Necula, V.; Neri, I.; Newton, G.; Nguyen, T.; Nishida, E.; Nishizawa, A.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L. K.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oppermann, P.; O'Reilly, B.; Ortega Larcher, W.; O'Shaughnessy, R.; Osthelder, C.; Ottaway, D. J.; Ottens, R. S.; Ou, J.; Overmier, H.; Owen, B. J.; Padilla, C.; Pai, A.; Palomba, C.; Pan, Y.; Pankow, C.; Paoletti, F.; Paoletti, R.; Papa, M. A.; Paris, H.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Pedraza, M.; Peiris, P.; Penn, S.; Perreca, A.; Phelps, M.; Pichot, M.; Pickenpack, M.; Piergiovanni, F.; Pierro, V.; Pinard, L.; Pindor, B.; Pinto, I. M.; Pitkin, M.; Pletsch, H. J.; Poeld, J.; Poggiani, R.; Poole, V.; Poux, C.; Predoi, V.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Quetschke, V.; Quintero, E.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Raja, S.; Rajalakshmi, G.; Rakhmanov, M.; Ramet, C.; Rapagnani, P.; Raymond, V.; Re, V.; Reed, C. M.; Reed, T.; Regimbau, T.; Reid, S.; Reitze, D. H.; Ricci, F.; Riesen, R.; Riles, K.; Robertson, N. A.; Robinet, F.; Rocchi, A.; Roddy, S.; Rodriguez, C.; Rodruck, M.; Roever, C.; Rolland, L.; Rollins, J. G.; Romano, J. D.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Salemi, F.; Sammut, L.; Sandberg, V.; Sanders, J.; Sannibale, V.; Santiago-Prieto, I.; Saracco, E.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Savage, R.; Schilling, R.; Schnabel, R.; Schofield, R. M. S.; Schreiber, E.; Schuette, D.; Schulz, B.; Schutz, B. F.; Schwinberg, P.; Scott, J.; Scott, S. M.; Seifert, F.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sergeev, A.; Shaddock, D.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sidery, T. L.; Siellez, K.; Siemens, X.; Sigg, D.; Simakov, D.; Singer, A.; Singer, L.; Sintes, A. M.; Skelton, G. R.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M. R.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Soden, K.; Son, E. J.; Sorazu, B.; Souradeep, T.; Sperandio, L.; Staley, A.; Steinert, E.; Steinlechner, J.; Steinlechner, S.; Steplewski, S.; Stevens, D.; Stochino, A.; Stone, R.; Strain, K. A.; Strigin, S.; Stroeer, A. S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Szeifert, G.; Tacca, M.; Talukder, D.; Tang, L.; Tanner, D. B.; Tarabrin, S. P.; Taylor, R.; ter Braack, A. P. M.; Thirugnanasambandam, M. P.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C. V.; Torrie, C. I.; Travasso, F.; Traylor, G.; Tse, M.; Ugolini, D.; Unnikrishnan, C. S.; Vahlbruch, H.; Vajente, G.; Vallisneri, M.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van der Sluys, M. V.; van Heijningen, J.; van Veggel, A. A.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Verma, S.; Vetrano, F.; Viceré, A.; Vincent-Finley, R.; Vinet, J.-Y.; Vitale, S.; Vlcek, B.; Vo, T.; Vocca, H.; Vorvick, C.; Vousden, W. D.; Vrinceanu, D.; Vyachanin, S. P.; Wade, A.; Wade, L.; Wade, M.; Waldman, S. J.; Walker, M.; Wallace, L.; Wan, Y.; Wang, J.; Wang, M.; Wang, X.; Wanner, A.; Ward, R. L.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; White, D. J.; Whiting, B. F.; Wibowo, S.; Wiesner, K.; Wilkinson, C.; Williams, L.; Williams, R.; Williams, T.; Willis, J. L.; Willke, B.; Wimmer, M.; Winkelmann, L.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Yablon, J.; Yakushin, I.; Yamamoto, H.; Yancey, C. C.; Yang, H.; Yeaton-Massey, D.; Yoshida, S.; Yum, H.; Yvert, M.; Zadrożny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, F.; Zhang, L.; Zhao, C.; Zhu, H.; Zhu, X. J.; Zotov, N.; Zucker, M. E.; Zweizig, J.

2013-11-01

We present the results of a directed search for continuous gravitational waves from unknown, isolated neutron stars in the Galactic center region, performed on two years of data from LIGO’s fifth science run from two LIGO detectors. The search uses a semicoherent approach, analyzing coherently 630 segments, each spanning 11.5 hours, and then incoherently combining the results of the single segments. It covers gravitational wave frequencies in a range from 78 to 496 Hz and a frequency-dependent range of first-order spindown values down to -7.86×10-8Hz/s at the highest frequency. No gravitational waves were detected. The 90% confidence upper limits on the gravitational wave amplitude of sources at the Galactic center are ˜3.35×10-25 for frequencies near 150 Hz. These upper limits are the most constraining to date for a large-parameter-space search for continuous gravitational wave signals.

Exact one-sided confidence limits for the difference between two correlated proportions.

PubMed

Lloyd, Chris J; Moldovan, Max V

2007-08-15

We construct exact and optimal one-sided upper and lower confidence bounds for the difference between two probabilities based on matched binary pairs using well-established optimality theory of Buehler. Starting with five different approximate lower and upper limits, we adjust them to have coverage probability exactly equal to the desired nominal level and then compare the resulting exact limits by their mean size. Exact limits based on the signed root likelihood ratio statistic are preferred and recommended for practical use.

Sensitivity Analysis in Sequential Decision Models.

PubMed

Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet

2017-02-01

Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.

Calculation of Weibull strength parameters and Batdorf flow-density constants for volume- and surface-flaw-induced fracture in ceramics

NASA Technical Reports Server (NTRS)

Shantaram, S. Pai; Gyekenyesi, John P.

1989-01-01

The calculation of shape and scale parametes of the two-parameter Weibull distribution is described using the least-squares analysis and maximum likelihood methods for volume- and surface-flaw-induced fracture in ceramics with complete and censored samples. Detailed procedures are given for evaluating 90 percent confidence intervals for maximum likelihood estimates of shape and scale parameters, the unbiased estimates of the shape parameters, and the Weibull mean values and corresponding standard deviations. Furthermore, the necessary steps are described for detecting outliers and for calculating the Kolmogorov-Smirnov and the Anderson-Darling goodness-of-fit statistics and 90 percent confidence bands about the Weibull distribution. It also shows how to calculate the Batdorf flaw-density constants by using the Weibull distribution statistical parameters. The techniques described were verified with several example problems, from the open literature, and were coded in the Structural Ceramics Analysis and Reliability Evaluation (SCARE) design program.

Linked Sensitivity Analysis, Calibration, and Uncertainty Analysis Using a System Dynamics Model for Stroke Comparative Effectiveness Research.

PubMed

Tian, Yuan; Hassmiller Lich, Kristen; Osgood, Nathaniel D; Eom, Kirsten; Matchar, David B

2016-11-01

As health services researchers and decision makers tackle more difficult problems using simulation models, the number of parameters and the corresponding degree of uncertainty have increased. This often results in reduced confidence in such complex models to guide decision making. To demonstrate a systematic approach of linked sensitivity analysis, calibration, and uncertainty analysis to improve confidence in complex models. Four techniques were integrated and applied to a System Dynamics stroke model of US veterans, which was developed to inform systemwide intervention and research planning: Morris method (sensitivity analysis), multistart Powell hill-climbing algorithm and generalized likelihood uncertainty estimation (calibration), and Monte Carlo simulation (uncertainty analysis). Of 60 uncertain parameters, sensitivity analysis identified 29 needing calibration, 7 that did not need calibration but significantly influenced key stroke outcomes, and 24 not influential to calibration or stroke outcomes that were fixed at their best guess values. One thousand alternative well-calibrated baselines were obtained to reflect calibration uncertainty and brought into uncertainty analysis. The initial stroke incidence rate among veterans was identified as the most influential uncertain parameter, for which further data should be collected. That said, accounting for current uncertainty, the analysis of 15 distinct prevention and treatment interventions provided a robust conclusion that hypertension control for all veterans would yield the largest gain in quality-adjusted life years. For complex health care models, a mixed approach was applied to examine the uncertainty surrounding key stroke outcomes and the robustness of conclusions. We demonstrate that this rigorous approach can be practical and advocate for such analysis to promote understanding of the limits of certainty in applying models to current decisions and to guide future data collection. © The Author(s) 2016.

Chasing Perfection: Should We Reduce Model Uncertainty in Carbon Cycle-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Lombardozzi, D.; Wieder, W. R.; Lindsay, K. T.; Thomas, R. Q.

2015-12-01

Earth system model simulations of the terrestrial carbon (C) cycle show large multi-model spread in the carbon-concentration and carbon-climate feedback parameters. Large differences among models are also seen in their simulation of global vegetation and soil C stocks and other aspects of the C cycle, prompting concern about model uncertainty and our ability to faithfully represent fundamental aspects of the terrestrial C cycle in Earth system models. Benchmarking analyses that compare model simulations with common datasets have been proposed as a means to assess model fidelity with observations, and various model-data fusion techniques have been used to reduce model biases. While such efforts will reduce multi-model spread, they may not help reduce uncertainty (and increase confidence) in projections of the C cycle over the twenty-first century. Many ecological and biogeochemical processes represented in Earth system models are poorly understood at both the site scale and across large regions, where biotic and edaphic heterogeneity are important. Our experience with the Community Land Model (CLM) suggests that large uncertainty in the terrestrial C cycle and its feedback with climate change is an inherent property of biological systems. The challenge of representing life in Earth system models, with the rich diversity of lifeforms and complexity of biological systems, may necessitate a multitude of modeling approaches to capture the range of possible outcomes. Such models should encompass a range of plausible model structures. We distinguish between model parameter uncertainty and model structural uncertainty. Focusing on improved parameter estimates may, in fact, limit progress in assessing model structural uncertainty associated with realistically representing biological processes. Moreover, higher confidence may be achieved through better process representation, but this does not necessarily reduce uncertainty.

Comparison of large-scale structures and velocities in the local universe

NASA Technical Reports Server (NTRS)

Yahil, Amos

1994-01-01

Comparison of the large-scale density and velocity fields in the local universe shows detailed agreement, strengthening the standard paradigm of the gravitational origin of these structures. Quantitative analysis can determine the cosmological density parameter, Omega, and biasing factor, b; there is virtually no sensitivity in any local analyses to the cosmologial constant, lambda. Comparison of the dipole anisotropy of the cosmic microwave background with the acceleration due to the Infrared Astronomy Satellite (IRAS) galaxies puts the linear growth factor in the range beta approximately equals Omega (exp 0.6)/b = 0.6(+0.7/-0.3) (95% confidence). A direct comparison of the density and velocity fields of nearby galaxies gives beta = 1.3 (+0.7/-0.6), and from nonlinear analysis the weaker limit (Omega greater than 0.45 for b greater than 0.5 (again 95% confidence). A tighter limit (Omega greater than 0.3 (4-6 sigma)), is obtained by a reconstruction of the probability distribution function of the initial fluctuations from which the structures observed today arose. The last two methods depend critically on the smooth velocity field determined from the observed velocities of nearby galaxies by the POTENT method. A new analysis of these velocities, with more than three times the data used to obtain the above quoted results, is now underway and promises to tighten the uncertainties considerably, as well as reduce systematic bias.

Circannual and circadian rhythms in the concentration of corticosterone in the plasma of the edible frog (Rana esculenta L.).

PubMed

Dupont, W; Bourgeois, P; Reinberg, A; Vaillant, R

1979-01-01

For a period of 21 months between May 1974 and September 1976, circadian variations in the plasma concentration of corticosterone were studied by competitive protein-binding techniques in mature male and female edible frogs living in their natural environment. Blood samples were taken from 8 to 12 frogs six times daily and conventional and cosinor methods were used for statistical analysis. Circadian rhythms were not detected during February and March (time of hibernation). Circannual rhythms were detected in three parameters of the circadian rhythm. The mean concentration of corticosterone over a 24 h period (24 h mean) reached a peak on 1 May (between 15 April and 15 May; 95% limits of confidence); the annual mean value of the 24 h means was 1.97 +/- 0.25 (S.E.M.) microgram/100 ml, with an amplitude of 0.66 microgram/100 ml (0.53--0.79 microgram/100 ml; 95% limits of confidence). Circadian variations in the concentration of corticosterone were largest in May (peak of reproductive activity). The times at which the peak concentration of corticosterone occurred showed circannual variations: peak values were detected around 24.00 h in May, 19.00 h in July and 08.00 h in November. Both circadian and circannual variations have therefore been demonstrated in an endocrine function of an amphibian in its natural habitat.

Transverse micro-erosion meter measurements; determining minimum sample size

NASA Astrophysics Data System (ADS)

Trenhaile, Alan S.; Lakhan, V. Chris

2011-11-01

Two transverse micro-erosion meter (TMEM) stations were installed in each of four rock slabs, a slate/shale, basalt, phyllite/schist, and sandstone. One station was sprayed each day with fresh water and the other with a synthetic sea water solution (salt water). To record changes in surface elevation (usually downwearing but with some swelling), 100 measurements (the pilot survey), the maximum for the TMEM used in this study, were made at each station in February 2010, and then at two-monthly intervals until February 2011. The data were normalized using Box-Cox transformations and analyzed to determine the minimum number of measurements needed to obtain station means that fall within a range of confidence limits of the population means, and the means of the pilot survey. The effect on the confidence limits of reducing an already small number of measurements (say 15 or less) is much greater than that of reducing a much larger number of measurements (say more than 50) by the same amount. There was a tendency for the number of measurements, for the same confidence limits, to increase with the rate of downwearing, although it was also dependent on whether the surface was treated with fresh or salt water. About 10 measurements often provided fairly reasonable estimates of rates of surface change but with fairly high percentage confidence intervals in slowly eroding rocks; however, many more measurements were generally needed to derive means within 10% of the population means. The results were tabulated and graphed to provide an indication of the approximate number of measurements required for given confidence limits, and the confidence limits that might be attained for a given number of measurements.

Detecting Dark Photons with Reactor Neutrino Experiments.

PubMed

Park, H K

2017-08-25

We propose to search for light U(1) dark photons, A^{'}, produced via kinetically mixing with ordinary photons via the Compton-like process, γe^{-}→A^{'}e^{-}, in a nuclear reactor and detected by their interactions with the material in the active volumes of reactor neutrino experiments. We derive 95% confidence-level upper limits on ε, the A^{'}-γ mixing parameter, ε, for dark-photon masses below 1 MeV of ε<1.3×10^{-5} and ε<2.1×10^{-5}, from NEOS and TEXONO experimental data, respectively. This study demonstrates the applicability of nuclear reactors as potential sources of intense fluxes of low-mass dark photons.

A Regions of Confidence Based Approach to Enhance Segmentation with Shape Priors.

PubMed

Appia, Vikram V; Ganapathy, Balaji; Abufadel, Amer; Yezzi, Anthony; Faber, Tracy

2010-01-18

We propose an improved region based segmentation model with shape priors that uses labels of confidence/interest to exclude the influence of certain regions in the image that may not provide useful information for segmentation. These could be regions in the image which are expected to have weak, missing or corrupt edges or they could be regions in the image which the user is not interested in segmenting, but are part of the object being segmented. In the training datasets, along with the manual segmentations we also generate an auxiliary map indicating these regions of low confidence/interest. Since, all the training images are acquired under similar conditions, we can train our algorithm to estimate these regions as well. Based on this training we will generate a map which indicates the regions in the image that are likely to contain no useful information for segmentation. We then use a parametric model to represent the segmenting curve as a combination of shape priors obtained by representing the training data as a collection of signed distance functions. We evolve an objective energy functional to evolve the global parameters that are used to represent the curve. We vary the influence each pixel has on the evolution of these parameters based on the confidence/interest label. When we use these labels to indicate the regions with low confidence; the regions containing accurate edges will have a dominant role in the evolution of the curve and the segmentation in the low confidence regions will be approximated based on the training data. Since our model evolves global parameters, it improves the segmentation even in the regions with accurate edges. This is because we eliminate the influence of the low confidence regions which may mislead the final segmentation. Similarly when we use the labels to indicate the regions which are not of importance, we will get a better segmentation of the object in the regions we are interested in.

The Consequences of Ignoring Item Parameter Drift in Longitudinal Item Response Models

ERIC Educational Resources Information Center

Lee, Wooyeol; Cho, Sun-Joo

2017-01-01

Utilizing a longitudinal item response model, this study investigated the effect of item parameter drift (IPD) on item parameters and person scores via a Monte Carlo study. Item parameter recovery was investigated for various IPD patterns in terms of bias and root mean-square error (RMSE), and percentage of time the 95% confidence interval covered…

The effect of thalidomide on the pharmacokinetics of irinotecan and metabolites in advanced solid tumor patients

PubMed Central

Ramírez, Jacqueline; Wu, Kehua; Janisch, Linda; Karrison, Theodore; House, Larry K.; Innocenti, Federico; Cohen, Ezra E. W.; Ratain, Mark J.

2011-01-01

Purpose Irinotecan and thalidomide are commonly administered antineoplastic drugs. Combination treatment may potentiate their antitumor effect and protect against irinotecan's intestinal toxicity. We investigated whether thalidomide can modulate the pharmacokinetics of irinotecan and metabolites. Methods The study employed a crossover design in which advanced solid tumor patients were randomized to two arms and treated with irinotecan 350 mg/m2 intravenously (IV) every 3 weeks and thalidomide orally (p.o.) 400 mg daily. Pharmacokinetic data when irinotecan was administered as a single agent in each arm were compared to data when the two study agents were co-administered using paired t tests. Eighty percent and 90% confidence intervals for the true difference were also calculated. Results The differences in pharmacokinetic parameters and metabolic markers after thalidomide administration were small and unlikely to be clinically significant. With the exception of APC T1/2, none of the upper confidence limits exceeds a 50% increase. Conclusions This study did not find any clinically meaningful effects of thalidomide on the pharmacokinetics of irinotecan or its metabolites. PMID:21861128

Bifurcation Phenomena of Opinion Dynamics in Complex Networks

NASA Astrophysics Data System (ADS)

Guo, Long; Cai, Xu

In this paper, we study the opinion dynamics of Improved Deffuant model (IDM), where the convergence parameter μ is a function of the opposite’s degree K according to the celebrity effect, in small-world network (SWN) and scale-free network (SFN). Generically, the system undergoes a phase transition from the plurality state to the polarization state and to the consensus state as the confidence parameter ɛ increasing. Furthermore, the evolution of the steady opinion s * as a function of ɛ, and the relation between the minority steady opinion s_{*}^{min} and the individual connectivity k also have been analyzed. Our present work shows the crucial role of the confidence parameter and the complex system topology in the opinion dynamics of IDM.

Large Sample Confidence Limits for Goodman and Kruskal's Proportional Prediction Measure TAU-b

ERIC Educational Resources Information Center

Berry, Kenneth J.; Mielke, Paul W.

1976-01-01

A Fortran Extended program which computes Goodman and Kruskal's Tau-b, its asymmetrical counterpart, Tau-a, and three sets of confidence limits for each coefficient under full multinomial and proportional stratified sampling is presented. A correction of an error in the calculation of the large sample standard error of Tau-b is discussed.…

SENSITIVITY OF NORMAL THEORY METHODS TO MODEL MISSPECIFICATION IN THE CALCULATION OF UPPER CONFIDENCE LIMITS ON THE RISK FUNCTION FOR CONTINUOUS RESPONSES. (R825385)

EPA Science Inventory

Normal theory procedures for calculating upper confidence limits (UCL) on the risk function for continuous responses work well when the data come from a normal distribution. However, if the data come from an alternative distribution, the application of the normal theory procedure...

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

Gaidos, Eric, E-mail: gaidos@hawaii.edu

A key goal of the Kepler mission is the discovery of Earth-size transiting planets in ''habitable zones'' where stellar irradiance maintains a temperate climate on an Earth-like planet. Robust estimates of planet radius and irradiance require accurate stellar parameters, but most Kepler systems are faint, making spectroscopy difficult and prioritization of targets desirable. The parameters of 2035 host stars were estimated by Bayesian analysis and the probabilities p{sub HZ} that 2738 candidate or confirmed planets orbit in the habitable zone were calculated. Dartmouth Stellar Evolution Program models were compared to photometry from the Kepler Input Catalog, priors for stellar mass,more » age, metallicity and distance, and planet transit duration. The analysis yielded probability density functions for calculating confidence intervals of planet radius and stellar irradiance, as well as p{sub HZ}. Sixty-two planets have p{sub HZ} > 0.5 and a most probable stellar irradiance within habitable zone limits. Fourteen of these have radii less than twice the Earth; the objects most resembling Earth in terms of radius and irradiance are KOIs 2626.01 and 3010.01, which orbit late K/M-type dwarf stars. The fraction of Kepler dwarf stars with Earth-size planets in the habitable zone ({eta}{sub Circled-Plus }) is 0.46, with a 95% confidence interval of 0.31-0.64. Parallaxes from the Gaia mission will reduce uncertainties by more than a factor of five and permit definitive assignments of transiting planets to the habitable zones of Kepler stars.« less

Metastases to the Liver from Neuroendocrine Tumors: Effect of Duration of Scan Acquisition on CT Perfusion Values

PubMed Central

Hobbs, Brian P.; Chandler, Adam G.; Anderson, Ella F.; Herron, Delise H.; Charnsangavej, Chusilp; Yao, James

2013-01-01

Purpose To assess the effects of acquisition duration on computed tomographic (CT) perfusion parameter values in neuroendocrine liver metastases and normal liver tissue. Materials and Methods This retrospective study was institutional review board approved, with waiver of informed consent. CT perfusion studies in 16 patients (median age, 57.5 years; range, 42.0–69.7 years), including six men (median, 54.1 years; range, 42.0–69.7), and 10 women (median, 59.3 years; range 43.6–66.3), with neuroendocrine liver metastases were analyzed by means of distributed parametric modeling to determine tissue blood flow, blood volume, mean transit time, permeability, and hepatic arterial fraction for tumors and normal liver tissue. Analyses were undertaken with acquisition time of 12–590 seconds. Nonparameteric regression analyses were used to evaluate the functional relationships between CT perfusion parameters and acquisition duration. Evidence for time invariance was evaluated for each parameter at multiple time points by inferring the fitted derivative to assess its proximity to zero as a function of acquisition time by using equivalence tests with three levels of confidence (20%, 70%, and 90%). Results CT perfusion parameter values varied, approaching stable values with increasing acquisition duration. Acquisition duration greater than 160 seconds was required to obtain at least low confidence stability in any of the CT perfusion parameters. At 160 seconds of acquisition, all five CT perfusion parameters stabilized with low confidence in tumor and normal tissues, with the exception of hepatic arterial fraction in tumors. After 220 seconds of acquisition, there was stabilization with moderate confidence for blood flow, blood volume, and hepatic arterial fraction in tumors and normal tissue, and for mean transit time in tumors; however, permeability values did not satisfy the moderate stabilization criteria in both tumors and normal tissue until 360 seconds of acquisition. Blood flow, mean transit time, permeability, and hepatic arterial fraction were significantly different between tumor and normal tissue at 360 seconds (P < .001). Conclusion CT perfusion parameter values are affected by acquisition duration and approach progressively stable values with increasing acquisition times. © RSNA, 2013 Online supplemental material is available for this article. PMID:23824990

Standard Errors and Confidence Intervals from Bootstrapping for Ramsay-Curve Item Response Theory Model Item Parameters

ERIC Educational Resources Information Center

Gu, Fei; Skorupski, William P.; Hoyle, Larry; Kingston, Neal M.

2011-01-01

Ramsay-curve item response theory (RC-IRT) is a nonparametric procedure that estimates the latent trait using splines, and no distributional assumption about the latent trait is required. For item parameters of the two-parameter logistic (2-PL), three-parameter logistic (3-PL), and polytomous IRT models, RC-IRT can provide more accurate estimates…

A simple method for assessing occupational exposure via the one-way random effects model.

PubMed

Krishnamoorthy, K; Mathew, Thomas; Peng, Jie

2016-11-01

A one-way random effects model is postulated for the log-transformed shift-long personal exposure measurements, where the random effect in the model represents an effect due to the worker. Simple closed-form confidence intervals are proposed for the relevant parameters of interest using the method of variance estimates recovery (MOVER). The performance of the confidence bounds is evaluated and compared with those based on the generalized confidence interval approach. Comparison studies indicate that the proposed MOVER confidence bounds are better than the generalized confidence bounds for the overall mean exposure and an upper percentile of the exposure distribution. The proposed methods are illustrated using a few examples involving industrial hygiene data.

FAST: Fitting and Assessment of Synthetic Templates

NASA Astrophysics Data System (ADS)

Kriek, Mariska; van Dokkum, Pieter G.; Labbé, Ivo; Franx, Marijn; Illingworth, Garth D.; Marchesini, Danilo; Quadri, Ryan F.; Aird, James; Coil, Alison L.; Georgakakis, Antonis

2018-03-01

FAST (Fitting and Assessment of Synthetic Templates) fits stellar population synthesis templates to broadband photometry and/or spectra. FAST is compatible with the photometric redshift code EAzY (ascl:1010.052) when fitting broadband photometry; it uses the photometric redshifts derived by EAzY, and the input files (for examply, photometric catalog and master filter file) are the same. FAST fits spectra in combination with broadband photometric data points or simultaneously fits two components, allowing for an AGN contribution in addition to the host galaxy light. Depending on the input parameters, FAST outputs the best-fit redshift, age, dust content, star formation timescale, metallicity, stellar mass, star formation rate (SFR), and their confidence intervals. Though some of FAST's functions overlap with those of HYPERZ (ascl:1108.010), it differs by fitting fluxes instead of magnitudes, allows the user to completely define the grid of input stellar population parameters and easily input photometric redshifts and their confidence intervals, and calculates calibrated confidence intervals for all parameters. Note that FAST is not a photometric redshift code, though it can be used as one.

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

PubMed

Piehowski, Paul D; Petyuk, Vladislav A; Sandoval, John D; Burnum, Kristin E; Kiebel, Gary R; Monroe, Matthew E; Anderson, Gordon A; Camp, David G; Smith, Richard D

2013-03-01

For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection--referred to as STEPS--utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true-positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Parameter optimization of parenchymal texture analysis for prediction of false-positive recalls from screening mammography

NASA Astrophysics Data System (ADS)

Ray, Shonket; Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina

2016-03-01

This work details a methodology to obtain optimal parameter values for a locally-adaptive texture analysis algorithm that extracts mammographic texture features representative of breast parenchymal complexity for predicting falsepositive (FP) recalls from breast cancer screening with digital mammography. The algorithm has two components: (1) adaptive selection of localized regions of interest (ROIs) and (2) Haralick texture feature extraction via Gray- Level Co-Occurrence Matrices (GLCM). The following parameters were systematically varied: mammographic views used, upper limit of the ROI window size used for adaptive ROI selection, GLCM distance offsets, and gray levels (binning) used for feature extraction. Each iteration per parameter set had logistic regression with stepwise feature selection performed on a clinical screening cohort of 474 non-recalled women and 68 FP recalled women; FP recall prediction was evaluated using area under the curve (AUC) of the receiver operating characteristic (ROC) and associations between the extracted features and FP recall were assessed via odds ratios (OR). A default instance of mediolateral (MLO) view, upper ROI size limit of 143.36 mm (2048 pixels2), GLCM distance offset combination range of 0.07 to 0.84 mm (1 to 12 pixels) and 16 GLCM gray levels was set. The highest ROC performance value of AUC=0.77 [95% confidence intervals: 0.71-0.83] was obtained at three specific instances: the default instance, upper ROI window equal to 17.92 mm (256 pixels2), and gray levels set to 128. The texture feature of sum average was chosen as a statistically significant (p<0.05) predictor and associated with higher odds of FP recall for 12 out of 14 total instances.

Calculation of Weibull strength parameters and Batdorf flow-density constants for volume- and surface-flaw-induced fracture in ceramics

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Gyekenyesi, John P.

1988-01-01

The calculation of shape and scale parameters of the two-parameter Weibull distribution is described using the least-squares analysis and maximum likelihood methods for volume- and surface-flaw-induced fracture in ceramics with complete and censored samples. Detailed procedures are given for evaluating 90 percent confidence intervals for maximum likelihood estimates of shape and scale parameters, the unbiased estimates of the shape parameters, and the Weibull mean values and corresponding standard deviations. Furthermore, the necessary steps are described for detecting outliers and for calculating the Kolmogorov-Smirnov and the Anderson-Darling goodness-of-fit statistics and 90 percent confidence bands about the Weibull distribution. It also shows how to calculate the Batdorf flaw-density constants by uing the Weibull distribution statistical parameters. The techniques described were verified with several example problems, from the open literature, and were coded. The techniques described were verified with several example problems from the open literature, and were coded in the Structural Ceramics Analysis and Reliability Evaluation (SCARE) design program.

Search for Excited or Exotic Electron Production Using the Dielectron + Photon Signature at CDF in Run II

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

Gerberich, Heather Kay

The author presents a search for excited or exotic electrons decaying to an electron and a photon with high transverse momentum. An oppositely charged electron is produced in association with the excited electron, yielding a final state dielectron + photon signature. The discovery of excited electrons would be a first indication of lepton compositeness. They use ~ 202 pb -1 of data collected in pmore » $$\\bar{p}$$ collisions at √s = 1.96 TeV with the Collider Detector at Fermilab during March 2001 through September 2003. The data are consistent with standard model expectations. Upper limits are set on the experimental cross-section σ($$\\bar{p}$$p → ee* → eeγ) at the 95% confidence level in a contact-interaction model and a gauge-mediated interaction model. Limits are also presented as exclusion regions in the parameter space of the excited electron mass (M e*) and the compositeness energy scale (Λ). In the contact-interaction model, for which there are no previously published limits, they find M e* < 906 GeV is excluded for M e* = Λ. In the gauge-mediated model, the exclusion region in the M e* versus the phenomenological coupling f/Λ parameter space is extended to M{sub e*} < 430 GeV for f/Λ ~ 10 -2 GeV -1. In comparison, other experiments have excluded M e* < 280 GeV for f/Λ ~ 10 -2 GeV -1.« less

Measurements of E-mode polarization and temperature-E-mode correlation in the cosmic microwave background from 100 square degrees of SPTPOL data

DOE PAGES

Crites, A. T.; Henning, J. W.; Ade, P. A. R.; ...

2015-05-18

Here, we present measurements ofmore » $E$-mode polarization and temperature-$E$$-mode correlation in the cosmic microwave background (CMB) using data from the first season of observations with SPTpol, the polarization-sensitive receiver currently installed on the South Pole Telescope (SPT). The observations used in this work cover 100~\\sqdeg\\ of sky with arcminute resolution at $$150\\,$GHz. We also report the $E$-mode angular auto-power spectrum ($EE$) and the temperature-$E$-mode angular cross-power spectrum ($TE$) over the multipole range $$500 < \\ell \\leq5000$$. These power spectra improve on previous measurements in the high-$$\\ell$$ (small-scale) regime. We fit the combination of the SPTpol power spectra, data from \\planck\\, and previous SPT measurements with a six-parameter \\LCDM cosmological model. Furthermore, we find that the best-fit parameters are consistent with previous results. The improvement in high-$$\\ell$$ sensitivity over previous measurements leads to a significant improvement in the limit on polarized point-source power: after masking sources brighter than 50\\,mJy in unpolarized flux at 150\\,GHz, we find a 95\\% confidence upper limit on unclustered point-source power in the $EE$ spectrum of $$D_\\ell = \\ell (\\ell+1) C_\\ell / 2 \\pi < 0.40 \\ \\mu{\\mbox{K}}^2$$ at $$\\ell=3000$$, indicating that future $EE$ measurements will not be limited by power from unclustered point sources in the multipole range $$\\ell < 3600$$, and possibly much higher in $$\\ell.$$« less

Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods

ERIC Educational Resources Information Center

MacKinnon, David P.; Lockwood, Chondra M.; Williams, Jason

2004-01-01

The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal…

Confidence limits for contribution plots in multivariate statistical process control using bootstrap estimates.

PubMed

Babamoradi, Hamid; van den Berg, Frans; Rinnan, Åsmund

2016-02-18

In Multivariate Statistical Process Control, when a fault is expected or detected in the process, contribution plots are essential for operators and optimization engineers in identifying those process variables that were affected by or might be the cause of the fault. The traditional way of interpreting a contribution plot is to examine the largest contributing process variables as the most probable faulty ones. This might result in false readings purely due to the differences in natural variation, measurement uncertainties, etc. It is more reasonable to compare variable contributions for new process runs with historical results achieved under Normal Operating Conditions, where confidence limits for contribution plots estimated from training data are used to judge new production runs. Asymptotic methods cannot provide confidence limits for contribution plots, leaving re-sampling methods as the only option. We suggest bootstrap re-sampling to build confidence limits for all contribution plots in online PCA-based MSPC. The new strategy to estimate CLs is compared to the previously reported CLs for contribution plots. An industrial batch process dataset was used to illustrate the concepts. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of Free-Breathing With Navigator-Triggered Technique in Diffusion Weighted Imaging for Evaluation of Small Hepatocellular Carcinoma: Effect on Image Quality and Intravoxel Incoherent Motion Parameters.

PubMed

Shan, Yan; Zeng, Meng-su; Liu, Kai; Miao, Xi-Yin; Lin, Jiang; Fu, Cai xia; Xu, Peng-ju

2015-01-01

To evaluate the effect on image quality and intravoxel incoherent motion (IVIM) parameters of small hepatocellular carcinoma (HCC) from choice of either free-breathing (FB) or navigator-triggered (NT) diffusion-weighted (DW) imaging. Thirty patients with 37 small HCCs underwent IVIM DW imaging using 12 b values (0-800 s/mm) with 2 sequences: NT, FB. A biexponential analysis with the Bayesian method yielded true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) in small HCCs and liver parenchyma. Apparent diffusion coefficient (ADC) was also calculated. The acquisition time and image quality scores were assessed for 2 sequences. Independent sample t test was used to compare image quality, signal intensity ratio, IVIM parameters, and ADC values between the 2 sequences; reproducibility of IVIM parameters, and ADC values between 2 sequences was assessed with the Bland-Altman method (BA-LA). Image quality with NT sequence was superior to that with FB acquisition (P = 0.02). The mean acquisition time for FB scheme was shorter than that of NT sequence (6 minutes 14 seconds vs 10 minutes 21 seconds ± 10 seconds P < 0.01). The signal intensity ratio of small HCCs did not vary significantly between the 2 sequences. The ADC and IVIM parameters from the 2 sequences show no significant difference. Reproducibility of D*and f parameters in small HCC was poor (BA-LA: 95% confidence interval, -180.8% to 189.2% for D* and -133.8% to 174.9% for f). A moderate reproducibility of D and ADC parameters was observed (BA-LA: 95% confidence interval, -83.5% to 76.8% for D and -74.4% to 88.2% for ADC) between the 2 sequences. The NT DW imaging technique offers no advantage in IVIM parameters measurements of small HCC except better image quality, whereas FB technique offers greater confidence in fitted diffusion parameters for matched acquisition periods.

Constraining models of f(R) gravity with Planck and WiggleZ power spectrum data

NASA Astrophysics Data System (ADS)

Dossett, Jason; Hu, Bin; Parkinson, David

2014-03-01

In order to explain cosmic acceleration without invoking ``dark'' physics, we consider f(R) modified gravity models, which replace the standard Einstein-Hilbert action in General Relativity with a higher derivative theory. We use data from the WiggleZ Dark Energy survey to probe the formation of structure on large scales which can place tight constraints on these models. We combine the large-scale structure data with measurements of the cosmic microwave background from the Planck surveyor. After parameterizing the modification of the action using the Compton wavelength parameter B0, we constrain this parameter using ISiTGR, assuming an initial non-informative log prior probability distribution of this cross-over scale. We find that the addition of the WiggleZ power spectrum provides the tightest constraints to date on B0 by an order of magnitude, giving log10(B0) < -4.07 at 95% confidence limit. Finally, we test whether the effect of adding the lensing amplitude ALens and the sum of the neutrino mass ∑mν is able to reconcile current tensions present in these parameters, but find f(R) gravity an inadequate explanation.

Differences in residents' self-reported confidence and case experience between two post-graduate rotation curricula: results of a nationwide survey in Japan.

PubMed

Ohde, Sachiko; Deshpande, Gautam A; Takahashi, Osamu; Fukui, Tsuguya

2014-07-12

In Japan, all trainee physicians must begin clinical practice in a standardized, mandatory junior residency program, which encompasses the first two years of post-graduate medical training (PGY1 - PGY2). Implemented in 2004 to foster primary care skills, the comprehensive rotation program (CRP) requires junior residents to spend 14 months rotating through a comprehensive array of clinical departments including internal medicine, surgery, anesthesiology, obstetrics-gynecology (OBGYN), pediatrics, psychiatry, and rural medicine. In 2010, Japan's health ministry relaxed this curricular requirement, allowing training programs to offer a limited rotation program (LRP), in which core departments constitute 10 months of training, with electives geared towards residents' choice of career specialty comprising the remaining 14 months. The effectiveness of primary care skill acquisition during early training warrants evaluation. This study assesses self-reported confidence with clinical competencies, as well as case experience, between residents in CRP versus LRP curricula. A nation-wide cross-sectional study of all PGY2 physicians in Japan was conducted in March 2011. Primary outcomes were self-report confidence for 98 clinical competency items, and number of cases experienced for 85 common diseases. We compared confidence scores and case experience between residents in CRP and LRP programs, adjusting for parameters relevant to training. Among 7506 PGY2 residents, 5052 replied to the survey (67.3%). Of 98 clinical competency items, CRP residents reported higher confidence in 12 items compared to those in an LRP curriculum, 10 of which remained significantly higher after adjustment. CRP trainees reported lower confidence scores in none of the items. Out of 85 diseases, LRP residents reported less experience with 11 diseases. CRP trainees reported lower case experience with one disease, though this did not remain significant on adjusted analysis. Confidence and case experience with OBGYN- and pediatrics-related items were particularly low among LRP trainees. Residents in the specialty-oriented LRP curriculum showed less confidence and less case experience compared to peers training in the broader CRP residency curriculum. In order to foster competence in independent primary care practice, junior residency programs requiring experience in a breadth of core departments should continue to be mandated to ensure adequate primary care skills.

Search for diphoton events with large missing transverse momentum in 1 fb(-1) of 7 TeV proton-proton collision data with the ATLAS detector

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

Aad G.; Abbott B.; Abdallah J.

2012-04-20

A search for diphoton events with large missing transverse momentum has been performed using 1.07 fb{sup -1} of proton-proton collision data at {radical}s = 7 TeV recorded with the ATLAS detector. No excess of events was observed above the Standard Model prediction and 95% Confidence Level (CL) upper limits are set on the production cross section for new physics. The limits depend on each model parameter space and vary as follows: {sigma} < (22-129) fb in the context of a generalized model of gauge-mediated supersymmetry breaking (GGM) with a bino-like lightest neutralino, {sigma} < (27-91) fb in the context ofmore » a minimal model of gauge-mediated supersymmetry breaking (SPS8), and {sigma} < (15-27) fb in the context of a specific model with one universal extra dimension (UED). A 95% CL lower limit of 805 GeV, for bino masses above 50 GeV, is set on the GGM gluino mass. Lower limits of 145 TeV and 1.23 TeV are set on the SPS8 breaking scale {Lambda} and on the UED compactification scale 1/R, respectively. These limits provide the most stringent tests of these models to date.« less

Search for diphoton events with large missing transverse momentum in 1 fb - 1 of 7 TeV proton–proton collision data with the ATLAS detector

DOE PAGES

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

2012-02-22

A search for diphoton events with large missing transverse momentum has been performed using 1.07fb -1 of proton–proton collision data at s=7TeV recorded with the ATLAS detector. No excess of events was observed above the Standard Model prediction and 95% Confidence Level (CL) upper limits are set on the production cross section for new physics. The limits depend on each model parameter space and vary as follows: σ<(22–129)fb in the context of a generalised model of gauge-mediated supersymmetry breaking (GGM) with a bino-like lightest neutralino, σ<(27–91)fb in the context of a minimal model of gauge-mediated supersymmetry breaking (SPS8), and σ<(15–27)fbmore » in the context of a specific model with one universal extra dimension (UED). A 95% CL lower limit of 805GeV, for bino masses above 50 GeV, is set on the GGM gluino mass. Lower limits of 145TeV and 1.23TeV are set on the SPS8 breaking scale Λ and on the UED compactification scale 1/R, respectively. These limits provide the most stringent tests of these models to date.« less

Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Wagler, Amy E.

2014-01-01

Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…

Assessment of NDE reliability data

NASA Technical Reports Server (NTRS)

Yee, B. G. W.; Couchman, J. C.; Chang, F. H.; Packman, D. F.

1975-01-01

Twenty sets of relevant nondestructive test (NDT) reliability data were identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations was formulated, and a model to grade the quality and validity of the data sets was developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, were formulated for each NDE method. A comprehensive computer program was written and debugged to calculate the probability of flaw detection at several confidence limits by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. An example of the calculated reliability of crack detection in bolt holes by an automatic eddy current method is presented.

On-Call Communication in Orthopaedic Trauma: "A Picture Is Worth a Thousand Words"--A Survey of OTA Members.

PubMed

Molina, Cesar S; Callan, Alexandra K; Burgos, Eduardo J; Mir, Hassan R

2015-05-01

To quantify the effects of varying clinical communication styles (verbal and pictorial) on the ability of orthopaedic trauma surgeons in understanding an injury and formulate an initial management plan. A Research Electronic Data Capture survey was e-mailed to all OTA members. Respondents quantified (5-point Likert scale) how confident they felt understanding an injury and establishing an initial management plan based on the information provided for 5 common orthopaedic trauma scenarios. Three verbal descriptions were created for each scenario and categorized as limited, moderate, or detailed. The questions were repeated with the addition of a radiographic image and then repeated a third time including a clinical photograph. Statistical evaluation consisted of descriptive statistics and Kruskal-Wallis analyses using STATA (version 12.0). Of the 221 respondents, there were a total of 95 who completed the entire survey. Nearly all were currently taking call (92/95 = 96.8%) and the majority were fellowship trained (79/95 = 83.2%). Most practice at a level I trauma center (58/95 = 61.1%) and work with orthopaedic residents (62/95 = 65.3%). There was a significant increase in confidence scores between a limited, moderate, and detailed description in all clinical scenarios for understanding the injury and establishing an initial management plan (P < 0.05). There was a significant difference in confidence scores between all 3 types of evidence presented (verbal, verbal + x-ray, verbal + x-ray + photograph) in both understanding and managing the injury for limited and moderate descriptions (P < 0.001). No differences were seen when adding pictorial information to the detailed verbal description. When comparing confidence scores between a detailed description without images and a limited description that includes radiographs and a photograph, no difference in confidence levels was seen in 7 of the 10 scenarios (P > 0.05). The addition of images in the form of radiographs and/or clinical photographs greatly improves the confidence of orthopaedic trauma surgeons in understanding injuries and establishing initial management plans with limited verbal information (P < 0.001). The inclusion of x-rays and photographs raises the confidence for understanding and management with limited verbal information to the level of a detailed verbal description in most scenarios. Mobile technology allows for easy secure transfer of images that can make up for the lack of available information from limited verbal descriptions because of the knowledge base of communicating providers.

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

NASA Technical Reports Server (NTRS)

Peterson, L. E.; Cucinotta, F. A.; Wilson, J. W. (Principal Investigator)

1999-01-01

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.

Opening a Window to Foster Children's Self-Confidence through Creative Art Activities

ERIC Educational Resources Information Center

Kim, Kyoung Jin; Wee, Su-Jeong; Gilbert, Beverly Boals

2017-01-01

Among various benefits of art for young children, this article highlights the emotional development aspect, specifically boosting self-confidence through art activities. The definition of self-confidence as having trust in one's self, clear knowledge of one's strengths and limitations, and assurance of one's ability to handle a variety of…

A proposal of the diagnosis-dynamic characteristic (DDC) model describing the relation between search time and confidence levels for a dichotomous judgment, and its application to ROC curve generation

NASA Astrophysics Data System (ADS)

Matsumoto, Toru; Fukuda, Nobuo; Furukawa, Akira; Suwa, Koji; Wada, Shinichi; Matsumoto, Mitsuomi; Sone, Shusuke

2006-03-01

When physicians inspect an image, they make up a certain degree of confidence that the image are abnormal; p(t), or normal; n(t)[n(t)=1-p(t)]. After infinite time of the inspection, they reach the equilibrium levels of the confidence of p*=p(∞) and n*=n(∞). There are psychological conflicts between the decisions of normal and abnormal. We assume that the decision of "normal" is distracted by the decision of "abnormal" by a factor of k(1 + ap), and in an inverse direction by a factor of k(1 + bn), where k ( > 0) is a parameter that relates with image quality and skill of the physicians, and a and b are unknown constants. After the infinite time of inspection, the conflict reaches the equilibrium, which satisfies the equation, k(1 + ap*)n* = k(1 + bn*)p*. Here we define a parameter C, which is 2p*/[p*(1 - p*)]. After the infinite time of inspection, the conflict reaches the equilibrium, which satisfies t that changes in the confidence level with the time (dp/dt) is proportional to [k(1+ap)n - k(1+bn)p], i.e. k[-cp2 + (c - 2)p + 1]. Solving the differential equation, we derived the equation; t(p) and p(t) depending with the parameters; k, c, S. S (0-1) is the value arbitrary selected and related with probability of "abnormal" before the image inspection (S = p(0)). Image reading studies were executed for CT images. ROC curves were generated both by the traditional 4-step score-based method and by the confidence level; p estimated from the equation t(p) of the DDC model using observed judgment time. It was concluded that ROC curves could be generated by measuring time for dichotomous judgment without the subjective scores of diagnostic confidence and applying the DDC model.

A Probabilistic Approach to Quantify the Impact of Uncertainty Propagation in Musculoskeletal Simulations

PubMed Central

Myers, Casey A.; Laz, Peter J.; Shelburne, Kevin B.; Davidson, Bradley S.

2015-01-01

Uncertainty that arises from measurement error and parameter estimation can significantly affect the interpretation of musculoskeletal simulations; however, these effects are rarely addressed. The objective of this study was to develop an open-source probabilistic musculoskeletal modeling framework to assess how measurement error and parameter uncertainty propagate through a gait simulation. A baseline gait simulation was performed for a male subject using OpenSim for three stages: inverse kinematics, inverse dynamics, and muscle force prediction. A series of Monte Carlo simulations were performed that considered intrarater variability in marker placement, movement artifacts in each phase of gait, variability in body segment parameters, and variability in muscle parameters calculated from cadaveric investigations. Propagation of uncertainty was performed by also using the output distributions from one stage as input distributions to subsequent stages. Confidence bounds (5–95%) and sensitivity of outputs to model input parameters were calculated throughout the gait cycle. The combined impact of uncertainty resulted in mean bounds that ranged from 2.7° to 6.4° in joint kinematics, 2.7 to 8.1 N m in joint moments, and 35.8 to 130.8 N in muscle forces. The impact of movement artifact was 1.8 times larger than any other propagated source. Sensitivity to specific body segment parameters and muscle parameters were linked to where in the gait cycle they were calculated. We anticipate that through the increased use of probabilistic tools, researchers will better understand the strengths and limitations of their musculoskeletal simulations and more effectively use simulations to evaluate hypotheses and inform clinical decisions. PMID:25404535

Confidence intervals for the population mean tailored to small sample sizes, with applications to survey sampling.

PubMed

Rosenblum, Michael A; Laan, Mark J van der

2009-01-07

The validity of standard confidence intervals constructed in survey sampling is based on the central limit theorem. For small sample sizes, the central limit theorem may give a poor approximation, resulting in confidence intervals that are misleading. We discuss this issue and propose methods for constructing confidence intervals for the population mean tailored to small sample sizes. We present a simple approach for constructing confidence intervals for the population mean based on tail bounds for the sample mean that are correct for all sample sizes. Bernstein's inequality provides one such tail bound. The resulting confidence intervals have guaranteed coverage probability under much weaker assumptions than are required for standard methods. A drawback of this approach, as we show, is that these confidence intervals are often quite wide. In response to this, we present a method for constructing much narrower confidence intervals, which are better suited for practical applications, and that are still more robust than confidence intervals based on standard methods, when dealing with small sample sizes. We show how to extend our approaches to much more general estimation problems than estimating the sample mean. We describe how these methods can be used to obtain more reliable confidence intervals in survey sampling. As a concrete example, we construct confidence intervals using our methods for the number of violent deaths between March 2003 and July 2006 in Iraq, based on data from the study "Mortality after the 2003 invasion of Iraq: A cross sectional cluster sample survey," by Burnham et al. (2006).

Investigation of fluorine content in PM2.5 airborne particles of Istanbul, Turkey.

PubMed

Ozbek, Nil; Baltaci, Hakki; Baysal, Asli

2016-07-01

Fluorine determination in airborne samples is important due to its spread into the air from both natural and artificial sources. It can travel by wind over large distances before depositing on the Earth's surface. Its concentration in various matrices are limited and controlled by the regulations for causing health risks associated with environmental exposures. In this work, fluorine was determined in PM2.5 airborne samples by high-resolution continuum source electrothermal atomic absorption spectrometry. For these purpose, the PM2.5 airborne particulates were collected on quartz filters using high-volume samplers (500 L/min) in Istanbul (Turkey) for 96 h during January to June in 2 years. Then, instrumental and experimental parameters were optimized for the analyte in airborne samples. The validity of the method for the analyte was tested using standard reference material, and certified values were found in the limits of 95 % confidence level. The fluorine concentrations and meteorological conditions were compared statistically.

Astrophysical constraints on resonantly produced sterile neutrino dark matter

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

Schneider, Aurel, E-mail: aurel@physik.uzh.ch

2016-04-01

Resonantly produced sterile neutrinos are considered an attractive dark matter (DM) candidate only requiring a minimal, well motivated extension to the standard model of particle physics. With a particle mass restricted to the keV range, sterile neutrinos are furthermore a prime candidate for warm DM, characterised by suppressed matter perturbations at the smallest observable scales. In this paper we take a critical look at the validity of the resonant scenario in the context of constraints from structure formation. We compare predicted and observed number of Milky-Way satellites and we introduce a new method to generalise existing Lyman-α limits based onmore » thermal relic warm DM to the case of resonant sterile neutrino DM . The tightest limits come from the Lyman-α analysis, excluding the entire parameter space (at 2-σ confidence level) still allowed by X-ray observations. Constraints from Milky-Way satellite counts are less stringent, leaving room for resonant sterile neutrino DM most notably around the suggested line signal at 7.1 keV.« less

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

Darling, Christopher Lynn

By determining the production cross sections for heavy flavor hadrons, we test the theoretical predictions from perturhative quantum chroma-dynamics (QCD). In the case of pion induced beauty production, the few published results do not resolve the issue of the applicability of perturbative QCD. This analysis is undertaken in order to help resolve this situation. We determine the total beauty and charm production cross sections using an analysis of single electron decay products. We extract the cross sections per nucleon from the two-dimensional distribution of electron p versus impact parameter ( d) to the primary vertex. We place an upper limit on the beauty production cross section of σ bmore » $$\\bar{b}$$ < 105 nb at the 90% confidence level, where the limit includes both statistical and systematic errors. The charm production cross section is determined to be σ cc = 13.9$$+2.4/atop{-2.3}$$ (stat) ± 1.8 (syst) μ.b, which is in good agreement with next-to-leading order QCD predictions and other measurements.« less

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

Darling, Christopher Lynn

By determining the production cross sections for heavy flavor hadrons, we test the theoretical predictions from perturhative quantum chroma-dynamics (QCD). In the case of pion induced beauty production, the few published results do not resolve the issue of the applicability of perturbative QCD. This analysis is undertaken in order to help resolve this situation. We determine the total beauty and charm production cross sections using an analysis of single electron decay products. We extract the cross sections per nucleon from the two-dimensional distribution of electronmore » $$p^2_{\\tau}$$ versus impact parameter (d) to the primary vertex. We place an upper limit on the beauty production cross section of $$\\sigma_{b\\overline{b}}$$ < 105 nb at the 90% confidence level, where the limit includes both statistical and systematic errors. The charm production cross section is determined to be $$\\sigma_{c\\overline{c}} = 13.9 ^{+2.4}_{-2.3}$$(stat)±l.8(syst) $$\\mu b$$, which is in good agreement with next-to-leading order QCD predictions and other measurements.« less

Search for Invisible Decays of a Dark Photon Produced in e^{+}e^{-} Collisions at BaBar.

PubMed

Lees, J P; Poireau, V; Tisserand, V; Grauges, E; Palano, A; Eigen, G; Brown, D N; Derdzinski, M; Giuffrida, A; Kolomensky, Yu G; Fritsch, M; Koch, H; Schroeder, T; Hearty, C; Mattison, T S; McKenna, J A; So, R Y; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Lankford, A J; Gary, J W; Long, O; Eisner, A M; Lockman, W S; Panduro Vazquez, W; Chao, D S; Cheng, C H; Echenard, B; Flood, K T; Hitlin, D G; Kim, J; Miyashita, T S; Ongmongkolkul, P; Porter, F C; Röhrken, M; Huard, Z; Meadows, B T; Pushpawela, B G; Sokoloff, M D; Sun, L; Smith, J G; Wagner, S R; Bernard, D; Verderi, M; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Fioravanti, E; Garzia, I; Luppi, E; Santoro, V; Calcaterra, A; de Sangro, R; Finocchiaro, G; Martellotti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rotondo, M; Zallo, A; Passaggio, S; Patrignani, C; Lacker, H M; Bhuyan, B; Mallik, U; Chen, C; Cochran, J; Prell, S; Ahmed, H; Gritsan, A V; Arnaud, N; Davier, M; Le Diberder, F; Lutz, A M; Wormser, G; Lange, D J; Wright, D M; Coleman, J P; Gabathuler, E; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Cowan, G; Banerjee, Sw; Brown, D N; Davis, C L; Denig, A G; Gradl, W; Griessinger, K; Hafner, A; Schubert, K R; Barlow, R J; Lafferty, G D; Cenci, R; Jawahery, A; Roberts, D A; Cowan, R; Robertson, S H; Dey, B; Neri, N; Palombo, F; Cheaib, R; Cremaldi, L; Godang, R; Summers, D J; Taras, P; De Nardo, G; Sciacca, C; Raven, G; Jessop, C P; LoSecco, J M; Honscheid, K; Kass, R; Gaz, A; Margoni, M; Posocco, M; Simi, G; Simonetto, F; Stroili, R; Akar, S; Ben-Haim, E; Bomben, M; Bonneaud, G R; Calderini, G; Chauveau, J; Marchiori, G; Ocariz, J; Biasini, M; Manoni, E; Rossi, A; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Chrzaszcz, M; Forti, F; Giorgi, M A; Lusiani, A; Oberhof, B; Paoloni, E; Rama, M; Rizzo, G; Walsh, J J; Smith, A J S; Anulli, F; Faccini, R; Ferrarotto, F; Ferroni, F; Pilloni, A; Piredda, G; Bünger, C; Dittrich, S; Grünberg, O; Heß, M; Leddig, T; Voß, C; Waldi, R; Adye, T; Wilson, F F; Emery, S; Vasseur, G; Aston, D; Cartaro, C; Convery, M R; Dorfan, J; Dunwoodie, W; Ebert, M; Field, R C; Fulsom, B G; Graham, M T; Hast, C; Innes, W R; Kim, P; Leith, D W G S; Luitz, S; MacFarlane, D B; Muller, D R; Neal, H; Ratcliff, B N; Roodman, A; Sullivan, M K; Va'vra, J; Wisniewski, W J; Purohit, M V; Wilson, J R; Randle-Conde, A; Sekula, S J; Bellis, M; Burchat, P R; Puccio, E M T; Alam, M S; Ernst, J A; Gorodeisky, R; Guttman, N; Peimer, D R; Soffer, A; Spanier, S M; Ritchie, J L; Schwitters, R F; Izen, J M; Lou, X C; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Lanceri, L; Vitale, L; Martinez-Vidal, F; Oyanguren, A; Albert, J; Beaulieu, A; Bernlochner, F U; King, G J; Kowalewski, R; Lueck, T; Nugent, I M; Roney, J M; Sobie, R J; Tasneem, N; Gershon, T J; Harrison, P F; Latham, T E; Prepost, R; Wu, S L

2017-09-29

We search for single-photon events in 53  fb^{-1} of e^{+}e^{-} collision data collected with the BABAR detector at the PEP-II B-Factory. We look for events with a single high-energy photon and a large missing momentum and energy, consistent with production of a spin-1 particle A^{'} through the process e^{+}e^{-}→γA^{'}; A^{'}→invisible. Such particles, referred to as "dark photons," are motivated by theories applying a U(1) gauge symmetry to dark matter. We find no evidence for such processes and set 90% confidence level upper limits on the coupling strength of A^{'} to e^{+}e^{-} in the mass range m_{A^{'}}≤8  GeV. In particular, our limits exclude the values of the A^{'} coupling suggested by the dark-photon interpretation of the muon (g-2)_{μ} anomaly, as well as a broad range of parameters for the dark-sector models.

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

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

A search for squarks and gluinos in final states containing hadronic jets, missing transverse momentum but no electrons or muons is presented. The data were recorded in 2015 by the ATLAS experiment in √s=13 TeV proton–proton collisions at the Large Hadron Collider. No excess above the Standard Model background expectation was observed in 3.2 fb -1 of analyzed data. Results are interpreted within simplified models that assume R-parity is conserved and the neutralino is the lightest supersymmetric particle. An exclusion limit at the 95 % confidence level on the mass of the gluino is set at 1.51 TeV for amore » simplified model incorporating only a gluino octet and the lightest neutralino, assuming the lightest neutralino is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.03 TeV are excluded for a massless lightest neutralino. Finally, these limits substantially extend the region of supersymmetric parameter space excluded by previous measurements with the ATLAS detector.« less

Rigidity spectrum of z greater than or equal to 3 cosmic-ray nuclei in the range 4-285 GV and a search for cosmic antimatter

NASA Technical Reports Server (NTRS)

Golden, R. L.; Adams, J. H., Jr.; Marar, T. M. K.; Deney, C. L.; Badhwar, G. D.; Heckman, H. H.; Lindstrom, P. J.

1974-01-01

A measurement, using the magnetic emulsion spectrometer system, of the differential rigidity spectrum of Z greater than or equal to 3 nuclei of the galactic cosmic radiation is presented. The system was flown on Aug. 22, 1969, from Palestine, Texas. The instrument floated above 125,000 feet for eight hours. The data in the rigidity range 8-285 GV can be represented by a power-law spectrum in rigidity, J(rho) = A rho to the minus gamma power, with the exponent gamma = 2.6 plus or minus 0.10. The spectrum in the range 15-285 GV is also described by the same exponent, gamma = 2.6 plus or minus 0.25. The data below 8 GV cannot be described by the same power law without invoking solar modulation. A set of nonunique parameters for modulation are given. Upper limit for the fraction of antimatter in the rigidity range 4-125 GV is .005 with 95% confidence limit.

Searches for Continuous Gravitational Waves from Nine Young Supernova Remnants

NASA Astrophysics Data System (ADS)

Aasi, J.; Abbott, B. P.; Abbott, R.; Abbott, T.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Ain, A.; Ajith, P.; Alemic, A.; Allen, B.; Allocca, A.; Amariutei, D.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C.; Areeda, J. S.; Ast, S.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Aylott, B. E.; Babak, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barbet, M.; Barclay, S.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Bartlett, J.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Bauer, Th. S.; Baune, C.; Bavigadda, V.; Behnke, B.; Bejger, M.; Belczynski, C.; Bell, A. S.; Bell, C.; Benacquista, M.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biscans, S.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackburn, L.; Blair, C. D.; Blair, D.; Bloemen, S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bojtos, P.; Bond, C.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, Sukanta; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Buchman, S.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Cadonati, L.; Cagnoli, G.; Calderón Bustillo, J.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Carbognani, F.; Caride, S.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C.; Colombini, M.; Cominsky, L.; Constancio, M., Jr.; Conte, A.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M. W.; Coulon, J.-P.; Countryman, S.; Couvares, P.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Cutler, C.; Dahl, K.; Dal Canton, T.; Damjanic, M.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dartez, L.; Dattilo, V.; Dave, I.; Daveloza, H.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Dhurandhar, S.; Díaz, M.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Dominguez, E.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S.; Eberle, T.; Edo, T.; Edwards, M.; Edwards, M.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Essick, R.; Etzel, T.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Feldbaum, D.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fuentes-Tapia, S.; Fulda, P.; Fyffe, M.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S.; Garufi, F.; Gatto, A.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; Gergely, L. Á.; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gleason, J.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gordon, N.; Gorodetsky, M. L.; Gossan, S.; Gossler, S.; Gouaty, R.; Gräf, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guido, C. J.; Guo, X.; Gushwa, K.; Gustafson, E. K.; Gustafson, R.; Hacker, J.; Hall, E. D.; Hammond, G.; Hanke, M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Heidmann, A.; Heintze, M.; Heinzel, G.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Heptonstall, A. W.; Heurs, M.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E.; Howell, E. J.; Hu, Y. M.; Huerta, E.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh, M.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Islas, G.; Isler, J. C.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacobson, M.; Jang, H.; Jaranowski, P.; Jawahar, S.; Ji, Y.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; K, Haris; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Keiser, G. M.; Keitel, D.; Kelley, D. B.; Kells, W.; Keppel, D. G.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, C.; Kim, K.; Kim, N. G.; Kim, N.; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kline, J.; Koehlenbeck, S.; Kokeyama, K.; Kondrashov, V.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, A.; Kumar, P.; Kuo, L.; Kutynia, A.; Landry, M.; Lantz, B.; Larson, S.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Lazzaro, C.; Le, J.; Leaci, P.; Leavey, S.; Lebigot, E.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B.; Lewis, J.; Li, T. G. F.; Libbrecht, K.; Libson, A.; Lin, A. C.; Littenberg, T. B.; Lockerbie, N. A.; Lockett, V.; Logue, J.; Lombardi, A. L.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Lubinski, M. J.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macarthur, J.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña na-Sandoval, F.; Magee, R.; Mageswaran, M.; Maglione, C.; Mailand, K.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mangano, V.; Mansell, G. L.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McLin, K.; McWilliams, S.; Meacher, D.; Meadors, G. D.; Meidam, J.; Meinders, M.; Melatos, A.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moe, B.; Moggi, A.; Mohan, M.; Mohanty, S. D.; Mohapatra, S. R. P.; Moore, B.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nagy, M. F.; Nardecchia, I.; Nash, T.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Neri, I.; Neri, M.; Newton, G.; Nguyen, T.; Nielsen, A. B.; Nissanke, S.; Nitz, A. H.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oppermann, P.; Oram, R.; O'Reilly, B.; Ortega, W.; O'Shaughnessy, R.; Osthelder, C.; Ott, C. D.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Padilla, C.; Pai, A.; Pai, S.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Papa, M. A.; Paris, H.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patrick, Z.; Pedraza, M.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poeld, J.; Poggiani, R.; Post, A.; Poteomkin, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qin, J.; Quetschke, V.; Quintero, E.; Quiroga, G.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Raja, S.; Rajalakshmi, G.; Rakhmanov, M.; Ramirez, K.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Reula, O.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Saleem, M.; Salemi, F.; Sammut, L.; Sandberg, V.; Sanders, J. R.; Sannibale, V.; Santiago-Prieto, I.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Savage, R.; Sawadsky, A.; Scheuer, J.; Schilling, R.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sidery, T. L.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, A. D.; Simakov, D.; Singer, A.; Singer, L.; Singh, R.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, J. R.; Smith, M. R.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Son, E. J.; Sorazu, B.; Souradeep, T.; Staley, A.; Stebbins, J.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Steplewski, S.; Stevenson, S.; Stone, R.; Strain, K. A.; Straniero, N.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sutton, P. J.; Swinkels, B.; Szczepanczyk, M.; Szeifert, G.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Tellez, G.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Travasso, F.; Traylor, G.; Tse, M.; Tshilumba, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Vajente, G.; Valdes, G.; Vallisneri, M.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; van den Broeck, C.; van der Sluys, M. V.; van Heijningen, J.; van Veggel, A. A.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vincent-Finley, R.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, H.; Wang, M.; Wang, X.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wessels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Wilkinson, C.; Williams, L.; Williams, R.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Xie, S.; Yablon, J.; Yakushin, I.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yang, Q.; Yvert, M.; Zadrożny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, Fan; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhu, X. J.; Zucker, M. E.; Zuraw, S.; Zweizig, J.

2015-11-01

We describe directed searches for continuous gravitational waves (GWs) in data from the sixth Laser Interferometer Gravitational-wave Observatory (LIGO) science data run. The targets were nine young supernova remnants not associated with pulsars; eight of the remnants are associated with non-pulsing suspected neutron stars. One target's parameters are uncertain enough to warrant two searches, for a total of 10. Each search covered a broad band of frequencies and first and second frequency derivatives for a fixed sky direction. The searches coherently integrated data from the two LIGO interferometers over time spans from 5.3-25.3 days using the matched-filtering {F}-statistic. We found no evidence of GW signals. We set 95% confidence upper limits as strong (low) as 4 × 10-25 on intrinsic strain, 2 × 10-7 on fiducial ellipticity, and 4 × 10-5 on r-mode amplitude. These beat the indirect limits from energy conservation and are within the range of theoretical predictions for neutron-star ellipticities and r-mode amplitudes.

Finding Mass Constraints Through Third Neutrino Mass Eigenstate Decay

NASA Astrophysics Data System (ADS)

Gangolli, Nakul; de Gouvêa, André; Kelly, Kevin

2018-01-01

In this paper we aim to constrain the decay parameter for the third neutrino mass utilizing already accepted constraints on the other mixing parameters from the Pontecorvo-Maki-Nakagawa-Sakata matrix (PMNS). The main purpose of this project is to determine the parameters that will allow the Jiangmen Underground Neutrino Observatory (JUNO) to observe a decay parameter with some statistical significance. Another goal is to determine the parameters that JUNO could detect in the case that the third neutrino mass is lighter than the first two neutrino species. We also replicate the results that were found in the JUNO Conceptual Design Report (CDR). By utilizing Χ2-squared analysis constraints have been put on the mixing angles, mass squared differences, and the third neutrino decay parameter. These statistical tests take into account background noise and normalization corrections and thus the finalized bounds are a good approximation for the true bounds that JUNO can detect. If the decay parameter is not included in our models, the 99% confidence interval lies within The bounds 0s to 2.80x10-12s. However, if we account for a decay parameter of 3x10-5 ev2, then 99% confidence interval lies within 8.73x10-12s to 8.73x10-11s.

Towards the estimation of effect measures in studies using respondent-driven sampling.

PubMed

Rotondi, Michael A

2014-06-01

Respondent-driven sampling (RDS) is an increasingly common sampling technique to recruit hidden populations. Statistical methods for RDS are not straightforward due to the correlation between individual outcomes and subject weighting; thus, analyses are typically limited to estimation of population proportions. This manuscript applies the method of variance estimates recovery (MOVER) to construct confidence intervals for effect measures such as risk difference (difference of proportions) or relative risk in studies using RDS. To illustrate the approach, MOVER is used to construct confidence intervals for differences in the prevalence of demographic characteristics between an RDS study and convenience study of injection drug users. MOVER is then applied to obtain a confidence interval for the relative risk between education levels and HIV seropositivity and current infection with syphilis, respectively. This approach provides a simple method to construct confidence intervals for effect measures in RDS studies. Since it only relies on a proportion and appropriate confidence limits, it can also be applied to previously published manuscripts.

Evaluation of CS (o-chlorobenzylidene malononitrile) concentrations during U.S. Army mask confidence training.

PubMed

Hout, Joseph J; Kluchinsky, Timothy; LaPuma, Peter T; White, Duvel W

2011-10-01

All soldiers in the U.S. Army are required to complete mask confidence training with o-chlorobenzylidene malononitrile (CS). To instill confidence in the protective capability of the military protective mask, CS is thermally dispersed in a room where soldiers wearing military protective masks are required to conduct various physical exercises, break the seal of their mask, speak, and remove their mask. Soldiers immediately feel the irritating effects of CS when the seal of the mask is broken, which reinforces the mask's ability to shield the soldier from airborne chemical hazards. In the study described in this article, the authors examined the CS concentration inside a mask confidence chamber operated in accordance with U.S. Army training guidelines. The daily average CS concentrations ranged from 2.33-3.29 mg/m3 and exceeded the threshold limit value ceiling, the recommended exposure limit ceiling, and the concentration deemed immediately dangerous to life and health. The minimum and maximum CS concentration used during mask confidence training should be evaluated.

Search for physics beyond the standard model in dilepton mass spectra in proton-proton collisions at TeV

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Luyckx, S.; Ochesanu, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Mora Herrera, C.; Pol, M. E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santaolalla, J.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Aleksandrov, A.; Genchev, V.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Tao, J.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Zou, W.; Avila, C.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Busson, P.; Charlot, C.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Mastrolorenzo, L.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Veelken, C.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Chabert, E. C.; Collard, C.; Conte, E.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Boudoul, G.; Bouvier, E.; Brochet, S.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Bontenackels, M.; Edelhoff, M.; Feld, L.; Hindrichs, O.; Klein, K.; Ostapchuk, A.; Perieanu, A.; Raupach, F.; Sammet, J.; Schael, S.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Erdmann, M.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Pook, T.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Weber, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Heister, A.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Perchalla, L.; Pooth, O.; Stahl, A.; Asin, I.; Bartosik, N.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bell, A. J.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garay Garcia, J.; Geiser, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Horton, D.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Krücker, D.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Novgorodova, O.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Pietsch, N.; Poehlsen, J.; Poehlsen, T.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Kuznetsova, E.; Lobelle Pardo, P.; Mozer, M. U.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Röcker, S.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; Kumar, R.; Mittal, M.; Nishu, N.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. 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S.; Colaleo, A.; Creanza, D.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Zito, G.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. 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M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Dosselli, U.; Galanti, M.; Gasparini, F.; Gasparini, U.; Giubilato, P.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fiori, F.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Moon, C. S.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Vernieri, C.; Barone, L.; Cavallari, F.; D'imperio, G.; Del Re, D.; Diemoz, M.; Grassi, M.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Soffi, L.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Casasso, S.; Costa, M.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; Ortona, G.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Potenza, A.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Tamponi, U.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Park, H.; Sakharov, A.; Son, D. C.; Kim, T. J.; Kim, J. Y.; Song, S.; Choi, S.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K. S.; Park, S. K.; Roh, Y.; Yoo, H. D.; Choi, M.; Kim, J. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Ali, M. A. B. Md; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Casimiro Linares, E.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khalid, S.; Khan, W. A.; Khurshid, T.; Shah, M. A.; Shoaib, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Brona, G.; Bunkowski, K.; Cwiok, M.; Dominik, W.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Wolszczak, W.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Lloret Iglesias, L.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Varela, J.; Vischia, P.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Konoplyanikov, V.; Kozlov, G.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Vorobyev, An.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Safronov, G.; Semenov, S.; Spiridonov, A.; Stolin, V.; Vlasov, E.; Zhokin, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Perfilov, M.; Savrin, V.; Snigirev, A.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. 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I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chang, Y. 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I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; John, J. St.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Nguyen, H.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Andrews, W.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Evans, D.; Holzner, A.; Kelley, R.; Klein, D.; Lebourgeois, M.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. 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M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kaadze, K.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Cheng, T.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Sakuma, T.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Vuosalo, C.; Woods, N.

2015-04-01

Dimuon and dielectron mass spectra, obtained from data resulting from proton-proton collisions at 8 TeV and recorded by the CMS experiment, are used to search for both narrow resonances and broad deviations from standard model predictions. The data correspond to an integrated luminosity of 20.6 (19.7) fb-1 for the dimuon (dielectron) channel. No evidence for non-standard-model physics is observed and 95% confidence level limits are set on parameters from a number of new physics models. The narrow resonance analyses exclude a Sequential Standard Model Z{SSM/'} resonance lighter than 2.90 TeV, a superstring-inspired Z{/ψ '} lighter than 2.57 TeV, and Randall-Sundrum Kaluza-Klein gravitons with masses below 2.73, 2.35, and 1.27 TeV for couplings of 0.10, 0.05, and 0.01, respectively. A notable feature is that the limits have been calculated in a model-independent way to enable straightforward reinterpretation in any model predicting a resonance structure. The observed events are also interpreted within the framework of two non-resonant analyses: one based on a large extra dimensions model and one based on a quark and lepton compositeness model with a left-left isoscalar contact interaction. Lower limits are established on MS, the scale characterizing the onset of quantum gravity, which range from 4.9 to 3.3 TeV, where the number of additional spatial dimensions varies from 3 to 7. Similarly, lower limits on Λ, the energy scale parameter for the contact interaction, are found to be 12.0 (15.2) TeV for destructive (constructive) interference in the dimuon channel and 13.5 (18.3) TeV in the dielectron channel. [Figure not available: see fulltext.

Search for physics beyond the standard model in dilepton mass spectra in proton-proton collisions at √s = 8 TeV

DOE PAGES

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

2015-04-07

Dimuon and dielectron mass spectra, obtained from data resulting from proton-proton collisions at 8 TeV and recorded by the CMS experiment, are used to search for both narrow resonances and broad deviations from standard model predictions. The data correspond to an integrated luminosity of 20.6 (19.7) fb –1 for the dimuon (dielectron) channel. No evidence for non-standard-model physics is observed and 95% confidence level limits are set on parameters from a number of new physics models. The narrow resonance analyses exclude a Sequential Standard Model Z SSM ' resonance lighter than 2.90 TeV, a superstring-inspired Z ψ ' lighter thanmore » 2.57 TeV, and Randall-Sundrum Kaluza-Klein gravitons with masses below 2.73, 2.35, and 1.27 TeV for couplings of 0.10, 0.05, and 0.01, respectively. A notable feature is that the limits have been calculated in a model-independent way to enable straightforward reinterpretation in any model predicting a resonance structure. The observed events are also interpreted within the framework of two non-resonant analyses: one based on a large extra dimensions model and one based on a quark and lepton compositeness model with a left-left isoscalar contact interaction. Lower limits are established on MS, the scale characterizing the onset of quantum gravity, which range from 4.9 to 3.3 TeV, where the number of additional spatial dimensions varies from 3 to 7. Thus lower limits on Λ, the energy scale parameter for the contact interaction, are found to be 12.0 (15.2) TeV for destructive (constructive) interference in the dimuon channel and 13.5 (18.3) TeV in the dielectron channel.« less

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

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

Dimuon and dielectron mass spectra, obtained from data resulting from proton-proton collisions at 8 TeV and recorded by the CMS experiment, are used to search for both narrow resonances and broad deviations from standard model predictions. The data correspond to an integrated luminosity of 20.6 (19.7) fb –1 for the dimuon (dielectron) channel. No evidence for non-standard-model physics is observed and 95% confidence level limits are set on parameters from a number of new physics models. The narrow resonance analyses exclude a Sequential Standard Model Z SSM ' resonance lighter than 2.90 TeV, a superstring-inspired Z ψ ' lighter thanmore » 2.57 TeV, and Randall-Sundrum Kaluza-Klein gravitons with masses below 2.73, 2.35, and 1.27 TeV for couplings of 0.10, 0.05, and 0.01, respectively. A notable feature is that the limits have been calculated in a model-independent way to enable straightforward reinterpretation in any model predicting a resonance structure. The observed events are also interpreted within the framework of two non-resonant analyses: one based on a large extra dimensions model and one based on a quark and lepton compositeness model with a left-left isoscalar contact interaction. Lower limits are established on MS, the scale characterizing the onset of quantum gravity, which range from 4.9 to 3.3 TeV, where the number of additional spatial dimensions varies from 3 to 7. Thus lower limits on Λ, the energy scale parameter for the contact interaction, are found to be 12.0 (15.2) TeV for destructive (constructive) interference in the dimuon channel and 13.5 (18.3) TeV in the dielectron channel.« less

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

NASA Technical Reports Server (NTRS)

Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric

2003-01-01

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been proposed by the Society of Automotive Engineers (SAE). The test cases compare different probabilistic methods within NESSUS because it is important that a user can have confidence that estimates of stochastic parameters of a response will be within an acceptable error limit. For each response, the mean, standard deviation, and 0.99 percentile, are repeatedly estimated which allows confidence statements to be made for each parameter estimated, and for each method. Thus, the ability of several stochastic methods to efficiently and accurately estimate density parameters is compared using four valid test cases. While all of the reliability methods used performed quite well, for the new LHS module within NESSUS it was found that it had a lower estimation error than MC when they were used to estimate the mean, standard deviation, and 0.99 percentile of the four different stochastic responses. Also, LHS required a smaller amount of calculations to obtain low error answers with a high amount of confidence than MC. It can therefore be stated that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ and the newest LHS module is a valuable new enhancement of the program.

Preparation, Clinical Support, and Confidence of Speech-Language Therapists Managing Clients with a Tracheostomy in the UK

ERIC Educational Resources Information Center

Ward, Elizabeth; Morgan, Tessa; McGowan, Sue; Spurgin, Ann-Louise; Solley, Maura

2012-01-01

Background: Literature regarding the education, training, clinical support and confidence of speech-language therapists (SLTs) working with patients with a tracheostomy is limited; however, it suggests that many clinicians have reduced clinical confidence when managing this complex population, many face role and team challenges practising in this…

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

USGS Publications Warehouse

Liu, S.; Anderson, P.; Zhou, G.; Kauffman, B.; Hughes, F.; Schimel, D.; Watson, Vicente; Tosi, Joseph

2008-01-01

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in seven life zones in Costa Rica. Net primary productivity from the Moderate-Resolution Imaging Spectroradiometer (MODIS), C and N stocks in aboveground live biomass, litter, coarse woody debris (CWD), and in soils were used to calibrate the model. To investigate the resolution of available observations on the number of adjustable parameters, inversion was performed using nine setups of adjustable parameters. Statistics including observation sensitivity, parameter correlation coefficient, parameter sensitivity, and parameter confidence limits were used to evaluate the information content of observations, resolution of model parameters, and overall model performance. Results indicated that soil organic carbon content, soil nitrogen content, and total aboveground biomass carbon had the highest information contents, while measurements of carbon in litter and nitrogen in CWD contributed little to the parameter estimation processes. The available information could resolve the values of 2-4 parameters. Adjusting just one parameter resulted in under-fitting and unacceptable model performance, while adjusting five parameters simultaneously led to over-fitting. Results further indicated that the MODIS NPP values were compressed as compared with the spatial variability of net primary production (NPP) values inferred from inverse modeling. Using inverse modeling to infer NPP and other sensitive model parameters from C and N stock observations provides an opportunity to utilize data collected by national to regional forest inventory systems to reduce the uncertainties in the carbon cycle and generate valuable databases to validate and improve MODIS NPP algorithms.

Development of experimental approach to examine U occurrence continuity over the extended area reconnoitory boreholes: Lostoin Block, West Khasi Hills district, Meghalaya (India).

PubMed

Kukreti, B M; Kumar, Pramod; Sharma, G K

2015-10-01

Exploratory drilling was undertaken in the Lostoin block, West Khasi Hills district of Meghalaya based on the geological extension to the major uranium deposit in the basin. Gamma ray logging of drilled boreholes shows considerable subsurface mineralization in the block. However, environmental and exploration related challenges such as climatic, logistic, limited core drilling and poor core recovery etc. in the block severely restricted the study of uranium exploration related index parameters for the block with a high degree confidence. The present study examines these exploration related challenges and develops an integrated approach using representative sampling of reconnoitory boreholes in the block. Experimental findings validate a similar geochemically coherent nature of radio elements (K, Ra and Th) in the Lostoin block uranium hosting environment with respect to the known block of Mahadek basin and uranium enrichment is confirmed by the lower U to Th correlation index (0.268) of hosting environment. A mineralized zone investigation in the block shows parent (refers to the actual parent uranium concentration at a location and not a secondary concentration such as the daughter elements which produce the signal from a total gamma ray measurement) favoring uranium mineralization. The confidence parameters generated under the present study have implications for the assessment of the inferred category of uranium ore in the block and setting up a road map for the systematic exploration of large uranium potential occurring over extended areas in the basin amid prevailing environmental and exploratory impediments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparative bioavailability study of cefuroxime axetil (equivalent to 500 mg cefuroxime/tablet) tablets (Zednad® versus Zinnat®) in healthy male volunteers.

PubMed

Asiri, Y A; Al-Hadiya, B M; Kadi, A A; Al-Khamis, K I; Mowafy, H A; El-Sayed, Y M

2011-09-01

This study was performed to investigate the bioequivalence of cefuroxime axetil tablets between a generic test product (A) Zednad® Tablet (500 mg cefuroxime/ tablet, Diamond Pharma, Syria), and the Reference Product (B) Zinnat® Tablet (500 mg cefuroxime/tablet, GlaxoSmithKline, Saudi Arabia). The bioavailability study was carried out for 24 healthy male volunteers. The subjects received 1 Zednad® Tablet (500 mg/ tablet) and 1 Zinnat® Tablet (500 mg/tablet) in a randomized, two-way crossover design fashion on 2 treatment days, after an overnight fast of at least 10 h, with a washout period of 7 days. 24 volunteers plus 2 alternatives completed the crossover. The bioanalysis of clinical plasma samples was accomplished by HPLC method, which was developed and validated in accordance with international guidelines. Pharmacokinetic parameters, determined by standard non-compartmental methods, and ANOVA statistics were calculated using SAS Statistical Software. The significance of a sequence effect was tested using the subjects nested in sequence as the error term. The 90% confidence intervals for the ratio between the test and reference product pharmacokinetic parameters of AUC0→t, AUC0→∞, and Cmax were calculated and found to be within the confidence limits of 80.00 - 125.00% for AUC0→t, AUC0→∞ and Cmax. The study demonstrated that the test product (A) was found bioequivalent to the reference product (B) following an oral dose of 500 mg tablet. Therefore, the two formulations were considered to be bioequivalent.

Bioequivalence of a methylphenidate hydrochloride extended-release preparation: comparison of an intact capsule and an opened capsule sprinkled on applesauce.

PubMed

Fischer, R; Schütz, H; Grossmann, M; Leis, H J; Ammer, R

2006-03-01

To assess bioequivalence between an intact capsule and the content of a capsule sprinkled on applesauce. Medikinet retard 20 mg capsules were obtained from Medice (Iserlohn, Germany). This was a single-center, completely randomized, open, 2-period, 2-sequence, balanced crossover study with a washout period of 1 week between administrations, in 12 healthy male and female subjects, aged 18-45 years. Blood samples were collected over 24 hours and methylphenidate plasma concentration-time data were used to calculate pharmacokinetic parameters for both administrations. The main parameters were (confirmatory) AUC0-tz (extent of BA), Cmax, tmax (rate of BA) and (descriptively) AUC0-infinity and t1/2. Equivalence was concluded if the 90% confidence interval (CI) for the ratio between test and reference was 0.80-1.25 (AUC0-tz). All 12 dosed subjects finished both treatment periods and were included in pharmacokinetic and safety analyses. 90% geometric confidence intervals for AUC0-tz and Cmax data were well within accepted bioequivalence limits. The study has shown that both treatment modes lead to similar pattern of absorption and elimination following single-dose administration in the fed state. The test treatment (content of capsule sprinkled over 15 ml applesauce) is bioequivalent to the reference treatment (intact capsule) in terms of extent and rate of absorption. Data collected from this study demonstrate that Medikinet retard capsules can be opened and the content sprinkled on a tablespoon of applesauce without influencing the rate and extent of bioavailability.

Ruling out Legionella in community-acquired pneumonia.

PubMed

Haubitz, Sebastian; Hitz, Fabienne; Graedel, Lena; Batschwaroff, Marcus; Wiemken, Timothy Lee; Peyrani, Paula; Ramirez, Julio A; Fux, Christoph Andreas; Mueller, Beat; Schuetz, Philipp

2014-10-01

Assessing the likelihood for Legionella sp. in community-acquired pneumonia is important because of differences in treatment regimens. Currently used antigen tests and culture have limited sensitivity with important time delays, making empirical broad-spectrum coverage necessary. Therefore, a score with 6 variables recently has been proposed. We sought to validate these parameters in an independent cohort. We analyzed adult patients with community-acquired pneumonia from a large multinational database (Community Acquired Pneumonia Organization) who were treated between 2001 and 2012 with more than 4 of the 6 prespecified clinical variables available. Association and discrimination were assessed using logistic regression analysis and area under the curve (AUC). Of 1939 included patients, the infectious cause was known in 594 (28.9%), including Streptococcus pneumoniae in 264 (13.6%) and Legionella sp. in 37 (1.9%). The proposed clinical predictors fever, cough, hyponatremia, lactate dehydrogenase, C-reactive protein, and platelet count were all associated or tended to be associated with Legionella cause. A logistic regression analysis including all these predictors showed excellent discrimination with an AUC of 0.91 (95% confidence interval, 0.87-0.94). The original dichotomized score showed good discrimination (AUC, 0.73; 95% confidence interval, 0.65-0.81) and a high negative predictive value of 99% for patients with less than 2 parameters present. With the use of a large independent patient sample from an international database, this analysis validates previously proposed clinical variables to accurately rule out Legionella sp., which may help to optimize initial empiric therapy. Copyright © 2014 Elsevier Inc. All rights reserved.

Using Stochastic Approximation Techniques to Efficiently Construct Confidence Intervals for Heritability.

PubMed

Schweiger, Regev; Fisher, Eyal; Rahmani, Elior; Shenhav, Liat; Rosset, Saharon; Halperin, Eran

2018-06-22

Estimation of heritability is an important task in genetics. The use of linear mixed models (LMMs) to determine narrow-sense single-nucleotide polymorphism (SNP)-heritability and related quantities has received much recent attention, due of its ability to account for variants with small effect sizes. Typically, heritability estimation under LMMs uses the restricted maximum likelihood (REML) approach. The common way to report the uncertainty in REML estimation uses standard errors (SEs), which rely on asymptotic properties. However, these assumptions are often violated because of the bounded parameter space, statistical dependencies, and limited sample size, leading to biased estimates and inflated or deflated confidence intervals (CIs). In addition, for larger data sets (e.g., tens of thousands of individuals), the construction of SEs itself may require considerable time, as it requires expensive matrix inversions and multiplications. Here, we present FIESTA (Fast confidence IntErvals using STochastic Approximation), a method for constructing accurate CIs. FIESTA is based on parametric bootstrap sampling, and, therefore, avoids unjustified assumptions on the distribution of the heritability estimator. FIESTA uses stochastic approximation techniques, which accelerate the construction of CIs by several orders of magnitude, compared with previous approaches as well as to the analytical approximation used by SEs. FIESTA builds accurate CIs rapidly, for example, requiring only several seconds for data sets of tens of thousands of individuals, making FIESTA a very fast solution to the problem of building accurate CIs for heritability for all data set sizes.

Evaluation of Effective Sources in Uncertainty Measurements of Personal Dosimetry by a Harshaw TLD System

PubMed Central

Hosseini Pooya, SM; Orouji, T

2014-01-01

Background: The accurate results of the individual doses in personal dosimety which are reported by the service providers in personal dosimetry are very important. There are national / international criteria for acceptable dosimetry system performance. Objective: In this research, the sources of uncertainties are identified, measured and calculated in a personal dosimetry system by TLD. Method: These sources are included; inhomogeneity of TLDs sensitivity, variability of TLD readings due to limited sensitivity and background, energy dependence, directional dependence, non-linearity of the response, fading, dependent on ambient temperature / humidity and calibration errors, which may affect on the dose responses. Some parameters which influence on the above sources of uncertainty are studied for Harshaw TLD-100 cards dosimeters as well as the hot gas Harshaw 6600 TLD reader system. Results: The individual uncertainties of each sources was measured less than 6.7% in 68% confidence level. The total uncertainty was calculated 17.5% with 95% confidence level. Conclusion: The TLD-100 personal dosimeters as well as the Harshaw TLD-100 reader 6600 system show the total uncertainty value which is less than that of admissible value of 42% for personal dosimetry services. PMID:25505769

Calculation of Confidence Intervals for the Maximum Magnitude of Earthquakes in Different Seismotectonic Zones of Iran

NASA Astrophysics Data System (ADS)

Salamat, Mona; Zare, Mehdi; Holschneider, Matthias; Zöller, Gert

2017-03-01

The problem of estimating the maximum possible earthquake magnitude m_max has attracted growing attention in recent years. Due to sparse data, the role of uncertainties becomes crucial. In this work, we determine the uncertainties related to the maximum magnitude in terms of confidence intervals. Using an earthquake catalog of Iran, m_max is estimated for different predefined levels of confidence in six seismotectonic zones. Assuming the doubly truncated Gutenberg-Richter distribution as a statistical model for earthquake magnitudes, confidence intervals for the maximum possible magnitude of earthquakes are calculated in each zone. While the lower limit of the confidence interval is the magnitude of the maximum observed event,the upper limit is calculated from the catalog and the statistical model. For this aim, we use the original catalog which no declustering methods applied on as well as a declustered version of the catalog. Based on the study by Holschneider et al. (Bull Seismol Soc Am 101(4):1649-1659, 2011), the confidence interval for m_max is frequently unbounded, especially if high levels of confidence are required. In this case, no information is gained from the data. Therefore, we elaborate for which settings finite confidence levels are obtained. In this work, Iran is divided into six seismotectonic zones, namely Alborz, Azerbaijan, Zagros, Makran, Kopet Dagh, Central Iran. Although calculations of the confidence interval in Central Iran and Zagros seismotectonic zones are relatively acceptable for meaningful levels of confidence, results in Kopet Dagh, Alborz, Azerbaijan and Makran are not that much promising. The results indicate that estimating m_max from an earthquake catalog for reasonable levels of confidence alone is almost impossible.

Search for anomalous couplings in the W tb vertex from the measurement of double differential angular decay rates of single top quarks produced in the t-channel with the ATLAS detector

DOE PAGES

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

2016-04-05

The electroweak production and subsequent decay of single top quarks is determined by the properties of the Wtb vertex. This vertex can be described by the complex parameters of an effective Lagrangian. An analysis of angular distributions of the decay products of single top quarks produced in the t -channel constrains these parameters simultaneously. The analysis described in this paper uses 4.6 fb -1 of proton-proton collision data at √s=7 TeV collected with the ATLAS detector at the LHC. Two parameters are measured simultaneously in this analysis. The fraction f 1 of decays containing transversely polarised W bosons is measuredmore » to be 0.37 ± 0.07 (stat.⊕syst.). The phase δ - between amplitudes for transversely and longitudinally polarised W bosons recoiling against left-handed b-quarks is measured to be -0.014π ± 0.036π (stat.⊕syst.). The correlation in the measurement of these parameters is 0.15. These values result in two-dimensional limits at the 95% confidence level on the ratio of the complex coupling parameters g R and V L, yielding Re[g R /V L] ϵ [-0.36, 0.10] and Im[g R /V L] ϵ [-0.17, 0.23] with a correlation of 0.11. We find the results are in good agreement with the predictions of the Standard Model.« less

Exact one-sided confidence bounds for the risk ratio in 2 x 2 tables with structural zero.

PubMed

Lloyd, Chris J; Moldovan, Max V

2007-12-01

This paper examines exact one-sided confidence limits for the risk ratio in a 2 x 2 table with structural zero. Starting with four approximate lower and upper limits, we adjust each using the algorithm of Buehler (1957) to arrive at lower (upper) limits that have exact coverage properties and are as large (small) as possible subject to coverage, as well as an ordering, constraint. Different Buehler limits are compared by their mean size, since all are exact in their coverage. Buehler limits based on the signed root likelihood ratio statistic are found to have the best performance and recommended for practical use. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Reliability of spatiotemporal and kinetic gait parameters determined by a new instrumented treadmill system.

PubMed

Reed, Lloyd F; Urry, Stephen R; Wearing, Scott C

2013-08-21

Despite the emerging use of treadmills integrated with pressure platforms as outcome tools in both clinical and research settings, published evidence regarding the measurement properties of these new systems is limited. This study evaluated the within- and between-day repeatability of spatial, temporal and vertical ground reaction force parameters measured by a treadmill system instrumented with a capacitance-based pressure platform. Thirty three healthy adults (mean age, 21.5 ± 2.8 years; height, 168.4 ± 9.9 cm; and mass, 67.8 ± 18.6 kg), walked barefoot on a treadmill system (FDM-THM-S, Zebris Medical GmbH) on three separate occasions. For each testing session, participants set their preferred pace but were blinded to treadmill speed. Spatial (foot rotation, step width, stride and step length), temporal (stride and step times, duration of stance, swing and single and double support) and peak vertical ground reaction force variables were collected over a 30-second capture period, equating to an average of 52 ± 5 steps of steady-state walking. Testing was repeated one week following the initial trial and again, for a third time, 20 minutes later. Repeated measures ANOVAs within a generalized linear modelling framework were used to assess between-session differences in gait parameters. Agreement between gait parameters measured within the same day (session 2 and 3) and between days (session 1 and 2; 1 and 3) were evaluated using the 95% repeatability coefficient. There were statistically significant differences in the majority (14/16) of temporal, spatial and kinetic gait parameters over the three test sessions (P < .01). The minimum change that could be detected with 95% confidence ranged between 3% and 17% for temporal parameters, 14% and 33% for spatial parameters, and 4% and 20% for kinetic parameters between days. Within-day repeatability was similar to that observed between days. Temporal and kinetic gait parameters were typically more consistent than spatial parameters. The 95% repeatability coefficient for vertical force peaks ranged between ± 53 and ± 63 N. The limits of agreement in spatial parameters and ground reaction forces for the treadmill system encompass previously reported changes with neuromuscular pathology and footwear interventions. These findings provide clinicians and researchers with an indication of the repeatability and sensitivity of the Zebris treadmill system to detect changes in common spatiotemporal gait parameters and vertical ground reaction forces.

Weakly dynamic dark energy via metric-scalar couplings with torsion

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

Sur, Sourav; Bhatia, Arshdeep Singh, E-mail: sourav.sur@gmail.com, E-mail: arshdeepsb@gmail.com

We study the dynamical aspects of dark energy in the context of a non-minimally coupled scalar field with curvature and torsion. Whereas the scalar field acts as the source of the trace mode of torsion, a suitable constraint on the torsion pseudo-trace provides a mass term for the scalar field in the effective action. In the equivalent scalar-tensor framework, we find explicit cosmological solutions representing dark energy in both Einstein and Jordan frames. We demand the dynamical evolution of the dark energy to be weak enough, so that the present-day values of the cosmological parameters could be estimated keeping themmore » within the confidence limits set for the standard LCDM model from recent observations. For such estimates, we examine the variations of the effective matter density and the dark energy equation of state parameters over different redshift ranges. In spite of being weakly dynamic, the dark energy component differs significantly from the cosmological constant, both in characteristics and features, for e.g. it interacts with the cosmological (dust) fluid in the Einstein frame, and crosses the phantom barrier in the Jordan frame. We also obtain the upper bounds on the torsion mode parameters and the lower bound on the effective Brans-Dicke parameter. The latter turns out to be fairly large, and in agreement with the local gravity constraints, which therefore come in support of our analysis.« less

Weakly dynamic dark energy via metric-scalar couplings with torsion

NASA Astrophysics Data System (ADS)

Sur, Sourav; Singh Bhatia, Arshdeep

2017-07-01

We study the dynamical aspects of dark energy in the context of a non-minimally coupled scalar field with curvature and torsion. Whereas the scalar field acts as the source of the trace mode of torsion, a suitable constraint on the torsion pseudo-trace provides a mass term for the scalar field in the effective action. In the equivalent scalar-tensor framework, we find explicit cosmological solutions representing dark energy in both Einstein and Jordan frames. We demand the dynamical evolution of the dark energy to be weak enough, so that the present-day values of the cosmological parameters could be estimated keeping them within the confidence limits set for the standard LCDM model from recent observations. For such estimates, we examine the variations of the effective matter density and the dark energy equation of state parameters over different redshift ranges. In spite of being weakly dynamic, the dark energy component differs significantly from the cosmological constant, both in characteristics and features, for e.g. it interacts with the cosmological (dust) fluid in the Einstein frame, and crosses the phantom barrier in the Jordan frame. We also obtain the upper bounds on the torsion mode parameters and the lower bound on the effective Brans-Dicke parameter. The latter turns out to be fairly large, and in agreement with the local gravity constraints, which therefore come in support of our analysis.

Commentary on Holmes et al. (2007): resolving the debate on when extinction risk is predictable.

PubMed

Ellner, Stephen P; Holmes, Elizabeth E

2008-08-01

We reconcile the findings of Holmes et al. (Ecology Letters, 10, 2007, 1182) that 95% confidence intervals for quasi-extinction risk were narrow for many vertebrates of conservation concern, with previous theory predicting wide confidence intervals. We extend previous theory, concerning the precision of quasi-extinction estimates as a function of population dynamic parameters, prediction intervals and quasi-extinction thresholds, and provide an approximation that specifies the prediction interval and threshold combinations where quasi-extinction estimates are precise (vs. imprecise). This allows PVA practitioners to define the prediction interval and threshold regions of safety (low risk with high confidence), danger (high risk with high confidence), and uncertainty.

How Near is a Near-Optimal Solution: Confidence Limits for the Global Optimum.

DTIC Science & Technology

1980-05-01

or near-optimal solutions are the only practical solutions available. This paper identifies and compares some procedures which use independent near...approximate or near-optimal solutions are the only practical solutions available. This paper identifies and compares some procedures which use inde- pendent...The objective of this paper is to indicate some relatively new statistical procedures for obtaining an upper confidence limit on G Each of these

Evaluation of trace analyte identification in complex matrices by low-resolution gas chromatography--Mass spectrometry through signal simulation.

PubMed

Bettencourt da Silva, Ricardo J N

2016-04-01

The identification of trace levels of compounds in complex matrices by conventional low-resolution gas chromatography hyphenated with mass spectrometry is based in the comparison of retention times and abundance ratios of characteristic mass spectrum fragments of analyte peaks from calibrators with sample peaks. Statistically sound criteria for the comparison of these parameters were developed based on the normal distribution of retention times and the simulation of possible non-normal distribution of correlated abundances ratios. The confidence level used to set the statistical maximum and minimum limits of parameters defines the true positive rates of identifications. The false positive rate of identification was estimated from worst-case signal noise models. The estimated true and false positive identifications rate from one retention time and two correlated ratios of three fragments abundances were combined using simple Bayes' statistics to estimate the probability of compound identification being correct designated examination uncertainty. Models of the variation of examination uncertainty with analyte quantity allowed the estimation of the Limit of Examination as the lowest quantity that produced "Extremely strong" evidences of compound presence. User friendly MS-Excel files are made available to allow the easy application of developed approach in routine and research laboratories. The developed approach was successfully applied to the identification of chlorpyrifos-methyl and malathion in QuEChERS method extracts of vegetables with high water content for which the estimated Limit of Examination is 0.14 mg kg(-1) and 0.23 mg kg(-1) respectively. Copyright © 2015 Elsevier B.V. All rights reserved.

Search for new light gauge bosons in Higgs boson decays to four-lepton final states in p p collisions at s = 8 TeV with the ATLAS detector at the LHC

DOE PAGES

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

2015-11-01

This research presents a search for Higgs bosons decaying to four leptons, either electrons or muons, via one or two light exotic gauge bosons Z d, H → ZZ d → 4ℓ or H → Z dZ d → 4ℓ. The search was performed using pp collision data corresponding to an integrated luminosity of about 20 fb –1 at the center-of-mass energy of \\(\\sqrt{s} = 8\\) TeV recorded with the ATLAS detector at the Large Hadron Collider. The observed data are well described by the Standard Model prediction. Upper bounds on the branching ratio of H → ZZ d →more » 4ℓ and on the kinetic mixing parameter between the Z d and the Standard Model hypercharge gauge boson are set in the range (1-9) × 10 –5 and (4–17) × 10 -2 respectively, at 95% confidence level assuming the Standard Model branching ratio of H → ZZ* → 4ℓ, for Z d masses between 15 and 55 GeV. Upper bounds on the effective mass mixing parameter between the Z and the Z d are also set using the branching ratio limits in the H → ZZ d → 4ℓ search, and are in the range (1.5-8.7) × 10 -4 for 15 < m Zd < 35 GeV. Upper bounds on the branching ratio of H → Z dZ d → 4ℓ and on the Higgs portal coupling parameter, controlling the strength of the coupling of the Higgs boson to dark vector bosons are set in the range (2–3) × 10 -5 and (1–10) × 10 -4 respectively, at 95% confidence level assuming the Standard Model Higgs boson production cross sections, for Z d masses between 15 and 60 GeV.« less

The Atacama Cosmology Telescope: cosmological parameters from three seasons of data

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

Sievers, Jonathan L.; Appel, John William; Hlozek, Renée A.

2013-10-01

We present constraints on cosmological and astrophysical parameters from high-resolution microwave background maps at 148 GHz and 218 GHz made by the Atacama Cosmology Telescope (ACT) in three seasons of observations from 2008 to 2010. A model of primary cosmological and secondary foreground parameters is fit to the map power spectra and lensing deflection power spectrum, including contributions from both the thermal Sunyaev-Zeldovich (tSZ) effect and the kinematic Sunyaev-Zeldovich (kSZ) effect, Poisson and correlated anisotropy from unresolved infrared sources, radio sources, and the correlation between the tSZ effect and infrared sources. The power ℓ{sup 2}C{sub ℓ}/2π of the thermal SZmore » power spectrum at 148 GHz is measured to be 3.4±1.4  μK{sup 2} at ℓ = 3000, while the corresponding amplitude of the kinematic SZ power spectrum has a 95% confidence level upper limit of 8.6  μK{sup 2}. Combining ACT power spectra with the WMAP 7-year temperature and polarization power spectra, we find excellent consistency with the LCDM model. We constrain the number of effective relativistic degrees of freedom in the early universe to be N{sub eff} = 2.79±0.56, in agreement with the canonical value of N{sub eff} = 3.046 for three massless neutrinos. We constrain the sum of the neutrino masses to be Σm{sub ν} < 0.39 eV at 95% confidence when combining ACT and WMAP 7-year data with BAO and Hubble constant measurements. We constrain the amount of primordial helium to be Y{sub p} = 0.225±0.034, and measure no variation in the fine structure constant α since recombination, with α/α{sub 0} = 1.004±0.005. We also find no evidence for any running of the scalar spectral index, dn{sub s}/dln k = −0.004±0.012.« less

The Atacama Cosmology Telescope: Cosmological Parameters from Three Seasons of Data

NASA Technical Reports Server (NTRS)

Seivers, Jonathan L.; Hlozek, Renee A.; Nolta, Michael R.; Acquaviva, Viviana; Addison, Graeme E.; Ade, Peter A. R.; Aguirre, Paula; Amiri, Mandana; Appel, John W.; Barrientos, L. Felipe;

Pulsar Timing Array Based Search for Supermassive Black Hole Binaries in the Square Kilometer Array Era

NASA Astrophysics Data System (ADS)

Wang, Yan; Mohanty, Soumya D.

2017-04-01

The advent of next generation radio telescope facilities, such as the Square Kilometer Array (SKA), will usher in an era where a pulsar timing array (PTA) based search for gravitational waves (GWs) will be able to use hundreds of well timed millisecond pulsars rather than the few dozens in existing PTAs. A realistic assessment of the performance of such an extremely large PTA must take into account the data analysis challenge posed by an exponential increase in the parameter space volume due to the large number of so-called pulsar phase parameters. We address this problem and present such an assessment for isolated supermassive black hole binary (SMBHB) searches using a SKA era PTA containing 1 03 pulsars. We find that an all-sky search will be able to confidently detect nonevolving sources with a redshifted chirp mass of 1 010 M⊙ out to a redshift of about 28 (corresponding to a rest-frame chirp mass of 3.4 ×1 08 M⊙). We discuss the important implications that the large distance reach of a SKA era PTA has on GW observations from optically identified SMBHB candidates. If no SMBHB detections occur, a highly unlikely scenario in the light of our results, the sky-averaged upper limit on strain amplitude will be improved by about 3 orders of magnitude over existing limits.

On protection of Freedom's solar dynamic radiator from the orbital debris environment. Part 1: Preliminary analyses and testing

NASA Technical Reports Server (NTRS)

Rhatigan, Jennifer L.; Christiansen, Eric L.; Fleming, Michael L.

1990-01-01

A great deal of experimentation and analysis was performed to quantify penetration thresholds of components which will experience orbital debris impacts. Penetration was found to depend upon mission specific parameters such as orbital altitude, inclination, and orientation of the component; and upon component specific parameters such as material, density and the geometry particular to its shielding. Experimental results are highly dependent upon shield configuration and cannot be extrapolated with confidence to alternate shield configurations. Also, current experimental capabilities are limited to velocities which only approach the lower limit of predicted orbital debris velocities. Therefore, prediction of the penetrating particle size for a particular component having a complex geometry remains highly uncertain. An approach is described which was developed to assess on-orbit survivability of the solar dynamic radiator due to micrometeoroid and space debris impacts. Preliminary analyses are presented to quantify the solar dynamic radiator survivability, and include the type of particle and particle population expected to defeat the radiator bumpering (i.e., penetrate a fluid flow tube). Results of preliminary hypervelocity impact testing performed on radiator panel samples (in the 6 to 7 km/sec velocity range) are also presented. Plans for further analyses and testing are discussed. These efforts are expected to lead to a radiator design which will perform to requirements over the expected lifetime.

Constraints on a new post-general relativity cosmological parameter

NASA Astrophysics Data System (ADS)

Caldwell, Robert; Cooray, Asantha; Melchiorri, Alessandro

2007-07-01

A new cosmological variable is introduced to characterize the degree of departure from Einstein’s general relativity with a cosmological constant. The new parameter, ϖ, is the cosmological analog of γ, the parametrized post-Newtonian variable which measures the amount of spacetime curvature per unit mass. In the cosmological context, ϖ measures the difference between the Newtonian and longitudinal potentials in response to the same matter sources, as occurs in certain scalar-tensor theories of gravity. Equivalently, ϖ measures the scalar shear fluctuation in a dark-energy component. In the context of a vanilla, cosmological constant-dominated universe, a nonzero ϖ signals a departure from general relativity or a fluctuating cosmological constant. Using a phenomenological model for the time evolution ϖ=ϖ0ρDE/ρM which depends on the ratio of energy density in the cosmological constant to the matter density at each epoch, it is shown that the observed cosmic microwave background temperature anisotropies limit the overall normalization constant to be -0.4<ϖ0<0.1 at the 95% confidence level. Existing measurements of the cross-correlations of the cosmic microwave background with large-scale structure further limit ϖ0>-0.2 at the 95% CL. In the future, integrated Sachs-Wolfe and weak lensing measurements can more tightly constrain ϖ0, providing a valuable clue to the nature of dark energy and the validity of general relativity.

Pulsar Timing Array Based Search for Supermassive Black Hole Binaries in the Square Kilometer Array Era.

PubMed

Wang, Yan; Mohanty, Soumya D

2017-04-14

The advent of next generation radio telescope facilities, such as the Square Kilometer Array (SKA), will usher in an era where a pulsar timing array (PTA) based search for gravitational waves (GWs) will be able to use hundreds of well timed millisecond pulsars rather than the few dozens in existing PTAs. A realistic assessment of the performance of such an extremely large PTA must take into account the data analysis challenge posed by an exponential increase in the parameter space volume due to the large number of so-called pulsar phase parameters. We address this problem and present such an assessment for isolated supermassive black hole binary (SMBHB) searches using a SKA era PTA containing 10^{3} pulsars. We find that an all-sky search will be able to confidently detect nonevolving sources with a redshifted chirp mass of 10^{10}  M_{⊙} out to a redshift of about 28 (corresponding to a rest-frame chirp mass of 3.4×10^{8}  M_{⊙}). We discuss the important implications that the large distance reach of a SKA era PTA has on GW observations from optically identified SMBHB candidates. If no SMBHB detections occur, a highly unlikely scenario in the light of our results, the sky-averaged upper limit on strain amplitude will be improved by about 3 orders of magnitude over existing limits.

Muon Neutrino Disappearance Measurement at MINOS+

NASA Astrophysics Data System (ADS)

Carroll, T. J.

2017-09-01

We report new measurements of neutrino oscillation parameters from the MINOS+ experiment using the first two years of accelerator beam exposure combined with the complete set of accelerator and atmospheric data from MINOS. The analysis combined νµ disappearance and νe appearance data using the three-flavor oscillation formalism. Our results give the confidence limits ≤ft| {Δ m32^2} \\right| = ≤ft[ {2.33 - 2.51} \\right] × {10 - 3}{{ e}}{{{V}}^2} (68% C.L.) and sin2 θ 23 = 0.35 - 0.65 (90% C.L.) for normal hierarchy, and ≤ft| {Δ m32^2} \\right| = ≤ft[ {2.37 - 2.57} \\right] × {10 - 3}{{ e}}{{{V}}^2} (68% C.L.) and sin2 θ 23 = 0.35 - 0.66 (90% C.L.) for inverted hierarchy.

Study of {Lambda}-{Lambda} oscillation in quantum coherent {Lambda}{Lambda} by using J/{psi}{yields}{Lambda}{Lambda} decay

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

Kang Xianwei; Department of Physics, Henan Normal University, Xinxiang 453007; Li Haibo

2010-03-01

We discuss the possibility of searching for the {Lambda}-{Lambda} oscillations for coherent {Lambda}{Lambda} production in the J/{psi}{yields}{Lambda}{Lambda} decay process. The sensitivity of measurement of {Lambda}-{Lambda} oscillation in the external field at BES-III experiment is considered. These considerations indicate an alternative way to probe the {Delta}B=2 amplitude in addition to neutron oscillation experiments. Both coherent and time-dependent information can be used to extract the {Lambda}-{Lambda} oscillation parameter. With one year's luminosity at BES-III, we can set an upper limit of {delta}m{sub {Lambda}{Lambda}<}10{sup -15} MeV at 90% confidence level, corresponding to about 10{sup -6} s of {Lambda}-{Lambda} oscillation time.

A new bound on axion-like particles

NASA Astrophysics Data System (ADS)

Marsh, M. C. David; Russell, Helen R.; Fabian, Andrew C.; McNamara, Brian R.; Nulsen, Paul; Reynolds, Christopher S.

2017-12-01

Axion-like particles (ALPs) and photons can quantum mechanically interconvert when propagating through magnetic fields, and ALP-photon conversion may induce oscillatory features in the spectra of astrophysical sources. We use deep (370 ks), short frame time Chandra observations of the bright nucleus at the centre of the radio galaxy M87 in the Virgo cluster to search for signatures of light ALPs. The absence of substantial irregularities in the X-ray power-law spectrum leads to a new upper limit on the photon-ALP coupling, gaγ: using a very conservative model of the cluster magnetic field consistent with Faraday rotation measurements from M87 and M84, we find gaγ < 2.6 × 10-12 GeV-1 at 95% confidence level for ALP masses ma <= 10‑13 eV. Other consistent magnetic field models lead to stronger limits of gaγ lesssim 1.1–1.5 × 10‑12 GeV‑1. These bounds are all stronger than the limit inferred from the absence of a gamma-ray burst from SN1987A, and rule out a substantial fraction of the parameter space accessible to future experiments such as ALPS-II and IAXO.

An upper limit on the stochastic gravitational-wave background of cosmological origin.

PubMed

Abbott, B P; Abbott, R; Acernese, F; Adhikari, R; Ajith, P; Allen, B; Allen, G; Alshourbagy, M; Amin, R S; Anderson, S B; Anderson, W G; Antonucci, F; Aoudia, S; Arain, M A; Araya, M; Armandula, H; Armor, P; Arun, K G; Aso, Y; Aston, S; Astone, P; Aufmuth, P; Aulbert, C; Babak, S; Baker, P; Ballardin, G; Ballmer, S; Barker, C; Barker, D; Barone, F; Barr, B; Barriga, P; Barsotti, L; Barsuglia, M; Barton, M A; Bartos, I; Bassiri, R; Bastarrika, M; Bauer, Th S; Behnke, B; Beker, M; Benacquista, M; Betzwieser, J; Beyersdorf, P T; Bigotta, S; Bilenko, I A; Billingsley, G; Birindelli, S; Biswas, R; Bizouard, M A; Black, E; Blackburn, J K; Blackburn, L; Blair, D; Bland, B; Boccara, C; Bodiya, T P; Bogue, L; Bondu, F; Bonelli, L; Bork, R; Boschi, V; Bose, S; Bosi, L; Braccini, S; Bradaschia, C; Brady, P R; Braginsky, V B; Brand, J F J van den; Brau, J E; Bridges, D O; Brillet, A; Brinkmann, M; Brisson, V; Van Den Broeck, C; Brooks, A F; Brown, D A; Brummit, A; Brunet, G; Bullington, A; Bulten, H J; Buonanno, A; Burmeister, O; Buskulic, D; Byer, R L; Cadonati, L; Cagnoli, G; Calloni, E; Camp, J B; Campagna, E; Cannizzo, J; Cannon, K C; Canuel, B; Cao, J; Carbognani, F; Cardenas, L; Caride, S; Castaldi, G; Caudill, S; Cavaglià, M; Cavalier, F; Cavalieri, R; Cella, G; Cepeda, C; Cesarini, E; Chalermsongsak, T; Chalkley, E; Charlton, P; Chassande-Mottin, E; Chatterji, S; Chelkowski, S; Chen, Y; Christensen, N; Chung, C T Y; Clark, D; Clark, J; Clayton, J H; Cleva, F; Coccia, E; Cokelaer, T; Colacino, C N; Colas, J; Colla, A; Colombini, M; Conte, R; Cook, D; Corbitt, T R C; Corda, C; Cornish, N; Corsi, A; Coulon, J-P; Coward, D; Coyne, D C; Creighton, J D E; Creighton, T D; Cruise, A M; Culter, R M; Cumming, A; Cunningham, L; Cuoco, E; Danilishin, S L; D'Antonio, S; Danzmann, K; Dari, A; Dattilo, V; Daudert, B; Davier, M; Davies, G; Daw, E J; Day, R; De Rosa, R; Debra, D; Degallaix, J; Del Prete, M; Dergachev, V; Desai, S; Desalvo, R; Dhurandhar, S; Di Fiore, L; Di Lieto, A; Di Paolo Emilio, M; Di Virgilio, A; Díaz, M; Dietz, A; Donovan, F; Dooley, K L; Doomes, E E; Drago, M; Drever, R W P; Dueck, J; Duke, I; Dumas, J-C; Dwyer, J G; Echols, C; Edgar, M; Effler, A; Ehrens, P; Ely, G; Espinoza, E; Etzel, T; Evans, M; Evans, T; Fafone, V; Fairhurst, S; Faltas, Y; Fan, Y; Fazi, D; Fehrmann, H; Ferrante, I; Fidecaro, F; Finn, L S; Fiori, I; Flaminio, R; Flasch, K; Foley, S; Forrest, C; Fotopoulos, N; Fournier, J-D; Franc, J; Franzen, A; Frasca, S; Frasconi, F; Frede, M; Frei, M; Frei, Z; Freise, A; Frey, R; Fricke, T; Fritschel, P; Frolov, V V; Fyffe, M; Galdi, V; Gammaitoni, L; Garofoli, J A; Garufi, F; Genin, E; Gennai, A; Gholami, I; Giaime, J A; Giampanis, S; Giardina, K D; Giazotto, A; Goda, K; Goetz, E; Goggin, L M; González, G; Gorodetsky, M L; Gobler, S; Gouaty, R; Granata, M; Granata, V; Grant, A; Gras, S; Gray, C; Gray, M; Greenhalgh, R J S; Gretarsson, A M; Greverie, C; Grimaldi, F; Grosso, R; Grote, H; Grunewald, S; Guenther, M; Guidi, G; Gustafson, E K; Gustafson, R; Hage, B; Hallam, J M; Hammer, D; Hammond, G D; Hanna, C; Hanson, J; Harms, J; Harry, G M; Harry, I W; Harstad, E D; Haughian, K; Hayama, K; Heefner, J; Heitmann, H; Hello, P; Heng, I S; Heptonstall, A; Hewitson, M; Hild, S; Hirose, E; Hoak, D; Hodge, K A; Holt, K; Hosken, D J; Hough, J; Hoyland, D; Huet, D; Hughey, B; Huttner, S H; Ingram, D R; Isogai, T; Ito, M; Ivanov, A; Johnson, B; Johnson, W W; Jones, D I; Jones, G; Jones, R; Sancho de la Jordana, L; Ju, L; Kalmus, P; Kalogera, V; Kandhasamy, S; Kanner, J; Kasprzyk, D; Katsavounidis, E; Kawabe, K; Kawamura, S; Kawazoe, F; Kells, W; Keppel, D G; Khalaidovski, A; Khalili, F Y; Khan, R; Khazanov, E; King, P; Kissel, J S; Klimenko, S; Kokeyama, K; Kondrashov, V; Kopparapu, R; Koranda, S; Kozak, D; Krishnan, B; Kumar, R; Kwee, P; La Penna, P; Lam, P K; Landry, M; Lantz, B; Laval, M; Lazzarini, A; Lei, H; Lei, M; Leindecker, N; Leonor, I; Leroy, N; Letendre, N; Li, C; Lin, H; Lindquist, P E; Littenberg, T B; Lockerbie, N A; Lodhia, D; Longo, M; Lorenzini, M; Loriette, V; Lormand, M; Losurdo, G; Lu, P; Lubinski, M; Lucianetti, A; Lück, H; Machenschalk, B; Macinnis, M; Mackowski, J-M; Mageswaran, M; Mailand, K; Majorana, E; Man, N; Mandel, I; Mandic, V; Mantovani, M; Marchesoni, F; Marion, F; Márka, S; Márka, Z; Markosyan, A; Markowitz, J; Maros, E; Marque, J; Martelli, F; Martin, I W; Martin, R M; Marx, J N; Mason, K; Masserot, A; Matichard, F; Matone, L; Matzner, R A; Mavalvala, N; McCarthy, R; McClelland, D E; McGuire, S C; McHugh, M; McIntyre, G; McKechan, D J A; McKenzie, K; Mehmet, M; Melatos, A; Melissinos, A C; Mendell, G; Menéndez, D F; Menzinger, F; Mercer, R A; Meshkov, S; Messenger, C; Meyer, M S; Michel, C; Milano, L; Miller, J; Minelli, J; Minenkov, Y; Mino, Y; Mitrofanov, V P; Mitselmakher, G; Mittleman, R; Miyakawa, O; Moe, B; Mohan, M; Mohanty, S D; Mohapatra, S R P; Moreau, J; Moreno, G; Morgado, N; Morgia, A; Morioka, T; Mors, K; Mosca, S; Mossavi, K; Mours, B; Mowlowry, C; Mueller, G; Muhammad, D; Mühlen, H Zur; Mukherjee, S; Mukhopadhyay, H; Mullavey, A; Müller-Ebhardt, H; Munch, J; Murray, P G; Myers, E; Myers, J; Nash, T; Nelson, J; Neri, I; Newton, G; Nishizawa, A; Nocera, F; Numata, K; Ochsner, E; O'Dell, J; Ogin, G H; O'Reilly, B; O'Shaughnessy, R; Ottaway, D J; Ottens, R S; Overmier, H; Owen, B J; Pagliaroli, G; Palomba, C; Pan, Y; Pankow, C; Paoletti, F; Papa, M A; Parameshwaraiah, V; Pardi, S; Pasqualetti, A; Passaquieti, R; Passuello, D; Patel, P; Pedraza, M; Penn, S; Perreca, A; Persichetti, G; Pichot, M; Piergiovanni, F; Pierro, V; Pinard, L; Pinto, I M; Pitkin, M; Pletsch, H J; Plissi, M V; Poggiani, R; Postiglione, F; Principe, M; Prix, R; Prodi, G A; Prokhorov, L; Punken, O; Punturo, M; Puppo, P; Putten, S van der; Quetschke, V; Raab, F J; Rabaste, O; Rabeling, D S; Radkins, H; Raffai, P; Raics, Z; Rainer, N; Rakhmanov, M; Rapagnani, P; Raymond, V; Re, V; Reed, C M; Reed, T; Regimbau, T; Rehbein, H; Reid, S; Reitze, D H; Ricci, F; Riesen, R; Riles, K; Rivera, B; Roberts, P; Robertson, N A; Robinet, F; Robinson, C; Robinson, E L; Rocchi, A; Roddy, S; Rolland, L; Rollins, J; Romano, J D; Romano, R; Romie, J H; Röver, C; Rowan, S; Rüdiger, A; Ruggi, P; Russell, P; Ryan, K; Sakata, S; Salemi, F; Sandberg, V; Sannibale, V; Santamaría, L; Saraf, S; Sarin, P; Sassolas, B; Sathyaprakash, B S; Sato, S; Satterthwaite, M; Saulson, P R; Savage, R; Savov, P; Scanlan, M; Schilling, R; Schnabel, R; Schofield, R; Schulz, B; Schutz, B F; Schwinberg, P; Scott, J; Scott, S M; Searle, A C; Sears, B; Seifert, F; Sellers, D; Sengupta, A S; Sentenac, D; Sergeev, A; Shapiro, B; Shawhan, P; Shoemaker, D H; Sibley, A; Siemens, X; Sigg, D; Sinha, S; Sintes, A M; Slagmolen, B J J; Slutsky, J; van der Sluys, M V; Smith, J R; Smith, M R; Smith, N D; Somiya, K; Sorazu, B; Stein, A; Stein, L C; Steplewski, S; Stochino, A; Stone, R; Strain, K A; Strigin, S; Stroeer, A; Sturani, R; Stuver, A L; Summerscales, T Z; Sun, K-X; Sung, M; Sutton, P J; Swinkels, B L; Szokoly, G P; Talukder, D; Tang, L; Tanner, D B; Tarabrin, S P; Taylor, J R; Taylor, R; Terenzi, R; Thacker, J; Thorne, K A; Thorne, K S; Thüring, A; Tokmakov, K V; Toncelli, A; Tonelli, M; Torres, C; Torrie, C; Tournefier, E; Travasso, F; Traylor, G; Trias, M; Trummer, J; Ugolini, D; Ulmen, J; Urbanek, K; Vahlbruch, H; Vajente, G; Vallisneri, M; Vass, S; Vaulin, R; Vavoulidis, M; Vecchio, A; Vedovato, G; van Veggel, A A; Veitch, J; Veitch, P; Veltkamp, C; Verkindt, D; Vetrano, F; Viceré, A; Villar, A; Vinet, J-Y; Vocca, H; Vorvick, C; Vyachanin, S P; Waldman, S J; Wallace, L; Ward, H; Ward, R L; Was, M; Weidner, A; Weinert, M; Weinstein, A J; Weiss, R; Wen, L; Wen, S; Wette, K; Whelan, J T; Whitcomb, S E; Whiting, B F; Wilkinson, C; Willems, P A; Williams, H R; Williams, L; Willke, B; Wilmut, I; Winkelmann, L; Winkler, W; Wipf, C C; Wiseman, A G; Woan, G; Wooley, R; Worden, J; Wu, W; Yakushin, I; Yamamoto, H; Yan, Z; Yoshida, S; Yvert, M; Zanolin, M; Zhang, J; Zhang, L; Zhao, C; Zotov, N; Zucker, M E; Zweizig, J

2009-08-20

A stochastic background of gravitational waves is expected to arise from a superposition of a large number of unresolved gravitational-wave sources of astrophysical and cosmological origin. It should carry unique signatures from the earliest epochs in the evolution of the Universe, inaccessible to standard astrophysical observations. Direct measurements of the amplitude of this background are therefore of fundamental importance for understanding the evolution of the Universe when it was younger than one minute. Here we report limits on the amplitude of the stochastic gravitational-wave background using the data from a two-year science run of the Laser Interferometer Gravitational-wave Observatory (LIGO). Our result constrains the energy density of the stochastic gravitational-wave background normalized by the critical energy density of the Universe, in the frequency band around 100 Hz, to be <6.9 x 10(-6) at 95% confidence. The data rule out models of early Universe evolution with relatively large equation-of-state parameter, as well as cosmic (super)string models with relatively small string tension that are favoured in some string theory models. This search for the stochastic background improves on the indirect limits from Big Bang nucleosynthesis and cosmic microwave background at 100 Hz.

Application of tolerance limits to the characterization of image registration performance.

PubMed

Fedorov, Andriy; Wells, William M; Kikinis, Ron; Tempany, Clare M; Vangel, Mark G

2014-07-01

Deformable image registration is used increasingly in image-guided interventions and other applications. However, validation and characterization of registration performance remain areas that require further study. We propose an analysis methodology for deriving tolerance limits on the initial conditions for deformable registration that reliably lead to a successful registration. This approach results in a concise summary of the probability of registration failure, while accounting for the variability in the test data. The (β, γ) tolerance limit can be interpreted as a value of the input parameter that leads to successful registration outcome in at least 100β% of cases with the 100γ% confidence. The utility of the methodology is illustrated by summarizing the performance of a deformable registration algorithm evaluated in three different experimental setups of increasing complexity. Our examples are based on clinical data collected during MRI-guided prostate biopsy registered using publicly available deformable registration tool. The results indicate that the proposed methodology can be used to generate concise graphical summaries of the experiments, as well as a probabilistic estimate of the registration outcome for a future sample. Its use may facilitate improved objective assessment, comparison and retrospective stress-testing of deformable.

A Search for Supersymmetric Higgs Bosons in the Di-tau Decay Mode in Proton - Anti-proton Collisions at 1.8 TeV

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

Connolly, Amy Lynn

A search for directly produced Supersymmetric Higgs Bosons has been performed in the di-tau decay channel in 86.3 ± 3.5 pb -1 of data collected by CDF during Run1b at the Tevatron. They search for events where one tau decays to an electron and the other tau decays hadronically. They perform a counting experiment and set limits on the cross section for Higgs production in the high tan β region of the m A-tan β plane. For a benchmark parameter space point where m A = 100 and tan β = 50, they set a 95% confidence level upper limitmore » at 891 pb compared to the theoretically predicted cross section of 122 pb. For events where the tau candidates are not back-to-back, they utilize a di-tau mass reconstruction technique for the first time on hadron collider data. Limits based on a likelihood binned in di-tau mass from non-back-to-back events alone are weaker than the limits obtained from the counting experiment using the full di-tau sample.« less

confFuse: High-Confidence Fusion Gene Detection across Tumor Entities.

PubMed

Huang, Zhiqin; Jones, David T W; Wu, Yonghe; Lichter, Peter; Zapatka, Marc

2017-01-01

Background: Fusion genes play an important role in the tumorigenesis of many cancers. Next-generation sequencing (NGS) technologies have been successfully applied in fusion gene detection for the last several years, and a number of NGS-based tools have been developed for identifying fusion genes during this period. Most fusion gene detection tools based on RNA-seq data report a large number of candidates (mostly false positives), making it hard to prioritize candidates for experimental validation and further analysis. Selection of reliable fusion genes for downstream analysis becomes very important in cancer research. We therefore developed confFuse, a scoring algorithm to reliably select high-confidence fusion genes which are likely to be biologically relevant. Results: confFuse takes multiple parameters into account in order to assign each fusion candidate a confidence score, of which score ≥8 indicates high-confidence fusion gene predictions. These parameters were manually curated based on our experience and on certain structural motifs of fusion genes. Compared with alternative tools, based on 96 published RNA-seq samples from different tumor entities, our method can significantly reduce the number of fusion candidates (301 high-confidence from 8,083 total predicted fusion genes) and keep high detection accuracy (recovery rate 85.7%). Validation of 18 novel, high-confidence fusions detected in three breast tumor samples resulted in a 100% validation rate. Conclusions: confFuse is a novel downstream filtering method that allows selection of highly reliable fusion gene candidates for further downstream analysis and experimental validations. confFuse is available at https://github.com/Zhiqin-HUANG/confFuse.

Constraints on the Generalized Chaplygin Gas Model from Recent Supernova Data and Baryonic Acoustic Oscillations

NASA Astrophysics Data System (ADS)

Wu, Puxun; Yu, Hongwei

2007-04-01

Constraints from the Gold sample Type Ia supernova (SN Ia) data, the Supernova Legacy Survey (SNLS) SN Ia data, and the size of the baryonic acoustic oscillation (BAO) peak found in the Sloan Digital Sky Survey (SDSS) on the generalized Chaplygin gas (GCG) model, proposed as a candidate for the unified dark matter-dark energy scenario (UDME), are examined in the cases of both a spatially flat and a spatially curved universe. Our results reveal that the GCG model is consistent with a flat universe up to the 68% confidence level, and the model parameters are within the allowed parameter ranges of the GCG as a candidate for UDME. Meanwhile, we find that in the flat case, both the Gold sample + SDSS BAO data and the SNLS sample + SDSS BAO data break the degeneracy of As and α and allow for the scenario of a cosmological constant plus dark matter (α=0) at the 68% confidence level, although they rule out the standard Chaplygin gas model (α=1) at the 99% confidence level. However, for the case without a flat prior, the SNLS SN Ia + SDSS BAO data do not break the degeneracy between As and α, and they allow for ΛCDM (α=0) and the standard Chaplygin gas model (α=1) at a 68% confidence level, while the Gold SN Ia + SDSS BAO break the degeneracy of As and α and rule out ΛCDM at a 68% confidence level and the standard Chaplygin gas model at a 99% confidence level.

Challenging the assumption of habitat limitation: An example from centrarchid fishes over an intermediate spatial scale

USGS Publications Warehouse

Gutreuter, S.

2004-01-01

Habitat rehabilitation efforts are predicated on the frequently untested assumption that habitat is limiting to populations. These efforts are typically costly and will be ineffective if habitat is not limiting. Therefore it is important to assess, rather than assume, habitat limitation wherever habitat rehabilitation projects are considered. Catch-count data from a standardized probability-based stratified-random monitoring programme were examined for indirect evidence of backwater habitat limitation by centrarchid fishes in the Upper Mississippi River System. The monitoring design enabled fitting statistical models of the association between mean catch at the spatial scale of tens of river kilometres and the percentage of contiguous aquatic area in backwater at least 1 m deep by maximizing a stratum-area weighted negative binomial log-likelihood function. Statistical models containing effects for backwater limitation failed to account for substantial variation in the data. However, 95% confidence intervals on the backwater parameter estimates excluded zero, indicating that population abundance may be limited by backwater prevalence where backwaters are extremely scarce. The combined results indicate, at most, a weak signal of backwater limitation where backwaters are extremely scarce in the lower reaches, but not elsewhere in the Upper Mississippi River System. This suggests that habitat restoration projects designed to increase the area of backwaters suitable for winter survival of centrarchids are unlikely to produce measurable benefits over intermediate spatial scales in much of the Upper Mississippi River System, and indicates the importance of correct identification of limiting processes. Published in 2004 by John Wiley and Sons, Ltd.

Estimation of the uncertainty of analyte concentration from the measurement uncertainty.

PubMed

Brown, Simon; Cooke, Delwyn G; Blackwell, Leonard F

2015-09-01

Ligand-binding assays, such as immunoassays, are usually analysed using standard curves based on the four-parameter and five-parameter logistic models. An estimate of the uncertainty of an analyte concentration obtained from such curves is needed for confidence intervals or precision profiles. Using a numerical simulation approach, it is shown that the uncertainty of the analyte concentration estimate becomes significant at the extremes of the concentration range and that this is affected significantly by the steepness of the standard curve. We also provide expressions for the coefficient of variation of the analyte concentration estimate from which confidence intervals and the precision profile can be obtained. Using three examples, we show that the expressions perform well.

Evaluation of a single-item screening question to detect limited health literacy in peritoneal dialysis patients.

PubMed

Jain, Deepika; Sheth, Heena; Bender, Filitsa H; Weisbord, Steven D; Green, Jamie A

2014-01-01

Studies have shown that a single-item question might be useful in identifying patients with limited health literacy. However, the utility of the approach has not been studied in patients receiving maintenance peritoneal dialysis (PD). We assessed health literacy in a cohort of 31 PD patients by administering the Rapid Estimate of Adult Literacy in Medicine (REALM) and a single-item health literacy (SHL) screening question "How confident are you filling out medical forms by yourself?" (Extremely, Quite a bit, Somewhat, A little bit, or Not at all). To determine the accuracy of the single-item question for detecting limited health literacy, we performed sensitivity and specificity analyses of the SHL and plotted the area under the receiver operating characteristic (AUROC) curve using the REALM as a reference standard. Using a cut-off of "Somewhat" or less confident, the sensitivity of the SHL for detecting limited health literacy was 80%, and the specificity was 88%. The positive likelihood ratio was 6.9. The SHL had an AUROC of 0.79 (95% confidence interval: 0.52 to 1.00). Our results show that the SHL could be effective in detecting limited health literacy in PD patients.

Confidence in the efficacy and safety of dietary supplements among United States active duty army personnel.

PubMed

Carvey, Christina E; Farina, Emily K; Lieberman, Harris R

2012-10-10

United States Army Soldiers regularly use dietary supplements (DS) to promote general health, enhance muscle strength, and increase energy, but limited scientific evidence supports the use of many DS for these benefits. This study investigated factors associated with Soldiers' confidence in the efficacy and safety of DS, and assessed Soldiers' knowledge of federal DS regulatory requirements. Between 2006 and 2007, 990 Soldiers were surveyed at 11 Army bases world-wide to assess their confidence in the effectiveness and safety of DS, knowledge of federal DS regulations, demographic characteristics, lifestyle-behaviors and DS use. A majority of Soldiers were at least somewhat confident that DS work as advertised (67%) and thought they are safe to consume (71%). Confidence in both attributes was higher among regular DS users than non-users. Among users, confidence in both attributes was positively associated with rank, self-rated diet quality and fitness level, education, and having never experienced an apparent DS-related adverse event. Fewer than half of Soldiers knew the government does not require manufacturers to demonstrate efficacy, and almost a third incorrectly believed there are effective pre-market federal safety requirements for DS. Despite limited scientific evidence supporting the purported benefits and safety of many popular DS, most Soldiers were confident that DS are effective and safe. The positive associations between confidence and DS use should be considered when developing DS-related interventions or policies. Additionally, education to clarify Soldiers' misperceptions about federal DS safety and efficacy regulations is warranted.

Transition Services: An Investigation of the Knowledge, Confidence, and Practice of Special Education Teachers in District of Columbia Public Charter High Schools

ERIC Educational Resources Information Center

Henry, Wallace R., III

2015-01-01

This study was intended to enhance the limited research on the knowledge and confidence of special education teachers in public education regarding transition services and the quality of transition plans they develop. The key variables examined in this study are knowledge, confidence, and the quality of student transition plans. The sample…

Another look at confidence intervals: Proposal for a more relevant and transparent approach

NASA Astrophysics Data System (ADS)

Biller, Steven D.; Oser, Scott M.

2015-02-01

The behaviors of various confidence/credible interval constructions are explored, particularly in the region of low event numbers where methods diverge most. We highlight a number of challenges, such as the treatment of nuisance parameters, and common misconceptions associated with such constructions. An informal survey of the literature suggests that confidence intervals are not always defined in relevant ways and are too often misinterpreted and/or misapplied. This can lead to seemingly paradoxical behaviors and flawed comparisons regarding the relevance of experimental results. We therefore conclude that there is a need for a more pragmatic strategy which recognizes that, while it is critical to objectively convey the information content of the data, there is also a strong desire to derive bounds on model parameter values and a natural instinct to interpret things this way. Accordingly, we attempt to put aside philosophical biases in favor of a practical view to propose a more transparent and self-consistent approach that better addresses these issues.

Monitoring of deep brain temperature in infants using multi-frequency microwave radiometry and thermal modelling.

PubMed

Han, J W; Van Leeuwen, G M; Mizushina, S; Van de Kamer, J B; Maruyama, K; Sugiura, T; Azzopardi, D V; Edwards, A D

2001-07-01

In this study we present a design for a multi-frequency microwave radiometer aimed at prolonged monitoring of deep brain temperature in newborn infants and suitable for use during hypothermic neural rescue therapy. We identify appropriate hardware to measure brightness temperature and evaluate the accuracy of the measurements. We describe a method to estimate the tissue temperature distribution from measured brightness temperatures which uses the results of numerical simulations of the tissue temperature as well as the propagation of the microwaves in a realistic detailed three-dimensional infant head model. The temperature retrieval method is then used to evaluate how the statistical fluctuations in the measured brightness temperatures limit the confidence interval for the estimated temperature: for an 18 degrees C temperature differential between cooled surface and deep brain we found a standard error in the estimated central brain temperature of 0.75 degrees C. Evaluation of the systematic errors arising from inaccuracies in model parameters showed that realistic deviations in tissue parameters have little impact compared to uncertainty in the thickness of the bolus between the receiving antenna and the infant's head or in the skull thickness. This highlights the need to pay particular attention to these latter parameters in future practical implementation of the technique.

The ROC Toolbox: A toolbox for analyzing receiver-operating characteristics derived from confidence ratings.

PubMed

Koen, Joshua D; Barrett, Frederick S; Harlow, Iain M; Yonelinas, Andrew P

2017-08-01

Signal-detection theory, and the analysis of receiver-operating characteristics (ROCs), has played a critical role in the development of theories of episodic memory and perception. The purpose of the current paper is to present the ROC Toolbox. This toolbox is a set of functions written in the Matlab programming language that can be used to fit various common signal detection models to ROC data obtained from confidence rating experiments. The goals for developing the ROC Toolbox were to create a tool (1) that is easy to use and easy for researchers to implement with their own data, (2) that can flexibly define models based on varying study parameters, such as the number of response options (e.g., confidence ratings) and experimental conditions, and (3) that provides optimal routines (e.g., Maximum Likelihood estimation) to obtain parameter estimates and numerous goodness-of-fit measures.The ROC toolbox allows for various different confidence scales and currently includes the models commonly used in recognition memory and perception: (1) the unequal variance signal detection (UVSD) model, (2) the dual process signal detection (DPSD) model, and (3) the mixture signal detection (MSD) model. For each model fit to a given data set the ROC toolbox plots summary information about the best fitting model parameters and various goodness-of-fit measures. Here, we present an overview of the ROC Toolbox, illustrate how it can be used to input and analyse real data, and finish with a brief discussion on features that can be added to the toolbox.

Spacecraft utility and the development of confidence intervals for criticality of anomalies

NASA Technical Reports Server (NTRS)

Williams, R. E.

1980-01-01

The concept of spacecraft utility, a measure of its performance in orbit, is discussed and its formulation is described. Performance is defined in terms of the malfunctions that occur and the criticality to the mission of these malfunctions. Different approaches to establishing average or expected values of criticality are discussed and confidence intervals are developed for parameters used in the computation of utility.

Improved Limits on Gamma-Ray Burst Repetition from BATSE

NASA Technical Reports Server (NTRS)

Tegmark, Max; Hartmann, Dieter H.; Briggs, Michael S.; Hakkila, Jon; Meegan, Charles A.

1996-01-01

We tighten previous upper limits on gamma-ray burst repetition by analyzing the angular power spectrum of the BATSE 3B catalog of 1122 bursts. At 95% confidence, we find that no more than 2% of all observed bursts can be labeled as repeaters, even if no sources are observed to repeat more than once. If a fraction f of all observed bursts can be labeled as repeaters that are observed to burst upsilon times each, then all models with (upsilon - 1)f greater than or equal to 0.05 are ruled out at 99% confidence, as compared to the best previous 99% limit (upsilon - 1)f greater than or equal to 0.27. At 95% confidence, our new limit is (upsilon - 1)f greater than or equal to 0.02. Thus, even a cluster of six events from a single source would have caused excess power above that present in the 3B catalog. We conclude that the current BATSE data are consistent with no repetition of classical gamma-ray bursts and that any repeater model is severely constrained by the near-perfect isotropy of their angular distribution.

Improved Limits on Gamma-Ray Burst Repetition from BATSE

NASA Technical Reports Server (NTRS)

Tegmark, Max; Hartmann, Dieter H.; Briggs, Michael S.; Meegan, Charles A.; Hakkila, Jon

1996-01-01

We tighten previous upper limits on gamma-ray burst repetition by analyzing the angular power spectrum of the BATSE 3B catalog of 1122 bursts. At 95% confidence, we find that no more than 2% of all observed bursts can be labeled as repeaters, even if no sources are observed to repeat more than once. If a fraction f of all observed bursts can be labeled as repeaters that are observed to burst nu times each, then all models with (nu - 1)f greater than or equal to 0.05 are ruled out at 99% confidence, as compared to the best previous 99% limit (nu - 1)f greater than or equal to 0.27. At 95% confidence, our new limit is (nu - 1)f greater than or equal to 0.02. Thus, even a cluster of six events from a single source would have caused excess power above that present in the 3B catalog. We conclude that the current BATSE data are consistent with no repetition of classical gamma-ray bursts and that any repeater model is severely constrained by the near-perfect isotropy of their angular dis- tribution.

Right ventricular dysfunction affects survival after surgical left ventricular restoration.

PubMed

Couperus, Lotte E; Delgado, Victoria; Palmen, Meindert; van Vessem, Marieke E; Braun, Jerry; Fiocco, Marta; Tops, Laurens F; Verwey, Harriëtte F; Klautz, Robert J M; Schalij, Martin J; Beeres, Saskia L M A

2017-04-01

Several clinical and left ventricular parameters have been associated with prognosis after surgical left ventricular restoration in patients with ischemic heart failure. The aim of this study was to determine the prognostic value of right ventricular function. A total of 139 patients with ischemic heart failure (62 ± 10 years; 79% were male; left ventricular ejection fraction 27% ± 7%) underwent surgical left ventricular restoration. Biventricular function was assessed with echocardiography before surgery. The independent association between all-cause mortality and right ventricular fractional area change, tricuspid annular plane systolic excursion, and right ventricular longitudinal peak systolic strain was assessed. The additive effect of multiple impaired right ventricular parameters on mortality also was assessed. Baseline right ventricular fractional area change was 42% ± 9%, tricuspid annular plane systolic excursion was 18 ± 3 mm, and right ventricular longitudinal peak systolic strain was -24% ± 7%. Within 30 days after surgery, 15 patients died. Right ventricular fractional area change (hazard ratio, 0.93; 95% confidence interval, 0.88-0.98; P < .01), tricuspid annular plane systolic excursion (hazard ratio, 0.80; 95% confidence interval, 0.66-0.96; P = .02), and right ventricular longitudinal peak systolic strain (hazard ratio, 1.15; 95% confidence interval, 1.05-1.26; P < .01) were independently associated with 30-day mortality, after adjusting for left ventricular ejection fraction and aortic crossclamping time. Right ventricular function was impaired in 21%, 20%, and 27% of patients on the basis of right ventricular fractional area change, tricuspid annular plane systolic excursion, and right ventricular longitudinal peak systolic strain, respectively. Any echocardiographic parameter of right ventricular dysfunction was present in 39% of patients. The coexistence of several impaired right ventricular parameters per patient was independently associated with increased 30-day mortality (hazard ratio, 2.83; 95% confidence interval, 1.64-4.87, P < .01 per additional impaired parameter). Baseline right ventricular systolic dysfunction is independently associated with increased mortality in patients with ischemic heart failure undergoing surgical left ventricular restoration. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Validity Study of a Jump Mat Compared to the Reference Standard Force Plate.

PubMed

Rogan, Slavko; Radlinger, Lorenz; Imhasly, Caroline; Kneubuehler, Andrea; Hilfiker, Roger

2015-12-01

In the field of vertical jump diagnostics, force plates (FP) are the reference standard. Recently, despite a lack of evidence, jump mats have been used increasingly. Important factors in favor of jumping mats are their low cost and portability. This validity study compared the Haynl-Elektronik jump mat (HE jump mat) with the reference standard force plate. Ten healthy volunteers participated and each participant completed three series of five drop jumps (DJ). The parameters ground contact time (GCT) and vertical jump height (VJH) from the HE jump mat and the FP were used to evaluate the concurrent validity. The following statistical calculations were performed: Pearson's correlation (r), Bland-Altman plots (standard and for adjusted trend), and regression equations. The Bland-Altman plots suggest that the HE jump mat measures shorter contact times and higher jump heights than the FP. The trend-adjusted Bland-Altman plot shows higher mean differences and wider wing-spreads of confidence limits during longer GCT. During the VJH the mean differences and the wing-spreads of the confidence limits throughout the range present as relatively constant. The following regression equations were created, as close as possible to the true value: GCT = 5.920385 + 1.072293 × [value HE jump mat] and VJH = -1.73777 + 1.011156 × [value HE jump mat]. The HE jump mat can be recommended in relation to the validity of constraints. In this study, only a part of the quality criteria were examined. For the final recommendation it is advised to examine the HE jump mat on the other quality criteria (test-retest reliability, sensitivity change).

Using evolutionary computation to optimize an SVM used in detecting buried objects in FLIR imagery

NASA Astrophysics Data System (ADS)

Paino, Alex; Popescu, Mihail; Keller, James M.; Stone, Kevin

2013-06-01

In this paper we describe an approach for optimizing the parameters of a Support Vector Machine (SVM) as part of an algorithm used to detect buried objects in forward looking infrared (FLIR) imagery captured by a camera installed on a moving vehicle. The overall algorithm consists of a spot-finding procedure (to look for potential targets) followed by the extraction of several features from the neighborhood of each spot. The features include local binary pattern (LBP) and histogram of oriented gradients (HOG) as these are good at detecting texture classes. Finally, we project and sum each hit into UTM space along with its confidence value (obtained from the SVM), producing a confidence map for ROC analysis. In this work, we use an Evolutionary Computation Algorithm (ECA) to optimize various parameters involved in the system, such as the combination of features used, parameters on the Canny edge detector, the SVM kernel, and various HOG and LBP parameters. To validate our approach, we compare results obtained from an SVM using parameters obtained through our ECA technique with those previously selected by hand through several iterations of "guess and check".

Tables of Confidence Limits for Proportions

DTIC Science & Technology

1990-09-01

0.972 180 49 0.319 0.332 0,357 175 165 0.964 0.969 0.976 ISO 50 0.325 0.338 0.363 175 166 0.969 0.973 0.980 180 51 0.331 0.344 0.368 175 167 0.973 0.977...0.528 180 18 0.135 0 145 0.164 180 19 0.141 0.151 0.171 ISO 80 0.495 0,508 0.534 347 UPPER CONFIDENCE LIMIT FOR PROPORTIONS CONFIDENCE LEVEL...500 409 0.8401 0.8459 0.8565 500 355 0.7364 0.7434 0.7564 500 356 0.7383 0.7453 0.7582 500 410 0.8420 0.8478 0 8583 500 357 0.7402 0.7472 0.7602 500

Stock assessment of fishery target species in Lake Koka, Ethiopia.

PubMed

Tesfaye, Gashaw; Wolff, Matthias

2015-09-01

Effective management is essential for small-scale fisheries to continue providing food and livelihoods for households, particularly in developing countries where other options are often limited. Studies on the population dynamics and stock assessment on fishery target species are thus imperative to sustain their fisheries and the benefits for the society. In Lake Koka (Ethiopia), very little is known about the vital population parameters and exploitation status of the fishery target species: tilapia Oreochromis niloticus, common carp Cyprinus carpio and catfish Clarias gariepinus. Our study, therefore, aimed at determining the vital population parameters and assessing the status of these target species in Lake Koka using length frequency data collected quarterly from commercial catches from 2007-2012. A total of 20,097 fish specimens (distributed as 7,933 tilapia, 6,025 catfish and 6,139 common carp) were measured for the analysis. Von Bertalarffy growth parameters and their confidence intervals were determined from modal progression analysis using ELEFAN I and applying the jackknife technique. Mortality parameters were determined from length-converted catch curves and empirical models. The exploitation status of these target species were then assessed by computing exploitation rates (E) from mortality parameters as well as from size indicators i.e., assessing the size distribution of fish catches relative to the size at maturity (Lm), the size that provides maximum cohort biomass (Lopt) and the abundance of mega-spawners. The mean value of growth parameters L∞, K and the growth performance index ø' were 44.5 cm, 0.41/year and 2.90 for O. niloticus, 74.1 cm, 0.28/year and 3.19 for C. carpio and 121.9 cm, 0.16/year and 3.36 for C. gariepinus, respectively. The 95 % confidence intervals of the estimates were also computed. Total mortality (Z) estimates were 1.47, 0.83 and 0.72/year for O. niloticus, C. carpio and C. gariepinus, respectively. Our study suggest that O. niloticus is in a healthy state, while C. gariepinus show signs of growth overfishing (when both exploitation rate (E) and size indicators were considered). In case of C. carpio, the low exploitation rate encountered would point to underfishing, while the size indicators of the catches would suggest that too small fish are harvested leading to growth overfishing. We concluded that fisheries production in Lake Koka could be enhanced by increasing E toward optimum level of exploitation (Eopt) for the underexploited C. carpio and by increasing the size at first capture (Lc) toward the Lopt, range for all target species.

Dynamic Fatigue of ULE Glass

NASA Technical Reports Server (NTRS)

Tucker, Dennis S.; Nettles, Alan T.; Brantley, Lott W. (Technical Monitor)

2001-01-01

Ultra Low Expansion (ULE) glass is used in a number of applications which require a low thermal expansion coefficient. One such application is telescope mirror elements. An allowable stress can be calculated for this material based upon modulus of rupture data; however, this does not take into account the problem of delayed failure. Delayed failure, due to stress corrosion can significantly shorten the lifetime of a glass article. Knowledge of the factors governing the rate of subcritical flaw growth in a given environment enables the development of relations between lifetime, applied stress and failure probability for the material under study. Dynamic fatigue is one method of obtaining the necessary information to develop these relationships. In this study, the dynamic fatigue method was used to construct time-to-failure diagrams for both 230/270 ground and optically polished samples. The grinding and polishing process reduces the surface flaw size and subsurface damage, and relieves residual stress by removing materials with successively smaller grinding media. This resulted in an increase in the strength of the optic during the grinding and polishing sequence. There was also an increase in the lifetime due to grinding and polishing. It was found that using the fatigue parameters determined from the 230/270 grit surface are not significantly different from the optically polished values. Although the lower bound of the polished samples is more conservative, neither time-to-failure curves lie beyond the upper or lower bound of the confidence limits. Therefore, designers preferring conservative limits could use samples without residual stress present (polished samples) to determine the fatigue parameters and inert Weibull parameters from samples with the service condition surface, to determine time-to-failure of the optical element.

Model parameter uncertainty analysis for an annual field-scale P loss model

NASA Astrophysics Data System (ADS)

Bolster, Carl H.; Vadas, Peter A.; Boykin, Debbie

2016-08-01

Phosphorous (P) fate and transport models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. Because all models are simplifications of complex systems, there will exist an inherent amount of uncertainty associated with their predictions. It is therefore important that efforts be directed at identifying, quantifying, and communicating the different sources of model uncertainties. In this study, we conducted an uncertainty analysis with the Annual P Loss Estimator (APLE) model. Our analysis included calculating parameter uncertainties and confidence and prediction intervals for five internal regression equations in APLE. We also estimated uncertainties of the model input variables based on values reported in the literature. We then predicted P loss for a suite of fields under different management and climatic conditions while accounting for uncertainties in the model parameters and inputs and compared the relative contributions of these two sources of uncertainty to the overall uncertainty associated with predictions of P loss. Both the overall magnitude of the prediction uncertainties and the relative contributions of the two sources of uncertainty varied depending on management practices and field characteristics. This was due to differences in the number of model input variables and the uncertainties in the regression equations associated with each P loss pathway. Inspection of the uncertainties in the five regression equations brought attention to a previously unrecognized limitation with the equation used to partition surface-applied fertilizer P between leaching and runoff losses. As a result, an alternate equation was identified that provided similar predictions with much less uncertainty. Our results demonstrate how a thorough uncertainty and model residual analysis can be used to identify limitations with a model. Such insight can then be used to guide future data collection and model development and evaluation efforts.

The Use of One-Sample Prediction Intervals for Estimating CO2 Scrubber Canister Durations

DTIC Science & Technology

2012-10-01

Grade and 812 D-Grade Sofnolime.3 Definitions According to Devore,4 A CI (confidence interval) refers to a parameter, or population ... characteristic , whose value is fixed but unknown to us. In contrast, a future value of Y is not a parameter but instead a random variable; for this

Estimating equivalence with quantile regression

USGS Publications Warehouse

Cade, B.S.

2011-01-01

Equivalence testing and corresponding confidence interval estimates are used to provide more enlightened statistical statements about parameter estimates by relating them to intervals of effect sizes deemed to be of scientific or practical importance rather than just to an effect size of zero. Equivalence tests and confidence interval estimates are based on a null hypothesis that a parameter estimate is either outside (inequivalence hypothesis) or inside (equivalence hypothesis) an equivalence region, depending on the question of interest and assignment of risk. The former approach, often referred to as bioequivalence testing, is often used in regulatory settings because it reverses the burden of proof compared to a standard test of significance, following a precautionary principle for environmental protection. Unfortunately, many applications of equivalence testing focus on establishing average equivalence by estimating differences in means of distributions that do not have homogeneous variances. I discuss how to compare equivalence across quantiles of distributions using confidence intervals on quantile regression estimates that detect differences in heterogeneous distributions missed by focusing on means. I used one-tailed confidence intervals based on inequivalence hypotheses in a two-group treatment-control design for estimating bioequivalence of arsenic concentrations in soils at an old ammunition testing site and bioequivalence of vegetation biomass at a reclaimed mining site. Two-tailed confidence intervals based both on inequivalence and equivalence hypotheses were used to examine quantile equivalence for negligible trends over time for a continuous exponential model of amphibian abundance. ?? 2011 by the Ecological Society of America.

A flexible Bayesian assessment for the expected impact of data on prediction confidence for optimal sampling designs

NASA Astrophysics Data System (ADS)

Leube, Philipp; Geiges, Andreas; Nowak, Wolfgang

2010-05-01

Incorporating hydrogeological data, such as head and tracer data, into stochastic models of subsurface flow and transport helps to reduce prediction uncertainty. Considering limited financial resources available for the data acquisition campaign, information needs towards the prediction goal should be satisfied in a efficient and task-specific manner. For finding the best one among a set of design candidates, an objective function is commonly evaluated, which measures the expected impact of data on prediction confidence, prior to their collection. An appropriate approach to this task should be stochastically rigorous, master non-linear dependencies between data, parameters and model predictions, and allow for a wide variety of different data types. Existing methods fail to fulfill all these requirements simultaneously. For this reason, we introduce a new method, denoted as CLUE (Cross-bred Likelihood Uncertainty Estimator), that derives the essential distributions and measures of data utility within a generalized, flexible and accurate framework. The method makes use of Bayesian GLUE (Generalized Likelihood Uncertainty Estimator) and extends it to an optimal design method by marginalizing over the yet unknown data values. Operating in a purely Bayesian Monte-Carlo framework, CLUE is a strictly formal information processing scheme free of linearizations. It provides full flexibility associated with the type of measurements (linear, non-linear, direct, indirect) and accounts for almost arbitrary sources of uncertainty (e.g. heterogeneity, geostatistical assumptions, boundary conditions, model concepts) via stochastic simulation and Bayesian model averaging. This helps to minimize the strength and impact of possible subjective prior assumptions, that would be hard to defend prior to data collection. Our study focuses on evaluating two different uncertainty measures: (i) expected conditional variance and (ii) expected relative entropy of a given prediction goal. The applicability and advantages are shown in a synthetic example. Therefor, we consider a contaminant source, posing a threat on a drinking water well in an aquifer. Furthermore, we assume uncertainty in geostatistical parameters, boundary conditions and hydraulic gradient. The two mentioned measures evaluate the sensitivity of (1) general prediction confidence and (2) exceedance probability of a legal regulatory threshold value on sampling locations.

Detection of Sea Ice and Open Water from RADARSAT-2 Images for Data Assimilation

NASA Astrophysics Data System (ADS)

Komarov, A.; Buehner, M.

2016-12-01

Automated detection of sea ice and open water from SAR data is very important for further assimilation into coupled ocean-sea ice-atmosphere numerical models, such as the Regional Ice-Ocean Prediction System being implemented at the Environment and Climate Change Canada. Conventional classification approaches based on various learning techniques are found to be limited by the fact that they typically do not indicate the level of confidence for ice and water retrievals. Meanwhile, only ice/water retrievals with a very high level of confidence are allowed to be assimilated into the sea ice model to avoid propagating and magnifying errors into the numerical prediction system. In this study we developed a new technique for ice and water detection from dual-polarization RADARSAT-2 HH-HV images which provides the probability of ice/water at a given location. We collected many hundreds of thousands of SAR signatures over various sea ice types (i.e. new, grey, first-year, and multi-year ice) and open water from all available RADARSAT-2 images and the corresponding Canadian Ice Service Image Analysis products over the period from November 2010 to May 2016. Our analysis of the dataset revealed that ice/water separation can be effectively performed in the space of SAR-based variables independent of the incidence angle and noise floor (such as texture measures) and auxiliary Global Environmental Multiscale Model parameters (such as surface wind speed). Choice of the parameters will be specifically discussed in the presentation. An ice probability empirical model as a function of the selected predictors was built in a form of logistic regression, based on the training dataset from 2012 to 2016. The developed ice probability model showed very good performance on the independent testing subset (year 2011). With the ice/water probability threshold of 0.95 reflecting a very high level of confidence, 79% of the testing ice and water samples were classified with the accuracy of 99%. These results are particularly important in light of the upcoming RADARSAT Constellation mission which will drastically increase the amount of SAR data over the Arctic region.

Sbottom discovery via mixed decays at the LHC

NASA Astrophysics Data System (ADS)

Han, Tao; Su, Shufang; Wu, Yongcheng; Zhang, Bin; Zhang, Huanian

2015-12-01

In the search for the bottom squark (sbottom) in supersymmetry (SUSY) at the LHC, the common practice has been to assume a 100% decay branching fraction for a given search channel. In realistic minimal supersymmetric Standard Model scenarios, there are often more than one significant decay modes to be present, which significantly weaken the current sbottom search limits at the LHC. On the other hand, the combination of the multiple decay modes offers alternative discovery channels for sbottom searches. In this paper, we present the sbottom decays in a few representative mass parameter scenarios. We then analyze the sbottom signal for the pair production in QCD with one sbottom decaying via b ˜ →b χ10 , b χ20 , and the other one decaying via b ˜→t χ1±. With the gaugino subsequent decaying to gauge bosons or a Higgs boson χ20→Z χ10 , h χ10 and χ1±→W±χ10, we study the reach of those signals at the 14 TeV LHC with 300 fb-1 integrated luminosity. For a left-handed bottom squark, we find that a mass up to 920 GeV can be discovered at 5 σ significance for 250 GeV 0 ); similarly, it can be discovered up to 840 GeV, or excluded up to 900 GeV at the 95% confidence level for the Z channel (μ <0 ). The top squark reach is close to that of the bottom squark. The sbottom and stop signals in the same SUSY parameter scenario are combined to obtain the optimal sensitivity, which is about 150 GeV better than the individual reach of the sbottom or stop. For a right-handed bottom squark with the b ˜ b˜ *→b χ10 , t χ1± channel, we find that the sbottom mass up to 880 GeV can be discovered at 5 σ significance, or excluded up to 1060 GeV at the 95% confidence level.

Standardized likelihood ratio test for comparing several log-normal means and confidence interval for the common mean.

PubMed

Krishnamoorthy, K; Oral, Evrim

2017-12-01

Standardized likelihood ratio test (SLRT) for testing the equality of means of several log-normal distributions is proposed. The properties of the SLRT and an available modified likelihood ratio test (MLRT) and a generalized variable (GV) test are evaluated by Monte Carlo simulation and compared. Evaluation studies indicate that the SLRT is accurate even for small samples, whereas the MLRT could be quite liberal for some parameter values, and the GV test is in general conservative and less powerful than the SLRT. Furthermore, a closed-form approximate confidence interval for the common mean of several log-normal distributions is developed using the method of variance estimate recovery, and compared with the generalized confidence interval with respect to coverage probabilities and precision. Simulation studies indicate that the proposed confidence interval is accurate and better than the generalized confidence interval in terms of coverage probabilities. The methods are illustrated using two examples.

Exploring separable components of institutional confidence.

PubMed

Hamm, Joseph A; PytlikZillig, Lisa M; Tomkins, Alan J; Herian, Mitchel N; Bornstein, Brian H; Neeley, Elizabeth M

2011-01-01

Despite its contemporary and theoretical importance in numerous social scientific disciplines, institutional confidence research is limited by a lack of consensus regarding the distinctions and relationships among related constructs (e.g., trust, confidence, legitimacy, distrust, etc.). This study examined four confidence-related constructs that have been used in studies of trust/confidence in the courts: dispositional trust, trust in institutions, obligation to obey the law, and cynicism. First, the separability of the four constructs was examined by exploratory factor analyses. Relationships among the constructs were also assessed. Next, multiple regression analyses were used to explore each construct's independent contribution to confidence in the courts. Finally, a second study replicated the first study and also examined the stability of the institutional confidence constructs over time. Results supported the hypothesized separability of, and correlations among, the four confidence-related constructs. The extent to which the constructs independently explained the observed variance in confidence in the courts differed as a function of the specific operationalization of confidence in the courts and the individual predictor measures. Implications for measuring institutional confidence and future research directions are discussed. Copyright © 2011 John Wiley & Sons, Ltd.

Use of and confidence in administering outcome measures among clinical prosthetists: Results from a national survey and mixed-methods training program.

PubMed

Gaunaurd, Ignacio; Spaulding, Susan E; Amtmann, Dagmar; Salem, Rana; Gailey, Robert; Morgan, Sara J; Hafner, Brian J

2015-08-01

Outcome measures can be used in prosthetic practices to evaluate interventions, inform decision making, monitor progress, document outcomes, and justify services. Strategies to enhance prosthetists' ability to use outcome measures are needed to facilitate their adoption in routine practice. To assess prosthetists' use of outcome measures and evaluate the effects of training on their confidence in administering performance-based measures. Cross-sectional and single-group pretest-posttest survey. Seventy-nine certified prosthetists (mean of 16.0 years of clinical experience) were surveyed about their experiences with 20 standardized outcome measures. Prosthetists were formally trained by the investigators to administer the Timed Up and Go and Amputee Mobility Predictor. Prosthetists' confidence in administering the Timed Up and Go and Amputee Mobility Predictor was measured before and after training. The majority of prosthetists (62%) were classified as non-routine outcome measure users. Confidence administering the Timed Up and Go and Amputee Mobility Predictor prior to training was low-to-moderate across the study sample. Training significantly (p < 0.0001) improved prosthetists' confidence in administering both instruments. Prosthetists in this study reported limited use of and confidence with standardized outcome measures. Interactive training resulted in a statistically significant increase of prosthetists' confidence in administering the Timed Up and Go and Amputee Mobility Predictor and may facilitate use of outcome measures in clinical practice. Frequency of outcome measure use in the care of persons with limb loss has not been studied. Study results suggest that prosthetists may not regularly use standardized outcome measures and report limited confidence in administering them. Training enhances confidence and may encourage use of outcome measures in clinical practice. © The International Society for Prosthetics and Orthotics 2014.

Time-varying associations between confidence and motivation to abstain from marijuana during treatment among adolescents

PubMed Central

Chung, Tammy; Maisto, Stephen A.

2016-01-01

Introduction An important goal of addictions treatment is to develop a positive association between high levels of confidence and motivation to abstain from substance use. This study modeled the time-varying association between confidence and motivation to abstain from marijuana use among youth in treatment, and the time-varying effect of pre-treatment covariates (marijuana abstinence goal and perceived peer marijuana use) on motivation to abstain. Method 150 adolescents (75% male, 83% White) in community-based intensive outpatient treatment in Pennsylvania completed a pre-treatment assessment of abstinence goal, perceived peer marijuana use, and motivation and confidence to abstain from marijuana. Ratings of motivation and confidence to abstain also were collected after each session. A Time-Varying Effect Model (TVEM) was used to characterize changes in the association between confidence and motivation to abstain (lagged), and included covariates representing pre-treatment abstinence goal and perceived peer marijuana use. Results Confidence and motivation to abstain from marijuana generally increased during treatment. The association between confidence and motivation strengthened across sessions 1-4, and was maintained through later sessions. Pre-treatment abstinence goal had an early time-limited effect (through session 6) on motivation to abstain. Pre-treatment perception of peer marijuana use had a significant effect on motivation to abstain only at session 2. Conclusions Early treatment sessions represent a critical period during which the association between confidence and motivation to abstain generally increased. The time-limited effects of pre-treatment characteristics suggest the importance of early sessions in addressing abstinence goal and peer substance use that may impact motivation to abstain from marijuana. PMID:26894550

Time-varying associations between confidence and motivation to abstain from marijuana during treatment among adolescents.

PubMed

Chung, Tammy; Maisto, Stephen A

2016-06-01

An important goal of addictions treatment is to develop a positive association between high levels of confidence and motivation to abstain from substance use. This study modeled the time-varying association between confidence and motivation to abstain from marijuana use among youth in treatment, and the time-varying effect of pre-treatment covariates (marijuana abstinence goal and perceived peer marijuana use) on motivation to abstain. 150 adolescents (75% male, 83% White) in community-based intensive outpatient treatment in Pennsylvania completed a pre-treatment assessment of abstinence goal, perceived peer marijuana use, and motivation and confidence to abstain from marijuana. Ratings of motivation and confidence to abstain also were collected after each session. A time-varying effect model (TVEM) was used to characterize changes in the association between confidence and motivation to abstain (lagged), and included covariates representing pre-treatment abstinence goal and perceived peer marijuana use. Confidence and motivation to abstain from marijuana generally increased during treatment. The association between confidence and motivation strengthened across sessions 1-4, and was maintained through later sessions. Pre-treatment abstinence goal had an early time-limited effect (through session 6) on motivation to abstain. Pre-treatment perception of peer marijuana use had a significant effect on motivation to abstain only at session 2. Early treatment sessions represent a critical period during which the association between confidence and motivation to abstain generally increased. The time-limited effects of pre-treatment characteristics suggest the importance of early sessions in addressing abstinence goal and peer substance use that may impact motivation to abstain from marijuana. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessing pharmacists' readiness to prescribe oral antibiotics for limited infections using a case-vignette technique.

PubMed

Ung, Elizabeth; Czarniak, Petra; Sunderland, Bruce; Parsons, Richard; Hoti, Kreshnik

2017-02-01

Background Pharmacist's skills are underutilized whilst they are directly involved with antibiotic supply to the community. Addressing this issue could lead to better use of antibiotics and hence decreased resistance. Objective Explore how pharmacists can prescribe oral antibiotics to treat a limited range of infections whilst focusing on their confidence and appropriateness of prescribing. Setting Community pharmacies, Western Australia. Method Data were collected using a self-administered questionnaire also containing case vignettes. These were distributed to a random sample of metropolitan and rural community pharmacies in Western Australia. A Generalised Estimating Equation was used to compare respondents' level of confidence in treating various infections and to assess appropriateness of prescribing. Main outcome measure Appropriateness and confidence of antibiotic prescribing. Results A response rate of 34.2% (i.e. 425 responses to case vignettes) was achieved from 240 pharmacies. There were high levels of confidence to treat simple infections such as uncomplicated UTIs (n = 73; 89.0%), impetigo (n = 65; 79.3%), mild bacterial skin infections (n = 62; 75.6%) and moderate acne (n = 61; 72.4%). Over 80% of respondents were confident to prescribe amoxicillin (n = 73; 89%), trimethoprim (n = 72; 87.8%), amoxicillin and clavulanic acid (n = 70; 85.4%), flucloxacillin (n = 70; 85.4%) and cephalexin (n = 68; 82.9%). High levels of appropriate antibiotic prescribing were shown for uncomplicated UTI (97.2%), cellulitis (98.2%) and adolescent acne (100.0%). Conclusion This study identified key limited infections and antibiotics for which pharmacists were supportive and confident to prescribe. This role could lead to better use of antibiotics in the community and minimisation of resistance.

A new, sophisticated test of the Binary Black Hole Hypothesis for Quasars with Double-peaked Broad Balmer Lines.

NASA Astrophysics Data System (ADS)

Nguyen Duy Doan, Anh; Eracleous, Michael; Runnoe, Jessie; Halpern, Jules P.; Liu, Jia; Mathes, Gavin; Flohic, Helene M. L. G.

2018-01-01

Displaced peaks in the Balmer lines of quasars could serve as indirect evidence for the existence of close, bound supermassive black hole binaries (SBHBs) at sub-parsec separations. In this work, we test the SBHB hypothesis for 14 quasars with double-peaked emission lines using their long-term radial velocity curves. We make use of a Markov Chain Monte Carlo method to explore the parameter space efficiently. Compared to previous works, we have relaxed the assumption of circular orbits, adding two parameters (eccentricity and argument of periapsis) to the parameter space. We also account for jitter, i.e., short-term fluctuations in the radial velocity curves due to processes that are intrinsic to an individual broad-line region. We have found that the distribution of jitter about a smooth radial velocity curve resembles a Gaussian. Thus, jitter is equivalent to increasing measurement uncertainty in individual measurements. The resulting posterior distributions show the lower mass limit of the SBHBs to be in the range of 10^8 - 10^11 solar masses. For several objects, the mass limit drops by a few orders of magnitude compared to previous results by Liu et. al. However, we note that solutions corresponding to minimum masses often require very high orbital eccentricity ( > 0.9). We also calculate the orbital decay timescale of the binaries due to gravitational radiation, finding values in the range 10^6 - 10^11 years; these values correspond to the minimum-mass solutions. For one third of our targets, we can confidently disfavor the SBHB hypothesis on the basis that the minimum mass exceeds even the most massive black holes measured so far (2 x 10^10 solar masses). For the remaining objects, we must take into account the plausibility of a variety of parameters (e.g. eccentricity, lifetime, etc.) in our evaluation.

Solid recovered fuel: influence of waste stream composition and processing on chlorine content and fuel quality.

PubMed

Velis, Costas; Wagland, Stuart; Longhurst, Phil; Robson, Bryce; Sinfield, Keith; Wise, Stephen; Pollard, Simon

2012-02-07

Solid recovered fuel (SRF) produced by mechanical-biological treatment (MBT) of municipal waste can replace fossil fuels, being a CO(2)-neutral, affordable, and alternative energy source. SRF application is limited by low confidence in quality. We present results for key SRF properties centered on the issue of chlorine content. A detailed investigation involved sampling, statistical analysis, reconstruction of composition, and modeling of SRF properties. The total chlorine median for a typical plant during summer operation was 0.69% w/w(d), with lower/upper 95% confidence intervals of 0.60% w/w(d) and 0.74% w/w(d) (class 3 of CEN Cl indicator). The average total chlorine can be simulated, using a reconciled SRF composition before shredding to <40 mm. The relative plastics vs paper mass ratios in particular result in an SRF with a 95% upper confidence limit for ash content marginally below the 20% w/w(d) deemed suitable for certain power plants; and a lower 95% confidence limit of net calorific value (NCV) at 14.5 MJ kg(ar)(-1). The data provide, for the first time, a high level of confidence on the effects of SRF composition on its chlorine content, illustrating interrelationships with other fuel properties. The findings presented here allow rational debate on achievable vs desirable MBT-derived SRF quality, informing the development of realistic SRF quality specifications, through modeling exercises, needed for effective thermal recovery.

Wilkinson Microwave Anisotropy Probe (WMAP) First Year Observations: TE Polarization

NASA Technical Reports Server (NTRS)

Kogut, A.; Spergel, D. N.; Barnes, C.; Bennett, C. L.; Halpern, M.; Hinshaw, G.; Jarosik, N.; Limon, M.; Meyer, S. S.; Page, L.;

The probability of being identified as an outlier with commonly used funnel plot control limits for the standardised mortality ratio.

PubMed

Seaton, Sarah E; Manktelow, Bradley N

2012-07-16

Emphasis is increasingly being placed on the monitoring of clinical outcomes for health care providers. Funnel plots have become an increasingly popular graphical methodology used to identify potential outliers. It is assumed that a provider only displaying expected random variation (i.e. 'in-control') will fall outside a control limit with a known probability. In reality, the discrete count nature of these data, and the differing methods, can lead to true probabilities quite different from the nominal value. This paper investigates the true probability of an 'in control' provider falling outside control limits for the Standardised Mortality Ratio (SMR). The true probabilities of an 'in control' provider falling outside control limits for the SMR were calculated and compared for three commonly used limits: Wald confidence interval; 'exact' confidence interval; probability-based prediction interval. The probability of falling above the upper limit, or below the lower limit, often varied greatly from the nominal value. This was particularly apparent when there were a small number of expected events: for expected events ≤ 50 the median probability of an 'in-control' provider falling above the upper 95% limit was 0.0301 (Wald), 0.0121 ('exact'), 0.0201 (prediction). It is important to understand the properties and probability of being identified as an outlier by each of these different methods to aid the correct identification of poorly performing health care providers. The limits obtained using probability-based prediction limits have the most intuitive interpretation and their properties can be defined a priori. Funnel plot control limits for the SMR should not be based on confidence intervals.

Molecular hydrogen absorption systems in Sloan Digital Sky Survey

NASA Astrophysics Data System (ADS)

Balashev, S. A.; Klimenko, V. V.; Ivanchik, A. V.; Varshalovich, D. A.; Petitjean, P.; Noterdaeme, P.

2014-05-01

We present a systematic search for molecular hydrogen absorption systems at high redshift in quasar spectra from the Sloan Digital Sky Survey (SDSS)-II Data Release 7 and SDSS-III Data Release 9. We have selected candidates using a modified profile fitting technique taking into account that the Lyα forest can effectively mimic H2 absorption systems at the resolution of SDSS data. To estimate the confidence level of the detections, we use two methods: a Monte Carlo sampling and an analysis of control samples. The analysis of control samples allows us to define regions of the spectral quality parameter space where H2 absorption systems can be confidently identified. We find that H2 absorption systems with column densities log NH2 > 19 can be detected in only less than 3 per cent of SDSS quasar spectra. We estimate the upper limit on the detection rate of saturated H2 absorption systems (NH2 > 19) in damped Lyα (DLA) systems to be about 7 per cent. We provide a sample of 23 confident H2 absorption system candidates that would be interesting to follow up with high-resolution spectrographs. There is a 1σ r - i colour excess and non-significant AV extinction excess in quasar spectra with an H2 candidate compared to standard DLA-bearing quasar spectra. The equivalent widths of C II, Si II and Al III (but not Fe II) absorptions associated with H2 candidate DLAs are larger compared to standard DLAs. This is probably related to a larger spread in velocity of the absorption lines in the H2-bearing sample.

Confidence in the efficacy and safety of dietary supplements among United States active duty army personnel

PubMed Central

2012-01-01

Background United States Army Soldiers regularly use dietary supplements (DS) to promote general health, enhance muscle strength, and increase energy, but limited scientific evidence supports the use of many DS for these benefits. This study investigated factors associated with Soldiers’ confidence in the efficacy and safety of DS, and assessed Soldiers’ knowledge of federal DS regulatory requirements. Methods Between 2006 and 2007, 990 Soldiers were surveyed at 11 Army bases world-wide to assess their confidence in the effectiveness and safety of DS, knowledge of federal DS regulations, demographic characteristics, lifestyle-behaviors and DS use. Results A majority of Soldiers were at least somewhat confident that DS work as advertised (67%) and thought they are safe to consume (71%). Confidence in both attributes was higher among regular DS users than non-users. Among users, confidence in both attributes was positively associated with rank, self-rated diet quality and fitness level, education, and having never experienced an apparent DS-related adverse event. Fewer than half of Soldiers knew the government does not require manufacturers to demonstrate efficacy, and almost a third incorrectly believed there are effective pre-market federal safety requirements for DS. Conclusions Despite limited scientific evidence supporting the purported benefits and safety of many popular DS, most Soldiers were confident that DS are effective and safe. The positive associations between confidence and DS use should be considered when developing DS-related interventions or policies. Additionally, education to clarify Soldiers’ misperceptions about federal DS safety and efficacy regulations is warranted. PMID:23051046

Bayesian inference of uncertainties in precipitation-streamflow modeling in a snow affected catchment

NASA Astrophysics Data System (ADS)

Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.

2012-11-01

Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.

The effects of variations in parameters and algorithm choices on calculated radiomics feature values: initial investigations and comparisons to feature variability across CT image acquisition conditions

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Wahi-Anwar, Muhammad; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael

2018-02-01

Translation of radiomics into clinical practice requires confidence in its interpretations. This may be obtained via understanding and overcoming the limitations in current radiomic approaches. Currently there is a lack of standardization in radiomic feature extraction. In this study we examined a few factors that are potential sources of inconsistency in characterizing lung nodules, such as 1)different choices of parameters and algorithms in feature calculation, 2)two CT image dose levels, 3)different CT reconstruction algorithms (WFBP, denoised WFBP, and Iterative). We investigated the effect of variation of these factors on entropy textural feature of lung nodules. CT images of 19 lung nodules identified from our lung cancer screening program were identified by a CAD tool and contours provided. The radiomics features were extracted by calculating 36 GLCM based and 4 histogram based entropy features in addition to 2 intensity based features. A robustness index was calculated across different image acquisition parameters to illustrate the reproducibility of features. Most GLCM based and all histogram based entropy features were robust across two CT image dose levels. Denoising of images slightly improved robustness of some entropy features at WFBP. Iterative reconstruction resulted in improvement of robustness in a fewer times and caused more variation in entropy feature values and their robustness. Within different choices of parameters and algorithms texture features showed a wide range of variation, as much as 75% for individual nodules. Results indicate the need for harmonization of feature calculations and identification of optimum parameters and algorithms in a radiomics study.

Mapping land water and energy balance relations through conditional sampling of remote sensing estimates of atmospheric forcing and surface states

NASA Astrophysics Data System (ADS)

Farhadi, Leila; Entekhabi, Dara; Salvucci, Guido

2016-04-01

In this study, we develop and apply a mapping estimation capability for key unknown parameters that link the surface water and energy balance equations. The method is applied to the Gourma region in West Africa. The accuracy of the estimation method at point scale was previously examined using flux tower data. In this study, the capability is scaled to be applicable with remotely sensed data products and hence allow mapping. Parameters of the system are estimated through a process that links atmospheric forcing (precipitation and incident radiation), surface states, and unknown parameters. Based on conditional averaging of land surface temperature and moisture states, respectively, a single objective function is posed that measures moisture and temperature-dependent errors solely in terms of observed forcings and surface states. This objective function is minimized with respect to parameters to identify evapotranspiration and drainage models and estimate water and energy balance flux components. The uncertainty of the estimated parameters (and associated statistical confidence limits) is obtained through the inverse of Hessian of the objective function, which is an approximation of the covariance matrix. This calibration-free method is applied to the mesoscale region of Gourma in West Africa using multiplatform remote sensing data. The retrievals are verified against tower-flux field site data and physiographic characteristics of the region. The focus is to find the functional form of the evaporative fraction dependence on soil moisture, a key closure function for surface and subsurface heat and moisture dynamics, using remote sensing data.

The CMB neutrino mass/vacuum energy degeneracy: a simple derivation of the degeneracy slopes

NASA Astrophysics Data System (ADS)

Sutherland, Will

2018-06-01

It is well known that estimating cosmological parameters from cosmic microwave background (CMB) data alone results in a significant degeneracy between the total neutrino mass and several other cosmological parameters, especially the Hubble constant H0 and the matter density parameter Ωm. Adding low-redshift measurements such as baryon acoustic oscillations (BAOs) breaks this degeneracy and greatly improves the constraints on neutrino mass. The sensitivity is surprisingly high, for example, adding the ˜1 percent measurement of the BAO ratio rs/DV from the BOSS survey leads to a limit Σ mν < 0.19 eV, equivalent to Ων < 0.0045 at 95 per cent confidence. For the case of Σ mν < 0.6 eV, the CMB degeneracy with neutrino mass almost follows a track of constant sound horizon angle (Howlett et al. 2012). For a ΛCDM + mν model, we use simple but quite accurate analytic approximations to derive the slope of this track, giving dimensionless multipliers between the neutrino to matter ratio (xν ≡ ων/ωcb) and the shifts in other cosmological parameters. The resulting multipliers are substantially larger than 1: conserving the CMB sound horizon angle requires parameter shifts δln H0 ≈ -2 δxν, δln Ωm ≈ +5 δxν, δln ωΛ ≈ -6.2 δxν, and most notably δωΛ ≈ -14 δων. These multipliers give an intuitive derivation of the degeneracy direction, which agrees well with the numerical likelihood results from the Planck team.

Statistical inferences with jointly type-II censored samples from two Pareto distributions

NASA Astrophysics Data System (ADS)

Abu-Zinadah, Hanaa H.

2017-08-01

In the several fields of industries the product comes from more than one production line, which is required to work the comparative life tests. This problem requires sampling of the different production lines, then the joint censoring scheme is appeared. In this article we consider the life time Pareto distribution with jointly type-II censoring scheme. The maximum likelihood estimators (MLE) and the corresponding approximate confidence intervals as well as the bootstrap confidence intervals of the model parameters are obtained. Also Bayesian point and credible intervals of the model parameters are presented. The life time data set is analyzed for illustrative purposes. Monte Carlo results from simulation studies are presented to assess the performance of our proposed method.

RhoGTPase Involvement in Breast Cancer Migration and Invasion

DTIC Science & Technology

2008-03-01

wound healing 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a...high confidence, MC= moderate confidence, indicated in absolute numbers. i) ii) iii) 10 Figure 2: Top signalling netowrk of direct relationships for

Hierarchical optimization for neutron scattering problems

DOE PAGES

Bao, Feng; Archibald, Rick; Bansal, Dipanshu; ...

2016-03-14

In this study, we present a scalable optimization method for neutron scattering problems that determines confidence regions of simulation parameters in lattice dynamics models used to fit neutron scattering data for crystalline solids. The method uses physics-based hierarchical dimension reduction in both the computational simulation domain and the parameter space. We demonstrate for silicon that after a few iterations the method converges to parameters values (interatomic force-constants) computed with density functional theory simulations.

Hierarchical optimization for neutron scattering problems

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

Bao, Feng; Archibald, Rick; Bansal, Dipanshu

In this study, we present a scalable optimization method for neutron scattering problems that determines confidence regions of simulation parameters in lattice dynamics models used to fit neutron scattering data for crystalline solids. The method uses physics-based hierarchical dimension reduction in both the computational simulation domain and the parameter space. We demonstrate for silicon that after a few iterations the method converges to parameters values (interatomic force-constants) computed with density functional theory simulations.

Search for neutral MSSM Higgs bosons decaying into a pair of bottom quarks

DOE PAGES

Khachatryan, Vardan

2015-11-11

A search for neutral Higgs bosons decaying into a bb¯ quark pair and produced in association with at least one additional b quark is presented. This signature is sensitive to the Higgs sector of the minimal supersymmetric standard model (MSSM) with large values of the parameter tan β. The analysis is based on data from proton-proton collisions at a center-of-mass energy of 8 TeV collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 19.7 fb –1. The results are combined with a previous analysis based on 7 TeV data. No signal is observed. Stringent uppermore » limits on the cross section times branching fraction are derived for Higgs bosons with masses up to 900 GeV, and the results are interpreted within different MSSM benchmark scenarios, m h max, m h mod+, m h mod–, light-stau and light-stop. Observed 95% confidence level upper limits on tan β, ranging from 14 to 50, are obtained in the m h mod+ benchmark scenario.« less

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

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

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

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

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

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

DOE PAGES

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

2015-03-10

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

Search for intermediate mass black hole binaries in the first observing run of Advanced LIGO

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Afrough, M.; Agarwal, B.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Allen, B.; Allen, G.; Allocca, A.; Almoubayyed, H.; Altin, P. A.; Amato, A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; AultONeal, K.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Bae, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Banagiri, S.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bawaj, M.; Bazzan, M.; Bécsy, B.; Beer, C.; Bejger, M.; Belahcene, I.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bode, N.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Canepa, M.; Canizares, P.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Carney, M. F.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chatterjee, D.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y.; Cheng, H.-P.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, A. K. W.; Chung, S.; Ciani, G.; Ciolfi, R.; Cirelli, C. E.; Cirone, A.; Clara, F.; Clark, J. A.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L. R.; Constancio, M.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Corley, K. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Daw, E. J.; Day, B.; De, S.; DeBra, D.; Deelman, E.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devenson, J.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Duncan, J.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Eisenstein, R. A.; Essick, R. C.; Etienne, Z. B.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fehrmann, H.; Feicht, J.; Fejer, M. M.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fong, H.; Forsyth, P. W. F.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gabel, M.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Ganija, M. R.; Gaonkar, S. G.; Garufi, F.; Gaudio, S.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, D.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glover, L.; Goetz, E.; Goetz, R.; Gomes, S.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Gruning, P.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O. A.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Horst, C.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Intini, G.; Isa, H. N.; Isac, J.-M.; Isi, M.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katolik, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kemball, A. J.; Kennedy, R.; Kent, C.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, W.; Kim, W. S.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kumar, S.; Kuo, L.; Kutynia, A.; Kwang, S.; Lackey, B. D.; Lai, K. H.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, H. W.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Liu, J.; Lockerbie, N. A.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lück, H.; Lumaca, D.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña Hernandez, I.; Magaña-Sandoval, F.; Magaña Zertuche, L.; Magee, R. M.; Majorana, E.; Maksimovic, I.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markakis, C.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mayani, R.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McCuller, L.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Mejuto-Villa, E.; Melatos, A.; Mendell, G.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minazzoli, O.; Minenkov, Y.; Ming, J.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muniz, E. A. M.; Murray, P. G.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Nery, M.; Neunzert, A.; Newport, J. M.; Newton, G.; Ng, K. K. Y.; Nguyen, T. T.; Nichols, D.; Nielsen, A. B.; Nissanke, S.; Noack, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ormiston, R.; Ortega, L. F.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Page, M. A.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pang, B.; Pang, P. T. H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Porter, E. K.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Ramirez, K. E.; Rapagnani, P.; Raymond, V.; Razzano, M.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Ricker, P. M.; Rieger, S.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romel, C. L.; Romie, J. H.; Rosińska, D.; Ross, M. P.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Rynge, M.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheuer, J.; Schmidt, E.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schulte, B. W.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Seidel, E.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D. A.; Shaffer, T. J.; Shah, A. A.; Shahriar, M. S.; Shao, L.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Son, E. J.; Sonnenberg, J. A.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Stratta, G.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Taracchini, A.; Taylor, J. A.; Taylor, R.; Theeg, T.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tonelli, M.; Tornasi, Z.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tsang, K. W.; Tse, M.; Tso, R.; Tuyenbayev, D.; Ueno, K.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahi, K.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walet, R.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, J. Z.; Wang, M.; Wang, Y.-F.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wessel, E. K.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Wofford, J.; Wong, K. W. K.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, Hang; Yu, Haocun; Yvert, M.; ZadroŻny, A.; Zanolin, M.; Zelenova, T.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.-H.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2017-07-01

During their first observational run, the two Advanced LIGO detectors attained an unprecedented sensitivity, resulting in the first direct detections of gravitational-wave signals produced by stellar-mass binary black hole systems. This paper reports on an all-sky search for gravitational waves (GWs) from merging intermediate mass black hole binaries (IMBHBs). The combined results from two independent search techniques were used in this study: the first employs a matched-filter algorithm that uses a bank of filters covering the GW signal parameter space, while the second is a generic search for GW transients (bursts). No GWs from IMBHBs were detected; therefore, we constrain the rate of several classes of IMBHB mergers. The most stringent limit is obtained for black holes of individual mass 100 M⊙ , with spins aligned with the binary orbital angular momentum. For such systems, the merger rate is constrained to be less than 0.93 Gpc-3 yr-1 in comoving units at the 90% confidence level, an improvement of nearly 2 orders of magnitude over previous upper limits.

Search for charged Higgs bosons in e+e- collisions at [Formula: see text].

PubMed

Abbiendi, G; Ainsley, C; Åkesson, P F; Alexander, G; Anagnostou, G; Anderson, K J; Asai, S; Axen, D; Bailey, I; Barberio, E; Barillari, T; Barlow, R J; Batley, R J; Bechtle, P; Behnke, T; Bell, K W; Bell, P J; Bella, G; Bellerive, A; Benelli, G; Bethke, S; Biebel, O; Boeriu, O; Bock, P; Boutemeur, M; Braibant, S; Brown, R M; Burckhart, H J; Campana, S; Capiluppi, P; Carnegie, R K; Carter, A A; Carter, J R; Chang, C Y; Charlton, D G; Ciocca, C; Csilling, A; Cuffiani, M; Dado, S; Dallavalle, M; De Roeck, A; De Wolf, E A; Desch, K; Dienes, B; Dubbert, J; Duchovni, E; Duckeck, G; Duerdoth, I P; Etzion, E; Fabbri, F; Ferrari, P; Fiedler, F; Fleck, I; Ford, M; Frey, A; Gagnon, P; Gary, J W; Geich-Gimbel, C; Giacomelli, G; Giacomelli, P; Giunta, M; Goldberg, J; Gross, E; Grunhaus, J; Gruwé, M; Gupta, A; Hajdu, C; Hamann, M; Hanson, G G; Harel, A; Hauschild, M; Hawkes, C M; Hawkings, R; Herten, G; Heuer, R D; Hill, J C; Hoffman, K; Horváth, D; Igo-Kemenes, P; Ishii, K; Jeremie, H; Jovanovic, P; Junk, T R; Kanzaki, J; Karlen, D; Kawagoe, K; Kawamoto, T; Keeler, R K; Kellogg, R G; Kennedy, B W; Kluth, S; Kobayashi, T; Kobel, M; Komamiya, S; Krämer, T; Krasznahorkay, A; Krieger, P; von Krogh, J; Kuhl, T; Kupper, M; Lafferty, G D; Landsman, H; Lanske, D; Lellouch, D; Letts, J; Levinson, L; Lillich, J; Lloyd, S L; Loebinger, F K; Lu, J; Ludwig, A; Ludwig, J; Mader, W; Marcellini, S; Marchant, T E; Martin, A J; Mashimo, T; Mättig, P; McKenna, J; McPherson, R A; Meijers, F; Menges, W; Merritt, F S; Mes, H; Meyer, N; Michelini, A; Mihara, S; Mikenberg, G; Miller, D J; Mohr, W; Mori, T; Mutter, A; Nagai, K; Nakamura, I; Nanjo, H; Neal, H A; O'Neale, S W; Oh, A; Okpara, A; Oreglia, M J; Orito, S; Pahl, C; Pásztor, G; Pater, J R; Pilcher, J E; Pinfold, J; Plane, D E; Pooth, O; Przybycień, M; Quadt, A; Rabbertz, K; Rembser, C; Renkel, P; Roney, J M; Rossi, A M; Rozen, Y; Runge, K; Sachs, K; Saeki, T; Sarkisyan, E K G; Schaile, A D; Schaile, O; Scharff-Hansen, P; Schieck, J; Schörner-Sadenius, T; Schröder, M; Schumacher, M; Seuster, R; Shears, T G; Shen, B C; Sherwood, P; Skuja, A; Smith, A M; Sobie, R; Söldner-Rembold, S; Spano, F; Stahl, A; Strom, D; Ströhmer, R; Tarem, S; Tasevsky, M; Teuscher, R; Thomson, M A; Torrence, E; Toya, D; Trigger, I; Trócsányi, Z; Tsur, E; Turner-Watson, M F; Ueda, I; Ujvári, B; Vollmer, C F; Vannerem, P; Vértesi, R; Verzocchi, M; Voss, H; Vossebeld, J; Ward, C P; Ward, D R; Watkins, P M; Watson, A T; Watson, N K; Wells, P S; Wengler, T; Wermes, N; Wilson, G W; Wilson, J A; Wolf, G; Wyatt, T R; Yamashita, S; Zer-Zion, D; Zivkovic, L

A search is made for charged Higgs bosons predicted by Two-Higgs-Doublet extensions of the Standard Model (2HDM) using electron-positron collision data collected by the OPAL experiment at [Formula: see text], corresponding to an integrated luminosity of approximately 600 pb -1 . Charged Higgs bosons are assumed to be pair-produced and to decay into [Formula: see text], τν τ or AW ± . No signal is observed. Model-independent limits on the charged Higgs-boson production cross section are derived by combining these results with previous searches at lower energies. Under the assumption [Formula: see text], motivated by general 2HDM type II models, excluded areas on the [Formula: see text] plane are presented and charged Higgs bosons are excluded up to a mass of 76.3 GeV at 95 % confidence level, independent of the branching ratio BR(H ± → τν τ ). A scan of the 2HDM type I model parameter space is performed and limits on the Higgs-boson masses [Formula: see text] and m A are presented for different choices of tan β .

A Search for supersymmetric Higgs bosons in the di-tau decay mode in p anti-p collisions at s**(1/2) = 1.8-TeV

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

Acosta, D.; Affolder, Anthony A.; Albrow, M.G.

2005-06-01

A search for direct production of Higgs bosons in the di-tau decay mode is performed with 86.3 {+-} 3.5 pb{sup -1} of data collected with the Collider Detector at Fermilab during the 1994-1995 data taking period of the Tevatron. We search for events where one tau decays to an electron plus neutrinos and the other tau decays hadronically. We perform a counting experiment and set limits on the cross section for supersymmetric Higgs boson production where tan {beta} is large and m{sub A} is small. For a benchmark parameter space point where m{sub A{sup 0}} = 100 GeV/c{sup 2} andmore » tan {beta} = 50, we limit the production cross section multiplied by the branching ratio to be less than 77.9 pb at the 95% confidence level compared to theoretically predicted value of 11.0 pb. This is the first search for Higgs bosons decaying to tau pairs at a hadron collider.« less

Roles of divergent and rotational winds in the kinetic energy balance during intense convective activity

NASA Technical Reports Server (NTRS)

Fuelberg, H. E.; Browning, P. A.

1983-01-01

Contributions of divergent and rotational wind components to the synoptic-scale kinetic energy balance are described using rawinsonde data at 3 and 6 h intervals from NASA's fourth Atmospheric Variability experiment. Two intense thunderstorm complexes occurred during the period. Energy budgets are described for the entire computational region and for limited volumes that enclosed storm-induced, upper level wind maxima located poleward of convection. Although small in magnitude, the divergent wind component played an important role in the cross-contour generation and horizontal flux divergence of kinetic energy. The importance of V(D) appears directly related to the presence and intensity of convection. Although K(D) usually comprised less than 10 percent of the total kinetic energy content, generation of kinetic energy by V(D) was a major factor in the creation of upper-level wind maxima to the north of the storm complexes. Omission of the divergent wind apparently would lead to serious misrepresentations of the energy balance. A random error analysis is presented to assess confidence limits in the various energy parameters.

Search for the lepton-flavour violating decay D 0 → e ±μ ∓

DOE PAGES

Aaij, R.; Abellán Beteta, C.; Adeva, B.; ...

2016-01-19

A search for the lepton-flavour violating decay D 0 →e ±μ ∓ is made with a dataset corresponding to an integrated luminosity of 3.0 fb -1 of proton–proton collisions at centre-of-mass energies of 7 TeV and 8 TeV, collected by the LHCb experiment. Candidate D 0 mesons are selected using the decay D *+ → D 0π + and the D 0 →e ±μ ∓ branching fraction is measured using the decay mode D 0 → K -π + as a normalization channel. No significant excess of D 0→e ±μ ∓ candidates over the expected background is seen, and amore » limit is set on the branching fraction, B(D 0→e ±μ ∓ ) < 1.3 × 10 -8, at 90% confidence level. This is an order of magnitude lower than the previous limit and it further constrains the parameter space in some leptoquark models and in supersymmetric models with R-parity violation.« less

Software for illustrative presentation of basic clinical characteristics of laboratory tests--GraphROC for Windows.

PubMed

Kairisto, V; Poola, A

1995-01-01

GraphROC for Windows is a program for clinical test evaluation. It was designed for the handling of large datasets obtained from clinical laboratory databases. In the user interface, graphical and numerical presentations are combined. For simplicity, numerical data is not shown unless requested. Relevant numbers can be "picked up" from the graph by simple mouse operations. Reference distributions can be displayed by using automatically optimized bin widths. Any percentile of the distribution with corresponding confidence limits can be chosen for display. In sensitivity-specificity analysis, both illness- and health-related distributions are shown in the same graph. The following data for any cutoff limit can be shown in a separate click window: clinical sensitivity and specificity with corresponding confidence limits, positive and negative likelihood ratios, positive and negative predictive values and efficiency. Predictive values and clinical efficiency of the cutoff limit can be updated for any prior probability of disease. Receiver Operating Characteristics (ROC) curves can be generated and combined into the same graph for comparison of several different tests. The area under the curve with corresponding confidence interval is calculated for each ROC curve. Numerical results of analyses and graphs can be printed or exported to other Microsoft Windows programs. GraphROC for Windows also employs a new method, developed by us, for the indirect estimation of health-related limits and change limits from mixed distributions of clinical laboratory data.

Optimal experimental design for improving the estimation of growth parameters of Lactobacillus viridescens from data under non-isothermal conditions.

PubMed

Longhi, Daniel Angelo; Martins, Wiaslan Figueiredo; da Silva, Nathália Buss; Carciofi, Bruno Augusto Mattar; de Aragão, Gláucia Maria Falcão; Laurindo, João Borges

2017-01-02

In predictive microbiology, the model parameters have been estimated using the sequential two-step modeling (TSM) approach, in which primary models are fitted to the microbial growth data, and then secondary models are fitted to the primary model parameters to represent their dependence with the environmental variables (e.g., temperature). The Optimal Experimental Design (OED) approach allows reducing the experimental workload and costs, and the improvement of model identifiability because primary and secondary models are fitted simultaneously from non-isothermal data. Lactobacillus viridescens was selected to this study because it is a lactic acid bacterium of great interest to meat products preservation. The objectives of this study were to estimate the growth parameters of L. viridescens in culture medium from TSM and OED approaches and to evaluate both the number of experimental data and the time needed in each approach and the confidence intervals of the model parameters. Experimental data for estimating the model parameters with TSM approach were obtained at six temperatures (total experimental time of 3540h and 196 experimental data of microbial growth). Data for OED approach were obtained from four optimal non-isothermal profiles (total experimental time of 588h and 60 experimental data of microbial growth), two profiles with increasing temperatures (IT) and two with decreasing temperatures (DT). The Baranyi and Roberts primary model and the square root secondary model were used to describe the microbial growth, in which the parameters b and T min (±95% confidence interval) were estimated from the experimental data. The parameters obtained from TSM approach were b=0.0290 (±0.0020) [1/(h 0.5 °C)] and T min =-1.33 (±1.26) [°C], with R 2 =0.986 and RMSE=0.581, and the parameters obtained with the OED approach were b=0.0316 (±0.0013) [1/(h 0.5 °C)] and T min =-0.24 (±0.55) [°C], with R 2 =0.990 and RMSE=0.436. The parameters obtained from OED approach presented smaller confidence intervals and best statistical indexes than those from TSM approach. Besides, less experimental data and time were needed to estimate the model parameters with OED than TSM. Furthermore, the OED model parameters were validated with non-isothermal experimental data with great accuracy. In this way, OED approach is feasible and is a very useful tool to improve the prediction of microbial growth under non-isothermal condition. Copyright © 2016 Elsevier B.V. All rights reserved.

A Bayesian Surrogate for Regional Skew in Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Kuczera, George

1983-06-01

The problem of how to best utilize site and regional flood data to infer the shape parameter of a flood distribution is considered. One approach to this problem is given in Bulletin 17B of the U.S. Water Resources Council (1981) for the log-Pearson distribution. Here a lesser known distribution is considered, namely, the power normal which fits flood data as well as the log-Pearson and has a shape parameter denoted by λ derived from a Box-Cox power transformation. The problem of regionalizing λ is considered from an empirical Bayes perspective where site and regional flood data are used to infer λ. The distortive effects of spatial correlation and heterogeneity of site sampling variance of λ are explicitly studied with spatial correlation being found to be of secondary importance. The end product of this analysis is the posterior distribution of the power normal parameters expressing, in probabilistic terms, what is known about the parameters given site flood data and regional information on λ. This distribution can be used to provide the designer with several types of information. The posterior distribution of the T-year flood is derived. The effect of nonlinearity in λ on inference is illustrated. Because uncertainty in λ is explicitly allowed for, the understatement in confidence limits due to fixing λ (analogous to fixing log skew) is avoided. Finally, it is shown how to obtain the marginal flood distribution which can be used to select a design flood with specified exceedance probability.

Test-Retest Intervisit Variability of Functional and Structural Parameters in X-Linked Retinoschisis.

PubMed

Jeffrey, Brett G; Cukras, Catherine A; Vitale, Susan; Turriff, Amy; Bowles, Kristin; Sieving, Paul A

2014-09-01

To examine the variability of four outcome measures that could be used to address safety and efficacy in therapeutic trials with X-linked juvenile retinoschisis. Seven men with confirmed mutations in the RS1 gene were evaluated over four visits spanning 6 months. Assessments included visual acuity, full-field electroretinograms (ERG), microperimetric macular sensitivity, and retinal thickness measured by optical coherence tomography (OCT). Eyes were separated into Better or Worse Eye groups based on acuity at baseline. Repeatability coefficients were calculated for each parameter and jackknife resampling used to derive 95% confidence intervals (CIs). The threshold for statistically significant change in visual acuity ranged from three to eight letters. For ERG a-wave, an amplitude reduction greater than 56% would be considered significant. For other parameters, variabilities were lower in the Worse Eye group, likely a result of floor effects due to collapse of the schisis pockets and/or retinal atrophy. The criteria for significant change (Better/Worse Eye) for three important parameters were: ERG b/a-wave ratio (0.44/0.23), point wise sensitivity (10.4/7.0 dB), and central retinal thickness (31%/18%). The 95% CI range for visual acuity, ERG, retinal sensitivity, and central retinal thickness relative to baseline are described for this cohort of participants with X-linked juvenile retinoschisis (XLRS). A quantitative understanding of the variability of outcome measures is vital to establishing the safety and efficacy limits for therapeutic trials of XLRS patients.

Search for D0-D(-)0 mixing and a measurement of the doubly Cabibbo-suppressed decay rate in D0-->Kpi decays.

PubMed

Aubert, B; Barate, R; Boutigny, D; Gaillard, J-M; Hicheur, A; Karyotakis, Y; Lees, J P; Robbe, P; Tisserand, V; Zghiche, A; Palano, A; Pompili, A; Chen, J C; Qi, N D; Rong, G; Wang, P; Zhu, Y S; Eigen, G; Ofte, I; Stugu, B; Abrams, G S; Borgland, A W; Breon, A B; Brown, D N; Button-Shafer, J; Cahn, R N; Charles, E; Day, C T; Gill, M S; Gritsan, A V; Groysman, Y; Jacobsen, R G; Kadel, R W; Kadyk, J; Kerth, L T; Kolomensky, Yu G; Kral, J F; Kukartsev, G; LeClerc, C; Levi, M E; Lynch, G; Mir, L M; Oddone, P J; Orimoto, T J; Pripstein, M; Roe, N A; Romosan, A; Ronan, M T; Shelkov, V G; Telnov, A V; Wenzel, W A; Harrison, T J; Hawkes, C M; Knowles, D J; Penny, R C; Watson, A T; Watson, N K; Deppermann, T; Goetzen, K; Koch, H; Lewandowski, B; Pelizaeus, M; Peters, K; Schmuecker, H; Steinke, M; Barlow, N R; Bhimji, W; Boyd, J T; Chevalier, N; Cottingham, W N; Mackay, C; Wilson, F F; Hearty, C; Mattison, T S; McKenna, J A; Thiessen, D; Kyberd, P; McKemey, A K; Blinov, V E; Bukin, A D; Golubev, V B; Ivanchenko, V N; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Yushkov, A N; Best, D; Chao, M; Kirkby, D; Lankford, A J; Mandelkern, M; McMahon, S; Mommsen, R K; Roethel, W; Stoker, D P; Buchanan, C; Hadavand, H K; Hill, E J; MacFarlane, D B; Paar, H P; Rahatlou, Sh; Schwanke, U; Sharma, V; Berryhill, J W; Campagnari, C; Dahmes, B; Kuznetsova, N; Levy, S L; Long, O; Lu, A; Mazur, M A; Richman, J D; Verkerke, W; Beringer, J; Eisner, A M; Grothe, M; Heusch, C A; Lockman, W S; Schalk, T; Schmitz, R E; Schumm, B A; Seiden, A; Turri, M; Walkowiak, W; Williams, D C; Wilson, M G; Albert, J; Chen, E; Dorsten, M P; Dubois-Felsmann, G P; Dvoretskii, A; Hitlin, D G; Narsky, I; Porter, F C; Ryd, A; Samuel, A; Yang, S; Jayatilleke, S; Mancinelli, G; Meadows, B T; Sokoloff, M D; Barillari, T; Blanc, F; Bloom, P; Clark, P J; Ford, W T; Nauenberg, U; Olivas, A; Rankin, P; Roy, J; Smith, J G; van Hoek, W C; Zhang, L; Harton, J L; Hu, T; Soffer, A; Toki, W H; Wilson, R J; Zhang, J; Altenburg, D; Brandt, T; Brose, J; Colberg, T; Dickopp, M; Dubitzky, R S; Hauke, A; Lacker, H M; Maly, E; Müller-Pfefferkorn, R; Nogowski, R; Otto, S; Schubert, K R; Schwierz, R; Spaan, B; Wilden, L; Bernard, D; Bonneaud, G R; Brochard, F; Cohen-Tanugi, J; Thiebaux, Ch; Vasileiadis, G; Verderi, M; Khan, A; Lavin, D; Muheim, F; Playfer, S; Swain, J E; Tinslay, J; Bozzi, C; Piemontese, L; Sarti, A; Treadwell, E; Anulli, F; Baldini-Ferroli, R; Calcaterra, A; de Sangro, R; Falciai, D; Finocchiaro, G; Patteri, P; Peruzzi, I M; Piccolo, M; Zallo, A; Buzzo, A; Contri, R; Crosetti, G; Lo Vetere, M; Macri, M; Monge, M R; Passaggio, S; Pastore, F C; Patrignani, C; Robutti, E; Santroni, A; Tosi, S; Bailey, S; Morii, M; Grenier, G J; Lee, S-J; Mallik, U; Cochran, J; Crawley, H B; Lamsa, J; Meyer, W T; Prell, S; Rosenberg, E I; Yi, J; Davier, M; Grosdidier, G; Höcker, A; Laplace, S; Le Diberder, F; Lepeltier, V; Lutz, A M; Petersen, T C; Plaszczynski, S; Schune, M H; Tantot, L; Wormser, G; Bionta, R M; Brigljević, V; Cheng, C H; Lange, D J; Wright, D M; Bevan, A J; Fry, J R; Gabathuler, E; Gamet, R; Kay, M; Payne, D J; Sloane, R J; Touramanis, C; Aspinwall, M L; Bowerman, D A; Dauncey, P D; Egede, U; Eschrich, I; Morton, G W; Nash, J A; Sanders, P; Taylor, G P; Back, J J; Bellodi, G; Harrison, P F; Shorthouse, H W; Strother, P; Vidal, P B; Cowan, G; Flaecher, H U; George, S; Green, M G; Kurup, A; Marker, C E; McMahon, T R; Ricciardi, S; Salvatore, F; Vaitsas, G; Winter, M A; Brown, D; Davis, C L; Allison, J; Barlow, R J; Forti, A C; Hart, P A; Jackson, F; Lafferty, G D; Lyon, A J; Weatherall, J H; Williams, J C; Farbin, A; Jawahery, A; Kovalskyi, D; Lae, C K; Lillard, V; Roberts, D A; Blaylock, G; Dallapiccola, C; Flood, K T; Hertzbach, S S; Kofler, R; Koptchev, V B; Moore, T B; Staengle, H; Willocq, S; Cowan, R; Sciolla, G; Taylor, F; Yamamoto, R K; Mangeol, D J J; Milek, M; Patel, P M; Lazzaro, A; Palombo, F; Bauer, J M; Cremaldi, L; Eschenburg, V; Godang, R; Kroeger, R; Reidy, J; Sanders, D A; Summers, D J; Zhao, H W; Hast, C; Taras, P; Nicholson, H; Cartaro, C; Cavallo, N; De Nardo, G; Fabozzi, F; Gatto, C; Lista, L; Paolucci, P; Piccolo, D; Sciacca, C; Baak, M A; Raven, G; LoSecco, J M; Gabriel, T A; Brau, B; Pulliam, T; Brau, J; Frey, R; Iwasaki, M; Potter, C T; Sinev, N B; Strom, D; Torrence, E; Colecchia, F; Dorigo, A; Galeazzi, F; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simonetto, F; Stroili, R; Tiozzo, G; Voci, C; Benayoun, M; Briand, H; Chauveau, J; David, P; de la Vaissière, Ch; Del Buono, L; Hamon, O; Leruste, Ph; Ocariz, J; Pivk, M; Roos, L; Stark, J; T'Jampens, S; Manfredi, P F; Re, V; Gladney, L; Guo, Q H; Panetta, J; Angelini, C; Batignani, G; Bettarini, S; Bondioli, M; Bucci, F; Calderini, G; Carpinelli, M; Forti, F; Giorgi, M A; Lusiani, A; Marchiori, G; Martinez-Vidal, F; Morganti, M; Neri, N; Paoloni, E; Rama, M; Rizzo, G; Sandrelli, F; Walsh, J; Haire, M; Judd, D; Paick, K; Wagoner, D E; Danielson, N; Elmer, P; Lu, C; Miftakov, V; Olsen, J; Smith, A J S; Varnes, E W; Bellini, F; Cavoto, G; del Re, D; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Leonardi, E; Mazzoni, M A; Morganti, S; Pierini, M; Piredda, G; Safai Tehrani, F; Serra, M; Voena, C; Christ, S; Wagner, G; Waldi, R; Adye, T; De Groot, N; Franek, B; Geddes, N I; Gopal, G P; Olaiya, E O; Xella, S M; Aleksan, R; Emery, S; Gaidot, A; Ganzhur, S F; Giraud, P-F; Hamel de Monchenault, G; Kozanecki, W; Langer, M; London, G W; Mayer, B; Schott, G; Vasseur, G; Yeche, Ch; Zito, M; Purohit, M V; Weidemann, A W; Yumiceva, F X; Aston, D; Bartoldus, R; Berger, N; Boyarski, A M; Buchmueller, O L; Convery, M R; Coupal, D P; Dong, D; Dorfan, J; Dujmic, D; Dunwoodie, W; Field, R C; Glanzman, T; Gowdy, S J; Grauges-Pous, E; Hadig, T; Halyo, V; Hryn'ova, T; Innes, W R; Jessop, C P; Kelsey, M H; Kim, P; Kocian, M L; Langenegger, U; Leith, D W G S; Luitz, S; Luth, V; Lynch, H L; Marsiske, H; Menke, S; Messner, R; Muller, D R; O'Grady, C P; Ozcan, V E; Perazzo, A; Perl, M; Petrak, S; Ratcliff, B N; Robertson, S H; Roodman, A; Salnikov, A A; Schindler, R H; Schwiening, J; Simi, G; Snyder, A; Soha, A; Stelzer, J; Su, D; Sullivan, M K; Tanaka, H A; Va'vra, J; Wagner, S R; Weaver, M; Weinstein, A J R; Wisniewski, W J; Wright, D H; Young, C C; Burchat, P R; Meyer, T I; Roat, C; Ahmed, S; Ernst, J A; Bugg, W; Krishnamurthy, M; Spanier, S M; Eckmann, R; Kim, H; Ritchie, J L; Schwitters, R F; Izen, J M; Kitayama, I; Lou, X C; Ye, S; Bianchi, F; Bona, M; Gallo, F; Gamba, D; Borean, C; Bosisio, L; Della Ricca, G; Dittongo, S; Grancagnolo, S; Lanceri, L; Poropat, P; Vitale, L; Vuagnin, G; Panvini, R S; Banerjee, Sw; Brown, C M; Fortin, D; Jackson, P D; Kowalewski, R; Roney, J M; Band, H R; Dasu, S; Datta, M; Eichenbaum, A M; Hu, H; Johnson, J R; Liu, R; Lodovico, F Di; Mohapatra, A K; Pan, Y; Prepost, R; Sekula, S J; von Wimmersperg-Toeller, J H; Wu, J; Wu, S L; Yu, Z; Neal, H

2003-10-24

We present results of a search for D0-D(-)0 mixing and a measurement of R(D), the ratio of doubly Cabibbo-suppressed decays to Cabibbo-favored decays, using D0-->K+pi- decays from 57.1 fb(-1) of data collected near sqrt[s]=10.6 GeV with the BABAR detector at the PEP-II collider. At the 95% confidence level, allowing for CP violation, we find the mixing parameters x('2)<0.0022 and -0.056

Precision timing measurements of PSR J1012+5307

NASA Astrophysics Data System (ADS)

Lange, Ch.; Camilo, F.; Wex, N.; Kramer, M.; Backer, D. C.; Lyne, A. G.; Doroshenko, O.

2001-09-01

We present results and applications of high-precision timing measurements of the binary millisecond pulsar J1012+5307. Combining our radio timing measurements with results based on optical observations, we derive complete 3D velocity information for this system. Correcting for Doppler effects, we derive the intrinsic spin parameters of this pulsar and a characteristic age of 8.6+/-1.9Gyr. Our upper limit for the orbital eccentricity of only 8×10-7 (68 per cent confidence level) is the smallest ever measured for a binary system. We demonstrate that this makes the pulsar an ideal laboratory in which to test certain aspects of alternative theories of gravitation. Our precision measurements suggest deviations from a simple pulsar spin-down timing model, which are consistent with timing noise and the extrapolation of the known behaviour of slowly rotating pulsars.

Two Decades of WRF/CMAQ simulations over the continental ...

EPA Pesticide Factsheets

Confidence in the application of models for forecasting and regulatory assessments is furthered by conducting four types of model evaluation: operational, dynamic, diagnostic, and probabilistic. Operational model evaluation alone does not reveal the confidence limits that can be associated with modeled air quality concentrations. This paper presents novel approaches for performing dynamic model evaluation and for evaluating the confidence limits of ozone exceedances using the WRF/CMAQ model simulations over the continental United States for the period from 1990 to 2010. The methodology presented here entails spectral decomposition of ozone time series using the KZ filter to assess the variations in the strengths of the synoptic (i.e., weather-induced variation) and baseline (i.e., long-term variation attributable to emissions, policy, and trends) forcings embedded in the modeled and observed concentrations. A method is presented where the future year observations are estimated based on the changes in the concentrations predicted by the model applied to the current year observations. The proposed method can provide confidence limits for ozone exceedances for a given emission reduction scenario. We present and discuss these new approaches to identify the strengths of the model in representing the changes in simulated O3 air quality over the 21-year period. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates

In Search of the Largest Possible Tsunami: An Example Following the 2011 Japan Tsunami

NASA Astrophysics Data System (ADS)

Geist, E. L.; Parsons, T.

2012-12-01

Many tsunami hazard assessments focus on estimating the largest possible tsunami: i.e., the worst-case scenario. This is typically performed by examining historic and prehistoric tsunami data or by estimating the largest source that can produce a tsunami. We demonstrate that worst-case assessments derived from tsunami and tsunami-source catalogs are greatly affected by sampling bias. Both tsunami and tsunami sources are well represented by a Pareto distribution. It is intuitive to assume that there is some limiting size (i.e., runup or seismic moment) for which a Pareto distribution is truncated or tapered. Likelihood methods are used to determine whether a limiting size can be determined from existing catalogs. Results from synthetic catalogs indicate that several observations near the limiting size are needed for accurate parameter estimation. Accordingly, the catalog length needed to empirically determine the limiting size is dependent on the difference between the limiting size and the observation threshold, with larger catalog lengths needed for larger limiting-threshold size differences. Most, if not all, tsunami catalogs and regional tsunami source catalogs are of insufficient length to determine the upper bound on tsunami runup. As an example, estimates of the empirical tsunami runup distribution are obtained from the Miyako tide gauge station in Japan, which recorded the 2011 Tohoku-oki tsunami as the largest tsunami among 51 other events. Parameter estimation using a tapered Pareto distribution is made both with and without the Tohoku-oki event. The catalog without the 2011 event appears to have a low limiting tsunami runup. However, this is an artifact of undersampling. Including the 2011 event, the catalog conforms more to a pure Pareto distribution with no confidence in estimating a limiting runup. Estimating the size distribution of regional tsunami sources is subject to the same sampling bias. Physical attenuation mechanisms such as wave breaking likely limit the maximum tsunami runup at a particular site. However, historic and prehistoric data alone cannot determine the upper bound on tsunami runup. Because of problems endemic to sampling Pareto distributions of tsunamis and their sources, we recommend that tsunami hazard assessment be based on a specific design probability of exceedance following a pure Pareto distribution, rather than attempting to determine the worst-case scenario.

Los Alamos National Laboratory W76 Pit Tube Lifetime Study

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

Abeln, Terri G.

2012-04-25

A metallurgical study was requested as part of the Los Alamos National Laboratory (LANL) W76-1 life-extension program (LEP) involving a lifetime analysis of type 304 stainless steel pit tubes subject to repeat bending loads during assembly and disassembly operations at BWXT/Pantex. This initial test phase was completed during the calendar years of 2004-2006 and the report not issued until additional recommended tests could be performed. These tests have not been funded to this date and therefore this report is considered final. Tubes were reportedly fabricated according to Rocky Flats specification P14548 - Seamless Type 304 VIM/VAR Stainless Steel Tubing. Tubemore » diameter was specified as 0.125 inches and wall thickness as 0.028 inches. A heat treat condition is not specified and the hardness range specification can be characteristic of both 1/8 and 1/4 hard conditions. Properties of all tubes tested were within specification. Metallographic analysis could not conclusively determine a specified limit to number of bends allowable. A statistical analysis suggests a range of 5-7 bends with a 99.95% confidence limit. See the 'Statistical Analysis' section of this report. The initial phase of this study involved two separate sets of test specimens. The first group was part of an investigation originating in the ESA-GTS [now Gas Transfer Systems (W-7) Group]. After the bend cycle test parameters were chosen (all three required bends subjected to the same amount of bend cycles) and the tubes bent, the investigation was transferred to Terri Abeln (Metallurgical Science and Engineering) for analysis. Subsequently, another limited quantity of tubes became available for testing and were cycled with the same bending fixture, but with different test parameters determined by T. Abeln.« less

SU-E-T-649: Quality Assurances for Proton Therapy Delivery Equipment

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

Arjomandy, B; Kase, Y; Flanz, J

2015-06-15

Purpose: The number of proton therapy centers has increased dramatically over the past decade. Currently, there is no comprehensive set of guidelines that addresses quality assurance (QA) procedures for the different technologies used for proton therapy. The AAPM has charged task group 224 (TG-224) to provide recommendations for QA required for accurate and safe dose delivery, using existing and next generation proton therapy delivery equipment. Methods: A database comprised of QA procedures and tolerance limits was generated from many existing proton therapy centers in and outside of the US. These consist of proton therapy centers that possessed double scattering, uniformmore » scanning, and pencil beams delivery systems. The diversity in beam delivery systems as well as the existing devices to perform QA checks for different beam parameters is the main subject of TG-224. Based on current practice at the clinically active proton centers participating in this task group, consensus QA recommendations were developed. The methodologies and requirements of the parameters that must be verified for consistency of the performance of the proton beam delivery systems are discussed. Results: TG-224 provides procedures and QA checks for mechanical, imaging, safety and dosimetry requirements for different proton equipment. These procedures are categorized based on their importance and their required frequencies in order to deliver a safe and consistent dose. The task group provides daily, weekly, monthly, and annual QA check procedures with their tolerance limits. Conclusions: The procedures outlined in this protocol provide sufficient information to qualified medical physicists to perform QA checks for any proton delivery system. Execution of these procedures should provide confidence that proton therapy equipment is functioning as commissioned for patient treatment and delivers dose safely and accurately within the established tolerance limits. The report will be published in late 2015.« less

Experimental optimization of the number of blocks by means of algorithms parameterized by confidence interval in popcorn breeding.

PubMed

Paula, T O M; Marinho, C D; Amaral Júnior, A T; Peternelli, L A; Gonçalves, L S A

2013-06-27

The objective of this study was to determine the optimal number of repetitions to be used in competition trials of popcorn traits related to production and quality, including grain yield and expansion capacity. The experiments were conducted in 3 environments representative of the north and northwest regions of the State of Rio de Janeiro with 10 Brazilian genotypes of popcorn, consisting by 4 commercial hybrids (IAC 112, IAC 125, Zélia, and Jade), 4 improved varieties (BRS Ângela, UFVM-2 Barão de Viçosa, Beija-flor, and Viçosa) and 2 experimental populations (UNB2U-C3 and UNB2U-C4). The experimental design utilized was a randomized complete block design with 7 repetitions. The Bootstrap method was employed to obtain samples of all of the possible combinations within the 7 blocks. Subsequently, the confidence intervals of the parameters of interest were calculated for all simulated data sets. The optimal number of repetition for all of the traits was considered when all of the estimates of the parameters in question were encountered within the confidence interval. The estimates of the number of repetitions varied according to the parameter estimated, variable evaluated, and environment cultivated, ranging from 2 to 7. It is believed that only the expansion capacity traits in the Colégio Agrícola environment (for residual variance and coefficient of variation), and number of ears per plot, in the Itaocara environment (for coefficient of variation) needed 7 repetitions to fall within the confidence interval. Thus, for the 3 studies conducted, we can conclude that 6 repetitions are optimal for obtaining high experimental precision.

Surveillance metrics sensitivity study.

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

Hamada, Michael S.; Bierbaum, Rene Lynn; Robertson, Alix A.

2011-09-01

In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculationsmore » and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.« less

Surveillance Metrics Sensitivity Study

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

Bierbaum, R; Hamada, M; Robertson, A

2011-11-01

In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculationsmore » and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.« less

Sensitivity analysis of respiratory parameter uncertainties: impact of criterion function form and constraints.

PubMed

Lutchen, K R

1990-08-01

A sensitivity analysis based on weighted least-squares regression is presented to evaluate alternative methods for fitting lumped-parameter models to respiratory impedance data. The goal is to maintain parameter accuracy simultaneously with practical experiment design. The analysis focuses on predicting parameter uncertainties using a linearized approximation for joint confidence regions. Applications are with four-element parallel and viscoelastic models for 0.125- to 4-Hz data and a six-element model with separate tissue and airway properties for input and transfer impedance data from 2-64 Hz. The criterion function form was evaluated by comparing parameter uncertainties when data are fit as magnitude and phase, dynamic resistance and compliance, or real and imaginary parts of input impedance. The proper choice of weighting can make all three criterion variables comparable. For the six-element model, parameter uncertainties were predicted when both input impedance and transfer impedance are acquired and fit simultaneously. A fit to both data sets from 4 to 64 Hz could reduce parameter estimate uncertainties considerably from those achievable by fitting either alone. For the four-element models, use of an independent, but noisy, measure of static compliance was assessed as a constraint on model parameters. This may allow acceptable parameter uncertainties for a minimum frequency of 0.275-0.375 Hz rather than 0.125 Hz. This reduces data acquisition requirements from a 16- to a 5.33- to 8-s breath holding period. These results are approximations, and the impact of using the linearized approximation for the confidence regions is discussed.

Morphology parameters for intracranial aneurysm rupture risk assessment.

PubMed

Dhar, Sujan; Tremmel, Markus; Mocco, J; Kim, Minsuok; Yamamoto, Junichi; Siddiqui, Adnan H; Hopkins, L Nelson; Meng, Hui

2008-08-01

The aim of this study is to identify image-based morphological parameters that correlate with human intracranial aneurysm (IA) rupture. For 45 patients with terminal or sidewall saccular IAs (25 unruptured, 20 ruptured), three-dimensional geometries were evaluated for a range of morphological parameters. In addition to five previously studied parameters (aspect ratio, aneurysm size, ellipticity index, nonsphericity index, and undulation index), we defined three novel parameters incorporating the parent vessel geometry (vessel angle, aneurysm [inclination] angle, and [aneurysm-to-vessel] size ratio) and explored their correlation with aneurysm rupture. Parameters were analyzed with a two-tailed independent Student's t test for significance; significant parameters (P < 0.05) were further examined by multivariate logistic regression analysis. Additionally, receiver operating characteristic analyses were performed on each parameter. Statistically significant differences were found between mean values in ruptured and unruptured groups for size ratio, undulation index, nonsphericity index, ellipticity index, aneurysm angle, and aspect ratio. Logistic regression analysis further revealed that size ratio (odds ratio, 1.41; 95% confidence interval, 1.03-1.92) and undulation index (odds ratio, 1.51; 95% confidence interval, 1.08-2.11) had the strongest independent correlation with ruptured IA. From the receiver operating characteristic analysis, size ratio and aneurysm angle had the highest area under the curve values of 0.83 and 0.85, respectively. Size ratio and aneurysm angle are promising new morphological metrics for IA rupture risk assessment. Because these parameters account for vessel geometry, they may bridge the gap between morphological studies and more qualitative location-based studies.

Estimation of the ARNO model baseflow parameters using daily streamflow data

NASA Astrophysics Data System (ADS)

Abdulla, F. A.; Lettenmaier, D. P.; Liang, Xu

1999-09-01

An approach is described for estimation of baseflow parameters of the ARNO model, using historical baseflow recession sequences extracted from daily streamflow records. This approach allows four of the model parameters to be estimated without rainfall data, and effectively facilitates partitioning of the parameter estimation procedure so that parsimonious search procedures can be used to estimate the remaining storm response parameters separately. Three methods of optimization are evaluated for estimation of four baseflow parameters. These methods are the downhill Simplex (S), Simulated Annealing combined with the Simplex method (SA) and Shuffled Complex Evolution (SCE). These estimation procedures are explored in conjunction with four objective functions: (1) ordinary least squares; (2) ordinary least squares with Box-Cox transformation; (3) ordinary least squares on prewhitened residuals; (4) ordinary least squares applied to prewhitened with Box-Cox transformation of residuals. The effects of changing the seed random generator for both SA and SCE methods are also explored, as are the effects of the bounds of the parameters. Although all schemes converge to the same values of the objective function, SCE method was found to be less sensitive to these issues than both the SA and the Simplex schemes. Parameter uncertainty and interactions are investigated through estimation of the variance-covariance matrix and confidence intervals. As expected the parameters were found to be correlated and the covariance matrix was found to be not diagonal. Furthermore, the linearized confidence interval theory failed for about one-fourth of the catchments while the maximum likelihood theory did not fail for any of the catchments.

Evenly spaced Detrended Fluctuation Analysis: Selecting the number of points for the diffusion plot

NASA Astrophysics Data System (ADS)

Liddy, Joshua J.; Haddad, Jeffrey M.

2018-02-01

Detrended Fluctuation Analysis (DFA) has become a widely-used tool to examine the correlation structure of a time series and provided insights into neuromuscular health and disease states. As the popularity of utilizing DFA in the human behavioral sciences has grown, understanding its limitations and how to properly determine parameters is becoming increasingly important. DFA examines the correlation structure of variability in a time series by computing α, the slope of the log SD- log n diffusion plot. When using the traditional DFA algorithm, the timescales, n, are often selected as a set of integers between a minimum and maximum length based on the number of data points in the time series. This produces non-uniformly distributed values of n in logarithmic scale, which influences the estimation of α due to a disproportionate weighting of the long-timescale regions of the diffusion plot. Recently, the evenly spaced DFA and evenly spaced average DFA algorithms were introduced. Both algorithms compute α by selecting k points for the diffusion plot based on the minimum and maximum timescales of interest and improve the consistency of α estimates for simulated fractional Gaussian noise and fractional Brownian motion time series. Two issues that remain unaddressed are (1) how to select k and (2) whether the evenly-spaced DFA algorithms show similar benefits when assessing human behavioral data. We manipulated k and examined its effects on the accuracy, consistency, and confidence limits of α in simulated and experimental time series. We demonstrate that the accuracy and consistency of α are relatively unaffected by the selection of k. However, the confidence limits of α narrow as k increases, dramatically reducing measurement uncertainty for single trials. We provide guidelines for selecting k and discuss potential uses of the evenly spaced DFA algorithms when assessing human behavioral data.

NASA Langley's Approach to the Sandia's Structural Dynamics Challenge Problem

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Kenny, Sean P.; Crespo, Luis G.; Elliott, Kenny B.

2007-01-01

The objective of this challenge is to develop a data-based probabilistic model of uncertainty to predict the behavior of subsystems (payloads) by themselves and while coupled to a primary (target) system. Although this type of analysis is routinely performed and representative of issues faced in real-world system design and integration, there are still several key technical challenges that must be addressed when analyzing uncertain interconnected systems. For example, one key technical challenge is related to the fact that there is limited data on target configurations. Moreover, it is typical to have multiple data sets from experiments conducted at the subsystem level, but often samples sizes are not sufficient to compute high confidence statistics. In this challenge problem additional constraints are placed as ground rules for the participants. One such rule is that mathematical models of the subsystem are limited to linear approximations of the nonlinear physics of the problem at hand. Also, participants are constrained to use these models and the multiple data sets to make predictions about the target system response under completely different input conditions. Our approach involved initially the screening of several different methods. Three of the ones considered are presented herein. The first one is based on the transformation of the modal data to an orthogonal space where the mean and covariance of the data are matched by the model. The other two approaches worked solutions in physical space where the uncertain parameter set is made of masses, stiffnesses and damping coefficients; one matches confidence intervals of low order moments of the statistics via optimization while the second one uses a Kernel density estimation approach. The paper will touch on all the approaches, lessons learned, validation 1 metrics and their comparison, data quantity restriction, and assumptions/limitations of each approach. Keywords: Probabilistic modeling, model validation, uncertainty quantification, kernel density

An MLE method for finding LKB NTCP model parameters using Monte Carlo uncertainty estimates

NASA Astrophysics Data System (ADS)

Carolan, Martin; Oborn, Brad; Foo, Kerwyn; Haworth, Annette; Gulliford, Sarah; Ebert, Martin

2014-03-01

The aims of this work were to establish a program to fit NTCP models to clinical data with multiple toxicity endpoints, to test the method using a realistic test dataset, to compare three methods for estimating confidence intervals for the fitted parameters and to characterise the speed and performance of the program.

Uncertainty estimation of the self-thinning process by Maximum-Entropy Principle

Treesearch

Shoufan Fang; George Z. Gertner

2000-01-01

When available information is scarce, the Maximum-Entropy Principle can estimate the distributions of parameters. In our case study, we estimated the distributions of the parameters of the forest self-thinning process based on literature information, and we derived the conditional distribution functions and estimated the 95 percent confidence interval (CI) of the self-...

Search for W' $$\\to $$ tb decays in the lepton + jets final state in pp collisions at $$\\sqrt{s}$$ = 8 TeV

DOE PAGES

Chatrchyan, Serguei

2014-05-23

Results are presented from a search for the production of a heavy gauge boson W' decaying into a top and a bottom quark, using a data set collected by the CMS experiment at sqrt(s) = 8 TeV and corresponding to an integrated luminosity of 19.5 inverse femtobarns. Various models of W'-boson production are studied by allowing for an arbitrary combination of left- and right-handed couplings. The analysis is based on the detection of events with a lepton (e, mu), jets, and missing transverse energy in the final state. No evidence for W'-boson production is found and 95% confidence level uppermore » limits on the production cross section times branching fraction are obtained. For W' bosons with purely right-handed couplings, and for those with left-handed couplings assuming no interference effects, the observed 95% confidence level limit is M(W') > 2.05 TeV. For W' bosons with purely left-handed couplings, including interference effects, the observed 95% confidence level limit is M(W') > 1.84 TeV. The results presented in this paper are the most stringent limits published to date.« less

Single Platform Geolocation of Radio Frequency Emitters

DTIC Science & Technology

2015-03-26

Error SNR Signal to Noise Ratio SOI Signal of Interest STK Systems Tool Kit UCA Uniform Circular Array WGS World Geodetic System xv SINGLE PLATFORM...Section 2.6 describes a method to visualize the confidence of estimated parameters. 2.1 Coordinate Systems and Reference Frames The following...be used to visualize the confidence surface using the method developed in Section 2.6. The NLO method will be shown to be the minimization of the

IMPACT OF INTERNAL LIMITING MEMBRANE PEELING ON MACULAR HOLE REOPENING: A Systematic Review and Meta-Analysis.

PubMed

Rahimy, Ehsan; McCannel, Colin A

2016-04-01

To assess the literature regarding macular hole reopening rates stratified by whether the internal limiting membrane (ILM) was peeled during vitrectomy surgery. Systematic review and meta-analysis of studies reporting on macular hole reopenings among previously surgically closed idiopathic macular holes. A comprehensive literature search using the National Library of Medicine PubMed interface was used to identify potentially eligible publications in English. The minimum mean follow-up period for reports to be included in this study was 12 months. Analysis was divided into eyes that underwent vitrectomy with and without ILM peeling. The primary outcome parameter was the proportion of macular hole reopenings among previously closed holes between the two groups. Secondary outcome parameters included duration from initial surgery to hole reopening and preoperative and postoperative best-corrected correct visual acuities among the non-ILM peeling and ILM peeling groups. A total of 50 publications reporting on 5,480 eyes met inclusion criteria and were assessed in this meta-analysis. The reopening rate without ILM peeling was 7.12% (125 of 1,756 eyes), compared with 1.18% (44 of 3,724 eyes) with ILM peeling (odds ratio: 0.16; 95% confidence interval: 0.11-0.22; Fisher's exact test: P < 0.0001). There were no other identifiable associations or risk factors for reopening. The results of this meta-analysis support the concept that ILM peeling during macular hole surgery reduces the likelihood of macular hole reopening.

Laboratory Studies on Surface Sampling of Bacillus anthracis Contamination: Summary, Gaps, and Recommendations

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

Piepel, Gregory F.; Amidan, Brett G.; Hu, Rebecca

2011-11-28

This report summarizes previous laboratory studies to characterize the performance of methods for collecting, storing/transporting, processing, and analyzing samples from surfaces contaminated by Bacillus anthracis or related surrogates. The focus is on plate culture and count estimates of surface contamination for swab, wipe, and vacuum samples of porous and nonporous surfaces. Summaries of the previous studies and their results were assessed to identify gaps in information needed as inputs to calculate key parameters critical to risk management in biothreat incidents. One key parameter is the number of samples needed to make characterization or clearance decisions with specified statistical confidence. Othermore » key parameters include the ability to calculate, following contamination incidents, the (1) estimates of Bacillus anthracis contamination, as well as the bias and uncertainties in the estimates, and (2) confidence in characterization and clearance decisions for contaminated or decontaminated buildings. Gaps in knowledge and understanding identified during the summary of the studies are discussed and recommendations are given for future studies.« less

Real-Time Stability and Control Derivative Extraction From F-15 Flight Data

NASA Technical Reports Server (NTRS)

Smith, Mark S.; Moes, Timothy R.; Morelli, Eugene A.

2003-01-01

A real-time, frequency-domain, equation-error parameter identification (PID) technique was used to estimate stability and control derivatives from flight data. This technique is being studied to support adaptive control system concepts currently being developed by NASA (National Aeronautics and Space Administration), academia, and industry. This report describes the basic real-time algorithm used for this study and implementation issues for onboard usage as part of an indirect-adaptive control system. A confidence measures system for automated evaluation of PID results is discussed. Results calculated using flight data from a modified F-15 aircraft are presented. Test maneuvers included pilot input doublets and automated inputs at several flight conditions. Estimated derivatives are compared to aerodynamic model predictions. Data indicate that the real-time PID used for this study performs well enough to be used for onboard parameter estimation. For suitable test inputs, the parameter estimates converged rapidly to sufficient levels of accuracy. The devised confidence measures used were moderately successful.

Non-robust dynamic inferences from macroeconometric models: Bifurcation stratification of confidence regions

NASA Astrophysics Data System (ADS)

Barnett, William A.; Duzhak, Evgeniya Aleksandrovna

2008-06-01

Grandmont [J.M. Grandmont, On endogenous competitive business cycles, Econometrica 53 (1985) 995-1045] found that the parameter space of the most classical dynamic models is stratified into an infinite number of subsets supporting an infinite number of different kinds of dynamics, from monotonic stability at one extreme to chaos at the other extreme, and with many forms of multiperiodic dynamics in between. The econometric implications of Grandmont’s findings are particularly important, if bifurcation boundaries cross the confidence regions surrounding parameter estimates in policy-relevant models. Stratification of a confidence region into bifurcated subsets seriously damages robustness of dynamical inferences. Recently, interest in policy in some circles has moved to New-Keynesian models. As a result, in this paper we explore bifurcation within the class of New-Keynesian models. We develop the econometric theory needed to locate bifurcation boundaries in log-linearized New-Keynesian models with Taylor policy rules or inflation-targeting policy rules. Central results needed in this research are our theorems on the existence and location of Hopf bifurcation boundaries in each of the cases that we consider.

Validating a two-high-threshold measurement model for confidence rating data in recognition.

PubMed

Bröder, Arndt; Kellen, David; Schütz, Julia; Rohrmeier, Constanze

2013-01-01

Signal Detection models as well as the Two-High-Threshold model (2HTM) have been used successfully as measurement models in recognition tasks to disentangle memory performance and response biases. A popular method in recognition memory is to elicit confidence judgements about the presumed old/new status of an item, allowing for the easy construction of ROCs. Since the 2HTM assumes fewer latent memory states than response options are available in confidence ratings, the 2HTM has to be extended by a mapping function which models individual rating scale usage. Unpublished data from 2 experiments in Bröder and Schütz (2009) validate the core memory parameters of the model, and 3 new experiments show that the response mapping parameters are selectively affected by manipulations intended to affect rating scale use, and this is independent of overall old/new bias. Comparisons with SDT show that both models behave similarly, a case that highlights the notion that both modelling approaches can be valuable (and complementary) elements in a researcher's toolbox.

Impact of influent data frequency and model structure on the quality of WWTP model calibration and uncertainty.

PubMed

Cierkens, Katrijn; Plano, Salvatore; Benedetti, Lorenzo; Weijers, Stefan; de Jonge, Jarno; Nopens, Ingmar

2012-01-01

Application of activated sludge models (ASMs) to full-scale wastewater treatment plants (WWTPs) is still hampered by the problem of model calibration of these over-parameterised models. This either requires expert knowledge or global methods that explore a large parameter space. However, a better balance in structure between the submodels (ASM, hydraulic, aeration, etc.) and improved quality of influent data result in much smaller calibration efforts. In this contribution, a methodology is proposed that links data frequency and model structure to calibration quality and output uncertainty. It is composed of defining the model structure, the input data, an automated calibration, confidence interval computation and uncertainty propagation to the model output. Apart from the last step, the methodology is applied to an existing WWTP using three models differing only in the aeration submodel. A sensitivity analysis was performed on all models, allowing the ranking of the most important parameters to select in the subsequent calibration step. The aeration submodel proved very important to get good NH(4) predictions. Finally, the impact of data frequency was explored. Lowering the frequency resulted in larger deviations of parameter estimates from their default values and larger confidence intervals. Autocorrelation due to high frequency calibration data has an opposite effect on the confidence intervals. The proposed methodology opens doors to facilitate and improve calibration efforts and to design measurement campaigns.

Influence of different dose calculation algorithms on the estimate of NTCP for lung complications.

PubMed

Hedin, Emma; Bäck, Anna

2013-09-06

Due to limitations and uncertainties in dose calculation algorithms, different algorithms can predict different dose distributions and dose-volume histograms for the same treatment. This can be a problem when estimating the normal tissue complication probability (NTCP) for patient-specific dose distributions. Published NTCP model parameters are often derived for a different dose calculation algorithm than the one used to calculate the actual dose distribution. The use of algorithm-specific NTCP model parameters can prevent errors caused by differences in dose calculation algorithms. The objective of this work was to determine how to change the NTCP model parameters for lung complications derived for a simple correction-based pencil beam dose calculation algorithm, in order to make them valid for three other common dose calculation algorithms. NTCP was calculated with the relative seriality (RS) and Lyman-Kutcher-Burman (LKB) models. The four dose calculation algorithms used were the pencil beam (PB) and collapsed cone (CC) algorithms employed by Oncentra, and the pencil beam convolution (PBC) and anisotropic analytical algorithm (AAA) employed by Eclipse. Original model parameters for lung complications were taken from four published studies on different grades of pneumonitis, and new algorithm-specific NTCP model parameters were determined. The difference between original and new model parameters was presented in relation to the reported model parameter uncertainties. Three different types of treatments were considered in the study: tangential and locoregional breast cancer treatment and lung cancer treatment. Changing the algorithm without the derivation of new model parameters caused changes in the NTCP value of up to 10 percentage points for the cases studied. Furthermore, the error introduced could be of the same magnitude as the confidence intervals of the calculated NTCP values. The new NTCP model parameters were tabulated as the algorithm was varied from PB to PBC, AAA, or CC. Moving from the PB to the PBC algorithm did not require new model parameters; however, moving from PB to AAA or CC did require a change in the NTCP model parameters, with CC requiring the largest change. It was shown that the new model parameters for a given algorithm are different for the different treatment types.

Searches for millisecond pulsations in low-mass X-ray binaries, 2

NASA Technical Reports Server (NTRS)

Vaughan, B. A.; Van Der Klis, M.; Wood, K. S.; Norris, J. P.; Hertz, P.; Michelson, P. F.; Paradijs, J. Van; Lewin, W. H. G.; Mitsuda, K.; Penninx, W.

1994-01-01

Coherent millisecond X-ray pulsations are expected from low-mass X-ray binaries (LMXBs), but remain undetected. Using the single-parameter Quadratic Coherence Recovery Technique (QCRT) to correct for unknown binary orbit motion, we have performed Fourier transform searches for coherent oscillations in all long, continuous segments of data obtained at 1 ms time resolution during Ginga observations of LMXB. We have searched the six known Z sources (GX 5-1, Cyg X-2, Sco X-1, GX 17+2, GX 340+0, and GX 349+2), seven of the 14 known atoll sources (GX 3+1. GX 9+1, GX 9+9, 1728-33. 1820-30, 1636-53 and 1608-52), the 'peculiar' source Cir X-1, and the high-mass binary Cyg X-3. We find no evidence for coherent pulsations in any of these sources, with 99% confidence limits on the pulsed fraction between 0.3% and 5.0% at frequencies below the Nyquist frequency of 512 Hz. A key assumption made in determining upper limits in previous searches is shown to be incorrect. We provide a recipe for correctly setting upper limits and detection thresholds. Finally we discuss and apply two strategies to improve sensitivity by utilizing multiple, independent, continuous segments of data with comparable count rates.

The challenges of modelling phosphorus in a headwater catchment: Applying a 'limits of acceptability' uncertainty framework to a water quality model

NASA Astrophysics Data System (ADS)

Hollaway, M. J.; Beven, K. J.; Benskin, C. McW. H.; Collins, A. L.; Evans, R.; Falloon, P. D.; Forber, K. J.; Hiscock, K. M.; Kahana, R.; Macleod, C. J. A.; Ockenden, M. C.; Villamizar, M. L.; Wearing, C.; Withers, P. J. A.; Zhou, J. G.; Barber, N. J.; Haygarth, P. M.

2018-03-01

There is a need to model and predict the transfer of phosphorus (P) from land to water, but this is challenging because of the large number of complex physical and biogeochemical processes involved. This study presents, for the first time, a 'limits of acceptability' approach of the Generalized Likelihood Uncertainty Estimation (GLUE) framework to the Soil and Water Assessment Tool (SWAT), in an application to a water quality problem in the Newby Beck catchment (12.5 km2), Cumbria, United Kingdom (UK). Using high frequency outlet data (discharge and P), individual evaluation criteria (limits of acceptability) were assigned to observed discharge and P loads for all evaluation time steps, identifying where the model was performing well/poorly and to infer which processes required improvement in the model structure. Initial limits of acceptability were required to be relaxed by a substantial amount (by factors of between 5.3 and 6.7 on a normalized scale depending on the evaluation criteria used) in order to gain a set of behavioral simulations (1001 and 1016, respectively out of 5,000,000). Of the 39 model parameters tested, the representation of subsurface processes and associated parameters, were consistently shown as critical to the model not meeting the evaluation criteria, irrespective of the chosen evaluation metric. It is therefore concluded that SWAT is not an appropriate model to guide P management in this catchment. This approach highlights the importance of high frequency monitoring data for setting robust model evaluation criteria. It also raises the question as to whether it is possible to have sufficient input data available to drive such models so that we can have confidence in their predictions and their ability to inform catchment management strategies to tackle the problem of diffuse pollution from agriculture.

Neutron multiplicity counting: Confidence intervals for reconstruction parameters

DOE PAGES

Verbeke, Jerome M.

2016-03-09

From nuclear materials accountability to homeland security, the need for improved nuclear material detection, assay, and authentication has grown over the past decades. Starting in the 1940s, neutron multiplicity counting techniques have enabled quantitative evaluation of masses and multiplications of fissile materials. In this paper, we propose a new method to compute uncertainties on these parameters using a model-based sequential Bayesian processor, resulting in credible regions in the fissile material mass and multiplication space. These uncertainties will enable us to evaluate quantitatively proposed improvements to the theoretical fission chain model. Additionally, because the processor can calculate uncertainties in real time,more » it is a useful tool in applications such as portal monitoring: monitoring can stop as soon as a preset confidence of non-threat is reached.« less

Mass media and heterogeneous bounds of confidence in continuous opinion dynamics

NASA Astrophysics Data System (ADS)

Pineda, M.; Buendía, G. M.

2015-02-01

This work focuses on the effects of an external mass media on continuous opinion dynamics with heterogeneous bounds of confidence. We modified the original Deffuant et al. and Hegselmann and Krause models to incorporate both, an external mass media and a heterogeneous distribution of confidence levels. We analysed two cases, one where only two bounds of confidence are taken into account, and other where each individual of the system has her/his own characteristic level of confidence. We found that, in the absence of mass media, diversity of bounds of confidence can improve the capacity of the systems to reach consensus. We show that the persuasion capacity of the external message is optimal for intermediate levels of heterogeneity. Our simulations also show the existence, for certain parameter values, of a counter-intuitive effect in which the persuasion capacity of the mass media decreases if the mass media intensity is too large. We discuss similarities and differences between the two heterogeneous versions of these continuous opinion dynamic models under the influence of mass media.

Anchoring effects in the judgment of confidence: semantic or numeric priming?

PubMed

Carroll, Steven R; Petrusic, William M; Leth-Steensen, Craig

2009-02-01

Over the last decade, researchers have debated whether anchoring effects are the result of semantic or numeric priming. The present study tested both hypotheses. In four experiments involving a sensory detection task, participants first made a relative confidence judgment by deciding whether they were more or less confident than an anchor value in the correctness of their decision. Subsequently, they expressed an absolute level of confidence. In two of these experiments, the relative confidence anchor values represented the midpoints between the absolute confidence scale values, which were either explicitly numeric or semantic, nonnumeric representations of magnitude. In two other experiments, the anchor values were drawn from a scale modally different from that used to express the absolute confidence (i.e., nonnumeric and numeric, respectively, or vice versa). Regardless of the nature of the anchors, the mean confidence ratings revealed anchoring effects only when the relative and absolute confidence values were drawn from identical scales. Together, the results of these four experiments limit the conditions under which both numeric and semantic priming would be expected to lead to anchoring effects.

Indoor radon regulation using tabulated values of temporal radon variation.

PubMed

Tsapalov, Andrey; Kovler, Konstantin

2018-03-01

Mass measurements of indoor radon concentrations have been conducted for about 30 years. In most of the countries, a national reference/action/limit level is adopted, limiting the annual average indoor radon (AAIR) concentration. However, until now, there is no single and generally accepted international protocol for determining the AAIR with a known confidence interval, based on measurements of different durations. Obviously, as the duration of measurements increases, the uncertainty of the AAIR estimation decreases. The lack of the information about the confidence interval of the determined AAIR level does not allow correct comparison with the radon reference level. This greatly complicates development of an effective indoor radon measurement protocol and strategy. The paper proposes a general principle of indoor radon regulation, based on the simple criteria widely used in metrology, and introduces a new parameter - coefficient of temporal radon variation K V (t) that depends on the measurement duration and determines the uncertainty of the AAIR. An algorithm for determining K V (t) based on the results of annual continuous radon monitoring in experimental rooms is proposed. Included are indoor radon activity concentrations and equilibrium equivalent concentration (EEC) of radon progeny. The monitoring was conducted in 10 selected experimental rooms located in 7 buildings, mainly in the Moscow region (Russia), from 2006 to 2013. The experimental and tabulated values of K V (t) and also the values of the coefficient of temporal EEC variation depending on the mode and duration of the measurements were obtained. The recommendations to improve the efficiency and reliability of indoor radon regulation are given. The importance of taking into account the geological factors is discussed. The representativity of the results of the study is estimated and the approach for their verification is proposed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Truncation of the Accretion Disk at One-third of the Eddington Limit in the Neutron Star Low-mass X-Ray Binary Aquila X-1

NASA Astrophysics Data System (ADS)

Ludlam, R. M.; Miller, J. M.; Degenaar, N.; Sanna, A.; Cackett, E. M.; Altamirano, D.; King, A. L.

2017-10-01

We perform a reflection study on a new observation of the neutron star (NS) low-mass X-ray binary Aquila X-1 taken with NuSTAR during the 2016 August outburst and compare with the 2014 July outburst. The source was captured at ˜32% L Edd, which is over four times more luminous than the previous observation during the 2014 outburst. Both observations exhibit a broadened Fe line profile. Through reflection modeling, we determine that the inner disk is truncated {R}{in,2016}={11}-1+2 {R}g (where R g = GM/c 2) and {R}{in,2014}=14+/- 2 {R}g (errors quoted at the 90% confidence level). Fiducial NS parameters (M NS = 1.4 M ⊙, R NS = 10 km) give a stellar radius of R NS = 4.85 R g ; our measurements rule out a disk extending to that radius at more than the 6σ level of confidence. We are able to place an upper limit on the magnetic field strength of B ≤ 3.0-4.5 × 109 G at the magnetic poles, assuming that the disk is truncated at the magnetospheric radius in each case. This is consistent with previous estimates of the magnetic field strength for Aquila X-1. However, if the magnetosphere is not responsible for truncating the disk prior to the NS surface, we estimate a boundary layer with a maximum extent of {R}{BL,2016}˜ 10 {R}g and {R}{BL,2014}˜ 6 {R}g. Additionally, we compare the magnetic field strength inferred from the Fe line profile of Aquila X-1 and other NS low-mass X-ray binaries to known accreting millisecond X-ray pulsars.

Benchmark duration of work hours for development of fatigue symptoms in Japanese workers with adjustment for job-related stress.

PubMed

Suwazono, Yasushi; Dochi, Mirei; Kobayashi, Etsuko; Oishi, Mitsuhiro; Okubo, Yasushi; Tanaka, Kumihiko; Sakata, Kouichi

2008-12-01

The objective of this study was to calculate benchmark durations and lower 95% confidence limits for benchmark durations of working hours associated with subjective fatigue symptoms by applying the benchmark dose approach while adjusting for job-related stress using multiple logistic regression analyses. A self-administered questionnaire was completed by 3,069 male and 412 female daytime workers (age 18-67 years) in a Japanese steel company. The eight dependent variables in the Cumulative Fatigue Symptoms Index were decreased vitality, general fatigue, physical disorders, irritability, decreased willingness to work, anxiety, depressive feelings, and chronic tiredness. Independent variables were daily working hours, four subscales (job demand, job control, interpersonal relationship, and job suitability) of the Brief Job Stress Questionnaire, and other potential covariates. Using significant parameters for working hours and those for other covariates, the benchmark durations of working hours were calculated for the corresponding Index property. Benchmark response was set at 5% or 10%. Assuming a condition of worst job stress, the benchmark duration/lower 95% confidence limit for benchmark duration of working hours per day with a benchmark response of 5% or 10% were 10.0/9.4 or 11.7/10.7 (irritability) and 9.2/8.9 or 10.4/9.8 (chronic tiredness) in men and 8.9/8.4 or 9.8/8.9 (chronic tiredness) in women. The threshold amounts of working hours for fatigue symptoms under the worst job-related stress were very close to the standard daily working hours in Japan. The results strongly suggest that special attention should be paid to employees whose working hours exceed threshold amounts based on individual levels of job-related stress.

N-mixture models for estimating population size from spatially replicated counts

USGS Publications Warehouse

Royle, J. Andrew

2004-01-01

Spatial replication is a common theme in count surveys of animals. Such surveys often generate sparse count data from which it is difficult to estimate population size while formally accounting for detection probability. In this article, i describe a class of models (n-mixture models) which allow for estimation of population size from such data. The key idea is to view site-specific population sizes, n, as independent random variables distributed according to some mixing distribution (e.g., Poisson). Prior parameters are estimated from the marginal likelihood of the data, having integrated over the prior distribution for n. Carroll and lombard (1985, journal of american statistical association 80, 423-426) proposed a class of estimators based on mixing over a prior distribution for detection probability. Their estimator can be applied in limited settings, but is sensitive to prior parameter values that are fixed a priori. Spatial replication provides additional information regarding the parameters of the prior distribution on n that is exploited by the n-mixture models and which leads to reasonable estimates of abundance from sparse data. A simulation study demonstrates superior operating characteristics (bias, confidence interval coverage) of the n-mixture estimator compared to the caroll and lombard estimator. Both estimators are applied to point count data on six species of birds illustrating the sensitivity to choice of prior on p and substantially different estimates of abundance as a consequence.

A classification of the galaxy groups

NASA Technical Reports Server (NTRS)

Anosova, Joanna P.

1990-01-01

A statistical criterion has been proposed to reveal the random and physical clusterings among stars, galaxies and other objects. This criterion has been applied to the galaxy triples of the list by Karachentseva, Karaschentsev and Scherbanovsky, and the double galaxies of the list by Dahari where the primary components are the Seyfert galaxies. The confident physical, probable physical, probable optical and confident optical groups have been identified. The limit difference of radial velocities of components for the confident physical multiple galaxies has also been estimated.

Holt-Winters Forecasting: A Study of Practical Applications for Healthcare Managers

DTIC Science & Technology

2006-05-25

Winters Forecasting 5 List of Tables Table 1. Holt-Winters smoothing parameters and Mean Absolute Percentage Errors: Pseudoephedrine prescriptions Table 2...confidence intervals Holt-Winters Forecasting 6 List of Figures Figure 1. Line Plot of Pseudoephedrine Prescriptions forecast using smoothing parameters...The first represents monthly prescriptions of pseudoephedrine . Pseudoephedrine is a drug commonly prescribed to relieve nasal congestion and other

A Violation of the Conditional Independence Assumption in the Two-High-Threshold Model of Recognition Memory

ERIC Educational Resources Information Center

Chen, Tina; Starns, Jeffrey J.; Rotello, Caren M.

2015-01-01

The 2-high-threshold (2HT) model of recognition memory assumes that test items result in distinct internal states: they are either detected or not, and the probability of responding at a particular confidence level that an item is "old" or "new" depends on the state-response mapping parameters. The mapping parameters are…

Confidence estimation for quantitative photoacoustic imaging

NASA Astrophysics Data System (ADS)

Gröhl, Janek; Kirchner, Thomas; Maier-Hein, Lena

2018-02-01

Quantification of photoacoustic (PA) images is one of the major challenges currently being addressed in PA research. Tissue properties can be quantified by correcting the recorded PA signal with an estimation of the corresponding fluence. Fluence estimation itself, however, is an ill-posed inverse problem which usually needs simplifying assumptions to be solved with state-of-the-art methods. These simplifications, as well as noise and artifacts in PA images reduce the accuracy of quantitative PA imaging (PAI). This reduction in accuracy is often localized to image regions where the assumptions do not hold true. This impedes the reconstruction of functional parameters when averaging over entire regions of interest (ROI). Averaging over a subset of voxels with a high accuracy would lead to an improved estimation of such parameters. To achieve this, we propose a novel approach to the local estimation of confidence in quantitative reconstructions of PA images. It makes use of conditional probability densities to estimate confidence intervals alongside the actual quantification. It encapsulates an estimation of the errors introduced by fluence estimation as well as signal noise. We validate the approach using Monte Carlo generated data in combination with a recently introduced machine learning-based approach to quantitative PAI. Our experiments show at least a two-fold improvement in quantification accuracy when evaluating on voxels with high confidence instead of thresholding signal intensity.

Limits on νμ(νμ)-->ντ(ντ) and νμ(νμ)-->(νe)νe oscillations from a precision measurement of neutrino-nucleon neutral current interactions

NASA Astrophysics Data System (ADS)

McFarland, K. S.; Naples, D.; Arroyo, C. G.; Auchincloss, P.; de Barbaro, P.; Bazarko, A. O.; Bernstein, R. H.; Bodek, A.; Bolton, T.; Budd, H.; Conrad, J.; Drucker, R. B.; Harris, D. A.; Johnson, R. A.; Kim, J. H.; King, B. J.; Kinnel, T.; Koizumi, G.; Koutsoliotas, S.; Lamm, M. J.; Lefmann, W. C.; Marsh, W.; McNulty, C.; Mishra, S. R.; Nienaber, P.; Nussbaum, M.; Oreglia, M. J.; Perera, L.; Quintas, P. Z.; Romosan, A.; Sakumoto, W. K.; Schumm, B. A.; Sciulli, F. J.; Seligman, W. G.; Shaevitz, M. H.; Smith, W. H.; Spentzouris, P.; Steiner, R.; Stern, E. G.; Vakili, M.; Yang, U. K.

1995-11-01

We present limits on νμ(νμ)-->ντ(ντ) and νμ(νμ)-->νe(νe) oscillations based on a study of inclusive νN interactions performed using the CCFR massive coarse-grained detector in the Fermilab Tevatron Quadrupole Triplet neutrino beam. The sensitivity to oscillations is from the difference in the longitudinal energy deposition pattern of νμN vs ντN or νeN charged-current interactions. The νμ energies ranged from 30 to 500 GeV with a mean of 140 GeV. The minimum and maximum νμ flight lengths are 0.9 and 1.4 km, respectively. For νμ-->ντ oscillations, the lowest 90% confidence upper limit in sin22α of 2.7×10-3 is obtained at Δm2~50 eV2. This result is the most stringent limit to date for 25<Δm2<90 eV2. For νμ-->νe oscillations, the lowest 90% confidence upper limit in sin22α of 1.9×10-3 is obtained at Δm2~350 eV2. This result is the most stringent limit to date for 250<Δm2<450 eV2, and also excludes at 90% confidence much of the high Δm2 region favored by the recent LSND observation.

Intermediate follow-up of a composite stentless porcine valved conduit of bovine pericardium in the pulmonary circulation.

PubMed

Aupècle, Bertrand; Serraf, Alain; Belli, Emre; Mohammadi, Siamak; Lacour-Gayet, François; Fornes, Paul; Planché, Claude

2002-07-01

In the pediatric population, glutaraldehyde-preserved bovine pericardium conduit containing a stentless porcine valve has been proposed as an alternative to homografts for right ventricular outflow tract reconstruction. Between June 1996 and March 2000, a total of 55 patients, 20 with truncus arteriosus, 21 with pulmonary atresia with ventricular septal defect, and 14 with miscellaneous defects, received this conduit. Median age at implantation was 3.4 months (range, 3 days to 19 years), and 27 patients (50%) were less than 3 months old. Clinical outcome, echocardiographic data, and pathologic analysis were recorded. End points for conduit failure were conduit replacement or dilation. A mean follow-up of 27 months (range, 2 to 46 months) was available for 47 survivors. Procedure for conduit obstruction was required in 13 patients. The most common procedure was operation, and all but 3 patients had an unsuccessful balloon angioplasty before reoperation. Actuarial freedom from conduit dilation or reoperation was 93.6% (95% confidence limits, 82% to 99%), 81.9% (95% confidence limits, 64% to 91%), 77.8% (95% confidence limits, 39% to 78%), and 64.3% (95% confidence limits, 26% to 73%) at 1, 2, 3, and 4 postoperative years, respectively. Univariate analysis identified small conduit size as a risk factor for conduit obstruction. Although this new conduit was not free from progressive obstruction, our clinical results (easy to work and good valvular function) and the availability in small sizes encouraged us to use it as an alternative to small-size homografts when those were not available.

Method validation for chemical composition determination by electron microprobe with wavelength dispersive spectrometer

NASA Astrophysics Data System (ADS)

Herrera-Basurto, R.; Mercader-Trejo, F.; Muñoz-Madrigal, N.; Juárez-García, J. M.; Rodriguez-López, A.; Manzano-Ramírez, A.

2016-07-01

The main goal of method validation is to demonstrate that the method is suitable for its intended purpose. One of the advantages of analytical method validation is translated into a level of confidence about the measurement results reported to satisfy a specific objective. Elemental composition determination by wavelength dispersive spectrometer (WDS) microanalysis has been used over extremely wide areas, mainly in the field of materials science, impurity determinations in geological, biological and food samples. However, little information is reported about the validation of the applied methods. Herein, results of the in-house method validation for elemental composition determination by WDS are shown. SRM 482, a binary alloy Cu-Au of different compositions, was used during the validation protocol following the recommendations for method validation proposed by Eurachem. This paper can be taken as a reference for the evaluation of the validation parameters more frequently requested to get the accreditation under the requirements of the ISO/IEC 17025 standard: selectivity, limit of detection, linear interval, sensitivity, precision, trueness and uncertainty. A model for uncertainty estimation was proposed including systematic and random errors. In addition, parameters evaluated during the validation process were also considered as part of the uncertainty model.

Inclusive Search for Supersymmetry Using Razor Variables in p p Collisions at s = 7 TeV

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

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

An inclusive search is presented for new heavy particle pairs produced inmore » $$\\sqrt{s}$$ = 7 TeV proton-proton collisions at the LHC using 4.7 +/- 0.1 inverse femtobarns of integrated luminosity. The selected events are analyzed in the 2D razor space of MR, an event-by-event indicator of the heavy particle mass scale, and R, a dimensionless variable related to the missing transverse energy. The third-generation sector is probed using the event heavy-flavor content. The search is sensitive to generic supersymmetry models with minimal assumptions about the superpartner decay chains. No excess is observed in the number of events beyond that predicted by the standard model. Exclusion limits are derived in the CMSSM framework as well as for simplified models. Within the CMSSM parameter space considered, gluino masses up to 800 GeV and squark masses up to 1.35 TeV are excluded at 95% confidence level depending on the model parameters. The direct production of pairs of stop or sbottom quarks is excluded for masses as high as 400 GeV.« less

Search for dark matter in association with a Higgs boson decaying to two photons at s = 13 TeV with the ATLAS detector

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

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

A search for dark matter in association with a Higgs boson decaying to two photons is presented. This study is based on data collected with the ATLAS detector, corresponding to an integrated luminosity of 36.1 fb -1 of proton-proton collisions at the LHC at a center-of-mass energy of 13 TeV in 2015 and 2016. No significant excess over the expected background is observed. Upper limits at 95% confidence level are set on the visible cross section for beyond the Standard Model physics processes, and the production cross section times branching fraction of the Standard Model Higgs boson decaying into twomore » photons in association with missing transverse momentum in three different benchmark models. Finally, limits at 95% confidence level are also set on the observed signal in two-dimensional mass planes. Additionally, the results are interpreted in terms of 90% confidence-level limits on the dark-matter–nucleon scattering cross section, as a function of the dark-matter particle mass, for a spin-independent scenario.« less

The Malpelo Plate Hypothesis and implications for nonclosure of the Cocos-Nazca-Pacific plate motion circuit

NASA Astrophysics Data System (ADS)

Zhang, Tuo; Gordon, Richard G.; Mishra, Jay K.; Wang, Chengzu

2017-08-01

Using global multiresolution topography, we estimate new transform-fault azimuths along the Cocos-Nazca plate boundary and show that the direction of relative plate motion is 3.3° ± 1.8° (95% confidence limits) clockwise of prior estimates. The new direction of Cocos-Nazca plate motion is, moreover, 4.9° ± 2.7° (95% confidence limits) clockwise of the azimuth of the Panama transform fault. We infer that the plate east of the Panama transform fault is not the Nazca plate but instead is a microplate that we term the Malpelo plate. With the improved transform-fault data, the nonclosure of the Nazca-Cocos-Pacific plate motion circuit is reduced from 15.0 mm a-1 ± 3.8 mm a-1 to 11.6 mm a-1 ± 3.8 mm a-1 (95% confidence limits). The nonclosure seems too large to be due entirely to horizontal thermal contraction of oceanic lithosphere and suggests that one or more additional plate boundaries remain to be discovered.

Search for dark matter in association with a Higgs boson decaying to two photons at √{s }=13 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Christodoulou, V.; Chromek-Burckhart, D.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Eramo, L.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vasconcelos Corga, K.; de Vivie de Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Bello, F. A.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Petrillo, K. F.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. 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T.; 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, 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.; Minegishi, Y.; Ming, Y.; Mir, L. M.; 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.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. 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S.; Neumann, M.; Newman, P. R.; Ng, T. Y.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. 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.; Nowak, S.; 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.; 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.; Oppen, H.; 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.; 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.; 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.; 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.; 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, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Poulard, G.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; 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, G.; Qin, Y.; Quadt, A.; 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.; Rangel-Smith, C.; 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.; 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.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; 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.; Roe, S.; Rogan, C. S.; Røhne, O.; 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.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Rothberg, J.; Rousseau, 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.; 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.; Sakurai, Y.; 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 Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; 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.; Sarrazin, B.; Sasaki, O.; Sato, K.; 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.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; 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.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, Dms; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; 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.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; 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, 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. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; 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, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamatani, M.; 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.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, 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.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2017-12-01

A search for dark matter in association with a Higgs boson decaying to two photons is presented. This study is based on data collected with the ATLAS detector, corresponding to an integrated luminosity of 36.1 fb-1 of proton-proton collisions at the LHC at a center-of-mass energy of 13 TeV in 2015 and 2016. No significant excess over the expected background is observed. Upper limits at 95% confidence level are set on the visible cross section for beyond the Standard Model physics processes, and the production cross section times branching fraction of the Standard Model Higgs boson decaying into two photons in association with missing transverse momentum in three different benchmark models. Limits at 95% confidence level are also set on the observed signal in two-dimensional mass planes. Additionally, the results are interpreted in terms of 90% confidence-level limits on the dark-matter-nucleon scattering cross section, as a function of the dark-matter particle mass, for a spin-independent scenario.

Search for dark matter in association with a Higgs boson decaying to two photons at s = 13 TeV with the ATLAS detector

DOE PAGES

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

2017-12-08

A search for dark matter in association with a Higgs boson decaying to two photons is presented. This study is based on data collected with the ATLAS detector, corresponding to an integrated luminosity of 36.1 fb -1 of proton-proton collisions at the LHC at a center-of-mass energy of 13 TeV in 2015 and 2016. No significant excess over the expected background is observed. Upper limits at 95% confidence level are set on the visible cross section for beyond the Standard Model physics processes, and the production cross section times branching fraction of the Standard Model Higgs boson decaying into twomore » photons in association with missing transverse momentum in three different benchmark models. Finally, limits at 95% confidence level are also set on the observed signal in two-dimensional mass planes. Additionally, the results are interpreted in terms of 90% confidence-level limits on the dark-matter–nucleon scattering cross section, as a function of the dark-matter particle mass, for a spin-independent scenario.« less

An Evaluation of the Predictive Validity of Confidence Ratings in Identifying Functional Behavioral Assessment Hypothesis Statements

ERIC Educational Resources Information Center

Borgmeier, Chris; Horner, Robert H.

2006-01-01

Faced with limited resources, schools require tools that increase the accuracy and efficiency of functional behavioral assessment. Yarbrough and Carr (2000) provided evidence that informant confidence ratings of the likelihood of problem behavior in specific situations offered a promising tool for predicting the accuracy of function-based…

Test of the cosmic transparency with the standard candles and the standard ruler

NASA Astrophysics Data System (ADS)

Chen, Jun

In this paper, the cosmic transparency is constrained by using the latest baryon acoustic oscillation (BAO) data and the type Ia supernova data with a model-independent method. We find that a transparent universe is consistent with observational data at the 1σ confidence level, except for the case of BAO+ Union 2.1 without the systematic errors where a transparent universe is favored only at the 2σ confidence level. To investigate the effect of the uncertainty of the Hubble constant on the test of the cosmic opacity, we assume h to be a free parameter and obtain that the observations favor a transparent universe at the 1σ confidence level.

Value of Computed Tomographic Perfusion-Based Patient Selection for Intra-Arterial Acute Ischemic Stroke Treatment.

PubMed

Borst, Jordi; Berkhemer, Olvert A; Roos, Yvo B W E M; van Bavel, Ed; van Zwam, Wim H; van Oostenbrugge, Robert J; van Walderveen, Marianne A A; Lingsma, Hester F; van der Lugt, Aad; Dippel, Diederik W J; Yoo, Albert J; Marquering, Henk A; Majoie, Charles B L M

2015-12-01

The utility of computed tomographic perfusion (CTP)-based patient selection for intra-arterial treatment of acute ischemic stroke has not been proven in randomized trials and requires further study in a cohort that was not selected based on CTP. Our objective was to study the relationship between CTP-derived parameters and outcome and treatment effect in patients with acute ischemic stroke because of a proximal intracranial arterial occlusion. We included 175 patients who underwent CTP in the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in The Netherlands (MR CLEAN). Association of CTP-derived parameters (ischemic-core volume, penumbra volume, and percentage ischemic core) with outcome was estimated with multivariable ordinal logistic regression as an adjusted odds ratio for a shift in the direction of a better outcome on the modified Rankin Scale. Interaction between CTP-derived parameters and treatment effect was determined using multivariable ordinal logistic regression. Interaction with treatment effect was also tested for mismatch (core <70 mL; penumbra core >1.2; penumbra core >10 mL). The adjusted odds ratio for improved functional outcome for ischemic core, percentage ischemic core, and penumbra were 0.79 per 10 mL (95% confidence interval: 0.71-0.89; P<0.001), 0.82 per 10% (95% confidence interval: 0.66-0.90; P=0.002), and 0.97 per 10 mL (96% confidence interval: 0.92-1.01; P=0.15), respectively. No significant interaction between any of the CTP-derived parameters and treatment effect was observed. We observed no significant interaction between mismatch and treatment effect. CTP seems useful for predicting functional outcome, but cannot reliably identify patients who will not benefit from intra-arterial therapy. © 2015 American Heart Association, Inc.

POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear Models

PubMed Central

Johnson, Jacqueline L.; Muller, Keith E.; Slaughter, James C.; Gurka, Matthew J.; Gribbin, Matthew J.; Simpson, Sean L.

2014-01-01

The POWERLIB SAS/IML software provides convenient power calculations for a wide range of multivariate linear models with Gaussian errors. The software includes the Box, Geisser-Greenhouse, Huynh-Feldt, and uncorrected tests in the “univariate” approach to repeated measures (UNIREP), the Hotelling Lawley Trace, Pillai-Bartlett Trace, and Wilks Lambda tests in “multivariate” approach (MULTIREP), as well as a limited but useful range of mixed models. The familiar univariate linear model with Gaussian errors is an important special case. For estimated covariance, the software provides confidence limits for the resulting estimated power. All power and confidence limits values can be output to a SAS dataset, which can be used to easily produce plots and tables for manuscripts. PMID:25400516

The effect of esthetic crown lengthening on perceptions of a patient's attractiveness, friendliness, trustworthiness, intelligence, and self-confidence.

PubMed

Malkinson, Sam; Waldrop, Thomas C; Gunsolley, John C; Lanning, Sharon K; Sabatini, Robert

2013-08-01

Smile esthetics have been shown to play a major role in the perception of whether a person is attractive, and whether they are perceived as friendly, trustworthy, intelligent, and self-confident. A proposed major determinant of the esthetics of a smile is the amount of gingival display, which can be excessive in cases of altered passive eruption. The aim of this study is to see whether altering the amount of gingival display of patients would affect dental professionals' and laypersons' perceptions of the aforementioned social parameters. Patients were identified as having altered passive eruption and excessive gingival display. Smiling "control" photographs were taken and then digitally altered so as to lengthen the teeth and thus reduce the amount of gingival display. These became the "test" photographs. The control and test photographs were shown in random order. The control group of evaluators consisted of senior dental students, and the test group of evaluators comprised students who had no formal dental training. Groups were asked to rate, on a visual analog scale, each picture's attractiveness, friendliness, trustworthiness, intelligence, and self-confidence. The test pictures with less gingival display were consistently and statistically significantly rated higher for all five social parameters than were their control counterparts (P <0.0001). When analyzed as an isolated effect, there were no statistically significant differences between the control group and the test group of evaluators when rating the pictures. Pictures depicting African Americans were judged to be more trustworthy (P = 0.0467) and self-confident (P = 0.0490) than pictures depicting white individuals. Pictures depicting women were judged to be more trustworthy (P = 0.0159) and intelligent (P = 0.0329) than pictures depicting men. All the social parameters were positively and statistically significantly correlated with each other (P <0.0001). Excessive gingival display did negatively affect how attractive a person's smile is judged to be. In addition, how friendly, trustworthy, intelligent, and self-confident a person was perceived to be was inversely related to the amount of gingival display. Untrained laypeople were just as sensitive to these differences as senior dental students.

Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics.

PubMed

Vaas, Lea A I; Sikorski, Johannes; Michael, Victoria; Göker, Markus; Klenk, Hans-Peter

2012-01-01

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data.

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

PubMed Central

Vaas, Lea A. I.; Sikorski, Johannes; Michael, Victoria; Göker, Markus; Klenk, Hans-Peter

2012-01-01

Background The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed ‘-omics’ techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. Methodology The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. Conclusions We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data. PMID:22536335

Influence of stellar multiplicity on planet formation. I. Evidence of suppressed planet formation due to stellar companions within 20 au and validation of four planets from the Kepler multiple planet candidates

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

Wang, Ji; Fischer, Debra A.; Xie, Ji-Wei

2014-03-01

The planet occurrence rate for multiple stars is important in two aspects. First, almost half of stellar systems in the solar neighborhood are multiple systems. Second, the comparison of the planet occurrence rate for multiple stars to that for single stars sheds light on the influence of stellar multiplicity on planet formation and evolution. We developed a method of distinguishing planet occurrence rates for single and multiple stars. From a sample of 138 bright (K{sub P} < 13.5) Kepler multi-planet candidate systems, we compared the stellar multiplicity rate of these planet host stars to that of field stars. Using dynamicalmore » stability analyses and archival Doppler measurements, we find that the stellar multiplicity rate of planet host stars is significantly lower than field stars for semimajor axes less than 20 AU, suggesting that planet formation and evolution are suppressed by the presence of a close-in companion star at these separations. The influence of stellar multiplicity at larger separations is uncertain because of search incompleteness due to a limited Doppler observation time baseline and a lack of high-resolution imaging observation. We calculated the planet confidence for the sample of multi-planet candidates and find that the planet confidences for KOI 82.01, KOI 115.01, KOI 282.01, and KOI 1781.02 are higher than 99.7% and thus validate the planetary nature of these four planet candidates. This sample of bright Kepler multi-planet candidates with refined stellar and orbital parameters, planet confidence estimation, and nearby stellar companion identification offers a well-characterized sample for future theoretical and observational study.« less

Mechanism-based pharmacokinetic-pharmacodynamic modeling of the antinociceptive effect of buprenorphine in healthy volunteers.

PubMed

Yassen, Ashraf; Olofsen, Erik; Romberg, Raymonda; Sarton, Elise; Danhof, Meindert; Dahan, Albert

2006-06-01

The objective of this investigation was to characterize the pharmacokinetic-pharmacodynamic relation of buprenorphine's antinociceptive effect in healthy volunteers. Data on the time course of the antinociceptive effect after intravenous administration of 0.05-0.6 mg/70 kg buprenorphine in healthy volunteers was analyzed in conjunction with plasma concentrations by nonlinear mixed-effects analysis. A three-compartment pharmacokinetic model best described the concentration time course. Four structurally different pharmacokinetic-pharmacodynamic models were evaluated for their appropriateness to describe the time course of buprenorphine's antinociceptive effect: (1) E(max) model with an effect compartment model, (2) "power" model with an effect compartment model, (3) receptor association-dissociation model with a linear transduction function, and (4) combined biophase equilibration/receptor association-dissociation model with a linear transduction function. The latter pharmacokinetic-pharmacodynamic model described the time course of effect best and was used to explain time dependencies in buprenorphine's pharmacodynamics. The model converged, yielding precise estimation of the parameters characterizing hysteresis and the relation between relative receptor occupancy and antinociceptive effect. The rate constant describing biophase equilibration (k(eo)) was 0.00447 min(-1) (95% confidence interval, 0.00299-0.00595 min(-1)). The receptor dissociation rate constant (k(off)) was 0.0785 min(-1) (95% confidence interval, 0.0352-0.122 min(-1)), and k(on) was 0.0631 ml . ng(-1) . min(-1) (95% confidence interval, 0.0390-0.0872 ml . ng(-1) . min(-1)). This is consistent with observations in rats, suggesting that the rate-limiting step in the onset and offset of the antinociceptive effect is biophase distribution rather than slow receptor association-dissociation. In the dose range studied, no saturation of receptor occupancy occurred explaining the lack of a ceiling effect for antinociception.

Art in a new light: Design and assessment of illuminants to reduce photochemical degradation of works of art

NASA Astrophysics Data System (ADS)

Delgado Ramos, Monica Fabiola

The purpose of this research is to design the best lighting that will minimize long term photochemical degradation of Old Master Drawings and/or other works of art, while maintaining the patron's appreciation of the object's color and detail. The present approach is a technological refinement to the basic underlying earlier work on fluorescent lighting by W. A. Thornton, W.A. at General Electric1. Thin-film dielectric, multi-coating technology is used to create filters that eliminate ultraviolet light, near infrared light and significant unnecessary parts from the visible spectrum, thus maximizing the reduction in photochemical degradation, while maintaining optimal color rendering. Three interference filters, were designed and manufactured successfully. The filters are designated Mark 1, Mark 2, & Mark 3. In this dissertation, the filters are analyzed with regard to their performance parameters. This includes color rendering, retardation in fading or color change, beam angle effects, filter stability, perceived brightness, and visual appreciation parameters. To a high confidence level, all three filters are perceived as being indistinguishable from Unfiltered light with regard to the color confusion index parameter (CCI). Subjective assessments by tests subjects suggest the Mark 3 filter may display some distinguishability with a confidence level for distinguishability of 35% for the overall satisfaction parameter. The Mark 3 filter is the most complex three-color type spectral profile and this might be expected due to beam angle effects or departures in accuracy of color theory. Beam angle affects suggest that the Mark 1 and Mark 2 filters do not display significant color rendering aberrations due to Newton's colors interference effects, except possibly at the periphery of the broadest (55-60+°) beam angle lamps. Filtered and Unfiltered light are effectively of the same perceived brightness, though to a low confidence level, Unfiltered light might be perceived brighter. Accelerated aging studies of the filters indicate useful mean time before failures of >20 years. In fact, no failure was observed in any of the accelerated studies, The Mark 2 and Mark 3 filters were evaluated in equal-luminosity studies with regard to their effect on limiting fading of both standard fading samples such as the ISO Blue Wool series, and also other commercial pigments or stains. Within experimental error, the Mark 2 filter either slowed fading or had no effect on fading for all pigments relative to Unfiltered light and OptivexRTM filtered light, OptivexRTM being a common commercial filter used to protect works of art. Mark 3 protected in many cases, but for some pigments it was less protective than OptivexRTM filtered light. This failure is interpreted in terms of the wavelength dependence of the excess light in certain wavelength regions on an equal luminosity condition, and suggests that more subtle wavelength dependent optimizations have to be undertaken for filters which possess significant band separation.

Perceived Effort of Walking: Relationship With Gait, Physical Function and Activity, Fear of Falling, and Confidence in Walking in Older Adults With Mobility Limitations

PubMed Central

Julius, Leslie M.; Brach, Jennifer S.; Wert, David M.

2012-01-01

Background Although clinicians have a number of measures to use to describe walking performance, few, if any, of the measures capture a person's perceived effort in walking. Perceived effort of walking may be a factor in what a person does versus what he or she is able to do. Objective The objective of this study was to examine the relationship of perceived effort of walking with gait, function, activity, fear of falling, and confidence in walking in older adults with mobility limitations. Design This investigation was a cross-sectional, descriptive, relational study. Methods The study took place at a clinical research training center. The participants were 50 older adults (mean age=76.8 years, SD=5.5) with mobility limitations. The measurements used were the Rating of Perceived Exertion (RPE) for walking; gait speed; the Modified Gait Abnormality Rating Scale; energy cost of walking; Late Life Function and Disability Instrument (LLFDI) for total, basic, and advanced lower-extremity function and for disability limitations; activity and restriction subscales of the Survey of Activities and Fear of Falling in the Elderly (SAFFE); activity counts; SAFFE fear subscale; and Gait Efficacy Scale (GES). The relationship of the RPE of walking with gait, function, activity, fear, and confidence was determined by using Spearman rank order coefficients and an analysis of variance (adjusted for age and sex) for mean differences between groups defined by no exertion during walking and some exertion during walking. Results The RPE was related to confidence in walking (GES, R=−.326, P=.021) and activity (activity counts, R=.295, P=.044). The RPE groups (no exertion versus some exertion) differed in LLFDI scores for total (57.9 versus 53.2), basic (68.6 versus 61.4), and advanced (49.1 versus 42.6) lower-extremity function; LLFDI scores for disability limitations (74.9 versus 67.5); SAFFE fear subscale scores (0.346 versus 0.643); and GES scores (80.1 versus 67.8) (all P<.05). Limitations The range of RPE scores for the participants studied was narrow. Thus, the real correlations between RPE and gait, physical function, and psychological aspects of walking may be greater than the relationships reported. Conclusions The perceived effort of walking was associated with physical activity and confidence in walking. Reducing the perceived effort of walking may be an important target of interventions to slow the decline in function of older adults with mobility limitations. PMID:22723433

Perceived effort of walking: relationship with gait, physical function and activity, fear of falling, and confidence in walking in older adults with mobility limitations.

PubMed

Julius, Leslie M; Brach, Jennifer S; Wert, David M; VanSwearingen, Jessie M

2012-10-01

Although clinicians have a number of measures to use to describe walking performance, few, if any, of the measures capture a person's perceived effort in walking. Perceived effort of walking may be a factor in what a person does versus what he or she is able to do. The objective of this study was to examine the relationship of perceived effort of walking with gait, function, activity, fear of falling, and confidence in walking in older adults with mobility limitations. Design This investigation was a cross-sectional, descriptive, relational study. The study took place at a clinical research training center. The participants were 50 older adults (mean age=76.8 years, SD=5.5) with mobility limitations. The measurements used were the Rating of Perceived Exertion (RPE) for walking; gait speed; the Modified Gait Abnormality Rating Scale; energy cost of walking; Late Life Function and Disability Instrument (LLFDI) for total, basic, and advanced lower-extremity function and for disability limitations; activity and restriction subscales of the Survey of Activities and Fear of Falling in the Elderly (SAFFE); activity counts; SAFFE fear subscale; and Gait Efficacy Scale (GES). The relationship of the RPE of walking with gait, function, activity, fear, and confidence was determined by using Spearman rank order coefficients and an analysis of variance (adjusted for age and sex) for mean differences between groups defined by no exertion during walking and some exertion during walking. The RPE was related to confidence in walking (GES, R=-.326, P=.021) and activity (activity counts, R=.295, P=.044). The RPE groups (no exertion versus some exertion) differed in LLFDI scores for total (57.9 versus 53.2), basic (68.6 versus 61.4), and advanced (49.1 versus 42.6) lower-extremity function; LLFDI scores for disability limitations (74.9 versus 67.5); SAFFE fear subscale scores (0.346 versus 0.643); and GES scores (80.1 versus 67.8) (all P<.05). Limitations The range of RPE scores for the participants studied was narrow. Thus, the real correlations between RPE and gait, physical function, and psychological aspects of walking may be greater than the relationships reported. The perceived effort of walking was associated with physical activity and confidence in walking. Reducing the perceived effort of walking may be an important target of interventions to slow the decline in function of older adults with mobility limitations.

Weighted regression analysis and interval estimators

Treesearch

Donald W. Seegrist

1974-01-01

A method for deriving the weighted least squares estimators for the parameters of a multiple regression model. Confidence intervals for expected values, and prediction intervals for the means of future samples are given.

Uremic Pruritus is Associated with Two-Year Cardiovascular Mortality in Long Term Hemodialysis Patients.

PubMed

Weng, Cheng-Hao; Hu, Ching-Chih; Yen, Tzung-Hai; Hsu, Ching-Wei; Huang, Wen-Hung

2018-06-15

Uremic pruritus (UP) is an unpleasant complication in patients undergoing maintenance dialysis. Cardiovascular and infection related deaths are the major causes of mortality in patients undergoing dialysis. Studies on the correlation between cardiovascular or infection related mortality and UP are limited. We analyze 866 maintenance hemodialysis (MHD) patients in our hemodialysis centers. Clinical parameters and 24-month cardiovascular and infection-related mortality are recorded. The associations between all-cause, cardiovascular and infection related mortality with clinical data including UP are analyzed. Multivariate Cox regression demonstrated that UP is a significantly predictor for 24-month cardiovascular mortality in the MHD patients (Hazard ratio: 3.164; 95% confidence interval, 1.743-5.744; p < 0.001). Uremic pruritus is one of the predictor of 24-month cardiovascular mortality in MHD patients. © 2018 The Author(s). Published by S. Karger AG, Basel.

Search for a dark photon in e(+)e(-) collisions at BABAR.

PubMed

Lees, J P; Poireau, V; Tisserand, V; Grauges, E; Palano, A; Eigen, G; Stugu, B; Brown, D N; Feng, M; Kerth, L T; Kolomensky, Yu G; Lee, M J; Lynch, G; Koch, H; Schroeder, T; Hearty, C; Mattison, T S; McKenna, J A; So, R Y; Khan, A; Blinov, V E; Buzykaev, A R; Druzhinin, V P; Golubev, V B; Kravchenko, E A; Onuchin, A P; Serednyakov, S I; Skovpen, Yu I; Solodov, E P; Todyshev, K Yu; Lankford, A J; Mandelkern, M; Dey, B; Gary, J W; Long, O; Campagnari, C; Franco Sevilla, M; Hong, T M; Kovalskyi, D; Richman, J D; West, C A; Eisner, A M; Lockman, W S; Panduro Vazquez, W; Schumm, B A; Seiden, A; Chao, D S; Cheng, C H; Echenard, B; Flood, K T; Hitlin, D G; Miyashita, T S; Ongmongkolkul, P; Porter, F C; Andreassen, R; Huard, Z; Meadows, B T; Pushpawela, B G; Sokoloff, M D; Sun, L; Bloom, P C; Ford, W T; Gaz, A; Smith, J G; Wagner, S R; Ayad, R; Toki, W H; Spaan, B; Bernard, D; Verderi, M; Playfer, S; Bettoni, D; Bozzi, C; Calabrese, R; Cibinetto, G; Fioravanti, E; Garzia, I; Luppi, E; Piemontese, L; Santoro, V; Calcaterra, A; de Sangro, R; Finocchiaro, G; Martellotti, S; Patteri, P; Peruzzi, I M; Piccolo, M; Rama, M; Zallo, A; Contri, R; Lo Vetere, M; Monge, M R; Passaggio, S; Patrignani, C; Robutti, E; Bhuyan, B; Prasad, V; Adametz, A; Uwer, U; Lacker, H M; Dauncey, P D; Mallik, U; Chen, C; Cochran, J; Prell, S; Ahmed, H; Gritsan, A V; Arnaud, N; Davier, M; Derkach, D; Grosdidier, G; Le Diberder, F; Lutz, A M; Malaescu, B; Roudeau, P; Stocchi, A; Wormser, G; Lange, D J; Wright, D M; Coleman, J P; Fry, J R; Gabathuler, E; Hutchcroft, D E; Payne, D J; Touramanis, C; Bevan, A J; Di Lodovico, F; Sacco, R; Cowan, G; Bougher, J; Brown, D N; Davis, C L; Denig, A G; Fritsch, M; Gradl, W; Griessinger, K; Hafner, A; Schubert, K R; Barlow, R J; Lafferty, G D; Cenci, R; Hamilton, B; Jawahery, A; Roberts, D A; Cowan, R; Sciolla, G; Cheaib, R; Patel, P M; Robertson, S H; Neri, N; Palombo, F; Cremaldi, L; Godang, R; Sonnek, P; Summers, D J; Simard, M; Taras, P; De Nardo, G; Onorato, G; Sciacca, C; Martinelli, M; Raven, G; Jessop, C P; LoSecco, J M; Honscheid, K; Kass, R; Feltresi, E; Margoni, M; Morandin, M; Posocco, M; Rotondo, M; Simi, G; Simonetto, F; Stroili, R; Akar, S; Ben-Haim, E; Bomben, M; Bonneaud, G R; Briand, H; Calderini, G; Chauveau, J; Leruste, Ph; Marchiori, G; Ocariz, J; Biasini, M; Manoni, E; Pacetti, S; Rossi, A; Angelini, C; Batignani, G; Bettarini, S; Carpinelli, M; Casarosa, G; Cervelli, A; Chrzaszcz, M; Forti, F; Giorgi, M A; Lusiani, A; Oberhof, B; Paoloni, E; Perez, A; Rizzo, G; Walsh, J J; Lopes Pegna, D; Olsen, J; Smith, A J S; Faccini, R; Ferrarotto, F; Ferroni, F; Gaspero, M; Li Gioi, L; Pilloni, A; Piredda, G; Bünger, C; Dittrich, S; Grünberg, O; Hartmann, T; Hess, M; Leddig, T; Voß, C; Waldi, R; Adye, T; Olaiya, E O; Wilson, F F; Emery, S; Vasseur, G; Anulli, F; Aston, D; Bard, D J; Cartaro, C; Convery, M R; Dorfan, J; Dubois-Felsmann, G P; Dunwoodie, W; Ebert, M; Field, R C; Fulsom, B G; Graham, M T; Hast, C; Innes, W R; Kim, P; Leith, D W G S; Lewis, P; Lindemann, D; Luitz, S; Luth, V; Lynch, H L; MacFarlane, D B; Muller, D R; Neal, H; Perl, M; Pulliam, T; Ratcliff, B N; Roodman, A; Salnikov, A A; Schindler, R H; Snyder, A; Su, D; Sullivan, M K; Va'vra, J; Wisniewski, W J; Wulsin, H W; Purohit, M V; White, R M; Wilson, J R; Randle-Conde, A; Sekula, S J; Bellis, M; Burchat, P R; Puccio, E M T; Alam, M S; Ernst, J A; Gorodeisky, R; Guttman, N; Peimer, D R; Soffer, A; Spanier, S M; Ritchie, J L; Ruland, A M; Schwitters, R F; Wray, B C; Izen, J M; Lou, X C; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Lanceri, L; Vitale, L; Martinez-Vidal, F; Oyanguren, A; Villanueva-Perez, P; Albert, J; Banerjee, Sw; Beaulieu, A; Bernlochner, F U; Choi, H H F; King, G J; Kowalewski, R; Lewczuk, M J; Lueck, T; Nugent, I M; Roney, J M; Sobie, R J; Tasneem, N; Gershon, T J; Harrison, P F; Latham, T E; Band, H R; Dasu, S; Pan, Y; Prepost, R; Wu, S L

2014-11-14

Dark sectors charged under a new Abelian interaction have recently received much attention in the context of dark matter models. These models introduce a light new mediator, the so-called dark photon (A^{'}), connecting the dark sector to the standard model. We present a search for a dark photon in the reaction e^{+}e^{-}→γA^{'}, A^{'}→e^{+}e^{-}, μ^{+}μ^{-} using 514  fb^{-1} of data collected with the BABAR detector. We observe no statistically significant deviations from the standard model predictions, and we set 90% confidence level upper limits on the mixing strength between the photon and dark photon at the level of 10^{-4}-10^{-3} for dark photon masses in the range 0.02-10.2  GeV. We further constrain the range of the parameter space favored by interpretations of the discrepancy between the calculated and measured anomalous magnetic moment of the muon.

Search for W' decaying to tau lepton and neutrino in proton-proton collisions at $$\\sqrt{s}$$ = 8 TeV

DOE PAGES

Khachatryan, Vardan

2016-02-03

We found that the first search for a heavy charged vector boson in the final state with a tau lepton and a neutrino is reported, using 19.7 fb -1 of LHC data at √s = 8 TeV. A signal would appear as an excess of events in kinematic regions where the standard model background is low. No excess is observed. Limits are set on a model in which the W' decays preferentially to fermions of the third generation. Our results substantially extend previous constraints on this model. Masses below 2.0 to 2.7 TeV are excluded, depending on the model parameters.more » In addition, the existence of a W' boson with universal fermion couplings is excluded at 95% confidence level, for W' masses below 2.7 TeV.« less

First Intrinsic Anisotropy Observations With the Cosmic Background Imager

NASA Technical Reports Server (NTRS)

Padin, S.; Cartwright, J. K.; Mason, B. S.; Pearson, T. J.; Readhead, A. C. S.; Shepherd, M. C.; Sievers, J.; Udomprasert, P. S.; Holzapfel, W. L.; Myers, S. T.;

Search for neutral MSSM Higgs bosons decaying to τ + τ – pairs in proton–proton collisions at s = 7 TeV with the ATLAS detector

DOE PAGES

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

2011-10-05

Here, a search for neutral Higgs bosons decaying to pairs of τ leptons with the ATLAS detector at the LHC is presented. The analysis is based on proton–proton collisions at a center-of-mass energy of 7 TeV, recorded in 2010 and corresponding to an integrated luminosity of 36 pb –1. After signal selection, 276 events are observed in this data sample. The observed number of events is consistent with the total expected background of 269 ± 36 events. Exclusion limits at the 95% confidence level are derived for the production cross section of a generic Higgs boson Φ as a functionmore » of the Higgs boson mass and for A/H/h production in the Minimal Supersymmetric Standard Model (MSSM) as a function of the parameters mA and tan β.« less

Search for supersymmetry in pp collisions at √7 TeV in events with two photons and missing transverse energy.

PubMed

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Cittolin, S; Dissertori, G; Dittmar, M; Eugster, J; Freudenreich, K; Grab, C; Hervé, A; Hintz, W; Lecomte, P; Lustermann, W; Marchica, C; Martinez Ruiz Del Arbol, P; Meridiani, P; Milenovic, P; Moortgat, F; Nägeli, C; Nef, P; Nessi-Tedaldi, F; Pape, L; Pauss, F; Punz, T; Rizzi, A; Ronga, F J; Rossini, M; Sala, L; Sanchez, A K; Sawley, M-C; Stieger, B; Tauscher, L; Thea, A; Theofilatos, K; Treille, D; Urscheler, C; Wallny, R; Weber, M; Wehrli, L; Weng, J; Aguiló, E; Amsler, C; Chiochia, V; De Visscher, S; Favaro, C; Ivova Rikova, M; Millan Mejias, B; Otiougova, P; Regenfus, C; Robmann, P; Schmidt, A; Snoek, H; Chang, Y H; Chen, K H; Kuo, C M; Li, S W; Lin, W; Liu, Z K; Lu, Y J; Mekterovic, D; Volpe, R; Wu, J H; Yu, S S; Bartalini, P; Chang, P; Chang, Y H; Chang, Y W; Chao, Y; Chen, K F; Hou, W-S; Hsiung, Y; Kao, K Y; Lei, Y J; Lu, R-S; Shiu, J G; Tzeng, Y M; Wang, M; Adiguzel, A; Bakirci, M N; Cerci, S; Dozen, C; Dumanoglu, I; Eskut, E; Girgis, S; Gokbulut, G; Guler, Y; Gurpinar, E; Hos, I; Kangal, E E; Karaman, T; Kayis Topaksu, A; Nart, A; Onengut, G; Ozdemir, K; Ozturk, S; Polatoz, A; Sogut, K; Sunar Cerci, D; Tali, B; Topakli, H; Uzun, D; Vergili, L N; Vergili, M; Zorbilmez, C; Akin, I V; Aliev, T; Bilmis, S; Deniz, M; Gamsizkan, H; Guler, A M; Ocalan, K; Ozpineci, A; Serin, M; Sever, R; Surat, U E; Yildirim, E; Zeyrek, M; Deliomeroglu, M; Demir, D; Gülmez, E; Isildak, B; Kaya, M; Kaya, O; Ozkorucuklu, S; Sonmez, N; Levchuk, L; Bostock, F; Brooke, J J; Cheng, T L; Clement, E; Cussans, D; Frazier, R; Goldstein, J; Grimes, M; Hansen, M; Hartley, D; Heath, G P; Heath, H F; Jackson, J; Kreczko, L; Metson, S; Newbold, D M; Nirunpong, K; Poll, A; Senkin, S; Smith, V J; Ward, S; Basso, L; Bell, K W; Belyaev, A; Brew, C; Brown, R M; Camanzi, B; Cockerill, D J A; Coughlan, J A; Harder, K; Harper, S; Kennedy, B W; Olaiya, E; Petyt, D; Radburn-Smith, B C; Shepherd-Themistocleous, C H; Tomalin, I R; Womersley, W J; Worm, S D; Bainbridge, R; Ball, G; Ballin, J; Beuselinck, R; Buchmuller, O; Colling, D; Cripps, N; Cutajar, M; Davies, G; Della Negra, M; Ferguson, W; Fulcher, J; Futyan, D; Gilbert, A; Guneratne Bryer, A; Hall, G; Hatherell, Z; Hays, J; Iles, G; Jarvis, M; Karapostoli, G; Lyons, L; MacEvoy, B C; Magnan, A-M; Marrouche, J; Mathias, B; Nandi, R; Nash, J; Nikitenko, A; Papageorgiou, A; Pesaresi, M; Petridis, K; Pioppi, M; Raymond, D M; Rogerson, S; Rompotis, N; Rose, A; Ryan, M J; Seez, C; Sharp, P; Sparrow, A; Tapper, A; Tourneur, S; Vazquez Acosta, M; Virdee, T; Wakefield, S; Wardle, N; Wardrope, D; Whyntie, T; Barrett, M; Chadwick, M; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Leslie, D; Martin, W; Reid, I D; Teodorescu, L; Hatakeyama, K; Bose, T; Carrera Jarrin, E; Fantasia, C; Heister, A; St John, J; Lawson, P; Lazic, D; Rohlf, J; Sperka, D; Sulak, L; Avetisyan, A; Bhattacharya, S; Chou, J P; Cutts, D; Ferapontov, A; Heintz, U; Jabeen, S; Kukartsev, G; Landsberg, G; Narain, M; Nguyen, D; Segala, M; Sinthuprasith, T; Speer, T; Tsang, K V; Breedon, R; Calderon De la Barca Sanchez, M; Chauhan, S; Chertok, M; Conway, J; Cox, P T; Dolen, J; Erbacher, R; Friis, E; Ko, W; Kopecky, A; Lander, R; Liu, H; Maruyama, S; Miceli, T; Nikolic, M; Pellett, D; Robles, J; Salur, S; Schwarz, T; Searle, M; Smith, J; Squires, M; Tripathi, M; Vasquez Sierra, R; Veelken, C; Andreev, V; Arisaka, K; Cline, D; Cousins, R; Deisher, A; Duris, J; Erhan, S; Farrell, C; Hauser, J; Ignatenko, M; Jarvis, C; Plager, C; Rakness, G; Schlein, P; Tucker, J; Valuev, V; Babb, J; Chandra, A; Clare, R; Ellison, J; Gary, J W; Giordano, F; Hanson, G; Jeng, G Y; Kao, S C; Liu, F; Liu, H; Long, O R; Luthra, A; Nguyen, H; Shen, B C; Stringer, R; Sturdy, J; Sumowidagdo, S; Wilken, R; Wimpenny, S; Andrews, W; Branson, J G; Cerati, G B; Dusinberre, E; Evans, D; Golf, F; Holzner, A; Kelley, R; Lebourgeois, M; Letts, J; Mangano, B; Padhi, S; Palmer, C; Petrucciani, G; Pi, H; Pieri, M; Ranieri, R; Sani, M; Sharma, V; Simon, S; Tu, Y; Vartak, A; Wasserbaech, S; Würthwein, F; Yagil, A; Yoo, J; Barge, D; Bellan, R; Campagnari, C; D'Alfonso, M; Danielson, T; Flowers, K; Geffert, P; Incandela, J; Justus, C; Kalavase, P; Koay, S A; Kovalskyi, D; Krutelyov, V; Lowette, S; McColl, N; Pavlunin, V; Rebassoo, F; Ribnik, J; Richman, J; Rossin, R; Stuart, D; To, W; Vlimant, J R; Apresyan, A; Bornheim, A; Bunn, J; Chen, Y; Gataullin, M; Ma, Y; Mott, A; Newman, H B; Rogan, C; Shin, K; Timciuc, V; Traczyk, P; Veverka, J; Wilkinson, R; Yang, Y; Zhu, R Y; Akgun, B; Carroll, R; Ferguson, T; Iiyama, Y; Jang, D W; Jun, S Y; Liu, Y F; Paulini, M; Russ, J; Vogel, H; Vorobiev, I; Cumalat, J P; Dinardo, M E; Drell, B R; Edelmaier, C J; Ford, W T; Gaz, A; Heyburn, B; Luiggi Lopez, E; Nauenberg, U; Smith, J G; Stenson, K; Ulmer, K A; Wagner, S R; Zang, S L; Agostino, L; Alexander, J; Cassel, D; Chatterjee, A; Das, S; Eggert, N; Gibbons, L K; Heltsley, B; Hopkins, W; Khukhunaishvili, A; Kreis, B; Nicolas Kaufman, G; Patterson, J R; Puigh, D; Ryd, A; Salvati, E; Shi, X; Sun, W; Teo, W D; Thom, J; Thompson, J; Vaughan, J; Weng, Y; Winstrom, L; Wittich, P; Biselli, A; Cirino, G; Winn, D; Abdullin, S; Albrow, M; Anderson, J; Apollinari, G; Atac, M; Bakken, J A; Banerjee, S; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bloch, I; Borcherding, F; Burkett, K; Butler, J N; Chetluru, V; Cheung, H W K; Chlebana, F; Cihangir, S; Cooper, W; Eartly, D P; Elvira, V D; Esen, S; Fisk, I; Freeman, J; Gao, Y; Gottschalk, E; Green, D; Gunthoti, K; Gutsche, O; Hanlon, J; Harris, R M; Hirschauer, J; Hooberman, B; Jensen, H; Johnson, M; Joshi, U; Khatiwada, R; Klima, B; Kousouris, K; Kunori, S; Kwan, S; Leonidopoulos, C; Limon, P; Lincoln, D; Lipton, R; Lykken, J; Maeshima, K; Marraffino, J M; Mason, D; McBride, P; Miao, T; Mishra, K; Mrenna, S; Musienko, Y; Newman-Holmes, C; O'Dell, V; Pordes, R; Prokofyev, O; Saoulidou, N; Sexton-Kennedy, E; Sharma, S; Spalding, W J; Spiegel, L; Tan, P; Taylor, L; Tkaczyk, S; Uplegger, L; Vaandering, E W; Vidal, R; Whitmore, J; Wu, W; Yang, F; Yumiceva, F; Yun, J C; Acosta, D; Avery, P; Bourilkov, D; Chen, M; De Gruttola, M; Di Giovanni, G P; Dobur, D; Drozdetskiy, A; Field, R D; Fisher, M; Fu, Y; Furic, I K; Gartner, J; Kim, B; Konigsberg, J; Korytov, A; Kropivnitskaya, A; Kypreos, T; Matchev, K; Mitselmakher, G; Muniz, L; Prescott, C; Remington, R; Schmitt, M; Scurlock, B; Sellers, P; Skhirtladze, N; Snowball, M; Wang, D; Yelton, J; Zakaria, M; Ceron, C; Gaultney, V; Kramer, L; Lebolo, L M; Linn, S; Markowitz, P; Martinez, G; Mesa, D; Rodriguez, J L; Adams, T; Askew, A; Bandurin, D; Bochenek, J; Chen, J; Diamond, B; Gleyzer, S V; Haas, J; Hagopian, S; Hagopian, V; Jenkins, M; Johnson, K F; Prosper, H; Quertenmont, L; Sekmen, S; Veeraraghavan, V; Baarmand, M M; Dorney, B; Guragain, S; Hohlmann, M; Kalakhety, H; Ralich, R; Vodopiyanov, I; Adams, M R; Anghel, I M; Apanasevich, L; Bai, Y; Bazterra, V E; Betts, R R; Callner, J; Cavanaugh, R; Dragoiu, C; Gauthier, L; Gerber, C E; Hofman, D J; Khalatyan, S; Kunde, G J; Lacroix, F; Malek, M; O'Brien, C; Silvestre, C; Smoron, A; Strom, D; Varelas, N; Akgun, U; Albayrak, E A; Bilki, B; Clarida, W; Duru, F; Lae, C K; McCliment, E; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Newsom, C R; Norbeck, E; Olson, J; Onel, Y; Ozok, F; Sen, S; Wetzel, J; Yetkin, T; Yi, K; Barnett, B A; Blumenfeld, B; Bonato, A; Eskew, C; Fehling, D; Giurgiu, G; Gritsan, A V; Hu, G; Maksimovic, P; Rappoccio, S; Swartz, M; Tran, N V; Whitbeck, A; Baringer, P; Bean, A; Benelli, G; Grachov, O; Kenny Iii, R P; Murray, M; Noonan, D; Sanders, S; Wood, J S; Zhukova, V; Barfuss, A F; Bolton, T; Chakaberia, I; Ivanov, A; Khalil, S; Makouski, M; Maravin, Y; Shrestha, S; Svintradze, I; Wan, Z; Gronberg, J; Lange, D; Wright, D; Baden, A; Boutemeur, M; Eno, S C; Ferencek, D; Gomez, J A; Hadley, N J; Kellogg, R G; Kirn, M; Lu, Y; Mignerey, A C; Rossato, K; Rumerio, P; Santanastasio, F; Skuja, A; Temple, J; Tonjes, M B; Tonwar, S C; Twedt, E; Alver, B; Bauer, G; Bendavid, J; Busza, W; Butz, E; Cali, I A; Chan, M; Dutta, V; Everaerts, P; Gomez Ceballos, G; Goncharov, M; Hahn, K A; Harris, P; Kim, Y; Klute, M; Lee, Y-J; Li, W; Loizides, C; Luckey, P D; Ma, T; Nahn, S; Paus, C; Ralph, D; Roland, C; Roland, G; Rudolph, M; Stephans, G S F; Stöckli, F; Sumorok, K; Sung, K; Wenger, E A; Xie, S; Yang, M; Yilmaz, Y; Yoon, A S; Zanetti, M; Cooper, S I; Cushman, P; Dahmes, B; De Benedetti, A; Dudero, P R; Franzoni, G; Haupt, J; Klapoetke, K; Kubota, Y; Mans, J; Rekovic, V; Rusack, R; Sasseville, M; Singovsky, A; Cremaldi, L M; Godang, R; Kroeger, R; Perera, L; Rahmat, R; Sanders, D A; Summers, D; Bloom, K; Bose, S; Butt, J; Claes, D R; Dominguez, A; Eads, M; Keller, J; Kelly, T; Kravchenko, I; Lazo-Flores, J; Malbouisson, H; Malik, S; Snow, G R; Baur, U; Godshalk, A; Iashvili, I; Jain, S; Kharchilava, A; Kumar, A; Shipkowski, S P; Smith, K; Alverson, G; Barberis, E; Baumgartel, D; Boeriu, O; Chasco, M; Reucroft, S; Swain, J; Trocino, D; Wood, D; Zhang, J; Anastassov, A; Kubik, A; Odell, N; Ofierzynski, R A; Pollack, B; Pozdnyakov, A; Schmitt, M; Stoynev, S; Velasco, M; Won, S; Antonelli, L; Berry, D; Hildreth, M; Jessop, C; Karmgard, D J; Kolb, J; Kolberg, T; Lannon, K; Luo, W; Lynch, S; Marinelli, N; Morse, D M; Pearson, T; Ruchti, R; Slaunwhite, J; Valls, N; Wayne, M; Ziegler, J; Bylsma, B; Durkin, L S; Gu, J; Hill, C; Killewald, P; Kotov, K; Ling, T Y; Rodenburg, M; Williams, G; Adam, N; Berry, E; Elmer, P; Gerbaudo, D; Halyo, V; Hebda, P; Hunt, A; Jones, J; Laird, E; Lopes Pegna, D; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Piroué, P; Quan, X; Saka, H; Stickland, D; Tully, C; Werner, J S; Zuranski, A; Acosta, J G; Huang, X T; Lopez, A; Mendez, H; Oliveros, S; Ramirez Vargas, J E; Zatserklyaniy, A; Alagoz, E; Barnes, V E; Bolla, G; Borrello, L; Bortoletto, D; Everett, A; Garfinkel, A F; Gutay, L; Hu, Z; Jones, M; Koybasi, O; Kress, M; Laasanen, A T; Leonardo, N; Liu, C; Maroussov, V; Merkel, P; Miller, D H; Neumeister, N; Shipsey, I; Silvers, D; Svyatkovskiy, A; Yoo, H D; Zablocki, J; Zheng, Y; Jindal, P; Parashar, N; Boulahouache, C; Cuplov, V; Ecklund, K M; Geurts, F J M; Padley, B P; Redjimi, R; Roberts, J; Zabel, J; Betchart, B; Bodek, A; Chung, Y S; Covarelli, R; de Barbaro, P; Demina, R; Eshaq, Y; Flacher, H; Garcia-Bellido, A; Goldenzweig, P; Gotra, Y; Han, J; Harel, A; Miner, D C; Orbaker, D; Petrillo, G; Vishnevskiy, D; Zielinski, M; Bhatti, A; Ciesielski, R; Demortier, L; Goulianos, K; Lungu, G; Malik, S; Mesropian, C; Yan, M; Atramentov, O; Barker, A; Duggan, D; Gershtein, Y; Gray, R; Halkiadakis, E; Hidas, D; Hits, D; Lath, A; Panwalkar, S; Patel, R; Richards, A; Rose, K; Schnetzer, S; Somalwar, S; Stone, R; Thomas, S; Cerizza, G; Hollingsworth, M; Spanier, S; Yang, Z C; York, A; Asaadi, J; Eusebi, R; Gilmore, J; Gurrola, A; Kamon, T; Khotilovich, V; Montalvo, R; Nguyen, C N; Osipenkov, I; Pakhotin, Y; Pivarski, J; Safonov, A; Sengupta, S; Tatarinov, A; Toback, D; Weinberger, M; Akchurin, N; Bardak, C; Damgov, J; Jeong, C; Kovitanggoon, K; Lee, S W; Roh, Y; Sill, A; Volobouev, I; Wigmans, R; Yazgan, E; Appelt, E; Brownson, E; Engh, D; Florez, C; Gabella, W; Issah, M; Johns, W; Kurt, P; Maguire, C; Melo, A; Sheldon, P; Snook, B; Tuo, S; Velkovska, J; Arenton, M W; Balazs, M; Boutle, S; Cox, B; Francis, B; Hirosky, R; Ledovskoy, A; Lin, C; Neu, C; Yohay, R; Gollapinni, S; Harr, R; Karchin, P E; Lamichhane, P; Mattson, M; Milstène, C; Sakharov, A; Anderson, M; Bachtis, M; Bellinger, J N; Carlsmith, D; Dasu, S; Efron, J; Flood, K; Gray, L; Grogg, K S; Grothe, M; Hall-Wilton, R; Herndon, M; Klabbers, P; Klukas, J; Lanaro, A; Lazaridis, C; Leonard, J; Loveless, R; Mohapatra, A; Palmonari, F; Reeder, D; Ross, I; Savin, A; Smith, W H; Swanson, J; Weinberg, M

2011-05-27

A search for supersymmetry in the context of general gauge-mediated breaking with the lightest neutralino as the next-to-lightest supersymmetric particle and the gravitino as the lightest is presented. The data sample corresponds to an integrated luminosity of 36 pb(-1) recorded by the CMS experiment at the LHC. The search is performed by using events containing two or more isolated photons, at least one hadronic jet, and significant missing transverse energy. No excess of events at high missing transverse energy is observed. Upper limits on the signal cross section for general gauge-mediated supersymmetry between 0.3 and 1.1 pb at the 95% confidence level are determined for a range of squark, gluino, and neutralino masses, excluding supersymmetry parameter space that was inaccessible to previous experiments. © 2011 CERN, for the CMS Collaboration

Constraining viscous dark energy models with the latest cosmological data

NASA Astrophysics Data System (ADS)

Wang, Deng; Yan, Yang-Jie; Meng, Xin-He

2017-10-01

Based on the assumption that the dark energy possessing bulk viscosity is homogeneously and isotropically permeated in the universe, we propose three new viscous dark energy (VDE) models to characterize the accelerating universe. By constraining these three models with the latest cosmological observations, we find that they just deviate very slightly from the standard cosmological model and can alleviate effectively the current H_0 tension between the local observation by the Hubble Space Telescope and the global measurement by the Planck Satellite. Interestingly, we conclude that a spatially flat universe in our VDE model with cosmic curvature is still supported by current data, and the scale invariant primordial power spectrum is strongly excluded at least at the 5.5σ confidence level in the three VDE models as the Planck result. We also give the 95% upper limits of the typical bulk viscosity parameter η in the three VDE scenarios.

High-precision branching-ratio measurement for the superallowed β+ emitter 26Alm

NASA Astrophysics Data System (ADS)

Finlay, P.; Ball, G. C.; Leslie, J. R.; Svensson, C. E.; Andreoiu, C.; Austin, R. A. E.; Bandyopadhyay, D.; Cross, D. S.; Demand, G.; Djongolov, M.; Ettenauer, S.; Garrett, P. E.; Green, K. L.; Grinyer, G. F.; Hackman, G.; Leach, K. G.; Pearson, C. J.; Phillips, A. A.; Rand, E. T.; Sumithrarachchi, C. S.; Triambak, S.; Williams, S. J.

2012-05-01

A high-precision branching-ratio measurement for the superallowed β+ emitter 26Alm was performed at the TRIUMF-ISAC radioactive ion beam facility. An upper limit of ⩽12 ppm at 90% confidence level was found for the second forbidden β+ decay of 26Alm to the 21+ state at 1809 keV in 26Mg. An inclusive upper limit of ⩽15 ppm at 90% confidence level was found when considering all possible nonanalog β+/EC decay branches of 26Alm, resulting in a superallowed branching ratio of 100.0000-0.0015+0%.

Acarbose bioequivalence: exploration of new pharmacodynamic parameters.

PubMed

Zhang, Min; Yang, Jin; Tao, Lei; Li, Lingjun; Ma, Pengcheng; Fawcett, John Paul

2012-06-01

To investigate bioequivalence (BE) testing of an acarbose formulation in healthy Chinese volunteers through the use of recommended and innovative pharmacodynamic (PD) parameters. Following the Food and Drug Administration (FDA) guidance, a randomized, cross-over study of acarbose test (T) and reference (R) (Glucobay®) formulations was performed with a 1-week wash-out period. Preliminary pilot studies showed that the appropriate dose of acarbose was 2 × 50 mg, and the required number of subjects was 40. Serum glucose concentrations after sucrose administration (baseline) and co-administration of sucrose/acarbose on the following day were both determined. Three newly defined PD measures of glucose fluctuation (glucose excursion (GE), GE' (glucose excursion without the effect of the homeostatic glucose control), and fAUC (degree of fluctuation of serum glucose based on AUC)), the plateau glucose concentration (C(ss)), and time of maximum reduction in glucose concentration (T (max)) were tested in the evaluation. The adequacy of the two parameters recommended by the FDA, ΔC(SG,max) (maximum reduction in serum glucose concentration) and AUEC((0-4h)) (reduction in the AUC((0-4h)) of glucose between baseline and acarbose formulation) was also evaluated. The T (max) values were comparable, and the 90% confidence intervals of the geometric test/reference ratios (T/R) for ΔC(SG,max), C(ss), GE, and fAUC were all within 80-125%. The parameter GE' was slightly outside the limits, and the parameter AUEC((0-4h)) could not be computed due to the presence of negative values. In acarbose BE evaluation, while the recommended parameter ΔC(SG,max) is valuable, the combination of C(ss) and one of the newly defined glucose fluctuation parameters, GE, GE', and fAUC is preferable than AUEC((0-4h)). The acarbose test formulation can be initially considered to be bioequivalent to Glucobay®.

Model-independent limits and constraints on extended theories of gravity from cosmic reconstruction techniques

NASA Astrophysics Data System (ADS)

de la Cruz-Dombriz, Álvaro; Dunsby, Peter K. S.; Luongo, Orlando; Reverberi, Lorenzo

2016-12-01

The onset of dark energy domination depends on the particular gravitational theory driving the cosmic evolution. Model independent techniques are crucial to test the both the present ΛCDM cosmological paradigm and alternative theories, making the least possible number of assumptions about the Universe. In this paper we investigate whether cosmography is able to distinguish between different gravitational theories, by determining bounds on model parameters for three different extensions of General Relativity, namely quintessence, F(𝒯) and f(R) gravitational theories. We expand each class of theories in powers of redshift z around the present time, making no additional assumptions. This procedure is an extension of previous work and can be seen as the most general approach for testing extended theories of gravity through the use of cosmography. In the case of F(𝒯) and f(R) theories, we show that some assumptions on model parameters often made in previous works are superfluous or even unjustified. We use data from the Union 2.1 supernovae catalogue, baryonic acoustic oscillation data and H(z) differential age compilations, which probe cosmology on different scales of the cosmological evolution. We perform a Monte Carlo analysis using a Metropolis-Hastings algorithm with a Gelman-Rubin convergence criterion, reporting 1-σ and 2-σ confidence levels. To do so, we perform two distinct fits, assuming only data within z < 1 first and then without limitations in redshift. We obtain the corresponding numerical intervals in which coefficients span, and find that the data is compatible the ΛCDM limit of all three theories at the 1-σ level, while still compatible with quite a large portion of parameter space. We compare our results to the truncated ΛCDM paradigm, demonstrating that our bounds divert from the expectations of previous works, showing that the permitted regions of coefficients are significantly modified and in general widened with respect to values usually reported in the existing literature. Finally, we test the extended theories through the Bayesian selection criteria AIC and BIC.

Model-independent limits and constraints on extended theories of gravity from cosmic reconstruction techniques

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

Cruz-Dombriz, Álvaro de la; Dunsby, Peter K.S.; Luongo, Orlando

The onset of dark energy domination depends on the particular gravitational theory driving the cosmic evolution. Model independent techniques are crucial to test the both the present ΛCDM cosmological paradigm and alternative theories, making the least possible number of assumptions about the Universe. In this paper we investigate whether cosmography is able to distinguish between different gravitational theories, by determining bounds on model parameters for three different extensions of General Relativity, namely quintessence, F (Τ) and f ( R ) gravitational theories. We expand each class of theories in powers of redshift z around the present time, making no additionalmore » assumptions. This procedure is an extension of previous work and can be seen as the most general approach for testing extended theories of gravity through the use of cosmography. In the case of F (Τ) and f ( R ) theories, we show that some assumptions on model parameters often made in previous works are superfluous or even unjustified. We use data from the Union 2.1 supernovae catalogue, baryonic acoustic oscillation data and H ( z ) differential age compilations, which probe cosmology on different scales of the cosmological evolution. We perform a Monte Carlo analysis using a Metropolis-Hastings algorithm with a Gelman-Rubin convergence criterion, reporting 1-σ and 2-σ confidence levels. To do so, we perform two distinct fits, assuming only data within z < 1 first and then without limitations in redshift. We obtain the corresponding numerical intervals in which coefficients span, and find that the data is compatible the ΛCDM limit of all three theories at the 1-σ level, while still compatible with quite a large portion of parameter space. We compare our results to the truncated ΛCDM paradigm, demonstrating that our bounds divert from the expectations of previous works, showing that the permitted regions of coefficients are significantly modified and in general widened with respect to values usually reported in the existing literature. Finally, we test the extended theories through the Bayesian selection criteria AIC and BIC.« less

Procedures for estimating confidence intervals for selected method performance parameters.

PubMed

McClure, F D; Lee, J K

2001-01-01

Procedures for estimating confidence intervals (CIs) for the repeatability variance (sigmar2), reproducibility variance (sigmaR2 = sigmaL2 + sigmar2), laboratory component (sigmaL2), and their corresponding standard deviations sigmar, sigmaR, and sigmaL, respectively, are presented. In addition, CIs for the ratio of the repeatability component to the reproducibility variance (sigmar2/sigmaR2) and the ratio of the laboratory component to the reproducibility variance (sigmaL2/sigmaR2) are also presented.

VizieR Online Data Catalog: TROY project. I. (Lillo-Box+, 2018)

NASA Astrophysics Data System (ADS)

Lillo-Box, J.; Barrado, D.; Figueira, P.; Leleu, A.; Santos, N. C.; Correia, A. C. M.; Robutel, P.; Faria, J. P.

2017-11-01

tablea4.dat: Posterior confidence intervals of the parameters explored to fit the radial velocity data according to equation 9 in the paper. tablea6.dat: Maximum mass of possible trojan bodies for the six tested models assuming their presence. We present the 95% confidence intervals of the mass computed from random samplings of the radial velocity semi-amplitude K2, the inclination i, the eccentricity e (when applicable), and the stellar mass obtained from the literature. (2 data files).

Simulating the effect of non-linear mode coupling in cosmological parameter estimation

NASA Astrophysics Data System (ADS)

Kiessling, A.; Taylor, A. N.; Heavens, A. F.

2011-09-01

Fisher Information Matrix methods are commonly used in cosmology to estimate the accuracy that cosmological parameters can be measured with a given experiment and to optimize the design of experiments. However, the standard approach usually assumes both data and parameter estimates are Gaussian-distributed. Further, for survey forecasts and optimization it is usually assumed that the power-spectrum covariance matrix is diagonal in Fourier space. However, in the low-redshift Universe, non-linear mode coupling will tend to correlate small-scale power, moving information from lower to higher order moments of the field. This movement of information will change the predictions of cosmological parameter accuracy. In this paper we quantify this loss of information by comparing naïve Gaussian Fisher matrix forecasts with a maximum likelihood parameter estimation analysis of a suite of mock weak lensing catalogues derived from N-body simulations, based on the SUNGLASS pipeline, for a 2D and tomographic shear analysis of a Euclid-like survey. In both cases, we find that the 68 per cent confidence area of the Ωm-σ8 plane increases by a factor of 5. However, the marginal errors increase by just 20-40 per cent. We propose a new method to model the effects of non-linear shear-power mode coupling in the Fisher matrix by approximating the shear-power distribution as a multivariate Gaussian with a covariance matrix derived from the mock weak lensing survey. We find that this approximation can reproduce the 68 per cent confidence regions of the full maximum likelihood analysis in the Ωm-σ8 plane to high accuracy for both 2D and tomographic weak lensing surveys. Finally, we perform a multiparameter analysis of Ωm, σ8, h, ns, w0 and wa to compare the Gaussian and non-linear mode-coupled Fisher matrix contours. The 6D volume of the 1σ error contours for the non-linear Fisher analysis is a factor of 3 larger than for the Gaussian case, and the shape of the 68 per cent confidence volume is modified. We propose that future Fisher matrix estimates of cosmological parameter accuracies should include mode-coupling effects.

Atmospheric neutrino oscillation analysis with external constraints in Super-Kamiokande I-IV

NASA Astrophysics Data System (ADS)

Abe, K.; Bronner, C.; Haga, Y.; Hayato, Y.; Ikeda, M.; Iyogi, K.; Kameda, J.; Kato, Y.; Kishimoto, Y.; Marti, Ll.; Miura, M.; Moriyama, S.; Nakahata, M.; Nakajima, T.; Nakano, Y.; Nakayama, S.; Okajima, Y.; Orii, A.; Pronost, G.; Sekiya, H.; Shiozawa, M.; Sonoda, Y.; Takeda, A.; Takenaka, A.; Tanaka, H.; Tasaka, S.; Tomura, T.; Akutsu, R.; Irvine, T.; Kajita, T.; Kametani, I.; Kaneyuki, K.; Nishimura, Y.; Okumura, K.; Richard, E.; Tsui, K. M.; Labarga, L.; Fernandez, P.; Blaszczyk, F. d. M.; Gustafson, J.; Kachulis, C.; Kearns, E.; Raaf, J. L.; Stone, J. L.; Sulak, L. R.; Berkman, S.; Tobayama, S.; Goldhaber, M.; Carminati, G.; Elnimr, M.; Kropp, W. R.; Mine, S.; Locke, S.; Renshaw, A.; Smy, M. B.; Sobel, H. W.; Takhistov, V.; Weatherly, P.; Ganezer, K. S.; Hartfiel, B. L.; Hill, J.; Hong, N.; Kim, J. Y.; Lim, I. T.; Park, R. G.; Akiri, T.; Himmel, A.; Li, Z.; O'Sullivan, E.; Scholberg, K.; Walter, C. W.; Wongjirad, T.; Ishizuka, T.; Nakamura, T.; Jang, J. S.; Choi, K.; Learned, J. G.; Matsuno, S.; Smith, S. N.; Amey, J.; Litchfield, R. P.; Ma, W. Y.; Uchida, Y.; Wascko, M. O.; Cao, S.; Friend, M.; Hasegawa, T.; Ishida, T.; Ishii, T.; Kobayashi, T.; Nakadaira, T.; Nakamura, K.; Oyama, Y.; Sakashita, K.; Sekiguchi, T.; Tsukamoto, T.; Abe, KE.; Hasegawa, M.; Suzuki, A. T.; Takeuchi, Y.; Yano, T.; Hayashino, T.; Hirota, S.; Huang, K.; Ieki, K.; Jiang, M.; Kikawa, T.; Nakamura, KE.; Nakaya, T.; Patel, N. D.; Suzuki, K.; Takahashi, S.; Wendell, R. A.; Anthony, L. H. V.; McCauley, N.; Pritchard, A.; Fukuda, Y.; Itow, Y.; Mitsuka, G.; Murase, M.; Muto, F.; Suzuki, T.; Mijakowski, P.; Frankiewicz, K.; Hignight, J.; Imber, J.; Jung, C. K.; Li, X.; Palomino, J. L.; Santucci, G.; Vilela, C.; Wilking, M. J.; Yanagisawa, C.; Ito, S.; Fukuda, D.; Ishino, H.; Kayano, T.; Kibayashi, A.; Koshio, Y.; Mori, T.; Nagata, H.; Sakuda, M.; Xu, C.; Kuno, Y.; Wark, D.; Di Lodovico, F.; Richards, B.; Tacik, R.; Kim, S. B.; Cole, A.; Thompson, L.; Okazawa, H.; Choi, Y.; Ito, K.; Nishijima, K.; Koshiba, M.; Totsuka, Y.; Suda, Y.; Yokoyama, M.; Calland, R. G.; Hartz, M.; Martens, K.; Quilain, B.; Simpson, C.; Suzuki, Y.; Vagins, M. R.; Hamabe, D.; Kuze, M.; Yoshida, T.; Ishitsuka, M.; Martin, J. F.; Nantais, C. M.; de Perio, P.; Tanaka, H. A.; Konaka, A.; Chen, S.; Wan, L.; Zhang, Y.; Wilkes, R. J.; Minamino, A.; Super-Kamiokande Collaboration

2018-04-01

An analysis of atmospheric neutrino data from all four run periods of Super-Kamiokande optimized for sensitivity to the neutrino mass hierarchy is presented. Confidence intervals for Δ m322 , sin2θ23, sin2θ13 and δC P are presented for normal neutrino mass hierarchy and inverted neutrino mass hierarchy hypotheses, based on atmospheric neutrino data alone. Additional constraints from reactor data on θ13 and from published binned T2K data on muon neutrino disappearance and electron neutrino appearance are added to the atmospheric neutrino fit to give enhanced constraints on the above parameters. Over the range of parameters allowed at 90% confidence level, the normal mass hierarchy is favored by between 91.9% and 94.5% based on the combined Super-Kamiokande plus T2K result.

Assessment of NDE Reliability Data

NASA Technical Reports Server (NTRS)

Yee, B. G. W.; Chang, F. H.; Couchman, J. C.; Lemon, G. H.; Packman, P. F.

1976-01-01

Twenty sets of relevant Nondestructive Evaluation (NDE) reliability data have been identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations has been formulated. A model to grade the quality and validity of the data sets has been developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, have been formulated for each NDE method. A comprehensive computer program has been written to calculate the probability of flaw detection at several confidence levels by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. Probability of detection curves at 95 and 50 percent confidence levels have been plotted for individual sets of relevant data as well as for several sets of merged data with common sets of NDE parameters.

Opinion formation and distribution in a bounded-confidence model on various networks

NASA Astrophysics Data System (ADS)

Meng, X. Flora; Van Gorder, Robert A.; Porter, Mason A.

2018-02-01

In the social, behavioral, and economic sciences, it is important to predict which individual opinions eventually dominate in a large population, whether there will be a consensus, and how long it takes for a consensus to form. Such ideas have been studied heavily both in physics and in other disciplines, and the answers depend strongly both on how one models opinions and on the network structure on which opinions evolve. One model that was created to study consensus formation quantitatively is the Deffuant model, in which the opinion distribution of a population evolves via sequential random pairwise encounters. To consider heterogeneity of interactions in a population along with social influence, we study the Deffuant model on various network structures (deterministic synthetic networks, random synthetic networks, and social networks constructed from Facebook data). We numerically simulate the Deffuant model and conduct regression analyses to investigate the dependence of the time to reach steady states on various model parameters, including a confidence bound for opinion updates, the number of participating entities, and their willingness to compromise. We find that network structure and parameter values both have important effects on the convergence time and the number of steady-state opinion groups. For some network architectures, we observe that the relationship between the convergence time and model parameters undergoes a transition at a critical value of the confidence bound. For some networks, the steady-state opinion distribution also changes from consensus to multiple opinion groups at this critical value.

The detection of impact regions of asteroids' orbits by means of constrained minimization of confidence coefficient. (Russian Title: Выявление областей столкновительных орбит астероидов с помощью условной минимизации доверительного коэффициента)

NASA Astrophysics Data System (ADS)

Baturin, A. P.

2014-12-01

The theme of NEO's impact orbits' regions detecting has been considered. The regions have been detected in the space of initial motion parameters. The detecting has been done by means of constrained minimization of so called "confidence coefficient". This coefficient determines the position of an orbit inside its confidence ellipsoid obtained from a least-square orbit fitting. As a condition the constraining of an asteroid-Earth distance at considered encounter has been used. By means of random variation of initial approximations for the minimization and of the parameter constraining an asteroid-Earth distance it has been demonstrated that impact regions usually have a form of some long tubes in the space of initial motion parameters. The demonstration has been done for the asteroids 2009 FD, 2011 TO and 2012 PB20 at their waited closest encounters to the Earth.

Characterization and Uncertainty Analysis of a Reference Pressure Measurement System for Wind Tunnels

NASA Technical Reports Server (NTRS)

Amer, Tahani; Tripp, John; Tcheng, Ping; Burkett, Cecil; Sealey, Bradley

2004-01-01

This paper presents the calibration results and uncertainty analysis of a high-precision reference pressure measurement system currently used in wind tunnels at the NASA Langley Research Center (LaRC). Sensors, calibration standards, and measurement instruments are subject to errors due to aging, drift with time, environment effects, transportation, the mathematical model, the calibration experimental design, and other factors. Errors occur at every link in the chain of measurements and data reduction from the sensor to the final computed results. At each link of the chain, bias and precision uncertainties must be separately estimated for facility use, and are combined to produce overall calibration and prediction confidence intervals for the instrument, typically at a 95% confidence level. The uncertainty analysis and calibration experimental designs used herein, based on techniques developed at LaRC, employ replicated experimental designs for efficiency, separate estimation of bias and precision uncertainties, and detection of significant parameter drift with time. Final results, including calibration confidence intervals and prediction intervals given as functions of the applied inputs, not as a fixed percentage of the full-scale value are presented. System uncertainties are propagated beginning with the initial reference pressure standard, to the calibrated instrument as a working standard in the facility. Among the several parameters that can affect the overall results are operating temperature, atmospheric pressure, humidity, and facility vibration. Effects of factors such as initial zeroing and temperature are investigated. The effects of the identified parameters on system performance and accuracy are discussed.

VizieR Online Data Catalog: Fermi/GBM GRB time-resolved spectral catalog (Yu+, 2016)

NASA Astrophysics Data System (ADS)

Yu, H.-F.; Preece, R. D.; Greiner, J.; Bhat, P. N.; Bissaldi, E.; Briggs, M. S.; Cleveland, W. H.; Connaughton, V.; Goldstein, A.; von Kienlin; A.; Kouveliotou, C.; Mailyan, B.; Meegan, C. A.; Paciesas, W. S.; Rau, A.; Roberts, O. J.; Veres, P.; Wilson-Hodge, C.; Zhang, B.-B.; van Eerten, H. J.

2016-01-01

Time-resolved spectral analysis results of BEST models: for each spectrum GRB name using the Fermi GBM trigger designation, spectrum number within individual burst, start time Tstart and end time Tstop for the time bin, BEST model, best-fit parameters of the BEST model, value of CSTAT per degrees of freedom, 10keV-1MeV photon and energy flux are given. Ep evolutionary trends: for each burst GRB name, number of spectra with Ep, Spearman's Rank Correlation Coefficients between Ep_ and photon flux and 90%, 95%, and 99% confidence intervals, Spearman's Rank Correlation Coefficients between Ep and energy flux and 90%, 95%, and 99% confidence intervals, Spearman's Rank Correlation Coefficient between Ep and time and 90%, 95%, and 99% confidence intervals, trends as determined by computer for 90%, 95%, and 99% confidence intervals, trends as determined by human eyes are given. (2 data files).

A computational framework for the study of confidence in humans and animals

PubMed Central

Kepecs, Adam; Mainen, Zachary F.

2012-01-01

Confidence judgements, self-assessments about the quality of a subject's knowledge, are considered a central example of metacognition. Prima facie, introspection and self-report appear the only way to access the subjective sense of confidence or uncertainty. Contrary to this notion, overt behavioural measures can be used to study confidence judgements by animals trained in decision-making tasks with perceptual or mnemonic uncertainty. Here, we suggest that a computational approach can clarify the issues involved in interpreting these tasks and provide a much needed springboard for advancing the scientific understanding of confidence. We first review relevant theories of probabilistic inference and decision-making. We then critically discuss behavioural tasks employed to measure confidence in animals and show how quantitative models can help to constrain the computational strategies underlying confidence-reporting behaviours. In our view, post-decision wagering tasks with continuous measures of confidence appear to offer the best available metrics of confidence. Since behavioural reports alone provide a limited window into mechanism, we argue that progress calls for measuring the neural representations and identifying the computations underlying confidence reports. We present a case study using such a computational approach to study the neural correlates of decision confidence in rats. This work shows that confidence assessments may be considered higher order, but can be generated using elementary neural computations that are available to a wide range of species. Finally, we discuss the relationship of confidence judgements to the wider behavioural uses of confidence and uncertainty. PMID:22492750

First-order kinetic gas generation model parameters for wet landfills.

PubMed

Faour, Ayman A; Reinhart, Debra R; You, Huaxin

2007-01-01

Landfill gas collection data from wet landfill cells were analyzed and first-order gas generation model parameters were estimated for the US EPA landfill gas emissions model (LandGEM). Parameters were determined through statistical comparison of predicted and actual gas collection. The US EPA LandGEM model appeared to fit the data well, provided it is preceded by a lag phase, which on average was 1.5 years. The first-order reaction rate constant, k, and the methane generation potential, L(o), were estimated for a set of landfills with short-term waste placement and long-term gas collection data. Mean and 95% confidence parameter estimates for these data sets were found using mixed-effects model regression followed by bootstrap analysis. The mean values for the specific methane volume produced during the lag phase (V(sto)), L(o), and k were 33 m(3)/Megagrams (Mg), 76 m(3)/Mg, and 0.28 year(-1), respectively. Parameters were also estimated for three full scale wet landfills where waste was placed over many years. The k and L(o) estimated for these landfills were 0.21 year(-1), 115 m(3)/Mg, 0.11 year(-1), 95 m(3)/Mg, and 0.12 year(-1) and 87 m(3)/Mg, respectively. A group of data points from wet landfills cells with short-term data were also analyzed. A conservative set of parameter estimates was suggested based on the upper 95% confidence interval parameters as a k of 0.3 year(-1) and a L(o) of 100 m(3)/Mg if design is optimized and the lag is minimized.

Writing with Computers in ESL Classroom: Enhancing ESL Learners' Motivation, Confidence and Writing Proficiency

ERIC Educational Resources Information Center

Hadi, Marham Jupri

2013-01-01

Researcher's observation on his ESL class indicates the main issues concerning the writing skills: learners' low motivation to write, minimum interaction in writing, and poor writing skills. These limitations have led them to be less confidence to write in English. This article discusses how computers can be used for the purpose of increasing…

Correlation between PET/CT parameters and KRAS expression in colorectal cancer.

PubMed

Chen, Shang-Wen; Chiang, Hua-Che; Chen, William Tzu-Liang; Hsieh, Te-Chun; Yen, Kuo-Yang; Chiang, Shu-Fen; Kao, Chia-Hung

2014-08-01

The objective of this study was to correlate the association between mutated KRAS and wild-type colorectal cancer (CRC) by using various F-FDG PET-related parameters. One hundred twenty-one CRC patients who had undergone preoperative PET/CT were included in this study. Several PET/CT-related parameters, including SUVmax and various thresholds of metabolic tumor volume, total lesion glycolysis, and PET/CT-based tumor width, were measured. Tumor- and PET/CT-related parameters were correlated with genomic expression between KRAS mutant and wild-type groups, using a Mann-Whitney U test and logistic regression analysis. Colorectal cancer tumors with a mutated KRAS exhibited higher SUVmax and an increased accumulation of FDG among several threshold methods. Multivariate analysis showed that SUVmax and using a 40% threshold level for maximal uptake of TW (TW40%) were the 2 predictors of KRAS mutations. The odds ratio was 1.23 for SUVmax (P = 0.02; 95% confidence interval, 1.01-1.52) and 1.15 for TW40% (P = 0.02; 95% confidence interval, 1.02-1.30). The accuracy of SUVmax for predicting mutated KRAS was higher in patients with colon or sigmoid colon cancers, whereas it was TW40% in those with rectal cancers. SUVmax and TW40% were associated in CRC with KRAS mutations. PET/CT parameters can supplement genomic analysis to determine KRAS expression in CRC.

Neurofeedback training for peak performance.

PubMed

Graczyk, Marek; Pąchalska, Maria; Ziółkowski, Artur; Mańko, Grzegorz; Łukaszewska, Beata; Kochanowicz, Kazimierz; Mirski, Andrzej; Kropotov, Iurii D

2014-01-01

One of the applications of the Neurofeedback methodology is peak performance in sport. The protocols of the neurofeedback are usually based on an assessment of the spectral parameters of spontaneous EEG in resting state conditions. The aim of the paper was to study whether the intensive neurofeedback training of a well-functioning Olympic athlete who has lost his performance confidence after injury in sport, could change the brain functioning reflected in changes in spontaneous EEG and event related potentials (ERPs). The case is presented of an Olympic athlete who has lost his performance confidence after injury in sport. He wanted to resume his activities by means of neurofeedback training. His QEEG/ERP parameters were assessed before and after 4 intensive sessions of neurotherapy. Dramatic and statistically significant changes that could not be explained by error measurement were observed in the patient. Neurofeedback training in the subject under study increased the amplitude of the monitoring component of ERPs generated in the anterior cingulate cortex, accompanied by an increase in beta activity over the medial prefrontal cortex. Taking these changes together, it can be concluded that that even a few sessions of neurofeedback in a high performance brain can significantly activate the prefrontal cortical areas associated with increasing confidence in sport performance.

VizieR Online Data Catalog: Vela Junior (RX J0852.0-4622) HESS image (HESS+, 2018)

NASA Astrophysics Data System (ADS)

H. E. S. S. Collaboration; Abdalla, H.; Abramowski, A.; Aharonian, F.; Ait Benkhali, F.; Akhperjanian, A. G.; Andersson, T.; Anguener, E. O.; Arakawa, M.; Arrieta, M.; Aubert, P.; Backes, M.; Balzer, A.; Barnard, M.; Becherini, Y.; Becker Tjus, J.; Berge, D.; Bernhard, S.; Bernloehr, K.; Blackwell, R.; Boettcher, M.; Boisson, C.; Bolmont, J.; Bordas, P.; Bregeon, J.; Brun, F.; Brun, P.; Bryan, M.; Buechele, M.; Bulik, T.; Capasso, M.; Carr, J.; Casanova, S.; Cerruti, M.; Chakraborty, N.; Chalme-Calvet, R.; Chaves, R. C. G.; Chen, A.; Chevalier, J.; Chretien, M.; Coffaro, M.; Colafrancesco, S.; Cologna, G.; Condon, B.; Conrad, J.; Cui, Y.; Davids, I. D.; Decock, J.; Degrange, B.; Deil, C.; Devin, J.; Dewilt, P.; Dirson, L.; Djannati-Atai, A.; Domainko, W.; Donath, A.; Drury, L. O'c.; Dutson, K.; Dyks, J.; Edwards, T.; Egberts, K.; Eger, P.; Ernenwein, J.-P.; Eschbach, S.; Farnier, C.; Fegan, S.; Fernandes, M. V.; Fiasson, A.; Fontaine, G.; Foerster, A.; Funk, S.; Fuessling, M.; Gabici, S.; Gajdus, M.; Gallant, Y. A.; Garrigoux, T.; Giavitto, G.; Giebels, B.; Glicenstein, J. F.; Gottschall, D.; Goyal, A.; Grondin, M.-H.; Hahn, J.; Haupt, M.; Hawkes, J.; Heinzelmann, G.; Henri, G.; Hermann, G.; Hervet, O.; Hinton, J. A.; Hofmann, W.; Hoischen, C.; Holler, M.; Horns, D.; Ivascenko, A.; Iwasaki, H.; Jacholkowska, A.; Jamrozy, M.; Janiak, M.; Jankowsky, D.; Jankowsky, F.; Jingo, M.; Jogler, T.; Jouvin, L.; Jung-Richardt, I.; Kastendieck, M. A.; Katarzynski, K.; Katsuragawa, M.; Katz, U.; Kerszberg, D.; Khangulyan, D.; Khelifi, B.; Kieffer, M.; King, J.; Klepser, S.; Klochkov, D.; Kluzniak, W.; Kolitzus, D.; Komin, Nu.; Kosack, K.; Krakau, S.; Kraus, M.; Krueger, P. P.; Laffon, H.; Lamanna, G.; Lau, J.; Lees, J.-P.; Lefaucheur, J.; Lefranc, V.; Lemiere, A.; Lemoine-Goumard, M.; Lenain, J.-P.; Leser, E.; Lohse, T.; Lorentz, M.; Liu, R.; Lopez-Coto, R.; Lypova, I.; Marandon, V.; Marcowith, A.; Mariaud, C.; Marx, R.; Maurin, G.; Maxted, N.; Mayer, M.; Meintjes, P. J.; Meyer, M.; Mitchell, A. M. W.; Moderski, R.; Mohamed, M.; Mohrmann, L.; Mora, K.; Moulin, E.; Murach, T.; Nakashima, S.; de Naurois, M.; Niederwanger, F.; Niemiec J.; Oakes, L.; O'Brien, P.; Odaka, H.; Oettl, S.; Ohm, S.; Ostrowski, M.; Oya, I.; Padovani, M.; Panter, M.; Parsons, R. D.; Paz Arribas, M.; Pekeur, N. W.; Pelletier, G.; Perennes, C.; Petrucci, P.-O.; Peyaud, B.; Piel, Q.; Pita, S.; Poon, H.; Prokhorov, D.; Prokoph, H.; Puehlhofer, G.; Punch, M.; Quirrenbach, A.; Raab, S.; Reimer, A.; Reimer, O.; Renaud, M.; de Los Reyes, R.; Richter, S.; Rieger, F.; Romoli, C.; Rowell, G.; Rudak, B.; Rulten, C. B.; Sahakian, V.; Saito, S.; Salek, D.; Sanchez, D. A.; Santangelo, A.; Sasaki, M.; Schlickeiser, R.; Schuessler, F.; Schulz, A.; Schwanke, U.; Schwemmer, S.; Seglar-Arroyo, M.; Settimo, M.; Seyffert, A. S.; Shafi, N.; Shilon, I.; Simoni, R.; Sol, H.; Spanier, F.; Spengler, G.; Spies, F.; Stawarz, L.; Steenkamp, R.; Stegmann, C.; Stycz, K.; Sushch, I.; Takahashi, T.; Tavernet, J.-P.; Tavernier, T.; Taylor, A. M.; Terrier, R.; Tibaldo, L.; Tiziani, D.; Tluczykont, M.; Trichard, C.; Tsuji, N.; Tuffs, R.; Uchiyama, Y.; van der, Walt D. J.; van Eldik, C.; van Rensburg, C.; van Soelen, B.; Vasileiadis, G.; Veh, J.; Venter, C.; Viana, A.; Vincent, P.; Vink, J.; Voisin, F.; Voelk, H. J.; Vuillaume, T.; Wadiasingh, Z.; Wagner, S. J.; Wagner, P.; Wagner, R. M.; White, R.; Wierzcholska, A.; Willmann, P.; Woernlein, A.; Wouters, D.; Yang, R.; Zabalza, V.; Zaborov, D.; Zacharias, M.; Zanin, R.; Zdziarski, A. A.; Zech, A.; Zefi, F.; Ziegler, A.; Zywucka, N.

2018-03-01

skymap.fit: H.E.S.S. excess skymap in FITS format of the region comprising Vela Junior and its surroundings. The excess map has been corrected for the gradient of exposure and smoothed with a Gaussian function of width 0.08° to match the analysis point spread function, matching the procedure applied to derive the maps in Fig. 1. sp_stat.txt: H.E.S.S. spectral points and fit parameters for Vela Junior (H.E.S.S. data points in Fig. 3 and Tab. A.2 and H.E.S.S. spectral fit parameters in Tab. 4). The errors in this file represent statistical uncertainties at 1 sigma confidence level. The covariance matrix of the fit is also included in the format: c11 c12 c_13 c21 c22 c_23 c31 c32 c_33 where the subindices represent the following parameters of the power-law with exponential cut-off (ECPL) formula in Tab. 2: 1: flux normalization (Phi0) 2: spectral index (Gamma) 3: inverse of the cutoff energy (lambda=1/Ecut) The units for the covariance matrix are the same as for the fit parameters. Notice that, while the fit parameters section of the file shows E_cut as parameter, the fit was done in lambda=1/Ecut; hence the covariance matrix shows the values for lambda in TeV-1. sp_syst.txt: H.E.S.S. spectral points and fit parameters for Vela Junior (H.E.S.S. data points in Fig. 3 and Tab. A.2 and H.E.S.S. spectral fit parameters in Tab. 4). The errors in this file represent systematic uncertainties at 1 sigma confidence level. The integral fluxes for several energy ranges are also included. (4 data files).

Anthropometry profiles of elite rugby players: quantifying changes in lean mass.

PubMed

Duthie, G M; Pyne, D B; Hopkins, W G; Livingstone, S; Hooper, S L

2006-03-01

To demonstrate the utility of a practical measure of lean mass for monitoring changes in the body composition of athletes. Between 1999 and 2003 body mass and sum of seven skinfolds were recorded for 40 forwards and 32 backs from one Super 12 rugby union franchise. Players were assessed on 13 (7) occasions (mean (SD)) over 1.9 (1.3) years. Mixed modelling of log transformed variables provided a lean mass index (LMI) of the form mass/skinfolds(x), for monitoring changes in mass controlled for changes in skinfold thickness. Mean effects of phase of season and time in programme were modelled as percentage changes. Effects were standardised for interpretation of magnitudes. The exponent x was 0.13 for forwards and 0.14 for backs (90% confidence limits +/-0.03). The forwards had a small decrease in skinfolds (5.3%, 90% confidence limits +/-2.2%) between preseason and competition phases, and a small increase (7.8%, 90% confidence limits +/-3.1%) during the club season. A small decrease in LMI (approximately 1.5%) occurred after one year in the programme for forwards and backs, whereas increases in skinfolds for forwards became substantial (4.3%, 90% confidence limits +/-2.2%) after three years. Individual variation in body composition was small within a season (within subject SD: body mass, 1.6%; skinfolds, 6.8%; LMI, 1.1%) and somewhat greater for body mass (2.1%) and LMI (1.7%) between seasons. Despite a lack of substantial mean changes, there was substantial individual variation in lean mass within and between seasons. An index of lean mass based on body mass and skinfolds is a potentially useful tool for assessing body composition of athletes.

Anthropometry profiles of elite rugby players: quantifying changes in lean mass

PubMed Central

Duthie, G M; Pyne, D B; Hopkins, W G; Livingstone, S; Hooper, S L

2006-01-01

Objective To demonstrate the utility of a practical measure of lean mass for monitoring changes in the body composition of athletes. Methods Between 1999 and 2003 body mass and sum of seven skinfolds were recorded for 40 forwards and 32 backs from one Super 12 rugby union franchise. Players were assessed on 13 (7) occasions (mean (SD)) over 1.9 (1.3) years. Mixed modelling of log transformed variables provided a lean mass index (LMI) of the form mass/skinfoldsx, for monitoring changes in mass controlled for changes in skinfold thickness. Mean effects of phase of season and time in programme were modelled as percentage changes. Effects were standardised for interpretation of magnitudes. Results The exponent x was 0.13 for forwards and 0.14 for backs (90% confidence limits ±0.03). The forwards had a small decrease in skinfolds (5.3%, 90% confidence limits ±2.2%) between preseason and competition phases, and a small increase (7.8%, 90% confidence limits ±3.1%) during the club season. A small decrease in LMI (∼1.5%) occurred after one year in the programme for forwards and backs, whereas increases in skinfolds for forwards became substantial (4.3%, 90% confidence limits ±2.2%) after three years. Individual variation in body composition was small within a season (within subject SD: body mass, 1.6%; skinfolds, 6.8%; LMI, 1.1%) and somewhat greater for body mass (2.1%) and LMI (1.7%) between seasons. Conclusions Despite a lack of substantial mean changes, there was substantial individual variation in lean mass within and between seasons. An index of lean mass based on body mass and skinfolds is a potentially useful tool for assessing body composition of athletes. PMID:16505074

Temporal Variability in the Deglutition Literature

PubMed Central

Molfenter, Sonja M.; Steele, Catriona M.

2013-01-01

A literature review was conducted on temporal measures of swallowing in healthy individuals with the purpose of determining the degree of variability present in such measures within the literature. A total of 46 studies that met inclusion criteria were reviewed. The definitions and descriptive statistics for all reported temporal parameters were compiled for meta-analysis. In total, 119 different temporal parameters were found in the literature. The three most-frequently occurring durational measures were: UES opening, laryngeal closure and hyoid movement. The three most-frequently occurring interval measures were: stage transition duration, pharyngeal transit time and duration from laryngeal closure to UES opening. Subtle variations in operational definitions across studies were noted, making the comparison of data challenging. Analysis of forest plots compiling descriptive statistical data (means and 95% confidence intervals) across studies revealed differing degrees of variability across durations and intervals. Two parameters (UES opening duration and the laryngeal-closure-to-UES-opening interval) demonstrated the least variability, reflected by small ranges for mean values and tight confidence intervals. Trends emerged for factors of bolus size and participant age for some variables. Other potential sources of variability are discussed. PMID:22366761

Binary neutron star merger rate via the luminosity function of short gamma-ray bursts

NASA Astrophysics Data System (ADS)

Paul, Debdutta

2018-04-01

The luminosity function of short Gamma Ray Bursts (GRBs) is modelled by using the available catalogue data of all short GRBs (sGRBs) detected till October, 2017. The luminosities are estimated via the `pseudo-redshifts' obtained from the `Yonetoku correlation', assuming a standard delay distribution between the cosmic star formation rate and the production rate of their progenitors. While the simple powerlaw is ruled out to high confidence, the data is fit well both by exponential cutoff powerlaw and broken powerlaw models. Using the derived parameters of these models along with conservative values in the jet opening angles seen from afterglow observations, the true rate of short GRBs are derived. Assuming a short GRB is produced from each binary neutron star merger (BNSM), the rate of gravitational wave (GW) detections from these mergers are derived for the past, present and future configurations of the GW detector networks. Stringent lower limits of 1.87yr-1 for the aLIGO-VIRGO, and 3.11yr-1 for the upcoming aLIGO-VIRGO-KAGRA-LIGO/India configurations are thus derived for the BNSM rate at 68% confidence. The BNSM rates calculated from this work and that independently inferred from the observation of the only confirmed BNSM observed till date, are shown to have a mild tension; however the scenario that all BNSMs produce sGRBs cannot be ruled out.

Binary neutron star merger rate via the luminosity function of short gamma-ray bursts

NASA Astrophysics Data System (ADS)

Paul, Debdutta

2018-07-01

The luminosity function of short gamma ray bursts (GRBs) is modelled by using the available catalogue data of all short GRBs (sGRBs) detected till 2017 October. The luminosities are estimated via the `pseudo-redshifts' obtained from the `Yonetoku correlation', assuming a standard delay distribution between the cosmic star formation rate and the production rate of their progenitors. While the simple power law is ruled out to high confidence, the data is fit well both by exponential cutoff power law and broken power law models. Using the derived parameters of these models along with conservative values in the jet opening angles seen from afterglow observations, the true rate of sGRBs is derived. Assuming a sGRB is produced from each binary neutron star merger (BNSM), the rate of gravitational wave (GW) detections from these mergers are derived for the past, present, and future configurations of the GW detector networks. Stringent lower limits of 1.87 { yr^{-1}} for the aLIGO-VIRGO, and 3.11 { yr^{-1}} for the upcoming aLIGO-VIRGO-KAGRA-LIGO/India configurations are thus derived for the BNSM rate at 68 per cent confidence. The BNSM rates calculated from this work and that independently inferred from the observation of the only confirmed BNSM observed till date are shown to have a mild tension; however, the scenario that all BNSMs produce sGRBs cannot be ruled out.

Evaluation of dual-tip micromanometers during 21-day implantation in goats

NASA Technical Reports Server (NTRS)

Reister, C. A.; Koenig, S. C.; Schaub, J. D.; Ewert, D. L.; Swope, R. D.; Latham, R. D.; Fanton, J. W.; Convertino, V. A. (Principal Investigator)

1998-01-01

Investigative research efforts using a cardiovascular model required the determination of central circulatory haemodynamic and arterial system parameters for the evaluation of cardiovascular performance. These calculations required continuous beat-to-beat measurement of pressure within the four chambers of the heart and great vessels. Sensitivity and offset drift, longevity, and sources of error for eight 3F dual-tipped micromanometers were determined during 21 days of implantation in goats. Subjects were instrumented with pairs of chronically implanted fluid-filled access catheters in the left and right ventricles, through which dual-tipped (test) micromanometers were chronically inserted and single-tip (standard) micromanometers were acutely inserted. Acutely inserted sensors were calibrated daily and measured pressures were compared in vivo to the chronically inserted sensors. Comparison of the pre- and post-gain calibration of the chronically inserted sensors showed a mean sensitivity drift of 1.0 +/- 0.4% (99% confidence, n = 9 sensors) and mean offset drift of 5.0 +/- 1.5 mmHg (99% confidence, n = 9 sensors). Potential sources of error for these drifts were identified, and included measurement system inaccuracies, temperature drift, hydrostatic column gradients, and dynamic pressure changes. Based upon these findings, we determined that these micromanometers may be chronically inserted in high-pressure chambers for up to 17 days with an acceptable error, but should be limited to acute (hours) insertions in low-pressure applications.

Comparison of bioavailability between the most available generic tablet formulation containing artemether and lumefantrine on the Tanzanian market and the innovator's product.

PubMed

Minzi, Omary M S; Marealle, Ignace A; Shekalaghe, Seif; Juma, Omar; Ngaimisi, Eliford; Chemba, Mwajuma; Rutaihwa, Mastidia; Abdulla, Salim; Sasi, Philip

2013-05-30

Existence of anti-malarial generic drugs with low bioavailability marketed on sub-Saharan Africa raises a concern on patients achieving therapeutic concentrations after intake of such products. This work compared bioavailability of one generic tablet formulation with innovator's product. Both were fixed dose combination tablet formulations containing artemether and lumefantrine. The study was conducted in Dar Es Salaam, Tanzania, in which a survey of the most abundant generic containing artemether-lumefantrine tablet formulation was carried out in retail pharmacies. The most widely available generic (Artefan®, Ajanta Pharma Ltd, Maharashtra, India) was sampled for bioavailability comparison with Coartem® (Novartis Pharma, Basel, Switzerland)--the innovator's product. A randomized, two-treatment cross-over study was conducted in 18 healthy Tanzanian black male volunteers. Each volunteer received Artefan® (test) and Coartem® (as reference) formulation separated by 42 days of drug-free washout period. Serial blood samples were collected up to 168 hours after oral administration of a single dose of each treatment. Quantitation of lumefantrine plasma levels was done using HPLC with UV detection. Bioequivalence of the two products was assessed in accordance with the US Food and Drug Authority (FDA) guidelines. The most widely available generic in pharmacies was Artefan® from India. All eighteen enrolled volunteers completed the study and both test and reference tablet formulations were well tolerated. It was possible to quantify lumefantrine alone, therefore, the pharmacokinetic parameters reported herein are for lumefantrine. The geometric mean ratios for Cmax, AUC0-t and AUC0-∞ were 84% in all cases and within FDA recommended bioequivalence limits of 80%-125%, but the 90% confidence intervals were outside FDA recommended limits (CI 49-143%, 53-137%, 52-135% respectively). There were no statistical significant differences between the two formulations with regard to PK parameters (P > 0.05). Although the ratios of AUCs and Cmax were within the acceptable FDA range, bioequivalence between Artefan® and Coartem® tablet formulations was not demonstrated due to failure to comply with the FDA 90% confidence interval criteria. Based on the observed total drug exposure (AUCs), Artefan® is likely to produce a similar therapeutic response as Coartem®.

Gravitational-wave cosmology across 29 decades in frequency

DOE PAGES

Lasky, Paul D.; Mingarelli, Chiara M. F.; Smith, Tristan L.; ...

2016-03-31

Here, quantum fluctuations of the gravitational field in the early Universe, amplified by inflation, produce a primordial gravitational-wave background across a broad frequency band. We derive constraints on the spectrum of this gravitational radiation, and hence on theories of the early Universe, by combining experiments that cover 29 orders of magnitude in frequency. These include Planck observations of cosmic microwave background temperature and polarization power spectra and lensing, together with baryon acoustic oscillations and big bang nucleosynthesis measurements, as well as new pulsar timing array and ground-based interferometer limits. While individual experiments constrain the gravitational-wave energy density in specific frequencymore » bands, the combination of experiments allows us to constrain cosmological parameters, including the inflationary spectral index n t and the tensor-to-scalar ratio r. Results from individual experiments include the most stringent nanohertz limit of the primordial background to date from the Parkes Pulsar Timing Array, Ω GW(f) < 2.3 × 10 -10. Observations of the cosmic microwave background alone limit the gravitational-wave spectral index at 95% confidence to n t ≲ 5 for a tensor-toscalar ratio of r = 0.11. However, the combination of all the above experiments limits n t < 0.36. Future Advanced LIGO observations are expected to further constrain n t < 0.34 by 2020. When cosmic microwave background experiments detect a nonzero r, our results will imply even more stringent constraints on n t and, hence, theories of the early Universe.« less

Dark Matter Search in a Proton Beam Dump with MiniBooNE

NASA Astrophysics Data System (ADS)

Aguilar-Arevalo, A. A.; Backfish, M.; Bashyal, A.; Batell, B.; Brown, B. C.; Carr, R.; Chatterjee, A.; Cooper, R. L.; deNiverville, P.; Dharmapalan, R.; Djurcic, Z.; Ford, R.; Garcia, F. G.; Garvey, G. T.; Grange, J.; Green, J. A.; Huelsnitz, W.; de Icaza Astiz, I. L.; Karagiorgi, G.; Katori, T.; Ketchum, W.; Kobilarcik, T.; Liu, Q.; Louis, W. C.; Marsh, W.; Moore, C. D.; Mills, G. B.; Mirabal, J.; Nienaber, P.; Pavlovic, Z.; Perevalov, D.; Ray, H.; Roe, B. P.; Shaevitz, M. H.; Shahsavarani, S.; Stancu, I.; Tayloe, R.; Taylor, C.; Thornton, R. T.; Van de Water, R.; Wester, W.; White, D. H.; Yu, J.; MiniBooNE-DM Collaboration

2017-06-01

The MiniBooNE-DM Collaboration searched for vector-boson mediated production of dark matter using the Fermilab 8-GeV Booster proton beam in a dedicated run with 1.86 ×1 020 protons delivered to a steel beam dump. The MiniBooNE detector, 490 m downstream, is sensitive to dark matter via elastic scattering with nucleons in the detector mineral oil. Analysis methods developed for previous MiniBooNE scattering results were employed, and several constraining data sets were simultaneously analyzed to minimize systematic errors from neutrino flux and interaction rates. No excess of events over background was observed, leading to a 90% confidence limit on the dark matter cross section parameter, Y =ɛ2αD(mχ/mV)4≲10-8 , for αD=0.5 and for dark matter masses of 0.01

Validation of a method to detect cocaine and its metabolites in nails by gas chromatography-mass spectrometry.

PubMed

Valente-Campos, Simone; Yonamine, Mauricio; de Moraes Moreau, Regina Lucia; Silva, Ovandir Alves

2006-06-02

The objective of the present work was to compare previously published methods and provide validation data to detect simultaneously cocaine (COC), benzoylecgonine (BE) and norcocaine (NCOC) in nail. Finger and toenail samples (5mg) were cut in very small pieces and submitted to an initial procedure for external decontamination. Methanol (3 ml) was used to release analytes from the matrix. A cleanup step was performed simultaneously by solid-phase extraction (SPE) and the residue was derivatized with pentafluoropropionic anhydride/pentafluoropropanol (PFPA/PFP). Gas chromatography-mass spectrometry (GC-MS) was used to detect the analytes in selected ion monitoring mode (SIM). Confidence parameters of validation of the method were: recovery, intra- and inter-assay precision, as well as limit of detection (LOD) of the analytes. The limits of detection were: 3.5 ng/mg for NCOC and 3.0 ng/mg for COC and BE. Good intra-assay precision was observed for all detected substances (coefficient of variation (CV)<11%). The inter-assay precision for norcocaine and benzoylecgonine were <4%. For intra- and inter-assay precision deuterated internal standards were used. Toenail and fingernail samples from eight declared cocaine users were submitted to the validated method.

Dark Matter Search in a Proton Beam Dump with MiniBooNE.

PubMed

Aguilar-Arevalo, A A; Backfish, M; Bashyal, A; Batell, B; Brown, B C; Carr, R; Chatterjee, A; Cooper, R L; deNiverville, P; Dharmapalan, R; Djurcic, Z; Ford, R; Garcia, F G; Garvey, G T; Grange, J; Green, J A; Huelsnitz, W; de Icaza Astiz, I L; Karagiorgi, G; Katori, T; Ketchum, W; Kobilarcik, T; Liu, Q; Louis, W C; Marsh, W; Moore, C D; Mills, G B; Mirabal, J; Nienaber, P; Pavlovic, Z; Perevalov, D; Ray, H; Roe, B P; Shaevitz, M H; Shahsavarani, S; Stancu, I; Tayloe, R; Taylor, C; Thornton, R T; Van de Water, R; Wester, W; White, D H; Yu, J

2017-06-02

The MiniBooNE-DM Collaboration searched for vector-boson mediated production of dark matter using the Fermilab 8-GeV Booster proton beam in a dedicated run with 1.86×10^{20} protons delivered to a steel beam dump. The MiniBooNE detector, 490 m downstream, is sensitive to dark matter via elastic scattering with nucleons in the detector mineral oil. Analysis methods developed for previous MiniBooNE scattering results were employed, and several constraining data sets were simultaneously analyzed to minimize systematic errors from neutrino flux and interaction rates. No excess of events over background was observed, leading to a 90% confidence limit on the dark matter cross section parameter, Y=ε^{2}α_{D}(m_{χ}/m_{V})^{4}≲10^{-8}, for α_{D}=0.5 and for dark matter masses of 0.01

Contributions of divergent and nondivergent winds to the kinetic energy balance of a severe storm environment

NASA Technical Reports Server (NTRS)

Browning, P. A.; Fuelberg, H. E.

1983-01-01

Divergent and rotational components of the synoptic scale kinetic energy balance are presented using rawinsonde data at 3 and 6 h intervals from the Atmospheric Variability Experiment (AVE 4). Two intense thunderstorm complexes occurred during the period. Energy budgets are described for the entire computational region and for limited volumes that enclose and move with the convection. Although small in magnitude, the divergent wind component played an important role in the cross contour generation and horizontal flux divergence of kinetic energy. The importance of V sub D appears directly to the presence and intensity of convection within the area. Although K sub D usually comprised less than 10 percent of the total kinetic energy content within the storm environment, as much as 87 percent of the total horizontal flux divergence and 68 percent of the total cross contour generation was due to the divergent component in the upper atmosphere. Generation of kinetic energy by the divergent component appears to be a major factor in the creation of an upper level wind maximum on the poleward side of one of the complexes. A random error analysis is presented to assess confidence limits in the various energy parameters.

Search for squarks and gluinos in final states with jets and missing transverse momentum using 36 fb-1 of √{s }=13 TeV p p collision data with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Christodoulou, V.; Chromek-Burckhart, D.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Eramo, L.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vasconcelos Corga, K.; de Vivie de Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Bello, F. A.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Petrillo, K. F.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. 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T.; 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, 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.; Minegishi, Y.; Ming, Y.; Mir, L. M.; 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.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. 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S.; Neumann, M.; Newman, P. R.; Ng, T. Y.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. 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.; 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.; 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.; Oppen, H.; 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.; 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.; 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.; 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.; 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, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Poulard, G.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; 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, G.; Qin, Y.; Quadt, A.; 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.; Rangel-Smith, C.; 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.; 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.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; 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.; Roe, S.; Rogan, C. S.; Røhne, O.; 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.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Rothberg, J.; Rousseau, 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.; 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.; Sakurai, Y.; 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 Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; 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.; Sarrazin, B.; Sasaki, O.; Sato, K.; 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.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; 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.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, Dms; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; 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.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, A. M.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; 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. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; 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, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamatani, M.; 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.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, 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.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2018-06-01

A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing hadronic jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded in 2015 and 2016 by the ATLAS experiment in √{s }=13 TeV proton-proton collisions at the Large Hadron Collider, corresponding to an integrated luminosity of 36.1 fb-1 . The results are interpreted in the context of various models where squarks and gluinos are pair produced and the neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 2.03 TeV for a simplified model incorporating only a gluino and the lightest neutralino, assuming the lightest neutralino is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.55 TeV are excluded if the lightest neutralino is massless. These limits substantially extend the region of supersymmetric parameter space previously excluded by searches with the ATLAS detector.

Search for new physics with long-lived particles decaying to photons and missing energy in pp collisions at $$ \\sqrt{s}=7 $$ TeV

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

Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.

A search is performed for long-lived neutral particles decaying into a photon and invisible particles. An example of such a signature is the decay of the lightest neutralino with nonzero lifetime into a gravitino and a photon in gauge-mediated supersymmetry, with the neutralino as the next-to-lightest supersymmetric particle and the gravitino as the lightest. The search uses events containing photons, missing transverse energy, and jets. The impact parameter of the photon relative to the beam-beam collision point can be reconstructed using converted photons. The method is sensitive to lifetimes of the order of 0.1 to 1 ns. The data samplemore » corresponds to an integrated luminosity of 2.23 inverse femtobarns in pp collisions at sqrt(s) = 7 TeV, recorded in the first part of 2011 by the CMS experiment at the LHC. Cross-section limits are presented on pair production for such particles, each of which decays into a photon and invisible particles. The observed 95% confidence level limits vary between 0.11 and 0.21 pb, depending on the neutral particle lifetime.« less

Search for squarks and gluinos in final states with jets and missing transverse momentum at √s =13 TeV with the ATLAS detector

DOE PAGES

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

2016-07-12

A search for squarks and gluinos in final states containing hadronic jets, missing transverse momentum but no electrons or muons is presented. The data were recorded in 2015 by the ATLAS experiment in √s=13 TeV proton–proton collisions at the Large Hadron Collider. No excess above the Standard Model background expectation was observed in 3.2 fb -1 of analyzed data. Results are interpreted within simplified models that assume R-parity is conserved and the neutralino is the lightest supersymmetric particle. An exclusion limit at the 95 % confidence level on the mass of the gluino is set at 1.51 TeV for amore » simplified model incorporating only a gluino octet and the lightest neutralino, assuming the lightest neutralino is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.03 TeV are excluded for a massless lightest neutralino. Finally, these limits substantially extend the region of supersymmetric parameter space excluded by previous measurements with the ATLAS detector.« less

The Mine Safety and Health Administration's criterion threshold value policy increases miners' risk of pneumoconiosis.

PubMed

Weeks, James L

2006-06-01

The Mine Safety and Health Administration (MSHA) proposes to issue citations for non-compliance with the exposure limit for respirable coal mine dust when measured exposure exceeds the exposure limit with a "high degree of confidence." This criterion threshold value (CTV) is derived from the sampling and analytical error of the measurement method. This policy is based on a combination of statistical and legal reasoning: the one-tailed 95% confidence limit of the sampling method, the apparent principle of due process and a standard of proof analogous to "beyond a reasonable doubt." This policy raises the effective exposure limit, it is contrary to the precautionary principle, it is not a fair sharing of the burden of uncertainty, and it employs an inappropriate standard of proof. Its own advisory committee and NIOSH have advised against this policy. For longwall mining sections, it results in a failure to issue citations for approximately 36% of the measured values that exceed the statutory exposure limit. Citations for non-compliance with the respirable dust standard should be issued for any measure exposure that exceeds the exposure limit.

SPIPS: Spectro-Photo-Interferometry of Pulsating Stars

NASA Astrophysics Data System (ADS)

Mérand, Antoine

2017-10-01

SPIPS (Spectro-Photo-Interferometry of Pulsating Stars) combines radial velocimetry, interferometry, and photometry to estimate physical parameters of pulsating stars, including presence of infrared excess, color excess, Teff, and ratio distance/p-factor. The global model-based parallax-of-pulsation method is implemented in Python. Derived parameters have a high level of confidence; statistical precision is improved (compared to other methods) due to the large number of data taken into account, accuracy is improved by using consistent physical modeling and reliability of the derived parameters is strengthened by redundancy in the data.

Design of ceramic components with the NASA/CARES computer program

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Manderscheid, Jane M.; Gyekenyesi, John P.

1990-01-01

The ceramics analysis and reliability evaluation of structures (CARES) computer program is described. The primary function of the code is to calculate the fast-fracture reliability or failure probability of macro-scopically isotropic ceramic components. These components may be subjected to complex thermomechanical loadings, such as those found in heat engine applications. CARES uses results from MSC/NASTRAN or ANSYS finite-element analysis programs to evaluate how inherent surface and/or volume type flaws component reliability. CARES utilizes the Batdorf model and the two-parameter Weibull cumulative distribution function to describe the effects of multiaxial stress states on material strength. The principle of independent action (PIA) and the Weibull normal stress averaging models are also included. Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities are estimated from four-point bend bar or uniform uniaxial tensile specimen fracture strength data. Parameter estimation can be performed for a single or multiple failure modes by using a least-squares analysis or a maximum likelihood method. Kolmogorov-Smirnov and Anderson-Darling goodness-to-fit-tests, 90 percent confidence intervals on the Weibull parameters, and Kanofsky-Srinivasan 90 percent confidence band values are also provided. Examples are provided to illustrate the various features of CARES.

Fundamental properties of Fanaroff-Riley type II radio galaxies investigated via Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Kapińska, A. D.; Uttley, P.; Kaiser, C. R.

2012-08-01

Radio galaxies and quasars are among the largest and most powerful single objects known and are believed to have had a significant impact on the evolving Universe and its large-scale structure. We explore the intrinsic and extrinsic properties of the population of Fanaroff-Riley type II (FR II) objects, i.e. their kinetic luminosities, lifetimes and the central densities of their environments. In particular, the radio and kinetic luminosity functions of these powerful radio sources are investigated using the complete, flux-limited radio catalogues of the Third Cambridge Revised Revised Catalogue (3CRR) and Best et al. We construct multidimensional Monte Carlo simulations using semi-analytical models of FR II source time evolution to create artificial samples of radio galaxies. Unlike previous studies, we compare radio luminosity functions found with both the observed and simulated data to explore the best-fitting fundamental source parameters. The new Monte Carlo method we present here allows us to (i) set better limits on the predicted fundamental parameters of which confidence intervals estimated over broad ranges are presented and (ii) generate the most plausible underlying parent populations of these radio sources. Moreover, as has not been done before, we allow the source physical properties (kinetic luminosities, lifetimes and central densities) to co-evolve with redshift, and we find that all the investigated parameters most likely undergo cosmological evolution. Strikingly, we find that the break in the kinetic luminosity function must undergo redshift evolution of at least (1 + z)3. The fundamental parameters are strongly degenerate, and independent constraints are necessary to draw more precise conclusions. We use the estimated kinetic luminosity functions to set constraints on the duty cycles of these powerful radio sources. A comparison of the duty cycles of powerful FR IIs with those determined from radiative luminosities of active galactic nuclei of comparable black hole mass suggests a transition in behaviour from high to low redshifts, corresponding to either a drop in the typical black hole mass of powerful FR IIs at low redshifts, or a transition to a kinetically dominated, radiatively inefficient FR II population.

Impact of referral letters on scheduling of hospital appointments: a randomised control trial.

PubMed

Jiwa, Moyez; Meng, Xingqiong; O'Shea, Carolyn; Magin, Parker; Dadich, Ann; Pillai, Vinita

2014-07-01

Communication is essential for triage, but intervention trials to improve it are scarce. Referral Writer (RW), a referral letter software program, enables documentation of clinical data and extracts relevant patient details from clinical software. To evaluate whether specialists are more confident about scheduling appointments when they receive more information in referral letters. Single-blind, parallel-groups, controlled design with a 1:1 randomisation. Australian GPs watched video vignettes virtually. GPs wrote referral letters after watching vignettes of patients with cancer symptoms. Letter content was scored against a benchmark. The proportions of referral letters triagable by a specialist with confidence, and in which the specialist was confident the patient had potentially life-limiting pathology were determined. Categorical outcomes were tested with χ(2) and continuous outcomes with t-tests. A random-effects logistic model assessed the influence of group randomisation (RW versus control), GP demographics, clinical specialty, and specialist referral assessor on specialist confidence in the information provided. The intervention (RW) group referred more patients and scored significantly higher on information relayed (mean difference 21.6 [95% confidence intervals {CI} = 20.1 to 23.2]). There was no difference in the proportion of letters for which specialists were confident they had sufficient information for appointment scheduling (RW 77.7% versus control 80.6%, P = 0.16). In the logistic model, limited agreement among specialists contributed substantially to the observed differences in appointment scheduling (P = 35% [95% CI 16% to 59%]). In isolation, referral letter templates are unlikely to improve the scheduling of specialist appointments, even when more information is relayed. © British Journal of General Practice 2014.

Volume Fraction Determination in Cast Superalloys and DS Eutectic Alloys by a New Practice for Manual Point Counting

NASA Technical Reports Server (NTRS)

Andrews, C. W.

1976-01-01

Volume fraction of a constituent or phase was estimated in six specimens of conventional and DS-eutectic superalloys, using ASTM E562-76, a new standard recommended practice for determining volume fraction by systematic manual point count. Volume fractions determined ranged from 0.086 to 0.36, and with one exception, the 95 percent relative confidence limits were approximately 10 percent of the determined volume fractions. Since the confidence-limit goal of 10 percent, which had been arbitrarily chosen previously, was achieved in all but one case, this application of the new practice was considered successful.

An evaluation of risk estimation procedures for mixtures of carcinogens

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

Hwang, J.S.; Chen, J.J.

1999-12-01

The estimation of health risks from exposure to a mixture of chemical carcinogens is generally based on the combination of information from several available single compound studies. The current practice of directly summing the upper bound risk estimates of individual carcinogenic components as an upper bound on the total risk of a mixture is known to be generally too conservative. Gaylor and Chen (1996, Risk Analysis) proposed a simple procedure to compute an upper bound on the total risk using only the upper confidence limits and central risk estimates of individual carcinogens. The Gaylor-Chen procedure was derived based on anmore » underlying assumption of the normality for the distributions of individual risk estimates. IN this paper the authors evaluated the Gaylor-Chen approach in terms the coverages of the upper confidence limits on the true risks of individual carcinogens. In general, if the coverage probabilities for the individual carcinogens are all approximately equal to the nominal level, then the Gaylor-Chen approach should perform well. However, the Gaylor-Chen approach can be conservative or anti-conservative if some of all individual upper confidence limit estimates are conservative or anti-conservative.« less

Searches for continuous gravitational waves from Scorpius X-1 and XTE J1751-305 in LIGO's sixth science run

NASA Astrophysics Data System (ADS)

Meadors, G. D.; Goetz, E.; Riles, K.; Creighton, T.; Robinet, F.

2017-02-01

Scorpius X-1 (Sco X-1) and x-ray transient XTE J1751-305 are low-mass x-ray binaries (LMXBs) that may emit continuous gravitational waves detectable in the band of ground-based interferometric observatories. Neutron stars in LMXBs could reach a torque-balance steady-state equilibrium in which angular momentum addition from infalling matter from the binary companion is balanced by angular momentum loss, conceivably due to gravitational-wave emission. Torque balance predicts a scale for detectable gravitational-wave strain based on observed x-ray flux. This paper describes a search for Sco X-1 and XTE J1751-305 in LIGO science run 6 data using the TwoSpect algorithm, based on searching for orbital modulations in the frequency domain. While no detections are claimed, upper limits on continuous gravitational-wave emission from Sco X-1 are obtained, spanning gravitational-wave frequencies from 40 to 2040 Hz and projected semimajor axes from 0.90 to 1.98 light-seconds. These upper limits are injection validated, equal any previous set in initial LIGO data, and extend over a broader parameter range. At optimal strain sensitivity, achieved at 165 Hz, the 95% confidence level random-polarization upper limit on dimensionless strain h0 is approximately 1.8 ×10-24. The closest approach to the torque-balance limit, within a factor of 27, is also at 165 Hz. Upper limits are set in particular narrow frequency bands of interest for J1751-305. These are the first upper limits known to date on r -mode emission from this XTE source. The TwoSpect method will be used in upcoming searches of Advanced LIGO and Virgo data.

Esophageal-guided biopsy with volumetric laser endomicroscopy and laser cautery marking: a pilot clinical study

PubMed Central

Suter, Melissa J.; Gora, Michalina J.; Lauwers, Gregory Y.; Arnason, Thomas; Sauk, Jenny; Gallagher, Kevin A.; Kava, Lauren; Tan, Khay M.; Soomro, Amna R.; Gallagher, Timothy P.; Gardecki, Joseph A.; Bouma, Brett E.; Rosenberg, Mireille; Nishioka, Norman S.; Tearney, Guillermo J.

2018-01-01

Background Biopsy surveillance protocols for the assessment of Barrett’s esophagus can be subject to sampling errors, resulting in diagnostic uncertainty. Optical coherence tomography is a cross-sectional imaging technique that can be used to conduct volumetric laser endomicroscopy (VLE) of the entire distal esophagus. We have developed a biopsy guidance platform that places endoscopically visible marks at VLE-determined biopsy sites. Objective The objective of this study was to demonstrate in human participants the safety and feasibility of VLE-guided biopsy in vivo. Design A pilot feasibility study. Setting Massachusetts General Hospital. Patients A total of 22 participants were enrolled from January 2011 to June 2012 with a prior diagnosis of Barrett’s esophagus. Twelve participants were used to optimize the laser marking parameters and the system platform. A total of 30 target sites were selected and marked in real-time by using the VLE-guided biopsy platform in the remaining 10 participants. Intervention Volumetric laser endomicroscopy. Main Outcome Measurements Endoscopic and VLE visibility, and accuracy of VLE diagnosis of the tissue between the laser cautery marks. Results There were no adverse events of VLE and laser marking. The optimal laser marking parameters were determined to be 2 seconds at 410 mW, with a mark separation of 6 mm. All marks made with these parameters were visible on endoscopy and VLE. The accuracies for diagnosing tissue in between the laser cautery marks by independent blinded readers for endoscopy were 67% (95% confidence interval [CI], 47%–83%), for VLE intent-to-biopsy images 93% (95% CI, 78%–99%), and for corrected VLE post-marking images 100% when compared with histopathology interpretations. Limitations This is a single-center feasibility study with a limited number of patients. Conclusion Our results demonstrate that VLE-guided biopsy of the esophagus is safe and can be used to guide biopsy site selection based on the acquired volumetric optical coherence tomography imaging data. (Clinical trial registration number: NCT01439633.) PMID:24462171

Complementing the ground-based CMB-S4 experiment on large scales with the PIXIE satellite

NASA Astrophysics Data System (ADS)

Calabrese, Erminia; Alonso, David; Dunkley, Jo

2017-03-01

We present forecasts for cosmological parameters from future cosmic microwave background (CMB) data measured by the stage-4 (S4) generation of ground-based experiments in combination with large-scale anisotropy data from the PIXIE satellite. We demonstrate the complementarity of the two experiments and focus on science targets that benefit from their combination. We show that a cosmic-variance-limited measurement of the optical depth to reionization provided by PIXIE, with error σ (τ )=0.002 , is vital for enabling a 5 σ detection of the sum of the neutrino masses when combined with a CMB-S4 lensing measurement and with lower-redshift constraints on the growth of structure and the distance-redshift relation. Parameters characterizing the epoch of reionization will also be tightly constrained; PIXIE's τ constraint converts into σ (zre)=0.2 for the mean time of reionization, and a kinematic Sunyaev-Zel'dovich measurement from S4 gives σ (Δ zre)=0.03 for the duration of reionization. Both PIXIE and S4 will put strong constraints on primordial tensor fluctuations, vital for testing early-Universe models, and will do so at distinct angular scales. We forecast σ (r )≈5 ×10-4 for a signal with a tensor-to-scalar ratio r =10-3, after accounting for diffuse foreground removal and delensing. The wide and dense frequency coverage of PIXIE results in an expected foreground-degradation factor on r of only ≈25 %. By measuring large and small scales PIXIE and S4 will together better limit the energy injection at recombination from dark matter annihilation, with pann<0.09 ×10-6 m3/s /kg projected at 95% confidence. Cosmological parameters measured from the damping tail with S4 will be best constrained by polarization, which has the advantage of minimal contamination from extragalactic emission.

NEWTONP - CUMULATIVE BINOMIAL PROGRAMS

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

The cumulative binomial program, NEWTONP, is one of a set of three programs which calculate cumulative binomial probability distributions for arbitrary inputs. The three programs, NEWTONP, CUMBIN (NPO-17555), and CROSSER (NPO-17557), can be used independently of one another. NEWTONP can be used by statisticians and users of statistical procedures, test planners, designers, and numerical analysts. The program has been used for reliability/availability calculations. NEWTONP calculates the probably p required to yield a given system reliability V for a k-out-of-n system. It can also be used to determine the Clopper-Pearson confidence limits (either one-sided or two-sided) for the parameter p of a Bernoulli distribution. NEWTONP can determine Bayesian probability limits for a proportion (if the beta prior has positive integer parameters). It can determine the percentiles of incomplete beta distributions with positive integer parameters. It can also determine the percentiles of F distributions and the midian plotting positions in probability plotting. NEWTONP is designed to work well with all integer values 0 < k <= n. To run the program, the user simply runs the executable version and inputs the information requested by the program. NEWTONP is not designed to weed out incorrect inputs, so the user must take care to make sure the inputs are correct. Once all input has been entered, the program calculates and lists the result. It also lists the number of iterations of Newton's method required to calculate the answer within the given error. The NEWTONP program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly with most C compilers. The program format is interactive. It has been implemented under DOS 3.2 and has a memory requirement of 26K. NEWTONP was developed in 1988.

Methods for the behavioral, educational, and social sciences: an R package.

PubMed

Kelley, Ken

2007-11-01

Methods for the Behavioral, Educational, and Social Sciences (MBESS; Kelley, 2007b) is an open source package for R (R Development Core Team, 2007b), an open source statistical programming language and environment. MBESS implements methods that are not widely available elsewhere, yet are especially helpful for the idiosyncratic techniques used within the behavioral, educational, and social sciences. The major categories of functions are those that relate to confidence interval formation for noncentral t, F, and chi2 parameters, confidence intervals for standardized effect sizes (which require noncentral distributions), and sample size planning issues from the power analytic and accuracy in parameter estimation perspectives. In addition, MBESS contains collections of other functions that should be helpful to substantive researchers and methodologists. MBESS is a long-term project that will continue to be updated and expanded so that important methods can continue to be made available to researchers in the behavioral, educational, and social sciences.

Inferring subunit stoichiometry from single molecule photobleaching

PubMed Central

2013-01-01

Single molecule photobleaching is a powerful tool for determining the stoichiometry of protein complexes. By attaching fluorophores to proteins of interest, the number of associated subunits in a complex can be deduced by imaging single molecules and counting fluorophore photobleaching steps. Because some bleaching steps might be unobserved, the ensemble of steps will be binomially distributed. In this work, it is shown that inferring the true composition of a complex from such data is nontrivial because binomially distributed observations present an ill-posed inference problem. That is, a unique and optimal estimate of the relevant parameters cannot be extracted from the observations. Because of this, a method has not been firmly established to quantify confidence when using this technique. This paper presents a general inference model for interpreting such data and provides methods for accurately estimating parameter confidence. The formalization and methods presented here provide a rigorous analytical basis for this pervasive experimental tool. PMID:23712552

Influence of different dose calculation algorithms on the estimate of NTCP for lung complications

PubMed Central

Bäck, Anna

2013-01-01

Due to limitations and uncertainties in dose calculation algorithms, different algorithms can predict different dose distributions and dose‐volume histograms for the same treatment. This can be a problem when estimating the normal tissue complication probability (NTCP) for patient‐specific dose distributions. Published NTCP model parameters are often derived for a different dose calculation algorithm than the one used to calculate the actual dose distribution. The use of algorithm‐specific NTCP model parameters can prevent errors caused by differences in dose calculation algorithms. The objective of this work was to determine how to change the NTCP model parameters for lung complications derived for a simple correction‐based pencil beam dose calculation algorithm, in order to make them valid for three other common dose calculation algorithms. NTCP was calculated with the relative seriality (RS) and Lyman‐Kutcher‐Burman (LKB) models. The four dose calculation algorithms used were the pencil beam (PB) and collapsed cone (CC) algorithms employed by Oncentra, and the pencil beam convolution (PBC) and anisotropic analytical algorithm (AAA) employed by Eclipse. Original model parameters for lung complications were taken from four published studies on different grades of pneumonitis, and new algorithm‐specific NTCP model parameters were determined. The difference between original and new model parameters was presented in relation to the reported model parameter uncertainties. Three different types of treatments were considered in the study: tangential and locoregional breast cancer treatment and lung cancer treatment. Changing the algorithm without the derivation of new model parameters caused changes in the NTCP value of up to 10 percentage points for the cases studied. Furthermore, the error introduced could be of the same magnitude as the confidence intervals of the calculated NTCP values. The new NTCP model parameters were tabulated as the algorithm was varied from PB to PBC, AAA, or CC. Moving from the PB to the PBC algorithm did not require new model parameters; however, moving from PB to AAA or CC did require a change in the NTCP model parameters, with CC requiring the largest change. It was shown that the new model parameters for a given algorithm are different for the different treatment types. PACS numbers: 87.53.‐j, 87.53.Kn, 87.55.‐x, 87.55.dh, 87.55.kd PMID:24036865

Wave-formed structures and paleoenvironmental reconstruction

USGS Publications Warehouse

Clifton, H.E.; Dingler, J.R.

1984-01-01

Wave-formed sedimentary structures can be powerful interpretive tools because they reflect not only the velocity and direction of the oscillatory currents, but also the length of the horizontal component of orbital motion and the presence of velocity asymmetry within the flow. Several of these aspects can be related through standard wave theories to combinations of wave dimensions and water depth that have definable natural limits. For a particular grain size, threshold of particle movement and that of conversion from a rippled to flat bed indicate flow-velocity limits. The ratio of ripple spacing to grain size provides an estimate of the length of the near-bottom orbital motion. The degree of velocity asymmetry is related to the asymmetry of the bedforms, though it presently cannot be estimated with confidence. A plot of water depth versus wave height (h-H diagram) provides a convenient approach for showing the combination of wave parameters and water depths capable of generating any particular structure in sand of a given grain size. Natural limits on wave height and inferences or assumptions regarding either water depth or wave period based on geologic evidence allow refinement of the paleoenvironmental reconstruction. The assumptions and the degree of approximation involved in the different techniques impose significant constraints. Inferences based on wave-formed structures are most reliable when they are drawn in the context of other evidence such as the association of sedimentary features or progradational sequences. ?? 1984.

EULAR definition of arthralgia suspicious for progression to rheumatoid arthritis.

PubMed

van Steenbergen, Hanna W; Aletaha, Daniel; Beaart-van de Voorde, Liesbeth J J; Brouwer, Elisabeth; Codreanu, Catalin; Combe, Bernard; Fonseca, João E; Hetland, Merete L; Humby, Frances; Kvien, Tore K; Niedermann, Karin; Nuño, Laura; Oliver, Sue; Rantapää-Dahlqvist, Solbritt; Raza, Karim; van Schaardenburg, Dirkjan; Schett, Georg; De Smet, Liesbeth; Szücs, Gabriella; Vencovský, Jirí; Wiland, Piotr; de Wit, Maarten; Landewé, Robert L; van der Helm-van Mil, Annette H M

2017-03-01

During the transition to rheumatoid arthritis (RA) many patients pass through a phase characterised by the presence of symptoms without clinically apparent synovitis. These symptoms are not well-characterised. This taskforce aimed to define the clinical characteristics of patients with arthralgia who are considered at risk for RA by experts based on their clinical experience. The taskforce consisted of 18 rheumatologists, 1 methodologist, 2 patients, 3 health professionals and 1 research fellow. The process had three phases. In phase I, a list of parameters considered characteristic for clinically suspect arthralgia (CSA) was derived; the most important parameters were selected by a three-phased Delphi approach. In phase II, the experts evaluated 50 existing patients on paper, classified them as CSA/no-CSA and indicated their level of confidence. A provisional set of parameters was derived. This was studied for validation in phase III, where all rheumatologists collected patients with and without CSA from their outpatient clinics. The comprehensive list consisted of 55 parameters, of which 16 were considered most important. A multivariable model based on the data from phase II identified seven relevant parameters: symptom duration <1 year, symptoms of metacarpophalangeal (MCP) joints, morning stiffness duration ≥60 min, most severe symptoms in early morning, first-degree relative with RA, difficulty with making a fist and positive squeeze test of MCP joints. In phase III, the combination of these parameters was accurate in identifying patients with arthralgia who were considered at risk of developing RA (area under the receiver operating characteristic curve 0.92, 95% CI 0.87 to 0.96). Test characteristics for different cut-off points were determined. A set of clinical characteristics for patients with arthralgia who are at risk of progression to RA was established. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Biomedical research competencies for osteopathic medical students

PubMed Central

Cruser, des Anges; Dubin, Bruce; Brown, Sarah K; Bakken, Lori L; Licciardone, John C; Podawiltz, Alan L; Bulik, Robert J

2009-01-01

Background Without systematic exposure to biomedical research concepts or applications, osteopathic medical students may be generally under-prepared to efficiently consume and effectively apply research and evidence-based medicine information in patient care. The academic literature suggests that although medical residents are increasingly expected to conduct research in their post graduate training specialties, they generally have limited understanding of research concepts. With grant support from the National Center for Complementary and Alternative Medicine, and a grant from the Osteopathic Heritage Foundation, the University of North Texas Health Science Center (UNTHSC) is incorporating research education in the osteopathic medical school curriculum. The first phase of this research education project involved a baseline assessment of students' understanding of targeted research concepts. This paper reports the results of that assessment and discusses implications for research education during medical school. Methods Using a novel set of research competencies supported by the literature as needed for understanding research information, we created a questionnaire to measure students' confidence and understanding of selected research concepts. Three matriculating medical school classes completed the on-line questionnaire. Data were analyzed for differences between groups using analysis of variance and t-tests. Correlation coefficients were computed for the confidence and applied understanding measures. We performed a principle component factor analysis of the confidence items, and used multiple regression analyses to explore how confidence might be related to the applied understanding. Results Of 496 total incoming, first, and second year medical students, 354 (71.4%) completed the questionnaire. Incoming students expressed significantly more confidence than first or second year students (F = 7.198, df = 2, 351, P = 0.001) in their ability to understand the research concepts. Factor analyses of the confidence items yielded conceptually coherent groupings. Regression analysis confirmed a relationship between confidence and applied understanding referred to as knowledge. Confidence scores were important in explaining variability in knowledge scores of the respondents. Conclusion Medical students with limited understanding of research concepts may struggle to understand the medical literature. Assessing medical students' confidence to understand and objectively measured ability to interpret basic research concepts can be used to incorporate competency based research material into the existing curriculum. PMID:19825171

The Spatial Relationship between Apparent Diffusion Coefficient and Standardized Uptake Value of 18F-Fluorodeoxyglucose Has a Crucial Influence on the Numeric Correlation of Both Parameters in PET/MRI of Lung Tumors

PubMed Central

Stieltjes, Bram; Weikert, Thomas; Gatidis, Sergios; Wiese, Mark; Wild, Damian; Lardinois, Didier

2017-01-01

The minimum apparent diffusion coefficient (ADCmin) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUVmax) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADCmin- and SUVmax-voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance (D) between ADCmin- and SUVmax-voxels was 14.0 mm (average of two readers). Spatial mismatch (D > 12 mm) between ADCmin and SUVmax was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUVmax and ADCmin was seen, while a moderate negative linear relationship (r = −0.5) between SUVmax and ADCmin was observed in tumors with a spatial match (D ≤ 12 mm). In conclusion, spatial mismatch between ADCmin and SUVmax is found in a considerable percentage of patients. The spatial connection of the two parameters SUVmax and ADCmin has a crucial influence on their numeric correlation. PMID:29391862

Prediction of Cerebral Hyperperfusion Syndrome with Velocity Blood Pressure Index.

PubMed

Lai, Zhi-Chao; Liu, Bao; Chen, Yu; Ni, Leng; Liu, Chang-Wei

2015-06-20

Cerebral hyperperfusion syndrome is an important complication of carotid endarterectomy (CEA). An >100% increase in middle cerebral artery velocity (MCAV) after CEA is used to predict the cerebral hyperperfusion syndrome (CHS) development, but the accuracy is limited. The increase in blood pressure (BP) after surgery is a risk factor of CHS, but no study uses it to predict CHS. This study was to create a more precise parameter for prediction of CHS by combined the increase of MCAV and BP after CEA. Systolic MCAV measured by transcranial Doppler and systematic BP were recorded preoperatively; 30 min postoperatively. The new parameter velocity BP index (VBI) was calculated from the postoperative increase ratios of MCAV and BP. The prediction powers of VBI and the increase ratio of MCAV (velocity ratio [VR]) were compared for predicting CHS occurrence. Totally, 6/185 cases suffered CHS. The best-fit cut-off point of 2.0 for VBI was identified, which had 83.3% sensitivity, 98.3% specificity, 62.5% positive predictive value and 99.4% negative predictive value for CHS development. This result is significantly better than VR (33.3%, 97.2%, 28.6% and 97.8%). The area under the curve (AUC) of receiver operating characteristic: AUC(VBI) = 0.981, 95% confidence interval [CI] 0.949-0.995; AUC(VR) = 0.935, 95% CI 0.890-0.966, P = 0.02. The new parameter VBI can more accurately predict patients at risk of CHS after CEA. This observation needs to be validated by larger studies.

ANALYSIS OF KEPLER'S SHORT-CADENCE PHOTOMETRY FOR TrES-2b

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

Kipping, David; Bakos, Gaspar, E-mail: dkipping@cfa.harvard.edu

2011-05-20

We present an analysis of 18 short-cadence (SC) transit light curves of TrES-2b using quarter 0 (Q0) and quarter 1 (Q1) from the Kepler Mission. The photometry is of unprecedented precision, 237 ppm minute{sup -1}, allowing for the most accurate determination of the transit parameters yet obtained for this system. Global fits of the transit photometry, radial velocities, and known transit times are used to obtain a self-consistent set of refined parameters for this system, including updated stellar and planetary parameters. Special attention is paid to fitting for limb darkening and eccentricity. We place an upper limit on the occultationmore » depth to be <72.9 ppm to 3{sigma} confidence, indicating TrES-2b has the lowest determined geometric albedo for an exoplanet, of A{sub g} < 0.146. We also produce a transit timing analysis using Kepler's SC data and demonstrate exceptional timing precision at the level of a few seconds for each transit event. With 18 fully sampled transits at such high precision, we are able to produce stringent constraints on the presence of perturbing planets, Trojans, and extrasolar moons. We introduce the novel use of control data to identify phasing effects. We also exclude the previously proposed hypotheses of short-period transit time variation and additional transits but find that the hypothesis of long-term inclination change is neither supported nor refuted by our analysis.« less

The Spatial Relationship between Apparent Diffusion Coefficient and Standardized Uptake Value of 18F-Fluorodeoxyglucose Has a Crucial Influence on the Numeric Correlation of Both Parameters in PET/MRI of Lung Tumors.

PubMed

Sauter, Alexander W; Stieltjes, Bram; Weikert, Thomas; Gatidis, Sergios; Wiese, Mark; Klarhöfer, Markus; Wild, Damian; Lardinois, Didier; Bremerich, Jens; Sommer, Gregor

2017-01-01

The minimum apparent diffusion coefficient (ADC min ) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUV max ) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADC min - and SUV max -voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance ( D ) between ADC min - and SUV max -voxels was 14.0 mm (average of two readers). Spatial mismatch ( D > 12 mm) between ADC min and SUV max was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUV max and ADC min was seen, while a moderate negative linear relationship ( r = -0.5) between SUV max and ADC min was observed in tumors with a spatial match ( D ≤ 12 mm). In conclusion, spatial mismatch between ADC min and SUV max is found in a considerable percentage of patients. The spatial connection of the two parameters SUV max and ADC min has a crucial influence on their numeric correlation.

Constraints on a generalized deceleration parameter from cosmic chronometers

NASA Astrophysics Data System (ADS)

Mamon, Abdulla Al

2018-04-01

In this paper, we have proposed a generalized parametrization for the deceleration parameter q in order to study the evolutionary history of the universe. We have shown that the proposed model can reproduce three well known q-parametrized models for some specific values of the model parameter α. We have used the latest compilation of the Hubble parameter measurements obtained from the cosmic chronometer (CC) method (in combination with the local value of the Hubble constant H0) and the Type Ia supernova (SNIa) data to place constraints on the parameters of the model for different values of α. We have found that the resulting constraints on the deceleration parameter and the dark energy equation of state support the ΛCDM model within 1σ confidence level at the present epoch.

Reporting of various methodological and statistical parameters in negative studies published in prominent Indian Medical Journals: a systematic review.

PubMed

Charan, J; Saxena, D

2014-01-01

Biased negative studies not only reflect poor research effort but also have an impact on 'patient care' as they prevent further research with similar objectives, leading to potential research areas remaining unexplored. Hence, published 'negative studies' should be methodologically strong. All parameters that may help a reader to judge validity of results and conclusions should be reported in published negative studies. There is a paucity of data on reporting of statistical and methodological parameters in negative studies published in Indian Medical Journals. The present systematic review was designed with an aim to critically evaluate negative studies published in prominent Indian Medical Journals for reporting of statistical and methodological parameters. Systematic review. All negative studies published in 15 Science Citation Indexed (SCI) medical journals published from India were included in present study. Investigators involved in the study evaluated all negative studies for the reporting of various parameters. Primary endpoints were reporting of "power" and "confidence interval." Power was reported in 11.8% studies. Confidence interval was reported in 15.7% studies. Majority of parameters like sample size calculation (13.2%), type of sampling method (50.8%), name of statistical tests (49.1%), adjustment of multiple endpoints (1%), post hoc power calculation (2.1%) were reported poorly. Frequency of reporting was more in clinical trials as compared to other study designs and in journals having impact factor more than 1 as compared to journals having impact factor less than 1. Negative studies published in prominent Indian medical journals do not report statistical and methodological parameters adequately and this may create problems in the critical appraisal of findings reported in these journals by its readers.

Weighting Mean and Variability during Confidence Judgments

PubMed Central

de Gardelle, Vincent; Mamassian, Pascal

2015-01-01

Humans can not only perform some visual tasks with great precision, they can also judge how good they are in these tasks. However, it remains unclear how observers produce such metacognitive evaluations, and how these evaluations might be dissociated from the performance in the visual task. Here, we hypothesized that some stimulus variables could affect confidence judgments above and beyond their impact on performance. In a motion categorization task on moving dots, we manipulated the mean and the variance of the motion directions, to obtain a low-mean low-variance condition and a high-mean high-variance condition with matched performances. Critically, in terms of confidence, observers were not indifferent between these two conditions. Observers exhibited marked preferences, which were heterogeneous across individuals, but stable within each observer when assessed one week later. Thus, confidence and performance are dissociable and observers’ confidence judgments put different weights on the stimulus variables that limit performance. PMID:25793275

Confidence intervals for the between-study variance in random-effects meta-analysis using generalised heterogeneity statistics: should we use unequal tails?

PubMed

Jackson, Dan; Bowden, Jack

2016-09-07

Confidence intervals for the between study variance are useful in random-effects meta-analyses because they quantify the uncertainty in the corresponding point estimates. Methods for calculating these confidence intervals have been developed that are based on inverting hypothesis tests using generalised heterogeneity statistics. Whilst, under the random effects model, these new methods furnish confidence intervals with the correct coverage, the resulting intervals are usually very wide, making them uninformative. We discuss a simple strategy for obtaining 95 % confidence intervals for the between-study variance with a markedly reduced width, whilst retaining the nominal coverage probability. Specifically, we consider the possibility of using methods based on generalised heterogeneity statistics with unequal tail probabilities, where the tail probability used to compute the upper bound is greater than 2.5 %. This idea is assessed using four real examples and a variety of simulation studies. Supporting analytical results are also obtained. Our results provide evidence that using unequal tail probabilities can result in shorter 95 % confidence intervals for the between-study variance. We also show some further results for a real example that illustrates how shorter confidence intervals for the between-study variance can be useful when performing sensitivity analyses for the average effect, which is usually the parameter of primary interest. We conclude that using unequal tail probabilities when computing 95 % confidence intervals for the between-study variance, when using methods based on generalised heterogeneity statistics, can result in shorter confidence intervals. We suggest that those who find the case for using unequal tail probabilities convincing should use the '1-4 % split', where greater tail probability is allocated to the upper confidence bound. The 'width-optimal' interval that we present deserves further investigation.

CORONAL PROPERTIES OF THE SEYFERT 1.9 GALAXY MCG-05-23-016 DETERMINED FROM HARD X-RAY SPECTROSCOPY WITH NuSTAR

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

Baloković, M.; Harrison, F. A.; Esmerian, C. J.

2015-02-10

Measurements of the high-energy cut-off in the coronal continuum of active galactic nuclei have long been elusive for all but a small number of the brightest examples. We present a direct measurement of the cut-off energy in the nuclear continuum of the nearby Seyfert 1.9 galaxy MCG-05-23-016 with unprecedented precision. The high sensitivity of NuSTAR up to 79 keV allows us to clearly disentangle the spectral curvature of the primary continuum from that of its reflection component. Using a simple phenomenological model for the hard X-ray spectrum, we constrain the cut-off energy to 116{sub −5}{sup +6} keV with 90% confidence.more » Testing for more complex models and nuisance parameters that could potentially influence the measurement, we find that the cut-off is detected robustly. We further use simple Comptonized plasma models to provide independent constraints for both the kinetic temperature of the electrons in the corona and its optical depth. At the 90% confidence level, we find kT{sub e} = 29 ± 2 keV and τ {sub e} = 1.23 ± 0.08 assuming a slab (disk-like) geometry, and kT{sub e} = 25 ± 2 keV and τ {sub e} = 3.5 ± 0.2 assuming a spherical geometry. Both geometries are found to fit the data equally well and their two principal physical parameters are correlated in both cases. With the optical depth in the τ {sub e} ≳ 1 regime, the data are pushing the currently available theoretical models of the Comptonized plasma to the limits of their validity. Since the spectral features and variability arising from the inner accretion disk have been observed previously in MCG-05-23-016, the inferred high optical depth implies that a spherical or disk-like corona cannot be homogeneous.« less

Safety and utility of magnetic resonance imaging in patients with cardiac implantable electronic devices.

PubMed

Strom, Jordan B; Whelan, Jill B; Shen, Changyu; Zheng, Shuang Qi; Mortele, Koenraad J; Kramer, Daniel B

2017-08-01

Off-label magnetic resonance imaging (MRI) for patients with cardiac implantable electrical devices has been limited owing to concerns about safety and unclear diagnostic and prognostic utility. The purpose of this study was to define major and minor adverse events with off-label MRI scans. We prospectively evaluated patients with non-MRI-conditional cardiac implantable electrical devices referred for MRI scans under a strict clinical protocol. The primary safety outcome was incidence of major adverse events (loss of pacing, inappropriate shock or antitachycardia pacing, need for system revision, or death) or minor adverse events (inappropriate pacing, arrhythmias, power-on-reset events, heating at the generator site, or changes in device parameters at baseline or at 6 months). A total of 189 MRI scans were performed in 123 patients (63.1% [78] men; median age 70 ± 18.5 years; 56.9% [70] patients with implantable cardioverter-defibrillators; 33.3% [41] pacemaker-dependent patients) predominantly for brain or spinal conditions. A minority of scans (22.7% [43]) were performed for urgent or emergent indications. Major adverse events were rare: 1 patient with loss of pacing, no deaths, or system revisions (overall rate 0.5%; 95% confidence interval 0.01-2.91). Minor adverse events were similarly rare (overall rate 1.6%; 95% confidence interval 0.3-4.6). Nearly all studies (98.4% [186]) were interpretable, while 75.1% [142] were determined to change management according to the prespecified criteria. No clinically significant changes were observed in device parameters acutely after MRI or at 6 months as compared with baseline across all patient and device categories. Off-label MRI scans performed under a strict protocol demonstrated excellent short- and medium-term safety while providing interpretable imaging that frequently influenced clinical care. Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Constraints on cosmological models and reconstructing the acceleration history of the Universe with gamma-ray burst distance indicators

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

Liang Nan; Wu Puxun; Zhang Shuangnan

2010-04-15

Gamma-ray bursts (GRBs) have been regarded as standard candles at very high redshift for cosmology research. We have proposed a new method to calibrate GRB distance indicators with Type Ia supernova (SNe Ia) data in a completely cosmology-independent way to avoid the circularity problem that had limited the direct use of GRBs to probe cosmology [N. Liang, W. K. Xiao, Y. Liu, and S. N. Zhang, Astrophys. J. 685, 354 (2008).]. In this paper, a simple method is provided to combine GRB data into the joint observational data analysis to constrain cosmological models; in this method those SNe Ia datamore » points used for calibrating the GRB data are not used to avoid any correlation between them. We find that the {Lambda}CDM model is consistent with the joint data in the 1-{sigma} confidence region, using the GRB data at high redshift calibrated with the interpolating method, the Constitution set of SNe Ia, the cosmic microwave background radiation from Wilkinson Microwave Anisotropy Probe five year observation, the baryonic acoustic oscillation from the spectroscopic Sloan Digital Sky Survey Data Release 7 galaxy sample, the x-ray baryon mass fraction in clusters of galaxies, and the observational Hubble parameter versus redshift data. Comparing to the joint constraints with GRBs and without GRBs, we find that the contribution of GRBs to the joint cosmological constraints is a slight shift in the confidence regions of cosmological parameters to better enclose the {Lambda}CDM model. Finally, we reconstruct the acceleration history of the Universe up to z>6 with the distance moduli of SNe Ia and GRBs and find some features that deviate from the {Lambda}CDM model and seem to favor oscillatory cosmology models; however, further investigations are needed to better understand the situation.« less

Safety and utility of magnetic resonance imaging in patients with cardiac implantable electronic devices

PubMed Central

Strom, Jordan B.; Whelan, Jill B.; Shen, Changyu; Zheng, Shuang Qi; Mortele, Koenraad J.; Kramer, Daniel B.

2017-01-01

BACKGROUND Off-label magnetic resonance imaging (MRI) for patients with cardiac implantable electrical devices has been limited owing to concerns about safety and unclear diagnostic and prognostic utility. OBJECTIVE The purpose of this study was to define major and minor adverse events with off-label MRI scans. METHODS We prospectively evaluated patients with non–MRI-conditional cardiac implantable electrical devices referred for MRI scans under a strict clinical protocol. The primary safety outcome was incidence of major adverse events (loss of pacing, inappropriate shock or antitachycardia pacing, need for system revision, or death) or minor adverse events (inappropriate pacing, arrhythmias, power-on-reset events, heating at the generator site, or changes in device parameters at baseline or at 6 months). RESULTS A total of 189 MRI scans were performed in 123 patients (63.1% [78] men; median age 70 ± 18.5 years; 37.0% [70] patients with implantable cardioverter-defibrillators; 21.8% [41] pacemaker-dependent patients) predominantly for brain or spinal conditions. A minority of scans (22.7% [43]) were performed for urgent or emergent indications. Major adverse events were rare: 1 patient with loss of pacing, no deaths, or system revisions (overall rate 0.5%; 95% confidence interval 0.01–2.91). Minor adverse events were similarly rare (overall rate 1.6%; 95% confidence interval 0.3–4.6). Nearly all studies (98.4% [186]) were interpretable, while 74.9% [142] were determined to change management according to the prespecified criteria. No clinically significant changes were observed in device parameters acutely after MRI or at 6 months as compared with baseline across all patient and device categories. CONCLUSION Off-label MRI scans performed under a strict protocol demonstrated excellent short- and medium-term safety while providing interpretable imaging that frequently influenced clinical care. PMID:28385671

Search for gravitational waves from LIGO-Virgo science run and data interpretation

NASA Astrophysics Data System (ADS)

Biswas, Rahul

Search for gravitational wave events was performed on data jointly taken during LIGO's fifth science run (S5) and Virgo's first science mn (VSR1). The data taken during this period was broken down into five separate months. I shall report the analysis performed on one of these months. Apart from the search, I shall describe the work related to estimation of rate based on the loudest event in the search. I shall demonstrate methods used in construction of rate intervals at 90% confidence level and combination of rates from multiple experiments of similar duration. To have confidence in our detection, accurate estimation of false alarm probability (F.A.P.) associated with the event candidate is required. Current false alarm estimation techniques limit our ability to measure the F.A.P. to about 1 in 100. I shall describe a method that significantly improves this estimate using information from multiple detectors. Besides accurate knowledge of F.A.P., detection is also dependent on our ability to distinguish real signals to those from noise. Several tests exist which use the quality of the signal to differentiate between real and noise signal. The chi-square test is one such computationally expensive test applied in our search; we shall understand the dependence of the chi-square parameter on the signal to noise ratio (SNR) for a given signal, which will help us to model the chi-square parameter based on SNR. The two detectors at Hanford, WA, H1(4km) and H2(2km), share the same vacuum system and hence their noise is correlated. Our present method of background estimation cannot capture this correlation and often underestimates the background when only H1 and H2 are operating. I shall describe a novel method of time reversed filtering to correctly estimate the background.

Prevalence of Hypertension in Children with Early-Stage ADPKD.

PubMed

Massella, Laura; Mekahli, Djalila; Paripović, Dušan; Prikhodina, Larisa; Godefroid, Nathalie; Niemirska, Anna; Ağbaş, Ayşe; Kalicka, Karolina; Jankauskiene, Augustina; Mizerska-Wasiak, Malgorzata; Afonso, Alberto Caldas; Salomon, Rémi; Deschênes, Georges; Ariceta, Gema; Özçakar, Z Birsin; Teixeira, Ana; Duzova, Ali; Harambat, Jérôme; Seeman, Tomáš; Hrčková, Gabriela; Lungu, Adrian Catalin; Papizh, Svetlana; Peco-Antic, Amira; De Rechter, Stéphanie; Giordano, Ugo; Kirchner, Marietta; Lutz, Teresa; Schaefer, Franz; Devuyst, Olivier; Wühl, Elke; Emma, Francesco

2018-04-19

Autosomal dominant polycystic kidney disease is the most common inheritable kidney disease, frequently thought to become symptomatic in adulthood. However, patients with autosomal dominant polycystic kidney disease may develop signs or symptoms during childhood, in particular hypertension. Although ambulatory BP monitoring is the preferred method to diagnose hypertension in pediatrics, data in children with autosomal dominant polycystic kidney disease are limited. Our retrospective multicenter study was conducted to collect ambulatory BP monitoring recordings from patients with autosomal dominant polycystic kidney disease age <18 years old. Basic anthropometric parameters as well as data on kidney function, BP treatment, and kidney ultrasound were also collected. Data from 310 children with autosomal dominant polycystic kidney disease with a mean age of 11.5±4.1 years old were collected at 22 European centers. At the time when ambulatory BP monitoring was performed, 95% of children had normal kidney function. Reference data for ambulatory BP monitoring were available for 292 patients. The prevalence rates of children with hypertension and/or those who were treated with antihypertensive drugs were 31%, 42%, and 35% during daytime, nighttime, or the entire 24-hour cycle, respectively. In addition, 52% of participants lacked a physiologic nocturnal BP dipping, and 18% had isolated nocturnal hypertension. Logistic regression analysis showed a significant association between a categorical cyst score that was calculated on the basis of the number of cysts >1 cm per kidney and daytime hypertension (odds ratio, 1.70; 95% confidence interval, 1.21 to 2.4; P =0.002), nighttime hypertension (odds ratio, 1.31; 95% confidence interval, 1.05 to 1.63; P =0.02), or 24-hour hypertension (odds ratio, 1.39; 95% confidence interval, 1.08 to 1.81; P =0.01). Kidney length, expressed as SD score, was also significantly associated with nighttime hypertension (odds ratio, 1.23; 95% confidence interval, 1.06 to 1.42; P =0.10). These data indicate high prevalence of hypertension in children with autosomal dominant polycystic kidney disease starting at young ages. Copyright © 2018 by the American Society of Nephrology.

Optimization of process parameters for drilled hole quality characteristics during cortical bone drilling using Taguchi method.

PubMed

Singh, Gurmeet; Jain, Vivek; Gupta, Dheeraj; Ghai, Aman

2016-09-01

Orthopaedic surgery involves drilling of bones to get them fixed at their original position. The drilling process used in orthopaedic surgery is most likely to the mechanical drilling process and there is all likelihood that it may harm the already damaged bone, the surrounding bone tissue and nerves, and the peril is not limited at that. It is very much feared that the recovery of that part may be impeded so that it may not be able to sustain life long. To achieve sustainable orthopaedic surgery, a surgeon must try to control the drilling damage at the time of bone drilling. The area around the holes decides the life of bone joint and so, the contiguous area of drilled hole must be intact and retain its properties even after drilling. This study mainly focuses on optimization of drilling parameters like rotational speed, feed rate and the type of tool at three levels each used by Taguchi optimization for surface roughness and material removal rate. The confirmation experiments were also carried out and results found with the confidence interval. Scanning electrode microscopy (SEM) images assisted in getting the micro level information of bone damage. Copyright © 2016 Elsevier Ltd. All rights reserved.

LOGISTIC FUNCTION PROFILE FIT: A least-squares program for fitting interface profiles to an extended logistic function

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

Kirchhoff, William H.

2012-09-15

The extended logistic function provides a physically reasonable description of interfaces such as depth profiles or line scans of surface topological or compositional features. It describes these interfaces with the minimum number of parameters, namely, position, width, and asymmetry. Logistic Function Profile Fit (LFPF) is a robust, least-squares fitting program in which the nonlinear extended logistic function is linearized by a Taylor series expansion (equivalent to a Newton-Raphson approach) with no apparent introduction of bias in the analysis. The program provides reliable confidence limits for the parameters when systematic errors are minimal and provides a display of the residuals frommore » the fit for the detection of systematic errors. The program will aid researchers in applying ASTM E1636-10, 'Standard practice for analytically describing sputter-depth-profile and linescan-profile data by an extended logistic function,' and may also prove useful in applying ISO 18516: 2006, 'Surface chemical analysis-Auger electron spectroscopy and x-ray photoelectron spectroscopy-determination of lateral resolution.' Examples are given of LFPF fits to a secondary ion mass spectrometry depth profile, an Auger surface line scan, and synthetic data generated to exhibit known systematic errors for examining the significance of such errors to the extrapolation of partial profiles.« less

Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment

NASA Astrophysics Data System (ADS)

Shen, Chengcheng; Shi, Honghua; Liu, Yongzhi; Li, Fen; Ding, Dewen

2016-07-01

Marine ecosystem dynamic models (MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization (PO), which is an important step in model calibration. An efficient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the efficiency of model calibration by analyzing and estimating the goodness-of-fit of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confidence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientific and normative technical framework for the improvement of MEDM skill.

Measuring the Viewing Angle of GW170817 with Electromagnetic and Gravitational Waves

NASA Astrophysics Data System (ADS)

Finstad, Daniel; De, Soumi; Brown, Duncan A.; Berger, Edo; Biwer, Christopher M.

2018-06-01

The joint detection of gravitational waves (GWs) and electromagnetic (EM) radiation from the binary neutron star merger GW170817 ushered in a new era of multi-messenger astronomy. Joint GW–EM observations can be used to measure the parameters of the binary with better precision than either observation alone. Here, we use joint GW–EM observations to measure the viewing angle of GW170817, the angle between the binary’s angular momentum and the line of sight. We combine a direct measurement of the distance to the host galaxy of GW170817 (NGC 4993) of 40.7 ± 2.36 Mpc with the Laser Interferometer Gravitational-wave Observatory (LIGO)/Virgo GW data and find that the viewing angle is {32}-13+10 +/- 1.7 degrees (90% confidence, statistical, and systematic errors). We place a conservative lower limit on the viewing angle of ≥13°, which is robust to the choice of prior. This measurement provides a constraint on models of the prompt γ-ray and radio/X-ray afterglow emission associated with the merger; for example, it is consistent with the off-axis viewing angle inferred for a structured jet model. We provide for the first time the full posterior samples from Bayesian parameter estimation of LIGO/Virgo data to enable further analysis by the community.

Revision and proposed modification for a total maximum daily load model for Upper Klamath Lake, Oregon

USGS Publications Warehouse

Wherry, Susan A.; Wood, Tamara M.; Anderson, Chauncey W.

2015-01-01

Using the extended 1991–2010 external phosphorus loading dataset, the lake TMDL model was recalibrated following the same procedures outlined in the Phase 1 review. The version of the model selected for further development incorporated an updated sediment initial condition, a numerical solution method for the chlorophyll a model, changes to light and phosphorus factors limiting algal growth, and a new pH-model regression, which removed Julian day dependence in order to avoid discontinuities in pH at year boundaries. This updated lake TMDL model was recalibrated using the extended dataset in order to compare calibration parameters to those obtained from a calibration with the original 7.5-year dataset. The resulting algal settling velocity calibrated from the extended dataset was more than twice the value calibrated with the original dataset, and, because the calibrated values of algal settling velocity and recycle rate are related (more rapid settling required more rapid recycling), the recycling rate also was larger than that determined with the original dataset. These changes in calibration parameters highlight the uncertainty in critical rates in the Upper Klamath Lake TMDL model and argue for their direct measurement in future data collection to increase confidence in the model predictions.

Estimation of suspended sediment concentration from Acoustic Doppler Current Profiler (ADCP) instrument: A case study of Lembeh Strait, North Sulawesi

NASA Astrophysics Data System (ADS)

Dwinovantyo, Angga; Manik, Henry M.; Prartono, Tri; Susilohadi; Ilahude, Delyuzar

2017-01-01

Measurement of suspended sediment concentration (SSC) is one of the parameters needed to determine the characteristics of sediment transport. However, the measurement of SSC nowadays still uses conventional technique and it has limitations; especially in temporal resolution. With advanced technology, the measurement can use hydroacoustic technology such as Acoustic Doppler Current Profiler (ADCP). ADCP measures the intensity of backscatter as echo intensity unit from sediment particles. The frequency of ADCP used in this study was 400 kHz. The samples were measured and collected from Lembeh Strait, North Sulawesi. The highest concentration of suspended sediment was 98.89 mg L-1 and the lowest was 45.20 mg L-1. Time series data showed the tidal condition affected the SSC. From the research, we also made correction from sound signal losses effect such as spherical spreading and sound absorption to get more accurate results by eliminating these parameters in echo intensity data. Simple linear regression analysis at echo intensity measured from ADCP to direct measurement of SSC was performed to obtain the estimation of the SSC. The comparison result of estimation of SSC from ADCP measurements and SSC from laboratory analyses was insignificantly different based on t-test statistical analysis with 95% confidence interval percentage.

The Applicability of Confidence Intervals of Quantiles for the Generalized Logistic Distribution

NASA Astrophysics Data System (ADS)

Shin, H.; Heo, J.; Kim, T.; Jung, Y.

2007-12-01

The generalized logistic (GL) distribution has been widely used for frequency analysis. However, there is a little study related to the confidence intervals that indicate the prediction accuracy of distribution for the GL distribution. In this paper, the estimation of the confidence intervals of quantiles for the GL distribution is presented based on the method of moments (MOM), maximum likelihood (ML), and probability weighted moments (PWM) and the asymptotic variances of each quantile estimator are derived as functions of the sample sizes, return periods, and parameters. Monte Carlo simulation experiments are also performed to verify the applicability of the derived confidence intervals of quantile. As the results, the relative bias (RBIAS) and relative root mean square error (RRMSE) of the confidence intervals generally increase as return period increases and reverse as sample size increases. And PWM for estimating the confidence intervals performs better than the other methods in terms of RRMSE when the data is almost symmetric while ML shows the smallest RBIAS and RRMSE when the data is more skewed and sample size is moderately large. The GL model was applied to fit the distribution of annual maximum rainfall data. The results show that there are little differences in the estimated quantiles between ML and PWM while distinct differences in MOM.

Search for magnetic monopoles in sqrt[s]=7  TeV pp collisions with the ATLAS detector.

PubMed

Aad, G; Abajyan, T; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdelalim, A A; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Acerbi, E; Acharya, B S; Adamczyk, L; Adams, D L; Addy, T N; Adelman, J; Adomeit, S; Adragna, P; Adye, T; Aefsky, S; Aguilar-Saavedra, J A; Agustoni, M; Aharrouche, M; Ahlen, S P; Ahles, F; Ahmad, A; Ahsan, M; Aielli, G; Akdogan, T; Åkesson, T P A; Akimoto, G; Akimov, A V; Alam, M S; Alam, M A; Albert, J; Albrand, S; Aleksa, M; Aleksandrov, I N; Alessandria, F; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Aliev, M; Alimonti, G; Alison, J; Allbrooke, B M M; Allport, P P; Allwood-Spiers, S E; Almond, J; Aloisio, A; Alon, R; Alonso, A; Alonso, F; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amelung, C; Ammosov, V V; Amorim, A; Amram, N; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Anduaga, X S; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A; Anjos, N; Annovi, A; Antonaki, A; Antonelli, M; Antonov, A; Antos, J; Anulli, F; Aoki, M; Aoun, S; Aperio Bella, L; Apolle, R; Arabidze, G; Aracena, I; Arai, Y; Arce, A T H; Arfaoui, S; Arguin, J-F; Arik, E; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arnault, C; Artamonov, A; Artoni, G; Arutinov, D; Asai, S; Asfandiyarov, R; Ask, S; Åsman, B; Asquith, L; Assamagan, K; Astbury, A; Atkinson, M; Aubert, B; Auge, E; Augsten, K; Aurousseau, M; Avolio, G; Avramidou, R; Axen, D; Azuelos, G; Azuma, Y; Baak, M A; Baccaglioni, G; Bacci, C; Bach, A M; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Badescu, E; Bagnaia, P; Bahinipati, S; Bai, Y; Bailey, D C; Bain, T; Baines, J T; Baker, O K; Baker, M D; Baker, S; Banas, E; Banerjee, P; Banerjee, Sw; Banfi, D; Bangert, A; Bansal, V; Bansil, H S; Barak, L; Baranov, S P; Barbaro Galtieri, A; Barber, T; Barberio, E L; Barberis, D; Barbero, M; Bardin, D Y; Barillari, T; Barisonzi, M; Barklow, T; Barlow, N; Barnett, B M; Barnett, R M; Baroncelli, A; 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2012-12-28

This Letter presents a search for magnetic monopoles with the ATLAS detector at the CERN Large Hadron Collider using an integrated luminosity of 2.0  fb(-1) of pp collisions recorded at a center-of-mass energy of sqrt[s]=7  TeV. No event is found in the signal region, leading to an upper limit on the production cross section at 95% confidence level of 1.6/ϵ  fb for Dirac magnetic monopoles with the minimum unit magnetic charge and with mass between 200 GeV and 1500 GeV, where ϵ is the monopole reconstruction efficiency. The efficiency ϵ is high and uniform in the fiducial region given by pseudorapidity |η|<1.37 and transverse kinetic energy 600-700

Limits on Axion Couplings from the First 80 Days of Data of the PandaX-II Experiment.

PubMed

Fu, Changbo; Zhou, Xiaopeng; Chen, Xun; Chen, Yunhua; Cui, Xiangyi; Fang, Deqing; Giboni, Karl; Giuliani, Franco; Han, Ke; Huang, Xingtao; Ji, Xiangdong; Ju, Yonglin; Lei, Siao; Li, Shaoli; Liu, Huaxuan; Liu, Jianglai; Ma, Yugang; Mao, Yajun; Ren, Xiangxiang; Tan, Andi; Wang, Hongwei; Wang, Jimin; Wang, Meng; Wang, Qiuhong; Wang, Siguang; Wang, Xuming; Wang, Zhou; Wu, Shiyong; Xiao, Mengjiao; Xie, Pengwei; Yan, Binbin; Yang, Yong; Yue, Jianfeng; Zhang, Hongguang; Zhang, Tao; Zhao, Li; Zhou, Ning

2017-11-03

We report new searches for solar axions and galactic axionlike dark matter particles, using the first low-background data from the PandaX-II experiment at China Jinping Underground Laboratory, corresponding to a total exposure of about 2.7×10^{4}  kg day. No solar axion or galactic axionlike dark matter particle candidate has been identified. The upper limit on the axion-electron coupling (g_{Ae}) from the solar flux is found to be about 4.35×10^{-12} in the mass range from 10^{-5} to 1  keV/c^{2} with 90% confidence level, similar to the recent LUX result. We also report a new best limit from the ^{57}Fe deexcitation. On the other hand, the upper limit from the galactic axions is on the order of 10^{-13} in the mass range from 1 to 10  keV/c^{2} with 90% confidence level, slightly improved compared with the LUX.

Search for the Decays B_{s}^{0}→τ^{+}τ^{-} and B^{0}→τ^{+}τ^{-}.

PubMed

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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 Gonzalo, D; 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; Schreiner, H F; 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; 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; Stoica, S; Stone, S; Storaci, B; Stracka, S; Stramaglia, M E; 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; Tourinho Jadallah Aoude, R; 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; Verlage, T 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; Winn, M A; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wraight, K; Wyllie, K; Xie, Y; Xing, Z; Xu, Z; Yang, Z; Yang, Z; Yao, Y; Yin, H; Yu, J; Yuan, X; Yushchenko, O; Zarebski, K A; Zavertyaev, M; Zhang, L; Zhang, Y; Zhelezov, A; Zheng, Y; Zhu, X; Zhukov, V; Zucchelli, S

2017-06-23

A search for the rare decays B_{s}^{0}→τ^{+}τ^{-} and B^{0}→τ^{+}τ^{-} is performed using proton-proton collision data collected with the LHCb detector. The data sample corresponds to an integrated luminosity of 3  fb^{-1} collected in 2011 and 2012. The τ leptons are reconstructed through the decay τ^{-}→π^{-}π^{+}π^{-}ν_{τ}. Assuming no contribution from B^{0}→τ^{+}τ^{-} decays, an upper limit is set on the branching fraction B(B_{s}^{0}→τ^{+}τ^{-})<6.8×10^{-3} at the 95% confidence level. If instead no contribution from B_{s}^{0}→τ^{+}τ^{-} decays is assumed, the limit is B(B^{0}→τ^{+}τ^{-})<2.1×10^{-3} at the 95% confidence level. These results correspond to the first direct limit on B(B_{s}^{0}→τ^{+}τ^{-}) and the world's best limit on B(B^{0}→τ^{+}τ^{-}).

Confidence intervals for a difference between lognormal means in cluster randomization trials.

PubMed

Poirier, Julia; Zou, G Y; Koval, John

2017-04-01

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.

Effects of heterogeneous convergence rate on consensus in opinion dynamics

NASA Astrophysics Data System (ADS)

Huang, Changwei; Dai, Qionglin; Han, Wenchen; Feng, Yuee; Cheng, Hongyan; Li, Haihong

2018-06-01

The Deffuant model has attracted much attention in the study of opinion dynamics. Here, we propose a modified version by introducing into the model a heterogeneous convergence rate which is dependent on the opinion difference between interacting agents and a tunable parameter κ. We study the effects of heterogeneous convergence rate on consensus by investigating the probability of complete consensus, the size of the largest opinion cluster, the number of opinion clusters, and the relaxation time. We find that the decrease of the convergence rate is favorable to decreasing the confidence threshold for the population to always reach complete consensus, and there exists optimal κ resulting in the minimal bounded confidence threshold. Moreover, we find that there exists a window before the threshold of confidence in which complete consensus may be reached with a nonzero probability when κ is not too large. We also find that, within a certain confidence range, decreasing the convergence rate will reduce the relaxation time, which is somewhat counterintuitive.

Interobserver agreement on the echocardiographic parameters that estimate right ventricular systolic function in the early postoperative period of cardiac surgery.

PubMed

Olmos-Temois, S G; Santos-Martínez, L E; Álvarez-Álvarez, R; Gutiérrez-Delgado, L G; Baranda-Tovar, F M

2016-11-01

To know the variability of transthoracic echocardiographic parameters that assess right ventricular systolic function by analyzing interobserver agreement in the early postoperative period of cardiovascular surgery. To assess the feasibility of these echocardiographic measurements. A cross-sectional study, double-blind pilot study was carried out from May 2011 to February 2013. Cardiovascular postoperative critical care at the National Institute of Cardiology "Ignacio Chávez", Mexico City, Mexico. Consecutive, non-probabilistic sampling. Fifty-six patients were studied in the postoperative period of cardiac surgery. The first echocardiographic parameters were obtained between 6-8hours after cardiac surgery, followed by blinded second measurements. Tricuspid annular plane systolic excursion (TAPSE), tricuspid annular peak systolic velocity on tissue Doppler imaging (VSPAT), diameters and right ventricular outflow area, tract fractional shortening. The agreement was analyzed by the Bland-Altman method, and its magnitude was assessed by the intraclass correlation coefficient (95% confidence interval). Both observers evaluated TAPSE and VSPAT in 48 patients (92%). The average TAPSE was 11.68±4.53mm (range 4-27mm). Right ventricular systolic dysfunction was observed in 41 cases (85%) and normal TAPSE in 7 patients (15%). The average difference and its limits according to TAPSE were -0.917±2.95 (-6.821, 4.988), with a magnitude of 0.725 (0.552, 0.837); the tricuspid annular peak systolic velocity on tissue Doppler imaging was -0.001±0.015 (-0.031, 0.030), and its magnitude 0.825 (0.708, 0.898), respectively. VSPAT and TAPSE were estimated by both observers in 92% of the patients, these parameters exhibiting the lowest interobserver variability. Copyright © 2016 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

An Improved Method to Measure the Cosmic Curvature

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

Wei, Jun-Jie; Wu, Xue-Feng, E-mail: jjwei@pmo.ac.cn

2017-04-01

In this paper, we propose an improved model-independent method to constrain the cosmic curvature by combining the most recent Hubble parameter H ( z ) and supernovae Ia (SNe Ia) data. Based on the H ( z ) data, we first use the model-independent smoothing technique, Gaussian processes, to construct a distance modulus μ {sub H} ( z ), which is susceptible to the cosmic curvature parameter Ω{sub k}. In contrary to previous studies, the light-curve-fitting parameters, which account for the distance estimation of SN (μ {sub SN}( z )), are set free to investigate whether Ω {sub k} hasmore » a dependence on them. By comparing μ {sub H} ( z ) to μ {sub SN}(z), we put limits on Ω {sub k}. Our results confirm that Ω {sub k} is independent of the SN light-curve parameters. Moreover, we show that the measured Ω {sub k} is in good agreement with zero cosmic curvature, implying that there is no significant deviation from a flat universe at the current observational data level. We also test the influence of different H(z) samples and different Hubble constant H {sub 0} values, finding that different H(z) samples do not have a significant impact on the constraints. However, different H {sub 0} priors can affect the constraints of Ω {sub k} to some degree. The prior of H {sub 0} = 73.24 ± 1.74 km s{sup −1} Mpc{sup −1} gives a value of Ω {sub k}, a little bit above the 1 σ confidence level away from 0, but H{sub 0} = 69.6 ± 0.7 km s{sup −1} Mpc{sup −1} gives it below 1 σ .« less

Dynamical modeling and multi-experiment fitting with PottersWheel

PubMed Central

Maiwald, Thomas; Timmer, Jens

2008-01-01

Motivation: Modelers in Systems Biology need a flexible framework that allows them to easily create new dynamic models, investigate their properties and fit several experimental datasets simultaneously. Multi-experiment-fitting is a powerful approach to estimate parameter values, to check the validity of a given model, and to discriminate competing model hypotheses. It requires high-performance integration of ordinary differential equations and robust optimization. Results: We here present the comprehensive modeling framework Potters-Wheel (PW) including novel functionalities to satisfy these requirements with strong emphasis on the inverse problem, i.e. data-based modeling of partially observed and noisy systems like signal transduction pathways and metabolic networks. PW is designed as a MATLAB toolbox and includes numerous user interfaces. Deterministic and stochastic optimization routines are combined by fitting in logarithmic parameter space allowing for robust parameter calibration. Model investigation includes statistical tests for model-data-compliance, model discrimination, identifiability analysis and calculation of Hessian- and Monte-Carlo-based parameter confidence limits. A rich application programming interface is available for customization within own MATLAB code. Within an extensive performance analysis, we identified and significantly improved an integrator–optimizer pair which decreases the fitting duration for a realistic benchmark model by a factor over 3000 compared to MATLAB with optimization toolbox. Availability: PottersWheel is freely available for academic usage at http://www.PottersWheel.de/. The website contains a detailed documentation and introductory videos. The program has been intensively used since 2005 on Windows, Linux and Macintosh computers and does not require special MATLAB toolboxes. Contact: maiwald@fdm.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:18614583

Analysis of pelvic rotation on the standard hip ventrodorsal extended radiographic view.

PubMed

Martins, João; Colaço, Bruno J; Ferreira, António J; Ginja, Mário M

2016-01-01

To study the symmetry of the iliac horizontal diameter (IHD) maximum obturator foramen width (OFW), ischiatic femoral overlap (IFO), pelvic horizontal radius (PHR), femoral head diameter (FHD), and obturator foramen area (OFA) parameters in the normal hip extended radiographic view and to evaluate the correlation of pelvic rotation with the magnitude of asymmetry of these parameters. Nine canine cadavers from adult, large and giant breeds were radiographed in standard hip extended views and with 2°, 4° and 6° degrees of rotation. The variables IHD, OFW, IFO, PHR, FHD, and OFA were analysed in radiographs. The IHD measurements exhibited repeatability, bilateral symmetry and 95% of confidence interval of asymmetry in different pelvic rotations without superposition (p <0.05); OFW and IFO exhibited repeatability, bilateral symmetry and a small superposition in 95% of confidence interval of asymmetry according different pelvic rotations; PHR, FHD and OFA exhibited repeatability, bilateral symmetry and unacceptable superposition in 95% of confidence interval of asymmetry depending on pelvic rotation. The IHD is the recommended variable and OFW is an acceptable variable in order to evaluate slight pelvic rotation. The data may be used in qualitative analyses of hip extended radiographic views. In the future, complementary studies should be performed to evaluate the impact of degree of pelvic rotation on the hip dysplasia score.

Dimensions of human ejaculated spermatozoa in Papanicolaou-stained seminal and swim-up smears obtained from the Integrated Semen Analysis System (ISAS®)

PubMed Central

Bellastella, Giuseppe; Cooper, Trevor G.; Battaglia, Marina; Ströse, Anda; Torres, Inma; Hellenkemper, Barbara; Soler, Carles; Sinisi, Antonio A.

2010-01-01

Objective measurements are required for computer-aided sperm morphometric analysis (CASMA) machines to distinguish normal from abnormal sperm heads. The morphometric characteristics of spermatozoa in 72 samples of semen and of spermatozoa from 72 other semen samples after swim-up were quantified by the semi-automated Integrated Sperm Analysis System (ISAS) computer-aided system, which measured the sperm head parameters length (L), width (W), area (A), perimeter (P), acrosomal area (Ac), and the derived values L/W and P/A. For each man a homogeneous population of distributions characterized seminal spermatozoa (7 942 cells: median values L 4.4 μm, W 2.8 μm, A 9.8 μm2, P 12.5 μm, Ac 47.5%, L/W 1.57, P/A 1.27), and there was no significant difference in within- and among-individual variation. Different men could have spermatozoa of significantly different dimensions. Head dimensions for swim-up spermatozoa from different men (4 812 cells) were similar to those in semen, differing only by 2%–5%. The values of L, W and L/W fell within the limits given by the World Health Organization (WHO). Although these samples were not biologically matched, linear mixed-effects statistical analyses permitted valid comparison of the groups. A subpopulation of 404 spermatozoa considered to fit the stringent criteria of WHO 'normal' seminal spermatozoa from both semen and swim-up were characterized by median values (and 95% confidence intervals) of L, 4.3 μm (3.8–4.9), W, 2.9 μm (2.6–3.3), A, 10.2 μm2 (8.5–12.2), P, 12.4 μm (11.3–13.9), Ac, 49% (36–60), L/W, 1.49 (1.32–1.67) and P/A, 1.22 (1.11–1.35). These median values fall within the 95th centile confidence limits given by WHO, but the confidence intervals for L and W were larger. Although these differences in head dimensions among men and after swim-up could be detected by CASMA, the small differences make it unlikely that technicians would be able to distinguish them. The values could be used as default sperm head values for the CASMA machine used here. PMID:20852650

Dimensions of human ejaculated spermatozoa in Papanicolaou-stained seminal and swim-up smears obtained from the Integrated Semen Analysis System (ISAS(®)).

PubMed

Bellastella, Giuseppe; Cooper, Trevor G; Battaglia, Marina; Ströse, Anda; Torres, Inma; Hellenkemper, Barbara; Soler, Carles; Sinisi, Antonio A

2010-11-01

Objective measurements are required for computer-aided sperm morphometric analysis (CASMA) machines to distinguish normal from abnormal sperm heads. The morphometric characteristics of spermatozoa in 72 samples of semen and of spermatozoa from 72 other semen samples after swim-up were quantified by the semi-automated Integrated Sperm Analysis System (ISAS) computer-aided system, which measured the sperm head parameters length (L), width (W), area (A), perimeter (P), acrosomal area (Ac), and the derived values L/W and P/A. For each man a homogeneous population of distributions characterized seminal spermatozoa (7 942 cells: median values L 4.4 μm, W 2.8 μm, A 9.8 μm(2), P 12.5 μm, Ac 47.5%, L/W 1.57, P/A 1.27), and there was no significant difference in within- and among-individual variation. Different men could have spermatozoa of significantly different dimensions. Head dimensions for swim-up spermatozoa from different men (4 812 cells) were similar to those in semen, differing only by 2%-5%. The values of L, W and L/W fell within the limits given by the World Health Organization (WHO). Although these samples were not biologically matched, linear mixed-effects statistical analyses permitted valid comparison of the groups. A subpopulation of 404 spermatozoa considered to fit the stringent criteria of WHO 'normal' seminal spermatozoa from both semen and swim-up were characterized by median values (and 95% confidence intervals) of L, 4.3 μm (3.8-4.9), W, 2.9 μm (2.6-3.3), A, 10.2 μm(2) (8.5-12.2), P, 12.4 μm (11.3-13.9), Ac, 49% (36-60), L/W, 1.49 (1.32-1.67) and P/A, 1.22 (1.11-1.35). These median values fall within the 95th centile confidence limits given by WHO, but the confidence intervals for L and W were larger. Although these differences in head dimensions among men and after swim-up could be detected by CASMA, the small differences make it unlikely that technicians would be able to distinguish them. The values could be used as default sperm head values for the CASMA machine used here.

Optimization of Biomathematical Model Predictions for Cognitive Performance Impairment in Individuals: Accounting for Unknown Traits and Uncertain States in Homeostatic and Circadian Processes

PubMed Central

Van Dongen, Hans P. A.; Mott, Christopher G.; Huang, Jen-Kuang; Mollicone, Daniel J.; McKenzie, Frederic D.; Dinges, David F.

2007-01-01

Current biomathematical models of fatigue and performance do not accurately predict cognitive performance for individuals with a priori unknown degrees of trait vulnerability to sleep loss, do not predict performance reliably when initial conditions are uncertain, and do not yield statistically valid estimates of prediction accuracy. These limitations diminish their usefulness for predicting the performance of individuals in operational environments. To overcome these 3 limitations, a novel modeling approach was developed, based on the expansion of a statistical technique called Bayesian forecasting. The expanded Bayesian forecasting procedure was implemented in the two-process model of sleep regulation, which has been used to predict performance on the basis of the combination of a sleep homeostatic process and a circadian process. Employing the two-process model with the Bayesian forecasting procedure to predict performance for individual subjects in the face of unknown traits and uncertain states entailed subject-specific optimization of 3 trait parameters (homeostatic build-up rate, circadian amplitude, and basal performance level) and 2 initial state parameters (initial homeostatic state and circadian phase angle). Prior information about the distribution of the trait parameters in the population at large was extracted from psychomotor vigilance test (PVT) performance measurements in 10 subjects who had participated in a laboratory experiment with 88 h of total sleep deprivation. The PVT performance data of 3 additional subjects in this experiment were set aside beforehand for use in prospective computer simulations. The simulations involved updating the subject-specific model parameters every time the next performance measurement became available, and then predicting performance 24 h ahead. Comparison of the predictions to the subjects' actual data revealed that as more data became available for the individuals at hand, the performance predictions became increasingly more accurate and had progressively smaller 95% confidence intervals, as the model parameters converged efficiently to those that best characterized each individual. Even when more challenging simulations were run (mimicking a change in the initial homeostatic state; simulating the data to be sparse), the predictions were still considerably more accurate than would have been achieved by the two-process model alone. Although the work described here is still limited to periods of consolidated wakefulness with stable circadian rhythms, the results obtained thus far indicate that the Bayesian forecasting procedure can successfully overcome some of the major outstanding challenges for biomathematical prediction of cognitive performance in operational settings. Citation: Van Dongen HPA; Mott CG; Huang JK; Mollicone DJ; McKenzie FD; Dinges DF. Optimization of biomathematical model predictions for cognitive performance impairment in individuals: accounting for unknown traits and uncertain states in homeostatic and circadian processes. SLEEP 2007;30(9):1129-1143. PMID:17910385

Community pharmacists require additional support to develop capacity in delivering alcohol-related health information to older adults.

PubMed

Dare, Julie; Wilkinson, Celia; Garlepp, Michael; Lo, Johnny; Allsop, Steve

2017-08-01

This qualitative study explored the barriers and enablers influencing Western Australian (WA) community pharmacists' knowledge, confidence, willingness and practice in engaging older clients (>60 years) in alcohol-related health discussions. Two focus groups were conducted with a total of 14 community pharmacists who had previously completed a formative quantitative survey (n = 63), and indicated willingness to participate in a follow-up focus group. Focus group questions, informed by the survey results, explored participants' perceptions about barriers and enablers to delivering health information and advice about alcohol to older clients (60+ years). Shaw and colleagues' theoretical framework was used to understand barriers and enablers in relation to role legitimacy, role adequacy and role support. Participants acknowledged that providing health information about alcohol to older clients is a legitimate part of a community pharmacist's role, and most were confident performing this role in situations perceived as core to their professional practice, such as while dispensing medicines. However, many participants identified limited knowledge, skills and confidence in assisting older clients who may have alcohol issues, beyond advising them on medication and alcohol use. Structural barriers such as time and financial barriers were also identified. Routine professional practice including dispensing medicine and home medicine reviews may provide valuable opportunities to engage older clients in alcohol-related discussions. However, limited knowledge concerning appropriate strategies to assist older clients reduce their alcohol consumption, coupled with limited skills and confidence among community pharmacists in raising sensitive alcohol-related issues with clients, suggest the need for specific alcohol-related training and support. © 2016 Royal Pharmaceutical Society.

Detecting reliable cognitive change in individual patients with the MATRICS Consensus Cognitive Battery.

PubMed

Gray, Bradley E; McMahon, Robert P; Green, Michael F; Seidman, Larry J; Mesholam-Gately, Raquelle I; Kern, Robert S; Nuechterlein, Keith H; Keefe, Richard S; Gold, James M

2014-10-01

Clinicians often need to evaluate the treatment response of an individual person and to know that observed change is true improvement or worsening beyond usual week-to-week changes. This paper gives clinicians tools to evaluate individual changes on the MATRICS Consensus Cognitive Battery (MCCB). We compare three different approaches: a descriptive analysis of MCCB test-retest performance with no intervention, a reliable change index (RCI) approach controlling for average practice effects, and a regression approach. Data were gathered as part of the MATRICS PASS study (Nuechterlein et al., 2008). A total of 159 people with schizophrenia completed the MCCB at baseline and 4weeks later. Data were analyzed using an RCI and a regression formula establishing confidence intervals. The RCI and regression approaches agree within one point when baseline values are close to the sample mean. However, the regression approach offers more accurate limits for expected change at the tails of the distribution of baseline scores. Although both approaches have their merits, the regression approach provides the most accurate measure of significant change across the full range of scores. As the RCI does not account for regression to the mean and has confidence limits that remain constant across baseline scores, the RCI approach effectively gives narrower confidence limits around an inaccurately predicted average change value. Further, despite the high test-retest reliability of the MCCB, a change in an individual's score must be relatively large to be confident that it is beyond normal month-to-month variation. Copyright © 2014 Elsevier B.V. All rights reserved.

Impact of referral letters on scheduling of hospital appointments: a randomised control trial

PubMed Central

Jiwa, Moyez; Meng, Xingqiong; O’Shea, Carolyn; Magin, Parker; Dadich, Ann; Pillai, Vinita

2014-01-01

Background Communication is essential for triage, but intervention trials to improve it are scarce. Referral Writer (RW), a referral letter software program, enables documentation of clinical data and extracts relevant patient details from clinical software. Aim To evaluate whether specialists are more confident about scheduling appointments when they receive more information in referral letters. Design and setting Single-blind, parallel-groups, controlled design with a 1:1 randomisation. Australian GPs watched video vignettes virtually. Method GPs wrote referral letters after watching vignettes of patients with cancer symptoms. Letter content was scored against a benchmark. The proportions of referral letters triagable by a specialist with confidence, and in which the specialist was confident the patient had potentially life-limiting pathology were determined. Categorical outcomes were tested with χ2 and continuous outcomes with t-tests. A random-effects logistic model assessed the influence of group randomisation (RW versus control), GP demographics, clinical specialty, and specialist referral assessor on specialist confidence in the information provided. Results The intervention (RW) group referred more patients and scored significantly higher on information relayed (mean difference 21.6 [95% confidence intervals {CI} = 20.1 to 23.2]). There was no difference in the proportion of letters for which specialists were confident they had sufficient information for appointment scheduling (RW 77.7% versus control 80.6%, P = 0.16). In the logistic model, limited agreement among specialists contributed substantially to the observed differences in appointment scheduling (P = 35% [95% CI 16% to 59%]). Conclusion In isolation, referral letter templates are unlikely to improve the scheduling of specialist appointments, even when more information is relayed. PMID:24982494

Statistical evaluation of the Local Lymph Node Assay.

PubMed

Hothorn, Ludwig A; Vohr, Hans-Werner

2010-04-01

In the Local Lymph Node Assay measured endpoints for each animal, such as cell proliferation, cell counts and/or lymph node weight should be evaluated separately. The primary criterion for a positive response is when the estimated stimulation index is larger than a specified relative threshold that is endpoint- and strain-specific. When the lower confidence limit for ratio-to-control comparisons is larger than a relevance threshold, a biologically relevant increase can be concluded according to the proof of hazard. Alternatively, when the upper confidence limit for ratio-to-control comparisons is smaller than a tolerable margin, harmlessness can be concluded according to a proof of safety. Copyright 2009 Elsevier Inc. All rights reserved.

Pharmacokinetics and bioequivalence study of two brands of loxoprofen tablets in healthy volunteers.

PubMed

Jhee, Ok Hwa; Lee, Min Ho; Shaw, Leslie M; Lee, Seo Eun; Park, Jin Hee; Kang, Ju Seop

2007-01-01

The aims of this study were to assess the pharmacokinetics and bioequivalence of two brands of loxoprofen (CAS 80832-23-6) 60 mg tablets in healthy male volunteers. The several pharmacokinetic parameters were evaluated after an oral administration after an overnight fast according to a single dose, two-sequence, and cross-over randomized design with a 1-week washout interval. Serial blood samples were collected throughout 10 h after administration of the reference and test drug. Plasma was analyzed by validated HPLC with UV detection. Several pharmacokinetic parameters, including AUC(infnity), AUC(t), C(max), T(max), T1/2, and Ke were determined from blood concentrations of both formulations. AUC(t), AUC(infinity) and C(max) were evaluated for bioequivalence after log-transformation of data using ANOVA with 90% confidence interval level. The parametric 90% confidence intervals of AUC(t), AUC(infinity), and C(max) were 90.13-106.34%, 91.43-106.94%, and 91.17-108.53%, respectively. All of the tested parameters were within the acceptable range of 80-125%. Based on these statistical considerations, it was concluded that the test drug was bioequivalent to the reference drug.

A Comparison of Seyfert 1 and 2 Host Galaxies

NASA Astrophysics Data System (ADS)

De Robertis, M.; Virani, S.

2000-12-01

Wide-field, R-band CCD data of 15 Seyfert 1 and 15 Seyfert 2 galaxies taken from the CfA survey were analysed in order to compare the properties of their host galaxies. As well, B-band images for a subset of 12 Seyfert 1s and 7 Seyfert 2s were acquired and analysed in the same way. A robust technique for decomposing the three components---nucleus, bulge and disk---was developed in order determine the structural parameters for each galaxy. In effect, the nuclear contribution was removed empirically by using a spatially nearby, high signal-to-noise ratio point source as a template. Profile fits to the bulge+disk ignored data within three seeing disks of the nucleus. Of the many parameters that were compared between Seyfert 1s and 2s, only two distributions differed at greater than the 95% confidence level for the K-S test: the magnitude of the nuclear component, and the radial color gradient outside the nucleus. The former is expected. The latter could be consistent with some proposed evolutionary models. There is some suggestion that other parameters may differ, but at a lower confidence level.

CONSTRAINTS ON SCALAR AND TENSOR PERTURBATIONS IN PHENOMENOLOGICAL AND TWO-FIELD INFLATION MODELS: BAYESIAN EVIDENCES FOR PRIMORDIAL ISOCURVATURE AND TENSOR MODES

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

Vaeliviita, Jussi; Savelainen, Matti; Talvitie, Marianne

2012-07-10

We constrain cosmological models where the primordial perturbations have an adiabatic and a (possibly correlated) cold dark matter (CDM) or baryon isocurvature component. We use both a phenomenological approach, where the power spectra of primordial perturbations are parameterized with amplitudes and spectral indices, and a slow-roll two-field inflation approach where slow-roll parameters are used as primary parameters, determining the spectral indices and the tensor-to-scalar ratio. In the phenomenological case, with CMB data, the upper limit to the CDM isocurvature fraction is {alpha} < 6.4% at k = 0.002 Mpc{sup -1} and 15.4% at k = 0.01 Mpc{sup -1}. The non-adiabaticmore » contribution to the CMB temperature variance is -0.030 < {alpha}{sub T} < 0.049 at the 95% confidence level. Including the supernova (SN) (or large-scale structure) data, these limits become {alpha} < 7.0%, 13.7%, and -0.048 < {alpha}{sub T} < 0.042 (or {alpha} < 10.2%, 16.0%, and -0.071 < {alpha}{sub T} < 0.024). The CMB constraint on the tensor-to-scalar ratio, r < 0.26 at k = 0.01 Mpc{sup -1}, is not affected by the non-adiabatic modes. In the slow-roll two-field inflation approach, the spectral indices are constrained close to 1. This leads to tighter limits on the isocurvature fraction; with the CMB data {alpha} < 2.6% at k = 0.01 Mpc{sup -1}, but the constraint on {alpha}{sub T} is not much affected, -0.058 < {alpha}{sub T} < 0.045. Including SN (or LSS) data, these limits become {alpha} < 3.2% and -0.056 < {alpha}{sub T} < 0.030 (or {alpha} < 3.4% and -0.063 < {alpha}{sub T} < -0.008). In addition to the generally correlated models, we study also special cases where the adiabatic and isocurvature modes are uncorrelated or fully (anti)correlated. We calculate Bayesian evidences (model probabilities) in 21 different non-adiabatic cases and compare them to the corresponding adiabatic models, and find that in all cases the data support the pure adiabatic model.« less

Restructuring Schools To Be Math Friendly to Females.

ERIC Educational Resources Information Center

Karp, Karen; Shakeshaft, Charol

1997-01-01

The gender gap in math Scholastic Aptitude Test scores, attributable to course avoidance, lack of confidence, and unbalanced classroom instruction, can have serious consequences for young women, such as limited university selection, limited career choices, and lower lifetime salaries. Solutions include hiring math specialists, establishing role…

Species limits, phylogeography and reproductive mode in the Metarhizium anisopliae complex

USDA-ARS?s Scientific Manuscript database

An essential first step toward understanding the ecology and life histories of Metarhizium anisopliae-group species as entomopathogens, endophytes and soil-adapted fungi is the ability to accurately define species limits and confidently infer a species tree. Here we present a multilocus phylogeny of...

Amnioinfusion for meconium-stained liquor in labour.

PubMed

Hofmeyr, G J

2000-01-01

Amnioinfusion aims to prevent or relieve umbilical cord compression during labour by infusing a solution into the uterine cavity. It is also thought to dilute meconium when present in the amniotic fluid and so reduce the risk of meconium aspiration. However it may be that the mechanism of effect is that it corrects oligohydramnios (reduced amniotic fluid), for which thick meconium staining is a marker. The objective of this review was to assess the effects of amnioinfusion for meconium-stained liquor on perinatal outcome. The Cochrane Pregnancy and Childbirth Group trials register and the Cochrane Controlled Trials Register were searched. Randomised trials comparing amnioinfusion with no amnioinfusion for women in labour with moderate or thick meconium-staining of the amniotic fluid. Eligibility and trial quality were assessed by one reviewer. Ten studies, most involving small numbers of participants, were included. Under standard perinatal surveillance, amnioinfusion was associated with a reduction in the following: heavy meconium staining of the liquor (relative risk 0.03, 95% confidence interval 0.01 to 0.15); variable fetal heart rate deceleration (relative risk 0.47, 95% confidence interval 0.24 to 0. 90); and a trend to reduced caesarean section overall (relative risk 0.83, 95% confidence interval 0.69 to 1.00). No perinatal deaths were reported. Under limited perinatal surveillance, amnioinfusion was associated with a reduction in the following: meconium aspiration syndrome (relative risk 0.24, 95% confidence interval 0. 12 to 0.48); neonatal hypoxic ischaemic encephalopathy (relative risk 0.07, 95% confidence interval 0.01 to 0.56) and neonatal ventilation or intensive care unit admission (relative risk 0.56, 95% confidence interval 0.39 to 0.79); there was a trend towards reduced perinatal mortality (relative risk 0.34, 95% confidence interval 0.11 to 1.06). Amnioinfusion is associated with improvements in perinatal outcome, particularly in settings where facilities for perinatal surveillance are limited. The trials reviewed are too small to address the possibility of rare but serious maternal adverse effects of amnioinfusion.

Amnioinfusion for meconium-stained liquor in labour.

PubMed

Hofmeyr, G J

2002-01-01

Amnioinfusion aims to prevent or relieve umbilical cord compression during labour by infusing a solution into the uterine cavity. It is also thought to dilute meconium when present in the amniotic fluid and so reduce the risk of meconium aspiration. However, it may be that the mechanism of effect is that it corrects oligohydramnios (reduced amniotic fluid), for which thick meconium staining is a marker. The objective of this review was to assess the effects of amnioinfusion for meconium-stained liquor on perinatal outcome. The Cochrane Pregnancy and Childbirth Group trials register (October 2001) and the Cochrane Controlled Trials Register (Issue 3, 2001) were searched. Randomised trials comparing amnioinfusion with no amnioinfusion for women in labour with moderate or thick meconium-staining of the amniotic fluid. Eligibility and trial quality were assessed by one reviewer. Twelve studies, most involving small numbers of participants, were included. Under standard perinatal surveillance, amnioinfusion was associated with a reduction in the following: heavy meconium staining of the liquor (relative risk 0.03, 95% confidence interval 0.01 to 0.15); variable fetal heart rate deceleration (relative risk 0.65, 95% confidence interval 0.49 to 0.88); and reduced caesarean section overall (relative risk 0.82, 95% confidence interval 0.69 to 1.97). No perinatal deaths were reported. Under limited perinatal surveillance, amnioinfusion was associated with a reduction in the following: meconium aspiration syndrome (relative risk 0.24, 95% confidence interval 0.12 to 0.48); neonatal hypoxic ischaemic encephalopathy (relative risk 0.07, 95% confidence interval 0.01 to 0.56) and neonatal ventilation or intensive care unit admission (relative risk 0.56, 95% confidence interval 0.39 to 0.79); there was a trend towards reduced perinatal mortality (relative risk 0.34, 95% confidence interval 0.11 to 1.06). Amnioinfusion is associated with improvements in perinatal outcome, particularly in settings where facilities for perinatal surveillance are limited. The trials reviewed are too small to address the possibility of rare but serious maternal adverse effects of amnioinfusion.

Analysis of convergence of an evolutionary algorithm with self-adaptation using a stochastic Lyapunov function.

PubMed

Semenov, Mikhail A; Terkel, Dmitri A

2003-01-01

This paper analyses the convergence of evolutionary algorithms using a technique which is based on a stochastic Lyapunov function and developed within the martingale theory. This technique is used to investigate the convergence of a simple evolutionary algorithm with self-adaptation, which contains two types of parameters: fitness parameters, belonging to the domain of the objective function; and control parameters, responsible for the variation of fitness parameters. Although both parameters mutate randomly and independently, they converge to the "optimum" due to the direct (for fitness parameters) and indirect (for control parameters) selection. We show that the convergence velocity of the evolutionary algorithm with self-adaptation is asymptotically exponential, similar to the velocity of the optimal deterministic algorithm on the class of unimodal functions. Although some martingale inequalities have not be proved analytically, they have been numerically validated with 0.999 confidence using Monte-Carlo simulations.

The Colombian Awakening: President Alvaro Uribe’s Integrated Action Approach to Counterinsurgency

DTIC Science & Technology

2010-06-01

Colombia. Soon after taking office in 2002, Colombian President Alvaro Uribe developed the Democratic Security and Defense Policy to reinstate the rule...confidence to overcome poverty and inequality, and confidence in Colombia as full of possibilities rather than limitations. -- Alvaro Uribe An...which had been historically neglected by the government. Uribe’s Leadership There is no denying that Colombian President Alvaro Uribe is an

Inferring speaker attributes in adductor spasmodic dysphonia: ratings from unfamiliar listeners.

PubMed

Isetti, Derek; Xuereb, Linnea; Eadie, Tanya L

2014-05-01

To determine whether unfamiliar listeners' perceptions of speakers with adductor spasmodic dysphonia (ADSD) differ from control speakers on the parameters of relative age, confidence, tearfulness, and vocal effort and are related to speaker-rated vocal effort or voice-specific quality of life. Twenty speakers with ADSD (including 6 speakers with ADSD plus tremor) and 20 age- and sex-matched controls provided speech recordings, completed a voice-specific quality-of-life instrument (Voice Handicap Index; Jacobson et al., 1997), and rated their own vocal effort. Twenty listeners evaluated speech samples for relative age, confidence, tearfulness, and vocal effort using rating scales. Listeners judged speakers with ADSD as sounding significantly older, less confident, more tearful, and more effortful than control speakers (p < .01). Increased vocal effort was strongly associated with decreased speaker confidence (rs = .88-.89) and sounding more tearful (rs = .83-.85). Self-rated speaker effort was moderately related (rs = .45-.52) to listener impressions. Listeners' perceptions of confidence and tearfulness were also moderately associated with higher Voice Handicap Index scores (rs = .65-.70). Unfamiliar listeners judge speakers with ADSD more negatively than control speakers, with judgments extending beyond typical clinical measures. The results have implications for counseling and understanding the psychosocial effects of ADSD.

Search for narrow resonances in dilepton mass spectra in proton-proton collisions at √{ s} = 13 TeV and combination with 8 TeV data

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Sharma, A.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Nuttens, C.; Piotrzkowski, K.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Micanovic, S.; Sudic, L.; Susa, T.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Ellithi Kamel, A.; Mahmoud, M. A.; Radi, A.; Calpas, B.; Kadastik, M.; Murumaa, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Toriashvili, T.; Rurua, L.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulte, J. F.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Seitz, C.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Poehlsen, J.; Sander, C.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Barth, C.; Baus, C.; Berger, J.; Butz, E.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Katkov, I.; Lobelle Pardo, P.; Maier, B.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Bahinipati, S.; Choudhury, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Malhotra, S.; Naimuddin, M.; Nishu, N.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhowmik, S.; Dewanjee, R. K.; Ganguly, S.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Rane, A.; Sharma, S.; Behnamian, H.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Fahim, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Chiorboli, M.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; D'imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; 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.; Costa, M.; Cotto, G.; Covarelli, R.; Degano, A.; Demaria, N.; Finco, L.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Rotondo, F.; Ruspa, M.; Sacchi, R.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; La Licata, C.; Schizzi, A.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, S.; Lee, S. W.; Oh, Y. 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A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Rodrigues Antunes, J.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Vischia, P.; Belotelov, I.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Chtchipounov, L.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Murzin, V.; Oreshkin, V.; Sulimov, V.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Bylinkin, A.; Chadeeva, M.; Popova, E.; Tarkovskii, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Rusakov, S. V.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Blinov, V.; Skovpen, Y.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Barrio Luna, M.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Castiñeiras De Saa, J. R.; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. 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T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Yang, Y.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Tzeng, Y. M.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Bakirci, M. N.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Bilmis, S.; Isildak, B.; Karapinar, G.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, E. A.; Yetkin, T.; Cakir, A.; Cankocak, K.; Sen, S.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Barducci, D.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Nash, J.; Nikitenko, A.; Pela, J.; Penning, B.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Seez, C.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. 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I.; Shrinivas, A.; Si, W.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Holzner, A.; Klein, D.; Krutelyov, V.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mccoll, N.; Mullin, S. D.; Ovcharova, A.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Apresyan, A.; Bendavid, J.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Lawhorn, J. M.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Azzolini, V.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. 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F.; Sumorok, K.; Tatar, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bartek, R.; Bloom, K.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Malta Rodrigues, A.; Meier, F.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Baumgartel, D.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Hahn, K. A.; Kubik, A.; Kumar, A.; Low, J. F.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Medvedeva, T.; Mei, K.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Miller, D. H.; Neumeister, N.; Shi, X.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Agapitos, A.; Chou, J. P.; Contreras-Campana, E.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Nash, K.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; De Guio, F.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ojalvo, I.; Perry, T.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

2017-05-01

A search for narrow resonances in dielectron and dimuon invariant mass spectra has been performed using data obtained from proton-proton collisions at √{ s} = 13 TeV collected with the CMS detector. The integrated luminosity for the dielectron sample is 2.7 fb-1 and for the dimuon sample 2.9 fb-1. The sensitivity of the search is increased by combining these data with a previously analyzed set of data obtained at √{ s} = 8 TeV and corresponding to a luminosity of 20 fb-1. No evidence for non-standard-model physics is found, either in the 13 TeV data set alone, or in the combined data set. Upper limits on the product of production cross section and branching fraction have also been calculated in a model-independent manner to enable interpretation in models predicting a narrow dielectron or dimuon resonance structure. Limits are set on the masses of hypothetical particles that could appear in new-physics scenarios. For the ZSSM‧ particle, which arises in the sequential standard model, and for the superstring inspired Zψ‧ particle, 95% confidence level lower mass limits for the combined data sets and combined channels are found to be 3.37 and 2.82 TeV, respectively. The corresponding limits for the lightest Kaluza-Klein graviton arising in the Randall-Sundrum model of extra dimensions with coupling parameters 0.01 and 0.10 are 1.46 and 3.11 TeV, respectively. These results significantly exceed the limits based on the 8 TeV LHC data.