A comparison of multiple imputation methods for handling missing values in longitudinal data in the presence of a time-varying covariate with a non-linear association with time: a simulation study.

PubMed

De Silva, Anurika Priyanjali; Moreno-Betancur, Margarita; De Livera, Alysha Madhu; Lee, Katherine Jane; Simpson, Julie Anne

2017-07-25

Missing data is a common problem in epidemiological studies, and is particularly prominent in longitudinal data, which involve multiple waves of data collection. Traditional multiple imputation (MI) methods (fully conditional specification (FCS) and multivariate normal imputation (MVNI)) treat repeated measurements of the same time-dependent variable as just another 'distinct' variable for imputation and therefore do not make the most of the longitudinal structure of the data. Only a few studies have explored extensions to the standard approaches to account for the temporal structure of longitudinal data. One suggestion is the two-fold fully conditional specification (two-fold FCS) algorithm, which restricts the imputation of a time-dependent variable to time blocks where the imputation model includes measurements taken at the specified and adjacent times. To date, no study has investigated the performance of two-fold FCS and standard MI methods for handling missing data in a time-varying covariate with a non-linear trajectory over time - a commonly encountered scenario in epidemiological studies. We simulated 1000 datasets of 5000 individuals based on the Longitudinal Study of Australian Children (LSAC). Three missing data mechanisms: missing completely at random (MCAR), and a weak and a strong missing at random (MAR) scenarios were used to impose missingness on body mass index (BMI) for age z-scores; a continuous time-varying exposure variable with a non-linear trajectory over time. We evaluated the performance of FCS, MVNI, and two-fold FCS for handling up to 50% of missing data when assessing the association between childhood obesity and sleep problems. The standard two-fold FCS produced slightly more biased and less precise estimates than FCS and MVNI. We observed slight improvements in bias and precision when using a time window width of two for the two-fold FCS algorithm compared to the standard width of one. We recommend the use of FCS or MVNI in a similar longitudinal setting, and when encountering convergence issues due to a large number of time points or variables with missing values, the two-fold FCS with exploration of a suitable time window.

Missing, Abducted, Runaway, and Thrownaway Children in America. First Report: Numbers and Characteristics, National Incidence Studies. Executive Summary.

ERIC Educational Resources Information Center

Finkelhor, David; And Others

What has in the past been called the missing children problem is in reality a set of at least five distinct problems, each of which needs to be researched, analyzed, and treated separately. The problems are family abductions, nonfamily abductions, runaways, thrownaways, and lost, injured, or otherwise missing children. Many of the children in at…

Insufficient sleep rather than the apnea-hypopnea index can be associated with sleepiness-related driving problems of Japanese obstructive sleep apnea syndrome patients residing in metropolitan areas.

PubMed

Matsui, Kentaro; Sasai-Sakuma, Taeko; Ishigooka, Jun; Inoue, Yuichi

2017-05-01

Obstructive sleep apnea syndrome (OSAS) and insufficient sleep might increase the risk of drowsy driving and sleepiness-related vehicular accidents. This study retrospectively investigated the factors associated with these driving problems, particularly addressing OSAS severity and sleep amounts of affected drivers. This study examined 161 patients (146 male and 15 female) with OSAS (apnea-hypopnea index [AHI] ≥ 5) who drove on a routine basis and who completed study questionnaires. To investigate factors associated with drowsy driving during the prior year and sleepiness-related vehicular accidents or near-miss events during the prior five years, logistic regression analyses were performed with age, body mass index, monthly driving distance, habitual sleep duration on weekdays, the Japanese version of Epworth Sleepiness Scale score, AHI, and periodic limb movement index as independent variables. Of the patients, 68 (42.2%) reported drowsy driving experiences, and 86 (53.4%) reported sleepiness-related vehicular accidents or near-miss events. Analyses revealed the following: older age (46-65 years, ≥66 years) was negatively associated with drowsy driving (p <0.05, p <0.05), and habitually shorter sleep duration on weekdays (≤6 hours) was positively associated with drowsy driving (p <0.01). Habitual sleep duration of ≤6 hours (p <0.01) and Epworth Sleepiness Scale score of ≥11 (p <0.01) were positively associated with sleepiness-related vehicular accidents and near-miss events. However, AHI was not associated with these driving problems. Insufficient sleep, rather than severity of OSAS, was associated with sleepiness-related driving problems in these Japanese OSAS patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Model independent particle mass measurements in missing energy events at hadron colliders

NASA Astrophysics Data System (ADS)

Park, Myeonghun

2011-12-01

This dissertation describes several new kinematic methods to measure the masses of new particles in events with missing transverse energy at hadron colliders. Each method relies on the measurement of some feature (a peak or an endpoint) in the distribution of a suitable kinematic variable. The first method makes use of the "Gator" variable s min , whose peak provides a global and fully inclusive measure of the production scale of the new particles. In the early stage of the LHC, this variable can be used both as an estimator and a discriminator for new physics over the standard model backgrounds. The next method studies the invariant mass distributions of the visible decay products from a cascade decay chain and the shapes and endpoints of those distributions. Given a sufficient number of endpoint measurements, one could in principle attempt to invert and solve for the mass spectrum. However, the non-linear character of the relevant coupled quadratic equations often leads to multiple solutions. In addition, there is a combinatorial ambiguity related to the ordering of the decay products from the cascade decay chain. We propose a new set of invariant mass variables which are less sensitive to these problems. We demonstrate how the new particle mass spectrum can be extracted from the measurement of their kinematic endpoints. The remaining methods described in the dissertation are based on "transverse" invariant mass variables like the "Cambridge" transverse mass MT2, the "Sheffield" contrasverse mass MCT and their corresponding one-dimensional projections MT2⊥, M T2||, MCT⊥ , and MCT|| with respect to the upstream transverse momentum U⃗T . The main advantage of all those methods is that they can be applied to very short (single-stage) decay topologies, as well as to a subsystem of the observed event. The methods can also be generalized to the case of non-identical missing particles, as demonstrated in Chapter 7. A complete set of analytical results for the calculation of the relevant variables in each event, as well as the dependence of their endpoints on the underlying mass spectrum is given for each case. In some circumstances, the whole shape of the differential distribution can be theoretically predicted as well. The methods are illustrated with examples from supersymmetry and from top quark production in the standard model.

Measuring the Association Between Body Mass Index and All-Cause Mortality in the Presence of Missing Data: Analyses From the Scottish National Diabetes Register.

PubMed

Read, Stephanie H; Lewis, Steff C; Halbesma, Nynke; Wild, Sarah H

2017-04-15

Incorrectly handling missing data can lead to imprecise and biased estimates. We describe the effect of applying different approaches to handling missing data in an analysis of the association between body mass index and all-cause mortality among people with type 2 diabetes. We used data from the Scottish diabetes register that were linked to hospital admissions data and death registrations. The analysis was based on people diagnosed with type 2 diabetes between 2004 and 2011, with follow-up until May 31, 2014. The association between body mass index and mortality was investigated using Cox proportional hazards models. Findings were compared using 4 different missing-data methods: complete-case analysis, 2 multiple-imputation models, and nearest-neighbor imputation. There were 124,451 cases of type 2 diabetes, among which there were 17,085 deaths during 787,275 person-years of follow-up. Patients with missing data (24.8%) had higher mortality than those without missing data (adjusted hazard ratio = 1.36, 95% confidence interval: 1.31, 1.41). A U-shaped relationship between body mass index and mortality was observed, with the lowest hazard ratios occurring among moderately obese people, regardless of the chosen approach for handling missing data. Missing data may affect absolute and relative risk estimates differently and should be considered in analyses of routinely collected data. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Implications of Systematic Nominator Missingness for Peer Nomination Data

ERIC Educational Resources Information Center

Babcock, Ben; Marks, Peter E. L.; van den Berg, Yvonne H. M.; Cillessen, Antonius H. N.

2018-01-01

Missing data are a persistent problem in psychological research. Peer nomination data present a unique missing data problem, because a nominator's nonparticipation results in missing data for other individuals in the study. This study examined the range of effects of systematic nonparticipation on the correlations between peer nomination data when…

Accounting for undetected compounds in statistical analyses of mass spectrometry 'omic studies.

PubMed

Taylor, Sandra L; Leiserowitz, Gary S; Kim, Kyoungmi

2013-12-01

Mass spectrometry is an important high-throughput technique for profiling small molecular compounds in biological samples and is widely used to identify potential diagnostic and prognostic compounds associated with disease. Commonly, this data generated by mass spectrometry has many missing values resulting when a compound is absent from a sample or is present but at a concentration below the detection limit. Several strategies are available for statistically analyzing data with missing values. The accelerated failure time (AFT) model assumes all missing values result from censoring below a detection limit. Under a mixture model, missing values can result from a combination of censoring and the absence of a compound. We compare power and estimation of a mixture model to an AFT model. Based on simulated data, we found the AFT model to have greater power to detect differences in means and point mass proportions between groups. However, the AFT model yielded biased estimates with the bias increasing as the proportion of observations in the point mass increased while estimates were unbiased with the mixture model except if all missing observations came from censoring. These findings suggest using the AFT model for hypothesis testing and mixture model for estimation. We demonstrated this approach through application to glycomics data of serum samples from women with ovarian cancer and matched controls.

Longitudinal data analysis with non-ignorable missing data.

PubMed

Tseng, Chi-hong; Elashoff, Robert; Li, Ning; Li, Gang

2016-02-01

A common problem in the longitudinal data analysis is the missing data problem. Two types of missing patterns are generally considered in statistical literature: monotone and non-monotone missing data. Nonmonotone missing data occur when study participants intermittently miss scheduled visits, while monotone missing data can be from discontinued participation, loss to follow-up, and mortality. Although many novel statistical approaches have been developed to handle missing data in recent years, few methods are available to provide inferences to handle both types of missing data simultaneously. In this article, a latent random effects model is proposed to analyze longitudinal outcomes with both monotone and non-monotone missingness in the context of missing not at random. Another significant contribution of this article is to propose a new computational algorithm for latent random effects models. To reduce the computational burden of high-dimensional integration problem in latent random effects models, we develop a new computational algorithm that uses a new adaptive quadrature approach in conjunction with the Taylor series approximation for the likelihood function to simplify the E-step computation in the expectation-maximization algorithm. Simulation study is performed and the data from the scleroderma lung study are used to demonstrate the effectiveness of this method. © The Author(s) 2012.

Bulk stabilization, the extra-dimensional Higgs portal and missing energy in Higgs events

NASA Astrophysics Data System (ADS)

Diener, Ross; Burgess, C. P.

2013-05-01

To solve the hierarchy problem, extra-dimensional models must explain why the new dimensions stabilize to the right size, and the known mechanisms for doing so require bulk scalars that couple to the branes. Because of these couplings the energetics of dimensional stabilization competes with the energetics of the Higgs vacuum, with potentially observable effects. These effects are particularly strong for one or two extra dimensions because the bulk-Higgs couplings can then be super-renormalizable or dimensionless. Experimental reach for such extra-dimensional Higgs `portals' are stronger than for gravitational couplings because they are less suppressed at low-energies. We compute how Higgs-bulk coupling through such a portal with two extra dimensions back-reacts onto properties of the Higgs boson. When the KK mass is smaller than the Higgs mass, mixing with KK modes results in an invisible Higgs decay width, missing-energy signals at high-energy colliders, and new mechanisms of energy loss in stars and supernovae. Astrophysical bounds turn out to be complementary to collider measurements, with observable LHC signals allowed by existing constraints. We comment on the changes to the Higgs mass-coupling relationship caused by Higgs-bulk mixing, and how the resulting modifications to the running of Higgs couplings alter vacuum-stability and triviality bounds.

Estimation of Item Response Theory Parameters in the Presence of Missing Data

ERIC Educational Resources Information Center

Finch, Holmes

2008-01-01

Missing data are a common problem in a variety of measurement settings, including responses to items on both cognitive and affective assessments. Researchers have shown that such missing data may create problems in the estimation of item difficulty parameters in the Item Response Theory (IRT) context, particularly if they are ignored. At the same…

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

Jenkovszky, L. L., E-mail: jenk@bitp.kiev.ua; Kuprash, O. E., E-mail: oleg.kuprash@desy.de; Orava, R., E-mail: risto.orava@cern.ch

The cross sections for single and double diffraction dissociation at low missing masses are calculated for the LHC energies on the basis of the dual (Regge) model under the assumption of a dominant contribution of the exchange of the Pomeron Regge pole. The model reproduces the rich resonance structure in the region of low missing masses M{sub x}. Diffractively excited states lie on the nucleon trajectory M{sub x} supplemented with the isolated Roper resonance. Detailed predictions for the squared momentum transfer and missing-mass dependence of the differential and integrated single and double diffraction dissociation in the kinematical range of presentmore » and future LHC measurements are given.« less

Falling paper: Navier-Stokes solutions, model of fluid forces, and center of mass elevation.

PubMed

Pesavento, Umberto; Wang, Z Jane

2004-10-01

We investigate the problem of falling paper by solving the two dimensional Navier-Stokes equations subject to the motion of a free-falling body at Reynolds numbers around 10(3). The aerodynamic lift on a tumbling plate is found to be dominated by the product of linear and angular velocities rather than velocity squared, as appropriate for an airfoil. This coupling between translation and rotation provides a mechanism for a brief elevation of center of mass near the cusplike turning points. The Navier-Stokes solutions further provide the missing quantity in the classical theory of lift, the instantaneous circulation, and suggest a revised model for the fluid forces.

Treatment of Missing Data in Workforce Education Research

ERIC Educational Resources Information Center

Gemici, Sinan; Rojewski, Jay W.; Lee, In Heok

2012-01-01

Most quantitative analyses in workforce education are affected by missing data. Traditional approaches to remedy missing data problems often result in reduced statistical power and biased parameter estimates due to systematic differences between missing and observed values. This article examines the treatment of missing data in pertinent…

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a)(1) of this subpart... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a) of this subpart cannot... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a)(1) of this subpart... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a)(1) of this subpart... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a)(1) of this subpart... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data.

PubMed

Wei, Runmin; Wang, Jingye; Su, Mingming; Jia, Erik; Chen, Shaoqiu; Chen, Tianlu; Ni, Yan

2018-01-12

Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student's t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics ( https://metabolomics.cc.hawaii.edu/software/MetImp/ ).

A HUPO test sample study reveals common problems in mass spectrometry-based proteomics

PubMed Central

Bell, Alexander W.; Deutsch, Eric W.; Au, Catherine E.; Kearney, Robert E.; Beavis, Ron; Sechi, Salvatore; Nilsson, Tommy; Bergeron, John J.M.

2009-01-01

We carried out a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in LC-MS-based proteomics. We distributed a test sample consisting of an equimolar mix of 20 highly purified recombinant human proteins, to 27 laboratories for identification. Each protein contained one or more unique tryptic peptides of 1250 Da to also test for ion selection and sampling in the mass spectrometer. Of the 27 labs, initially only 7 labs reported all 20 proteins correctly, and only 1 lab reported all the tryptic peptides of 1250 Da. Nevertheless, a subsequent centralized analysis of the raw data revealed that all 20 proteins and most of the 1250 Da peptides had in fact been detected by all 27 labs. The centralized analysis allowed us to determine sources of problems encountered in the study, which include missed identifications (false negatives), environmental contamination, database matching, and curation of protein identifications. Improved search engines and databases are likely to increase the fidelity of mass spectrometry-based proteomics. PMID:19448641

Constraining the Mass of the Local Group through Proper Motion Measurements of Local Group Galaxies

NASA Astrophysics Data System (ADS)

Sohn, S. Tony; van der Marel, R.; Anderson, J.

2012-01-01

The Local Group and its two dominant spiral galaxies have been the benchmark for testing many aspects of cosmological and galaxy formation theories. This includes, e.g., dark halo profiles and shapes, substructure and the "missing satellite" problem, and the minimum mass for galaxy formation. But despite the extensive work in all of these areas, our knowledge of the mass of the Milky Way and M31, and thus the total mass of the Local Group remains one of the most poorly established astronomical parameters (uncertain by a factor of 4). One important reason for this problem is the lack of information in tangential motions of galaxies, which can be only obtained through proper motion measurements. In this study, we introduce our projects for measuring absolute proper motions of (1) the dwarf spheroidal galaxy Leo I, (2) M31, and (3) the 4 dwarf galaxies near the edge of the Local Group (Cetus, Leo A, Tucana, and Sag DIG). Results from these three independent measurements will provide important clues to the mass of the Milky Way, M31, and the Local Group as a whole, respectively. We also present our proper motion measurement technique that uses compact background galaxies as astrometric reference sources.

Deconstructed transverse mass variables

DOE PAGES

Ismail, Ahmed; Schwienhorst, Reinhard; Virzi, Joseph S.; ...

2015-04-02

Traditional searches for R-parity conserving natural supersymmetry (SUSY) require large transverse mass and missing energy cuts to separate the signal from large backgrounds. SUSY models with compressed spectra inherently produce signal events with small amounts of missing energy that are hard to explore. We use this difficulty to motivate the construction of "deconstructed" transverse mass variables which are designed preserve information on both the norm and direction of the missing momentum. Here, we demonstrate the effectiveness of these variables in searches for the pair production of supersymmetric top-quark partners which subsequently decay into a final state with an isolated lepton,more » jets and missing energy. We show that the use of deconstructed transverse mass variables extends the accessible compressed spectra parameter space beyond the region probed by traditional methods. The parameter space can further be expanded to neutralino masses that are larger than the difference between the stop and top masses. In addition, we also discuss how these variables allow for novel searches of single stop production, in order to directly probe unconstrained stealth stops in the small stop-and neutralino-mass regime. We also demonstrate the utility of these variables for generic gluino and stop searches in all-hadronic final states. Overall, we demonstrate that deconstructed transverse variables are essential to any search wanting to maximize signal separation from the background when the signal has undetected particles in the final state.« less

40 CFR 75.70 - NOX mass emissions provisions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... applicable quality assurance requirements of those appendices. (f) Missing data procedures. Except as... owner or operator using a continuous emissions monitoring system, substitute for missing data in accordance with the applicable missing data procedures in §§ 75.31 through 75.37 whenever the unit combusts...

40 CFR 75.70 - NOX mass emissions provisions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... applicable quality assurance requirements of those appendices. (f) Missing data procedures. Except as... owner or operator using a continuous emissions monitoring system, substitute for missing data in accordance with the applicable missing data procedures in §§ 75.31 through 75.37 whenever the unit combusts...

40 CFR 75.70 - NOX mass emissions provisions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... applicable quality assurance requirements of those appendices. (f) Missing data procedures. Except as... owner or operator using a continuous emissions monitoring system, substitute for missing data in accordance with the applicable missing data procedures in §§ 75.31 through 75.37 whenever the unit combusts...

Mass

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

Quigg, Chris

2007-12-05

In the classical physics we inherited from Isaac Newton, mass does not arise, it simply is. The mass of a classical object is the sum of the masses of its parts. Albert Einstein showed that the mass of a body is a measure of its energy content, inviting us to consider the origins of mass. The protons we accelerate at Fermilab are prime examples of Einsteinian matter: nearly all of their mass arises from stored energy. Missing mass led to the discovery of the noble gases, and a new form of missing mass leads us to the notion of darkmore » matter. Starting with a brief guided tour of the meanings of mass, the colloquium will explore the multiple origins of mass. We will see how far we have come toward understanding mass, and survey the issues that guide our research today.« less

Remedial Sheets for Progress Checks, Segments 19-40.

ERIC Educational Resources Information Center

New York Inst. of Tech., Old Westbury.

The second part of the Self-Paced Physics Course remediation materials is presented for U. S. Naval Academy students who miss core problems on the progress check. The total of 101 problems is incorporated in this volume to match study segments 19 through 40. Each remedial sheet is composed of a statement of the missed problem and references to…

Silver Alerts and the Problem of Missing Adults with Dementia

ERIC Educational Resources Information Center

Carr, Dawn; Muschert, Glenn W.; Kinney, Jennifer; Robbins, Emily; Petonito, Gina; Manning, Lydia; Brown, J. Scott

2010-01-01

In the months following the introduction of the National AMBER (America's Missing: Broadcast Emergency Response) Alert plan used to locate missing and abducted children, Silver Alert programs began to emerge. These programs use the same infrastructure and approach to find a different missing population, cognitively impaired older adults. By late…

Decoding the Effect of Isobaric Substitutions on Identifying Missing Proteins and Variant Peptides in Human Proteome.

PubMed

Choong, Wai-Kok; Lih, Tung-Shing Mamie; Chen, Yu-Ju; Sung, Ting-Yi

2017-12-01

To confirm the existence of missing proteins, we need to identify at least two unique peptides with length of 9-40 amino acids of a missing protein in bottom-up mass-spectrometry-based proteomic experiments. However, an identified unique peptide of the missing protein, even identified with high level of confidence, could possibly coincide with a peptide of a commonly observed protein due to isobaric substitutions, mass modifications, alternative splice isoforms, or single amino acid variants (SAAVs). Besides unique peptides of missing proteins, identified variant peptides (SAAV-containing peptides) could also alternatively map to peptides of other proteins due to the aforementioned issues. Therefore, we conducted a thorough comparative analysis on data sets in PeptideAtlas Tiered Human Integrated Search Proteome (THISP, 2017-03 release), including neXtProt (2017-01 release), to systematically investigate the possibility of unique peptides in missing proteins (PE2-4), unique peptides in dubious proteins, and variant peptides affected by isobaric substitutions, causing doubtful identification results. In this study, we considered 11 isobaric substitutions. From our analysis, we found <5% of the unique peptides of missing proteins and >6% of variant peptides became shared with peptides of PE1 proteins after isobaric substitutions.

A Cautious Note on Auxiliary Variables That Can Increase Bias in Missing Data Problems.

PubMed

Thoemmes, Felix; Rose, Norman

2014-01-01

The treatment of missing data in the social sciences has changed tremendously during the last decade. Modern missing data techniques such as multiple imputation and full-information maximum likelihood are used much more frequently. These methods assume that data are missing at random. One very common approach to increase the likelihood that missing at random is achieved consists of including many covariates as so-called auxiliary variables. These variables are either included based on data considerations or in an inclusive fashion; that is, taking all available auxiliary variables. In this article, we point out that there are some instances in which auxiliary variables exhibit the surprising property of increasing bias in missing data problems. In a series of focused simulation studies, we highlight some situations in which this type of biasing behavior can occur. We briefly discuss possible ways how one can avoid selecting bias-inducing covariates as auxiliary variables.

Multiple Imputation for Multivariate Missing-Data Problems: A Data Analyst's Perspective.

ERIC Educational Resources Information Center

Schafer, Joseph L.; Olsen, Maren K.

1998-01-01

The key ideas of multiple imputation for multivariate missing data problems are reviewed. Software programs available for this analysis are described, and their use is illustrated with data from the Adolescent Alcohol Prevention Trial (W. Hansen and J. Graham, 1991). (SLD)

A Review On Missing Value Estimation Using Imputation Algorithm

NASA Astrophysics Data System (ADS)

Armina, Roslan; Zain, Azlan Mohd; Azizah Ali, Nor; Sallehuddin, Roselina

2017-09-01

The presence of the missing value in the data set has always been a major problem for precise prediction. The method for imputing missing value needs to minimize the effect of incomplete data sets for the prediction model. Many algorithms have been proposed for countermeasure of missing value problem. In this review, we provide a comprehensive analysis of existing imputation algorithm, focusing on the technique used and the implementation of global or local information of data sets for missing value estimation. In addition validation method for imputation result and way to measure the performance of imputation algorithm also described. The objective of this review is to highlight possible improvement on existing method and it is hoped that this review gives reader better understanding of imputation method trend.

Observation of shape isomers states in fission fragments

NASA Astrophysics Data System (ADS)

Kamanin, D. V.; Pyatkov, Yu V.; Alexandrov, A. A.; Alexandrova, I. A.; Mkaza, N.; Malaza, V.; Kuznetsova, E. A.; Strekalovsky, A. O.; Strekalovsky, O. V.; Zhuchko, V. E.

2017-06-01

We discuss the manifestations of a new original effect appeared at crossing of the metal foils by fission fragments. We have observed significant mass deficit in the total mass Ms of the fission fragments detected in coincidence with ions knocked out from the foil. It was shown that at the large angles of scattering of the knocked-out ions from the foil predominantly conventional elastic Rutherford scattering takes place. As the result Ms corresponds to the mean mass of the mother system after emission of fission neutrons (no missing mass). In contrast, in near frontal impacts fission fragment misses essential part of its mass. Residual nuclei at least for the fragments from the heavy mass peak show magic nucleon composition.

A Review of Missing Data Handling Methods in Education Research

ERIC Educational Resources Information Center

Cheema, Jehanzeb R.

2014-01-01

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…

Effects of Modified Schema-Based Instruction on Real-World Algebra Problem Solving of Students with Autism Spectrum Disorder and Moderate Intellectual Disability

ERIC Educational Resources Information Center

Root, Jenny Rose

2016-01-01

The current study evaluated the effects of modified schema-based instruction (SBI) on the algebra problem solving skills of three middle school students with autism spectrum disorder and moderate intellectual disability (ASD/ID). Participants learned to solve two types of group word problems: missing-whole and missing-part. The themes of the word…

Combination of Multiple Spectral Libraries Improves the Current Search Methods Used to Identify Missing Proteins in the Chromosome-Centric Human Proteome Project.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Kim, Kwang-Youl; Kwon, Kyung-Hoon; Yoo, Jong Shin; Omenn, Gilbert S; Baker, Mark S; Hancock, William S; Paik, Young-Ki

2015-12-04

Approximately 2.9 billion long base-pair human reference genome sequences are known to encode some 20 000 representative proteins. However, 3000 proteins, that is, ~15% of all proteins, have no or very weak proteomic evidence and are still missing. Missing proteins may be present in rare samples in very low abundance or be only temporarily expressed, causing problems in their detection and protein profiling. In particular, some technical limitations cause missing proteins to remain unassigned. For example, current mass spectrometry techniques have high limits and error rates for the detection of complex biological samples. An insufficient proteome coverage in a reference sequence database and spectral library also raises major issues. Thus, the development of a better strategy that results in greater sensitivity and accuracy in the search for missing proteins is necessary. To this end, we used a new strategy, which combines a reference spectral library search and a simulated spectral library search, to identify missing proteins. We built the human iRefSPL, which contains the original human reference spectral library and additional peptide sequence-spectrum match entries from other species. We also constructed the human simSPL, which contains the simulated spectra of 173 907 human tryptic peptides determined by MassAnalyzer (version 2.3.1). To prove the enhanced analytical performance of the combination of the human iRefSPL and simSPL methods for the identification of missing proteins, we attempted to reanalyze the placental tissue data set (PXD000754). The data from each experiment were analyzed using PeptideProphet, and the results were combined using iProphet. For the quality control, we applied the class-specific false-discovery rate filtering method. All of the results were filtered at a false-discovery rate of <1% at the peptide and protein levels. The quality-controlled results were then cross-checked with the neXtProt DB (2014-09-19 release). The two spectral libraries, iRefSPL and simSPL, were designed to ensure no overlap of the proteome coverage. They were shown to be complementary to spectral library searching and significantly increased the number of matches. From this trial, 12 new missing proteins were identified that passed the following criterion: at least 2 peptides of 7 or more amino acids in length or one of 9 or more amino acids in length with one or more unique sequences. Thus, the iRefSPL and simSPL combination can be used to help identify peptides that have not been detected by conventional sequence database searches with improved sensitivity and a low error rate.

A two-tiered correlation of dark matter with missing transverse energy: reconstructing the lightest supersymmetric particle mass at the LHC

NASA Astrophysics Data System (ADS)

Li, Tianjun; Maxin, James A.; Nanopoulos, Dimitri V.; Walker, Joel W.

2012-02-01

We suggest that non-trivial correlations between the dark matter particle mass and collider based probes of missing transverse energy H_{text{T}}^{text{miss}} may facilitate a two tiered approach to the initial discovery of supersymmetry and the subsequent reconstruction of the lightest supersymmetric particle (LSP) mass at the LHC. These correlations are demonstrated via extensive Monte Carlo simulation of seventeen benchmark models, each sampled at five distinct LHC center-of-mass beam energies, spanning the parameter space of No-Scale mathcal{F} -SU(5). This construction is defined in turn by the union of the mathcal{F} -lipped SU(5) Grand Unified Theory, two pairs of hypothetical TeV scale vector-like supersymmetric multiplets with origins in mathcal{F} -theory, and the dynamically established boundary conditions of No-Scale Supergravity. In addition, we consider a control sample comprised of a standard minimal Supergravity benchmark point. Led by a striking similarity between the H_{text{T}}^{text{miss}} distribution and the familiar power spectrum of a black body radiator at various temperatures, we implement a broad empirical fit of our simulation against a Poisson distribution ansätz. We advance the resulting fit as a theoretical blueprint for deducing the mass of the LSP, utilizing only the missing transverse energy in a statistical sampling of ≥ 9 jet events. Cumulative uncertainties central to the method subsist at a satisfactory 12-15% level. The fact that supersymmetric particle spectrum of No-Scale mathcal{F} -SU(5) has thrived the withering onslaught of early LHC data that is steadily decimating the Constrained Minimal Supersymmetric Standard Model and minimal Supergravity parameter spaces is a prime motivation for augmenting more conventional LSP search methodologies with the presently proposed alternative.

The Missing Curriculum in Physics Problem-Solving Education

NASA Astrophysics Data System (ADS)

Williams, Mobolaji

2018-05-01

Physics is often seen as an excellent introduction to science because it allows students to learn not only the laws governing the world around them, but also, through the problems students solve, a way of thinking which is conducive to solving problems outside of physics and even outside of science. In this article, we contest this latter idea and argue that in physics classes, students do not learn widely applicable problem-solving skills because physics education almost exclusively requires students to solve well-defined problems rather than the less-defined problems which better model problem solving outside of a formal class. Using personal, constructed, and the historical accounts of Schrödinger's development of the wave equation and Feynman's development of path integrals, we argue that what is missing in problem-solving education is practice in identifying gaps in knowledge and in framing these knowledge gaps as questions of the kind answerable using techniques students have learned. We discuss why these elements are typically not taught as part of the problem-solving curriculum and end with suggestions on how to incorporate these missing elements into physics classes.

40 CFR 98.176 - Data reporting requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... weight of gaseous fuels. (5) If you used the missing data procedures in § 98.175(b), you must report how the monthly mass for each process input or output with missing data was determined and the number of months the missing data procedures were used. (f) If you used the site-specific emission factor method in...

40 CFR 98.176 - Data reporting requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... weight of gaseous fuels. (5) If you used the missing data procedures in § 98.175(b), you must report how the monthly mass for each process input or output with missing data was determined and the number of months the missing data procedures were used. (f) If you used the site-specific emission factor method in...

40 CFR 98.176 - Data reporting requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... weight of gaseous fuels. (5) If you used the missing data procedures in § 98.175(b), you must report how the monthly mass for each process input or output with missing data was determined and the number of months the missing data procedures were used. (f) If you used the site-specific emission factor method in...

Consent process for US-based family reference DNA samples.

PubMed

Katsanis, Sara H; Snyder, Lindsey; Arnholt, Kelly; Mundorff, Amy Z

2018-01-01

DNA collection from family members of the missing is a tenet for missing persons' and mass fatality investigations. Procedures for consenting family members are disparate, depending on the context supporting the reason for sample collection. While guidelines and best practices have been developed for handling mass fatalities and for identification of the missing, these guidelines do not address standard consent practices for living family members of potential victims. We examined the relevant U.S. laws, international guidelines and best practices, sampled consent forms currently used for DNA collection of family members, and drafted model language for a consent form to communicate the required and recommended information. We modeled the consent form on biobank consenting practices and tested the consent language among students and the general population for constructive feedback and readability. We also asked respondents to consider the options for DNA collection and either hypothetically agree or disagree. The model language presented here highlights information important to relay in consent processes and can serve as a foundation for future consent practices in mass fatalities and missing persons' investigations. Copyright © 2017 Elsevier B.V. All rights reserved.

40 CFR 98.445 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... quantities calculations is required. Whenever the monitoring procedures cannot be followed, you must use the...) A quarterly mass or volume of contents in containers received that is missing must be estimated as...

40 CFR 98.445 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... quantities calculations is required. Whenever the monitoring procedures cannot be followed, you must use the...) A quarterly mass or volume of contents in containers received that is missing must be estimated as...

40 CFR 98.445 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... quantities calculations is required. Whenever the monitoring procedures cannot be followed, you must use the...) A quarterly mass or volume of contents in containers received that is missing must be estimated as...

Searching for the missing baryons in clusters

PubMed Central

Rasheed, Bilhuda; Bahcall, Neta; Bode, Paul

2011-01-01

Observations of clusters of galaxies suggest that they contain fewer baryons (gas plus stars) than the cosmic baryon fraction. This “missing baryon” puzzle is especially surprising for the most massive clusters, which are expected to be representative of the cosmic matter content of the universe (baryons and dark matter). Here we show that the baryons may not actually be missing from clusters, but rather are extended to larger radii than typically observed. The baryon deficiency is typically observed in the central regions of clusters (∼0.5 the virial radius). However, the observed gas-density profile is significantly shallower than the mass-density profile, implying that the gas is more extended than the mass and that the gas fraction increases with radius. We use the observed density profiles of gas and mass in clusters to extrapolate the measured baryon fraction as a function of radius and as a function of cluster mass. We find that the baryon fraction reaches the cosmic value near the virial radius for all groups and clusters above . This suggests that the baryons are not missing, they are simply located in cluster outskirts. Heating processes (such as shock-heating of the intracluster gas, supernovae, and Active Galactic Nuclei feedback) likely contribute to this expanded distribution. Upcoming observations should be able to detect these baryons. PMID:21321229

Suspended Education in Massachusetts: Using Days of Lost Instruction Due to Suspension to Evaluate Our Schools

ERIC Educational Resources Information Center

Losen, Daniel J.; Sun, Wei-Ling; Keith, Michael A., II

2017-01-01

Missed instruction can have a devastating impact on educational outcomes. Some reasons for missed instruction are beyond the control of schools and districts: some students miss school due to mental or physical illness or injury, and transportation problems sometimes are to blame. One major reason for missed instruction that schools can directly…

The continuing problem of missed test results in an integrated health system with an advanced electronic medical record.

PubMed

Wahls, Terry; Haugen, Thomas; Cram, Peter

2007-08-01

Missed results can cause needless treatment delays. However, there is little data about the magnitude of this problem and the systems that clinics use to manage test results. Surveys about potential problems related to test results management were developed and administered to clinical staff in a regional Veterans Administration (VA) health care network. The provider survey, conducted four times between May 2005 and October 2006, sampling VA staff physicians, physician assistants, nurse practitioners, and internal medicine trainees, asked questions about the frequency of missed results and diagnosis or treatment delays seen in the antecedent two weeks in their clinics, or if a trainee, the antecedent month. Clinical staff survey response rate was 39% (143 of 370), with 40% using standard operating procedures to manage test results. Forty-four percent routinely reported all results to patients. The provider survey response rate was 50% (441 of 884) overall, with responses often (37% overall; range 29% to 46%) indicating they had seen patients with diagnosis or treatment delays attributed to a missed result; 15% reported two or more such encounters. Even in an integrated health system with an advanced electronic medical record, missed test results and associated diagnosis or treatment delays are common. Additional study and measures of missed results and associated treatment delays are needed.

Are We Really Missing Small Galaxies?

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2018-02-01

One long-standing astrophysical puzzle is that of so-called missing dwarf galaxies: the number of small dwarf galaxies that we observe is far fewer than that predicted by theory. New simulations, however, suggest that perhaps theres no mystery after all.Missing DwarfsDark-matter cosmological simulations predict many small galaxy halos for every large halo that forms. [The Via Lactea project]Models of a lambda-cold-dark-matter (CDM) universe predict the distribution of galaxy halo sizes throughout the universe, suggesting there should be many more small galaxies than large ones. In what has become known as the missing dwarf problem, however, we find that while we observe the expected numbers of galaxies at the larger end of the scale, we dont see nearly enough small galaxies to match the predictions.Are these galaxies actually missing? Are our predictions wrong? Or are the galaxies there and were just not spotting them? A recent study led by Alyson Brooks (Rutgers University) uses new simulations to explore whatscausing the difference between theory and observation.The fraction of detectable halos as a function of velocity, according to the authors simulations. Below 35 km/s, the detectability of the galaxies drops precipitously. [Brooks et al. 2017]Simulating Galactic VelocitiesBecause we cant weigh a galaxy directly, one proxy used for galaxy mass is its circular velocity; the more massive a galaxy, the faster gas and stars rotate around its center. The discrepancy between models and observations lies in whats known as the galaxy velocity function, which describes the number density of galaxies for a given circular velocity. While theory and observations agree for galaxies with circular velocities above 100 km/s, theory predicts far more dwarfs below this velocity than we observe.To investigate this problem, Brooks and collaborators ran a series of cosmological simulations based on our understanding of a CDM universe. Instead of exploring the result using only dark matter, however, the team included baryons in their simulations. They then produced mock observations of the resulting galaxy velocities to see what an observed velocity function would look like for their simulated galaxies.No Problem After All?Comparison of theoretical velocity functions to observations. The black dashed line shows the original, dark-matter-only model predictions; the black solid line includes the effects of detectability. Blue lines show the authors new model, including the effects of detectability and inclusion of baryons. The red and teal data points from observations match this corrected model well. [Brooks et al. 2017]Based on their baryon-inclusive simulations, Brooks and collaborators argue that there are two main factors that have contributed to the seeming theory/observation mismatch of the missing dwarf problem:Galaxies with low velocities arent detectable by our current surveys.The authors found that the detectable fraction of their simulated galaxies plunges as soon as galaxy velocity drops below 35 km/s. They conclude that were probably unable to see a large fraction of the smallest galaxies.Were not correctly inferring the circular velocity of the galaxies.Circular velocity is usually measured by looking at the line width of a gas tracer like HI. The authors find that this doesnt trace the full potential wells of the dwarf galaxies, however, resulting in an incorrect interpretation of their velocities.The authors show that the inclusion of these effects in the theoretical model significantly changes the predicted shape of the galaxy velocity function. This new function beautifully matches observations, neatly eliminating the missing dwarf problem. Perhaps this long-standing mystery has been a problem of interpretation all along!CitationAlyson M. Brooks et al 2017 ApJ 850 97. doi:10.3847/1538-4357/aa9576

Methods for Handling Missing Secondary Respondent Data

ERIC Educational Resources Information Center

Young, Rebekah; Johnson, David

2013-01-01

Secondary respondent data are underutilized because researchers avoid using these data in the presence of substantial missing data. The authors reviewed, evaluated, and tested solutions to this problem. Five strategies of dealing with missing partner data were reviewed: (a) complete case analysis, (b) inverse probability weighting, (c) correction…

Why Missing Data Matter in the Longitudinal Study of Adolescent Development: Using the 4-H Study to Understand the Uses of Different Missing Data Methods

ERIC Educational Resources Information Center

Jelicic, Helena; Phelps, Erin; Lerner, Richard M.

2010-01-01

The study of adolescent development rests on methodologically appropriate collection and interpretation of longitudinal data. While all longitudinal studies of adolescent development involve missing data, the methods to treat missingness that have been recommended most often focus on missing data from cross-sectional studies. The problems of…

Search for supersymmetry in events with photons and missing transverse energy in pp collisions at 13 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.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Waltenberger, W.; Wulz, C.-E.; 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.; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; 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.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Albert, A.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; 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.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; 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.; Kumari, P.; 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. 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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.; 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.; 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.; 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.; 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, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Kim, H.; Brochero Cifuentes, J. A.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, B.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Lee, H.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Goh, J.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; 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.; Zolkapli, Z.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Magaña Villalba, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Carpinteyro, S.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; 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. 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V.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Blinov, V.; Skovpen, Y.; 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. 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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.; Zucchetta, A.; 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.; Adiguzel, A.; Bakirci, M. N.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Eskut, E.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; 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.; 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. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Berry, E.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Breto, G.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Florent, A.; Hauser, J.; Ignatenko, M.; Saltzberg, D.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Si, W.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Holzner, A.; Klein, D.; Krutelyov, V.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; 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. T.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; 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.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Diamond, B.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Santra, A.; Weinberg, M.; 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.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Jung, K.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Turner, P.; Varelas, N.; Wang, H.; Wu, Z.; Zakaria, M.; 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.; Anderson, I.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Osherson, M.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Bruner, C.; Castle, J.; Forthomme, L.; Kenny, R. P., III; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; 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.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Apyan, A.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. 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.; 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.; Miller, D. H.; Neumeister, N.; Schulte, J. F.; 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.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; 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.; 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.; 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.; Sturdy, J.; Belknap, D. A.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

2017-06-01

The results of a search for new physics in final states with photons and missing transverse energy are reported. The study is based on a sample of proton-proton collisions collected at a center-of-mass energy of 13 TeV with the CMS detector in 2015, corresponding to an integrated luminosity of 2.3 fb-1. Final states with two photons and significant missing transverse energy are used to search for supersymmetric particles in models of supersymmetry (SUSY) with general gauge-mediated (GGM) supersymmetry breaking. No excess is observed with respect to the standard model expectation, and the results are used to set limits on gluino pair production and squark pair production in the GGM SUSY framework. Gluino masses below 1.65 TeV and squark masses below 1.37 TeV are excluded at a 95% confidence level.

Search for supersymmetry in events with photons and missing transverse energy in pp collisions at 13 TeV

DOE PAGES

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

2017-04-07

Results of a search for new physics in final states with photons and missing transverse energy are reported. The study is based on a sample of proton–proton collisions collected at a center-of-mass energy of 13 TeV with the CMS detector in 2015, corresponding to an integrated luminosity of 2.3 fb -1. Final states with two photons and significant missing transverse energy are used to search for supersymmetric particles in models of supersymmetry (SUSY) with general gauge-mediated (GGM) supersymmetry breaking. We did not observe an excess with respect to the standard model expectation, and the results are used to set limitsmore » on gluino pair production and squark pair production in the GGM SUSY framework. Gluino masses below 1.65 TeV and squark masses below 1.37 TeV are excluded at a 95% confidence level.« less

Dark Matter Ignition of Type Ia Supernovae.

PubMed

Bramante, Joseph

2015-10-02

Recent studies of low redshift type Ia supernovae (SN Ia) indicate that half explode from less than Chandrasekhar mass white dwarfs, implying ignition must proceed from something besides the canonical criticality of Chandrasekhar mass SN Ia progenitors. We show that 1-100 PeV mass asymmetric dark matter, with imminently detectable nucleon scattering interactions, can accumulate to the point of self-gravitation in a white dwarf and collapse, shedding gravitational potential energy by scattering off nuclei, thereby heating the white dwarf and igniting the flame front that precedes SN Ia. We combine data on SN Ia masses with data on the ages of SN Ia-adjacent stars. This combination reveals a 2.8σ inverse correlation between SN Ia masses and ignition ages, which could result from increased capture of dark matter in 1.4 vs 1.1 solar mass white dwarfs. Future studies of SN Ia in galactic centers will provide additional tests of dark-matter-induced type Ia ignition. Remarkably, both bosonic and fermionic SN Ia-igniting dark matter also resolve the missing pulsar problem by forming black holes in ≳10  Myr old pulsars at the center of the Milky Way.

Xenon Fractionation and Archean Hydrogen Escape

NASA Technical Reports Server (NTRS)

Zahnle, K. J.

2015-01-01

Xenon is the heaviest gas found in significant quantities in natural planetary atmospheres. It would seem the least likely to escape. Yet there is more evidence for xenon escape from Earth than for any element other than helium and perhaps neon. The most straightforward evidence is that most of the radiogenic Xe from the decay of (129)I (half-life 15.7 Myr) and (244)Pu (half-life 81 Myr) that is Earth's birthright is missing. The missing xenon is often attributed to the impact erosion of early atmospheres of Earth and its ancestors. It is obvious that if most of the radiogenic xenon were driven off by impacts, most of the rest of the atmophiles fared the same fate. The other line of evidence is in the nonradiogenic isotopes of xenon and its silent partner, krypton. Atmospheric xenon is strongly mass fractionated (at about 4% per amu) compared to any known solar system source (Figure 1). This is in stark contrast to krypton, which may not be fractionated at all: atmospheric Kr is slightly heavier than solar Kr (at about 0.5% per amu), but it is the same as in carbonaceous chondrites. Nonradiogenic xenon is also under abundant relative to krypton (the so-called "missing xenon" problem). Together these observations imply that xenon has been subject to fractionating escape and krypton not.

Astronomical Constraints on Quantum Cold Dark Matter

NASA Astrophysics Data System (ADS)

Spivey, Shane; Musielak, Z.; Fry, J.

2012-01-01

A model of quantum (`fuzzy') cold dark matter that accounts for both the halo core problem and the missing dwarf galaxies problem, which plague the usual cold dark matter paradigm, is developed. The model requires that a cold dark matter particle has a mass so small that its only allowed physical description is a quantum wave function. Each such particle in a galactic halo is bound to a gravitational potential that is created by luminous matter and by the halo itself, and the resulting wave function is described by a Schrödinger equation. To solve this equation on a galactic scale, we impose astronomical constraints that involve several density profiles used to fit data from simulations of dark matter galactic halos. The solutions to the Schrödinger equation are quantum waves which resemble the density profiles acquired from simulations, and they are used to determine the mass of the cold dark matter particle. The effects of adding certain types of baryonic matter to the halo, such as a dwarf elliptical galaxy or a supermassive black hole, are also discussed.

A Comparison of Missing-Data Procedures for Arima Time-Series Analysis

ERIC Educational Resources Information Center

Velicer, Wayne F.; Colby, Suzanne M.

2005-01-01

Missing data are a common practical problem for longitudinal designs. Time-series analysis is a longitudinal method that involves a large number of observations on a single unit. Four different missing-data methods (deletion, mean substitution, mean of adjacent observations, and maximum likelihood estimation) were evaluated. Computer-generated…

They Remember the "Lost" People.

ERIC Educational Resources Information Center

Klages, Karen

Estimates of the number of children currently missing in the United States are only approximate because there is no effective central data bank to collect information on missing persons and unidentified bodies. However, the problem appears to have reached epidemic proportions. Some parents of missing persons have formed organizations in different…

The Empirical Nature and Statistical Treatment of Missing Data

ERIC Educational Resources Information Center

Tannenbaum, Christyn E.

2009-01-01

Introduction. Missing data is a common problem in research and can produce severely misleading analyses, including biased estimates of statistical parameters, and erroneous conclusions. In its 1999 report, the APA Task Force on Statistical Inference encouraged authors to report complications such as missing data and discouraged the use of…

Impact of Missing Data for Body Mass Index in an Epidemiologic Study.

PubMed

Razzaghi, Hilda; Tinker, Sarah C; Herring, Amy H; Howards, Penelope P; Waller, D Kim; Johnson, Candice Y

2016-07-01

Objective To assess the potential impact of missing data on body mass index (BMI) on the association between prepregnancy obesity and specific birth defects. Methods Data from the National Birth Defects Prevention Study (NBDPS) were analyzed. We assessed the factors associated with missing BMI data among mothers of infants without birth defects. Four analytic methods were then used to assess the impact of missing BMI data on the association between maternal prepregnancy obesity and three birth defects; spina bifida, gastroschisis, and cleft lip with/without cleft palate. The analytic methods were: (1) complete case analysis; (2) assignment of missing values to either obese or normal BMI; (3) multiple imputation; and (4) probabilistic sensitivity analysis. Logistic regression was used to estimate crude and adjusted odds ratios (aOR) and 95 % confidence intervals (CI). Results Of NBDPS control mothers 4.6 % were missing BMI data, and most of the missing values were attributable to missing height (~90 %). Missing BMI data was associated with birth outside of the US (aOR 8.6; 95 % CI 5.5, 13.4), interview in Spanish (aOR 2.4; 95 % CI 1.8, 3.2), Hispanic ethnicity (aOR 2.0; 95 % CI 1.2, 3.4), and <12 years education (aOR 2.3; 95 % CI 1.7, 3.1). Overall the results of the multiple imputation and probabilistic sensitivity analysis were similar to the complete case analysis. Conclusions Although in some scenarios missing BMI data can bias the magnitude of association, it does not appear likely to have impacted conclusions from a traditional complete case analysis of these data.

Reliability and Validity in Measuring the Value Added of Schools

ERIC Educational Resources Information Center

van de Grift, Wim

2009-01-01

Instability in the school population between school entrance and school leaving is not "just a problem of missing data" but often the visible result of the educational problems in some schools and is, therefore, not merely to be treated as missing data but as indicator for the quality of educational processes. Even the most superior…

A Couple of "Lim (h[right arrow]0)-Is-Missing" Problems

ERIC Educational Resources Information Center

Lau, Ko Hin

2007-01-01

Since most students "hate" the concept of limit, in order to make them "happier," this article suggests a couple of naive "lim (h[right arrow]0)-is-missing" problems for them to try for fun. Indeed, differential functional equations that are related to difference quotients in calculus are studied in this paper. In particular, two interesting…

Addressing the Missing Instructional Data Problem: Using a Teacher Log to Document Tier 1 Instruction

ERIC Educational Resources Information Center

Kurz, Alexander; Elliott, Stephen N.; Roach, Andrew T.

2015-01-01

Response-to-intervention (RTI) systems posit that Tier 1 consists of high-quality general classroom instruction using evidence-based methods to address the needs of most students. However, data on the extent to which general education teachers provide such instruction are rarely collected. This missing instructional data problem may result in RTI…

A non-resonant mass sensor to eliminate the "missing mass" effect during mass measurement of biological materials

NASA Astrophysics Data System (ADS)

Shrikanth, V.; Bobji, M. S.

2014-10-01

Resonant sensors and crystal oscillators for mass detection need to be excited at very high natural frequencies (MHz). Use of such systems to measure mass of biological materials affects the accuracy of mass measurement due to their viscous and/or viscoelastic properties. The measurement limitation of such sensor system is the difficulty in accounting for the "missing mass" of the biological specimen in question. A sensor system has been developed in this work, to be operated in the stiffness controlled region at very low frequencies as compared to its fundamental natural frequency. The resulting reduction in the sensitivity due to non-resonant mode of operation of this sensor is compensated by the high resolution of the sensor. The mass of different aged drosophila melanogaster (fruit fly) is measured. The difference in its mass measurement during resonant mode of operation is also presented. That, viscosity effects do not affect the working of this non-resonant mass sensor is clearly established by direct comparison.

Missing data on body mass index in a breast cancer register: how is it associated with patient characteristics and clinical outcomes?

PubMed

Tin Tin, Sandar; Elwood, J Mark; Lawrenson, Ross; Campbell, Ian

2017-03-03

To assess the completeness of data on body mass index (BMI) in a regional breast cancer register, and its association with patient characteristics and clinical outcomes. This analysis used the data from the Waikato Breast Cancer Register and involved all women who were diagnosed with primary breast cancer in the Waikato District Health Board Region between January 2000 and June 2014. Patients with recorded BMI were compared with those with missing data in terms of demographics, disease factors and treatment factors. Cox regression modelling was performed, and hazards of specific outcomes associated with missing data on BMI were assessed. Of the 3,536 patients included in this analysis, 27.4% had missing data on BMI. Missing data was more frequent in older patients, rural dwellers, patients with comorbidities, screen detected patients, patients with early stage or low grade cancer and hormone receptor positive patients, but was minimal in patients who received chemotherapy. Patients with missing data were less likely to experience loco-regional recurrence (although not significant), metastasis and breast cancer specific mortality, but more likely to experience death from other causes even after demographic, disease and treatment factors were adjusted. Height or weight or both were not recorded for more than one quarter of the patients. Missing data was differential by specific patient characteristics and clinical outcomes.

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

Zhang, Jing, E-mail: jing.zhang2@duke.edu; Ghate, Sujata V.; Yoon, Sora C.

Purpose: Mammography is the most widely accepted and utilized screening modality for early breast cancer detection. Providing high quality mammography education to radiology trainees is essential, since excellent interpretation skills are needed to ensure the highest benefit of screening mammography for patients. The authors have previously proposed a computer-aided education system based on trainee models. Those models relate human-assessed image characteristics to trainee error. In this study, the authors propose to build trainee models that utilize features automatically extracted from images using computer vision algorithms to predict likelihood of missing each mass by the trainee. This computer vision-based approach tomore » trainee modeling will allow for automatically searching large databases of mammograms in order to identify challenging cases for each trainee. Methods: The authors’ algorithm for predicting the likelihood of missing a mass consists of three steps. First, a mammogram is segmented into air, pectoral muscle, fatty tissue, dense tissue, and mass using automated segmentation algorithms. Second, 43 features are extracted using computer vision algorithms for each abnormality identified by experts. Third, error-making models (classifiers) are applied to predict the likelihood of trainees missing the abnormality based on the extracted features. The models are developed individually for each trainee using his/her previous reading data. The authors evaluated the predictive performance of the proposed algorithm using data from a reader study in which 10 subjects (7 residents and 3 novices) and 3 experts read 100 mammographic cases. Receiver operating characteristic (ROC) methodology was applied for the evaluation. Results: The average area under the ROC curve (AUC) of the error-making models for the task of predicting which masses will be detected and which will be missed was 0.607 (95% CI,0.564-0.650). This value was statistically significantly different from 0.5 (p < 0.0001). For the 7 residents only, the AUC performance of the models was 0.590 (95% CI,0.537-0.642) and was also significantly higher than 0.5 (p = 0.0009). Therefore, generally the authors’ models were able to predict which masses were detected and which were missed better than chance. Conclusions: The authors proposed an algorithm that was able to predict which masses will be detected and which will be missed by each individual trainee. This confirms existence of error-making patterns in the detection of masses among radiology trainees. Furthermore, the proposed methodology will allow for the optimized selection of difficult cases for the trainees in an automatic and efficient manner.« less

Sparse subspace clustering for data with missing entries and high-rank matrix completion.

PubMed

Fan, Jicong; Chow, Tommy W S

2017-09-01

Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Singularity free N-body simulations called 'Dynamic Universe Model' don't require dark matter

NASA Astrophysics Data System (ADS)

Naga Parameswara Gupta, Satyavarapu

For finding trajectories of Pioneer satellite (Anomaly), New Horizons satellite going to Pluto, the Calculations of Dynamic Universe model can be successfully applied. No dark matter is assumed within solar system radius. The effect on the masses around SUN shows as though there is extra gravitation pull toward SUN. It solves the Dynamics of Extra-solar planets like Planet X, satellite like Pioneer and NH for 3-Position, 3-velocity 3-accelaration for their masses, considering the complex situation of Multiple planets, Stars, Galaxy parts and Galaxy centre and other Galaxies Using simple Newtonian Physics. It already solved problems Missing mass in Galaxies observed by galaxy circular velocity curves successfully. Singularity free Newtonian N-body simulations Historically, King Oscar II of Sweden an-nounced a prize to a solution of N-body problem with advice given by Güsta Mittag-Leffler in 1887. He announced `Given a system of arbitrarily many mass points that attract each according to Newton's law, under the assumption that no two points ever collide, try to find a representation of the coordinates of each point as a series in a variable that is some known function of time and for all of whose values the series converges uniformly.'[This is taken from Wikipedia]. The announced dead line that time was1st June 1888. And after that dead line, on 21st January 1889, Great mathematician Poincaré claimed that prize. Later he himself sent a telegram to journal Acta Mathematica to stop printing the special issue after finding the error in his solution. Yet for such a man of science reputation is important than money. [ Ref Book `Celestial mechanics: the waltz of the planets' By Alessandra Celletti, Ettore Perozzi, page 27]. He realized that he has been wrong in his general stability result! But till now nobody could solve that problem or claimed that prize. Later all solutions resulted in singularities and collisions of masses, given by many people . . . . . . . . . . . . . . . . . . . . . . . . .. Now I can say that the Dynamic Universe Model solves this classical N-body problem where only Newtonian Gravi-tation law and classical Physics were used. The solution converges at all points. There are no multiple values, diverging solutions or divided by zero singularities. Collisions of masses depend on physical values of masses and their space distribution only. These collisions do not happen due to internal inherent problems of Dynamic universe Model. If the mass distribution is homogeneous and isotropic, the masses will colloid. If the mass distribution is heterogeneous and anisotropic, they do not colloid. This approach solves many problems which otherwise can not be solved by General relativity, Steady state universe model etc. . .

Los Alamos Science, Number 25 -- 1997: Celebrating the Neutrino

DOE R&D Accomplishments Database

Cooper, N. G. ed.

1997-01-01

This issue is devoted to the neutrino and its remaining mysteries. It is divided into the following areas: (1) The Reines-Cowan experiment -- detecting the poltergeist; (2) The oscillating neutrino -- an introduction to neutrino masses and mixing; (3) A brief history of neutrino experiments at LAMPF; (4) A thousand eyes -- the story of LSND (Los Alamos neutrino oscillation experiment); (5) The evidence for oscillations; (6) The nature of neutrinos in muon decay and physics beyond the Standard Model; (7) Exorcising ghosts -- in pursuit of the missing solar neutrinos; (8) MSW -- a possible solution to the solar neutrino problem; (8) Neutrinos and supernovae; and (9) Dark matter and massive neutrinos.

LHC phenomenology of natural MSSM with non-universal gaugino masses at the unification scale

NASA Astrophysics Data System (ADS)

Abe, Hiroyuki; Kawamura, Junichiro; Omura, Yuji

2015-08-01

In this letter, we study collider phenomenology in the supersymmetric Standard Model with a certain type of non-universal gaugino masses at the gauge coupling unification scale, motivated by the little hierarchy problem. In this scenario, especially the wino mass is relatively large compared to the gluino mass at the unification scale, and the heavy wino can relax the fine-tuning of the higgsino mass parameter, so-called μ-parameter. Besides, it will enhance the lightest Higgs boson mass due to the relatively large left-right mixing of top squarks through the renormalization group (RG) effect. Then 125 GeV Higgs boson could be accomplished, even if the top squarks are lighter than 1 TeV and the μ parameter is within a few hundreds GeV. The right-handed top squark tends to be lighter than the other sfermions due to the RG runnings, then we focus on the top squark search at the LHC. Since the top squark is almost right-handed and the higgsinos are nearly degenerate, 2 b + E T miss channel is the most sensitive to this scenario. We figure out current and expected experimental bounds on the lightest top squark mass and model parameters at the gauge coupling unification scale.

Strategies for Dealing with Missing Accelerometer Data.

PubMed

Stephens, Samantha; Beyene, Joseph; Tremblay, Mark S; Faulkner, Guy; Pullnayegum, Eleanor; Feldman, Brian M

2018-05-01

Missing data is a universal research problem that can affect studies examining the relationship between physical activity measured with accelerometers and health outcomes. Statistical techniques are available to deal with missing data; however, available techniques have not been synthesized. A scoping review was conducted to summarize the advantages and disadvantages of identified methods of dealing with missing data from accelerometers. Missing data poses a threat to the validity and interpretation of trials using physical activity data from accelerometry. Imputation using multiple imputation techniques is recommended to deal with missing data and improve the validity and interpretation of studies using accelerometry. Copyright © 2018 Elsevier Inc. All rights reserved.

Do word-problem features differentially affect problem difficulty as a function of students' mathematics difficulty with and without reading difficulty?

PubMed

Powell, Sarah R; Fuchs, Lynn S; Fuchs, Douglas; Cirino, Paul T; Fletcher, Jack M

2009-01-01

This study examined whether and, if so, how word-problem features differentially affect problem difficulty as a function of mathematics difficulty (MD) status: no MD (n = 109), MD only (n = 109), or MD in combination with reading difficulties (MDRD; n = 109). The problem features were problem type (total, difference, or change) and position of missing information in the number sentence representing the word problem (first, second, or third position). Students were assessed on 14 word problems near the beginning of third grade. Consistent with the hypothesis that mathematical cognition differs as a function of MD subtype, problem type affected problem difficulty differentially for MDRD versus MD-only students; however, the position of missing information in word problems did not. Implications for MD subtyping and for instruction are discussed.

A comparison of model-based imputation methods for handling missing predictor values in a linear regression model: A simulation study

NASA Astrophysics Data System (ADS)

Hasan, Haliza; Ahmad, Sanizah; Osman, Balkish Mohd; Sapri, Shamsiah; Othman, Nadirah

2017-08-01

In regression analysis, missing covariate data has been a common problem. Many researchers use ad hoc methods to overcome this problem due to the ease of implementation. However, these methods require assumptions about the data that rarely hold in practice. Model-based methods such as Maximum Likelihood (ML) using the expectation maximization (EM) algorithm and Multiple Imputation (MI) are more promising when dealing with difficulties caused by missing data. Then again, inappropriate methods of missing value imputation can lead to serious bias that severely affects the parameter estimates. The main objective of this study is to provide a better understanding regarding missing data concept that can assist the researcher to select the appropriate missing data imputation methods. A simulation study was performed to assess the effects of different missing data techniques on the performance of a regression model. The covariate data were generated using an underlying multivariate normal distribution and the dependent variable was generated as a combination of explanatory variables. Missing values in covariate were simulated using a mechanism called missing at random (MAR). Four levels of missingness (10%, 20%, 30% and 40%) were imposed. ML and MI techniques available within SAS software were investigated. A linear regression analysis was fitted and the model performance measures; MSE, and R-Squared were obtained. Results of the analysis showed that MI is superior in handling missing data with highest R-Squared and lowest MSE when percent of missingness is less than 30%. Both methods are unable to handle larger than 30% level of missingness.

Missing Data and Multiple Imputation in the Context of Multivariate Analysis of Variance

ERIC Educational Resources Information Center

Finch, W. Holmes

2016-01-01

Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…

SPSS Syntax for Missing Value Imputation in Test and Questionnaire Data

ERIC Educational Resources Information Center

van Ginkel, Joost R.; van der Ark, L. Andries

2005-01-01

A well-known problem in the analysis of test and questionnaire data is that some item scores may be missing. Advanced methods for the imputation of missing data are available, such as multiple imputation under the multivariate normal model and imputation under the saturated logistic model (Schafer, 1997). Accompanying software was made available…

Genetics Home Reference: Fraser syndrome

MedlinePlus

... them, or they may be small ( microphthalmia ) or missing (anophthalmia). Eye abnormalities typically lead to impairment or ... other problems related to abnormal eye development, including missing eyebrows or eyelashes or a patch of hair ...

The "Missing Males" and Other Gender-Related Issues in Music Education: A Critical Analysis of Evidence from the Music Supervisors' Journal, 1914-1924.

ERIC Educational Resources Information Center

Koza, Julia Eklund

Boys' reluctance to participate in music education programs, particularly in school singing groups -- termed in this paper the "missing males" problem -- is just one among many pressing gender problems in music education. In order to discover whether boys' lack of participation in music, along with other gender-related issues, are merely…

Multi-task Gaussian process for imputing missing data in multi-trait and multi-environment trials.

PubMed

Hori, Tomoaki; Montcho, David; Agbangla, Clement; Ebana, Kaworu; Futakuchi, Koichi; Iwata, Hiroyoshi

2016-11-01

A method based on a multi-task Gaussian process using self-measuring similarity gave increased accuracy for imputing missing phenotypic data in multi-trait and multi-environment trials. Multi-environmental trial (MET) data often encounter the problem of missing data. Accurate imputation of missing data makes subsequent analysis more effective and the results easier to understand. Moreover, accurate imputation may help to reduce the cost of phenotyping for thinned-out lines tested in METs. METs are generally performed for multiple traits that are correlated to each other. Correlation among traits can be useful information for imputation, but single-trait-based methods cannot utilize information shared by traits that are correlated. In this paper, we propose imputation methods based on a multi-task Gaussian process (MTGP) using self-measuring similarity kernels reflecting relationships among traits, genotypes, and environments. This framework allows us to use genetic correlation among multi-trait multi-environment data and also to combine MET data and marker genotype data. We compared the accuracy of three MTGP methods and iterative regularized PCA using rice MET data. Two scenarios for the generation of missing data at various missing rates were considered. The MTGP performed a better imputation accuracy than regularized PCA, especially at high missing rates. Under the 'uniform' scenario, in which missing data arise randomly, inclusion of marker genotype data in the imputation increased the imputation accuracy at high missing rates. Under the 'fiber' scenario, in which missing data arise in all traits for some combinations between genotypes and environments, the inclusion of marker genotype data decreased the imputation accuracy for most traits while increasing the accuracy in a few traits remarkably. The proposed methods will be useful for solving the missing data problem in MET data.

Biases in comparative analyses of extinction risk: mind the gap.

PubMed

González-Suárez, Manuela; Lucas, Pablo M; Revilla, Eloy

2012-11-01

1. Comparative analyses are used to address the key question of what makes a species more prone to extinction by exploring the links between vulnerability and intrinsic species' traits and/or extrinsic factors. This approach requires comprehensive species data but information is rarely available for all species of interest. As a result comparative analyses often rely on subsets of relatively few species that are assumed to be representative samples of the overall studied group. 2. Our study challenges this assumption and quantifies the taxonomic, spatial, and data type biases associated with the quantity of data available for 5415 mammalian species using the freely available life-history database PanTHERIA. 3. Moreover, we explore how existing biases influence results of comparative analyses of extinction risk by using subsets of data that attempt to correct for detected biases. In particular, we focus on links between four species' traits commonly linked to vulnerability (distribution range area, adult body mass, population density and gestation length) and conduct univariate and multivariate analyses to understand how biases affect model predictions. 4. Our results show important biases in data availability with c.22% of mammals completely lacking data. Missing data, which appear to be not missing at random, occur frequently in all traits (14-99% of cases missing). Data availability is explained by intrinsic traits, with larger mammals occupying bigger range areas being the best studied. Importantly, we find that existing biases affect the results of comparative analyses by overestimating the risk of extinction and changing which traits are identified as important predictors. 5. Our results raise concerns over our ability to draw general conclusions regarding what makes a species more prone to extinction. Missing data represent a prevalent problem in comparative analyses, and unfortunately, because data are not missing at random, conventional approaches to fill data gaps, are not valid or present important challenges. These results show the importance of making appropriate inferences from comparative analyses by focusing on the subset of species for which data are available. Ultimately, addressing the data bias problem requires greater investment in data collection and dissemination, as well as the development of methodological approaches to effectively correct existing biases. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

Search for Anomalous Production of Photon + Jets + Missing Transverse Energy in $$p\\bar{p}$$ Collisions at $$\\sqrt{s}=1.96$$~TeV Using the CDF II Detector

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

Hewamanage, Samantha Kaushalya

2011-01-01

A model-independent signature-based search for physics beyond the Standard Model is performed in the photon + jets + missing transverse energy channel in \\ppbar collisions at a center of mass energy of 1.96 TeV using the CDF II detector. Events with a photon + jets are predicted by the Standard Model and also by many theoretical models beyond the Standard Model. In the Standard Model, the main mechanisms for photon + jets production include quark-antiquark annihilation and quark-gluon scattering. No intrinsic missing transverse energy is present in any of these Standard Model processes. In this search, photon +more » $$\\geq$$1 jet and photon + $$\\geq$$2 jet events are analyzed with and without a minimum requirement on the missing transverse energy. Numerous mass distributions and kinematic distributions are studied and no significant excess over the background prediction is found. All results indicate good agreement with expectations of the Standard Model.« less

A MAP-based image interpolation method via Viterbi decoding of Markov chains of interpolation functions.

PubMed

Vedadi, Farhang; Shirani, Shahram

2014-01-01

A new method of image resolution up-conversion (image interpolation) based on maximum a posteriori sequence estimation is proposed. Instead of making a hard decision about the value of each missing pixel, we estimate the missing pixels in groups. At each missing pixel of the high resolution (HR) image, we consider an ensemble of candidate interpolation methods (interpolation functions). The interpolation functions are interpreted as states of a Markov model. In other words, the proposed method undergoes state transitions from one missing pixel position to the next. Accordingly, the interpolation problem is translated to the problem of estimating the optimal sequence of interpolation functions corresponding to the sequence of missing HR pixel positions. We derive a parameter-free probabilistic model for this to-be-estimated sequence of interpolation functions. Then, we solve the estimation problem using a trellis representation and the Viterbi algorithm. Using directional interpolation functions and sequence estimation techniques, we classify the new algorithm as an adaptive directional interpolation using soft-decision estimation techniques. Experimental results show that the proposed algorithm yields images with higher or comparable peak signal-to-noise ratios compared with some benchmark interpolation methods in the literature while being efficient in terms of implementation and complexity considerations.

Estimated Environmental Exposures for MISSE-7B

NASA Technical Reports Server (NTRS)

Finckenor, Miria M.; Moore, Chip; Norwood, Joseph K.; Henrie, Ben; DeGroh, Kim

2012-01-01

This paper details the 18-month environmental exposure for Materials International Space Station Experiment 7B (MISSE-7B) ram and wake sides. This includes atomic oxygen, ultraviolet radiation, particulate radiation, thermal cycling, meteoroid/space debris impacts, and observed contamination. Atomic oxygen fluence was determined by measured mass and thickness loss of polymers of known reactivity. Diodes sensitive to ultraviolet light actively measured solar radiation incident on the experiment. Comparisons to earlier MISSE flights are discussed.

Kalman Filtering for Genetic Regulatory Networks with Missing Values

PubMed Central

Liu, Qiuhua; Lai, Tianyue; Wang, Wu

2017-01-01

The filter problem with missing value for genetic regulation networks (GRNs) is addressed, in which the noises exist in both the state dynamics and measurement equations; furthermore, the correlation between process noise and measurement noise is also taken into consideration. In order to deal with the filter problem, a class of discrete-time GRNs with missing value, noise correlation, and time delays is established. Then a new observation model is proposed to decrease the adverse effect caused by the missing value and to decouple the correlation between process noise and measurement noise in theory. Finally, a Kalman filtering is used to estimate the states of GRNs. Meanwhile, a typical example is provided to verify the effectiveness of the proposed method, and it turns out to be the case that the concentrations of mRNA and protein could be estimated accurately. PMID:28814967

Instrumental Variable Methods for Continuous Outcomes That Accommodate Nonignorable Missing Baseline Values.

PubMed

Ertefaie, Ashkan; Flory, James H; Hennessy, Sean; Small, Dylan S

2017-06-15

Instrumental variable (IV) methods provide unbiased treatment effect estimation in the presence of unmeasured confounders under certain assumptions. To provide valid estimates of treatment effect, treatment effect confounders that are associated with the IV (IV-confounders) must be included in the analysis, and not including observations with missing values may lead to bias. Missing covariate data are particularly problematic when the probability that a value is missing is related to the value itself, which is known as nonignorable missingness. In such cases, imputation-based methods are biased. Using health-care provider preference as an IV method, we propose a 2-step procedure with which to estimate a valid treatment effect in the presence of baseline variables with nonignorable missing values. First, the provider preference IV value is estimated by performing a complete-case analysis using a random-effects model that includes IV-confounders. Second, the treatment effect is estimated using a 2-stage least squares IV approach that excludes IV-confounders with missing values. Simulation results are presented, and the method is applied to an analysis comparing the effects of sulfonylureas versus metformin on body mass index, where the variables baseline body mass index and glycosylated hemoglobin have missing values. Our result supports the association of sulfonylureas with weight gain. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Top-quark pair plus large missing energy at the LHC

NASA Astrophysics Data System (ADS)

Han, Tao; Mahbubani, Rakhi; Walker, Devin G. E.; Wang, Lian-Tao

2009-05-01

We study methods of extracting new physics signals in final states with a top-quark pair plus large missing energy at the LHC. We consider two typical examples of such new physics: pair production of a fermionic top partner (a T' in Little Higgs models for example) and of a scalar top partner (a tilde t in SUSY). With a commonly-adopted discrete symmetry under which non Standard Model particles are odd, the top partner is assumed to decay predominantly to a top quark plus a massive neutral stable particle A0. We focus on the case in which one of the top quarks decays leptonically and the other decays hadronically, pp → tbar tA0A0X → bj1j2 bar bl-bar nu A0A0X + c.c., where the A0s escape detection. We identify a key parameter for the signal observation: the mass splitting between the top partner and the missing particle. We reconstruct a transverse mass for the lepton-missing transverse energy system to separate the real W background from the signal and propose a definition for the reconstructed top quark mass that allows it to take unphysical values as an indication of new physics. We perform a scan over the two masses to map out the discovery reach at the LHC in this channel. We also comment on the possibility of distinguishing between scalar and fermionic top partners using collider signatures.

Predicting the Velocity Dispersions of the Dwarf Satellite Galaxies of Andromeda

NASA Astrophysics Data System (ADS)

McGaugh, Stacy S.

2016-05-01

Dwarf Spheroidal galaxies in the Local Group are the faintest and most diffuse stellar systems known. They exhibit large mass discrepancies, making them popular laboratories for studying the missing mass problem. The PANDAS survey of M31 revealed dozens of new examples of such dwarfs. As these systems were discovered, it was possible to use the observed photometric properties to predict their stellar velocity dispersions with the modified gravity theory MOND. These predictions, made in advance of the observations, have since been largely confirmed. A unique feature of MOND is that a structurally identical dwarf will behave differently when it is or is not subject to the external field of a massive host like Andromeda. The role of this "external field effect" is critical in correctly predicting the velocity dispersions of dwarfs that deviate from empirical scaling relations. With continued improvement in the observational data, these systems could provide a test of the strong equivalence principle.

Missing Children's Assistance Act. Hearings before the Subcommittee on Juvenile Justice of the Committee on the Judiciary. United States Senate. Ninety-Eighth Congress, Second Session on S. 2014, a Bill to Amend the Juvenile Justice and Delinquency Prevention Act of 1974 to Provide for Assistance in Locating Missing Children (February 7 and 21; March 8, 13, and 21, 1984).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. Senate Committee on the Judiciary.

This document presents testimony and proceedings from Congressional hearings on the problem of missing children and the remedies proposed by the Missing Children's Assistance Act. Opening testimony by Senators Arlen Specter and Paula Hawkins is presented, as is the text of the Missing Children's Assistance Act of 1983. Prepared testimony from…

Empirical Likelihood in Nonignorable Covariate-Missing Data Problems.

PubMed

Xie, Yanmei; Zhang, Biao

2017-04-20

Missing covariate data occurs often in regression analysis, which frequently arises in the health and social sciences as well as in survey sampling. We study methods for the analysis of a nonignorable covariate-missing data problem in an assumed conditional mean function when some covariates are completely observed but other covariates are missing for some subjects. We adopt the semiparametric perspective of Bartlett et al. (Improving upon the efficiency of complete case analysis when covariates are MNAR. Biostatistics 2014;15:719-30) on regression analyses with nonignorable missing covariates, in which they have introduced the use of two working models, the working probability model of missingness and the working conditional score model. In this paper, we study an empirical likelihood approach to nonignorable covariate-missing data problems with the objective of effectively utilizing the two working models in the analysis of covariate-missing data. We propose a unified approach to constructing a system of unbiased estimating equations, where there are more equations than unknown parameters of interest. One useful feature of these unbiased estimating equations is that they naturally incorporate the incomplete data into the data analysis, making it possible to seek efficient estimation of the parameter of interest even when the working regression function is not specified to be the optimal regression function. We apply the general methodology of empirical likelihood to optimally combine these unbiased estimating equations. We propose three maximum empirical likelihood estimators of the underlying regression parameters and compare their efficiencies with other existing competitors. We present a simulation study to compare the finite-sample performance of various methods with respect to bias, efficiency, and robustness to model misspecification. The proposed empirical likelihood method is also illustrated by an analysis of a data set from the US National Health and Nutrition Examination Survey (NHANES).

Menstrual Cycle Problems

MedlinePlus

... MoreDepression in Children and TeensRead MoreBMI Calculator Menstrual Cycle ProblemsFrom missed periods to painful periods, menstrual cycle problems are common, but usually not serious. Follow ...

Supersymmetry models and phenomenology

NASA Astrophysics Data System (ADS)

Carpenter, Linda M.

We present several models of supersymmetry breaking and explore their phenomenological consequences. First, we build models utilizing the supersymmetry breaking formalism of anomaly mediation. Our first model consists of the minimal supersymmetric standard model plus a singlet, anomaly-mediated soft masses and a Dirac mass which marries the bino to the singlet. The Dirac mass does not affect the so-called "UV insensitivity" of the other soft parameters to running or supersymmetric thresholds and thus flavor physics at intermediate scales would not reintroduce the flavor problem. The Dirac bino is integrated out at a few TeV and produces finite and positive contributions to all hyper-charged scalars at one loop thus producing positive squared slepton masses. Our second model approaches anomaly mediation from the point of view of the mu problem. We present a minimal method for generating a mu term while still generating a viable spectrum. We introduce a new operator involving a hidden sector U(1) gauge field which is then canceled against a Giudice-Masiero-like mu term. No new flavor violating operators are allowed. This procedure produces viable electroweak symmetry breaking in the Higgs sector. Only a single pair of new vector-like messenger fields is needed to correct the slepton masses by deflecting them from their anomaly mediated trajectories. Finally we attempt to solve the Higgs mass tuning problem in the MSSM; both electroweak precision measurements and simple supersymmetric extensions of the standard model prefer the mass of the Higgs boson to be around the Z mass. However, LEP II rules out a standard model-like Higgs lighter than 114.4 GeV. We show that supersymmetric models with R parity violation have a large range of parameter space in which the Higgs effectively decays to six jets (for Baryon number violation) or four jets plus taus and/or missing energy (for Lepton number violation). These decays are much more weakly constrained by current LEP analyses and could be probed by new exclusive channel analyses as well as a combined "model independent" Higgs search analysis by all experiments.

Missing value imputation: with application to handwriting data

NASA Astrophysics Data System (ADS)

Xu, Zhen; Srihari, Sargur N.

2015-01-01

Missing values make pattern analysis difficult, particularly with limited available data. In longitudinal research, missing values accumulate, thereby aggravating the problem. Here we consider how to deal with temporal data with missing values in handwriting analysis. In the task of studying development of individuality of handwriting, we encountered the fact that feature values are missing for several individuals at several time instances. Six algorithms, i.e., random imputation, mean imputation, most likely independent value imputation, and three methods based on Bayesian network (static Bayesian network, parameter EM, and structural EM), are compared with children's handwriting data. We evaluate the accuracy and robustness of the algorithms under different ratios of missing data and missing values, and useful conclusions are given. Specifically, static Bayesian network is used for our data which contain around 5% missing data to provide adequate accuracy and low computational cost.

What to Do when Data Are Missing in Group Randomized Controlled Trials. NCEE 2009-0049

ERIC Educational Resources Information Center

Puma, Michael J.; Olsen, Robert B.; Bell, Stephen H.; Price, Cristofer

2009-01-01

This NCEE Technical Methods report examines how to address the problem of missing data in the analysis of data in Randomized Controlled Trials (RCTs) of educational interventions, with a particular focus on the common educational situation in which groups of students such as entire classrooms or schools are randomized. Missing outcome data are a…

Working with Missing Data in Higher Education Research: A Primer and Real-World Example

ERIC Educational Resources Information Center

Cox, Bradley E.; McIntosh, Kadian; Reason, Robert D.; Terenzini, Patrick T.

2014-01-01

Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

Postmodeling Sensitivity Analysis to Detect the Effect of Missing Data Mechanisms

ERIC Educational Resources Information Center

Jamshidian, Mortaza; Mata, Matthew

2008-01-01

Incomplete or missing data is a common problem in almost all areas of empirical research. It is well known that simple and ad hoc methods such as complete case analysis or mean imputation can lead to biased and/or inefficient estimates. The method of maximum likelihood works well; however, when the missing data mechanism is not one of missing…

Modeling missing data in knowledge space theory.

PubMed

de Chiusole, Debora; Stefanutti, Luca; Anselmi, Pasquale; Robusto, Egidio

2015-12-01

Missing data are a well known issue in statistical inference, because some responses may be missing, even when data are collected carefully. The problem that arises in these cases is how to deal with missing data. In this article, the missingness is analyzed in knowledge space theory, and in particular when the basic local independence model (BLIM) is applied to the data. Two extensions of the BLIM to missing data are proposed: The former, called ignorable missing BLIM (IMBLIM), assumes that missing data are missing completely at random; the latter, called missing BLIM (MissBLIM), introduces specific dependencies of the missing data on the knowledge states, thus assuming that the missing data are missing not at random. The IMBLIM and the MissBLIM modeled the missingness in a satisfactory way, in both a simulation study and an empirical application, depending on the process that generates the missingness: If the missing data-generating process is of type missing completely at random, then either IMBLIM or MissBLIM provide adequate fit to the data. However, if the pattern of missingness is functionally dependent upon unobservable features of the data (e.g., missing answers are more likely to be wrong), then only a correctly specified model of the missingness distribution provides an adequate fit to the data. (c) 2015 APA, all rights reserved).

Fitting the multitemporal curve: a fourier series approach to the missing data problem in remote sensing analysis

Treesearch

Evan Brooks; Valerie Thomas; Wynne Randolph; John Coulston

2012-01-01

With the advent of free Landsat data stretching back decades, there has been a surge of interest in utilizing remotely sensed data in multitemporal analysis for estimation of biophysical parameters. Such analysis is confounded by cloud cover and other image-specific problems, which result in missing data at various aperiodic times of the year. While there is a wealth...

Search for Physics Beyond the Standard Model in Events with High-Momentum Higgs Bosons and Missing Transverse Momentum in Proton-Proton Collisions at 13 TeV

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Escalante Del Valle, A.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Taurok, A.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Pieters, M.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Marchesini, I.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Bilin, B.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Dorney, B.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Kalsi, A. K.; Lenzi, T.; Luetic, J.; Seva, T.; Starling, E.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Trocino, D.; Tytgat, M.; Verbeke, W.; Vit, M.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; Caudron, A.; David, P.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Saggio, A.; Vidal Marono, M.; Wertz, S.; Zobec, J.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correia Silva, G.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Coelho, E.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Medina Jaime, M.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Sanchez Rosas, L. J.; Santoro, A.; Sznajder, A.; Thiel, M.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Tomei, T. R. Fernandez Perez; 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.; Marinov, A.; Misheva, M.; Rodozov, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Yuan, L.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, J.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Wang, Y.; Avila, C.; Cabrera, A.; Carrillo Montoya, C. A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Segura Delgado, M. A.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Abdelalim, A. A.; Elgammal, S.; Khalil, S.; Bhowmik, S.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Veelken, C.; Eerola, P.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkilä, J. K.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Leloup, C.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Granier de Cassagnac, R.; Jo, M.; Kucher, I.; 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.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. 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S.; Lee, J.; Lee, S.; Lee, S. W.; Moon, C. S.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Kim, H.; Moon, D. H.; Oh, G.; Brochero Cifuentes, J. A.; Goh, J.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Kim, J. S.; Lee, H.; Lee, K.; Nam, K.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Choi, Y.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Reyes-Almanza, R.; Ramirez-Sanchez, G.; Duran-Osuna, M. C.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Rabadan-Trejo, R. 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V.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Blinov, V.; Shtol, D.; Skovpen, Y.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Godizov, A.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Mandrik, P.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Babaev, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Alcaraz Maestre, J.; Bachiller, I.; Barrio Luna, M.; Cerrada, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Moran, D.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Redondo, I.; Romero, L.; Soares, M. S.; Triossi, A.; Álvarez Fernández, A.; Albajar, C.; de Trocóniz, J. 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M.; Rabady, D.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Selvaggi, M.; Sharma, A.; Silva, P.; Sphicas, P.; Stakia, A.; Steggemann, J.; Stoye, M.; Tosi, M.; Treille, D.; Tsirou, A.; Veckalns, V.; Verweij, M.; Zeuner, W. D.; Bertl, W.; Caminada, L.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Backhaus, M.; Bäni, L.; Berger, P.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dorfer, C.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Klijnsma, T.; Lustermann, W.; Marionneau, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Reichmann, M.; Sanz Becerra, D. A.; Schönenberger, M.; Shchutska, L.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Brzhechko, D.; Canelli, M. F.; De Cosa, A.; Del Burgo, R.; Donato, S.; Galloni, C.; Hreus, T.; Kilminster, B.; Neutelings, I.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Schweiger, K.; Seitz, C.; Takahashi, Y.; Zucchetta, A.; Candelise, V.; Chang, Y. H.; Cheng, K. y.; Doan, T. H.; Jain, Sh.; Khurana, R.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Paganis, E.; Psallidas, A.; Steen, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Bat, A.; Boran, F.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Sunar Cerci, D.; Tali, B.; Tok, U. G.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Karapinar, G.; Ocalan, K.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Komurcu, Y.; Grynyov, B.; Levchuk, L.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Davignon, O.; Flacher, H.; Goldstein, J.; Heath, G. P.; Heath, H. F.; Kreczko, L.; Newbold, D. M.; Paramesvaran, S.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Linacre, J.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Womersley, W. J.; Auzinger, G.; Bainbridge, R.; Bloch, P.; Borg, J.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; Della Negra, M.; Di Maria, R.; Elwood, A.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Komm, M.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Palladino, V.; Pesaresi, M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Strebler, T.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wardle, N.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Morton, A.; Reid, I. D.; Teodorescu, L.; Zahid, S.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Smith, C.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Hadley, M.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Lee, J.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Stolp, D.; Taylor, D.; Tos, K.; Tripathi, M.; Wang, Z.; Zhang, F.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Regnard, S.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Karapostoli, G.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Si, W.; Wang, L.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Gilbert, D.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Citron, M.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; Gouskos, L.; Heller, R.; Incandela, J.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bornheim, A.; Bunn, J.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T. Q.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Macdonald, E.; Mulholland, T.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chaves, J.; Cheng, Y.; Chu, J.; Datta, A.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Quach, D.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Alyari, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kortelainen, M. J.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Savoy-Navarro, A.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Wu, W.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Joshi, B. M.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Shi, K.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Dittmer, S.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Rogan, C.; Royon, C.; Sanders, S.; Schmitz, E.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Modak, A.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Rebassoo, F.; Wright, D.; Baden, A.; Baron, O.; Belloni, A.; Eno, S. C.; Feng, Y.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bauer, G.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Harris, P.; Hsu, D.; Hu, M.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Stephans, G. S. F.; Sumorok, K.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Zhaozhong, S.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Wadud, M. A.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Golf, F.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Freer, C.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Orimoto, T.; Teixeira De Lima, R.; Wamorkar, T.; Wang, B.; Wisecarver, A.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Bucci, R.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Li, W.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Siddireddy, P.; Smith, G.; Taroni, S.; Wayne, M.; Wightman, A.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Ling, T. Y.; Luo, W.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Kalogeropoulos, A.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Salfeld-Nebgen, J.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Das, S.; Gutay, L.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xiao, R.; Xie, W.; Cheng, T.; Parashar, N.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. M.; Guilbaud, M.; Kilpatrick, M.; Li, W.; Michlin, B.; Padley, B. P.; Roberts, J.; Rorie, J.; Shi, W.; Tu, Z.; Zabel, J.; Zhang, A.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Mengke, T.; Muthumuni, S.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Poudyal, N.; Sturdy, J.; Thapa, P.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Carlsmith, D.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Rekovic, V.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Woods, N.; CMS Collaboration

2018-06-01

A search for physics beyond the standard model in events with one or more high-momentum Higgs bosons, H , decaying to pairs of b quarks in association with missing transverse momentum is presented. The data, corresponding to an integrated luminosity of 35.9 fb-1, were collected with the CMS detector at the LHC in proton-proton collisions at the center-of-mass energy √{s }=13 TeV . The analysis utilizes a new b quark tagging technique based on jet substructure to identify jets from H →b b ¯ . Events are categorized by the multiplicity of H -tagged jets, jet mass, and the missing transverse momentum. No significant deviation from standard model expectations is observed. In the context of supersymmetry (SUSY), limits on the cross sections of pair-produced gluinos are set, assuming that gluinos decay to quark pairs, H (or Z ), and the lightest SUSY particle, LSP, through an intermediate next-to-lightest SUSY particle, NLSP. With large mass splitting between the NLSP and LSP, and 100% NLSP branching fraction to H , the lower limit on the gluino mass is found to be 2010 GeV.

MISSE-X: An ISS External Platform for Space Environmental Studies in the Post-Shuttle Era

NASA Technical Reports Server (NTRS)

Thibeault, Sheila A.; Cooke, Stuart A.; Ashe, Melissa P.; Saucillo, Rudolph J.; Murphy, Douglas G.; deGroh, Kim K.; Jaworske, Donald A.; Nguyen, Quang-Viet

2011-01-01

Materials International Space Station Experiment-X (MISSE-X) is a proposed International Space Station (ISS) external platform for space environmental studies designed to advance the technology readiness of materials and devices critical for future space exploration. The MISSE-X platform will expand ISS utilization by providing experimenters with unprecedented low-cost space access and return on investment (ROI). As a follow-on to the highly successful MISSE series of ISS experiments, MISSE-X will provide advances over the original MISSE configurations including incorporation of plug-and-play experiments that will minimize return mass requirements in the post-Shuttle era, improved active sensing and monitoring of the ISS external environment for better characterization of environmental effects, and expansion of the MISSE-X user community through incorporation of new, customer-desired capabilities. MISSE-X will also foster interest in science, technology, engineering, and math (STEM) in primary and secondary schools through student collaboration and participation.1,2

A Solution to ``Too Big to Fail''

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2016-10-01

Its a tricky business to reconcile simulations of our galaxys formation with our current observations of the Milky Way and its satellites. In a recent study, scientists have addressed one discrepancy between simulations and observations: the so-called to big to fail problem.From Missing Satellites to Too Big to FailThe favored model of the universe is the lambda-cold-dark-matter (CDM) cosmological model. This model does a great job of correctly predicting the large-scale structure of the universe, but there are still a few problems with it on smaller scales.Hubble image of UGC 5497, a dwarf galaxy associated with Messier 81. In the missing satellite problem, simulations of galaxy formation predict that there should be more such satellite galaxies than we observe. [ESA/NASA]The first is the missing satellites problem: CDM cosmology predicts that galaxies like the Milky Way should have significantly more satellite galaxies than we observe. A proposed solution to this problem is the argument that there may exist many more satellites than weve observed, but these dwarf galaxies have had their stars stripped from them during tidal interactions which prevents us from being able to see them.This solution creates a new problem, though: the too big to fail problem. This problem states that many of the satellites predicted by CDM cosmology are simply so massive that theres no way they couldnt have visible stars. Another way of looking at it: the observed satellites of the Milky Way are not massive enough to be consistent with predictions from CDM.Artists illustration of a supernova, a type of stellar feedback that can modify the dark-matter distribution of a satellite galaxy. [NASA/CXC/M. Weiss]Density Profiles and Tidal StirringLed by Mihai Tomozeiu (University of Zurich), a team of scientists has published a study in which they propose a solution to the too big to fail problem. By running detailed cosmological zoom simulations of our galaxys formation, Tomozeiu and collaborators modeled the dark matter and the stellar content of the galaxy, tracking the formation and evolution of dark-matter subhalos.Based on the results of their simulations, the team argues that the too big to fail problem can be resolved by combining two effects:Stellar feedback in a satellite galaxy can modify its dark-matter distribution, lowering the dark-matter density in the galaxys center and creating a shallower density profile. Satellites with such shallow density profiles evolve differently than those typically modeled, which have a high concentration of dark matter in their centers.After these satellites fall into the Milky Ways potential, tidal effects such as shocks and stripping modify the mass distribution of both the dark matter and the baryons even further.Each curve represents a simulated satellites circular velocity (which corresponds to its total mass) at z=0. Left: results using typical dark-matter density profiles. Right: results using the shallower profiles expected when stellar feedback is included. Results from the shallower profiles are consistent with observed Milky-Way satellites(black crosses). [Adapted from Tomozeiu et al. 2016]A Match to ObservationsTomozeiu and collaborators found that when they used traditional density profiles to model the satellites, the satellites at z=0 in the simulation were much larger than those we observe around the Milky Way consistent with the too big to fail problem.When the team used shallower density profiles and took into account tidal effects, however, the simulations produced a distribution of satellites at z=0 that is consistent with what we observe.This study provides a tidy potential solution to the too big to fail problem, further strengthening the support for CDM cosmology.CitationMihai Tomozeiu et al 2016 ApJ 827 L15. doi:10.3847/2041-8205/827/1/L15

Is Spending More Time Associated With Less Missed Care?: A Comparison of Time Use and Missed Care Across 15 Nursing Units at 2 Hospitals.

PubMed

McNair, Norma; Baird, Jennifer; Grogan, Tristan R; Walsh, Catherine M; Liang, Li-Jung; Worobel-Luk, Pamela; Needleman, Jack; Nuckols, Teryl K

2016-09-01

The aim of this study is to examine the relationship between nursing time use and perceptions of missed care. Recent literature has highlighted the problem of missed nursing care, but little is known about how nurses' time use patterns are associated with reports of missed care. In 15 nursing units at 2 hospitals, we assessed registered nurse (RN) perceptions of missed care, observed time use by RNs, and examined the relationship between time spent and degree of missed care at the nursing unit level. Patterns of time use were similar across hospitals, with 25% of time spent on documentation. For 6 different categories of nursing tasks, no association was detected between time use, including time spent on documentation, and the degree of missed care at the nursing unit level. Nursing time use cannot fully explain variation in missed care across nursing units. Further work is needed to account for patterns of missed care.

Considerations of multiple imputation approaches for handling missing data in clinical trials.

PubMed

Quan, Hui; Qi, Li; Luo, Xiaodong; Darchy, Loic

2018-07-01

Missing data exist in all clinical trials and missing data issue is a very serious issue in terms of the interpretability of the trial results. There is no universally applicable solution for all missing data problems. Methods used for handling missing data issue depend on the circumstances particularly the assumptions on missing data mechanisms. In recent years, if the missing at random mechanism cannot be assumed, conservative approaches such as the control-based and returning to baseline multiple imputation approaches are applied for dealing with the missing data issues. In this paper, we focus on the variability in data analysis of these approaches. As demonstrated by examples, the choice of the variability can impact the conclusion of the analysis. Besides the methods for continuous endpoints, we also discuss methods for binary and time to event endpoints as well as consideration for non-inferiority assessment. Copyright © 2018. Published by Elsevier Inc.

The Effect of a Brief Acceptance and Commitment Therapy Intervention on the Near-Miss Effect in Problem Gamblers

ERIC Educational Resources Information Center

Nastally, Becky L.; Dixon, Mark R.

2012-01-01

In the current study, 3 participants with a history of problem gambling were exposed to computerized slot machine play consisting of outcomes that depicted wins, losses, and near misses (2 out of 3 identical slot machine symbols). Participants were asked to rate each type of outcome in terms of its closeness to a win on a scale of 1 to 10 before…

Top-quark mass measurement using events with missing transverse energy and jets at CDF

DOE PAGES

Aaltonen, T.

2011-11-30

We present a measurement of the top-quark mass with tt events using a data sample corresponding to an integrated luminosity of 5.7 fb -1 of pp collisions at the Fermilab Tevatron with √s = 1.96 TeV and collected by the CDF II Detector. We select events having no identified charged leptons, large missing transverse energy, and four, five, or six jets with at least one jet containing a secondary vertex consistent with the decay of a b quark. This analysis considers events from the semileptonic tt decay channel, including events that contain tau leptons, which are usually not includedmore » in the top-quark mass measurements. The measurement uses as kinematic variables the invariant mass of two jets consistent with the mass of the W boson, and the invariant masses of two different three-jet combinations. We fit the data to signal templates of varying top-quark masses and background templates, and measure a top-quark mass of M top = 172.3 ± 2.4 (stat) ± 1.0 (syst) GeV/c 2.« less

Children's food store, restaurant, and home food environments and their relationship with body mass index: a pilot study.

PubMed

Holsten, Joanna E; Compher, Charlene W

2012-01-01

This pilot research assessed the feasibility and utility of a study designed to examine the relationship between children's BMI and food store, restaurant, and home food environments. Home visits were conducted with sixth-grade children (N = 12). BMI z-scores were calculated with weight and height measurements. Nutrition Environment Measures Surveys evaluated children's food environments. The study protocol involved a feasible time duration, minimal missing data for primary variables, and participant satisfaction. Potential design problems included the homogeneous store environments and low restaurant exposure of the sample recruited from one school, and the adequacy of a single cross-sectional measure of the home environment.

Los Alamos Science, Number 25 -- 1997: Celebrating the neutrino

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

Cooper, N.G.

1997-12-31

This issue is devoted to the neutrino and its remaining mysteries. It is divided into the following areas: (1) The Reines-Cowan experiment -- detecting the poltergeist; (2) The oscillating neutrino -- an introduction to neutrino masses and mixing; (3) A brief history of neutrino experiments at LAMPF; (4) A thousand eyes -- the story of LSND (Los Alamos neutrino oscillation experiment); (5) The evidence for oscillations; (6) The nature of neutrinos in muon decay and physics beyond the Standard Model; (7) Exorcising ghosts -- in pursuit of the missing solar neutrinos; (8) MSW -- a possible solution to the solarmore » neutrino problem; (8) Neutrinos and supernovae; and (9) Dark matter and massive neutrinos.« less

Surface brightness and color distributions in blue compact dwarf galaxies. I - Haro 2, an extreme example of a star-forming young elliptical galaxy

NASA Technical Reports Server (NTRS)

Loose, Hans-Hermann; Thuan, Trinh X.

1986-01-01

The first results of a large-scale program to study the morphology and structure of blue compact dwarf galaxies from CCD observations are presented. The observations and reduction procedures are described, and surface brightness and color profiles are shown. The results are used to discuss the morphological type of Haro 2 and its stellar populations. It is found that Haro 2 appears to be an extreme example of an elliptical galaxy undergoing intense star formation in its central regions, and that the oldest stars it contains were made only about four million yr ago. The 'missing' mass problem of Haro 2 is also discussed.

Search for top squarks in final states with one isolated lepton, jets, and missing transverse momentum in √{s }=13 TeV p p collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. 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B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Vallecorsa, S.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2016-09-01

The results of a search for the top squark, the supersymmetric partner of the top quark, in final states with one isolated electron or muon, jets, and missing transverse momentum are reported. The search uses the 2015 LHC p p collision data at a center-of-mass energy of √{s }=13 TeV recorded by the ATLAS detector and corresponding to an integrated luminosity of 3.2 fb-1 . The analysis targets two types of signal models: gluino-mediated pair production of top squarks with a nearly mass-degenerate top squark and neutralino and direct pair production of top squarks, decaying to the top quark and the lightest neutralino. The experimental signature in both signal scenarios is similar to that of a top quark pair produced in association with large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits on gluino and top squark masses are set at 95% confidence level. The results extend the LHC run-1 exclusion limit on the gluino mass up to 1460 GeV in the gluino-mediated scenario in the high gluino and low top squark mass region and add an excluded top squark mass region from 745 to 780 GeV for the direct top squark model with a massless lightest neutralino. The results are also reinterpreted to set exclusion limits in a model of vectorlike top quarks.

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

Search for New Physics in a Final State with Same-Sign Dileptons, Jets, and Missing Transverse Energy at 7 TeV Center of Mass Energy

NASA Astrophysics Data System (ADS)

Ghiglieri, Jacopo

We report on a search for new physics in a final state with two same sign leptons, missing transverse energy, and significant hadronic activity at a center of mass energy sqrt(s) = 7 TeV. The data were collected with the CMS detector at the CERN LHC and correspond to an integrated luminosity of 0.98 inverse femtobarns. Data-driven methods are developed to estimate the dominant Standard Model backgrounds. No evidence for new physics is observed. The dominant background to the analysis comes from failures of lepton identification in Standard Model ttbar events. The ttbar production cross section in the dilepton final state is measured using 3.1 inverse picobarns of data. The cross section is measured to be 194 +/- 72 (stat) +/- 24 (syst) +/- 21 (lumi) pb. An algorithm is developed that uses tracking information to improve the reconstruction of missing transverse energy. The reconstruction of missing transverse energy is commissioned using the first collisions recorded at 0.9, 2.36 and 7 TeV data. Events with abnormally large values of missing transverse energy are identified as arising from anomalous signals in the calorimeters. Tools are developed to identify and remove these anomalous signals.

The Impact of the Nursing Practice Environment on Missed Nursing Care.

PubMed

Hessels, Amanda J; Flynn, Linda; Cimiotti, Jeannie P; Cadmus, Edna; Gershon, Robyn R M

2015-12-01

Missed nursing care is an emerging problem negatively impacting patient outcomes. There are gaps in our knowledge of factors associated with missed nursing care. The aim of this study was to determine the relationship between the nursing practice environment and missed nursing care in acute care hospitals. This is a secondary analysis of cross sectional data from a survey of over 7.000 nurses from 70 hospitals on workplace and process of care. Ordinary least squares and multiple regression models were constructed to examine the relationship between the nursing practice environment and missed nursing care while controlling for characteristics of nurses and hospitals. Nurses missed delivering a significant amount of necessary patient care (10-27%). Inadequate staffing and inadequate resources were the practice environment factors most strongly associated with missed nursing care events. This multi-site study examined the risk and risk factors associated with missed nursing care. Improvements targeting modifiable risk factors may reduce the risk of missed nursing care.

Stop the top background of the stop search

NASA Astrophysics Data System (ADS)

Bai, Yang; Cheng, Hsin-Chia; Gallicchio, Jason; Gu, Jiayin

2012-07-01

The main background for the supersymmetric stop direct production search comes from Standard Model toverline t events. For the single-lepton search channel, we introduce a few kinematic variables to further suppress this background by focusing on its dileptonic and semileptonic topologies. All are defined to have end points in the background, but not signal distributions. They can substantially improve the stop signal significance and mass reach when combined with traditional kinematic variables such as the total missing transverse energy. Among them, our variable M_{{T2}}^W hasthebestoverallperformancebecause it uses all available kinematic information, including the on-shell mass of both W's. We see 20 %-30 % improvement on the discovery significance and estimate that the 8 TeV LHC run with 20 fb-1 of data would be able to reach an exclusion limit of 650-700 GeV for direct stop production, as long as the stop decays dominantly to the top quark and a light stable neutralino. Most of the mass range required for the supersymmetric solution of the naturalness problem in the standard scenario can be covered.

Outgassing history of Venus and the absence of water on Venus

NASA Technical Reports Server (NTRS)

Zhang, Youxue; Zindler, Alan

1992-01-01

Similarities in the size and mean density of Earth and Venus encourage the use of Earth-analogue models for the evolution of Venus. However, the amount of water in the present Venus atmosphere is miniscule compared to Earth's oceans. The 'missing' water is thus one of the most significant problems related to the origin and evolution of Venus. Other researchers proposed that Venus accreted with less water, but this was challenged. The high D/H ratio in Venus' atmosphere is consistent with an earlier water mass more than 100 times higher than at present conditions and is often cited to support a 'wet' Venus, but this amounts to only 0.01 to 0.1 percent of the water in terrestrial oceans and the high D/H ratio on Venus could easily reflect cometary injection. Nevertheless, many authors begin with the premise that Venus once had an oceanlike water mass on its surface, and investigate the many possible mechanisms that might account for its loss. In this paper we propose that Venus degassed to lower degree than the Earth and never had an oceanlike surface water mass.

Middleweight black holes found at last

NASA Astrophysics Data System (ADS)

Clery, Daniel

2018-06-01

How did giant black holes grow so big? Astronomers have long had evidence of baby black holes with masses of no more than tens of suns, and of million- or billion-solar-mass behemoths lurking at the centers of galaxies. But middle-size ones, weighing thousands or tens of thousands of suns, seemed to be missing. Their absence forced theorists to propose that supermassive black holes didn't grow gradually by slowly consuming matter, but somehow emerged as ready-made giants. Now, astronomers appear to have located some missing middleweights. An international team has scoured an archive of galaxy spectra and found more than 300 small galaxies that have the signature of intermediate mass black holes in their cores, opening new questions for theorists.

Landscape of supersymmetric particle mass hierarchies and their signature space at the CERN Large Hadron Collider.

PubMed

Feldman, Daniel; Liu, Zuowei; Nath, Pran

2007-12-21

The minimal supersymmetric standard model with soft breaking has a large landscape of supersymmetric particle mass hierarchies. This number is reduced significantly in well-motivated scenarios such as minimal supergravity and alternatives. We carry out an analysis of the landscape for the first four lightest particles and identify at least 16 mass patterns, and provide benchmarks for each. We study the signature space for the patterns at the CERN Large Hadron Collider by analyzing the lepton+ (jet> or =2) + missing P{T} signals with 0, 1, 2, and 3 leptons. Correlations in missing P{T} are also analyzed. It is found that even with 10 fb{-1} of data a significant discrimination among patterns emerges.

Application of a novel hybrid method for spatiotemporal data imputation: A case study of the Minqin County groundwater level

NASA Astrophysics Data System (ADS)

Zhang, Zhongrong; Yang, Xuan; Li, Hao; Li, Weide; Yan, Haowen; Shi, Fei

2017-10-01

The techniques for data analyses have been widely developed in past years, however, missing data still represent a ubiquitous problem in many scientific fields. In particular, dealing with missing spatiotemporal data presents an enormous challenge. Nonetheless, in recent years, a considerable amount of research has focused on spatiotemporal problems, making spatiotemporal missing data imputation methods increasingly indispensable. In this paper, a novel spatiotemporal hybrid method is proposed to verify and imputed spatiotemporal missing values. This new method, termed SOM-FLSSVM, flexibly combines three advanced techniques: self-organizing feature map (SOM) clustering, the fruit fly optimization algorithm (FOA) and the least squares support vector machine (LSSVM). We employ a cross-validation (CV) procedure and FOA swarm intelligence optimization strategy that can search available parameters and determine the optimal imputation model. The spatiotemporal underground water data for Minqin County, China, were selected to test the reliability and imputation ability of SOM-FLSSVM. We carried out a validation experiment and compared three well-studied models with SOM-FLSSVM using a different missing data ratio from 0.1 to 0.8 in the same data set. The results demonstrate that the new hybrid method performs well in terms of both robustness and accuracy for spatiotemporal missing data.

Simulation-based sensitivity analysis for non-ignorably missing data.

PubMed

Yin, Peng; Shi, Jian Q

2017-01-01

Sensitivity analysis is popular in dealing with missing data problems particularly for non-ignorable missingness, where full-likelihood method cannot be adopted. It analyses how sensitively the conclusions (output) may depend on assumptions or parameters (input) about missing data, i.e. missing data mechanism. We call models with the problem of uncertainty sensitivity models. To make conventional sensitivity analysis more useful in practice we need to define some simple and interpretable statistical quantities to assess the sensitivity models and make evidence based analysis. We propose a novel approach in this paper on attempting to investigate the possibility of each missing data mechanism model assumption, by comparing the simulated datasets from various MNAR models with the observed data non-parametrically, using the K-nearest-neighbour distances. Some asymptotic theory has also been provided. A key step of this method is to plug in a plausibility evaluation system towards each sensitivity parameter, to select plausible values and reject unlikely values, instead of considering all proposed values of sensitivity parameters as in the conventional sensitivity analysis method. The method is generic and has been applied successfully to several specific models in this paper including meta-analysis model with publication bias, analysis of incomplete longitudinal data and mean estimation with non-ignorable missing data.

A novel approach for incremental uncertainty rule generation from databases with missing values handling: application to dynamic medical databases.

PubMed

Konias, Sokratis; Chouvarda, Ioanna; Vlahavas, Ioannis; Maglaveras, Nicos

2005-09-01

Current approaches for mining association rules usually assume that the mining is performed in a static database, where the problem of missing attribute values does not practically exist. However, these assumptions are not preserved in some medical databases, like in a home care system. In this paper, a novel uncertainty rule algorithm is illustrated, namely URG-2 (Uncertainty Rule Generator), which addresses the problem of mining dynamic databases containing missing values. This algorithm requires only one pass from the initial dataset in order to generate the item set, while new metrics corresponding to the notion of Support and Confidence are used. URG-2 was evaluated over two medical databases, introducing randomly multiple missing values for each record's attribute (rate: 5-20% by 5% increments) in the initial dataset. Compared with the classical approach (records with missing values are ignored), the proposed algorithm was more robust in mining rules from datasets containing missing values. In all cases, the difference in preserving the initial rules ranged between 30% and 60% in favour of URG-2. Moreover, due to its incremental nature, URG-2 saved over 90% of the time required for thorough re-mining. Thus, the proposed algorithm can offer a preferable solution for mining in dynamic relational databases.

Consequences of severe obstetric complications on women's health in Morocco: please, listen to me!

PubMed

Assarag, Bouchra; Dujardin, Bruno; Essolbi, Amina; Cherkaoui, Imad; De Brouwere, Vincent

2015-11-01

In Morocco, medical care for women with severe obstetric complications (near-miss cases) ends at discharge from the hospital. Little information exists regarding what happens after returning home. The aim of the study was to assess the physical and mental health consequences of near-miss events on Moroccan women 8 months after childbirth. A prospective cohort study of 76 near-miss women was conducted in three hospitals. For every case, we recruited at least two women from the same hospital who had uncomplicated deliveries (n = 169). We used a mixed-methods approach. For the quantitative part, we analysed sociodemographic characteristics collected via a questionnaire and medical complications extracted from the medical records during a medical consultation at 8 months post-partum. Forty in-depth interviews were also conducted with 20 near-miss cases and 20 women with uncomplicated deliveries. The near-miss women were poorer and less educated than those who had uncomplicated deliveries. The proportion of physical consequences (serious illness) was higher among near-miss cases (22%) than uncomplicated deliveries (6%, P = 0.001). The risk of depression was significantly higher among near-miss cases with perinatal death (OR = 7.16; [95% CI: 2.85-17.98]) than among those who had an uncomplicated delivery. Interviews revealed that the economic burden of near-miss care contributed to social problems among the women and their households. A near-miss event has consequences that go beyond the first days after delivery. Developing new mechanisms for maternal and newborn health follow-up is essential and should address the mother's physical and mental health problems and involve husbands and family members. © 2015 The Authors. Tropical Medicine & International Health Published by John Wiley & Sons Ltd.

Data Quality and Reliability Analysis of U.S. Marine Corps Ground Vehicle Maintenance Records

DTIC Science & Technology

2015-06-01

Corporation conducted a study on data quality issues present in U. S. Army logistics data ( Galway & Hanks, 1996). The study breaks data issues into three...categories: operational, conceptual, and organizational problems ( Galway & Hanks, 1996). Operational data problems relate to the number of missing or...codes (EIC) are left blank ( Galway & Hanks, 1996, p. 26). Missing entries are attributed to an assumed lack of significance of the EIC. The issue is

Atomic Oxygen Erosion Yield Prediction for Spacecraft Polymers in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Backus, Jane A.; Manno, Michael V.; Waters, Deborah L.; Cameron, Kevin C.; deGroh, Kim K.

2009-01-01

The ability to predict the atomic oxygen erosion yield of polymers based on their chemistry and physical properties has been only partially successful because of a lack of reliable low Earth orbit (LEO) erosion yield data. Unfortunately, many of the early experiments did not utilize dehydrated mass loss measurements for erosion yield determination, and the resulting mass loss due to atomic oxygen exposure may have been compromised because samples were often not in consistent states of dehydration during the pre-flight and post-flight mass measurements. This is a particular problem for short duration mission exposures or low erosion yield materials. However, as a result of the retrieval of the Polymer Erosion and Contamination Experiment (PEACE) flown as part of the Materials International Space Station Experiment 2 (MISSE 2), the erosion yields of 38 polymers and pyrolytic graphite were accurately measured. The experiment was exposed to the LEO environment for 3.95 years from August 16, 2001 to July 30, 2005 and was successfully retrieved during a space walk on July 30, 2005 during Discovery s STS-114 Return to Flight mission. The 40 different materials tested (including Kapton H fluence witness samples) were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The MISSE 2 PEACE Polymers experiment used carefully dehydrated mass measurements, as well as accurate density measurements to obtain accurate erosion yield data for high-fluence (8.43 1021 atoms/sq cm). The resulting data was used to develop an erosion yield predictive tool with a correlation coefficient of 0.895 and uncertainty of +/-6.3 10(exp -25)cu cm/atom. The predictive tool utilizes the chemical structures and physical properties of polymers to predict in-space atomic oxygen erosion yields. A predictive tool concept (September 2009 version) is presented which represents an improvement over an earlier (December 2008) version.

Spectroscopic Study of L Hypernuclei with Electron Beams at Jefferson Lab

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

Nakamura, Satoshi; Gogami, Toshiyuki; Tang, Liguang

The missing mass spectroscopy of L hypernuclei with the (e, e'K^+) reaction was started from 2000 at Jefferson Lab. In this fifteen years, various hypernuclei (A = 7 - 52) including hyperon (L, S^0) productions have been studied with newly developed experimental techniques. The (e, e'K^+) reaction spectroscopy of L hypernuclei features its capability of absolute missing mass calibration and production of new species of hypernuclei which are the isospin partners of well studied hypernuclei by (K^-, pi-) and (pi^+, K^+) reactions. In this paper, we will review how we established the (e, e'K^+) spectroscopic study of hypernuclei.

Causal inference with missing exposure information: Methods and applications to an obstetric study.

PubMed

Zhang, Zhiwei; Liu, Wei; Zhang, Bo; Tang, Li; Zhang, Jun

2016-10-01

Causal inference in observational studies is frequently challenged by the occurrence of missing data, in addition to confounding. Motivated by the Consortium on Safe Labor, a large observational study of obstetric labor practice and birth outcomes, this article focuses on the problem of missing exposure information in a causal analysis of observational data. This problem can be approached from different angles (i.e. missing covariates and causal inference), and useful methods can be obtained by drawing upon the available techniques and insights in both areas. In this article, we describe and compare a collection of methods based on different modeling assumptions, under standard assumptions for missing data (i.e. missing-at-random and positivity) and for causal inference with complete data (i.e. no unmeasured confounding and another positivity assumption). These methods involve three models: one for treatment assignment, one for the dependence of outcome on treatment and covariates, and one for the missing data mechanism. In general, consistent estimation of causal quantities requires correct specification of at least two of the three models, although there may be some flexibility as to which two models need to be correct. Such flexibility is afforded by doubly robust estimators adapted from the missing covariates literature and the literature on causal inference with complete data, and by a newly developed triply robust estimator that is consistent if any two of the three models are correct. The methods are applied to the Consortium on Safe Labor data and compared in a simulation study mimicking the Consortium on Safe Labor. © The Author(s) 2013.

Search for physics beyond the standard model in events with high-momentum Higgs bosons and missing transverse momentum in proton-proton collisions at 13 TeV

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

Sirunyan, Albert M; et al.

A search for physics beyond the standard model in events with one or more high-momentum Higgs bosons, H, decaying to pairs of b quarks in association with missing transverse momentum is presented. The data, corresponding to an integrated luminosity of 35.9 fbmore » $$^{-1}$$, were collected with the CMS detector at the LHC in proton-proton collisions at the center-of-mass energy $$\\sqrt{s}=$$ 13 TeV. The analysis utilizes a new b quark tagging technique based on jet substructure to identify jets from H$$\\to$$bb. Events are categorized by the multiplicity of H-tagged jets, jet mass, and the missing transverse momentum. No significant deviation from standard model expectations is observed. In the context of supersymmetry (SUSY), limits on the cross sections of pair-produced gluinos are set, assuming that gluinos decay to quark pairs, H (or Z), and the lightest SUSY particle, LSP, through an intermediate next-to-lightest SUSY particle, NLSP. With large mass splitting between the NLSP and LSP, and 100% NLSP branching fraction to H, the lower limit on the gluino mass is found to be 2010 GeV.« less

Search for Physics Beyond the Standard Model in Events with High-Momentum Higgs Bosons and Missing Transverse Momentum in Proton-Proton Collisions at 13 TeV

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

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

Here, a search for physics beyond the standard model in events with one or more high-momentum Higgs bosons, H, decaying to pairs of b quarks in association with missing transverse momentum is presented. The data, corresponding to an integrated luminosity of 35.9 fb -1, were collected with the CMS detector at the LHC in proton-proton collisions at the center-of-mass energy √s = 13 TeV. The analysis utilizes a new b quark tagging technique based on jet substructure to identify jets from H → bb¯. Events are categorized by the multiplicity of H-tagged jets, jet mass, and the missing transverse momentum.more » No significant deviation from standard model expectations is observed. In the context of supersymmetry (SUSY), limits on the cross sections of pair-produced gluinos are set, assuming that gluinos decay to quark pairs, H (or Z), and the lightest SUSY particle, LSP, through an intermediate next-to-lightest SUSY particle, NLSP. With large mass splitting between the NLSP and LSP, and 100% NLSP branching fraction to H, the lower limit on the gluino mass is found to be 2010 GeV.« less

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

DOE PAGES

Khachatryan, Vardan

2015-05-22

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

Search for Physics Beyond the Standard Model in Events with High-Momentum Higgs Bosons and Missing Transverse Momentum in Proton-Proton Collisions at 13 TeV.

PubMed

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2018-06-15

A search for physics beyond the standard model in events with one or more high-momentum Higgs bosons, H, decaying to pairs of b quarks in association with missing transverse momentum is presented. The data, corresponding to an integrated luminosity of 35.9  fb^{-1}, were collected with the CMS detector at the LHC in proton-proton collisions at the center-of-mass energy sqrt[s]=13  TeV. The analysis utilizes a new b quark tagging technique based on jet substructure to identify jets from H→bb[over ¯]. Events are categorized by the multiplicity of H-tagged jets, jet mass, and the missing transverse momentum. No significant deviation from standard model expectations is observed. In the context of supersymmetry (SUSY), limits on the cross sections of pair-produced gluinos are set, assuming that gluinos decay to quark pairs, H (or Z), and the lightest SUSY particle, LSP, through an intermediate next-to-lightest SUSY particle, NLSP. With large mass splitting between the NLSP and LSP, and 100% NLSP branching fraction to H, the lower limit on the gluino mass is found to be 2010 GeV.

Search for Physics Beyond the Standard Model in Events with High-Momentum Higgs Bosons and Missing Transverse Momentum in Proton-Proton Collisions at 13 TeV

DOE PAGES

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

2018-06-11

Here, a search for physics beyond the standard model in events with one or more high-momentum Higgs bosons, H, decaying to pairs of b quarks in association with missing transverse momentum is presented. The data, corresponding to an integrated luminosity of 35.9 fb -1, were collected with the CMS detector at the LHC in proton-proton collisions at the center-of-mass energy √s = 13 TeV. The analysis utilizes a new b quark tagging technique based on jet substructure to identify jets from H → bb¯. Events are categorized by the multiplicity of H-tagged jets, jet mass, and the missing transverse momentum.more » No significant deviation from standard model expectations is observed. In the context of supersymmetry (SUSY), limits on the cross sections of pair-produced gluinos are set, assuming that gluinos decay to quark pairs, H (or Z), and the lightest SUSY particle, LSP, through an intermediate next-to-lightest SUSY particle, NLSP. With large mass splitting between the NLSP and LSP, and 100% NLSP branching fraction to H, the lower limit on the gluino mass is found to be 2010 GeV.« less

Counting missing values in a metabolite-intensity data set for measuring the analytical performance of a metabolomics platform.

PubMed

Huan, Tao; Li, Liang

2015-01-20

Metabolomics requires quantitative comparison of individual metabolites present in an entire sample set. Unfortunately, missing intensity values in one or more samples are very common. Because missing values can have a profound influence on metabolomic results, the extent of missing values found in a metabolomic data set should be treated as an important parameter for measuring the analytical performance of a technique. In this work, we report a study on the scope of missing values and a robust method of filling the missing values in a chemical isotope labeling (CIL) LC-MS metabolomics platform. Unlike conventional LC-MS, CIL LC-MS quantifies the concentration differences of individual metabolites in two comparative samples based on the mass spectral peak intensity ratio of a peak pair from a mixture of differentially labeled samples. We show that this peak-pair feature can be explored as a unique means of extracting metabolite intensity information from raw mass spectra. In our approach, a peak-pair peaking algorithm, IsoMS, is initially used to process the LC-MS data set to generate a CSV file or table that contains metabolite ID and peak ratio information (i.e., metabolite-intensity table). A zero-fill program, freely available from MyCompoundID.org , is developed to automatically find a missing value in the CSV file and go back to the raw LC-MS data to find the peak pair and, then, calculate the intensity ratio and enter the ratio value into the table. Most of the missing values are found to be low abundance peak pairs. We demonstrate the performance of this method in analyzing an experimental and technical replicate data set of human urine metabolome. Furthermore, we propose a standardized approach of counting missing values in a replicate data set as a way of gauging the extent of missing values in a metabolomics platform. Finally, we illustrate that applying the zero-fill program, in conjunction with dansylation CIL LC-MS, can lead to a marked improvement in finding significant metabolites that differentiate bladder cancer patients and their controls in a metabolomics study of 109 subjects.

Top-quark mass measurement using events with missing transverse energy and jets at CDF.

PubMed

Aaltonen, T; Álvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Apresyan, A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Auerbach, B; Aurisano, A; Azfar, F; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauce, M; Bauer, G; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Bland, K R; Blumenfeld, B; Bocci, A; Bodek, A; Bortoletto, D; Boudreau, J; Boveia, A; Brigliadori, L; Brisuda, A; Bromberg, C; Brucken, E; Bucciantonio, M; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clarke, C; Compostella, G; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Dagenhart, D; d'Ascenzo, N; Datta, M; de Barbaro, P; De Cecco, S; De Lorenzo, G; Dell'Orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Devoto, F; d'Errico, M; Di Canto, A; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, M; Dorigo, T; Ebina, K; Elagin, A; Eppig, A; Erbacher, R; Errede, D; Errede, S; Ershaidat, N; Eusebi, R; Fang, H C; Farrington, S; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Funakoshi, Y; Furic, I; Gallinaro, M; Galyardt, J; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Grinstein, S; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, S R; Halkiadakis, E; Hamaguchi, A; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harr, R F; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Hewamanage, S; Hidas, D; Hocker, A; Hopkins, W; Horn, D; Hou, S; Hughes, R E; Hurwitz, M; Husemann, U; Hussain, N; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirby, M; Klimenko, S; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kuhr, T; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; LeCompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lin, C-J; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maeshima, K; Makhoul, K; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Martínez, M; Martínez-Ballarín, R; Mastrandrea, P; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Paramonov, A A; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Poukhov, O; Prokoshin, F; Pronko, A; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Rescigno, M; Riddick, T; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rubbo, F; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Safonov, A; Sakumoto, W K; Sakurai, Y; Santi, L; Sartori, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shreyber, I; Simonenko, A; Sinervo, P; Sissakian, A; Sliwa, K; Smith, J R; Snider, F D; Soha, A; Somalwar, S; Sorin, V; Squillacioti, P; Stancari, M; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Tu, Y; Ukegawa, F; Uozumi, S; Varganov, A; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wagner, R L; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Wick, F; Williams, H H; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, H; Wright, T; Wu, X; Wu, Z; Yamamoto, K; Yamaoka, J; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zucchelli, S

2011-12-02

We present a measurement of the top-quark mass using a sample of t ̄t events in 5.7 fb(-1) of integrated luminosity from p ̄p collisions at the Fermilab Tevatron with √s=1.96 TeV and collected by the CDF II Detector. We select events having large missing transverse energy, and four, five, or six jets with at least one jet tagged as coming from a b quark, and reject events with identified charged leptons. This analysis considers events from the semileptonic t ̄t decay channel, including events that contain tau leptons. The measurement is based on a multidimensional template method. We fit the data to signal templates of varying top-quark masses and background templates, and measure a top-quark mass of M(top)=172.32±2.4(stat)±1.0(syst)  GeV/c(2). © 2011 American Physical Society

A complete solution classification and unified algorithmic treatment for the one- and two-step asymmetric S-transverse mass event scale statistic

NASA Astrophysics Data System (ADS)

Walker, Joel W.

2014-08-01

The M T2, or "s-transverse mass", statistic was developed to associate a parent mass scale to a missing transverse energy signature, given that escaping particles are generally expected in pairs, while collider experiments are sensitive to just a single transverse momentum vector sum. This document focuses on the generalized extension of that statistic to asymmetric one- and two-step decay chains, with arbitrary child particle masses and upstream missing transverse momentum. It provides a unified theoretical formulation, complete solution classification, taxonomy of critical points, and technical algorithmic prescription for treatment of the event scale. An implementation of the described algorithm is available for download, and is also a deployable component of the author's selection cut software package AEAC uS (Algorithmic Event Arbiter and C ut Selector). appendices address combinatoric event assembly, algorithm validation, and a complete pseudocode.

Accounting for missing data in the estimation of contemporary genetic effective population size (N(e) ).

PubMed

Peel, D; Waples, R S; Macbeth, G M; Do, C; Ovenden, J R

2013-03-01

Theoretical models are often applied to population genetic data sets without fully considering the effect of missing data. Researchers can deal with missing data by removing individuals that have failed to yield genotypes and/or by removing loci that have failed to yield allelic determinations, but despite their best efforts, most data sets still contain some missing data. As a consequence, realized sample size differs among loci, and this poses a problem for unbiased methods that must explicitly account for random sampling error. One commonly used solution for the calculation of contemporary effective population size (N(e) ) is to calculate the effective sample size as an unweighted mean or harmonic mean across loci. This is not ideal because it fails to account for the fact that loci with different numbers of alleles have different information content. Here we consider this problem for genetic estimators of contemporary effective population size (N(e) ). To evaluate bias and precision of several statistical approaches for dealing with missing data, we simulated populations with known N(e) and various degrees of missing data. Across all scenarios, one method of correcting for missing data (fixed-inverse variance-weighted harmonic mean) consistently performed the best for both single-sample and two-sample (temporal) methods of estimating N(e) and outperformed some methods currently in widespread use. The approach adopted here may be a starting point to adjust other population genetics methods that include per-locus sample size components. © 2012 Blackwell Publishing Ltd.

MSFC Thermal Protection System Materials on MISSE-6

NASA Technical Reports Server (NTRS)

Finckenor, Miria M.; Valentine, Peter G.; Gubert, Michael K.

2010-01-01

The Lightweight Nonmetallic Thermal Protection Materials Technology (LNTPMT) program studied a number of ceramic matrix composites, ablator materials, and tile materials for durability in simulated space environment. Materials that indicated low atomic oxygen reactivity and negligible change in thermo-optical properties in ground testing were selected to fly on the Materials on International Space Station Experiment (MISSE)-6. These samples were exposed for 17 months to the low Earth orbit environment on both the ram and wake sides of MISSE-6B. Thermo-optical properties are discussed, along with any changes in mass.

Replacing missing values using trustworthy data values from web data sources

NASA Astrophysics Data System (ADS)

Izham Jaya, M.; Sidi, Fatimah; Mat Yusof, Sharmila; Suriani Affendey, Lilly; Ishak, Iskandar; Jabar, Marzanah A.

2017-09-01

In practice, collected data usually are incomplete and contains missing value. Existing approaches in managing missing values overlook the importance of trustworthy data values in replacing missing values. In view that trusted completed data is very important in data analysis, we proposed a framework of missing value replacement using trustworthy data values from web data sources. The proposed framework adopted ontology to map data values from web data sources to the incomplete dataset. As data from web is conflicting with each other, we proposed a trust score measurement based on data accuracy and data reliability. Trust score is then used to select trustworthy data values from web data sources for missing values replacement. We successfully implemented the proposed framework using financial dataset and presented the findings in this paper. From our experiment, we manage to show that replacing missing values with trustworthy data values is important especially in a case of conflicting data to solve missing values problem.

Transitioning to multiple imputation : a new method to impute missing blood alcohol concentration (BAC) values in FARS

DOT National Transportation Integrated Search

2002-01-01

The National Center for Statistics and Analysis (NCSA) of the National Highway Traffic Safety : Administration (NHTSA) has undertaken several approaches to remedy the problem of missing blood alcohol : test results in the Fatality Analysis Reporting ...

Detection of damaged supports under railway track based on frequency shift

NASA Astrophysics Data System (ADS)

Wang, Longqi; Zhang, Yao; Lie, Seng Tjhen

2017-03-01

In railway transportation systems, the tracks are usually fastened on sleepers which are supported by the ballast. A lot of research has been conducted to guarantee the safety of railway track because of its importance, and more concern is expressed about monitoring of track itself such as railway level and alignment. The ballast and fasteners which provide strong support to the railway track are important as well whereas the detection of loose or missing fasteners and damaged ballast mainly relies on visual inspection. Although it is reliable when the fastener is missing and the damaged ballast is on the surface, it provides less help if the fastener is only loose and the damaged ballast is under the sleepers, which are however frequently observed in practice. This paper proposes an approach based on frequency shift to identify the damaged supports including the loose or missing fasteners and damaged ballast. In this study, the rail-sleeper-ballast system is modeled as an Euler beam evenly supported by a series of springs, the stiffness of which are reduced when the fastener is loose or missing and the ballast under the sleepers is damaged. An auxiliary mass is utilized herein and when it is mounted on the beam, the natural frequencies of the whole system will change with respect to the location of the auxiliary mass. The auxiliary mass induced frequency shift is analyzed and it is found the natural frequencies change periodically when the supports are undamaged, whereas the periodicity will be broken due to damaged supports. In fact, the natural frequencies drop clearly when the auxiliary mass moves over the damaged support. A special damage index only using the information of the damaged states is proposed and both numerical and experimental examples are carried out to validate the proposed method.

Missed and Delayed Diagnosis of Dementia in Primary Care: Prevalence and Contributing Factors

PubMed Central

Bradford, Andrea; Kunik, Mark E.; Schulz, Paul; Williams, Susan P.; Singh, Hardeep

2009-01-01

Dementia is a growing public health problem for which early detection may be beneficial. Currently, the diagnosis of dementia in primary care is dependent mostly on clinical suspicion based on patient symptomsor caregivers’ concerns and is prone to be missed or delayed. We conducted a systematic review of the literature to ascertain the prevalence and contributing factors for missed and delayed dementia diagnoses in primary care. Prevalence of missed and delayed diagnosis was estimated by abstracting quantitative data from studies of diagnostic sensitivity among primary care providers. Possible predictors and contributory factors were determined from the text of quantitative and qualitative studies of patient-, caregiver-, provider-, and system-related barriers. Overall estimates of diagnostic sensitivity varied among studies and appeared to be in part a function of dementia severity, degree of patient impairment, dementia subtype, and frequency of patient-provider contact. Major contributory factors included problems with attitudes and patient-provider communication, educational deficits, and system resource constraints. The true prevalence of missed and delayed diagnoses of dementia is unknown but appears to be high. Until the case for dementia screening becomes more compelling, efforts to promote timely detection should focus on removing barriers to diagnosis. PMID:19568149

A quantification strategy for missing bone mass in case of osteolytic bone lesions

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

Fränzle, Andrea, E-mail: a.fraenzle@dkfz.de; Giske, Kristina; Bretschi, Maren

Purpose: Most of the patients who died of breast cancer have developed bone metastases. To understand the pathogenesis of bone metastases and to analyze treatment response of different bone remodeling therapies, preclinical animal models are examined. In breast cancer, bone metastases are often bone destructive. To assess treatment response of bone remodeling therapies, the volumes of these lesions have to be determined during the therapy process. The manual delineation of missing structures, especially if large parts are missing, is very time-consuming and not reproducible. Reproducibility is highly important to have comparable results during the therapy process. Therefore, a computerized approachmore » is needed. Also for the preclinical research, a reproducible measurement of the lesions is essential. Here, the authors present an automated segmentation method for the measurement of missing bone mass in a preclinical rat model with bone metastases in the hind leg bones based on 3D CT scans. Methods: The affected bone structure is compared to a healthy model. Since in this preclinical rat trial the metastasis only occurs on the right hind legs, which is assured by using vessel clips, the authors use the left body side as a healthy model. The left femur is segmented with a statistical shape model which is initialised using the automatically segmented medullary cavity. The left tibia and fibula are segmented using volume growing starting at the tibia medullary cavity and stopping at the femur boundary. Masked images of both segmentations are mirrored along the median plane and transferred manually to the position of the affected bone by rigid registration. Affected bone and healthy model are compared based on their gray values. If the gray value of a voxel indicates bone mass in the healthy model and no bone in the affected bone, this voxel is considered to be osteolytic. Results: The lesion segmentations complete the missing bone structures in a reasonable way. The mean ratiov{sub r}/v{sub m} of the reconstructed bone volume v{sub r} and the healthy model bone volume v{sub m} is 1.07, which indicates a good reconstruction of the modified bone. Conclusions: The qualitative and quantitative comparison of manual and semi-automated segmentation results have shown that comparing a modified bone structure with a healthy model can be used to identify and measure missing bone mass in a reproducible way.« less

Search for top squarks in final states with one isolated lepton, jets, and missing transverse momentum in s = 13 TeV p p collisions with the ATLAS detector

DOE PAGES

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

2016-09-19

The results of a search for the top squark, the supersymmetric partner of the top quark, in final states with one isolated electron or muon, jets, and missing transverse momentum are reported. The search uses the 2015 LHC pp collision data at a center-of-mass energy of √s=13 TeV recorded by the ATLAS detector and corresponding to an integrated luminosity of 3.2 fb -1. The analysis targets two types of signal models: gluino-mediated pair production of top squarks with a nearly mass-degenerate top squark and neutralino and direct pair production of top squarks, decaying to the top quark and the lightestmore » neutralino. The experimental signature in both signal scenarios is similar to that of a top quark pair produced in association with large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits on gluino and top squark masses are set at 95% confidence level. The results extend the LHC run-1 exclusion limit on the gluino mass up to 1460 GeV in the gluino-mediated scenario in the high gluino and low top squark mass region and add an excluded top squark mass region from 745 to 780 GeV for the direct top squark model with a massless lightest neutralino. The results are also reinterpreted to set exclusion limits in a model of vectorlike top quarks.« less

Space Flight Experiments to Measure Polymer Erosion and Contamination on Spacecraft

NASA Technical Reports Server (NTRS)

Lillis, Maura C.; Youngstrom, Erica E.; Marx, Laura M.; Hammerstrom, Anne M.; Finefrock, Katherine D.; Youngstrom, Christiane A.; Kaminski, Carolyn; Fine, Elizabeth S.; Hunt, Patricia K.; deGroh, Kim K.

2002-01-01

Atomic oxygen erosion and silicone contamination are serious issues that could damage or destroy spacecraft components after orbiting for an extended period of time, such as on a space station or satellite. An experiment, the Polymer Erosion And Contamination Experiment (PEACE) will be conducted to study the effects of atomic oxygen (AO) erosion and silicone contamination, and it will provide information and contribute to a solution for these problems. PEACE will fly 43 different polymer materials that will be analyzed for AO erosion effects through two techniques: mass loss measurement and recession depth measurement. Pinhole cameras will provide information about the arrival direction of AO, and silicone contamination pinhole cameras will identify the source of silicone contamination on a spacecraft. All experimental hardware will be passively exposed to AO for up to two weeks in the actual space environment when it flies in the bay of a space shuttle. A second set of the PEACE Polymers is being exposed to the space environment for erosion yield determination as part of a second experiment, Materials International Space Station Experiment (MISSE). MISSE is a collaboration between several federal agencies and aerospace companies. During a space walk on August 16, 2001, MISSE was attached to the outside of the International Space Station (ISS) during an extravehicular activity (EVA), where it began its exposure to AO for approximately 1.5 years. The PEACE polymers, therefore, will be analyzed after both short-term and long-term AO exposures for a more complete study of AO effects.

Search for supersymmetric particles in events with lepton pairs and large missing transverse momentum in sqrt{s}=7 {TeV} proton-proton collisions with the ATLAS experiment

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdelalim, A. A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abramowicz, H.; Abreu, H.; Acerbi, E.; Acharya, B. S.; Adams, D. L.; Addy, T. N.; Adelman, J.; Aderholz, M.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Akiyama, A.; Alam, M. S.; Alam, M. A.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Aliyev, M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alviggi, M. G.; Amako, K.; Amaral, P.; Amelung, C.; Ammosov, V. V.; Amorim, A.; Amorós, G.; Amram, N.; Anastopoulos, C.; Andeen, T.; Anders, C. F.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angerami, A.; Anghinolfi, F.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonelli, S.; Antonov, A.; Antos, J.; Anulli, F.; Aoun, S.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Archambault, J. P.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Asfandiyarov, R.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Atoian, G.; Aubert, B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Austin, N.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Bachy, G.; Backes, M.; Backhaus, M.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Dos Santos Pedrosa, F. Baltasar; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barashkou, A.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, D.; Bartsch, V.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Battistoni, G.; Bauer, F.; Bawa, H. S.; Beare, B.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Begel, M.; Harpaz, S. Behar; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Ami, S. Ben; Benary, O.; Benchekroun, D.; Benchouk, C.; Bendel, M.; Benedict, B. H.; Benekos, N.; Benhammou, Y.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernardet, K.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertin, A.; Bertinelli, F.; Bertolucci, F.; Besana, M. I.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boelaert, N.; Böser, S.; Bogaerts, J. A.; Bogdanchikov, A.; Bogouch, A.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Bona, M.; Bondarenko, V. G.; Boonekamp, M.; Boorman, G.; Booth, C. N.; Booth, P.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borroni, S.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Botterill, D.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E. V.; Boulahouache, C.; Bourdarios, C.; Bousson, N.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozhko, N. I.; Bozovic-Jelisavcic, I.; Bracinik, J.; Braem, A.; Branchini, P.; Brandenburg, G. W.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brelier, B.; Bremer, J.; Brenner, R.; Bressler, S.; Breton, D.; Brett, N. D.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brodbeck, T. J.; Brodet, E.; Broggi, F.; Bromberg, C.; Brooijmans, G.; Brooks, W. K.; Brown, G.; Brubaker, E.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Buanes, T.; Bucci, F.; Buchanan, J.; Buchanan, N. J.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Budick, B.; Büscher, V.; Bugge, L.; Buira-Clark, D.; Buis, E. J.; Bulekov, O.; Bunse, M.; Buran, T.; Burckhart, H.; Burdin, S.; Burgess, T.; Burke, S.; Busato, E.; Bussey, P.; Buszello, C. P.; Butin, F.; Butler, B.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Buttinger, W.; Byatt, T.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Caloi, R.; Calvet, D.; Calvet, S.; Camacho Toro, R.; Camard, A.; Camarri, P.; Cambiaghi, M.; Cameron, D.; Cammin, J.; Campana, S.; Campanelli, M.; Canale, V.; Canelli, F.; Canepa, A.; Cantero, J.; Capasso, L.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capriotti, D.; Capua, M.; Caputo, R.; Caramarcu, C.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, B.; Caron, S.; Carpentieri, C.; Carrillo Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Cascella, M.; Caso, C.; Castaneda Hernandez, A. M.; Castaneda-Miranda, E.; Castillo Gimenez, V.; Castro, N. F.; Cataldi, G.; Cataneo, F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cauz, D.; Cavallari, A.; Cavalleri, P.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Cazzato, A.; Ceradini, F.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cetin, S. A.; Cevenini, F.; Chafaq, A.; Chakraborty, D.; Chan, K.; Chapleau, B.; Chapman, J. D.; Chapman, J. W.; Chareyre, E.; Charlton, D. G.; Chavda, V.; Cheatham, S.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, L.; Chen, S.; Chen, T.; Chen, X.; Cheng, S.; Cheplakov, A.; Chepurnov, V. F.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Cheung, S. L.; Chevalier, L.; Chiefari, G.; Chikovani, L.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chizhov, M. V.; Choudalakis, G.; Chouridou, S.; Christidi, I. A.; Christov, A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Ciapetti, G.; Ciba, K.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciobotaru, M. D.; Ciocca, C.; Ciocio, A.; Cirilli, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Clifft, R. W.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coe, P.; Cogan, J. G.; Coggeshall, J.; Cogneras, E.; Cojocaru, C. D.; Colas, J.; Colijn, A. P.; Collard, C.; Collins, N. J.; Collins-Tooth, C.; Collot, J.; Colon, G.; Comune, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Consonni, M.; Constantinescu, S.; Conta, C.; Conventi, F.; Cook, J.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Costin, T.; Côté, D.; Coura Torres, R.; Courneyea, L.; Cowan, G.; Cowden, C.; Cox, B. E.; Cranmer, K.; Crescioli, F.; Cristinziani, M.; Crosetti, G.; Crupi, R.; Crépé-Renaudin, S.; Almenar, C. Cuenca; Cuhadar Donszelmann, T.; Cuneo, S.; Curatolo, M.; Curtis, C. J.; Cwetanski, P.; Czirr, H.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; D'Orazio, A.; Da Rocha Gesualdi Mello, A.; Da Silva, P. V. M.; Da Via, C.; Dabrowski, W.; Dahlhoff, A.; Dai, T.; Dallapiccola, C.; Dallison, S. J.; Dam, M.; Dameri, M.; Damiani, D. S.; Danielsson, H. O.; Dankers, R.; Dannheim, D.; Dao, V.; Darbo, G.; Darlea, G. L.; Daum, C.; Dauvergne, J. P.; Davey, W.; Davidek, T.; Davidson, N.; Davidson, R.; Davies, M.; Davison, A. R.; Dawe, E.; Dawson, I.; Dawson, J. W.; Daya, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Castro Faria Salgado, P. E.; De Cecco, S.; de Graat, J.; De Groot, N.; de Jong, P.; De La Taille, C.; De la Torre, H.; De Lotto, B.; De Mora, L.; De Nooij, L.; De Oliveira Branco, M.; De Pedis, D.; de Saintignon, P.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; Dean, S.; Dedovich, D. V.; Degenhardt, J.; Dehchar, M.; Deile, M.; Del Papa, C.; Del Peso, J.; Del Prete, T.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delpierre, P.; Delruelle, N.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demirkoz, B.; Deng, J.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Devetak, E.; Deviveiros, P. O.; Dewhurst, A.; DeWilde, B.; Dhaliwal, S.; Dhullipudi, R.; Di Ciaccio, A.; Di Ciaccio, L.; Di Girolamo, A.; Di Girolamo, B.; Di Luise, S.; Di Mattia, A.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Diaz, M. A.; Diblen, F.; Diehl, E. B.; Dietl, H.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dindar Yagci, K.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djilkibaev, R.; Djobava, T.; do Vale, M. A. B.; Do Valle Wemans, A.; Doan, T. K. O.; Dobbs, M.; Dobinson, R.; Dobos, D.; Dobson, E.; Dobson, M.; Dodd, J.; Dogan, O. B.; Doglioni, C.; Doherty, T.; Doi, Y.; Dolejsi, J.; Dolenc, I.; Dolezal, Z.; Dolgoshein, B. A.; Dohmae, T.; Donadelli, M.; Donega, M.; Donini, J.; Dopke, J.; Doria, A.; Dos Anjos, A.; Dosil, M.; Dotti, A.; Dova, M. T.; Dowell, J. D.; Doxiadis, A. D.; Doyle, A. T.; Drasal, Z.; Drees, J.; Dressnandt, N.; Drevermann, H.; Driouichi, C.; Dris, M.; Drohan, J. G.; Dubbert, J.; Dubbs, T.; Dube, S.; Duchovni, E.; Duckeck, G.; Dudarev, A.; Dudziak, F.; Dührssen, M.; Duerdoth, I. P.; Duflot, L.; Dufour, M.-A.; Dunford, M.; Yildiz, H. Duran; Duxfield, R.; Dwuznik, M.; Dydak, F.; Dzahini, D.; Düren, M.; Ebenstein, W. L.; Ebke, J.; Eckert, S.; Eckweiler, S.; Edmonds, K.; Edwards, C. A.; Ehrenfeld, W.; Ehrich, T.; Eifert, T.; Eigen, G.; Einsweiler, K.; Eisenhandler, E.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, K.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Ely, R.; Emeliyanov, D.; Engelmann, R.; Engl, A.; Epp, B.; Eppig, A.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Escobar, C.; Espinal Curull, X.; Esposito, B.; Etienne, F.; Etienvre, A. I.; Etzion, E.; Evangelakou, D.; Evans, H.; Fabbri, L.; Fabre, C.; Facius, K.; Fakhrutdinov, R. M.; Falciano, S.; Falou, A. C.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farley, J.; Farooque, T.; Farrington, S. M.; Farthouat, P.; Fasching, D.; Fassnacht, P.; Fassouliotis, D.; Fatholahzadeh, B.; Favareto, A.; Fayard, L.; Fazio, S.; Febbraro, R.; Federic, P.; Fedin, O. L.; Fedorko, I.; Fedorko, W.; Fehling-Kaschek, M.; Feligioni, L.; Fellmann, D.; Felzmann, C. U.; Feng, C.; Feng, E. J.; Fenyuk, A. B.; Ferencei, J.; Ferland, J.; Fernandes, B.; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferrer, A.; Ferrer, M. L.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filippas, A.; Filthaut, F.; Fincke-Keeler, M.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, G.; Fischer, P.; Fisher, M. J.; Fisher, S. M.; Flammer, J.; Flechl, M.; Fleck, I.; Fleckner, J.; Fleischmann, P.; Fleischmann, S.; Flick, T.; Flores Castillo, L. R.; Flowerdew, M. J.; Föhlisch, F.; Fokitis, M.; Martin, T. Fonseca; Forbush, D. A.; Formica, A.; Forti, A.; Fortin, D.; Foster, J. M.; Fournier, D.; Foussat, A.; Fowler, A. J.; Fowler, K.; Fox, H.; Francavilla, P.; Franchino, S.; Francis, D.; Frank, T.; Franklin, M.; Franz, S.; Fraternali, M.; Fratina, S.; French, S. T.; Froeschl, R.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gadfort, T.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Gallas, E. J.; Gallas, M. V.; Gallo, V.; Gallop, B. J.; Gallus, P.; Galyaev, E.; Gan, K. K.; Gao, Y. S.; Gapienko, V. A.; Gaponenko, A.; Garberson, F.; Garcia-Sciveres, M.; García, C.; Navarro, J. E. García; Gardner, R. W.; Garelli, N.; Garitaonandia, H.; Garonne, V.; Garvey, J.; Gatti, C.; Gaudio, G.; Gaumer, O.; Gaur, B.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gayde, J.-C.; Gazis, E. N.; Ge, P.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Gemmell, A.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerlach, P.; Gershon, A.; Geweniger, C.; Ghazlane, H.; Ghez, P.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giakoumopoulou, V.; Giangiobbe, V.; Gianotti, F.; Gibbard, B.; Gibson, A.; Gibson, S. M.; Gieraltowski, G. F.; Gilbert, L. M.; Gilchriese, M.; Gilewsky, V.; Gillberg, D.; Gillman, A. R.; Gingrich, D. M.; Ginzburg, J.; Giokaris, N.; Giordano, R.; Giorgi, F. M.; Giovannini, P.; Giraud, P. F.; Giugni, D.; Giusti, P.; Gjelsten, B. K.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glazov, A.; Glitza, K. W.; Glonti, G. L.; Godfrey, J.; Godlewski, J.; Goebel, M.; Göpfert, T.; Goeringer, C.; Gössling, C.; Göttfert, T.; Goldfarb, S.; Goldin, D.; Golling, T.; Golovnia, S. N.; Gomes, A.; Fajardo, L. S. Gomez; Gonçalo, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, L.; Gonidec, A.; Gonzalez, S.; González de la Hoz, S.; Silva, M. L. Gonzalez; Gonzalez-Sevilla, S.; Goodson, J. J.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorfine, G.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Gorokhov, S. A.; Goryachev, V. N.; Gosdzik, B.; Gosselink, M.; Gostkin, M. I.; Gouanère, M.; Eschrich, I. Gough; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Grabowska-Bold, I.; Grabski, V.; Grafström, P.; Grah, C.; Grahn, K.-J.; Grancagnolo, F.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Grau, N.; Gray, H. M.; Gray, J. A.; Graziani, E.; Grebenyuk, O. G.; Greenfield, D.; Greenshaw, T.; Greenwood, Z. D.; Gregor, I. M.; Grenier, P.; Griesmayer, E.; Griffiths, J.; Grigalashvili, N.; Grillo, A. A.; Grinstein, S.; Gris, P. L. Y.; Grishkevich, Y. V.; Grivaz, J.-F.; Grognuz, J.; Groh, M.; Gross, E.; Grosse-Knetter, J.; Groth-Jensen, J.; Gruwe, M.; Grybel, K.; Guarino, V. J.; Guest, D.; Guicheney, C.; Guida, A.; Guillemin, T.; Guindon, S.; Guler, H.; Gunther, J.; Guo, B.; Guo, J.; Gupta, A.; Gusakov, Y.; Gushchin, V. N.; Gutierrez, A.; Gutierrez, P.; Guttman, N.; Gutzwiller, O.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haas, S.; Haber, C.; Hackenburg, R.; Hadavand, H. K.; Hadley, D. R.; Haefner, P.; Hahn, F.; Haider, S.; Hajduk, Z.; Hakobyan, H.; Haller, J.; Hamacher, K.; Hamal, P.; Hamilton, A.; Hamilton, S.; Han, H.; Han, L.; Hanagaki, K.; Hance, M.; Handel, C.; Hanke, P.; Hansen, C. J.; Hansen, J. R.; Hansen, J. B.; Hansen, J. D.; Hansen, P. H.; Hansson, P.; Hara, K.; Hare, G. A.; Harenberg, T.; Harper, D.; Harrington, R. D.; Harris, O. M.; Harrison, K.; Hartert, J.; Hartjes, F.; Haruyama, T.; Harvey, A.; Hasegawa, S.; Hasegawa, Y.; Hassani, S.; Hatch, M.; Hauff, D.; Haug, S.; Hauschild, M.; Hauser, R.; Havranek, M.; Hawes, B. M.; Hawkes, C. M.; Hawkings, R. J.; Hawkins, D.; Hayakawa, T.; Hayden, D.; Hayward, H. S.; Haywood, S. J.; Hazen, E.; He, M.; Head, S. J.; Hedberg, V.; Heelan, L.; Heim, S.; Heinemann, B.; Heisterkamp, S.; Helary, L.; Heldmann, M.; Heller, M.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Henke, M.; Henrichs, A.; Correia, A. M. Henriques; Henrot-Versille, S.; Henry-Couannier, F.; Hensel, C.; Henß, T.; Hernández Jiménez, Y.; Herrberg, R.; Hershenhorn, A. D.; Herten, G.; Hertenberger, R.; Hervas, L.; Hessey, N. P.; Hidvegi, A.; Higón-Rodriguez, E.; Hill, D.; Hill, J. C.; Hill, N.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirsch, F.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoffman, J.; Hoffmann, D.; Hohlfeld, M.; Holder, M.; Holmes, A.; Holmgren, S. O.; Holy, T.; Holzbauer, J. L.; Homma, Y.; Hooft van Huysduynen, L.; Horazdovsky, T.; Horn, C.; Horner, S.; Horton, K.; Hostachy, J.-Y.; Hou, S.; Houlden, M. A.; Hoummada, A.; Howarth, J.; Howell, D. F.; Hristova, I.; Hrivnac, J.; Hruska, I.; Hryn'ova, T.; Hsu, P. J.; Hsu, S.-C.; Huang, G. S.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Hughes-Jones, R. 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B.; Savard, P.; Savinov, V.; Savu, D. O.; Savva, P.; Sawyer, L.; Saxon, D. H.; Says, L. P.; Sbarra, C.; Sbrizzi, A.; Scallon, O.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schäfer, U.; Schaepe, S.; Schaetzel, S.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schamov, A. G.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schioppa, M.; Schlenker, S.; Schlereth, J. L.; Schmidt, E.; Schmidt, M. P.; Schmieden, K.; Schmitt, C.; Schmitz, M.; Schöning, A.; Schott, M.; Schouten, D.; Schovancova, J.; Schram, M.; Schroeder, C.; Schroer, N.; Schuh, S.; Schuler, G.; Schultes, J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, J. W.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwemling, Ph.; Schwienhorst, R.; Schwierz, R.; Schwindling, J.; Scott, W. G.; Searcy, J.; Sedykh, E.; Segura, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Seliverstov, D. M.; Sellden, B.; Sellers, G.; Seman, M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Seuster, R.; Severini, H.; Sevior, M. E.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shank, J. T.; Shao, Q. T.; Shapiro, M.; Shatalov, P. B.; Shaver, L.; Shaw, C.; Shaw, K.; Sherman, D.; Sherwood, P.; Shibata, A.; Shimizu, S.; Shimojima, M.; Shin, T.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shupe, M. A.; Sicho, P.; Sidoti, A.; Siebel, A.; Siegert, F.; Siegrist, J.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simmons, B.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skovpen, K.; Skubic, P.; Skvorodnev, N.; Slater, M.; Slavicek, T.; Sliwa, K.; Sloan, T. J.; Sloper, J.; Smakhtin, V.; Smirnov, S. Yu.; Smirnova, L. N.; Smirnova, O.; Smith, B. C.; Smith, D.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snow, S. W.; Snow, J.; Snuverink, J.; Snyder, S.; Soares, M.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E.; Soldevila, U.; Solfaroli Camillocci, E.; Solodkov, A. A.; Solovyanov, O. V.; Sondericker, J.; Soni, N.; Sopko, V.; Sopko, B.; Sorbi, M.; Sosebee, M.; Soukharev, A.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spila, F.; Spiriti, E.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; Denis, R. D. St.; Stahl, T.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staude, A.; Stavina, P.; Stavropoulos, G.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, K.; Stewart, G. A.; Stillings, J. A.; Stockmanns, T.; Stockton, M. C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Strube, J.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Soh, D. A.; Su, D.; Subramania, H. S.; Succurro, A.; Sugaya, Y.; Sugimoto, T.; Suhr, C.; Suita, K.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Sushkov, S.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Sviridov, Yu. M.; Swedish, S.; Sykora, I.; Sykora, T.; Szeless, B.; Sánchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taga, A.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Talby, M.; Talyshev, A.; Tamsett, M. C.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanaka, Y.; Tani, K.; Tannoury, N.; Tappern, G. P.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tatarkhanov, M.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Castanheira, M. Teixeira Dias; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terwort, M.; Testa, M.; Teuscher, R. J.; Tevlin, C. M.; Thadome, J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thioye, M.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomson, E.; Thomson, M.; Thun, R. P.; Tic, T.; Tikhomirov, V. O.; Tikhonov, Y. A.; Timmermans, C. J. W. P.; Tipton, P.; Tique Aires Viegas, F. J.; Tisserant, S.; Tobias, J.; Toczek, B.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokunaga, K.; Tokushuku, K.; Tollefson, K.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, G.; Tonoyan, A.; Topfel, C.; Topilin, N. D.; Torchiani, I.; Torrence, E.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Traynor, D.; Trefzger, T.; Treis, J.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Trinh, T. N.; Tripiana, M. F.; Triplett, N.; Trischuk, W.; Trivedi, A.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiakiris, M.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsung, J.-W.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tuggle, J. M.; Turala, M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Tyrvainen, H.; Tzanakos, G.; Uchida, K.; Ueda, I.; Ueno, R.; Ugland, M.; Uhlenbrock, M.; Uhrmacher, M.; Ukegawa, F.; Unal, G.; Underwood, D. G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Urkovsky, E.; Urrejola, P.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valderanis, C.; Valenta, J.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; van der Graaf, H.; van der Kraaij, E.; Van Der Leeuw, R.; van der Poel, E.; van der Ster, D.; Van Eijk, B.; van Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vandelli, W.; Vandoni, G.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Varela Rodriguez, F.; Vari, R.; Varnes, E. W.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Vegni, G.; Veillet, J. J.; Vellidis, C.; Veloso, F.; Veness, R.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Vichou, I.; Vickey, T.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinek, E.; Vinogradov, V. B.; Virchaux, M.; Viret, S.; Virzi, J.; Vitale, A.; Vitells, O.; Viti, M.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobiev, A. P.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T. T.; Vossebeld, J. H.; Vovenko, A. S.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Anh, T. Vu; Vuillermet, R.; Vukotic, I.; Wagner, W.; Wagner, P.; Wahlen, H.; Wakabayashi, J.; Walbersloh, J.; Walch, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Wang, C.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, J. C.; Wang, R.; Wang, S. M.; Warburton, A.; Ward, C. P.; Warsinsky, M.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, A. T.; Waugh, B. M.; Weber, J.; Weber, M.; Weber, M. S.; Weber, P.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P. S.; Wen, M.; Wenaus, T.; Wendler, S.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Wessels, M.; Whalen, K.; Wheeler-Ellis, S. J.; Whitaker, S. P.; White, A.; White, M. J.; White, S.; Whitehead, S. R.; Whiteson, D.; Whittington, D.; Wicek, F.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilhelm, I.; Wilkens, H. G.; Will, J. Z.; Williams, E.; Williams, H. H.; Willis, W.; Willocq, S.; Wilson, J. A.; Wilson, M. G.; Wilson, A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wolter, M. W.; Wolters, H.; Wooden, G.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wraight, K.; Wright, C.; Wrona, B.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wunstorf, R.; Wynne, B. M.; Xaplanteris, L.; Xella, S.; Xie, S.; Xie, Y.; Xu, C.; Xu, D.; Xu, G.; Yabsley, B.; Yamada, M.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U. K.; Yang, Y.; Yang, Y.; Yang, Z.; Yanush, S.; Yao, W.-M.; Yao, Y.; Yasu, Y.; Ybeles Smit, G. V.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Youssef, S.; Yu, D.; Yu, J.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zaets, V. G.; Zaidan, R.; Zaitsev, A. M.; Zajacova, Z.; Zalite, Yo. K.; Zanello, L.; Zarzhitsky, P.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zema, P. F.; Zemla, A.; Zendler, C.; Zenin, A. V.; Zenin, O.; Ženiš, T.; Zenonos, Z.; Zenz, S.; Zerwas, D.; della Porta, G. Zevi; Zhan, Z.; Zhang, D.; Zhang, H.; Zhang, J.; Zhang, X.; Zhang, Z.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zheng, S.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zieminska, D.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; Zolnierowski, Y.; Zsenei, A.; zur Nedden, M.; Zutshi, V.; Zwalinski, L.

2011-07-01

Results are presented of searches for the production of supersymmetric particles decaying into final states with missing transverse momentum and exactly two isolated leptons in sqrt {s}=7 TeV proton-proton collisions at the Large Hadron Collider. Search strategies requiring lepton pairs with identical-sign or opposite-sign electric charges are described. In a data sample corresponding to an integrated luminosity of 35 pb-1 collected with the ATLAS detector, no significant excesses are observed. Based on specific benchmark models, limits are placed on the squark mass between 450 and 690 GeV for squarks approximately degenerate in mass with gluinos, depending on the supersymmetric mass hierarchy considered.

Search for supersymmetric particles in events with lepton pairs and large missing transverse momentum in $$\\sqrt{s}=7~\\mbox{TeV}$$ proton–proton collisions with the ATLAS experiment

DOE PAGES

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

2011-07-09

Results are presented of searches for the production of supersymmetric particles decaying into final states with missing transverse momentum and exactly two isolated leptons in √s = 7 TeV proton-proton collisions at the Large Hadron Collider. Search strategies requiring lepton pairs with identical-sign or opposite-sign electric charges are described. In a data sample corresponding to an integrated luminosity of 35 pb -1 collected with the ATLAS detector, no significant excesses are observed. Based on specific benchmark models, limits are placed on the squark mass between 450 and 690 GeV for squarks approximately degenerate in mass with gluinos, depending on themore » supersymmetric mass hierarchy considered.« less

Thermal and Dynamic Properties of Volcanic Lava Inferred from Measurements on its Surface

NASA Astrophysics Data System (ADS)

Ismail-Zadeh, A.; Korotkii, A.; Kovtunov, D.; Tsepelev, I.; Melnik, O. E.

2015-12-01

Modern remote sensing technologies allow for detecting the absolute temperature at the surface of volcanic lava, and the heat flow could be then inferred from the Stefan-Boltzmann law. Is it possible to use these surface thermal data to constrain the thermal and dynamic conditions inside the lava? We propose a quantitative approach to reconstruct temperature and velocity in the steady-state volcanic lava flow from thermal observations at its surface. This problem is reduced to a combination of the direct and inverse problems of mass- and heat transport. Namely, using known conditions at the lava surface we determine the missing condition at the bottom of lava (the inverse problem) and then search for the physical properties of lava - temperature and flow velocity - inside the lava (the direct problem). Assuming that the lava rheology and the thermal conductivity are temperature-dependent, we determine the flow characteristics in the model domain using an adjoint method. We show that in the case of smooth input data (observations) the lava temperature and the flow velocity can be reconstructed with a high accuracy. The noise imposed on the smooth input data results in a less accurate solution, but still acceptable below some noise level.

Sensitivity Analysis of Multiple Informant Models When Data are Not Missing at Random

PubMed Central

Blozis, Shelley A.; Ge, Xiaojia; Xu, Shu; Natsuaki, Misaki N.; Shaw, Daniel S.; Neiderhiser, Jenae; Scaramella, Laura; Leve, Leslie; Reiss, David

2014-01-01

Missing data are common in studies that rely on multiple informant data to evaluate relationships among variables for distinguishable individuals clustered within groups. Estimation of structural equation models using raw data allows for incomplete data, and so all groups may be retained even if only one member of a group contributes data. Statistical inference is based on the assumption that data are missing completely at random or missing at random. Importantly, whether or not data are missing is assumed to be independent of the missing data. A saturated correlates model that incorporates correlates of the missingness or the missing data into an analysis and multiple imputation that may also use such correlates offer advantages over the standard implementation of SEM when data are not missing at random because these approaches may result in a data analysis problem for which the missingness is ignorable. This paper considers these approaches in an analysis of family data to assess the sensitivity of parameter estimates to assumptions about missing data, a strategy that may be easily implemented using SEM software. PMID:25221420

Why are they missing? : Bioinformatics characterization of missing human proteins.

PubMed

Elguoshy, Amr; Magdeldin, Sameh; Xu, Bo; Hirao, Yoshitoshi; Zhang, Ying; Kinoshita, Naohiko; Takisawa, Yusuke; Nameta, Masaaki; Yamamoto, Keiko; El-Refy, Ali; El-Fiky, Fawzy; Yamamoto, Tadashi

2016-10-21

NeXtProt is a web-based protein knowledge platform that supports research on human proteins. NeXtProt (release 2015-04-28) lists 20,060 proteins, among them, 3373 canonical proteins (16.8%) lack credible experimental evidence at protein level (PE2:PE5). Therefore, they are considered as "missing proteins". A comprehensive bioinformatic workflow has been proposed to analyze these "missing" proteins. The aims of current study were to analyze physicochemical properties, existence and distribution of the tryptic cleavage sites, and to pinpoint the signature peptides of the missing proteins. Our findings showed that 23.7% of missing proteins were hydrophobic proteins possessing transmembrane domains (TMD). Also, forty missing entries generate tryptic peptides were either out of mass detection range (>30aa) or mapped to different proteins (<9aa). Additionally, 21% of missing entries didn't generate any unique tryptic peptides. In silico endopeptidase combination strategy increased the possibility of missing proteins identification. Coherently, using both mature protein database and signal peptidome database could be a promising option to identify some missing proteins by targeting their unique N-terminal tryptic peptide from mature protein database and or C-terminus tryptic peptide from signal peptidome database. In conclusion, Identification of missing protein requires additional consideration during sample preparation, extraction, digestion and data analysis to increase its incidence of identification. Copyright © 2016. Published by Elsevier B.V.

Florence Nightingale and the Salisbury incident.

PubMed

Palmer, I S

1976-01-01

Florence Nightingale's astute handling of mismanagement in Free Gifts Stores during the Crimean War underscored her administrative ability. Miss Nightingale went to Scutari ostensibly to nurse the British soldiers, and while there encountered innumerable instances of administrative and managerial ineffectiveness and difficulties. Among these were the problems in the accountability and deployment of supplies as well as the assignment and supervision of female personnel-an untried situation. The article identifies the misdirected organizational management which occasioned the introduction of women into British war nursing and the voluntary participation of the British citizenry in providing supplies and comfort for the Army. Through analysis of Miss Nightingale's and others' private correspondence, the problems of personnel management and supply distribution are brought into sharp focus. The interplay of policies and principles to which Miss Nightingale subscribed, the human frailty of one of her women, Miss Nightingale's illness, and the confusion and stress which characterized the Crimean War are discussed. The compassion, understanding, and rectitude as well as the human values to which Miss Nightingale subscribed in protecting a woman guilty of a breach of trust and felony and the troublesome slanderous attack to which Miss Nightingale was subjected at the instigation of her foes on the home front provide a background for the presentation of the Salisbury affair as an interesting aspect of historical research into the life of the Victorian heroine.

Restoration of HST images with missing data

NASA Technical Reports Server (NTRS)

Adorf, Hans-Martin

1992-01-01

Missing data are a fairly common problem when restoring Hubble Space Telescope observations of extended sources. On Wide Field and Planetary Camera images cosmic ray hits and CCD hot spots are the prevalent causes of data losses, whereas on Faint Object Camera images data are lossed due to reseaux marks, blemishes, areas of saturation and the omnipresent frame edges. This contribution discusses a technique for 'filling in' missing data by statistical inference using information from the surrounding pixels. The major gain consists in minimizing adverse spill-over effects to the restoration in areas neighboring those where data are missing. When the mask delineating the support of 'missing data' is made dynamic, cosmic ray hits, etc. can be detected on the fly during restoration.

Seventh Grade Students' Problem Solving Success Rates on Proportional Reasoning Problems

ERIC Educational Resources Information Center

Pelen, Mustafa Serkan; Artut, Perihan Dinç

2016-01-01

This research was conducted to investigate 7th grade students' problem solving success rates on proportional reasoning problems and whether these success rates change with different problem types. 331 randomly selected students of grade seven participated in this study. A problem test which contains three different types of missing value (direct…

Learning from Non-Reported Data: Interpreting Missing Body Mass Index Values in Young Children

ERIC Educational Resources Information Center

Arbour-Nicitopoulos, Kelly P.; Faulkner, Guy E.; Leatherdale, Scott T.

2010-01-01

The objective of this study was to examine the pattern of relations between missing weight and height (BMI) data and a range of demographic, physical activity, sedentary behavior, and academic measures in a young sample of elementary school children. A secondary analysis of a large cross-sectional study, PLAY-On, was conducted using self-reported…

Large-scale forensic investigations into the missing: Challenges and considerations.

PubMed

Salado Puerto, Mercedes; Tuller, Hugh

2017-10-01

Large-scale forensic investigations may follow episodes of mass violence and disasters where hundreds or thousands of people have died or are missing. A number of unique challenges for forensic science, different from domestic investigations, arise in these contexts. The setting and situation of these investigations regularly force forensic scientists into practices not regularly encountered while working in a standard criminal justice system. These practices can entail activities not specific to a practitioner's particular field or necessarily be scientific in nature, but are still needed in order for the investigation to move forward. These activities can include (1) establishing the number of and who exactly is missing after mass violence and disaster, (2) the creation of working protocols to deal with the scale of the loss of life that often overwhelm domestic practices and institutions, (3) negotiating the form that the investigation will take with various stakeholders, (4) addressing cultural beliefs of the affected society regarding the dead and missing, and (5) working within prescribed economic, political, and time constraints, among others. Forensic scientific responses to these challenges have proven to be flexible, innovative, and continually evolving. Copyright © 2017 Elsevier B.V. All rights reserved.

Testing the Cubic Galileon Gravity Model by the Milky Way Rotation Curve and SPARC Data

NASA Astrophysics Data System (ADS)

Chan, Man Ho; Hui, Hon Ka

2018-04-01

Recently, the cubic Galileon gravity (CGG) model has been suggested as an alternative gravity theory to general relativity. The model consists of an extra field potential term that can serve as the “fifth force.” In this article, we examine the possibility of whether or not this extra force term can explain the missing mass problem in galaxies without the help of dark matter. By using the Milky Way rotation curve and the Spitzer Photomery and Accurate Rotation Curves data, we show that this CGG model can satisfactorily explain the shapes of these rotation curves without dark matter. The CGG model can be regarded as a new alternative theory to challenge the existing dark matter paradigm.

Reconstructing missing daily precipitation data using regression trees and artificial neural networks

USDA-ARS?s Scientific Manuscript database

Incomplete meteorological data has been a problem in environmental modeling studies. The objective of this work was to develop a technique to reconstruct missing daily precipitation data in the central part of Chesapeake Bay Watershed using regression trees (RT) and artificial neural networks (ANN)....

Treatment of missing data in follow-up studies of randomised controlled trials: A systematic review of the literature.

PubMed

Sullivan, Thomas R; Yelland, Lisa N; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-08-01

After completion of a randomised controlled trial, an extended follow-up period may be initiated to learn about longer term impacts of the intervention. Since extended follow-up studies often involve additional eligibility restrictions and consent processes for participation, and a longer duration of follow-up entails a greater risk of participant attrition, missing data can be a considerable threat in this setting. As a potential source of bias, it is critical that missing data are appropriately handled in the statistical analysis, yet little is known about the treatment of missing data in extended follow-up studies. The aims of this review were to summarise the extent of missing data in extended follow-up studies and the use of statistical approaches to address this potentially serious problem. We performed a systematic literature search in PubMed to identify extended follow-up studies published from January to June 2015. Studies were eligible for inclusion if the original randomised controlled trial results were also published and if the main objective of extended follow-up was to compare the original randomised groups. We recorded information on the extent of missing data and the approach used to treat missing data in the statistical analysis of the primary outcome of the extended follow-up study. Of the 81 studies included in the review, 36 (44%) reported additional eligibility restrictions and 24 (30%) consent processes for entry into extended follow-up. Data were collected at a median of 7 years after randomisation. Excluding 28 studies with a time to event primary outcome, 51/53 studies (96%) reported missing data on the primary outcome. The median percentage of randomised participants with complete data on the primary outcome was just 66% in these studies. The most common statistical approach to address missing data was complete case analysis (51% of studies), while likelihood-based analyses were also well represented (25%). Sensitivity analyses around the missing data mechanism were rarely performed (25% of studies), and when they were, they often involved unrealistic assumptions about the mechanism. Despite missing data being a serious problem in extended follow-up studies, statistical approaches to addressing missing data were often inadequate. We recommend researchers clearly specify all sources of missing data in follow-up studies and use statistical methods that are valid under a plausible assumption about the missing data mechanism. Sensitivity analyses should also be undertaken to assess the robustness of findings to assumptions about the missing data mechanism.

Detailed Investigation and Comparison of the XCMS and MZmine 2 Chromatogram Construction and Chromatographic Peak Detection Methods for Preprocessing Mass Spectrometry Metabolomics Data.

PubMed

Myers, Owen D; Sumner, Susan J; Li, Shuzhao; Barnes, Stephen; Du, Xiuxia

2017-09-05

XCMS and MZmine 2 are two widely used software packages for preprocessing untargeted LC/MS metabolomics data. Both construct extracted ion chromatograms (EICs) and detect peaks from the EICs, the first two steps in the data preprocessing workflow. While both packages have performed admirably in peak picking, they also detect a problematic number of false positive EIC peaks and can also fail to detect real EIC peaks. The former and latter translate downstream into spurious and missing compounds and present significant limitations with most existing software packages that preprocess untargeted mass spectrometry metabolomics data. We seek to understand the specific reasons why XCMS and MZmine 2 find the false positive EIC peaks that they do and in what ways they fail to detect real compounds. We investigate differences of EIC construction methods in XCMS and MZmine 2 and find several problems in the XCMS centWave peak detection algorithm which we show are partly responsible for the false positive and false negative compound identifications. In addition, we find a problem with MZmine 2's use of centWave. We hope that a detailed understanding of the XCMS and MZmine 2 algorithms will allow users to work with them more effectively and will also help with future algorithmic development.

VIGAN: Missing View Imputation with Generative Adversarial Networks.

PubMed

Shang, Chao; Palmer, Aaron; Sun, Jiangwen; Chen, Ko-Shin; Lu, Jin; Bi, Jinbo

2017-01-01

In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.

Order-restricted inference for means with missing values.

PubMed

Wang, Heng; Zhong, Ping-Shou

2017-09-01

Missing values appear very often in many applications, but the problem of missing values has not received much attention in testing order-restricted alternatives. Under the missing at random (MAR) assumption, we impute the missing values nonparametrically using kernel regression. For data with imputation, the classical likelihood ratio test designed for testing the order-restricted means is no longer applicable since the likelihood does not exist. This article proposes a novel method for constructing test statistics for assessing means with an increasing order or a decreasing order based on jackknife empirical likelihood (JEL) ratio. It is shown that the JEL ratio statistic evaluated under the null hypothesis converges to a chi-bar-square distribution, whose weights depend on missing probabilities and nonparametric imputation. Simulation study shows that the proposed test performs well under various missing scenarios and is robust for normally and nonnormally distributed data. The proposed method is applied to an Alzheimer's disease neuroimaging initiative data set for finding a biomarker for the diagnosis of the Alzheimer's disease. © 2017, The International Biometric Society.

Spacecraft intercept guidance using zero effort miss steering

NASA Astrophysics Data System (ADS)

Newman, Brett

The suitability of proportional navigation, or an equivalent zero effort miss formulation, for spacecraft intercepts during midcourse guidance, followed by a ballistic coast to the endgame, is addressed. The problem is formulated in terms of relative motion in a general 3D framework. The proposed guidance law for the commanded thrust vector orientation consists of the sum of two terms: (1) along the line of sight unit direction and (2) along the zero effort miss component perpendicular to the line of sight and proportional to the miss itself and a guidance gain. If the guidance law is to be suitable for longer range targeting applications with significant ballistic coasting after burnout, determination of the zero effort miss must account for the different gravitational accelerations experienced by each vehicle. The proposed miss determination techniques employ approximations for the true differential gravity effect. Theoretical results are applied to a numerical engagement scenario and the resulting performance is evaluated in terms of the miss distances determined from nonlinear simulation.

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

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

Results of a search for new physics in final states with photons and missing transverse energy are reported. The study is based on a sample of proton–proton collisions collected at a center-of-mass energy of 13 TeV with the CMS detector in 2015, corresponding to an integrated luminosity of 2.3 fb -1. Final states with two photons and significant missing transverse energy are used to search for supersymmetric particles in models of supersymmetry (SUSY) with general gauge-mediated (GGM) supersymmetry breaking. We did not observe an excess with respect to the standard model expectation, and the results are used to set limitsmore » on gluino pair production and squark pair production in the GGM SUSY framework. Gluino masses below 1.65 TeV and squark masses below 1.37 TeV are excluded at a 95% confidence level.« less

Reducing Missed Laboratory Results: Defining Temporal Responsibility, Generating User Interfaces for Test Process Tracking, and Retrospective Analyses to Identify Problems

PubMed Central

Tarkan, Sureyya; Plaisant, Catherine; Shneiderman, Ben; Hettinger, A. Zachary

2011-01-01

Researchers have conducted numerous case studies reporting the details on how laboratory test results of patients were missed by the ordering medical providers. Given the importance of timely test results in an outpatient setting, there is limited discussion of electronic versions of test result management tools to help clinicians and medical staff with this complex process. This paper presents three ideas to reduce missed results with a system that facilitates tracking laboratory tests from order to completion as well as during follow-up: (1) define a workflow management model that clarifies responsible agents and associated time frame, (2) generate a user interface for tracking that could eventually be integrated into current electronic health record (EHR) systems, (3) help identify common problems in past orders through retrospective analyses. PMID:22195201

On-field performance of national football league players after return from concussion.

PubMed

Kumar, Neil S; Chin, Matthew; O'Neill, Craig; Jakoi, Andre M; Tabb, Loni; Wolf, Michael

2014-09-01

There are few data examining the short-term effects of concussions on player performance upon return to play. This study examined changes in on-field performance and the influence of epidemiologic factors on performance and return to play. On-field performance is different in players who return within 7 days after concussion compared with players who miss at least 1 game. Case-control study; Level of evidence, 3. Players in the National Football League who were active during the 2008 to 2012 seasons were considered for inclusion. Weekly injury reports identified concussed players. All players played in at least 4 games before and after the game of injury (sentinel game) within the year of injury (sentinel year). Players who had missed games secondary to another injury or had sustained a second concussion within the sentinel year were excluded. The players' league profiles were used to determine age, position, body mass index, career experience, and games missed. ProFootballFocus performance scores determined player ratings. Statistical analysis used 2-sided t tests and both univariate and multivariate logistic regression models. There were a total of 131 concussions in the 124 players who qualified for this study; 55% of these players missed no games. Defensive secondary, wide receiver, and offensive line were the most commonly affected positions. Players who missed at least 1 game were younger and less experienced. Preinjury ProFootballFocus performance scores were similar to postinjury performance in players without games missed (0.16 vs 0.33; P = .129) and players who missed at least 1 game (-0.06 vs 0.10; P = .219). Age, body mass index, experience, and previous concussion did not correlate with changes in postinjury scores (P > .05). Older, more experienced players and players with late-season concussions were more likely to return to play without missing games (P < .05). The odds of returning within 7 days increased by 18% for each career year and by 40% for each game before the sentinel game within the sentinel year; these same odds decreased by 85% after introduction of newer treatment guidelines in 2009. No difference in player performance after concussion was found whether the player did or did not miss games before return. Return without missing games may be associated with experience and timing of injury within a season and less likely after newer guidelines. © 2014 The Author(s).

Search for dark matter in events with a hadronically decaying W or Z boson and missing transverse momentum in pp collisions at √s=8  TeV with the ATLAS detector.

PubMed

Aad, G; Abajyan, T; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Addy, T N; Adelman, J; Adomeit, S; Adye, T; Aefsky, S; Agatonovic-Jovin, T; Aguilar-Saavedra, J A; Agustoni, M; Ahlen, S P; Ahmad, A; Ahmadov, F; Ahsan, M; Aielli, G; Åkesson, T P A; Akimoto, G; Akimov, A V; Alam, M A; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alessandria, F; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Aliev, M; Alimonti, G; Alio, L; Alison, J; Allbrooke, B M M; Allison, L J; Allport, P P; Allwood-Spiers, S E; Almond, J; Aloisio, A; Alon, R; Alonso, A; Alonso, F; Altheimer, A; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amaral Coutinho, Y; Amelung, C; Ammosov, V V; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amram, N; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; 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Richter-Was, E; Ridel, M; Rieck, P; Rijssenbeek, M; Rimoldi, A; Rinaldi, L; Rios, R R; Ritsch, E; Riu, I; Rivoltella, G; Rizatdinova, F; Rizvi, E; Robertson, S H; Robichaud-Veronneau, A; Robinson, D; Robinson, J E M; Robson, A; Rocha de Lima, J G; Roda, C; Roda Dos Santos, D; Rodrigues, L; Roe, A; Roe, S; Røhne, O; Rolli, S; Romaniouk, A; Romano, M; Romeo, G; Romero Adam, E; Rompotis, N; Roos, L; Ros, E; Rosati, S; Rosbach, K; Rose, A; Rose, M; Rosendahl, P L; Rosenthal, O; Rossetti, V; Rossi, E; Rossi, L P; Rosten, R; Rotaru, M; Roth, I; Rothberg, J; Rousseau, D; Royon, C R; Rozanov, A; Rozen, Y; Ruan, X; Rubbo, F; Rubinskiy, I; Rud, V I; Rudolph, C; Rudolph, M S; Rühr, F; Ruiz-Martinez, A; Rumyantsev, L; Rurikova, Z; Rusakovich, N A; Ruschke, A; Rutherfoord, J P; Ruthmann, N; Ruzicka, P; Ryabov, Y F; Rybar, M; Rybkin, G; Ryder, N C; Saavedra, A F; Saddique, A; Sadeh, I; Sadrozinski, H F-W; Sadykov, R; Safai Tehrani, F; Sakamoto, H; Sakurai, Y; Salamanna, G; Salamon, A; Saleem, M; Salek, D; 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Schneider, B; Schnellbach, Y J; Schnoor, U; Schoeffel, L; Schoening, A; Schoenrock, B D; Schorlemmer, A L S; Schott, M; Schouten, D; Schovancova, J; Schram, M; Schramm, S; Schreyer, M; Schroeder, C; Schroer, N; Schuh, N; Schultens, M J; Schultz-Coulon, H-C; Schulz, H; Schumacher, M; Schumm, B A; Schune, P; Schwartzman, A; Schwegler, P; Schwemling, P; Schwienhorst, R; Schwindling, J; Schwindt, T; Schwoerer, M; Sciacca, F G; Scifo, E; Sciolla, G; Scott, W G; Scutti, F; Searcy, J; Sedov, G; Sedykh, E; Seidel, S C; Seiden, A; Seifert, F; Seixas, J M; Sekhniaidze, G; Sekula, S J; Selbach, K E; Seliverstov, D M; Sellers, G; Seman, M; Semprini-Cesari, N; Serfon, C; Serin, L; Serkin, L; Serre, T; Seuster, R; Severini, H; Sforza, F; Sfyrla, A; Shabalina, E; Shamim, M; Shan, L Y; Shank, J T; Shao, Q T; Shapiro, M; Shatalov, P B; Shaw, K; Sherwood, P; Shimizu, S; Shimojima, M; Shin, T; Shiyakova, M; Shmeleva, A; Shochet, M J; Short, D; Shrestha, S; Shulga, E; Shupe, M A; Shushkevich, S; Sicho, P; Sidorov, D; Sidoti, A; Siegert, F; Sijacki, D; Silbert, O; Silva, J; Silver, Y; Silverstein, D; Silverstein, S B; Simak, V; Simard, O; Simic, L; Simion, S; Simioni, E; Simmons, B; Simoniello, R; Simonyan, M; Sinervo, P; Sinev, N B; Sipica, V; Siragusa, G; Sircar, A; Sisakyan, A N; Sivoklokov, S Y; Sjölin, J; Sjursen, T B; Skinnari, L A; Skottowe, H P; Skovpen, K Y; Skubic, P; Slater, M; Slavicek, T; Sliwa, K; Smakhtin, V; Smart, B H; Smestad, L; Smirnov, S Y; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, K M; Smizanska, M; Smolek, K; Snesarev, A A; Snidero, G; Snow, J; Snyder, S; Sobie, R; Socher, F; Sodomka, J; Soffer, A; Soh, D A; Solans, C A; Solar, M; Solc, J; Soldatov, E Y; Soldevila, U; Solfaroli Camillocci, E; Solodkov, A A; Solovyanov, O V; Solovyev, V; Soni, N; Sood, A; Sopko, V; Sopko, B; Sosebee, M; Soualah, R; Soueid, P; Soukharev, A M; South, D; Spagnolo, S; Spanò, F; Spearman, W R; Spighi, R; Spigo, G; Spousta, M; Spreitzer, T; Spurlock, B; St Denis, R D; Stahlman, J; Stamen, R; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stanitzki, M M; Stapnes, S; Starchenko, E A; Stark, J; Staroba, P; Starovoitov, P; Staszewski, R; Stavina, P; Steele, G; Steinbach, P; Steinberg, P; Stekl, I; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stewart, G A; Stillings, J A; Stockton, M C; Stoebe, M; Stoerig, K; Stoicea, G; Stonjek, S; Stradling, A R; Straessner, A; Strandberg, J; Strandberg, S; Strandlie, A; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Stroynowski, R; Stucci, S A; Stugu, B; Stumer, I; Stupak, J; Sturm, P; Styles, N A; Su, D; Subramania, H; Subramaniam, R; Succurro, A; Sugaya, Y; Suhr, C; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, Y; Svatos, M; Swedish, S; Swiatlowski, M; Sykora, I; Sykora, T; Ta, D; Tackmann, K; Taenzer, J; Taffard, A; Tafirout, R; Taiblum, N; Takahashi, Y; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A A; Tam, J Y C; Tamsett, M C; Tan, K G; Tanaka, J; Tanaka, R; Tanaka, S; Tanaka, S; Tanasijczuk, A J; Tani, K; Tannoury, N; Tapprogge, S; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tashiro, T; Tassi, E; Tavares Delgado, A; Tayalati, Y; Taylor, C; Taylor, F E; Taylor, G N; Taylor, W; Teischinger, F A; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Terada, S; Terashi, K; Terron, J; Terzo, S; Testa, M; Teuscher, R J; Therhaag, J; Theveneaux-Pelzer, T; Thoma, S; Thomas, J P; Thompson, E N; Thompson, P D; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thong, W M; Thun, R P; Tian, F; Tibbetts, M J; Tic, T; Tikhomirov, V O; Tikhonov, Y A; Timoshenko, S; Tiouchichine, E; Tipton, P; Tisserant, S; Todorov, T; Todorova-Nova, S; Toggerson, B; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Tonoyan, A; Topilin, N D; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Tran, H L; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Triplett, N; Trischuk, W; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trovatelli, M; True, P; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J-L; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsirintanis, N; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsung, J-W; Tsuno, S; Tsybychev, D; Tua, A; Tudorache, A; Tudorache, V; Tuggle, J M; Tuna, A N; Tupputi, S A; Turchikhin, S; Turecek, D; Turk Cakir, I; Turra, R; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Uchida, K; Ueda, I; Ueno, R; Ughetto, M; Ugland, M; Uhlenbrock, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Urbaniec, D; Urquijo, P; Usai, G; Usanova, A; Vacavant, L; Vacek, V; Vachon, B; Vahsen, S; Valencic, N; Valentinetti, S; Valero, A; Valery, L; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; Van Berg, R; Van Der Deijl, P C; van der Geer, R; van der Graaf, H; Van Der Leeuw, R; van der Ster, D; van Eldik, N; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; van Woerden, M C; Vanadia, M; Vandelli, W; Vaniachine, A; Vankov, P; Vannucci, F; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vassilakopoulos, V I; Vazeille, F; Vazquez Schroeder, T; Veatch, J; Veloso, F; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Viazlo, O; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Vigne, R; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinogradov, V B; Virzi, J; Vitells, O; Viti, M; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vogel, A; Vokac, P; Volpi, G; Volpi, M; Volpini, G; von der Schmitt, H; von Radziewski, H; von Toerne, E; Vorobel, V; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vu Anh, T; Vuillermet, R; Vukotic, I; Vykydal, Z; Wagner, W; Wagner, P; Wahrmund, S; Wakabayashi, J; Walch, S; Walder, J; Walker, R; Walkowiak, W; Wall, R; Waller, P; Walsh, B; Wang, C; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; Wang, X; Warburton, A; Ward, C P; Wardrope, D R; Warsinsky, M; Washbrook, A; Wasicki, C; Watanabe, I; Watkins, P M; Watson, A T; Watson, I J; Watson, M F; Watts, G; Watts, S; Waugh, A T; Waugh, B M; Webb, S; Weber, M S; Weber, S W; Webster, J S; Weidberg, A R; Weigell, P; Weingarten, J; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wendland, D; Weng, Z; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, P; Wessels, M; Wetter, J; Whalen, K; White, A; White, M J; White, R; White, S; Whiteson, D; Whittington, D; Wicke, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wijeratne, P A; Wildauer, A; Wildt, M A; Wilhelm, I; Wilkens, H G; Will, J Z; Williams, E; Williams, H H; Williams, S; Willis, W; Willocq, S; Wilson, J A; Wilson, A; Wingerter-Seez, I; Winkelmann, S; Winklmeier, F; Wittgen, M; Wittig, T; Wittkowski, J; Wollstadt, S J; Wolter, M W; Wolters, H; Wong, W C; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wraight, K; Wright, M; Wu, S L; Wu, X; Wu, Y; Wulf, E; Wyatt, T R; Wynne, B M; Xella, S; Xiao, M; Xu, C; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yamada, M; Yamaguchi, H; Yamaguchi, Y; Yamamoto, A; Yamamoto, K; Yamamoto, S; Yamamura, T; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, U K; Yang, Y; Yang, Z; Yanush, S; Yao, L; Yasu, Y; Yatsenko, E; Yau Wong, K H; Ye, J; Ye, S; Yen, A L; Yildirim, E; Yilmaz, M; Yoosoofmiya, R; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J; Yuan, L; Yurkewicz, A; Zabinski, B; Zaidan, R; Zaitsev, A M; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zaytsev, A; Zeitnitz, C; Zeman, M; Zemla, A; Zenin, O; Ženiš, T; Zerwas, D; Zevi della Porta, G; Zhang, D; Zhang, H; Zhang, J; Zhang, L; Zhang, X; Zhang, Z; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, L; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zibell, A; Zieminska, D; Zimin, N I; Zimmermann, C; Zimmermann, R; Zimmermann, S; Zimmermann, S; Zinonos, Z; Ziolkowski, M; Zitoun, R; Živković, L; Zobernig, G; Zoccoli, A; zur Nedden, M; Zurzolo, G; Zutshi, V; Zwalinski, L

2014-01-31

A search is presented for dark matter pair production in association with a W or Z boson in pp collisions representing 20.3  fb(-1) of integrated luminosity at √s=8  TeV using data recorded with the ATLAS detector at the Large Hadron Collider. Events with a hadronic jet with the jet mass consistent with a W or Z boson, and with large missing transverse momentum are analyzed. The data are consistent with the standard model expectations. Limits are set on the mass scale in effective field theories that describe the interaction of dark matter and standard model particles, and on the cross section of Higgs production and decay to invisible particles. In addition, cross section limits on the anomalous production of W or Z bosons with large missing transverse momentum are set in two fiducial regions.

Comparison of Modern Methods for Analyzing Repeated Measures Data with Missing Values

ERIC Educational Resources Information Center

Vallejo, G.; Fernandez, M. P.; Livacic-Rojas, P. E.; Tuero-Herrero, E.

2011-01-01

Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…

Solutions for Missing Data in Structural Equation Modeling

ERIC Educational Resources Information Center

Carter, Rufus Lynn

2006-01-01

Many times in both educational and social science research it is impossible to collect data that is complete. When administering a survey, for example, people may answer some questions and not others. This missing data causes a problem for researchers using structural equation modeling (SEM) techniques for data analyses. Because SEM and…

Use of Missing Data Methods in Longitudinal Studies: The Persistence of Bad Practices in Developmental Psychology

ERIC Educational Resources Information Center

Jelicic, Helena; Phelps, Erin; Lerner, Richard M.

2009-01-01

Developmental science rests on describing, explaining, and optimizing intraindividual changes and, hence, empirically requires longitudinal research. Problems of missing data arise in most longitudinal studies, thus creating challenges for interpreting the substance and structure of intraindividual change. Using a sample of reports of longitudinal…

Principle Component Analysis with Incomplete Data: A simulation of R pcaMethods package in Constructing an Environmental Quality Index with Missing Data

EPA Science Inventory

Missing data is a common problem in the application of statistical techniques. In principal component analysis (PCA), a technique for dimensionality reduction, incomplete data points are either discarded or imputed using interpolation methods. Such approaches are less valid when ...

Least-Squares Approximation of an Improper Correlation Matrix by a Proper One.

ERIC Educational Resources Information Center

Knol, Dirk L.; ten Berge, Jos M. F.

1989-01-01

An algorithm, based on a solution for C. I. Mosier's oblique Procrustes rotation problem, is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. Results are of interest for missing value and tetrachoric correlation, indefinite matrix correlation, and constrained…

Growth Problems

MedlinePlus

... hormones needed to grow and develop. For example, Turner syndrome is a genetic condition (due to a problem ... a missing or abnormal X chromosome. Girls with Turner syndrome tend to be short and don't usually ...

Dark matter particle spectroscopy at the LHC: generalizing M T2 to asymmetric event topologies

NASA Astrophysics Data System (ADS)

Konar, Partha; Kong, Kyoungchul; Matchev, Konstantin T.; Park, Myeonghun

2010-04-01

We consider SUSY-like missing energy events at hadron colliders and critically examine the common assumption that the missing energy is the result of two identical missing particles. In order to experimentally test this hypothesis, we generalize the subsystem M T2 variable to the case of asymmetric event topologies, where the two SUSY decay chains terminate in different “children” particles. In this more general approach, the endpoint M T2( max) of the M T2 distribution now gives the mass {tilde M_p}left( {tilde M_c^{(a)},tilde M_c^{(b)}} right) of the parent particles as a function of two input children masses tilde M_c^{(a)} and tilde M_c^{(b)} . We propose two methods for an independent determination of the individual children masses M ( a) c and M ( b) c . First, in the presence of upstream transverse momentum PUTM the corresponding function {tilde M_p}left( {tilde M_c^{(a)},tilde M_c^{(b)},{P_{text{UTM}}}} right) is independent of PUTM at precisely the right values of the children masses. Second, the previously discussed M T2 “kink” is now generalized to a “ridge” on the 2-dimensional surface {tilde M_p}left( {tilde M_c^{(a)},tilde M_c^{(b)}} right) . As we show in several examples, quite often there is a special point along that ridge which marks the true values of the children masses. Our results allow collider experiments to probe a multi-component dark matter sector directly and without any theoretical prejudice.

Direct imaging search for the "missing link" in giant planet formation

NASA Astrophysics Data System (ADS)

Ngo, Henry; Mawet, Dimitri; Ruane, Garreth; Xuan, Wenhao; Bowler, Brendan; Cook, Therese; Zawol, Zoe

2018-01-01

While transit and radial velocity detection techniques have probed giant planet populations at close separations (within a few au), current direct imaging surveys are finding giant planets at separations of 10s-100s au. Furthermore, these directly imaged planets are very massive, including some with masses above the deuterium burning limit. It is not certain whether these objects represent the high mass end of planet formation scenarios or the low mass end of star formation. We present a direct imaging survey to search for the "missing link" population between the close-in RV and transiting giant planets and the extremely distant directly imaged giant planets (i.e. giant planets between 5-10 au). Finding and characterizing this population allows for comparisons with the formation models of closer-in planets and connects directly imaged planets with closer-in planets in semi-major axis phase space. In addition, microlensing surveys have suggested a large reservoir of giant planets exist in this region. To find these "missing link" giant planets, our survey searches for giant planets around M-stars. The ubiquity of M-stars provide a large number of nearby targets and their L-band contrast with planets allow for sensitivities to smaller planet masses than surveys conducted at shorter wavelengths. Along with careful target selection, we use Keck's L-band vector vortex coronagraph to enable sensitivities of a few Jupiter masses as close as 4 au to their host stars. We present our completed 2-year survey targeting 200 young (10-150 Myr), nearby M-stars and our ongoing work to follow-up over 40 candidate objects.

From School Choice to Student Voice.

ERIC Educational Resources Information Center

Heckman, Paul E.; Montera, Viki L.

2001-01-01

Educational mass marketing approaches are like fast-food franchises; they offer homogeneous, standardized products that cannot satisfy every consumer's needs. A niche market looks inside the masses to address more individual, specialized choices missing from the menu. Variability, not uniformity, should guide development of public schooling. (MLH)

40 CFR 98.185 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... facility that estimate annual process CO2 emissions using the carbon mass balance procedure in § 98.183(b... best available estimate of the mass of the material from all available process data or data used for accounting purposes (such as purchase records). ...

Reconstructing (super)trees from data sets with missing distances: not all is lost.

PubMed

Kettleborough, George; Dicks, Jo; Roberts, Ian N; Huber, Katharina T

2015-06-01

The wealth of phylogenetic information accumulated over many decades of biological research, coupled with recent technological advances in molecular sequence generation, presents significant opportunities for researchers to investigate relationships across and within the kingdoms of life. However, to make best use of this data wealth, several problems must first be overcome. One key problem is finding effective strategies to deal with missing data. Here, we introduce Lasso, a novel heuristic approach for reconstructing rooted phylogenetic trees from distance matrices with missing values, for data sets where a molecular clock may be assumed. Contrary to other phylogenetic methods on partial data sets, Lasso possesses desirable properties such as its reconstructed trees being both unique and edge-weighted. These properties are achieved by Lasso restricting its leaf set to a large subset of all possible taxa, which in many practical situations is the entire taxa set. Furthermore, the Lasso approach is distance-based, rendering it very fast to run and suitable for data sets of all sizes, including large data sets such as those generated by modern Next Generation Sequencing technologies. To better understand the performance of Lasso, we assessed it by means of artificial and real biological data sets, showing its effectiveness in the presence of missing data. Furthermore, by formulating the supermatrix problem as a particular case of the missing data problem, we assessed Lasso's ability to reconstruct supertrees. We demonstrate that, although not specifically designed for such a purpose, Lasso performs better than or comparably with five leading supertree algorithms on a challenging biological data set. Finally, we make freely available a software implementation of Lasso so that researchers may, for the first time, perform both rooted tree and supertree reconstruction with branch lengths on their own partial data sets. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Modified Einstein's gravity as a possible missing link between sub- and super-Chandrasekhar type Ia supernovae

NASA Astrophysics Data System (ADS)

Das, Upasana; Mukhopadhyay, Banibrata

2015-05-01

We explore the effect of modification to Einstein's gravity in white dwarfs for the first time in the literature, to the best of our knowledge. This leads to significantly sub- and super-Chandrasekhar limiting masses of white dwarfs, determined by a single model parameter. On the other hand, type Ia supernovae (SNeIa), a key to unravel the evolutionary history of the universe, are believed to be triggered in white dwarfs having mass close to the Chandrasekhar limit. However, observations of several peculiar, under- and over-luminous SNeIa argue for exploding masses widely different from this limit. We argue that explosions of the modified gravity induced sub- and super-Chandrasekhar limiting mass white dwarfs result in under- and over-luminous SNeIa respectively, thus unifying these two apparently disjoint sub-classes and, hence, serving as a missing link. Our discovery raises two fundamental questions. Is the Chandrasekhar limit unique? Is Einstein's gravity the ultimate theory for understanding astronomical phenomena? Both the answers appear to be no!

Search for squarks and gluinos in events with isolated leptons, jets and missing transverse momentum at $$\\sqrt{s}=8 $$ TeV with the ATLAS detector

DOE PAGES

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

2015-04-21

The results of a search for supersymmetry in final states containing at least one isolated lepton (electron or muon), jets and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider are reported. The search is based on proton-proton collision data at a centre-of-mass energy √ = 8 TeV collected in 2012, corresponding to an integrated luminosity of 20 fb -1. No significant excess above the Standard Model expectation is observed. Limits are set on supersymmetric particle masses for various supersymmetric models. Depending on the model, the search excludes gluino masses up to 1.32 TeV and squarkmore » masses up to 840 GeV. Limits are also set on the parameters of a minimal universal extra dimension model, excluding a compactification radius of 1/R c = 950 GeV for a cut-off scale times radius (ΛR c) of approximately 30.« less

Mind the Gap: The Prospects of Missing Data.

PubMed

McConnell, Meghan; Sherbino, Jonathan; Chan, Teresa M

2016-12-01

The increasing use of workplace-based assessments (WBAs) in competency-based medical education has led to large data sets that assess resident performance longitudinally. With large data sets, problems that arise from missing data are increasingly likely. The purpose of this study is to examine (1) whether data are missing at random across various WBAs, and (2) the relationship between resident performance and the proportion of missing data. During 2012-2013, a total of 844 WBAs of CanMEDs Roles were completed for 9 second-year emergency medicine residents. To identify whether missing data were randomly distributed across various WBAs, the total number of missing data points was calculated for each Role. To examine whether the amount of missing data was related to resident performance, 5 faculty members rank-ordered the residents based on performance. A median rank score was calculated for each resident and was correlated with the proportion of missing data. More data were missing for Health Advocate and Professional WBAs relative to other competencies ( P  < .001). Furthermore, resident rankings were not related to the proportion of missing data points ( r  = 0.29, P  > .05). The results of the present study illustrate that some CanMEDS Roles are less likely to be assessed than others. At the same time, the amount of missing data did not correlate with resident performance, suggesting lower-performing residents are no more likely to have missing data than their higher-performing peers. This article discusses several approaches to dealing with missing data.

Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Kelly, Karen; Weiss, Robert H; Kim, Kyoungmi

2017-03-01

With expanded access to, and decreased costs of, mass spectrometry, investigators are collecting and analyzing multiple biological matrices from the same subject such as serum, plasma, tissue and urine to enhance biomarker discoveries, understanding of disease processes and identification of therapeutic targets. Commonly, each biological matrix is analyzed separately, but multivariate methods such as MANOVAs that combine information from multiple biological matrices are potentially more powerful. However, mass spectrometric data typically contain large amounts of missing values, and imputation is often used to create complete data sets for analysis. The effects of imputation on multiple biological matrix analyses have not been studied. We investigated the effects of seven imputation methods (half minimum substitution, mean substitution, k-nearest neighbors, local least squares regression, Bayesian principal components analysis, singular value decomposition and random forest), on the within-subject correlation of compounds between biological matrices and its consequences on MANOVA results. Through analysis of three real omics data sets and simulation studies, we found the amount of missing data and imputation method to substantially change the between-matrix correlation structure. The magnitude of the correlations was generally reduced in imputed data sets, and this effect increased with the amount of missing data. Significant results from MANOVA testing also were substantially affected. In particular, the number of false positives increased with the level of missing data for all imputation methods. No one imputation method was universally the best, but the simple substitution methods (Half Minimum and Mean) consistently performed poorly. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Constructing a Coherent Problem Model to Facilitate Algebra Problem Solving in a Chemistry Context

ERIC Educational Resources Information Center

Ngu, Bing Hiong; Yeung, Alexander Seeshing; Phan, Huy P.

2015-01-01

An experiment using a sample of 11th graders compared text editing and worked examples approaches in learning to solve dilution and molarity algebra word problems in a chemistry context. Text editing requires students to assess the structure of a word problem by specifying whether the problem text contains sufficient, missing, or irrelevant…

"Asia's missing women" as a problem in applied evolutionary psychology?

PubMed

Brooks, Robert

2012-12-20

In many parts of Asia, the Middle East and North Africa, women and children are so undervalued, neglected, abused, and so often killed, that sex ratios are now strongly male biased. In recent decades, sex-biased abortion has exacerbated the problem. In this article I highlight several important insights from evolutionary biology into both the origin and the severe societal consequences of "Asia's missing women", paying particular attention to interactions between evolution, economics and culture. Son preferences and associated cultural practices like patrilineal inheritance, patrilocality and the Indian Hindu dowry system arise among the wealthy and powerful elites for reasons consistent with models of sex-biased parental investment. Those practices then spread via imitation as technology gets cheaper and economic development allows the middle class to grow rapidly. I will consider evidence from India, China and elsewhere that grossly male-biased sex ratios lead to increased crime, violence, local warfare, political instability, drug abuse, prostitution and trafficking of women. The problem of Asia's missing women presents a challenge for applied evolutionary psychology to help us understand and ameliorate sex ratio biases and their most severe consequences.

Sampled-data H∞ filtering for Markovian jump singularly perturbed systems with time-varying delay and missing measurements

NASA Astrophysics Data System (ADS)

Yan, Yifang; Yang, Chunyu; Ma, Xiaoping; Zhou, Linna

2018-02-01

In this paper, sampled-data H∞ filtering problem is considered for Markovian jump singularly perturbed systems with time-varying delay and missing measurements. The sampled-data system is represented by a time-delay system, and the missing measurement phenomenon is described by an independent Bernoulli random process. By constructing an ɛ-dependent stochastic Lyapunov-Krasovskii functional, delay-dependent sufficient conditions are derived such that the filter error system satisfies the prescribed H∞ performance for all possible missing measurements. Then, an H∞ filter design method is proposed in terms of linear matrix inequalities. Finally, numerical examples are given to illustrate the feasibility and advantages of the obtained results.

Limb Loss

MedlinePlus

... in amputation. Injuries, including from traffic accidents and military combat Cancer Birth defects Some amputees have phantom pain, which is the feeling of pain in the missing limb. Other physical problems include surgical complications and skin problems, if you ...

Personal Narratives of Loss and the Exhumation of Missing Persons in the Aftermath of War: In Search of Public and School Pedagogies of Mourning

ERIC Educational Resources Information Center

Zembylas, Michalinos

2011-01-01

This paper is grounded in a phenomenological-interpretive exploration of how mourning is experienced and understood by the victim's nuclear family--the victims are Greek-Cypriot missing persons whose remains have been recovered, identified and properly buried, after exhumations of mass graves in the aftermath of war. Particularly, the focus is on…

Search for supersymmetry in electroweak production with photons and large missing transverse energy in pp collisions at $$\\sqrt{s}$$ = 8 TeV

DOE PAGES

Khachatryan, Vardan

2016-06-01

Results are reported from a search for supersymmetry with gauge-mediated supersymmetry breaking in electroweak production. Final states with photons and large missing transverse energy (more » $$E_{\\mathrm{T}}^{\\text{miss}}$$) were examined. The data sample was collected in pp collisions at $$\\sqrt{s} = $$ 8 TeV with the CMS detector at the LHC and corresponds to 7.4 fb$$^{-1}$$. The analysis focuses on scenarios in which the lightest neutralino has bino- or wino-like components, resulting in decays to photons and gravitinos, where the gravitinos escape undetected. The data were obtained using a specially designed trigger with dedicated low thresholds, providing good sensitivity to signatures with photons, $$E_{\\mathrm{T}}^{\\text{miss}}$$, and low hadronic energy. No excess of events over the standard model expectation is observed. The results are interpreted using the model of general gauge mediation. With the wino mass fixed at 10 GeV above that of the bino, wino masses below 710 GeV are excluded at 95% confidence level. Lastly, constraints are also set in the context of two simplified models, for which the analysis sets the lowest cross section limits on the electroweak production of supersymmetric particles.« less

The initial masses of the red supergiant progenitors to Type II supernovae

NASA Astrophysics Data System (ADS)

Davies, Ben; Beasor, Emma R.

2018-02-01

There are a growing number of nearby supernovae (SNe) for which the progenitor star is detected in archival pre-explosion imaging. From these images it is possible to measure the progenitor's brightness a few years before explosion, and ultimately estimate its initial mass. Previous work has shown that II-P and II-L SNe have red supergiant (RSG) progenitors, and that the range of initial masses for these progenitors seems to be limited to ≲ 17 M⊙. This is in contrast with the cut-off of 25-30 M⊙ predicted by evolutionary models, a result that is termed the `red supergiant problem'. Here we investigate one particular source of systematic error present in converting pre-explosion photometry into an initial mass, which of the bolometric correction (BC) used to convert a single-band flux into a bolometric luminosity. We show, using star clusters, that RSGs evolve to later spectral types as they approach SN, which in turn causes the BC to become larger. Failure to account for this results in a systematic underestimate of a star's luminosity, and hence its initial mass. Using our empirically motivated BCs we reappraise the II-P and II-L SNe that have their progenitors detected in pre-explosion imaging. Fitting an initial mass function to these updated masses results in an increased upper mass cut-off of Mhi = 19.0^{+2.5}_{-1.3} M⊙, with a 95 per cent upper confidence limit of <27 M⊙. Accounting for finite sample size effects and systematic uncertainties in the mass-luminosity relationship raises the cut-off to Mhi = 25 M⊙ (<33 M⊙, 95 per cent confidence). We therefore conclude that there is currently no strong evidence for `missing' high-mass progenitors to core-collapse SNe.

Analysis of International Space Station Vehicle Materials on MISSE 6

NASA Technical Reports Server (NTRS)

Finckenor, Miria; Golden, Johnny; Kravchenko, Michael; O'Rourke, Mary Jane

2010-01-01

The International Space Station Materials and Processes team has multiple material samples on MISSE 6, 7 and 8 to observe Low Earth Orbit (LEO) environmental effects on Space Station materials. Optical properties, thickness/mass loss, surface elemental analysis, visual and microscopic analysis for surface change are some of the techniques employed in this investigation. Results for the following MISSE 6 samples materials will be presented: deionized water sealed anodized aluminum; Hyzod(tm) polycarbonate used to temporarily protect ISS windows; Russian quartz window material; Beta Cloth with Teflon(tm) reformulated without perfluorooctanoic acid (PFOA), and electroless nickel. Discussion for current and future MISSE materials experiments will be presented. MISSE 7 samples are: more deionized water sealed anodized aluminum, including Photofoil(tm); indium tin oxide (ITO) over-coated Kapton(tm) used as thermo-optical surfaces; mechanically scribed tin-plated beryllium-copper samples for "tin pest" growth (alpha/beta transformation); and beta cloth backed with a black coating rather than aluminization. MISSE 8 samples are: exposed "scrim cloth" (fiberglass weave) from the ISS solar array wing material, protective fiberglass tapes and sleeve materials, and optical witness samples to monitor contamination.

H∞ filtering for discrete-time systems subject to stochastic missing measurements: a decomposition approach

NASA Astrophysics Data System (ADS)

Gu, Zhou; Fei, Shumin; Yue, Dong; Tian, Engang

2014-07-01

This paper deals with the problem of H∞ filtering for discrete-time systems with stochastic missing measurements. A new missing measurement model is developed by decomposing the interval of the missing rate into several segments. The probability of the missing rate in each subsegment is governed by its corresponding random variables. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square with a less conservatism while the disturbance rejection attenuation is constrained to a given level by means of an H∞ performance index. Based on Lyapunov theory, the reliable filter parameters are characterised in terms of the feasibility of a set of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.

The effectiveness of supermarket posters in helping to find missing children.

PubMed

Lampinen, James Michael; Arnal, Jack; Hicks, Jason L

2009-03-01

One approach used to help find missing children is to place posters of them at the exits of supermarkets. The present research addresses the question of how effective that approach is likely to be. Posters of 8 missing children were displayed on a bulletin board at a cooperating grocery store. Customers leaving the store completed a survey and took a recognition memory test for the children. Most customers thought the problem of missing children was an important issue. However, the majority of customers also reported either not looking at the posters or only briefly looking at the posters. Recognition memory for children depicted in the posters did not reliably differ from chance. It appears that there is much room for improvement when it comes to increasing the attention paid to posters meant to help find missing children.

Search for new resonances in events with one lepton and missing transverse momentum in pp collisions at s = 13   TeV with the ATLAS detector

DOE PAGES

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

2016-09-28

A search for W' bosons in events with one lepton (electron or muon) and missing transverse momentum is presented. The search uses 3.2 fb -1 of pp collision data collected at √s=13 TeV by the ATLAS experiment at the LHC in 2015. The transverse mass distribution is examined and no significant excess of events above the level expected from Standard Model processes is observed. Upper limits on the W' boson cross-section times branching ratio to leptons are set as a function of the W' mass. Within the Sequential Standard Model W ' masses below 4.07 TeV are excluded at the 95%more » confidence level. This extends the limit set using LHC data at √s=8 TeV by around 800 GeV.« less

Search for direct top squark pair production in final states with one isolated lepton, jets, and missing transverse momentum in sqrt[s] = 7 TeV pp collisions using 4.7 fb(-10 of ATLAS data.

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; 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; Akesson, 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; Altheimer, A D; 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; Asman, 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; Barone, G; Barr, A J; Barreiro, F; Barreiro Guimarães da Costa, J; Barrillon, P; Bartoldus, R; Barton, A E; Bartsch, V; Basye, A; Bates, R L; Batkova, L; Batley, J R; Battaglia, A; Battistin, M; Bauer, F; Bawa, H S; Beale, S; Beau, T; Beauchemin, P H; Beccherle, R; Bechtle, P; Beck, H P; Becker, A K; Becker, S; Beckingham, M; Becks, K H; Beddall, A J; Beddall, A; Bedikian, S; Bednyakov, V A; Bee, C P; Beemster, L J; Begel, M; Behar Harpaz, S; Beimforde, M; Belanger-Champagne, C; Bell, P J; Bell, W H; Bella, G; Bellagamba, L; Bellina, F; Bellomo, M; Belloni, A; Beloborodova, O; Belotskiy, K; Beltramello, O; Benary, O; Benchekroun, D; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez Garcia, J A; Benjamin, D P; Benoit, M; Bensinger, J R; Benslama, K; Bentvelsen, S; Berge, D; Bergeaas Kuutmann, E; Berger, N; Berghaus, F; Berglund, E; Beringer, J; Bernat, P; Bernhard, R; Bernius, C; Berry, T; Bertella, C; Bertin, A; Bertolucci, F; Besana, M I; Besjes, G J; Besson, N; Bethke, S; Bhimji, W; Bianchi, R M; Bianco, M; Biebel, O; Bieniek, S P; Bierwagen, K; Biesiada, J; Biglietti, M; Bilokon, H; Bindi, M; Binet, S; Bingul, A; Bini, C; Biscarat, C; Bittner, B; Black, K M; Blair, R E; Blanchard, J-B; Blanchot, G; Blazek, T; Bloch, I; Blocker, C; Blocki, J; Blondel, A; Blum, W; Blumenschein, U; Bobbink, G J; Bobrovnikov, V B; Bocchetta, S S; Bocci, A; Boddy, C R; Boehler, M; Boek, J; Boelaert, N; Bogaerts, J A; Bogdanchikov, A; Bogouch, A; Bohm, C; Bohm, J; Boisvert, V; Bold, T; Boldea, V; Bolnet, N M; Bomben, M; Bona, M; Boonekamp, M; Bordoni, S; Borer, C; Borisov, A; Borissov, G; Borjanovic, I; Borri, M; Borroni, S; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Boterenbrood, H; Bouchami, J; Boudreau, J; Bouhova-Thacker, E V; Boumediene, D; Bourdarios, C; Bousson, N; Boveia, A; Boyd, J; Boyko, I R; Bozovic-Jelisavcic, I; Bracinik, J; Branchini, P; Brandt, A; Brandt, G; Brandt, O; Bratzler, U; Brau, B; Brau, J E; Braun, H M; Brazzale, S F; Brelier, B; Bremer, J; Brendlinger, K; Brenner, R; Bressler, S; Britton, D; Brochu, F M; Brock, I; Brock, R; Broggi, F; Bromberg, C; Bronner, J; Brooijmans, G; Brooks, T; Brooks, W K; Brown, G; Brown, H; Bruckman de Renstrom, P A; Bruncko, D; Bruneliere, R; Brunet, S; Bruni, A; Bruni, G; Bruschi, M; Buanes, T; Buat, Q; Bucci, F; Buchanan, J; Buchholz, P; Buckingham, R M; Buckley, A G; Buda, S I; Budagov, I A; Budick, B; Büscher, V; Bugge, L; Bulekov, O; Bundock, A C; Bunse, M; Buran, T; Burckhart, H; Burdin, S; Burgess, T; Burke, S; Busato, E; Bussey, P; Buszello, C P; Butler, B; Butler, J M; Buttar, C M; Butterworth, J M; Buttinger, W; Cabrera Urbán, S; Caforio, D; Cakir, O; Calafiura, P; Calderini, G; Calfayan, P; Calkins, R; Caloba, L P; Caloi, R; Calvet, D; Calvet, S; Camacho Toro, R; Camarri, P; Cameron, D; Caminada, L M; Caminal Armadans, R; Campana, S; Campanelli, M; Canale, V; Canelli, F; Canepa, A; Cantero, J; Cantrill, R; Capasso, L; Capeans Garrido, M D M; Caprini, I; Caprini, M; Capriotti, D; Capua, M; Caputo, R; Cardarelli, R; Carli, T; Carlino, G; Carminati, L; Caron, B; Caron, S; Carquin, E; Carrillo Montoya, G D; Carter, A A; Carter, J R; Carvalho, J; Casadei, D; Casado, M P; Cascella, M; Caso, C; Castaneda Hernandez, A M; Castaneda-Miranda, E; Castillo Gimenez, V; Castro, N F; Cataldi, G; Catastini, P; Catinaccio, A; Catmore, J R; Cattai, A; Cattani, G; Caughron, S; Cavaliere, V; Cavalleri, P; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Ceradini, F; Cerqueira, A S; Cerri, A; Cerrito, L; Cerutti, F; Cetin, S A; Chafaq, A; Chakraborty, D; Chalupkova, I; Chan, K; Chang, P; Chapleau, B; Chapman, J D; Chapman, J W; Chareyre, E; Charlton, D G; Chavda, V; Chavez Barajas, C A; Cheatham, S; Chekanov, S; Chekulaev, S V; Chelkov, G A; Chelstowska, M A; Chen, C; Chen, H; Chen, S; Chen, X; Chen, Y; Cheplakov, A; Cherkaoui El Moursli, R; Chernyatin, V; Cheu, E; Cheung, S L; Chevalier, L; Chiefari, G; Chikovani, L; Childers, J T; Chilingarov, A; Chiodini, G; Chisholm, A S; Chislett, R T; Chitan, A; Chizhov, M V; Choudalakis, G; Chouridou, S; Christidi, I A; Christov, A; Chromek-Burckhart, D; Chu, M L; Chudoba, J; Ciapetti, G; Ciftci, A K; Ciftci, R; Cinca, D; Cindro, V; Ciocca, C; Ciocio, A; Cirilli, M; Cirkovic, P; Citterio, M; Ciubancan, M; Clark, A; Clark, P J; Clarke, R N; Cleland, W; Clemens, J C; Clement, B; Clement, C; Coadou, Y; Cobal, M; Coccaro, A; Cochran, J; Coffey, L; Cogan, J G; Coggeshall, J; Cogneras, E; Colas, J; Cole, S; Colijn, A P; Collins, N J; Collins-Tooth, C; Collot, J; Colombo, T; Colon, G; Conde Muiño, P; Coniavitis, E; Conidi, M C; Consonni, S M; Consorti, V; Constantinescu, S; Conta, C; Conti, G; Conventi, F; Cooke, M; Cooper, B D; Cooper-Sarkar, A M; Copic, K; Cornelissen, T; Corradi, M; Corriveau, F; Cortes-Gonzalez, A; Cortiana, G; Costa, G; Costa, M J; Costanzo, D; Côté, D; Courneyea, L; Cowan, G; Cowden, C; Cox, B E; Cranmer, K; Crescioli, F; Cristinziani, M; Crosetti, G; Crépé-Renaudin, S; Cuciuc, C-M; Cuenca Almenar, C; Cuhadar Donszelmann, T; Curatolo, M; Curtis, C J; Cuthbert, C; Cwetanski, P; Czirr, H; Czodrowski, P; Czyczula, Z; D'Auria, S; D'Onofrio, M; D'Orazio, A; Da Cunha Sargedas De Sousa, M J; Da Via, C; Dabrowski, W; Dafinca, A; Dai, T; Dallapiccola, C; Dam, M; Dameri, M; Damiani, D S; Danielsson, H O; Dao, V; Darbo, G; Darlea, G L; Dassoulas, J A; Davey, W; Davidek, T; Davidson, N; Davidson, R; Davies, E; Davies, M; Davignon, O; Davison, A R; Davygora, Y; Dawe, E; Dawson, I; Daya-Ishmukhametova, R K; De, K; de Asmundis, R; De Castro, S; De Cecco, S; de Graat, J; De Groot, N; de Jong, P; De La Taille, C; De la Torre, H; De Lorenzi, F; de Mora, L; De Nooij, L; De Pedis, D; De Salvo, A; De Sanctis, U; De Santo, A; De Vivie De Regie, J B; De Zorzi, G; Dearnaley, W J; Debbe, R; Debenedetti, C; Dechenaux, B; Dedovich, D V; Degenhardt, J; Del Papa, C; Del Peso, J; Del Prete, T; Delemontex, T; Deliyergiyev, M; Dell'Acqua, A; Dell'Asta, L; Della Pietra, M; Della Volpe, D; Delmastro, M; Delsart, P A; Deluca, C; Demers, S; Demichev, M; Demirkoz, B; Deng, J; Denisov, S P; Derendarz, D; Derkaoui, J E; Derue, F; Dervan, P; Desch, K; Devetak, E; Deviveiros, P O; Dewhurst, A; Dewilde, B; Dhaliwal, S; Dhullipudi, R; Di Ciaccio, A; Di Ciaccio, L; Di Girolamo, A; Di Girolamo, B; Di Luise, S; Di Mattia, A; Di Micco, B; Di Nardo, R; Di Simone, A; Di Sipio, R; Diaz, M A; Diehl, E B; Dietrich, J; Dietzsch, T A; Diglio, S; Dindar Yagci, K; Dingfelder, J; Dinut, F; Dionisi, C; Dita, P; Dita, S; Dittus, F; Djama, F; Djobava, T; do Vale, M A B; Do Valle Wemans, A; Doan, T K O; Dobbs, M; Dobinson, R; Dobos, D; Dobson, E; Dodd, J; Doglioni, C; Doherty, T; Doi, Y; Dolejsi, J; Dolenc, I; Dolezal, Z; Dolgoshein, B A; Dohmae, T; Donadelli, M; Donini, J; Dopke, J; Doria, A; Dos Anjos, A; Dotti, A; Dova, M T; Doxiadis, A D; Doyle, A T; Dris, M; Dubbert, J; Dube, S; Duchovni, E; Duckeck, G; Duda, D; Dudarev, A; Dudziak, F; Dührssen, M; Duerdoth, I P; Duflot, L; Dufour, M-A; Duguid, L; Dunford, M; Duran Yildiz, H; Duxfield, R; Dwuznik, M; Dydak, F; Düren, M; 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Ferreira de Lima, D E; Ferrer, A; Ferrere, D; Ferretti, C; Ferretto Parodi, A; Fiascaris, M; Fiedler, F; Filipčič, A; Filthaut, F; Fincke-Keeler, M; Fiolhais, M C N; Fiorini, L; Firan, A; Fischer, G; Fisher, M J; Flechl, M; Fleck, I; Fleckner, J; Fleischmann, P; Fleischmann, S; Flick, T; Floderus, A; Flores Castillo, L R; Flowerdew, M J; Fonseca Martin, T; Formica, A; Forti, A; Fortin, D; Fournier, D; Fox, H; Francavilla, P; Franchini, M; Franchino, S; Francis, D; Frank, T; Franz, S; Fraternali, M; Fratina, S; French, S T; Friedrich, C; Friedrich, F; Froeschl, R; Froidevaux, D; Frost, J A; Fukunaga, C; Fullana Torregrosa, E; Fulsom, B G; Fuster, J; Gabaldon, C; Gabizon, O; Gadfort, T; Gadomski, S; Gagliardi, G; Gagnon, P; Galea, C; Gallas, E J; Gallo, V; Gallop, B J; Gallus, P; Gan, K K; Gao, Y S; Gaponenko, A; Garberson, F; Garcia-Sciveres, M; García, C; García Navarro, J E; Gardner, R W; Garelli, N; Garitaonandia, H; Garonne, V; Gatti, C; Gaudio, G; Gaur, B; Gauthier, L; Gauzzi, P; Gavrilenko, I L; 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2012-11-21

A search is presented for direct top squark pair production in final states with one isolated electron or muon, jets, and missing transverse momentum in proton-proton collisions at sqrt[s] = 7 TeV. The measurement is based on 4.7 fb(-1) of data collected with the ATLAS detector at the LHC. Each top squark is assumed to decay to a top quark and the lightest supersymmetric particle (LSP). The data are found to be consistent with standard model expectations. Top squark masses between 230 GeV and 440 GeV are excluded with 95% confidence for massless LSPs, and top squark masses around 400 GeV are excluded for LSP masses up to 125 GeV.

Search for new particles in events with one lepton and missing transverse momentum in pp collisions at = 8 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Khalek, S. Abdel; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Almond, J.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Gonzalez, B. Alvarez; Alviggi, M. G.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Mayes, J. Backus; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, S.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, M.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Garcia, J. A. Benitez; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertsche, D.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; De Mendizabal, J. Bilbao; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boddy, C. R.; Boehler, M.; Boek, J.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. 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I.; Zimmermann, C.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Zinonos, Z.; Ziolkowski, M.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zutshi, V.; Zwalinski, L.

2014-09-01

This paper presents a search for new particles in events with one lepton (electron or muon) and missing transverse momentum using 20.3 fb-1 of proton-proton collision data at = 8 TeV recorded by the ATLAS experiment at the Large Hadron Collider. No significant excess beyond Standard Model expectations is observed. A W ' with Sequential Standard Model couplings is excluded at the 95% confidence level for masses up to 3.24 TeV. Excited chiral bosons ( W *) with equivalent coupling strengths are excluded for masses up to 3.21 TeV. In the framework of an effective field theory limits are also set on the dark matter-nucleon scattering cross-section as well as the mass scale M * of the unknown mediating interaction for dark matter pair production in association with a leptonically decaying W. [Figure not available: see fulltext.

Search for new resonances in events with one lepton and missing transverse momentum in pp collisions at √{ s} = 13 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

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A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero Y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagáčová, M.; Pagan Griso, S.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Palma, A.; St. Panagiotopoulou, E.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Perez Codina, E.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reisin, H.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosenthal, O.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Salazar Loyola, J. E.; Salek, D.; Sales de Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sandbach, R. L.; Sander, H. G.; Sandhoff, M.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sasaki, Y.; Sato, K.; Sauvage, G.; Sauvan, E.; Savage, G.; Savard, P.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schwegler, Ph.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Vallecorsa, S.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2016-11-01

A search for W‧ bosons in events with one lepton (electron or muon) and missing transverse momentum is presented. The search uses 3.2 fb-1 of pp collision data collected at √{ s} = 13 TeV by the ATLAS experiment at the LHC in 2015. The transverse mass distribution is examined and no significant excess of events above the level expected from Standard Model processes is observed. Upper limits on the W‧ boson cross-section times branching ratio to leptons are set as a function of the W‧ mass. Within the Sequential Standard Model W‧ masses below 4.07 TeV are excluded at the 95% confidence level. This extends the limit set using LHC data at √{ s} = 8 TeV by around 800 GeV.

Search for squarks and gluinos using final states with jets and missing transverse momentum with the ATLAS detector in √{ s} = 7 TeV proton-proton collisions

NASA Astrophysics Data System (ADS)

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

2011-07-01

A search for squarks and gluinos in final states containing jets, missing transverse momentum and no electrons or muons is presented. The data were recorded by the ATLAS experiment in √{ s} = 7 TeV proton-proton collisions at the Large Hadron Collider. No excess above the Standard Model background expectation was observed in 35 pb-1 of analysed data. Gluino masses below 500 GeV are excluded at the 95% confidence level in simplified models containing only squarks of the first two generations, a gluino octet and a massless neutralino. The exclusion increases to 870 GeV for equal mass squarks and gluinos. In MSUGRA/CMSSM models with tan β = 3, A0 = 0 and μ > 0, squarks and gluinos of equal mass are excluded below 775 GeV. These are the most stringent limits to date.

Search for gluinos and scalar quarks in pp collisions at square root[s] = 1.8 TeV using the missing energy plus multijets signature.

PubMed

Affolder, T; Akimoto, H; Akopian, A; Albrow, M G; Amaral, P; Amidei, D; Anikeev, K; Antos, J; Apollinari, G; Arisawa, T; Artikov, A; Asakawa, T; Ashmanskas, W; Azfar, F; Azzi-Bacchetta, P; Bacchetta, N; Bachacou, H; Bailey, S; de Barbaro, P; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Barone, M; Bauer, G; Bedeschi, F; Belforte, S; Bell, W H; Bellettini, G; Bellinger, J; Benjamin, D; Bensinger, J; Beretvas, A; Berge, J P; Berryhill, J; Bhatti, A; Binkley, M; Bisello, D; Bishai, M; Blair, R E; Blocker, C; Bloom, K; Blumenfeld, B; Blusk, S R; Bocci, A; Bodek, A; Bokhari, W; Bolla, G; Bonushkin, Y; Bortoletto, D; Boudreau, J; Brandl, A; van den Brink, S; Bromberg, C; Brozovic, M; Brubaker, E; Bruner, N; Buckley-Geer, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Byon-Wagner, A; Byrum, K L; Cabrera, S; Calafiura, P; Campbell, M; Carithers, W; Carlson, J; Carlsmith, D; Caskey, W; Castro, A; Cauz, D; Cerri, A; Chan, A W; Chang, P S; Chang, P T; Chapman, J; Chen, C; Chen, Y C; Cheng, M-T; Chertok, M; Chiarelli, G; Chirikov-Zorin, I; Chlachidze, G; Chlebana, F; Christofek, L; Chu, M L; Chung, Y S; Ciobanu, C I; Clark, A G; Connolly, A; Conway, J; Cordelli, M; Cranshaw, J; Cropp, R; Culbertson, R; Dagenhart, D; D'Auria, S; DeJongh, F; Dell'Agnello, S; Dell'Orso, M; Demortier, L; Deninno, M; Derwent, P F; Devlin, T; Dittmann, J R; Dominguez, A; Donati, S; Done, J; D'Onofrio, M; Dorigo, T; Eddy, N; Einsweiler, K; Elias, J E; Engels, E; Erbacher, R; Errede, D; Errede, S; Fan, Q; Feild, R G; Fernandez, J P; Ferretti, C; Field, R D; Fiori, I; Flaugher, B; Foster, G W; Franklin, M; Freeman, J; Friedman, J; Frisch, H J; Fukui, Y; Furic, I; Galeotti, S; Gallas, A; Gallinaro, M; Gao, T; Garcia-Sciveres, M; Garfinkel, A F; Gatti, P; Gay, C; Gerdes, D W; Giannetti, P; Giromini, P; Glagolev, V; Glenzinski, D; Gold, M; Goldstein, J; Gorelov, I; Goshaw, A T; Gotra, Y; Goulianos, K; Green, C; Grim, G; Gris, P; Groer, L; Grosso-Pilcher, C; Guenther, M; Guillian, G; Guimaraes da Costa, J; Haas, R M; Haber, C; Hahn, S R; Hall, C; Handa, T; Handler, R; Hao, W; Happacher, F; Hara, K; Hardman, A D; Harris, R M; Hartmann, F; Hatakeyama, K; Hauser, J; Heinrich, J; Heiss, A; Herndon, M; Hill, C; Hoffman, K D; Holck, C; Hollebeek, R; Holloway, L; Hughes, R; Huston, J; Huth, J; Ikeda, H; Incandela, J; Introzzi, G; Iwai, J; Iwata, Y; James, E; Jones, M; Joshi, U; Kambara, H; Kamon, T; Kaneko, T; Karr, K; Kasha, H; Kato, Y; Keaffaber, T A; Kelley, K; Kelly, M; Kennedy, R D; Kephart, R; Khazins, D; Kikuchi, T; Kilminster, B; Kim, B J; Kim, D H; Kim, H S; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kirby, M; Kirk, M; Kirsch, L; Klimenko, S; Koehn, P; Kondo, K; Konigsberg, J; Korn, A; Korytov, A; Kovacs, E; Kroll, J; Kruse, M; Kuhlmann, S E; Kurino, K; Kuwabara, T; Laasanen, A T; Lai, N; Lami, S; Lammel, S; Lancaster, J; Lancaster, M; Lander, R; Lath, A; Latino, G; LeCompte, T; Lee, A M; Lee, K; Leone, S; Lewis, J D; Lindgren, M; Liss, T M; Liu, J B; Liu, Y C; Litvintsev, D O; Lobban, O; Lockyer, N; Loken, J; Loreti, M; Lucchesi, D; Lukens, P; Lusin, S; Lyons, L; Lys, J; Madrak, R; Maeshima, K; Maksimovic, P; Malferrari, L; Mangano, M; Mariotti, M; Martignon, G; Martin, A; Matthews, J A J; Mayer, J; Mazzanti, P; McFarland, K S; McIntyre, P; McKigney, E; Menguzzato, M; Menzione, A; Mesropian, C; Meyer, A; Miao, T; Miller, R; Miller, J S; Minato, H; Miscetti, S; Mishina, M; Mitselmakher, G; Moggi, N; Moore, E; Moore, R; Morita, Y; Moulik, T; Mulhearn, M; Mukherjee, A; Muller, T; Munar, A; Murat, P; Murgia, S; Nachtman, J; Nagaslaev, V; Nahn, S; Nakada, H; Nakano, I; Nelson, C; Nelson, T; Neu, C; Neuberger, D; Newman-Holmes, C; Ngan, C-Y P; Niu, H; Nodulman, L; Nomerotski, A; Oh, S H; Oh, Y D; Ohmoto, T; Ohsugi, T; Oishi, R; Okusawa, T; Olsen, J; Orejudos, W; Pagliarone, C; Palmonari, F; Paoletti, R; Papadimitriou, V; Partos, D; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pescara, L; Phillips, T J; Piacentino, G; Pitts, K T; Pompos, A; Pondrom, L; Pope, G; Popovic, M; Prokoshin, F; Proudfoot, J; Ptohos, F; Pukhov, O; Punzi, G; Rakitine, A; Ratnikov, F; Reher, D; Reichold, A; Ribon, A; Riegler, W; Rimondi, F; Ristori, L; Riveline, M; Robertson, W J; Robinson, A; Rodrigo, T; Rolli, S; Rosenson, L; Roser, R; Rossin, R; Roy, A; Ruiz, A; Safonov, A; St Denis, R; Sakumoto, W K; Saltzberg, D; Sanchez, C; Sansoni, A; Santi, L; Sato, H; Savard, P; Schlabach, P; Schmidt, E E; Schmidt, M P; Schmitt, M; Scodellaro, L; Scott, A; Scribano, A; Segler, S; Seidel, S; Seiya, Y; Semenov, A; Semeria, F; Shah, T; Shapiro, M D; Shepard, P F; Shibayama, T; Shimojima, M; Shochet, M; Sidoti, A; Siegrist, J; Sill, A; Sinervo, P; Singh, P; Slaughter, A J; Sliwa, K; Smith, C; Snider, F D; Solodsky, A; Spalding, J; Speer, T; Sphicas, P; Spinella, F; Spiropulu, M; Spiegel, L; Steele, J; Stefanini, A; Strologas, J; Strumia, F; Stuart, D; Sumorok, K; Suzuki, T; Takano, T; Takashima, R; Takikawa, K; Tamburello, P; Tanaka, M; Tannenbaum, B; Tecchio, M; Tesarek, R; Teng, P K; Terashi, K; Tether, S; Thompson, A S; Thurman-Keup, R; Tipton, P; Tkaczyk, S; Toback, D; Tollefson, K; Tollestrup, A; Tonelli, D; Toyoda, H; Trischuk, W; de Troconiz, J F; Tseng, J; Turini, N; Ukegawa, F; Vaiciulis, T; Valls, J; Vejcik, S; Velev, G; Veramendi, G; Vidal, R; Vila, I; Vilar, R; Volobouev, I; von der Mey, M; Vucinic, D; Wagner, R G; Wagner, R L; Wallace, N B; Wan, Z; Wang, C; Wang, M J; Ward, B; Waschke, S; Watanabe, T; Waters, D; Watts, T; Webb, R; Wenzel, H; Wester, W C; Wicklund, A B; Wicklund, E; Wilkes, T; Williams, H H; Wilson, P; Winer, B L; Winn, D; Wolbers, S; Wolinski, D; Wolinski, J; Wolinski, S; Worm, S; Wu, X; Wyss, J; Yao, W; Yagil, A; Yeh, G P; Yoh, J; Yosef, C; Yoshida, T; Yu, I; Yu, S; Yu, Z; Zanetti, A; Zetti, F; Zucchelli, S

2002-01-28

We have performed a search for gluinos (g) and scalar quarks (q) in a data sample of 84 pb(-1) of pp collisions at square root[s] = 1.8 TeV, recorded by the Collider Detector at Fermilab. We investigate the final state of large missing transverse energy and three or more jets, a characteristic signature in R-parity-conserving supersymmetric models. The analysis has been performed "blind," in that the inspection of the signal region is made only after the predictions from standard model backgrounds have been calculated. Comparing the data with predictions of constrained supersymmetric models, we exclude gluino masses below 195 GeV/c2 (95% C.L.), independent of the squark mass. For the case m(q) approximately m(g), gluino masses below 300 GeV/c2 are excluded.

Covariance Structure Model Fit Testing under Missing Data: An Application of the Supplemented EM Algorithm

ERIC Educational Resources Information Center

Cai, Li; Lee, Taehun

2009-01-01

We apply the Supplemented EM algorithm (Meng & Rubin, 1991) to address a chronic problem with the "two-stage" fitting of covariance structure models in the presence of ignorable missing data: the lack of an asymptotically chi-square distributed goodness-of-fit statistic. We show that the Supplemented EM algorithm provides a…

The case of the missing third.

PubMed

Robertson, Robin

2005-01-01

How is it that form arises out of chaos? In attempting to deal with this primary question, time and again a "Missing Third" is posited that lies between extremes. The problem of the "Missing Third" can be traced through nearly the entire history of thought. The form it takes, the problems that arise from it, the solutions suggested for resolving it, are each representative of an age. This paper traces the issue from Plato and Parmenides in the 4th--5th centuries, B.C.; to Neoplatonism in the 3rd--5th centuries; to Locke and Descartes in the 17th century; on to Berkeley and Kant in the 18th century; Fechner and Wundt in the 19th century; to behaviorism and Gestalt psychology, Jung, early in the 20th century, ethology and cybernetics later in the 20th century, then culminates late in the 20th century, with chaos theory.

Sensitivity to imputation models and assumptions in receiver operating characteristic analysis with incomplete data

PubMed Central

Karakaya, Jale; Karabulut, Erdem; Yucel, Recai M.

2015-01-01

Modern statistical methods using incomplete data have been increasingly applied in a wide variety of substantive problems. Similarly, receiver operating characteristic (ROC) analysis, a method used in evaluating diagnostic tests or biomarkers in medical research, has also been increasingly popular problem in both its development and application. While missing-data methods have been applied in ROC analysis, the impact of model mis-specification and/or assumptions (e.g. missing at random) underlying the missing data has not been thoroughly studied. In this work, we study the performance of multiple imputation (MI) inference in ROC analysis. Particularly, we investigate parametric and non-parametric techniques for MI inference under common missingness mechanisms. Depending on the coherency of the imputation model with the underlying data generation mechanism, our results show that MI generally leads to well-calibrated inferences under ignorable missingness mechanisms. PMID:26379316

Search for new physics in events with two soft oppositely charged leptons and missing transverse momentum 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.; Escalante Del Valle, A.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Taurok, A.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Marchesini, I.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Bilin, B.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Dorney, B.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Kalsi, A. 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M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Lezki, S.; Maggi, G.; Maggi, M.; Marangelli, B.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Zito, G.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Borgonovi, L.; Braibant-Giacomelli, S.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Iemmi, F.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. 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A.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Fanzago, F.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Lujan, P.; Margoni, M.; Meneguzzo, A. T.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Tiko, A.; Torassa, E.; Zanetti, M.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Biasini, M.; Bilei, G. M.; Cecchi, C.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Manoni, E.; Mantovani, G.; Mariani, V.; Menichelli, M.; Rossi, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bianchini, L.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giannini, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Manca, E.; Mandorli, G.; Messineo, A.; Palla, F.; Rizzi, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Daci, N.; Del Re, D.; Di Marco, E.; Diemoz, M.; Gelli, S.; Longo, E.; 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.; Castello, R.; 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.; 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.; Kim, H.; Moon, D. H.; Oh, G.; Brochero Cifuentes, J. A.; Goh, J.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Kim, J. S.; Lee, H.; Lee, K.; Nam, K.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Choi, Y.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Reyes-Almanza, R.; Ramirez-Sanchez, G.; Duran-Osuna, M. C.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Rabadan-Trejo, R. I.; Lopez-Fernandez, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Eysermans, J.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Galinhas, B.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Seixas, J.; Strong, G.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Afanasiev, S.; Alexakhin, V.; Bunin, P.; Gavrilenko, M.; Golunov, A.; Golutvin, I.; Gorbounov, N.; Gorbunov, I.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Shmatov, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sosnov, D.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Stepennov, A.; Stolin, V.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Bylinkin, A.; Chadeeva, M.; Parygin, P.; Philippov, D.; Polikarpov, S.; Popova, E.; Rusinov, V.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; 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.; Shtol, D.; Skovpen, Y.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Godizov, A.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Mandrik, P.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Babaev, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Alcaraz Maestre, J.; Bachiller, I.; Barrio Luna, M.; Cerrada, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Moran, D.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Redondo, I.; Romero, L.; Soares, M. S.; Triossi, A.; Álvarez Fernández, A.; Albajar, C.; de Trocóniz, J. F.; Cuevas, J.; Erice, C.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Vischia, P.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Chazin Quero, B.; Duarte Campderros, J.; Fernandez, M.; Fernández Manteca, P. J.; Garcia-Ferrero, J.; García Alonso, A.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Martinez Ruiz del Arbol, P.; Matorras, F.; Piedra Gomez, J.; Prieels, C.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Akgun, B.; Auffray, E.; Baillon, P.; Ball, A. H.; Barney, D.; Bendavid, J.; Bianco, M.; Bocci, A.; Botta, C.; Camporesi, T.; Cepeda, M.; Cerminara, G.; Chapon, E.; Chen, Y.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Deelen, N.; Dobson, M.; du Pree, T.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Fallavollita, F.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gilbert, A.; Gill, K.; Glege, F.; Gulhan, D.; Hegeman, J.; Innocente, V.; Jafari, A.; Janot, P.; Karacheban, O.; Kieseler, J.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Krammer, M.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Milenovic, P.; Moortgat, F.; Mulders, M.; Neugebauer, H.; Ngadiuba, J.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pitters, F. M.; Rabady, D.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Selvaggi, M.; Sharma, A.; Silva, P.; Sphicas, P.; Stakia, A.; Steggemann, J.; Stoye, M.; Tosi, M.; Treille, D.; Tsirou, A.; Veckalns, V.; Verweij, M.; Zeuner, W. D.; Bertl, W.; Caminada, L.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Backhaus, M.; Bäni, L.; Berger, P.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dorfer, C.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Klijnsma, T.; Lustermann, W.; Mangano, B.; Marionneau, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Reichmann, M.; Sanz Becerra, D. A.; Schönenberger, M.; Shchutska, L.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Canelli, M. F.; De Cosa, A.; Del Burgo, R.; Donato, S.; Galloni, C.; Hreus, T.; Kilminster, B.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Schweiger, K.; Seitz, C.; Takahashi, Y.; Zucchetta, A.; Candelise, V.; Chang, Y. H.; Cheng, K. y.; Doan, T. H.; Jain, Sh.; Khurana, R.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Paganis, E.; Psallidas, A.; Steen, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Bat, A.; Boran, F.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Eskut, E.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Tali, B.; Tok, U. G.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Karapinar, G.; Ocalan, K.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Komurcu, Y.; Grynyov, B.; Levchuk, L.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Davignon, O.; Flacher, H.; Goldstein, J.; Heath, G. P.; Heath, H. F.; Kreczko, L.; Newbold, D. M.; Paramesvaran, S.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Linacre, J.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Womersley, W. J.; Auzinger, G.; Bainbridge, R.; Bloch, P.; Borg, J.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; Della Negra, M.; Di Maria, R.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Komm, M.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Palladino, V.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wardle, N.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Morton, A.; Reid, I. D.; Teodorescu, L.; Zahid, S.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Smith, C.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Hadley, M.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Lee, J.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Stolp, D.; Taylor, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Regnard, S.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Karapostoli, G.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Si, W.; Wang, L.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Gilbert, D.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Citron, M.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; Gouskos, L.; Heller, R.; Incandela, J.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bornheim, A.; Bunn, J.; Dutta, I.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T. Q.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Macdonald, E.; Mulholland, T.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chaves, J.; Cheng, Y.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Quach, D.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Alyari, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; 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.; Savoy-Navarro, A.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Wu, W.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Joshi, B. M.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Shi, K.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; 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.; Rogan, C.; 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.; Rebassoo, F.; Wright, D.; Baden, A.; Baron, O.; Belloni, A.; Eno, S. C.; Feng, Y.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bauer, G.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Harris, P.; Hsu, D.; Hu, M.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; 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.; Wadud, M. A.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Golf, F.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Freer, C.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Orimoto, T.; Teixeira De Lima, R.; Wamorkar, T.; Wang, B.; Wisecarver, A.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Bucci, R.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Li, W.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Siddireddy, P.; Smith, G.; Taroni, S.; Wayne, M.; Wightman, A.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Ling, T. Y.; Liu, B.; Luo, W.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Kalogeropoulos, A.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Das, S.; Folgueras, S.; Gutay, L.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xiao, R.; Xie, W.; Cheng, T.; Parashar, N.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. M.; Guilbaud, M.; Kilpatrick, M.; Li, W.; Michlin, B.; Padley, B. P.; Roberts, J.; Rorie, J.; Shi, W.; Tu, Z.; Zabel, J.; Zhang, A.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Mengke, T.; Muthumuni, S.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Poudyal, N.; Sturdy, J.; Thapa, P.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Carlsmith, D.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Rekovic, V.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Woods, N.; CMS Collaboration

2018-07-01

A search is presented for new physics in events with two low-momentum, oppositely charged leptons (electrons or muons) and missing transverse momentum in proton-proton collisions at a centre-of-mass energy of 13 TeV. The data collected using the CMS detector at the LHC correspond to an integrated luminosity of 35.9fb-1. The observed event yields are consistent with the expectations from the standard model. The results are interpreted in terms of pair production of charginos and neutralinos (χ˜ 1± and χ˜ 20) with nearly degenerate masses, as expected in natural supersymmetry models with light higgsinos, as well as in terms of the pair production of top squarks (t ˜), when the lightest neutralino and the top squark have similar masses. At 95% confidence level, wino-like χ˜ 1± / χ˜ 20 masses are excluded up to 230 GeV for a mass difference of 20 GeV relative to the lightest neutralino. In the higgsino-like model, masses are excluded up to 168 GeV for the same mass difference. For t ˜ pair production, top squark masses up to 450 GeV are excluded for a mass difference of 40 GeV relative to the lightest neutralino.

Bubbles, voids, and bumps in time: The new cosmology

NASA Astrophysics Data System (ADS)

Cornell, James

The history and current status of theoretical and observational cosmology are examined in chapters based on the Lowell Lectures, given in Boston and Washington DC in spring 1987. Topics addressed include the Aristotelian, Copernican, Newtonian, and Einsteinian universes; the measurement of the universe (redshifts and standard candles); mapping the universe (slices and bubbles); dark matter and missing mass; and the big bang and cosmic inflation. Six basic outstanding problems are identified, and the potential contributions of planned ground-based and space observatories to their solution are discussed. Particular attention is given to CCD detectors for large ground-based telescopes, the VLA, VLBI arrays, the ESO Very Large Telescope, the 10-m Keck telescope on Mauna Kea, the Hubble Space Telescope, the Gamma-Ray Observatory, and the Advanced X-ray Astrophysics Facility.

Diagnostic tolerance for missing sensor data

NASA Technical Reports Server (NTRS)

Scarl, Ethan A.

1989-01-01

For practical automated diagnostic systems to continue functioning after failure, they must not only be able to diagnose sensor failures but also be able to tolerate the absence of data from the faulty sensors. It is shown that conventional (associational) diagnostic methods will have combinatoric problems when trying to isolate faulty sensors, even if they adequately diagnose other components. Moreover, attempts to extend the operation of diagnostic capability past sensor failure will necessarily compound those difficulties. Model-based reasoning offers a structured alternative that has no special problems diagnosing faulty sensors and can operate gracefully when sensor data is missing.

N-body experiments and missing mass in clusters of galaxies

NASA Technical Reports Server (NTRS)

Smith, H.; Hintzen, P.; Sofia, S.; Oegerle, W.; Scott, J.; Holman, G.

1979-01-01

It is commonly assumed that the distributions of surface density and radial-velocity dispersion in clusters of galaxies are sensitive tracers of the underlying distribution of any unseen mass. N-body experiments have been used to test this assumption. Calculations with equal-mass systems indicate that the effects of the underlying mass distribution cannot be detected by observations of the surface-density or radial-velocity distributions, and the existence of an extended binding mass in all well-studied clusters would be consistent with available observations.

MPPhys—A many-particle simulation package for computational physics education

NASA Astrophysics Data System (ADS)

Müller, Thomas

2014-03-01

In a first course to classical mechanics elementary physical processes like elastic two-body collisions, the mass-spring model, or the gravitational two-body problem are discussed in detail. The continuation to many-body systems, however, is deferred to graduate courses although the underlying equations of motion are essentially the same and although there is a strong motivation for high-school students in particular because of the use of particle systems in computer games. The missing link between the simple and the more complex problem is a basic introduction to solve the equations of motion numerically which could be illustrated, however, by means of the Euler method. The many-particle physics simulation package MPPhys offers a platform to experiment with simple particle simulations. The aim is to give a principle idea how to implement many-particle simulations and how simulation and visualization can be combined for interactive visual explorations. Catalogue identifier: AERR_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERR_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 111327 No. of bytes in distributed program, including test data, etc.: 608411 Distribution format: tar.gz Programming language: C++, OpenGL, GLSL, OpenCL. Computer: Linux and Windows platforms with OpenGL support. Operating system: Linux and Windows. RAM: Source Code 4.5 MB Complete package 242 MB Classification: 14, 16.9. External routines: OpenGL, OpenCL Nature of problem: Integrate N-body simulations, mass-spring models Solution method: Numerical integration of N-body-simulations, 3D-Rendering via OpenGL. Running time: Problem dependent

Imaging in gynaecology: How good are we in identifying endometriomas?

PubMed Central

Van Holsbeke, C.; Van Calster, B.; Guerriero, S.; Savelli, L.; Leone, F.; Fischerova, D; Czekierdowski, A.; Fruscio, R.; Veldman, J.; Van de Putte, G.; Testa, A.C.; Bourne, T.; Valentin, L.; Timmerman, D.

2009-01-01

Aim: To evaluate the performance of subjective evaluation of ultrasound findings (pattern recognition) to discriminate endometriomas from other types of adnexal masses and to compare the demographic and ultrasound characteristics of the true positive cases with those cases that were presumed to be an endometrioma but proved to have a different histology (false positive cases) and the endometriomas missed by pattern recognition (false negative cases). Methods: All patients in the International Ovarian Tumor Analysis (IOTA ) studies were included for analysis. In the IOTA studies, patients with an adnexal mass that were preoperatively examined by expert sonologists following the same standardized ultrasound protocol were prospectively included in 21 international centres. Sensitivity and specificity to discriminate endometriomas from other types of adnexal masses using pattern recognition were calculated. Ultrasound and some demographic variables of the masses presumed to be an endometrioma were analysed (true positives and false positives) and compared with the variables of the endometriomas missed by pattern recognition (false negatives) as well as the true negatives. Results: IOTA phase 1, 1b and 2 included 3511 patients of which 2560 were benign (73%) and 951 malignant (27%). The dataset included 713 endometriomas. Sensitivity and specificity for pattern recognition were 81% (577/713) and 97% (2723/2798). The true positives were more often unilocular with ground glass echogenicity than the masses in any other category. Among the 75 false positive cases, 66 were benign but 9 were malignant (5 borderline tumours, 1 rare primary invasive tumour and 3 endometrioid adenocarcinomas). The presumed diagnosis suggested by the sonologist in case of a missed endometrioma was mostly functional cyst or cystadenoma. Conclusion: Expert sonologists can quite accurately discriminate endometriomas from other types of adnexal masses, but in this dataset 1% of the masses that were classified as endometrioma by pattern recognition proved to be malignancies. PMID:25478066

Use of missing data methods in longitudinal studies: the persistence of bad practices in developmental psychology.

PubMed

Jelicić, Helena; Phelps, Erin; Lerner, Richard M

2009-07-01

Developmental science rests on describing, explaining, and optimizing intraindividual changes and, hence, empirically requires longitudinal research. Problems of missing data arise in most longitudinal studies, thus creating challenges for interpreting the substance and structure of intraindividual change. Using a sample of reports of longitudinal studies obtained from three flagship developmental journals-Child Development, Developmental Psychology, and Journal of Research on Adolescence-we examined the number of longitudinal studies reporting missing data and the missing data techniques used. Of the 100 longitudinal studies sampled, 57 either reported having missing data or had discrepancies in sample sizes reported for different analyses. The majority of these studies (82%) used missing data techniques that are statistically problematic (either listwise deletion or pairwise deletion) and not among the methods recommended by statisticians (i.e., the direct maximum likelihood method and the multiple imputation method). Implications of these results for developmental theory and application, and the need for understanding the consequences of using statistically inappropriate missing data techniques with actual longitudinal data sets, are discussed.

Missing Data in Clinical Studies: Issues and Methods

PubMed Central

Ibrahim, Joseph G.; Chu, Haitao; Chen, Ming-Hui

2012-01-01

Missing data are a prevailing problem in any type of data analyses. A participant variable is considered missing if the value of the variable (outcome or covariate) for the participant is not observed. In this article, various issues in analyzing studies with missing data are discussed. Particularly, we focus on missing response and/or covariate data for studies with discrete, continuous, or time-to-event end points in which generalized linear models, models for longitudinal data such as generalized linear mixed effects models, or Cox regression models are used. We discuss various classifications of missing data that may arise in a study and demonstrate in several situations that the commonly used method of throwing out all participants with any missing data may lead to incorrect results and conclusions. The methods described are applied to data from an Eastern Cooperative Oncology Group phase II clinical trial of liver cancer and a phase III clinical trial of advanced non–small-cell lung cancer. Although the main area of application discussed here is cancer, the issues and methods we discuss apply to any type of study. PMID:22649133

VARIABLE SELECTION FOR REGRESSION MODELS WITH MISSING DATA

PubMed Central

Garcia, Ramon I.; Ibrahim, Joseph G.; Zhu, Hongtu

2009-01-01

We consider the variable selection problem for a class of statistical models with missing data, including missing covariate and/or response data. We investigate the smoothly clipped absolute deviation penalty (SCAD) and adaptive LASSO and propose a unified model selection and estimation procedure for use in the presence of missing data. We develop a computationally attractive algorithm for simultaneously optimizing the penalized likelihood function and estimating the penalty parameters. Particularly, we propose to use a model selection criterion, called the ICQ statistic, for selecting the penalty parameters. We show that the variable selection procedure based on ICQ automatically and consistently selects the important covariates and leads to efficient estimates with oracle properties. The methodology is very general and can be applied to numerous situations involving missing data, from covariates missing at random in arbitrary regression models to nonignorably missing longitudinal responses and/or covariates. Simulations are given to demonstrate the methodology and examine the finite sample performance of the variable selection procedures. Melanoma data from a cancer clinical trial is presented to illustrate the proposed methodology. PMID:20336190

Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets.

PubMed

Huang, Min-Wei; Lin, Wei-Chao; Tsai, Chih-Fong

2018-01-01

Many real-world medical datasets contain some proportion of missing (attribute) values. In general, missing value imputation can be performed to solve this problem, which is to provide estimations for the missing values by a reasoning process based on the (complete) observed data. However, if the observed data contain some noisy information or outliers, the estimations of the missing values may not be reliable or may even be quite different from the real values. The aim of this paper is to examine whether a combination of instance selection from the observed data and missing value imputation offers better performance than performing missing value imputation alone. In particular, three instance selection algorithms, DROP3, GA, and IB3, and three imputation algorithms, KNNI, MLP, and SVM, are used in order to find out the best combination. The experimental results show that that performing instance selection can have a positive impact on missing value imputation over the numerical data type of medical datasets, and specific combinations of instance selection and imputation methods can improve the imputation results over the mixed data type of medical datasets. However, instance selection does not have a definitely positive impact on the imputation result for categorical medical datasets.

A Bayesian approach to truncated data sets: An application to Malmquist bias in Supernova Cosmology

NASA Astrophysics Data System (ADS)

March, Marisa Cristina

2018-01-01

A problem commonly encountered in statistical analysis of data is that of truncated data sets. A truncated data set is one in which a number of data points are completely missing from a sample, this is in contrast to a censored sample in which partial information is missing from some data points. In astrophysics this problem is commonly seen in a magnitude limited survey such that the survey is incomplete at fainter magnitudes, that is, certain faint objects are simply not observed. The effect of this `missing data' is manifested as Malmquist bias and can result in biases in parameter inference if it is not accounted for. In Frequentist methodologies the Malmquist bias is often corrected for by analysing many simulations and computing the appropriate correction factors. One problem with this methodology is that the corrections are model dependent. In this poster we derive a Bayesian methodology for accounting for truncated data sets in problems of parameter inference and model selection. We first show the methodology for a simple Gaussian linear model and then go on to show the method for accounting for a truncated data set in the case for cosmological parameter inference with a magnitude limited supernova Ia survey.

Drug Abuse

MedlinePlus

... drugs, including opioids Drug abuse also plays a role in many major social problems, such as drugged driving, violence, stress, and child abuse. Drug abuse can lead to homelessness, crime, and missed work or problems with keeping a job. It harms ...

Math Is Not a Problem...When You Know How to Visualize It.

ERIC Educational Resources Information Center

Nelson, Dennis W.

1983-01-01

Visualization is an effective technique for determining exactly what students must do to solve a mathematics problem. Pictures and charts can be used to help children understand which mathematics facts are present and which are missing--an important step toward problem solving. (PP)

Tensor completion for estimating missing values in visual data.

PubMed

Liu, Ji; Musialski, Przemyslaw; Wonka, Peter; Ye, Jieping

2013-01-01

In this paper, we propose an algorithm to estimate missing values in tensors of visual data. The values can be missing due to problems in the acquisition process or because the user manually identified unwanted outliers. Our algorithm works even with a small amount of samples and it can propagate structure to fill larger missing regions. Our methodology is built on recent studies about matrix completion using the matrix trace norm. The contribution of our paper is to extend the matrix case to the tensor case by proposing the first definition of the trace norm for tensors and then by building a working algorithm. First, we propose a definition for the tensor trace norm that generalizes the established definition of the matrix trace norm. Second, similarly to matrix completion, the tensor completion is formulated as a convex optimization problem. Unfortunately, the straightforward problem extension is significantly harder to solve than the matrix case because of the dependency among multiple constraints. To tackle this problem, we developed three algorithms: simple low rank tensor completion (SiLRTC), fast low rank tensor completion (FaLRTC), and high accuracy low rank tensor completion (HaLRTC). The SiLRTC algorithm is simple to implement and employs a relaxation technique to separate the dependent relationships and uses the block coordinate descent (BCD) method to achieve a globally optimal solution; the FaLRTC algorithm utilizes a smoothing scheme to transform the original nonsmooth problem into a smooth one and can be used to solve a general tensor trace norm minimization problem; the HaLRTC algorithm applies the alternating direction method of multipliers (ADMMs) to our problem. Our experiments show potential applications of our algorithms and the quantitative evaluation indicates that our methods are more accurate and robust than heuristic approaches. The efficiency comparison indicates that FaLTRC and HaLRTC are more efficient than SiLRTC and between FaLRTC an- HaLRTC the former is more efficient to obtain a low accuracy solution and the latter is preferred if a high-accuracy solution is desired.

Inferential Precision in Single-Case Time-Series Data Streams: How Well Does the EM Procedure Perform When Missing Observations Occur in Autocorrelated Data?

PubMed Central

Smith, Justin D.; Borckardt, Jeffrey J.; Nash, Michael R.

2013-01-01

The case-based time-series design is a viable methodology for treatment outcome research. However, the literature has not fully addressed the problem of missing observations with such autocorrelated data streams. Mainly, to what extent do missing observations compromise inference when observations are not independent? Do the available missing data replacement procedures preserve inferential integrity? Does the extent of autocorrelation matter? We use Monte Carlo simulation modeling of a single-subject intervention study to address these questions. We find power sensitivity to be within acceptable limits across four proportions of missing observations (10%, 20%, 30%, and 40%) when missing data are replaced using the Expectation-Maximization Algorithm, more commonly known as the EM Procedure (Dempster, Laird, & Rubin, 1977).This applies to data streams with lag-1 autocorrelation estimates under 0.80. As autocorrelation estimates approach 0.80, the replacement procedure yields an unacceptable power profile. The implications of these findings and directions for future research are discussed. PMID:22697454

Integrative missing value estimation for microarray data.

PubMed

Hu, Jianjun; Li, Haifeng; Waterman, Michael S; Zhou, Xianghong Jasmine

2006-10-12

Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. We present the integrative Missing Value Estimation method (iMISS) by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS) imputation algorithm by up to 15% improvement in our benchmark tests. We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.

Reconciling Dwarf Galaxies with ΛCDM Cosmology: Simulating a Realistic Population of Satellites around a Milky Way-mass Galaxy

NASA Astrophysics Data System (ADS)

Wetzel, Andrew R.; Hopkins, Philip F.; Kim, Ji-hoon; Faucher-Giguère, Claude-André; Kereš, Dušan; Quataert, Eliot

2016-08-01

Low-mass “dwarf” galaxies represent the most significant challenges to the cold dark matter (CDM) model of cosmological structure formation. Because these faint galaxies are (best) observed within the Local Group (LG) of the Milky Way (MW) and Andromeda (M31), understanding their formation in such an environment is critical. We present first results from the Latte Project: the Milky Way on Feedback in Realistic Environments (FIRE). This simulation models the formation of an MW-mass galaxy to z=0 within ΛCDM cosmology, including dark matter, gas, and stars at unprecedented resolution: baryon particle mass of 7070 {M}⊙ with gas kernel/softening that adapts down to 1 {pc} (with a median of 25{--}60 {pc} at z=0). Latte was simulated using the GIZMO code with a mesh-free method for accurate hydrodynamics and the FIRE-2 model for star formation and explicit feedback within a multi-phase interstellar medium. For the first time, Latte self-consistently resolves the spatial scales corresponding to half-light radii of dwarf galaxies that form around an MW-mass host down to {M}{star}≳ {10}5 {M}⊙ . Latte’s population of dwarf galaxies agrees with the LG across a broad range of properties: (1) distributions of stellar masses and stellar velocity dispersions (dynamical masses), including their joint relation; (2) the mass-metallicity relation; and (3) diverse range of star formation histories, including their mass dependence. Thus, Latte produces a realistic population of dwarf galaxies at {M}{star}≳ {10}5 {M}⊙ that does not suffer from the “missing satellites” or “too big to fail” problems of small-scale structure formation. We conclude that baryonic physics can reconcile observed dwarf galaxies with standard ΛCDM cosmology.

Dark Matter Particle Spectroscopy at the LHC: Generalizing M(T2) to Asymmetric Event Topologies

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

Konar, Partha; /Florida U.; Kong, Kyoungchul

2012-04-03

We consider SUSY-like missing energy events at hadron colliders and critically examine the common assumption that the missing energy is the result of two identical missing particles. In order to experimentally test this hypothesis, we generalize the subsystem M{sub T2} variable to the case of asymmetric event topologies, where the two SUSY decay chains terminate in different 'children' particles. In this more general approach, the endpoint M{sub T2(max)} of the M{sub T2} distribution now gives the mass {tilde M}p({tilde M}{sub c}{sup (a)}, {tilde M}{sub c}{sup (b)}) of the parent particles as a function of two input children masses {tilde M}{submore » c}{sup (a)} and {tilde M}{sub c}{sup (b)}. We propose two methods for an independent determination of the individual children masses M{sub c}{sup (a)} and M{sub c}{sup (b)}. First, in the presence of upstream transverse momentum PUTM the corresponding function {tilde M}p({tilde M}{sub c}{sup (a)}, {tilde M}{sub c}{sup (b)}, P{sub UTM}) is independent of P{sub UTM} at precisely the right values of the children masses. Second, the previously discussed MT2 'kink' is now generalized to a 'ridge' on the 2-dimensional surface {tilde M}p({tilde M}{sub c}{sup (a)}, {tilde M}{sub c}{sup (b)}). As we show in several examples, quite often there is a special point along that ridge which marks the true values of the children masses. Our results allow collider experiments to probe a multi-component dark matter sector directly and without any theoretical prejudice.« less

Marginalized zero-inflated Poisson models with missing covariates.

PubMed

Benecha, Habtamu K; Preisser, John S; Divaris, Kimon; Herring, Amy H; Das, Kalyan

2018-05-11

Unlike zero-inflated Poisson regression, marginalized zero-inflated Poisson (MZIP) models for counts with excess zeros provide estimates with direct interpretations for the overall effects of covariates on the marginal mean. In the presence of missing covariates, MZIP and many other count data models are ordinarily fitted using complete case analysis methods due to lack of appropriate statistical methods and software. This article presents an estimation method for MZIP models with missing covariates. The method, which is applicable to other missing data problems, is illustrated and compared with complete case analysis by using simulations and dental data on the caries preventive effects of a school-based fluoride mouthrinse program. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Algebra Word Problem Solving Approaches in a Chemistry Context: Equation Worked Examples versus Text Editing

ERIC Educational Resources Information Center

Ngu, Bing Hiong; Yeung, Alexander Seeshing

2013-01-01

Text editing directs students' attention to the problem structure as they classify whether the texts of word problems contain sufficient, missing or irrelevant information for working out a solution. Equation worked examples emphasize the formation of a coherent problem structure to generate a solution. Its focus is on the construction of three…

Gender Differences in Solution of Algebraic Word Problems Containing Irrelevant Information.

ERIC Educational Resources Information Center

Low, Renae; Over, Ray

1993-01-01

Female tenth graders (n=217) were less likely than male tenth graders (n=219) to identify missing or irrelevant information in algebra problems. Female eleventh graders (n=234) were less likely than male eleventh graders (n=287) to solve problems with irrelevant information. Results indicate sex differences in knowledge of problem structure. (SLD)

Guide to Understanding Moebius Syndrome

MedlinePlus

... due to upper body weakness • Strabismus (crossed eyes) • Dry eyes and irritability • Dental problems • High palate • Cleft palate • Hand and feet problems including club foot and missing or fused fingers (syndactyly) • Hearing problems • Poland’s syndrome (chest wall and upper limb anomalies) Although they ...

Teaching Pronunciation in the Learner-Centered Classroom.

ERIC Educational Resources Information Center

Lin, Hsiang-Pao; And Others

Specific tools and techniques to help students of English as a Second Language overcome pronunciation problems are presented. The selection of problems addressed is based on the frequency and seriousness of errors that many native Chinese-speaking learners produce. Ways to resolve various problems (e.g., missing final consonants, misplaced stress…

Prediction of missing common genes for disease pairs using network based module separation on incomplete human interactome.

PubMed

Akram, Pakeeza; Liao, Li

2017-12-06

Identification of common genes associated with comorbid diseases can be critical in understanding their pathobiological mechanism. This work presents a novel method to predict missing common genes associated with a disease pair. Searching for missing common genes is formulated as an optimization problem to minimize network based module separation from two subgraphs produced by mapping genes associated with disease onto the interactome. Using cross validation on more than 600 disease pairs, our method achieves significantly higher average receiver operating characteristic ROC Score of 0.95 compared to a baseline ROC score 0.60 using randomized data. Missing common genes prediction is aimed to complete gene set associated with comorbid disease for better understanding of biological intervention. It will also be useful for gene targeted therapeutics related to comorbid diseases. This method can be further considered for prediction of missing edges to complete the subgraph associated with disease pair.

Missed injuries during the initial assessment in a cohort of 1124 level-1 trauma patients.

PubMed

Giannakopoulos, G F; Saltzherr, T P; Beenen, L F M; Reitsma, J B; Bloemers, F W; Goslings, J C; Bakker, F C

2012-09-01

Despite the presence of diagnostic guidelines for the initial evaluation in trauma, the reported incidence of missed injuries is considerable. The aim of this study was to assess the missed injuries in a large cohort of trauma patients originating from two European Level-1 trauma centres. We analysed the 1124 patients included in the randomised REACT trial. Missed injuries were defined as injuries not diagnosed or suspected during initial clinical and radiological evaluation in the trauma room. We assessed the frequency, type, consequences and the phase in which the missed injuries were diagnosed and used univariate analysis to identify potential contributing factors. Eight hundred and three patients were male, median age was 38 years and 1079 patients sustained blunt trauma. Overall, 122 injuries were missed in 92 patients (8.2%). Most injuries concerned the extremities. Sixteen injuries had an AIS grade of ≥ 3. Patients with missed injuries had significantly higher injury severity scores (ISSs) (median of 15 versus 5, p<0.001). Factors associated with missed injuries were severe traumatic brain injury (GCS ≤ 8) and multitrauma (ISS ≥ 16). Seventy-two missed injuries remained undetected during tertiary survey (59%). In total, 31 operations were required for 26 initially missed injuries. Despite guidelines to avoid missed injuries, this problem is hard to prevent, especially in the severely injured. The present study showed that the rate of missed injuries was comparable with the literature and their consequences not severe. A high index of suspicion remains warranted, especially in multitrauma patients. Copyright © 2011 Elsevier Ltd. All rights reserved.

Search for new physics in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum in pp collisions at √{s}=13 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.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; Ceard, L.; De Visscher, S.; Delaere, C.; Delcourt, M.; Forthomme, L.; 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.; 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.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Micanovic, S.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Assran, Y.; Elkafrawy, T.; Ellithi Kamel, A.; Mahrous, A.; Calpas, B.; Kadastik, M.; Murumaa, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Peltola, T.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Merlin, J. A.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulte, J. F.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; 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.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asawatangtrakuldee, C.; Asin, I.; 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.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kieseler, J.; Kleinwort, C.; Korol, I.; 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.; Trippkewitz, K. D.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Goebel, K.; 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.; Ott, J.; 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. 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T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; SavoyNavarro, 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.; Jorda, C.; 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.; Cenna, F.; Costa, M.; 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.; Ruspa, M.; Sacchi, R.; Shchelina, K.; 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. 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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.; 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.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; 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. 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T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Sauvan, J. B.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Simon, M.; Sphicas, P.; Steggemann, J.; Stoye, M.; Takahashi, Y.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Wardle, N.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lecomte, P.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; 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.; 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.; Adiguzel, A.; 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.; Sunar Cerci, D.; 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.; 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.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; 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.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; 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. I.; Henderson, C.; Rumerio, P.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Berry, E.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Breto, G.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Florent, A.; 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.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Malberti, M.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; 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.; West, C.; Yoo, J.; Anderson, D.; Apresyan, A.; Bendavid, J.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Azzolini, V.; Carlson, B.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; 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.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Diamond, B.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Santra, A.; Weinberg, M.; 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.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Turner, P.; Varelas, N.; Wang, H.; Wu, Z.; Zakaria, M.; 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.; Anderson, I.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Osherson, M.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Bowen, J.; Bruner, C.; Castle, J.; Kenny, R. P.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; 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.; Abercrombie, D.; Allen, B.; Apyan, A.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. 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.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Knowlton, D.; 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.; 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.; Valls, N.; 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.; Luo, J.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Benedetti, D.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Chou, J. P.; Contreras-Campana, E.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Nash, K.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; 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.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2016-12-01

A search is presented for physics beyond the standard model in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 2.3 fb-1 of proton-proton collisions at √{s}=13 TeV collected with the CMS detector at the LHC in 2015. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. Both search modes use several event categories in order to increase the sensitivity to new physics. These categories are based on the rapidity of the leptons, the multiplicity of jets and b jets, the scalar sum of jet transverse momenta, and missing transverse momentum. The observations in all signal regions are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry. [Figure not available: see fulltext.

Search for new physics in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum in pp collisions at $$ \\sqrt{s}=13 $$ TeV

DOE PAGES

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

2016-12-05

A search is presented for physics beyond the standard model in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 2.3 fb –1 of proton-proton collisions at √s = 13 TeV collected with the CMS detector at the LHC in 2015. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. Both search modes use several event categories in order to increase the sensitivity to new physics. These categories are based on themore » rapidity of the leptons, the multiplicity of jets and b jets, the scalar sum of jet transverse momenta, and missing transverse momentum. Furthermore, the observations in all signal regions are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry.« less

Search for new physics in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum in pp collisions at $$ \\sqrt{s}=13 $$ TeV

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

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

A search is presented for physics beyond the standard model in final states with two opposite-sign, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 2.3 fb –1 of proton-proton collisions at √s = 13 TeV collected with the CMS detector at the LHC in 2015. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. Both search modes use several event categories in order to increase the sensitivity to new physics. These categories are based on themore » rapidity of the leptons, the multiplicity of jets and b jets, the scalar sum of jet transverse momenta, and missing transverse momentum. Furthermore, the observations in all signal regions are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry.« less

Search for supersymmetry in events with photons and low missing transverse energy in pp collisions at s = 7   TeV

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

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

Many models of new physics, including versions of supersymmetry (SUSY), predict production of events with low missing transverse energy, electroweak gauge bosons, and many energetic final-state particles. The stealth SUSY model yields this signature while conserving R-parity by means of a new hidden sector in which SUSY is approximately conserved. The results of a general search for new physics, with no requirement on missing transverse energy, in events with two photons and four or more hadronic jets are reported. The study is based on a sample of proton-proton collisions at sqrt(s) = 7 TeV corresponding to 4.96 inverse femtobarns ofmore » integrated luminosity collected with the CMS detector in 2011. Based on good agreement between the data and the standard model expectation, the data are used to determine model-independent cross-section limits and a limit on the squark mass in the framework of stealth SUSY. With this first study of its kind, squark masses less than 1430 GeV are excluded at the 95% confidence level.« less

Search for dark matter in events with energetic, hadronically decaying top quarks and missing transverse momentum at √{s}=13 TeV

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Marchesini, I.; 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.; Seva, T.; Starling, E.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; Caudron, A.; David, P.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Saggio, A.; Vidal Marono, M.; Wertz, S.; Zobec, J.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Coelho, E.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Sanchez Rosas, L. J.; Santoro, A.; Sznajder, A.; Thiel, M.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Yuan, L.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhang, S.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Carrillo Montoya, C. A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Segura Delgado, M. A.; 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.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkilä, J. K.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Lindén, T.; Luukka, P.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Leloup, C.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Jansová, M.; Le Bihan, A.-C.; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Zhukov, V.; Albert, A.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bermúdez Martínez, A.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Guthoff, M.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Raspereza, A.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Aggleton, R.; Bein, S.; Blobel, V.; Centis Vignali, M.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Hoffmann, M.; Karavdina, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; 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. 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I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hadley, M.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Lee, J.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Regnard, S.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Si, W.; Wang, L.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Gilbert, D.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Macneill, I.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bornheim, A.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Quach, D.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Alyari, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Joshi, B. M.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; Shi, K.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Royon, C.; Sanders, S.; Schmitz, E.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Feng, Y.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Hu, M.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Hiltbrand, J.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Wadud, M. A.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Das, S.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Adair, A.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. M.; Guilbaud, M.; Kilpatrick, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Roberts, J.; Rorie, J.; Shi, W.; Tu, Z.; Zabel, J.; Zhang, A.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Mengke, T.; Muthumuni, S.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Poudyal, N.; Sturdy, J.; Thapa, P.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2018-06-01

A search for dark matter is conducted in events with large missing transverse momentum and a hadronically decaying, Lorentz-boosted top quark. This study is performed using proton-proton collisions at a center-of-mass energy of 13 TeV, in data recorded by the CMS detector in 2016 at the LHC, corresponding to an integrated luminosity of 36 fb-1. New substructure techniques, including the novel use of energy correlation functions, are utilized to identify the decay products of the top quark. With no significant deviations observed from predictions of the standard model, limits are placed on the production of new heavy bosons coupling to dark matter particles. For a scenario with purely vector-like or purely axial-vector-like flavor changing neutral currents, mediator masses between 0.20 and 1.75 TeV are excluded at 95% confidence level, given a sufficiently small dark matter mass. Scalar resonances decaying into a top quark and a dark matter fermion are excluded for masses below 3.4 TeV, assuming a dark matter mass of 100 GeV.

Search for dark matter in events with energetic, hadronically decaying top quarks and missing transverse momentum at $$ \\sqrt{s}=13 $$ TeV

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

Sirunyan, Albert M; et al.

A search for dark matter is conducted in events with large missing transverse momentum and a hadronically decaying, Lorentz-boosted top quark. This study is performed using proton-proton collisions at a center-of-mass energy of 13 TeV, in data recorded by the CMS detector in 2016 at the LHC, corresponding to an integrated luminosity of 36 fbmore » $$^{-1}$$. New substructure techniques, including the novel use of energy correlation functions, are utilized to identify the decay products of the top quark. With no significant deviations observed from predictions of the standard model, limits are placed on the production of new heavy bosons coupling to dark matter particles. For a scenario with purely vector-like or purely axial-vector-like flavor changing neutral currents, mediator masses between 0.20 and 1.75 TeV are excluded at 95% confidence level, given a sufficiently small dark matter mass. Scalar resonances decaying into a top quark and a dark matter fermion are excluded for masses below 3.4 TeV, assuming a dark matter mass of 100 GeV.« less

Re-analysis of Alaskan benchmark glacier mass-balance data using the index method

USGS Publications Warehouse

Van Beusekom, Ashely E.; O'Nell, Shad R.; March, Rod S.; Sass, Louis C.; Cox, Leif H.

2010-01-01

At Gulkana and Wolverine Glaciers, designated the Alaskan benchmark glaciers, we re-analyzed and re-computed the mass balance time series from 1966 to 2009 to accomplish our goal of making more robust time series. Each glacier's data record was analyzed with the same methods. For surface processes, we estimated missing information with an improved degree-day model. Degree-day models predict ablation from the sum of daily mean temperatures and an empirical degree-day factor. We modernized the traditional degree-day model and derived new degree-day factors in an effort to match the balance time series more closely. We estimated missing yearly-site data with a new balance gradient method. These efforts showed that an additional step needed to be taken at Wolverine Glacier to adjust for non-representative index sites. As with the previously calculated mass balances, the re-analyzed balances showed a continuing trend of mass loss. We noted that the time series, and thus our estimate of the cumulative mass loss over the period of record, was very sensitive to the data input, and suggest the need to add data-collection sites and modernize our weather stations.

Search for New Phenomena in tt¯ Events with Large Missing Transverse Momentum in Proton-Proton Collisions at √s=7 TeV with the ATLAS Detector

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

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

2012-01-26

A search for new phenomena in tt¯ events with large missing transverse momentum in proton-proton collisions at a center-of-mass energy of 7 TeV is presented. The measurement is based on 1.04  fb⁻¹ of data collected with the ATLAS detector at the LHC. Contributions to this final state may arise from a number of standard model extensions. The results are interpreted in terms of a model where new top-quark partners are pair produced and each decay to an on-shell top (or antitop) quark and a long-lived undetected neutral particle. The data are found to be consistent with standard model expectations. A limitmore » at 95% confidence level is set excluding a cross section times branching ratio of 1.1 pb for a top-partner mass of 420 GeV and a neutral particle mass less than 10 GeV. In a model of exotic fourth generation quarks, top-partner masses are excluded up to 420 GeV and neutral particle masses up to 140 GeV.« less

Mining Missing Membrane Proteins by High-pH Reverse-Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry.

PubMed

Kitata, Reta Birhanu; Dimayacyac-Esleta, Baby Rorielyn T; Choong, Wai-Kok; Tsai, Chia-Feng; Lin, Tai-Du; Tsou, Chih-Chiang; Weng, Shao-Hsing; Chen, Yi-Ju; Yang, Pan-Chyr; Arco, Susan D; Nesvizhskii, Alexey I; Sung, Ting-Yi; Chen, Yu-Ju

2015-09-04

Despite significant efforts in the past decade toward complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still "missing proteins". Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using nonsmall cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip prefractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue was incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet, and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring using synthetic peptides, we provided additional evidence of eight missing proteins including seven with transmembrane helix domains. This study demonstrates that mining missing proteins focused on cancer membrane subproteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224.

CHARACTERIZATION OF GROUNDWATER SAMPLES FROM SUPERFUND SITES BY AS CHROMATOGRAPHY/MASS SPECTROMETRY AND LIQUID CHROMATOGRAPHY/MASS SPECTROMETRY.

EPA Science Inventory

Groundwater at or near Superfund sites often contains much organic matter,as indicated by total organic carbon (TOC) measurements. Analyses by standard GC and GC/MS methodology often miss the more polar or nonvolatile of these organic compounds. The identification of the highly p...

40 CFR 97.374 - Recordkeeping and reporting.

Code of Federal Regulations, 2010 CFR

2010-07-01

... section, the NOX emission rate and NOX concentration values substituted for missing data under subpart D... report the NOX mass emissions data and heat input data for such unit, in an electronic quarterly report... emissions) for such unit for the entire year and report the NOX mass emissions data and heat input data for...

Modified Einstein's gravity as a possible missing link between sub- and super-Chandrasekhar type Ia supernovae

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

Das, Upasana; Mukhopadhyay, Banibrata, E-mail: upasana@physics.iisc.ernet.in, E-mail: bm@physics.iisc.ernet.in

2015-05-01

We explore the effect of modification to Einstein's gravity in white dwarfs for the first time in the literature, to the best of our knowledge. This leads to significantly sub- and super-Chandrasekhar limiting masses of white dwarfs, determined by a single model parameter. On the other hand, type Ia supernovae (SNeIa), a key to unravel the evolutionary history of the universe, are believed to be triggered in white dwarfs having mass close to the Chandrasekhar limit. However, observations of several peculiar, under- and over-luminous SNeIa argue for exploding masses widely different from this limit. We argue that explosions of themore » modified gravity induced sub- and super-Chandrasekhar limiting mass white dwarfs result in under- and over-luminous SNeIa respectively, thus unifying these two apparently disjoint sub-classes and, hence, serving as a missing link. Our discovery raises two fundamental questions. Is the Chandrasekhar limit unique? Is Einstein's gravity the ultimate theory for understanding astronomical phenomena? Both the answers appear to be no!.« less

A search for squarks and gluinos using the jets and missing energy signature at DO

NASA Astrophysics Data System (ADS)

Lyon, Adam Leonard

1997-11-01

This thesis reports on a search for evidence of production and decay of squarks (q) and gluinos (g) of Minimal Supergravity (mSUGRA) in pp collisions at a center of mass energy of 1.8 TeV using the DO detector at the Fermi National Accelerator Laboratory. Data corresponding to 79.2 ± 4.2 pb-1 were examined for events with large missing transverse energy (E/!/!/!/!/T), three or more jets, high energy leading jet, and the absence of isolated leptons. Since no events were observed in excess of Standard Model background predictions, limits are placed in the mSUGRA M0-M1/2 plane for fixed parameters tan /beta = 2,/ A0 = 0, and /mu < 0. The excluded region includes all mSUGRA models with m/tilde q < 250 GeV/c2. For small M0, gluinos with mass less than 300 GeV/c2 are excluded. If squarks and gluinos have the same mass, that common mass must be greater than 260 GeV/c2.

Strange Particle Reconstruction by the Missing Mass Method

NASA Astrophysics Data System (ADS)

Kisel, Pavel; Kisel, Ivan; Senger, Peter; Vassiliev, Iouri; Zyzak, Maksym

2018-02-01

The main goal of modern heavy-ion experiments is a comprehensive study of the QCD phase diagram, in a region of Quark-Gluon Plasma (QGP) and possible phase transition to QGP phase. Strange particles produced in the collision are sensitive probes of the created media. Reconstruction of Σ particles together with other strange particles completes the picture of strangeness production. Σ+ and Σ- have all decay modes with at least one neutral daughter, which can not be registered by the CBM detector. For their identification the missing mass method is proposed: a) tracks of the mother (Σ-) and the charged daughter (π-) particles are reconstructed in the tracking system; b) the neutral daughter particle (n) is reconstructed from these tracks; c) a mass constraint is set on the reconstructed neutral daughter; d) the mother particle is constructed of the charged and reconstructed neutral daughter particles and the mass spectrum is obtained, by which the particle can be identified. The method can be applied for other strange particles too. In total 18 particle decays with neutral daughter are now included into physics analysis.

Overcoming an obstacle in expanding a UMLS semantic type extent.

PubMed

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Geller, James

2012-02-01

This paper strives to overcome a major problem encountered by a previous expansion methodology for discovering concepts highly likely to be missing a specific semantic type assignment in the UMLS. This methodology is the basis for an algorithm that presents the discovered concepts to a human auditor for review and possible correction. We analyzed the problem of the previous expansion methodology and discovered that it was due to an obstacle constituted by one or more concepts assigned the UMLS Semantic Network semantic type Classification. A new methodology was designed that bypasses such an obstacle without a combinatorial explosion in the number of concepts presented to the human auditor for review. The new expansion methodology with obstacle avoidance was tested with the semantic type Experimental Model of Disease and found over 500 concepts missed by the previous methodology that are in need of this semantic type assignment. Furthermore, other semantic types suffering from the same major problem were discovered, indicating that the methodology is of more general applicability. The algorithmic discovery of concepts that are likely missing a semantic type assignment is possible even in the face of obstacles, without an explosion in the number of processed concepts. Copyright © 2011 Elsevier Inc. All rights reserved.

Overcoming an Obstacle in Expanding a UMLS Semantic Type Extent

PubMed Central

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Geller, James

2011-01-01

This paper strives to overcome a major problem encountered by a previous expansion methodology for discovering concepts highly likely to be missing a specific semantic type assignment in the UMLS. This methodology is the basis for an algorithm that presents the discovered concepts to a human auditor for review and possible correction. We analyzed the problem of the previous expansion methodology and discovered that it was due to an obstacle constituted by one or more concepts assigned the UMLS Semantic Network semantic type Classification. A new methodology was designed that bypasses such an obstacle without a combinatorial explosion in the number of concepts presented to the human auditor for review. The new expansion methodology with obstacle avoidance was tested with the semantic type Experimental Model of Disease and found over 500 concepts missed by the previous methodology that are in need of this semantic type assignment. Furthermore, other semantic types suffering from the same major problem were discovered, indicating that the methodology is of more general applicability. The algorithmic discovery of concepts that are likely missing a semantic type assignment is possible even in the face of obstacles, without an explosion in the number of processed concepts. PMID:21925287

Adaptive detection of missed text areas in OCR outputs: application to the automatic assessment of OCR quality in mass digitization projects

NASA Astrophysics Data System (ADS)

Ben Salah, Ahmed; Ragot, Nicolas; Paquet, Thierry

2013-01-01

The French National Library (BnF*) has launched many mass digitization projects in order to give access to its collection. The indexation of digital documents on Gallica (digital library of the BnF) is done through their textual content obtained thanks to service providers that use Optical Character Recognition softwares (OCR). OCR softwares have become increasingly complex systems composed of several subsystems dedicated to the analysis and the recognition of the elements in a page. However, the reliability of these systems is always an issue at stake. Indeed, in some cases, we can find errors in OCR outputs that occur because of an accumulation of several errors at different levels in the OCR process. One of the frequent errors in OCR outputs is the missed text components. The presence of such errors may lead to severe defects in digital libraries. In this paper, we investigate the detection of missed text components to control the OCR results from the collections of the French National Library. Our verification approach uses local information inside the pages based on Radon transform descriptors and Local Binary Patterns descriptors (LBP) coupled with OCR results to control their consistency. The experimental results show that our method detects 84.15% of the missed textual components, by comparing the OCR ALTO files outputs (produced by the service providers) to the images of the document.

Dark Matter characterization at the LHC in the Effective Field Theory approach

NASA Astrophysics Data System (ADS)

Belyaev, Alexander; Panizzi, Luca; Pukhov, Alexander; Thomas, Marc

2017-04-01

We have studied the complete set of dimension 5 and dimension 6 effective operators involving the interaction of scalar, fermion and vector Dark Matter (DM) with SM quarks and gluons, to explore the possibility to distinguish these operators and characterise the spin of DM at the LHC. We have found that three factors — the effective dimension of the operator, the structure of the SM part of the operator and the parton densities of the SM particles connected to the operator — uniquely define the shape of the (unobservable) invariant mass distribution of the DM pair and, consequently, the shape of the (observable) E T miss distribution related to it. Using χ2 analysis, we found that at the LHC, with a luminosity of 300 fb-1, certain classes of EFT operators can be distinguished from each other. Hence, since DM spin is partly correlated with the factors defining the shape of E T miss , the LHC can potentially shed a light also on DM spin. We have also observed a drastic difference in the efficiencies (up to two orders of magnitude) for large E T miss cuts scenarios with different DM spin, thus indicating that the DM discovery potential strongly depends on it. The study we perform here can be applied more generally than within the EFT paradigm, where the DM mediator is not produced on-the-mass-shell, such as the case of t-channel mediator or mediator with mass below 2 M DM, where the invariant mass of the DM pair is not fixed.

Search for supersymmetry in hadronic final states with missing transverse energy using the variables αT and b-quark multiplicity in pp collisions at [Formula: see text].

PubMed

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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; Sonmez, N; 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; Kreczko, L; Lucas, C; Meng, Z; Metson, S; Newbold, D M; Nirunpong, K; Poll, A; Senkin, S; Smith, V J; Williams, T; Basso, L; Bell, K W; Belyaev, A; Brew, C; Brown, R M; Cockerill, D J A; Coughlan, J A; Harder, K; Harper, S; Jackson, J; Olaiya, E; Petyt, D; Radburn-Smith, B C; Shepherd-Themistocleous, C H; Tomalin, I R; Womersley, W J; Bainbridge, R; Ball, G; Buchmuller, O; Burton, D; Colling, D; Cripps, N; Cutajar, M; Dauncey, P; Davies, G; Della Negra, M; Ferguson, W; Fulcher, J; Gilbert, A; Guneratne Bryer, A; Hall, G; Hatherell, Z; Hays, J; Iles, G; Jarvis, M; Karapostoli, G; Kenzie, M; 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; Whyntie, T; Chadwick, M; 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; Rohlf, J; Sperka, D; John, J St; Sulak, L; Alimena, J; Bhattacharya, S; Christopher, G; Cutts, D; Demiragli, Z; Ferapontov, A; Garabedian, A; Heintz, U; Kukartsev, G; Laird, E; Landsberg, G; Luk, M; Narain, M; Segala, M; Sinthuprasith, T; Speer, T; Breedon, R; Breto, G; Calderon De La Barca Sanchez, M; Caulfield, M; Chauhan, S; Chertok, M; Conway, J; Conway, R; Cox, P T; Dolen, J; Erbacher, R; Gardner, M; Houtz, R; Ko, W; Kopecky, A; Lander, R; Mall, O; Miceli, T; Nelson, R; Pellett, D; Ricci-Tam, F; Rutherford, B; Searle, M; Smith, J; Squires, M; Tripathi, M; Yohay, R; Andreev, V; Cline, D; Cousins, R; Duris, J; Erhan, S; Everaerts, P; Farrell, C; Felcini, M; Hauser, J; Ignatenko, M; Jarvis, C; Rakness, G; Schlein, P; Traczyk, P; Valuev, V; Weber, M; Babb, J; Clare, R; Dinardo, M E; Ellison, J; Gary, J W; Giordano, F; Hanson, G; Liu, H; Long, O R; Luthra, A; Nguyen, H; Paramesvaran, S; Sturdy, J; Sumowidagdo, S; Wilken, R; Wimpenny, S; Andrews, W; Branson, J G; Cerati, G B; Cittolin, S; Evans, D; Holzner, A; Kelley, R; Lebourgeois, M; Letts, J; Macneill, I; Mangano, B; Padhi, S; Palmer, C; Petrucciani, G; 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; Bellan, R; Campagnari, C; D'Alfonso, M; Danielson, T; Flowers, K; Geffert, P; George, C; Golf, F; Incandela, J; Justus, C; Kalavase, P; Kovalskyi, D; Krutelyov, V; Lowette, S; Magaña Villalba, R; Mccoll, N; Pavlunin, V; Ribnik, J; 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; Ma, Y; Mott, A; Newman, H B; Rogan, C; Spiropulu, M; Timciuc, V; Veverka, J; Wilkinson, R; Xie, S; Yang, Y; Zhu, R Y; Azzolini, V; Calamba, A; Carroll, R; Ferguson, T; Iiyama, Y; Jang, D W; Liu, Y F; 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; 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; Gutsche, O; Harris, R M; Hirschauer, J; Hooberman, B; Jindariani, S; Johnson, M; Joshi, U; Klima, B; Kunori, S; Kwan, S; Linacre, J; Lincoln, D; Lipton, R; Lykken, J; Maeshima, K; Marraffino, J M; Martinez Outschoorn, V I; Maruyama, S; Mason, D; McBride, P; Mishra, K; Mrenna, S; Musienko, Y; Newman-Holmes, C; O'Dell, V; Prokofyev, O; Sexton-Kennedy, E; Sharma, S; Spalding, W J; Spiegel, L; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vidal, R; Whitmore, J; Wu, W; Yang, F; Yun, J C; Acosta, D; Avery, P; Bourilkov, D; Chen, M; Cheng, T; Das, S; De Gruttola, M; Di Giovanni, G P; Dobur, D; Drozdetskiy, A; 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; Remington, R; Rinkevicius, A; Skhirtladze, N; Snowball, M; Yelton, J; Zakaria, M; Gaultney, V; Hewamanage, S; Lebolo, L M; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Adams, T; Askew, A; Bochenek, J; Chen, J; Diamond, B; Gleyzer, S V; 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; Callner, J; Cavanaugh, R; Evdokimov, O; Gauthier, L; Gerber, C E; Hofman, D J; Khalatyan, S; Kurt, P; Lacroix, F; O'Brien, C; Silkworth, C; Strom, D; Turner, P; Varelas, N; Akgun, U; Albayrak, E A; Bilki, B; Clarida, W; Dilsiz, K; Duru, F; Griffiths, S; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Newsom, C R; Ogul, H; Onel, Y; Ozok, F; Sen, S; Tan, P; Tiras, E; Wetzel, J; Yetkin, T; Yi, K; Barnett, B A; Blumenfeld, B; Bolognesi, S; Fehling, D; Giurgiu, G; Gritsan, A V; Hu, G; Maksimovic, P; Swartz, M; Whitbeck, A; Baringer, P; Bean, A; Benelli, G; Kenny Iii, R P; Murray, M; Noonan, D; Sanders, S; Stringer, R; Wood, J S; Barfuss, A F; Chakaberia, I; Ivanov, A; Khalil, S; Makouski, M; Maravin, Y; 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; Peterman, A; Skuja, A; Temple, J; Tonjes, M B; Tonwar, S C; Apyan, A; Bauer, G; Busza, W; Butz, E; Cali, I A; Chan, M; Dutta, V; Gomez Ceballos, G; Goncharov, M; Kim, Y; Klute, M; Levin, A; Luckey, P D; Ma, T; Nahn, S; Paus, C; Ralph, D; Roland, C; Roland, G; Stephans, G S F; Stöckli, F; Sumorok, K; Sung, K; Velicanu, D; Wolf, R; Wyslouch, B; Yang, M; Yilmaz, Y; Yoon, A S; Zanetti, M; Zhukova, V; Dahmes, B; De Benedetti, A; Franzoni, G; Gude, A; Haupt, J; Kao, S C; Klapoetke, K; Kubota, Y; Mans, J; Pastika, N; Rusack, R; Sasseville, M; Singovsky, A; Tambe, N; Turkewitz, J; Cremaldi, L M; Kroeger, R; Perera, L; Rahmat, R; Sanders, D A; Summers, D; Avdeeva, E; Bloom, K; Bose, S; Claes, D R; Dominguez, A; Eads, M; Keller, J; Kravchenko, I; Lazo-Flores, J; Malik, S; Snow, G R; Godshalk, A; Iashvili, I; Jain, S; Kharchilava, A; Kumar, A; Rappoccio, S; Wan, Z; Alverson, G; Barberis, E; Baumgartel, D; Chasco, M; Haley, J; 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; Velasco, M; Won, S; Berry, D; Brinkerhoff, A; Chan, K M; Hildreth, M; Jessop, C; Karmgard, D J; 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; Antonelli, L; Bylsma, B; Durkin, L S; Hill, C; Hughes, R; Kotov, K; Ling, T Y; Puigh, D; Rodenburg, M; Smith, G; Vuosalo, C; Williams, G; Winer, B L; Wolfe, H; Berry, E; Elmer, P; Halyo, V; Hebda, P; Hegeman, J; Hunt, A; Jindal, P; Koay, S A; Lopes Pegna, D; 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; Benedetti, D; Bolla, G; Bortoletto, D; De Mattia, M; Everett, A; Hu, Z; Jones, M; Koybasi, O; Kress, M; Leonardo, N; Maroussov, V; Merkel, P; Miller, D H; Neumeister, N; Shipsey, I; Silvers, D; Svyatkovskiy, A; Vidal Marono, M; Yoo, H D; Zablocki, J; Zheng, Y; Guragain, S; Parashar, N; Adair, A; Akgun, B; Ecklund, K M; Geurts, F J M; Li, W; 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; Rose, K; Salur, S; Schnetzer, S; Seitz, C; Somalwar, S; Stone, R; Walker, M; Cerizza, G; Hollingsworth, M; Spanier, S; Yang, Z C; York, A; Eusebi, R; Flanagan, W; Gilmore, J; Kamon, T; Khotilovich, V; Montalvo, R; Osipenkov, I; Pakhotin, Y; Perloff, A; Roe, J; Safonov, A; Sakuma, T; Suarez, I; Tatarinov, A; Toback, D; Akchurin, N; Damgov, J; Dragoiu, C; Dudero, P R; Jeong, C; Kovitanggoon, K; 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; Balazs, M; Boutle, S; Cox, B; Francis, B; Goodell, J; Hirosky, R; Ledovskoy, A; Lin, C; Neu, C; Wood, J; Gollapinni, S; Harr, R; Karchin, P E; Kottachchi Kankanamge Don, C; Lamichhane, P; Sakharov, A; Anderson, M; Belknap, D A; Borrello, L; Carlsmith, D; Cepeda, M; Dasu, S; Friis, E; Grogg, K S; Grothe, M; Hall-Wilton, R; Herndon, M; Hervé, A; Klabbers, P; Klukas, J; Lanaro, A; Lazaridis, C; Loveless, R; Mohapatra, A; Mozer, M U; Ojalvo, I; Pierro, G A; Ross, I; Savin, A; Smith, W H; Swanson, J

An inclusive search for supersymmetric processes that produce final states with jets and missing transverse energy is performed in pp collisions at a centre-of-mass energy of 8 TeV. The data sample corresponds to an integrated luminosity of 11.7 fb -1 collected by the CMS experiment at the LHC. In this search, a dimensionless kinematic variable, α T , is used to discriminate between events with genuine and misreconstructed missing transverse energy. The search is based on an examination of the number of reconstructed jets per event, the scalar sum of transverse energies of these jets, and the number of these jets identified as originating from bottom quarks. No significant excess of events over the standard model expectation is found. Exclusion limits are set in the parameter space of simplified models, with a special emphasis on both compressed-spectrum scenarios and direct or gluino-induced production of third-generation squarks. For the case of gluino-mediated squark production, gluino masses up to 950-1125 GeV are excluded depending on the assumed model. For the direct pair-production of squarks, masses up to 450 GeV are excluded for a single light first- or second-generation squark, increasing to 600 GeV for bottom squarks.

Search for supersymmetry in hadronic final states with missing transverse energy using the variables α T and b-quark multiplicity in pp collisions at $$\\sqrt{s} = 8\\ \\mathrm{TeV}$$

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

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

2013-09-01

An inclusive search for supersymmetric processes that produce final states with jets and missing transverse energy is performed in pp collisions at a centre-of-mass energy of 8 TeV. The data sample corresponds to an integrated luminosity of 11.7 fb -1 collected by the CMS experiment at the LHC. In this search, a dimensionless kinematic variable, α T, is used to discriminate between events with genuine and misreconstructed missing transverse energy. The search is based on an examination of the number of reconstructed jets per event, the scalar sum of transverse energies of these jets, and the number of these jetsmore » identified as originating from bottom quarks. No significant excess of events over the standard model expectation is found. Exclusion limits are set in the parameter space of simplified models, with a special emphasis on both compressed-spectrum scenarios and direct or gluino-induced production of third-generation squarks. For the case of gluino-mediated squark production, gluino masses up to 950–1125 GeV are excluded depending on the assumed model. Finally, for the direct pair-production of squarks, masses up to 450 GeV are excluded for a single light first- or second-generation squark, increasing to 600 GeV for bottom squarks.« less

Fidelity of Problem Solving in Everyday Practice: Typical Training May Miss the Mark

ERIC Educational Resources Information Center

Ruby, Susan F.; Crosby-Cooper, Tricia; Vanderwood, Michael L.

2011-01-01

With national attention on scaling up the implementation of Response to Intervention, problem solving teams remain one of the central components for development, implementation, and monitoring of school-based interventions. Studies have shown that problem solving teams evidence a sound theoretical base and demonstrated efficacy; however, limited…

Preservice Middle and High School Mathematics Teachers' Strategies When Solving Proportion Problems

ERIC Educational Resources Information Center

Arican, Muhammet

2018-01-01

The purpose of this study was to investigate eight preservice middle and high school mathematics teachers' solution strategies when solving single and multiple proportion problems. Real-world missing-value word problems were used in an interview setting to collect information about preservice teachers' (PSTs) reasoning about proportional…

Exoatmospheric intercepts using zero effort miss steering for midcourse guidance

NASA Astrophysics Data System (ADS)

Newman, Brett

The suitability of proportional navigation, or an equivalent zero effort miss formulation, for exatmospheric intercepts during midcourse guidance, followed by a ballistic coast to the endgame, is addressed. The problem is formulated in terms of relative motion in a general, three dimensional framework. The proposed guidance law for the commanded thrust vector orientation consists of the sum of two terms: (1) along the line of sight unit direction and (2) along the zero effort miss component perpendicular to the line of sight and proportional to the miss itself and a guidance gain. If the guidance law is to be suitable for longer range targeting applications with significant ballistic coasting after burnout, determination of the zero effort miss must account for the different gravitational accelerations experienced by each vehicle. The proposed miss determination techniques employ approximations for the true differential gravity effect and thus, are less accurate than a direct numerical propagation of the governing equations, but more accurate than a baseline determination, which assumes equal accelerations for both vehicles. Approximations considered are constant, linear, quadratic, and linearized inverse square models. Theoretical results are applied to a numerical engagement scenario and the resulting performance is evaluated in terms of the miss distances determined from nonlinear simulation.

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

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

A search for supersymmetry is presented based on proton-proton collision events containing identified hadronically decaying top quarks, no leptons, and an imbalance pmore » $$miss\\atop{T}$$ in transverse momentum. The data were collected with the CMS detector at the CERN LHC at a center-of-mass energy of 13 TeV, and correspond to an integrated luminosity of 35.9 fb -1. Search regions are defined in terms of the multiplicity of bottom quark jet and top quark candidates, the p$$miss\\atop{T}$$, the scalar sum of jet transverse momenta, and the m T2 mass variable. No statistically significant excess of events is observed relative to the expectation from the standard model. Lower limits on the masses of supersymmetric particles are determined at 95% confidence level in the context of simplified models with top quark production. For a model with direct top squark pair production followed by the decay of each top squark to a top quark and a neutralino, top squark masses up to 1020 GeV and neutralino masses up to 430 GeV are excluded. For a model with pair production of gluinos followed by the decay of each gluino to a top quark-antiquark pair and a neutralino, gluino masses up to 2040 GeV and neutralino masses up to 1150 GeV are excluded. Finally, these limits extend previous results.« less

Double-observer approach to estimating egg mass abundance of vernal pool breeding amphibians

USGS Publications Warehouse

Grant, E.H.C.; Jung, R.E.; Nichols, J.D.; Hines, J.E.

2005-01-01

Interest in seasonally flooded pools, and the status of associated amphibian populations, has initiated programs in the northeastern United States to document and monitor these habitats. Counting egg masses is an effective way to determine the population size of pool-breeding amphibians, such as wood frogs (Rana sylvatica) and spotted salamanders (Ambystoma maculatum). However, bias is associated with counts if egg masses are missed. Counts unadjusted for the proportion missed (i.e., without adjustment for detection probability) could lead to false assessments of population trends. We used a dependent double-observer method in 2002-2003 to estimate numbers of wood frog and spotted salamander egg masses at seasonal forest pools in 13 National Wildlife Refuges, 1 National Park, 1 National Seashore, and 1 State Park in the northeastern United States. We calculated detection probabilities for egg masses and examined whether detection probabilities varied by species, observers, pools, and in relation to pool characteristics (pool area, pool maximum depth, within-pool vegetation). For the 2 years, model selection indicated that no consistent set of variables explained the variation in data sets from individual Refuges and Parks. Because our results indicated that egg mass detection probabilities vary spatially and temporally, we conclude that it is essential to use estimation procedures, such as double-observer methods with egg mass surveys, to determine population sizes and trends of these species.

Search for new physics in events with two soft oppositely charged leptons and missing transverse momentum 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 physics in events with two low-momentum, oppositely charged leptons (electrons or muons) and missing transverse momentum in proton-proton collisions at a centre-of-mass energy of 13 TeV. The data collected using the CMS detector at the LHC correspond to an integrated luminosity of 35.9 fbmore » $$^{-1}$$. The observed event yields are consistent with the expectations from the standard model. The results are interpreted in terms of pair production of charginos and neutralinos ($$\\widetilde{\\chi}^\\pm_1$$ and $$\\widetilde{\\chi}^0_2$$) with nearly degenerate masses, as expected in natural supersymmetry models with light higgsinos, as well as in terms of the pair production of top squarks ($$\\widetilde{\\mathrm{t}}$$), when the lightest neutralino and the top squark have similar masses. At 95% confidence level, wino-like $$\\widetilde{\\chi}^\\pm_1$$/$$\\widetilde{\\chi}^0_2$$ masses are excluded up to 230 GeV for a mass difference of 20 GeV relative to the lightest neutralino, a region constrained thus far only by the LEP experiments. For $$\\widetilde{\\mathrm{t}}$$ pair production, top squark masses up to 450 GeV are excluded for a mass difference of 40 GeV relative to the lightest neutralino.« less

Study on miss distance based on projectile shock wave sensor

NASA Astrophysics Data System (ADS)

Gu, Guohua; Cheng, Gang; Zhang, Chenjun; Zhou, Lei

2017-05-01

The paper establishes miss distance models based on physical characteristic of shock-wave. The aerodynamic theory shows that the shock-wave of flying super-sonic projectile is generated for the projectile compressing and expending its ambient atmosphere. It advances getting miss distance according to interval of the first sensors, which first catches shock-wave, to solve the problem such as noise filtering on severe background, and signals of amplifier vibration dynamic disposal and electromagnetism compatibility, in order to improves the precision and reliability of gathering wave N signals. For the first time, it can identify the kinds of pills and firing units automatically, measure miss distance and azimuth when pills are firing. Application shows that the tactics and technique index is advanced all of the world.

[School absenteeism in Germany: prevalence of excused and unexcused absenteeism and its correlation with emotional and behavioural problems].

PubMed

Lenzen, Christoph; Fischer, Gloria; Jentzsch, Anika; Kaess, Michael; Parzer, Peter; Carli, Vladimir; Wasserman, Danuta; Resch, Franz; Brunner, Romuald

2013-01-01

Data about the prevalence of school absenteeism and its correlation with emotional and behavioural problems in Germany is scarce, in particular regarding excused absenteeism. This study aims to close the gap by examining a sample of 2,679 pupils attending the different types of secondary school (Hauptschule, Realschule, Gymnasium), who participated in a clinical trial for the prevention of truancy (WE-STAY-Project). Pupils' mean age was 14 years (M = 13.94, SD = 0.85, Range = 11-19) and gender distribution was balanced (49.35% males, 50.65% females). Using a self-report questionnaire, pupils where asked on how many days they had missed school on average per month during the last school year (excused and unexcused). Emotional and behavioural problems were measured by using the "Strengths and Difficulties Questionnaire" (SDQ). 4.1% of the pupils reported to have missed school without a valid excuse on more than four days per month (unexcused absenteeism). 6.1% had missed school having an excuse on more than ten days per month (excused absenteeism). Both, unexcused and excused absenteeism, showed an increase of emotional and behavioural problems dependent on the intensity of absenteeism. In conclusion, these findings show the relevance of school absenteeism in Germany. In the future, more attention should be given to pupils with also excused absenteeism.

Manifold regularized matrix completion for multi-label learning with ADMM.

PubMed

Liu, Bin; Li, Yingming; Xu, Zenglin

2018-05-01

Multi-label learning is a common machine learning problem arising from numerous real-world applications in diverse fields, e.g, natural language processing, bioinformatics, information retrieval and so on. Among various multi-label learning methods, the matrix completion approach has been regarded as a promising approach to transductive multi-label learning. By constructing a joint matrix comprising the feature matrix and the label matrix, the missing labels of test samples are regarded as missing values of the joint matrix. With the low-rank assumption of the constructed joint matrix, the missing labels can be recovered by minimizing its rank. Despite its success, most matrix completion based approaches ignore the smoothness assumption of unlabeled data, i.e., neighboring instances should also share a similar set of labels. Thus they may under exploit the intrinsic structures of data. In addition, the matrix completion problem can be less efficient. To this end, we propose to efficiently solve the multi-label learning problem as an enhanced matrix completion model with manifold regularization, where the graph Laplacian is used to ensure the label smoothness over it. To speed up the convergence of our model, we develop an efficient iterative algorithm, which solves the resulted nuclear norm minimization problem with the alternating direction method of multipliers (ADMM). Experiments on both synthetic and real-world data have shown the promising results of the proposed approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nutritional and oral health status of an elderly population in Nairobi.

PubMed

Ngatia, E M; Gathece, L W; Macigo, F G; Mulli, T K; Mutara, L N; Wagaiyu, E G

2008-08-01

To determine the nutrition and oral health status of elderly persons in Nairobi, Kenya. A cross-sectional study. Households in Dagoretti Division of Nairobi. Two hundred and eighty nine persons (29.8% males and 70.2% females) aged 45 years and above were assessed. The level of malnutrition using the mid upper arm circumference was 18.8% while by body mass index was 11.4%. Of the population assessed, 46.4% had normal nutritional status while 40.9% were overweight, with more females (48.0%) than males (25.9%) being overweight. The study established that many of the elderly persons suffered from dental problems, especially periodontitis with 89.9% having dental plaque, calculus 85.6%, gingival recession 82.5% and bleeding gums 77.4%. The decayed index missing and filled teeth, was 7.173 with 19.7% caries free, 51.9% reported tooth mobility and edentulousness was common. Under-nutrition, obesity and dental problems are issues of concern among the elderly. There is need to develop policies that will look into the nutrition and dental health of the elderly in order to improve their welfare.

A theoretical Deduction from the Hubble law based on a Modified Newtonian Dynamics with field of Yukawa inverse

NASA Astrophysics Data System (ADS)

Falcon, N.

2017-07-01

At cosmic scales the dynamics of the Universe are almost exclusively prescribed by the force of gravity; however the assumption of the law of gravitation, depending on the inverse of the distance, leads to the known problems of the rotation curves of galaxies and missing mass (dark matter). The problem of the coupling of gravity to changes in scale and deviations from the law of the inverse square is an old problem (Laplace, 1805; Seeliger 1898), which has motivated alternatives to Newtonian dynamics compatible with observations. The present paper postulates a modified Newtonian dynamics by adding an inverse Yukawa potential: U(r)≡U0(M)(r-r0)e-α/r is the the potential per unit mass (in N/kg) as a function of the barionic mass that causes the field, r0 is of the order of 50h-1 Mpc and alpha is a coupling constant of the order of 2.5 h-1 Mpc. This potential is zero within the solar system, slightly attractive at interstellar distances, very attractive in galactic range and repulsive at cosmic scales. Its origin is the barionic matter, it allows to include the Milgrow MoND theory to explain the rotation curves, it is compatible with the experiments Eovos type, and allows to deduce the law of Hubble to cosmic scales, in the form H0=100h km/s Mpc≍U0(M)/c, where U0(M)≍ 4pi×6.67 10-11m/s2, is obtained from the Laplace's equation, assuming that the gravitational force is the law of the inverse of the square plus a non-linear term type Yukawa inverse. It is concluded that the modification of the law of gravity with nonlinear terms, allows to model the dynamics of the Universe on a large scale and include non-locality without dark matter. (See Falcon et al. 2014, International Journal of Astronomy and Astrophysics, 4, 551-559).

Inferential precision in single-case time-series data streams: how well does the em procedure perform when missing observations occur in autocorrelated data?

PubMed

Smith, Justin D; Borckardt, Jeffrey J; Nash, Michael R

2012-09-01

The case-based time-series design is a viable methodology for treatment outcome research. However, the literature has not fully addressed the problem of missing observations with such autocorrelated data streams. Mainly, to what extent do missing observations compromise inference when observations are not independent? Do the available missing data replacement procedures preserve inferential integrity? Does the extent of autocorrelation matter? We use Monte Carlo simulation modeling of a single-subject intervention study to address these questions. We find power sensitivity to be within acceptable limits across four proportions of missing observations (10%, 20%, 30%, and 40%) when missing data are replaced using the Expectation-Maximization Algorithm, more commonly known as the EM Procedure (Dempster, Laird, & Rubin, 1977). This applies to data streams with lag-1 autocorrelation estimates under 0.80. As autocorrelation estimates approach 0.80, the replacement procedure yields an unacceptable power profile. The implications of these findings and directions for future research are discussed. Copyright © 2011. Published by Elsevier Ltd.

Search for direct production of charginos, neutralinos and sleptons in final states with two leptons and missing transverse momentum in pp collisions at = 8TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Khalek, S. Abdel; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmad, A.; Ahmadov, F.; Aielli, G.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Gonzalez, B. Alvarez; Alviggi, M. G.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Mayes, J. Backus; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, S.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belloni, A.; Beloborodova, O. L.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Garcia, J. A. Benitez; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertolucci, F.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; De Mendizabal, J. Bilbao; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boutouil, S.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozovic-Jelisavcic, I.; Bracinik, J.; Branchini, P.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brazzale, S. F.; Brelier, B.; Brendlinger, K.; Brennan, A. J.; Brenner, R.; Bressler, S.; Bristow, K.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Brown, G.; Brown, J.; de Renstrom, P. A. Bruckman; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Urbán, S. Cabrera; Caforio, D.; Cakir, O.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Toro, R. Camacho; Camarda, S.; Cameron, D.; Caminada, L. M.; Armadans, R. Caminal; Campana, S.; Campanelli, M.; Campoverde, A.; Canale, V.; Canepa, A.; Cantero, J.; Cantrill, R.; Cao, T.; Garrido, M. D. M. Capeans; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Castaneda-Miranda, E.; Castelli, A.; Gimenez, V. Castillo; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chan, K.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Chau, C. C.; Barajas, C. A. Chavez; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; El Moursli, R. Cherkaoui; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Christidi, I. A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chwastowski, J. C.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Cole, B.; Cole, S.; Colijn, A. P.; Collins-Tooth, C.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Muiño, P. Conde; Coniavitis, E.; Conidi, M. C.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Ortuzar, M. Crispin; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuciuc, C.-M.; Almenar, C. Cuenca; Donszelmann, T. Cuhadar; Cummings, J.; Curatolo, M.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Hoffmann, M. Dano; Dao, V.; Darbo, G.; Darlea, G. L.; Darmora, S.; Dassoulas, J. A.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Cecco, S.; de Graat, J.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Nooij, L.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; De Zorzi, G.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Degenhardt, J.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Deliot, F.; Delitzsch, C. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Ciaccio, A.; Di Ciaccio, L.; Di Domenico, A.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Mattia, A.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; do Vale, M. A. B.; Wemans, A. Do Valle; Doan, T. K. O.; Dobos, D.; Dobson, E.; Doglioni, C.; Doherty, T.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Anjos, A. Dos; Dova, M. T.; Doyle, A. T.; Dris, M.; Dubbert, J.; Dube, S.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudziak, F.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Durglishvili, A.; Dwuznik, M.; Dyndal, M.; Ebke, J.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernis, G.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Perez, S. Fernandez; Ferrag, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; de Lima, D. E. Ferreira; Ferrer, A.; Ferrere, D.; Ferretti, C.; Parodi, A. Ferretto; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, J.; Fisher, W. C.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Castillo, L. R. Flores; Bustos, A. C. Florez; Flowerdew, M. J.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franklin, M.; Franz, S.; Fraternali, M.; French, S. T.; Friedrich, C.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Torregrosa, E. Fullana; Fulsom, B. G.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallo, V.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gandrajula, R. P.; Gao, J.; Gao, Y. S.; Walls, F. M. Garay; Garberson, F.; ıa, C. Garc; Navarro, J. E. García; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gatti, C.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gauzzi, P.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Ge, P.; Gecse, Z.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Gemmell, A.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerbaudo, D.; Gershon, A.; Ghazlane, H.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giangiobbe, V.; Giannetti, P.; Gianotti, F.; Gibbard, B.; Gibson, S. M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giordano, R.; Giorgi, F. M.; Giraud, P. F.; Giugni, D.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkialas, I.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Glonti, G. L.; Goblirsch-Kolb, M.; Goddard, J. R.; Godfrey, J.; Godlewski, J.; Goeringer, C.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Fajardo, L. S. Gomez; Gonçalo, R.; Da Costa, J. Goncalves Pinto Firmino; Gonella, L.; de la Hoz, S. González; Parra, G. Gonzalez; Silva, M. L. Gonzalez; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorfine, G.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Gozpinar, S.; Grabas, H. M. X.; Graber, L.; Grabowska-Bold, I.; Grafström, P.; Grahn, K.-J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Gray, H. M.; Graziani, E.; Grebenyuk, O. G.; Greenwood, Z. D.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grigalashvili, N.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grishkevich, Y. V.; Grivaz, J.-F.; Grohs, J. P.; Grohsjean, A.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Groth-Jensen, J.; Grout, Z. J.; Grybel, K.; Guan, L.; Guescini, F.; Guest, D.; Gueta, O.; Guicheney, C.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Gunther, J.; Guo, J.; Gupta, S.; Gutierrez, P.; Ortiz, N. G. Gutierrez; Gutschow, C.; Guttman, N.; Guyot, C.; Gwenlan, C.; Gwilliam, C. 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2014-05-01

Searches for the electroweak production of charginos, neutralinos and sleptons in final states characterized by the presence of two leptons (electrons and muons) and missing transverse momentum are performed using 20.3 fb-1 of proton-proton collision data at = 8 TeV recorded with the ATLAS experiment at the Large Hadron Collider. No significant excess beyond Standard Model expectations is observed. Limits are set on the masses of the lightest chargino, next-to-lightest neutralino and sleptons for different lightest-neutralino mass hypotheses in simplified models. Results are also interpreted in various scenarios of the phenomenological Minimal Supersymmetric Standard Model. [Figure not available: see fulltext.

Search for supersymmetry with gauge-mediated breaking in diphoton events with missing transverse energy at CDF II.

PubMed

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Yun, J C; Zanetti, A; Zeng, Y; Zhang, X; Zheng, Y; Zucchelli, S

2010-01-08

We present the results of a search for supersymmetry with gauge-mediated breaking and chi(1)(0) --> gammaG in the gammagamma + missing transverse energy final state. In 2.6+/-0.2 fb(-1) of pp collisions at square root(s) = 1.96 TeV recorded by the CDF II detector we observe no candidate events, consistent with a standard model background expectation of 1.4+/-0.4 events. We set limits on the cross section at the 95% C.L. and place the world's best limit of 149 GeV/c2 on the chi(1)(0) mass at tau(chi(1)(0)) < 1 ns. We also exclude regions in the chi(1)(0) mass-lifetime plane for tau(chi(1)(0)) approximately < 2 ns.

The impact of different strategies to handle missing data on both precision and bias in a drug safety study: a multidatabase multinational population-based cohort study

PubMed Central

Martín-Merino, Elisa; Calderón-Larrañaga, Amaia; Hawley, Samuel; Poblador-Plou, Beatriz; Llorente-García, Ana; Petersen, Irene; Prieto-Alhambra, Daniel

2018-01-01

Background Missing data are often an issue in electronic medical records (EMRs) research. However, there are many ways that people deal with missing data in drug safety studies. Aim To compare the risk estimates resulting from different strategies for the handling of missing data in the study of venous thromboembolism (VTE) risk associated with antiosteoporotic medications (AOM). Methods New users of AOM (alendronic acid, other bisphosphonates, strontium ranelate, selective estrogen receptor modulators, teriparatide, or denosumab) aged ≥50 years during 1998–2014 were identified in two Spanish (the Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria [BIFAP] and EpiChron cohort) and one UK (Clinical Practice Research Datalink [CPRD]) EMR. Hazard ratios (HRs) according to AOM (with alendronic acid as reference) were calculated adjusting for VTE risk factors, body mass index (that was missing in 61% of patients included in the three databases), and smoking (that was missing in 23% of patients) in the year of AOM therapy initiation. HRs and standard errors obtained using cross-sectional multiple imputation (MI) (reference method) were compared to complete case (CC) analysis – using only patients with complete data – and longitudinal MI – adding to the cross-sectional MI model the body mass index/smoking values as recorded in the year before and after therapy initiation. Results Overall, 422/95,057 (0.4%), 19/12,688 (0.1%), and 2,051/161,202 (1.3%) VTE cases/participants were seen in BIFAP, EpiChron, and CPRD, respectively. HRs moved from 100.00% underestimation to 40.31% overestimation in CC compared with cross-sectional MI, while longitudinal MI methods provided similar risk estimates compared with cross-sectional MI. Precision for HR improved in cross-sectional MI versus CC by up to 160.28%, while longitudinal MI improved precision (compared with cross-sectional) only minimally (up to 0.80%). Conclusion CC may substantially affect relative risk estimation in EMR-based drug safety studies, since missing data are not often completely at random. Little improvement was seen in these data in terms of power with the inclusion of longitudinal MI compared with cross-sectional MI. The strategy for handling missing data in drug safety studies can have a large impact on both risk estimates and precision.

The impact of different strategies to handle missing data on both precision and bias in a drug safety study: a multidatabase multinational population-based cohort study.

PubMed

Martín-Merino, Elisa; Calderón-Larrañaga, Amaia; Hawley, Samuel; Poblador-Plou, Beatriz; Llorente-García, Ana; Petersen, Irene; Prieto-Alhambra, Daniel

2018-01-01

Missing data are often an issue in electronic medical records (EMRs) research. However, there are many ways that people deal with missing data in drug safety studies. To compare the risk estimates resulting from different strategies for the handling of missing data in the study of venous thromboembolism (VTE) risk associated with antiosteoporotic medications (AOM). New users of AOM (alendronic acid, other bisphosphonates, strontium ranelate, selective estrogen receptor modulators, teriparatide, or denosumab) aged ≥50 years during 1998-2014 were identified in two Spanish (the Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria [BIFAP] and EpiChron cohort) and one UK (Clinical Practice Research Datalink [CPRD]) EMR. Hazard ratios (HRs) according to AOM (with alendronic acid as reference) were calculated adjusting for VTE risk factors, body mass index (that was missing in 61% of patients included in the three databases), and smoking (that was missing in 23% of patients) in the year of AOM therapy initiation. HRs and standard errors obtained using cross-sectional multiple imputation (MI) (reference method) were compared to complete case (CC) analysis - using only patients with complete data - and longitudinal MI - adding to the cross-sectional MI model the body mass index/smoking values as recorded in the year before and after therapy initiation. Overall, 422/95,057 (0.4%), 19/12,688 (0.1%), and 2,051/161,202 (1.3%) VTE cases/participants were seen in BIFAP, EpiChron, and CPRD, respectively. HRs moved from 100.00% underestimation to 40.31% overestimation in CC compared with cross-sectional MI, while longitudinal MI methods provided similar risk estimates compared with cross-sectional MI. Precision for HR improved in cross-sectional MI versus CC by up to 160.28%, while longitudinal MI improved precision (compared with cross-sectional) only minimally (up to 0.80%). CC may substantially affect relative risk estimation in EMR-based drug safety studies, since missing data are not often completely at random. Little improvement was seen in these data in terms of power with the inclusion of longitudinal MI compared with cross-sectional MI. The strategy for handling missing data in drug safety studies can have a large impact on both risk estimates and precision.

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

NASA Astrophysics Data System (ADS)

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P.; Nackenhorst, O.; Nadal, J.; Nagai, K.; Nagai, R.; Nagai, Y.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Namasivayam, H.; Garcia, R. F. Naranjo; Narayan, R.; Villar, D. I. Narrias; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Nef, P. D.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Nickerson, R. B.; Nicolaidou, R.; Nicquevert, B.; Nielsen, J.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Nooney, T.; Norberg, S.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'grady, F.; O'Neil, D. 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D.; Papageorgiou, K.; Paramonov, A.; Hernandez, D. Paredes; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Patel, N. D.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Lopez, S. Pedraza; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Codina, E. Perez; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pina, J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Astigarraga, M. E. Pozo; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Puldon, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Raymond, M.; Read, A. L.; Readioff, N. P.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reisin, H.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Perez, A. Rodriguez; Rodriguez, D. Rodriguez; Roe, S.; Rogan, C. S.; Røhne, O.; Romaniouk, A.; Romano, M.; Saez, S. M. Romano; Adam, E. Romero; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosenthal, O.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. 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A.; Schwegler, Ph.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Saadi, D. Shoaleh; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. 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W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Araya, S. Tapia; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Kate, H. Ten; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Torres, R. E. Ticse; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tylmad, M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ueno, R.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. 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L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Nedden, M. zur; Zurzolo, G.; Zwalinski, L.

2016-10-01

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

Search for squarks and gluinos using final states with jets and missing transverse momentum with the ATLAS detector in s = 7   TeV proton–proton collisions

DOE PAGES

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

2011-06-01

A search for squarks and gluinos in final states containing jets, missing transverse momentum and no electrons or muons is presented. The data were recorded by the ATLAS experiment in √s=7 TeV proton–proton collisions at the Large Hadron Collider. No excess above the Standard Model background expectation was observed in 35 pb -1 of analysed data. Gluino masses below 500 GeV are excluded at the 95% confidence level in simplified models containing only squarks of the first two generations, a gluino octet and a massless neutralino. The exclusion increases to 870 GeV for equal mass squarks and gluinos. In MSUGRA/CMSSMmore » models with tanβ=3, A 0=0 and μ>0, squarks and gluinos of equal mass are excluded below 775 GeV. These are the most stringent limits to date.« less

Association of sleep habits with accidents and near misses in United States transportation operators.

PubMed

Johnson, Kevin D; Patel, Sanjay R; Baur, Dorothee M; Edens, Edward; Sherry, Patrick; Malhotra, Atul; Kales, Stefanos N

2014-05-01

To explore sleep risk factors and their association with adverse events in transportation operators. Self-reported sleep-related behaviors were analyzed in transportation operators (drivers, pilots, and rail operators) aged 26 to 78 years who completed the National Sleep Foundation's 2012 "Planes, Trains, Automobiles, and Sleep" survey. Regression analyses were used to assess the associations of various sleep-related variables with the combined outcome of self-reported accidents and near misses. Age- and body mass-adjusted predictors of accidents/near misses included an accident while commuting (odds ratio [OR] = 4.6; confidence interval [CI], 2.1 to 9.8), driving drowsy (OR = 4.1; CI, 2.5 to 6.7), and Sheehan Disability Scale score greater than 15 (OR = 3.5; CI, 2.2 to 5.5). Sleeping more than 7 hours nightly was protective for accident/near misses (OR = 0.6; CI, 0.4 to 0.9). Recognized risk factors for poor sleep or excessive daytime sleepiness were significantly associated with self-reported near misses and/or accidents in transportation operators.

Magnitude of dental caries, missing and filled teeth in Malawi: National Oral Health Survey.

PubMed

Msyamboza, Kelias Phiri; Phale, Enock; Namalika, Jessie Mlotha; Mwase, Younam; Samonte, Gian Carlo; Kajirime, Doubt; Sumani, Sewedi; Chalila, Pax D; Potani, Rennie; Mwale, George Chithope-; Kathyola, Damson; Mukiwa, Weston

2016-03-09

Oral health problems are significant cause of morbidity particularly in sub-Saharan Africa. In Malawi, routine health management information system data over the years showed that oral health problems were one of the top ten reasons for outpatient attendance. However, to date, no national oral survey has been carried out to determine the prevalence of oral health problems. A national population-based cross-sectional survey was conducted in 2013. A total of 130 enumeration areas (EAs) were randomly selected and from each EA, 40 participants were randomly selected as per WHO STEPS survey protocol. Eligible participants were 12, 15, 35-44 and 65-74 year old. A multi-stage sampling design was used to obtain a national representative sample of these age groups. Oral examination was based on WHO diagnostic criteria (2010). A total of 5400 participants were enrolled in the survey. Of these: 3304 (61.3 %) were females, 2090 (38.7 %) were males; 327 (6.9 %) were from urban and 4386 (93.1 %) from rural areas; 1115 (20.6 %), 993 (17.3 %), 2306 (42.7 %) and 683 (12.6 %) were aged 12, 15, 35-44, 65-74 years respectively. Among 12 year-old, 15 year-old, 35-44 and 65-74 year age groups, prevalence of dental caries was 19.1, 21.9, 49.0 and 49.2 % respectively, overall 37.4 %. Prevalence of missing teeth was 2.7, 5.2, 47.7 and 79.9 %, overall 35.2 %. Prevalence of filled teeth was 0.2 %, 1.3 %, 8.7 %, 12.7 %, overall 6.5 %. Prevalence of bleeding gums was 13.0, 11.8, 30.8 and 36.1 %, overall 23.5 %. Toothache, dental caries and missing teeth were more common in females than males; 46.5 % vs 37.9 %, 40.5 % vs 32.4 %, 37.7 % vs 30.1 % respectively, all p < 0.05. Prevalence of dental caries and missing teeth in urban areas were as high as in the rural areas; 33.3 % vs 37.4 % and 30.9 % vs 33.7 % respectively, all p > 0.05. The mean number of decayed, missing and filled teeth (DMFT) in 12, 15, 35-44, 65-74 year old was 0.67, 0.71, 3.11 and 6.87 respectively. Self- reported brushing of teeth was poor with only 35.2 % of people brushed their teeth twice a day and tobacco smoking was high, particularly among adult males where one in five (22.9 %) was a smoker. This study demonstrated that oral health problems are major public health problems in Malawi. One in five (21 %) adolescents aged 12-15 years and half (49 %) of adults aged 35 years or more had dental caries, half (48 %) and 80 % of the population aged 35-44, 65-74 years had missing teeth respectively. Toothache, dental caries and missing teeth were more prevalent in females than males and prevalence in urban was as high as in rural areas. Oral hygiene was poor with less than 40 % of the population brush their teeth twice a day and tobacco smoking was high, particularly in men where prevalence was 23 %. These findings could be used to develop evidence-informed national policy, action and resource mobilization plan and community based interventions to reduce the prevalence of oral health problems in Malawi.

Multiple imputation of missing fMRI data in whole brain analysis

PubMed Central

Vaden, Kenneth I.; Gebregziabher, Mulugeta; Kuchinsky, Stefanie E.; Eckert, Mark A.

2012-01-01

Whole brain fMRI analyses rarely include the entire brain because of missing data that result from data acquisition limits and susceptibility artifact, in particular. This missing data problem is typically addressed by omitting voxels from analysis, which may exclude brain regions that are of theoretical interest and increase the potential for Type II error at cortical boundaries or Type I error when spatial thresholds are used to establish significance. Imputation could significantly expand statistical map coverage, increase power, and enhance interpretations of fMRI results. We examined multiple imputation for group level analyses of missing fMRI data using methods that leverage the spatial information in fMRI datasets for both real and simulated data. Available case analysis, neighbor replacement, and regression based imputation approaches were compared in a general linear model framework to determine the extent to which these methods quantitatively (effect size) and qualitatively (spatial coverage) increased the sensitivity of group analyses. In both real and simulated data analysis, multiple imputation provided 1) variance that was most similar to estimates for voxels with no missing data, 2) fewer false positive errors in comparison to mean replacement, and 3) fewer false negative errors in comparison to available case analysis. Compared to the standard analysis approach of omitting voxels with missing data, imputation methods increased brain coverage in this study by 35% (from 33,323 to 45,071 voxels). In addition, multiple imputation increased the size of significant clusters by 58% and number of significant clusters across statistical thresholds, compared to the standard voxel omission approach. While neighbor replacement produced similar results, we recommend multiple imputation because it uses an informed sampling distribution to deal with missing data across subjects that can include neighbor values and other predictors. Multiple imputation is anticipated to be particularly useful for 1) large fMRI data sets with inconsistent missing voxels across subjects and 2) addressing the problem of increased artifact at ultra-high field, which significantly limit the extent of whole brain coverage and interpretations of results. PMID:22500925

Low Mass AGN: Combining IRAC With Near-IR Grism Spectroscopy

NASA Astrophysics Data System (ADS)

Colbert, James; Teplitz, Harry; Malkan, Matt; Scarlata, Claudia; Bagley, Micaela; Baronchelli, Ivano; Hayden-Pawson, Connor; Rafelski, Marc

2017-10-01

Low mass AGN are critical to understanding the evolution of AGNs and stars in galaxies, marking the time periods of highest accretion efficiency and greatest likely deviations from the black hole mass - sigma correlation. Using the WFC3 Infrared Spectroscopic Parallels (WISP), we have just recently identified 68 candidate z > 1 AGN in 27 fields from their near-infrared emission line ratios. The WISP survey selects emission line galaxies without any pre-selection bias and is exquisitely sensitive to low mass (down to 10^7 solar masses), high-equivalent width galaxies that are missed by most other surveys. We propose to take IRAC 4.5 micron imaging of these AGN candidate fields in order to confirm 68 low mass AGN candidates, identify additional low mass IR-AGN missed by emission line selection, and produce the SED fits that can separate hot dust from star light, allowing comparison of stellar mass to AGN bolometric luminosity. The upcoming Euclid and WFIRST missions will generate hundreds of thousands of near-infrared spectra over a similar redshift range to WISP. For most of these objects, near-infrared emission line ratios will be the only viable AGN diagnostic. The Spitzer IRAC color AGN selection is one of the most robust AGN identifiers available. We wish to test these near-infrared emission line selection methods against the IRAC selection in order to evaluate the reliability of the AGN these future missions are likely to produce.

Automating Web Collection and Validation of GPS data for Longitudinal Urban Travel Studies

DOT National Transportation Integrated Search

2012-08-01

Traditional paper and phone travel surveys are expensive, time consuming, and have problems of missing trips, illogical trip sequences, and : imprecise travel time. GPS-based travel surveys can avoid many of these problems and are becoming increasing...

Clustering and variable selection in the presence of mixed variable types and missing data.

PubMed

Storlie, C B; Myers, S M; Katusic, S K; Weaver, A L; Voigt, R G; Croarkin, P E; Stoeckel, R E; Port, J D

2018-05-17

We consider the problem of model-based clustering in the presence of many correlated, mixed continuous, and discrete variables, some of which may have missing values. Discrete variables are treated with a latent continuous variable approach, and the Dirichlet process is used to construct a mixture model with an unknown number of components. Variable selection is also performed to identify the variables that are most influential for determining cluster membership. The work is motivated by the need to cluster patients thought to potentially have autism spectrum disorder on the basis of many cognitive and/or behavioral test scores. There are a modest number of patients (486) in the data set along with many (55) test score variables (many of which are discrete valued and/or missing). The goal of the work is to (1) cluster these patients into similar groups to help identify those with similar clinical presentation and (2) identify a sparse subset of tests that inform the clusters in order to eliminate unnecessary testing. The proposed approach compares very favorably with other methods via simulation of problems of this type. The results of the autism spectrum disorder analysis suggested 3 clusters to be most likely, while only 4 test scores had high (>0.5) posterior probability of being informative. This will result in much more efficient and informative testing. The need to cluster observations on the basis of many correlated, continuous/discrete variables with missing values is a common problem in the health sciences as well as in many other disciplines. Copyright © 2018 John Wiley & Sons, Ltd.

A regressive methodology for estimating missing data in rainfall daily time series

NASA Astrophysics Data System (ADS)

Barca, E.; Passarella, G.

2009-04-01

The "presence" of gaps in environmental data time series represents a very common, but extremely critical problem, since it can produce biased results (Rubin, 1976). Missing data plagues almost all surveys. The problem is how to deal with missing data once it has been deemed impossible to recover the actual missing values. Apart from the amount of missing data, another issue which plays an important role in the choice of any recovery approach is the evaluation of "missingness" mechanisms. When data missing is conditioned by some other variable observed in the data set (Schafer, 1997) the mechanism is called MAR (Missing at Random). Otherwise, when the missingness mechanism depends on the actual value of the missing data, it is called NCAR (Not Missing at Random). This last is the most difficult condition to model. In the last decade interest arose in the estimation of missing data by using regression (single imputation). More recently multiple imputation has become also available, which returns a distribution of estimated values (Scheffer, 2002). In this paper an automatic methodology for estimating missing data is presented. In practice, given a gauging station affected by missing data (target station), the methodology checks the randomness of the missing data and classifies the "similarity" between the target station and the other gauging stations spread over the study area. Among different methods useful for defining the similarity degree, whose effectiveness strongly depends on the data distribution, the Spearman correlation coefficient was chosen. Once defined the similarity matrix, a suitable, nonparametric, univariate, and regressive method was applied in order to estimate missing data in the target station: the Theil method (Theil, 1950). Even though the methodology revealed to be rather reliable an improvement of the missing data estimation can be achieved by a generalization. A first possible improvement consists in extending the univariate technique to the multivariate approach. Another approach follows the paradigm of the "multiple imputation" (Rubin, 1987; Rubin, 1988), which consists in using a set of "similar stations" instead than the most similar. This way, a sort of estimation range can be determined allowing the introduction of uncertainty. Finally, time series can be grouped on the basis of monthly rainfall rates defining classes of wetness (i.e.: dry, moderately rainy and rainy), in order to achieve the estimation using homogeneous data subsets. We expect that integrating the methodology with these enhancements will certainly improve its reliability. The methodology was applied to the daily rainfall time series data registered in the Candelaro River Basin (Apulia - South Italy) from 1970 to 2001. REFERENCES D.B., Rubin, 1976. Inference and Missing Data. Biometrika 63 581-592 D.B. Rubin, 1987. Multiple Imputation for Nonresponce in Surveys, New York: John Wiley & Sons, Inc. D.B. Rubin, 1988. An overview of multiple imputation. In Survey Research Section, pp. 79-84, American Statistical Association, 1988. J.L., Schafer, 1997. Analysis of Incomplete Multivariate Data, Chapman & Hall. J., Scheffer, 2002. Dealing with Missing Data. Res. Lett. Inf. Math. Sci. 3, 153-160. Available online at http://www.massey.ac.nz/~wwiims/research/letters/ H. Theil, 1950. A rank-invariant method of linear and polynomial regression analysis. Indicationes Mathematicae, 12, pp.85-91.

Search for Dark Matter in events with a hight- pT photon and high missing transverse momentum in ATLAS

NASA Astrophysics Data System (ADS)

Ratti, M. G.

2016-01-01

We present the results of a search for new particles in events with a high-pT photon and high missing transverse momentum with the ATLAS experiment at the LHC. The analysis is performed on the data collected by ATLAS at a centre of mass energy of 8TeV and corresponding to a total integrated luminosity of 20.3 fb-1 . No excess has been found with respect to the Standard Model expectation. A model-independent upper limit on the fiducial cross section for the production of events with a photon and large missing transverse momentum is set. Exclusion limits on the direct pair production of dark matter candidates are presented.

Performance of algorithms that reconstruct missing transverse momentum in $$\\sqrt{s}=8$$ TeV proton–proton collisions in the ATLAS detector

DOE PAGES

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

2017-04-13

The reconstruction and calibration algorithms used to calculate missing transverse momentum (E miss T) with the ATLAS detector exploit energy deposits in the calorimeter and tracks reconstructed in the inner detector as well as the muon spectrometer. Various strategies are used to suppress effects arising from additional proton–proton interactions, called pileup, concurrent with the hard-scatter processes. Tracking information is used to distinguish contributions from the pileup interactions using their vertex separation along the beam axis. The performance of the E miss T reconstruction algorithms, especially with respect to the amount of pileup, is evaluated using data collected in proton–proton collisionsmore » at a centre-of-mass energy of 8 TeV during 2012, and results are shown for a data sample corresponding to an integrated luminosity of 20.3fb –1. The simulation and modelling of E miss T in events containing a Z boson decaying to two charged leptons (electrons or muons) or a W boson decaying to a charged lepton and a neutrino are compared to data. The acceptance for different event topologies, with and without high transverse momentum neutrinos, is shown for a range of threshold criteria for E miss T, and estimates of the systematic uncertainties in the E miss T measurements are presented.« less

Mining Missing Membrane Proteins by High-pH Reverse Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry

PubMed Central

Kitata, Reta Birhanu; Dimayacyac-Esleta, Baby Rorielyn T.; Choong, Wai-Kok; Tsai, Chia-Feng; Lin, Tai-Du; Tsou, Chih-Chiang; Weng, Shao-Hsing; Chen, Yi-Ju; Yang, Pan-Chyr; Arco, Susan D.; Nesvizhskii, Alexey I.; Sung, Ting-Yi; Chen, Yu-Ju

2016-01-01

Despite significant efforts in the past decade towards complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still “missing proteins”. Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using non-small cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip pre-fractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue were incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring (MRM) using synthetic peptides, we provided additional evidences for 8 missing proteins including 7 with transmembrane helix domains (TMH). This study demonstrates that mining missing proteins focused on cancer membrane sub-proteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224. PMID:26202522

Automatic Annotation Method on Learners' Opinions in Case Method Discussion

ERIC Educational Resources Information Center

Samejima, Masaki; Hisakane, Daichi; Komoda, Norihisa

2015-01-01

Purpose: The purpose of this paper is to annotate an attribute of a problem, a solution or no annotation on learners' opinions automatically for supporting the learners' discussion without a facilitator. The case method aims at discussing problems and solutions in a target case. However, the learners miss discussing some of problems and solutions.…

Students' Performance on Missing-Value Word Problems: A Cross-National Developmental Study

ERIC Educational Resources Information Center

Jiang, Ronghuan; Li, Xiaodong; Fernández, Ceneida; Fu, Xinchen

2017-01-01

This study investigates Spanish and Chinese students' performance on both addition problems and proportion problems considering a cross-national perspective. The effect of number structure and nature of quantities was also considered. Nine hundred twenty-five 4th to 8th graders (453 Chinese, 472 Spanish) took a test which is composed of addition…

Event-Based Variance-Constrained ${\\mathcal {H}}_{\\infty }$ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

PubMed

Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

2018-03-01

This paper is concerned with the distributed filtering problem for a class of discrete time-varying stochastic parameter systems with error variance constraints over a sensor network where the sensor outputs are subject to successive missing measurements. The phenomenon of the successive missing measurements for each sensor is modeled via a sequence of mutually independent random variables obeying the Bernoulli binary distribution law. To reduce the frequency of unnecessary data transmission and alleviate the communication burden, an event-triggered mechanism is introduced for the sensor node such that only some vitally important data is transmitted to its neighboring sensors when specific events occur. The objective of the problem addressed is to design a time-varying filter such that both the requirements and the variance constraints are guaranteed over a given finite-horizon against the random parameter matrices, successive missing measurements, and stochastic noises. By recurring to stochastic analysis techniques, sufficient conditions are established to ensure the existence of the time-varying filters whose gain matrices are then explicitly characterized in term of the solutions to a series of recursive matrix inequalities. A numerical simulation example is provided to illustrate the effectiveness of the developed event-triggered distributed filter design strategy.

Missing-value estimation using linear and non-linear regression with Bayesian gene selection.

PubMed

Zhou, Xiaobo; Wang, Xiaodong; Dougherty, Edward R

2003-11-22

Data from microarray experiments are usually in the form of large matrices of expression levels of genes under different experimental conditions. Owing to various reasons, there are frequently missing values. Estimating these missing values is important because they affect downstream analysis, such as clustering, classification and network design. Several methods of missing-value estimation are in use. The problem has two parts: (1) selection of genes for estimation and (2) design of an estimation rule. We propose Bayesian variable selection to obtain genes to be used for estimation, and employ both linear and nonlinear regression for the estimation rule itself. Fast implementation issues for these methods are discussed, including the use of QR decomposition for parameter estimation. The proposed methods are tested on data sets arising from hereditary breast cancer and small round blue-cell tumors. The results compare very favorably with currently used methods based on the normalized root-mean-square error. The appendix is available from http://gspsnap.tamu.edu/gspweb/zxb/missing_zxb/ (user: gspweb; passwd: gsplab).

Improving record linkage performance in the presence of missing linkage data.

PubMed

Ong, Toan C; Mannino, Michael V; Schilling, Lisa M; Kahn, Michael G

2014-12-01

Existing record linkage methods do not handle missing linking field values in an efficient and effective manner. The objective of this study is to investigate three novel methods for improving the accuracy and efficiency of record linkage when record linkage fields have missing values. By extending the Fellegi-Sunter scoring implementations available in the open-source Fine-grained Record Linkage (FRIL) software system we developed three novel methods to solve the missing data problem in record linkage, which we refer to as: Weight Redistribution, Distance Imputation, and Linkage Expansion. Weight Redistribution removes fields with missing data from the set of quasi-identifiers and redistributes the weight from the missing attribute based on relative proportions across the remaining available linkage fields. Distance Imputation imputes the distance between the missing data fields rather than imputing the missing data value. Linkage Expansion adds previously considered non-linkage fields to the linkage field set to compensate for the missing information in a linkage field. We tested the linkage methods using simulated data sets with varying field value corruption rates. The methods developed had sensitivity ranging from .895 to .992 and positive predictive values (PPV) ranging from .865 to 1 in data sets with low corruption rates. Increased corruption rates lead to decreased sensitivity for all methods. These new record linkage algorithms show promise in terms of accuracy and efficiency and may be valuable for combining large data sets at the patient level to support biomedical and clinical research. Copyright © 2014 Elsevier Inc. All rights reserved.

Reporting and dealing with missing quality of life data in RCTs: has the picture changed in the last decade?

PubMed

Fielding, S; Ogbuagu, A; Sivasubramaniam, S; MacLennan, G; Ramsay, C R

2016-12-01

Missing data are a major problem in the analysis of data from randomised trials affecting power and potentially producing biased treatment effects. Specifically focussing on quality of life outcomes, we aimed to report the amount of missing data, whether imputation was used and what methods and was the missing mechanism discussed from four leading medical journals and compare the picture to our previous review nearly a decade ago. A random selection (50 %) of all RCTS published during 2013-2014 in BMJ, JAMA, Lancet and NEJM was obtained. RCTs reported in research letters, cluster RCTs, non-randomised designs, review articles and meta-analysis were excluded. We included 87 RCTs in the review of which 35 % the amount of missing primary QoL data was unclear, 31 (36 %) used imputation. Only 23 % discussed the missing data mechanism. Nearly half used complete case analysis. Reporting was more unclear for secondary QoL outcomes. Compared to the previous review, multiple imputation was used more prominently but mainly in sensitivity analysis. Inadequate reporting and handling of missing QoL data in RCTs are still an issue. There is a large gap between statistical methods research relating to missing data and the use of the methods in applications. A sensitivity analysis should be undertaken to explore the sensitivity of the main results to different missing data assumptions. Medical journals can help to improve the situation by requiring higher standards of reporting and analytical methods to deal with missing data, and by issuing guidance to authors on expected standard.

[Near miss outcomes in gambling games].

PubMed

Pecsenye, Zsuzsa; Kurucz, Gyozo

2017-01-01

Games of chance operate with an intermittent reinforcement schedule in which the number of games takes the player to win differ in each turn thus they can not predict when the next positive reinforcement arrives. The near miss outcome (close to winning but actually a losing outcome) can be interpreted as a secondary (built in) reinforcement within variable ratio reinforcement schedule that presumably contribute to the development and maintanance of gambling addiction. The aim of this publication would be to introduce near miss outcomes and to summarize and critically analyze literature connected to this issue.We searched internet datebases using word "near miss" and analyse articles focusing on gambling games. Based on numerous authors' results a near miss rate set at around 30% increases the desire to continue playing among gamblers and players who have no former gambling experience as well. Some studies have demonstrated that this effect might be related to the extent the player has the situation under control during the gambling session. The hypothetical inhibiting effect of a 45% near miss ratio has not yet been proven. Neurobiological researches show middle-cerebral activity during near miss outcomes furthermore similar physiological patterns have been discovered following a near miss and winning outcomes. Regarding the connection between intrapsychic variables (cognitive and personality factors) and near misses there are very few studies. The fact that different authors interpret near miss outcomes differently even when studying the same game leads to problems in interpreting their results. It follows from the foregoing empirical results that near miss outcomes contribute to the development and maintanance of pathological gambling but we have little information on the factors implementing this effect.

Search for high-mass resonances in final states with a lepton and missing transverse momentum at $$\\sqrt{s}=$$ 13 TeV

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

Sirunyan, Albert M; et al.

A search for new high-mass resonances in proton-proton collisions having final states with an electron or muon and missing transverse momentum is presented. The analysis uses proton-proton collision data collected in 2016 with the CMS detector at the LHC at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fbmore » $$^{-1}$$. The transverse mass distribution of the charged lepton-neutrino system is used as the discriminating variable. No significant deviation from the standard model prediction is found. The best limit, from the combination of electron and muon channels, is 5.2 TeV at 95% confidence level for the mass of a W$'$ boson with the same couplings as those of the standard model W boson. Exclusion limits of 2.9 TeV are set on the inverse radius of the extra dimension in the framework of split universal extra dimensions. In addition, model-independent limits are set on the production cross section and coupling strength of W$'$ bosons decaying into this final state. An interpretation is also made in the context of an R parity violating supersymmetric model with a slepton as a mediator and flavor violating decay.« less

Search for new phenomena in events containing a same-flavour opposite-sign dilepton pair, jets, and large missing transverse momentum in [Formula: see text] [Formula: see text][Formula: see text] collisions with the ATLAS detector.

PubMed

Aaboud, M; Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Abeloos, B; AbouZeid, O S; Abraham, N L; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adachi, S; Adamczyk, L; Adams, D L; Adelman, J; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Agheorghiesei, C; Aguilar-Saavedra, J A; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimov, A V; Alberghi, G L; Albert, J; Verzini, M J Alconada; 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; Gonzalez, B Alvarez; Piqueras, D Álvarez; Alviggi, M G; Amadio, B T; Coutinho, Y Amaral; Amelung, C; Amidei, D; Santos, S P Amor Dos; 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; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antel, C; Antonelli, M; Antonov, A; Antrim, D J; Anulli, F; Aoki, M; Bella, L Aperio; Arabidze, G; Arai, Y; Araque, J P; Ferraz, V Araujo; Arce, A T H; Arduh, F A; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Armitage, L J; Arnaez, O; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Artz, S; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Augsten, K; Avolio, G; Axen, B; Ayoub, M K; Azuelos, G; Baak, M A; Baas, A E; Baca, M J; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Bagiacchi, P; Bagnaia, P; Bai, Y; Baines, J T; Bajic, M; Baker, O K; Baldin, E M; Balek, P; Balestri, T; Balli, F; Balunas, W K; Banas, E; Banerjee, Sw; Bannoura, A A E; Barak, L; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barisits, M-S; Barklow, T; Barlow, N; Barnes, S L; Barnett, B M; Barnett, R M; Barnovska-Blenessy, Z; Baroncelli, A; Barone, G; Barr, A J; Navarro, L Barranco; Barreiro, F; da Costa, J Barreiro Guimarães; Bartoldus, R; Barton, A E; Bartos, P; Basalaev, A; Bassalat, A; Bates, R L; Batista, S J; Batley, J R; Battaglia, M; Bauce, M; Bauer, F; Bawa, H S; Beacham, J B; Beattie, M D; Beau, T; Beauchemin, P H; Bechtle, P; Beck, H P; Becker, K; Becker, M; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bednyakov, V A; Bedognetti, M; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Bell, A S; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Belyaev, N L; Benary, O; Benchekroun, D; Bender, M; Bendtz, K; Benekos, N; Benhammou, Y; Noccioli, E Benhar; Benitez, J; Benjamin, D P; Bensinger, J R; Bentvelsen, S; Beresford, L; Beretta, M; Berge, D; Kuutmann, E Bergeaas; Berger, N; Beringer, J; Berlendis, S; Bernard, N R; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertram, I A; Bertsche, C; Bertsche, D; Besjes, G J; Bylund, O Bessidskaia; Bessner, M; Besson, N; Betancourt, C; 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Zobernig, G; Zoccoli, A; Nedden, M Zur; Zwalinski, L

2017-01-01

Two searches for new phenomena in final states containing a same-flavour opposite-sign lepton (electron or muon) pair, jets, and large missing transverse momentum are presented. These searches make use of proton-proton collision data, collected during 2015 and 2016 at a centre-of-mass energy [Formula: see text] [Formula: see text] by the ATLAS detector at the large hadron collider, which correspond to an integrated luminosity of [Formula: see text]. Both searches target the pair production of supersymmetric particles, squarks or gluinos, which decay to final states containing a same-flavour opposite-sign lepton pair via one of two mechanisms: a leptonically decaying Z boson in the final state, leading to a peak in the dilepton invariant-mass distribution around the Z boson mass; and decays of neutralinos (e.g. [Formula: see text]), yielding a kinematic endpoint in the dilepton invariant-mass spectrum. The data are found to be consistent with the Standard Model expectation. Results are interpreted in simplified models of gluino-pair (squark-pair) production, and provide sensitivity to gluinos (squarks) with masses as large as 1.70 [Formula: see text] (980 [Formula: see text]).

Search for new phenomena in events containing a same-flavour opposite-sign dilepton pair, jets, and large missing transverse momentum in \\varvec{√{s}=13} {TeV} \\varvec{pp} collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

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D.; Papageorgiou, K.; Paramonov, A.; Hernandez, D. Paredes; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Lopez, S. Pedraza; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Codina, E. Perez; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Astigarraga, M. E. Pozo; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; 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.; Roda, C.; Rodina, Y.; Perez, A. Rodriguez; Rodriguez, D. Rodriguez; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Saez, S. M. Romano; Adam, E. Romero; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Tehrani, F. Safai; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Loyola, J. E. Salazar; Salek, D.; De Bruin, P. H. Sales; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sánchez, J.; Martinez, V. Sanchez; Pineda, A. Sanchez; Sandaker, H.; Sandbach, R. L.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Castillo, I. Santoyo; Sapp, K.; 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.; Scarfone, V.; 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.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Saadi, D. Shoaleh; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Haddad, E. Sideras; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, 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.; Smestad, L.; Smiesko, J.; 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.; Soh, D. A.; Sokhrannyi, G.; Sanchez, C. A. Solans; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Denis, R. D. St.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; 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.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Araya, S. Tapia; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Kate, H. Ten; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Torres, R. E. Ticse; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, 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.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Santurio, E. Valdes; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Ferrer, J. A. Valls; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, Q.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yeletskikh, I.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J.; Yuan, L.; 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.; Zeman, M.; 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, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; 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.; Nedden, M. zur; Zwalinski, L.

2017-03-01

Two searches for new phenomena in final states containing a same-flavour opposite-sign lepton (electron or muon) pair, jets, and large missing transverse momentum are presented. These searches make use of proton-proton collision data, collected during 2015 and 2016 at a centre-of-mass energy √{s}=13 {TeV} by the ATLAS detector at the large hadron collider, which correspond to an integrated luminosity of 14.7 fb^{-1}. Both searches target the pair production of supersymmetric particles, squarks or gluinos, which decay to final states containing a same-flavour opposite-sign lepton pair via one of two mechanisms: a leptonically decaying Z boson in the final state, leading to a peak in the dilepton invariant-mass distribution around the Z boson mass; and decays of neutralinos (e.g. \\tilde{χ }_2^0 → ℓ ^+ℓ ^- \\tilde{χ }_1^0), yielding a kinematic endpoint in the dilepton invariant-mass spectrum. The data are found to be consistent with the Standard Model expectation. Results are interpreted in simplified models of gluino-pair (squark-pair) production, and provide sensitivity to gluinos (squarks) with masses as large as 1.70 {TeV} (980 {GeV}).

Galaxy And Mass Assembly (GAMA): bivariate functions of Hα star-forming galaxies

NASA Astrophysics Data System (ADS)

Gunawardhana, M. L. P.; Hopkins, A. M.; Taylor, E. N.; Bland-Hawthorn, J.; Norberg, P.; Baldry, I. K.; Loveday, J.; Owers, M. S.; Wilkins, S. M.; Colless, M.; Brown, M. J. I.; Driver, S. P.; Alpaslan, M.; Brough, S.; Cluver, M.; Croom, S.; Kelvin, L.; Lara-López, M. A.; Liske, J.; López-Sánchez, A. R.; Robotham, A. S. G.

2015-02-01

We present bivariate luminosity and stellar mass functions of Hα star-forming galaxies drawn from the Galaxy And Mass Assembly (GAMA) survey. While optically deep spectroscopic observations of GAMA over a wide sky area enable the detection of a large number of 0.001 < SFRHα (M⊙ yr-1) < 100 galaxies, the requirement for an Hα detection in targets selected from an r-band magnitude-limited survey leads to an incompleteness due to missing optically faint star-forming galaxies. Using z < 0.1 bivariate distributions as a reference we model the higher-z distributions, thereby approximating a correction for the missing optically faint star-forming galaxies to the local star formation rate (SFR) and M densities. Furthermore, we obtain the r-band luminosity functions (LFs) and stellar mass functions of Hα star-forming galaxies from the bivariate LFs. As our sample is selected on the basis of detected Hα emission, a direct tracer of ongoing star formation, this sample represents a true star-forming galaxy sample, and is drawn from both photometrically classified blue and red subpopulations, though mostly from the blue population. On average 20-30 per cent of red galaxies at all stellar masses are star forming, implying that these galaxies may be dusty star-forming systems.

The Particle Adventure | What is fundamental? | Fundamental

Science.gov Websites

Quiz - What particles are made of The four interactions How does matter interact? The unseen effect Half life Missing mass Particle decay mediators Virtual particles Different interactions Annihilations

Missing persons-missing data: the need to collect antemortem dental records of missing persons.

PubMed

Blau, Soren; Hill, Anthony; Briggs, Christopher A; Cordner, Stephen M

2006-03-01

The subject of missing persons is of great concern to the community with numerous associated emotional, financial, and health costs. This paper examines the forensic medical issues raised by the delayed identification of individuals classified as "missing" and highlights the importance of including dental data in the investigation of missing persons. Focusing on Australia, the current approaches employed in missing persons investigations are outlined. Of particular significance is the fact that each of the eight Australian states and territories has its own Missing Persons Unit that operates within distinct state and territory legislation. Consequently, there is a lack of uniformity within Australia about the legal and procedural framework within which investigations of missing persons are conducted, and the interaction of that framework with coronial law procedures. One of the main investigative problems in missing persons investigations is the lack of forensic medical, particularly, odontological input. Forensic odontology has been employed in numerous cases in Australia where identity is unknown or uncertain because of remains being skeletonized, incinerated, or partly burnt. The routine employment of the forensic odontologist to assist in missing person inquiries, has however, been ignored. The failure to routinely employ forensic odontology in missing persons inquiries has resulted in numerous delays in identification. Three Australian cases are presented where the investigation of individuals whose identity was uncertain or unknown was prolonged due to the failure to utilize the appropriate (and available) dental resources. In light of the outcomes of these cases, we suggest that a national missing persons dental records database be established for future missing persons investigations. Such a database could be easily managed between a coronial system and a forensic medical institute. In Australia, a national missing persons dental records database could be incorporated into the National Coroners Information System (NCIS) managed, on behalf of Australia's Coroners, by the Victorian Institute of Forensic Medicine. The existence of the NCIS would ensure operational collaboration in the implementation of the system and cost savings to Australian policing agencies involved in missing person inquiries. The implementation of such a database would facilitate timely and efficient reconciliation of clinical and postmortem dental records and have subsequent social and financial benefits.

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

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

The results of a search for the top squark, the supersymmetric partner of the top quark, in final states with one isolated electron or muon, jets, and missing transverse momentum are reported. The search uses the 2015 LHC pp collision data at a center-of-mass energy of √s=13 TeV recorded by the ATLAS detector and corresponding to an integrated luminosity of 3.2 fb -1. The analysis targets two types of signal models: gluino-mediated pair production of top squarks with a nearly mass-degenerate top squark and neutralino and direct pair production of top squarks, decaying to the top quark and the lightestmore » neutralino. The experimental signature in both signal scenarios is similar to that of a top quark pair produced in association with large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits on gluino and top squark masses are set at 95% confidence level. The results extend the LHC run-1 exclusion limit on the gluino mass up to 1460 GeV in the gluino-mediated scenario in the high gluino and low top squark mass region and add an excluded top squark mass region from 745 to 780 GeV for the direct top squark model with a massless lightest neutralino. The results are also reinterpreted to set exclusion limits in a model of vectorlike top quarks.« less

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

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

The results of a search for the top squark, the supersymmetric partner of the top quark, in final states with one isolated electron or muon, jets, and missing transverse momentum are reported. The search uses the 2015 LHC p p collision data at a center-of-mass energy of √ s = 13 TeV recorded by the ATLAS detector and corresponding to an integrated luminosity of 3.2 fb - 1 . The analysis targets two types of signal models: gluino-mediated pair production of top squarks with a nearly mass-degenerate top squark and neutralino and direct pair production of top squarks, decaying tomore » the top quark and the lightest neutralino. The experimental signature in both signal scenarios is similar to that of a top quark pair produced in association with large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits on gluino and top squark masses are set at 95% confidence level. The results extend the LHC run-1 exclusion limit on the gluino mass up to 1460 GeV in the gluino-mediated scenario in the high gluino and low top squark mass region and add an excluded top squark mass region from 745 to 780 GeV for the direct top squark model with a massless lightest neutralino. The results are also reinterpreted to set exclusion limits in a model of vectorlike top quarks.« less

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

Khachatryan, Vardan

Results are reported from a search for supersymmetry with gauge-mediated supersymmetry breaking in electroweak production. Final states with photons and large missing transverse energy (more » $$E_{\\mathrm{T}}^{\\text{miss}}$$) were examined. The data sample was collected in pp collisions at $$\\sqrt{s} = $$ 8 TeV with the CMS detector at the LHC and corresponds to 7.4 fb$$^{-1}$$. The analysis focuses on scenarios in which the lightest neutralino has bino- or wino-like components, resulting in decays to photons and gravitinos, where the gravitinos escape undetected. The data were obtained using a specially designed trigger with dedicated low thresholds, providing good sensitivity to signatures with photons, $$E_{\\mathrm{T}}^{\\text{miss}}$$, and low hadronic energy. No excess of events over the standard model expectation is observed. The results are interpreted using the model of general gauge mediation. With the wino mass fixed at 10 GeV above that of the bino, wino masses below 710 GeV are excluded at 95% confidence level. Lastly, constraints are also set in the context of two simplified models, for which the analysis sets the lowest cross section limits on the electroweak production of supersymmetric particles.« less

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

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

The reconstruction and calibration algorithms used to calculate missing transverse momentum (E miss T) with the ATLAS detector exploit energy deposits in the calorimeter and tracks reconstructed in the inner detector as well as the muon spectrometer. Various strategies are used to suppress effects arising from additional proton–proton interactions, called pileup, concurrent with the hard-scatter processes. Tracking information is used to distinguish contributions from the pileup interactions using their vertex separation along the beam axis. The performance of the E miss T reconstruction algorithms, especially with respect to the amount of pileup, is evaluated using data collected in proton–proton collisionsmore » at a centre-of-mass energy of 8 TeV during 2012, and results are shown for a data sample corresponding to an integrated luminosity of 20.3fb –1. The simulation and modelling of E miss T in events containing a Z boson decaying to two charged leptons (electrons or muons) or a W boson decaying to a charged lepton and a neutrino are compared to data. The acceptance for different event topologies, with and without high transverse momentum neutrinos, is shown for a range of threshold criteria for E miss T, and estimates of the systematic uncertainties in the E miss T measurements are presented.« less

Design, implementation and reporting strategies to reduce the instance and impact of missing patient-reported outcome (PRO) data: a systematic review

PubMed Central

Mercieca-Bebber, Rebecca; Palmer, Michael J; Brundage, Michael; Stockler, Martin R; King, Madeleine T

2016-01-01

Objectives Patient-reported outcomes (PROs) provide important information about the impact of treatment from the patients' perspective. However, missing PRO data may compromise the interpretability and value of the findings. We aimed to report: (1) a non-technical summary of problems caused by missing PRO data; and (2) a systematic review by collating strategies to: (A) minimise rates of missing PRO data, and (B) facilitate transparent interpretation and reporting of missing PRO data in clinical research. Our systematic review does not address statistical handling of missing PRO data. Data sources MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases (inception to 31 March 2015), and citing articles and reference lists from relevant sources. Eligibility criteria English articles providing recommendations for reducing missing PRO data rates, or strategies to facilitate transparent interpretation and reporting of missing PRO data were included. Methods 2 reviewers independently screened articles against eligibility criteria. Discrepancies were resolved with the research team. Recommendations were extracted and coded according to framework synthesis. Results 117 sources (55% discussion papers, 26% original research) met the eligibility criteria. Design and methodological strategies for reducing rates of missing PRO data included: incorporating PRO-specific information into the protocol; carefully designing PRO assessment schedules and defining termination rules; minimising patient burden; appointing a PRO coordinator; PRO-specific training for staff; ensuring PRO studies are adequately resourced; and continuous quality assurance. Strategies for transparent interpretation and reporting of missing PRO data include utilising auxiliary data to inform analysis; transparently reporting baseline PRO scores, rates and reasons for missing data; and methods for handling missing PRO data. Conclusions The instance of missing PRO data and its potential to bias clinical research can be minimised by implementing thoughtful design, rigorous methodology and transparent reporting strategies. All members of the research team have a responsibility in implementing such strategies. PMID:27311907

Search for supersymmetry in events containing a same-flavour opposite-sign dilepton pair, jets, and large missing transverse momentum in [Formula: see text] TeV pp collisions with the ATLAS detector.

PubMed

Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Aben, R; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Aguilar-Saavedra, J A; Agustoni, M; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimoto, G; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Alimonti, G; Alio, L; Alison, J; Alkire, S P; Allbrooke, B M M; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Altheimer, A; Alvarez Gonzalez, B; Piqueras, D Álvarez; Alviggi, M G; Amako, K; Amaral Coutinho, Y; Amelung, C; Amidei, D; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amram, N; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; Anghinolfi, F; 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Two searches for supersymmetric particles in final states containing a same-flavour opposite-sign lepton pair, jets and large missing transverse momentum are presented. The proton-proton collision data used in these searches were collected at a centre-of-mass energy [Formula: see text] TeV by the ATLAS detector at the Large Hadron Collider and corresponds to an integrated luminosity of 20.3 fb[Formula: see text]. Two leptonic production mechanisms are considered: decays of squarks and gluinos with Z bosons in the final state, resulting in a peak in the dilepton invariant mass distribution around the Z -boson mass; and decays of neutralinos (e.g. [Formula: see text]), resulting in a kinematic endpoint in the dilepton invariant mass distribution. For the former, an excess of events above the expected Standard Model background is observed, with a significance of three standard deviations. In the latter case, the data are well-described by the expected Standard Model background. The results from each channel are interpreted in the context of several supersymmetric models involving the production of squarks and gluinos.

Why a geoeffective CME was missed by SOHO LASCO?

NASA Astrophysics Data System (ADS)

Chi, Y.; Zhang, J.; Shen, C.; Hess, P.; Feng, L.; Wang, Y.; Mishra, W.

2017-12-01

During 2011 May 25, two Earth directed coronal mass ejections (CMEs) were recorded by STEREO COR2 as limb CMEs, when the separation between twin STEREO spacecraft and Earth was approximately 90°. At the same time, SOHO LASCO did not record corresponding halo or partial halo CME. These CMEs provided an opportunity to study why SOHO LASCO may miss Earth direction CME. According to GCS model, we find the two CMEs both have small half angle and aspect ratio. Most part of CMEs are behind the occulter of SOHO LASCO C2. We also estimated the two CMEs' mass and find the both CMEs' mass is small. The expected CME brightness according to the CME's mass is in the same order of the noise of SOHO LASCO. In the HI1 Fov, We have found evidence of interaction between the two CMEs. Combining with the WIND in situ observations, we find the CMEs are adjacent to each other. The duration of the two flux rope structure are 7 and 6.6 hours, respectively. This may provide an evidence that small flux structure without corresponding CME is also the solar erupted structure.

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

Khachatryan, Vardan

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

Search for long-lived, massive particles in events with displaced vertices and missing transverse momentum in s = 13 TeV p p collisions with the ATLAS detector

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

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

A search for long-lived, massive particles predicted by many theories beyond the Standard Model is presented. Here, the search targets final states with large missing transverse momentum and at least one high-mass displaced vertex with five or more tracks, and uses 32.8 fb -1 of √ s = 13 TeV pp collision data collected by the ATLAS detector at the LHC. The observed yield is consistent with the expected background. The results are used to extract 95% C.L. exclusion limits on the production of long-lived gluinos with masses up to 2.37 TeV and lifetimes of O (10 - 2) -more » O (10) ns in a simplified model inspired by split supersymmetry.« less

Search for long-lived, massive particles in events with displaced vertices and missing transverse momentum in s = 13 TeV p p collisions with the ATLAS detector

DOE PAGES

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

2018-03-28

A search for long-lived, massive particles predicted by many theories beyond the Standard Model is presented. Here, the search targets final states with large missing transverse momentum and at least one high-mass displaced vertex with five or more tracks, and uses 32.8 fb -1 of √ s = 13 TeV pp collision data collected by the ATLAS detector at the LHC. The observed yield is consistent with the expected background. The results are used to extract 95% C.L. exclusion limits on the production of long-lived gluinos with masses up to 2.37 TeV and lifetimes of O (10 - 2) -more » O (10) ns in a simplified model inspired by split supersymmetry.« less

Search for squarks and gluinos in events with an isolated lepton, jets, and missing transverse momentum at s = 13 TeV with the ATLAS detector

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

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

Tmore » he results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a center-of-mass energy of s = 13 eV are presented. he data set used was recorded during 2015 and 2016 by the ALAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb -1 . No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 eV for gluino pair production and up to 1.25 eV for squark pair production.« less

Search for squarks and gluinos in events with an isolated lepton, jets, and missing transverse momentum at s = 13 TeV with the ATLAS detector

DOE PAGES

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

2017-12-26

Tmore » he results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a center-of-mass energy of s = 13 eV are presented. he data set used was recorded during 2015 and 2016 by the ALAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb -1 . No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 eV for gluino pair production and up to 1.25 eV for squark pair production.« less

Search for supersymmetry in events with three leptons and missing transverse momentum in √[s]=7 TeV pp collisions with the ATLAS detector.

PubMed

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Williams, E; Williams, H H; Willis, W; Willocq, S; Wilson, J A; Wilson, M G; Wilson, A; Wingerter-Seez, I; Winkelmann, S; Winklmeier, F; Wittgen, M; Wolter, M W; Wolters, H; Wong, W C; Wooden, G; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wraight, K; Wright, C; Wright, M; Wrona, B; Wu, S L; Wu, X; Wu, Y; Wulf, E; Wynne, B M; Xella, S; Xiao, M; Xie, S; Xu, C; Xu, D; Yabsley, B; Yacoob, S; Yamada, M; Yamaguchi, H; Yamamoto, A; Yamamoto, K; Yamamoto, S; Yamamura, T; Yamanaka, T; Yamaoka, J; Yamazaki, T; Yamazaki, Y; Yan, Z; Yang, H; Yang, U K; Yang, Y; Yang, Z; Yanush, S; Yao, L; Yao, Y; Yasu, Y; Ybeles Smit, G V; Ye, J; Ye, S; Yilmaz, M; Yoosoofmiya, R; Yorita, K; Yoshida, R; Young, C; Young, C J; Youssef, S; Yu, D; Yu, J; Yu, J; Yuan, L; Yurkewicz, A; Zabinski, B; Zaidan, R; Zaitsev, A M; Zajacova, Z; Zanello, L; Zaytsev, A; Zeitnitz, C; Zeller, M; Zeman, M; Zemla, A; Zendler, C; Zenin, O; Ženiš, T; Zinonos, Z; Zenz, S; Zerwas, D; Zevi della Porta, G; Zhan, Z; Zhang, D; Zhang, H; Zhang, J; Zhang, X; Zhang, Z; Zhao, L; Zhao, T; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, N; Zhou, Y; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhuravlov, V; Zieminska, D; Zimmermann, R; Zimmermann, S; Zimmermann, S; Ziolkowski, M; Zitoun, R; Živković, L; Zmouchko, V V; Zobernig, G; Zoccoli, A; zur Nedden, M; Zutshi, V; Zwalinski, L

2012-06-29

A search for the weak production of charginos and neutralinos decaying to a final state with three leptons (electrons or muons) and missing transverse momentum is presented. The analysis uses 2.06 fb(-1) of √[s]=7 TeV proton-proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with standard model expectations in two signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric and simplified models. For the simplified models, degenerate lightest chargino and next-to-lightest neutralino masses up to 300 GeV are excluded for mass differences from the lightest neutralino up to 300 GeV.

Missing-mass spectroscopy of the 12C(p ,d ) reaction near the η'-meson production threshold

NASA Astrophysics Data System (ADS)

Tanaka, Y. K.; Itahashi, K.; Fujioka, H.; Ayyad, Y.; Benlliure, J.; Brinkmann, K.-T.; Friedrich, S.; Geissel, H.; Gellanki, J.; Guo, C.; Gutz, E.; Haettner, E.; Harakeh, M. N.; Hayano, R. S.; Higashi, Y.; Hirenzaki, S.; Hornung, C.; Igarashi, Y.; Ikeno, N.; Iwasaki, M.; Jido, D.; Kalantar-Nayestanaki, N.; Kanungo, R.; Knöbel, R.; Kurz, N.; Metag, V.; Mukha, I.; Nagae, T.; Nagahiro, H.; Nanova, M.; Nishi, T.; Ong, H. J.; Pietri, S.; Prochazka, A.; Rappold, C.; Reiter, M. P.; Rodríguez-Sánchez, J. L.; Scheidenberger, C.; Simon, H.; Sitar, B.; Strmen, P.; Sun, B.; Suzuki, K.; Szarka, I.; Takechi, M.; Tanihata, I.; Terashima, S.; Watanabe, Y. N.; Weick, H.; Widmann, E.; Winfield, J. S.; Xu, X.; Yamakami, H.; Zhao, J.; η-PRiME/Super-FRS Collaboration

2018-01-01

Excitation-energy spectra of 11C nuclei near the η'-meson production threshold have been measured by missing-mass spectroscopy using the 12C(p ,d ) reaction. A carbon target has been irradiated with a 2.5 GeV proton beam supplied by the synchrotron SIS-18 at GSI to produce η'-meson bound states in 11C nuclei. Deuterons emitted at 0∘ in the reaction have been momentum analyzed by the fragment separator (FRS), used as a high-resolution spectrometer. No distinct structure due to the formation of η'-mesic states is observed although a high statistical sensitivity is achieved in the experimental spectra. Upper limits on the formation cross sections of η'-mesic states are determined, and thereby a constraint imposed on the η'-nucleus interaction is discussed.

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

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; 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. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. 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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. 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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

The results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a center-of-mass energy of √{s }=13 TeV are presented. The data set used was recorded during 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb-1 . No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 TeV for gluino pair production and up to 1.25 TeV for squark pair production.

En-masse protraction of mandibular posterior teeth into missing mandibular lateral incisor spaces using a fixed functional appliance.

PubMed

Chhibber, Aditya; Upadhyay, Madhur

2016-11-01

Protraction of mandibular posterior teeth requiring absolute anchorage has always been a challenge, especially when the space is located in the anterior region, since more teeth must be protracted. Traditionally, skeletal anchorage devices have been used for anchorage reinforcement during protraction. However, drawbacks such as requirement of a surgical step, inability to tolerate heavy forces, and patient willingness to undergo such surgical procedures can be limiting factors. Additionally, the mechanics involved can sometimes create undesirable side effects, thereby limiting their application in such situations. This report describes the use of a fixed functional appliance as an anchorage-reinforcement device for en-masse protraction of mandibular posterior teeth into a missing lateral incisor space. Copyright © 2016 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Search for long-lived, massive particles in events with displaced vertices and missing transverse momentum in √{s }=13 TeV p p collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

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J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Bello, F. A.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Girolamo, B.; di Micco, B.; di Nardo, R.; di Petrillo, K. F.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Duvnjak, D.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. 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W.; Higashino, S.; Higón-Rodriguez, E.; Hildebrand, K.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hils, M.; Hinchliffe, I.; Hirose, M.; Hirschbuehl, D.; Hiti, B.; Hladik, O.; Hoad, X.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohn, D.; Holmes, T. R.; Homann, M.; Honda, S.; Honda, T.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hoya, J.; Hrabovsky, M.; Hrdinka, J.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, P. J.; Hsu, S.-C.; Hu, Q.; Hu, S.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Isacson, M. F.; Ishijima, N.; Ishino, M.; Ishitsuka, M.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, P.; Jacobs, R. M.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javå¯Rek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. 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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. 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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.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. 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.; 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.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, 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

2018-03-01

A search for long-lived, massive particles predicted by many theories beyond the Standard Model is presented. The search targets final states with large missing transverse momentum and at least one high-mass displaced vertex with five or more tracks, and uses 32.8 fb-1 of √{s }=13 TeV p p collision data collected by the ATLAS detector at the LHC. The observed yield is consistent with the expected background. The results are used to extract 95% C.L. exclusion limits on the production of long-lived gluinos with masses up to 2.37 TeV and lifetimes of O (10-2)-O (10 ) ns in a simplified model inspired by split supersymmetry.

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

Search for gauge-mediated supersymmetry in events with at least one photon and missing transverse momentum in pp 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.; 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. 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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, J.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Wang, Y.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Segura Delgado, M. A.; 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.; Ellithi Kamel, A.; Khalil, S.; Mohamed, A.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkilä, J. K.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Lindén, T.; Luukka, P.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Leloup, C.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. 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K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Teroerde, M.; Zhukov, V.; Albert, A.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bermúdez Martínez, A.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Guthoff, M.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Raspereza, A.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Aggleton, R.; Bein, S.; Blobel, V.; Centis Vignali, M.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Hoffmann, M.; Karavdina, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baselga, M.; Baur, S.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Faltermann, N.; Freund, B.; Friese, R.; Giffels, M.; Harrendorf, M. A.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Karathanasis, G.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Kousouris, K.; Evangelou, I.; Foudas, C.; Gianneios, P.; Katsoulis, P.; Kokkas, P.; Mallios, S.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Tsitsonis, D.; Csanad, M.; Filipovic, N.; Pasztor, G.; Surányi, O.; Veres, G. I.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kaur, S.; Kumar, R.; Kumari, P.; Mehta, A.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Bhawandeep, U.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. 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M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Lezki, S.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Borgonovi, L.; Braibant-Giacomelli, S.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. 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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.; Eno, S. C.; Feng, Y.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Hu, M.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Hiltbrand, J.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Wadud, M. A.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Freer, C.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wamorkar, T.; Wang, B.; Wisecarver, A.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Bucci, R.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Li, W.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Siddireddy, P.; Smith, G.; Taroni, S.; Wayne, M.; Wightman, A.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Kalogeropoulos, A.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Das, S.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xiao, R.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. M.; Guilbaud, M.; Kilpatrick, M.; Li, W.; Michlin, B.; Padley, B. P.; Roberts, J.; Rorie, J.; Shi, W.; Tu, Z.; Zabel, J.; Zhang, A.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Mengke, T.; Muthumuni, S.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Poudyal, N.; Sturdy, J.; Thapa, P.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

2018-05-01

A search for gauge-mediated supersymmetry (SUSY) in final states with photons and large missing transverse momentum is presented. The data sample of pp collisions at √{ s } = 13TeV was collected with the CMS detector at the CERN LHC and corresponds to an integrated luminosity of 35.9 fb-1. Data are compared with models in which the lightest neutralino has bino- or wino-like components, resulting in decays to photons and gravitinos, where the gravitinos escape detection. The event selection is optimized for both electroweak (EWK) and strong production SUSY scenarios. The observed data are consistent with standard model predictions, and limits are set in the context of a general gauge mediation model in which gaugino masses up to 980 GeV are excluded at 95% confidence level. Gaugino masses below 780 and 950 GeV are excluded in two simplified models with EWK production of mass-degenerate charginos and neutralinos. Stringent limits are set on simplified models based on gluino and squark pair production, excluding gluino (squark) masses up to 2100 (1750) GeV depending on the assumptions made for the decay modes and intermediate particle masses. This analysis sets the highest mass limits to date in the studied EWK models, and in the considered strong production models when the mass difference between the gauginos and the squarks or gluinos is small.

Search for gauge-mediated supersymmetry in events with at least one photon and missing transverse momentum in pp collisions at s = 13 TeV

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

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

A search for gauge-mediated supersymmetry (SUSY) in final states with photons and large missing transverse momentum is presented. The data sample of pp collisions atmore » $$\\sqrt{s} = $$ 13 TeV was collected with the CMS detector at the CERN LHC and corresponds to an integrated luminosity of 35.9 fb$$^{-1}$$. Data are compared with models in which the lightest neutralino has bino- or wino-like components, resulting in decays to photons and gravitinos, where the gravitinos escape detection. The event selection is optimized for both electroweak (EWK) and strong production SUSY scenarios. The observed data are consistent with standard model predictions, and limits are set in the context of a general gauge mediation model in which gaugino masses up to 980 GeV are excluded at 95% confidence level. Gaugino masses below 780 and 950 GeV are excluded in two simplified models with EWK production of mass-degenerate charginos and neutralinos. Stringent limits are set on simplified models based on gluino and squark pair production, excluding gluino (squark) masses up to 2100 (1750) GeV depending on the assumptions made for the decay modes and intermediate particle masses. This analysis sets the highest mass limits to date in the studied EWK models, and in the considered strong production models when the mass difference between the gauginos and the squarks or gluinos is small.« less

Search for squarks and gluinos in events with hadronically decaying tau leptons, jets and missing transverse momentum in proton-proton collisions at [Formula: see text] TeV recorded with the ATLAS detector.

PubMed

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2016-01-01

A search for supersymmetry in events with large missing transverse momentum, jets, and at least one hadronically decaying tau lepton has been performed using 3.2 fb[Formula: see text] of proton-proton collision data at [Formula: see text] recorded by the ATLAS detector at the Large Hadron Collider in 2015. Two exclusive final states are considered, with either exactly one or at least two tau leptons. No excess over the Standard Model prediction is observed in the data. Results are interpreted in the context of gauge-mediated supersymmetry breaking and a simplified model of gluino pair production with tau-rich cascade decays, substantially improving on previous limits. In the GMSB model considered, supersymmetry-breaking scale ([Formula: see text]) values below [Formula: see text] are excluded at the 95% confidence level, corresponding to gluino masses below [Formula: see text]. For large values of [Formula: see text], values of [Formula: see text] up to [Formula: see text] and gluino masses up to [Formula: see text] are excluded. In the simplified model, gluino masses are excluded up to [Formula: see text] for neutralino masses around [Formula: see text]. Neutralino masses below [Formula: see text] are excluded for all gluino masses between 800 and [Formula: see text], while the strongest exclusion of [Formula: see text] is achieved for gluino masses around [Formula: see text].

Search for squarks and gluinos in events with hadronically decaying tau leptons, jets and missing transverse momentum in proton-proton collisions at √{s}=13 TeV recorded with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; 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.; Gonzalez, B. Alvarez; Piqueras, D. Álvarez; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. 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E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Navarro, L. Barranco; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. 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M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shirabe, S.; Shiyakova, M.; Shmeleva, A.; Saadi, D. Shoaleh; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Sanchez, C. A. Solans; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Denis, R. D. St.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Araya, S. Tapia; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Kate, H. Ten; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Torres, R. E. Ticse; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Santurio, E. Valdes; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Ferrer, J. A. Valls; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, W.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wolf, T. M. H.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Nedden, M. zur; Zwalinski, L.

2016-12-01

A search for supersymmetry in events with large missing transverse momentum, jets, and at least one hadronically decaying tau lepton has been performed using 3.2 fb^{-1} of proton-proton collision data at √{s}=13{ TeV} recorded by the ATLAS detector at the Large Hadron Collider in 2015. Two exclusive final states are considered, with either exactly one or at least two tau leptons. No excess over the Standard Model prediction is observed in the data. Results are interpreted in the context of gauge-mediated supersymmetry breaking and a simplified model of gluino pair production with tau-rich cascade decays, substantially improving on previous limits. In the GMSB model considered, supersymmetry-breaking scale (Λ ) values below 92 { TeV} are excluded at the 95% confidence level, corresponding to gluino masses below 2000 { GeV}. For large values of tan β , values of Λ up to 107 { TeV} and gluino masses up to 2300 { GeV} are excluded. In the simplified model, gluino masses are excluded up to 1570 { GeV} for neutralino masses around 100 { GeV}. Neutralino masses below 700 { GeV} are excluded for all gluino masses between 800 and 1500 { GeV}, while the strongest exclusion of 750 { GeV} is achieved for gluino masses around 1450 { GeV}.

Search for squarks and gluinos in events with hadronically decaying tau leptons, jets and missing transverse momentum in proton–proton collisions at $$\\sqrt{s}=13$$ TeV recorded with the ATLAS detector

DOE PAGES

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

2016-12-10

A search for supersymmetry in events with large missing transverse momentum, jets, and at least one hadronically decaying tau lepton has been performed using 3.2 fb –1 of proton–proton collision data at √s = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider in 2015. Two exclusive final states are considered, with either exactly one or at least two tau leptons. No excess over the Standard Model prediction is observed in the data. Results are interpreted in the context of gauge-mediated supersymmetry breaking and a simplified model of gluino pair production with tau-rich cascade decays, substantially improvingmore » on previous limits. In the GMSB model considered, supersymmetry-breaking scale (Λ) values below 92 TeV are excluded at the 95% confidence level, corresponding to gluino masses below 2000 GeV. For large values of tanβ, values of Λ up to 107 TeV and gluino masses up to 2300 GeV are excluded. In the simplified model, gluino masses are excluded up to 1570 GeV for neutralino masses around 100 GeV. Neutralino masses below 700 GeV are excluded for all gluino masses between 800 and 1500 GeV, while the strongest exclusion of 750 GeV is achieved for gluino masses around 1450 GeV.« less

Search for supersymmetry in proton-proton collisions at 13 TeV using identified top quarks

DOE PAGES

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

2018-01-31

A search for supersymmetry is presented based on proton-proton collision events containing identified hadronically decaying top quarks, no leptons, and an imbalance pmore » $$miss\\atop{T}$$ in transverse momentum. The data were collected with the CMS detector at the CERN LHC at a center-of-mass energy of 13 TeV, and correspond to an integrated luminosity of 35.9 fb -1. Search regions are defined in terms of the multiplicity of bottom quark jet and top quark candidates, the p$$miss\\atop{T}$$, the scalar sum of jet transverse momenta, and the m T2 mass variable. No statistically significant excess of events is observed relative to the expectation from the standard model. Lower limits on the masses of supersymmetric particles are determined at 95% confidence level in the context of simplified models with top quark production. For a model with direct top squark pair production followed by the decay of each top squark to a top quark and a neutralino, top squark masses up to 1020 GeV and neutralino masses up to 430 GeV are excluded. For a model with pair production of gluinos followed by the decay of each gluino to a top quark-antiquark pair and a neutralino, gluino masses up to 2040 GeV and neutralino masses up to 1150 GeV are excluded. Finally, these limits extend previous results.« less

Search for gauge-mediated supersymmetry in events with at least one photon and missing transverse momentum in pp collisions at s = 13 TeV

DOE PAGES

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

2018-02-23

A search for gauge-mediated supersymmetry (SUSY) in final states with photons and large missing transverse momentum is presented. The data sample of pp collisions atmore » $$\\sqrt{s} = $$ 13 TeV was collected with the CMS detector at the CERN LHC and corresponds to an integrated luminosity of 35.9 fb$$^{-1}$$. Data are compared with models in which the lightest neutralino has bino- or wino-like components, resulting in decays to photons and gravitinos, where the gravitinos escape detection. The event selection is optimized for both electroweak (EWK) and strong production SUSY scenarios. The observed data are consistent with standard model predictions, and limits are set in the context of a general gauge mediation model in which gaugino masses up to 980 GeV are excluded at 95% confidence level. Gaugino masses below 780 and 950 GeV are excluded in two simplified models with EWK production of mass-degenerate charginos and neutralinos. Stringent limits are set on simplified models based on gluino and squark pair production, excluding gluino (squark) masses up to 2100 (1750) GeV depending on the assumptions made for the decay modes and intermediate particle masses. This analysis sets the highest mass limits to date in the studied EWK models, and in the considered strong production models when the mass difference between the gauginos and the squarks or gluinos is small.« less

Modeling and Analysis of Wholesale Electricity Market Design. Understanding the Missing Money Problem. December 2013 - January 2015

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

Papalexopoulos, A.; Hansen, C.; Perrino, D.

This project examined the impact of renewable energy sources, which have zero incremental energy costs, on the sustainability of conventional generation. This “missing money” problem refers to market outcomes in which infra-marginal energy revenues in excess of operations and maintenance (O&M) costs are systematically lower than the amortized costs of new entry for a marginal generator. The problem is caused by two related factors: (1) conventional generation is dispatched less, and (2) the price that conventional generation receives for its energy is lower. This lower revenue stream may not be sufficient to cover both the variable and fixed costs ofmore » conventional generation. In fact, this study showed that higher wind penetrations in the Electric Reliability Council of Texas (ERCOT) system could cause many conventional generators to become uneconomic.« less

A method to estimate the additional uncertainty in gap-filled NEE resulting from long gaps in the CO2 flux record

Treesearch

Andrew D. Richardson; David Y. Hollinger

2007-01-01

Missing values in any data set create problems for researchers. The process by which missing values are replaced, and the data set is made complete, is generally referred to as imputation. Within the eddy flux community, the term "gap filling" is more commonly applied. A major challenge is that random errors in measured data result in uncertainty in the gap-...

Search for supersymmetry in events with at least three electrons or muons, jets, and missing transverse momentum in proton-proton collisions at $$ \\sqrt{s}=13 $$ TeV

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

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

Here, a search for new physics is carried out in events with at least three electrons or muons in any combination, jets, and missing transverse momentum. Results are based on the sample of proton-proton collision data produced by the LHC at a center-of-mass energy of 13 TeV and collected by the CMS experiment in 2016. The data sample analyzed corresponds to an integrated luminosity of 35.9 fbmore » $$^{-1}$$. Events are classified according to the number of b jets, missing transverse momentum, hadronic transverse momentum, and the invariant mass of same-flavor dilepton pairs with opposite charge. No significant excess above the expected standard model background is observed. Exclusion limits at 95% confidence level are computed for four different supersymmetric simplified models with pair production of gluinos or third-generation squarks. In the model with gluino pair production, with subsequent decays into a top quark-antiquark pair and a neutralino, gluinos with masses smaller than 1610 GeV are excluded for a massless lightest supersymmetric particle. In the case of bottom squark pair production, the bottom squark masses are excluded up to 840 GeV for charginos lighter than 200 GeV. For a simplified model of heavy top squark pair production, the $$\\mathrm{\\widetilde{\\text{t}}_2}$$ mass is excluded up to 720, 780, or 710 GeV for models with an exclusive $$\\mathrm{\\widetilde{\\text{t}}_2}\\rightarrow\\mathrm{\\widetilde{\\text{t}}_1}\\mathrm{H}$$ decay, an exclusive $$\\mathrm{\\widetilde{\\text{t}}_2}\\rightarrow\\mathrm{\\widetilde{\\text{t}}_1}\\mathrm{Z}$$ decay, or an equally probable mix of those two decays. In order to provide a simplified version of the analysis for easier interpretation, a small set of aggregate signal regions also has been defined, providing a compromise between simplicity and analysis sensitivity.« less

Search for supersymmetry in events with at least three electrons or muons, jets, and missing transverse momentum in proton-proton collisions at √{s}=13 TeV

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; 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.; Gonzalez, J. Suarez; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Zeid, S. Abu; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Velde, C. Vander; 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.; Marono, M. Vidal; Wertz, S.; Beliy, N.; Júnior, W. L. Aldá; Alves, F. L.; Alves, G. A.; Brito, L.; Junior, M. Correa Martins; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Chagas, E. Belchior Batista Das; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Fonseca De Souza, S.; Guativa, L. M. Huertas; Malbouisson, H.; Melo De Almeida, M.; Herrera, C. Mora; Mundim, L.; Nogima, H.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Da Silva De Araujo, F. Torres; Pereira, A. Vilela; Ahuja, S.; Bernardes, C. A.; Tomei, T. R. Fernandez Perez; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Abad, D. Romero; Vargas, J. C. Ruiz; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Shopova, M.; Stoykova, S.; Sultanov, G.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhang, S.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Sierra, L. F. Chaparro; Florez, C.; Hernández, C. F. González; Alvarez, J. D. Ruiz; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Cipriano, P. M. Ribeiro; 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.; Jarrin, E. Carrera; Kamel, A. Ellithi; Khalil, 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.; Blanco, J. Martin; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Leiton, A. G. Stahl; 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.; Donckt, M. Vander; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Feld, L.; Kiesel, M. 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Kayis; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Cerci, D. Sunar; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Karapinar, G.; Ocalan, K.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Grynyov, B.; Levchuk, L.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Davignon, O.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Auzinger, G.; Bainbridge, R.; Borg, J.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Negra, M. Della; Di Maria, R.; Elwood, A.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Palladino, V.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wardle, N.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Smith, C.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Regnard, S.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Shirazi, S. M. A. Ghiasi; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Negrete, M. Olmedo; Paneva, M. I.; Shrinivas, A.; Si, W.; Wang, L.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Macneill, I.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Porta, G. Zevi Della; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Sevilla, M. Franco; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bendavid, J.; Bornheim, A.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Alyari, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Gonzalez, I. D. Sandoval; 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.; Takaki, J. D. Tapia; 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.; Ceballos, G. Gomez; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Anampa, K. Hurtado; 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.; Espinosa, T. A. Gómez; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Elayavalli, R. Kunnawalkam; 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.; Hernandez, A. Castaneda; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2018-02-01

A search for new physics is carried out in events with at least three electrons or muons in any combination, jets, and missing transverse momentum. Results are based on the sample of proton-proton collision data produced by the LHC at a center-of-mass energy of 13 TeV and collected by the CMS experiment in 2016. The data sample analyzed corresponds to an integrated luminosity of 35.9 fb-1. Events are classified according to the number of b jets, missing transverse momentum, hadronic transverse momentum, and the invariant mass of same-flavor dilepton pairs with opposite charge. No significant excess above the expected standard model background is observed. Exclusion limits at 95% confidence level are computed for four different supersymmetric simplified models with pair production of gluinos or third-generation squarks. In the model with gluino pair production, with subsequent decays into a top quark-antiquark pair and a neutralino, gluinos with masses smaller than 1610 GeV are excluded for a massless lightest supersymmetric particle. In the case of bottom squark pair production, the bottom squark masses are excluded up to 840 GeV for charginos lighter than 200 GeV. For a simplified model of heavy top squark pair production, the \\tilde{t}_2 mass is excluded up to 720, 780, or 710 GeV for models with an exclusive \\tilde{t}_2\\to \\tilde{t}_1H decay, an exclusive \\tilde{t}_2\\to \\tilde{t}_1Z decay, or an equally probable mix of those two decays. In order to provide a simplified version of the analysis for easier interpretation, a small set of aggregate signal regions also has been defined, providing a compromise between simplicity and analysis sensitivity.

Search for supersymmetry in events with at least three electrons or muons, jets, and missing transverse momentum in proton-proton collisions at $$ \\sqrt{s}=13 $$ TeV

DOE PAGES

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

2018-02-12

Here, a search for new physics is carried out in events with at least three electrons or muons in any combination, jets, and missing transverse momentum. Results are based on the sample of proton-proton collision data produced by the LHC at a center-of-mass energy of 13 TeV and collected by the CMS experiment in 2016. The data sample analyzed corresponds to an integrated luminosity of 35.9 fbmore » $$^{-1}$$. Events are classified according to the number of b jets, missing transverse momentum, hadronic transverse momentum, and the invariant mass of same-flavor dilepton pairs with opposite charge. No significant excess above the expected standard model background is observed. Exclusion limits at 95% confidence level are computed for four different supersymmetric simplified models with pair production of gluinos or third-generation squarks. In the model with gluino pair production, with subsequent decays into a top quark-antiquark pair and a neutralino, gluinos with masses smaller than 1610 GeV are excluded for a massless lightest supersymmetric particle. In the case of bottom squark pair production, the bottom squark masses are excluded up to 840 GeV for charginos lighter than 200 GeV. For a simplified model of heavy top squark pair production, the $$\\mathrm{\\widetilde{\\text{t}}_2}$$ mass is excluded up to 720, 780, or 710 GeV for models with an exclusive $$\\mathrm{\\widetilde{\\text{t}}_2}\\rightarrow\\mathrm{\\widetilde{\\text{t}}_1}\\mathrm{H}$$ decay, an exclusive $$\\mathrm{\\widetilde{\\text{t}}_2}\\rightarrow\\mathrm{\\widetilde{\\text{t}}_1}\\mathrm{Z}$$ decay, or an equally probable mix of those two decays. In order to provide a simplified version of the analysis for easier interpretation, a small set of aggregate signal regions also has been defined, providing a compromise between simplicity and analysis sensitivity.« less

Testing Verlinde's emergent gravity in early-type galaxies

NASA Astrophysics Data System (ADS)

Tortora, C.; Koopmans, L. V. E.; Napolitano, N. R.; Valentijn, E. A.

2018-01-01

Emergent Gravity (EG) has been proposed to resolve the missing mass problem in galaxies, replacing the potential of dark matter (DM) by the effect of the entropy displacement of dark energy by baryonic matter. This apparent DM depends only on the baryonic mass distribution and the present-day value of the Hubble parameter. In this paper we test the EG proposition, formalized by Verlinde for a spherical and isolated mass distribution using the central dynamics (Sloan Digital Sky Survey velocity dispersion, σ) and the K-band light distribution in a sample of 4032 massive (M_{\\star }≳ 10^{10} M_{⊙}) and local early-type galaxies (ETGs) from the SPIDER datasample. Our results remain unaltered if we consider the sample of 750 roundest field galaxies. Using these observations we derive the predictions by EG for the stellar mass-to-light ratio (M/L) and the initial mass function (IMF). We demonstrate that, consistently with a classical Newtonian framework with a DM halo component or alternative theories of gravity as MOdified Newtonian Dynamics (MOND), the central dynamics can be fitted if the IMF is assumed non-universal and systematically changing with σ. For the case of EG, we find lower, but still acceptable, stellar M/L if compared with the DM-based Navarro, Frenk & White (NFW) model and with MOND, but pretty similar to adiabatically contracted DM haloes and with expectations from spectral gravity-sensitive features. If the strain caused by the entropy displacement would be not maximal, as adopted in the current formulation, then the dynamics of ETGs could be reproduced with larger M/L.

A review of the handling of missing longitudinal outcome data in clinical trials

PubMed Central

2014-01-01

The aim of this review was to establish the frequency with which trials take into account missingness, and to discover what methods trialists use for adjustment in randomised controlled trials with longitudinal measurements. Failing to address the problems that can arise from missing outcome data can result in misleading conclusions. Missing data should be addressed as a means of a sensitivity analysis of the complete case analysis results. One hundred publications of randomised controlled trials with longitudinal measurements were selected randomly from trial publications from the years 2005 to 2012. Information was extracted from these trials, including whether reasons for dropout were reported, what methods were used for handing the missing data, whether there was any explanation of the methods for missing data handling, and whether a statistician was involved in the analysis. The main focus of the review was on missing data post dropout rather than missing interim data. Of all the papers in the study, 9 (9%) had no missing data. More than half of the papers included in the study failed to make any attempt to explain the reasons for their choice of missing data handling method. Of the papers with clear missing data handling methods, 44 papers (50%) used adequate methods of missing data handling, whereas 30 (34%) of the papers used missing data methods which may not have been appropriate. In the remaining 17 papers (19%), it was difficult to assess the validity of the methods used. An imputation method was used in 18 papers (20%). Multiple imputation methods were introduced in 1987 and are an efficient way of accounting for missing data in general, and yet only 4 papers used these methods. Out of the 18 papers which used imputation, only 7 displayed the results as a sensitivity analysis of the complete case analysis results. 61% of the papers that used an imputation explained the reasons for their chosen method. Just under a third of the papers made no reference to reasons for missing outcome data. There was little consistency in reporting of missing data within longitudinal trials. PMID:24947664

PHYSICS OF ECLIPSING BINARIES. II. TOWARD THE INCREASED MODEL FIDELITY

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

Prša, A.; Conroy, K. E.; Horvat, M.

The precision of photometric and spectroscopic observations has been systematically improved in the last decade, mostly thanks to space-borne photometric missions and ground-based spectrographs dedicated to finding exoplanets. The field of eclipsing binary stars strongly benefited from this development. Eclipsing binaries serve as critical tools for determining fundamental stellar properties (masses, radii, temperatures, and luminosities), yet the models are not capable of reproducing observed data well, either because of the missing physics or because of insufficient precision. This led to a predicament where radiative and dynamical effects, insofar buried in noise, started showing up routinely in the data, but weremore » not accounted for in the models. PHOEBE (PHysics Of Eclipsing BinariEs; http://phoebe-project.org) is an open source modeling code for computing theoretical light and radial velocity curves that addresses both problems by incorporating missing physics and by increasing the computational fidelity. In particular, we discuss triangulation as a superior surface discretization algorithm, meshing of rotating single stars, light travel time effects, advanced phase computation, volume conservation in eccentric orbits, and improved computation of local intensity across the stellar surfaces that includes the photon-weighted mode, the enhanced limb darkening treatment, the better reflection treatment, and Doppler boosting. Here we present the concepts on which PHOEBE is built and proofs of concept that demonstrate the increased model fidelity.« less

Mining Missing Hyperlinks from Human Navigation Traces: A Case Study of Wikipedia.

PubMed

West, Robert; Paranjape, Ashwin; Leskovec, Jure

Hyperlinks are an essential feature of the World Wide Web. They are especially important for online encyclopedias such as Wikipedia: an article can often only be understood in the context of related articles, and hyperlinks make it easy to explore this context. But important links are often missing, and several methods have been proposed to alleviate this problem by learning a linking model based on the structure of the existing links. Here we propose a novel approach to identifying missing links in Wikipedia. We build on the fact that the ultimate purpose of Wikipedia links is to aid navigation. Rather than merely suggesting new links that are in tune with the structure of existing links, our method finds missing links that would immediately enhance Wikipedia's navigability. We leverage data sets of navigation paths collected through a Wikipedia-based human-computation game in which users must find a short path from a start to a target article by only clicking links encountered along the way. We harness human navigational traces to identify a set of candidates for missing links and then rank these candidates. Experiments show that our procedure identifies missing links of high quality.

Exemplar-based inpainting as a solution to the missing wedge problem in electron tomography.

PubMed

Trampert, Patrick; Wang, Wu; Chen, Delei; Ravelli, Raimond B G; Dahmen, Tim; Peters, Peter J; Kübel, Christian; Slusallek, Philipp

2018-04-21

A new method for dealing with incomplete projection sets in electron tomography is proposed. The approach is inspired by exemplar-based inpainting techniques in image processing and heuristically generates data for missing projection directions. The method has been extended to work on three dimensional data. In general, electron tomography reconstructions suffer from elongation artifacts along the beam direction. These artifacts can be seen in the corresponding Fourier domain as a missing wedge. The new method synthetically generates projections for these missing directions with the help of a dictionary based approach that is able to convey both structure and texture at the same time. It constitutes a preprocessing step that can be combined with any tomographic reconstruction algorithm. The new algorithm was applied to phantom data, to a real electron tomography data set taken from a catalyst, as well as to a real dataset containing solely colloidal gold particles. Visually, the synthetic projections, reconstructions, and corresponding Fourier power spectra showed a decrease of the typical missing wedge artifacts. Quantitatively, the inpainting method is capable to reduce missing wedge artifacts and improves tomogram quality with respect to full width half maximum measurements. Copyright © 2018. Published by Elsevier B.V.

Mining Missing Hyperlinks from Human Navigation Traces: A Case Study of Wikipedia

PubMed Central

West, Robert; Paranjape, Ashwin; Leskovec, Jure

2015-01-01

Hyperlinks are an essential feature of the World Wide Web. They are especially important for online encyclopedias such as Wikipedia: an article can often only be understood in the context of related articles, and hyperlinks make it easy to explore this context. But important links are often missing, and several methods have been proposed to alleviate this problem by learning a linking model based on the structure of the existing links. Here we propose a novel approach to identifying missing links in Wikipedia. We build on the fact that the ultimate purpose of Wikipedia links is to aid navigation. Rather than merely suggesting new links that are in tune with the structure of existing links, our method finds missing links that would immediately enhance Wikipedia's navigability. We leverage data sets of navigation paths collected through a Wikipedia-based human-computation game in which users must find a short path from a start to a target article by only clicking links encountered along the way. We harness human navigational traces to identify a set of candidates for missing links and then rank these candidates. Experiments show that our procedure identifies missing links of high quality. PMID:26634229

Performance of missing transverse momentum reconstruction in proton-proton collisions at $$\\sqrt{s} = 7~\\mbox{TeV}$$ with ATLAS

DOE PAGES

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

2012-01-03

The measurement of missing transverse momentum in the ATLAS detector, described in this paper, makes use of the full event reconstruction and a calibration based on reconstructed physics objects. The performance of the missing transverse momentum reconstruction is evaluated using data collected in pp collisions at a centre-of-mass energy of 7 TeV in 2010. Minimum bias events and events with jets of hadrons are used from data samples corresponding to an integrated luminosity of about 0.3 nb –1 and 600 nb –1 respectively, together with events containing a Z boson decaying to two leptons (electrons or muons) or a Wmore » boson decaying to a lepton (electron or muon) and a neutrino, from a data sample corresponding to an integrated luminosity of about 36 pb –1. In conclusion, an estimate of the systematic uncertainty on the missing transverse momentum scale is presented.« less

Variable and complex food web structures revealed by exploring missing trophic links between birds and biofilm.

PubMed

Kuwae, Tomohiro; Miyoshi, Eiichi; Hosokawa, Shinya; Ichimi, Kazuhiko; Hosoya, Jun; Amano, Tatsuya; Moriya, Toshifumi; Kondoh, Michio; Ydenberg, Ronald C; Elner, Robert W

2012-04-01

Food webs are comprised of a network of trophic interactions and are essential to elucidating ecosystem processes and functions. However, the presence of unknown, but critical networks hampers understanding of complex and dynamic food webs in nature. Here, we empirically demonstrate a missing link, both critical and variable, by revealing that direct predator-prey relationships between shorebirds and biofilm are widespread and mediated by multiple ecological and evolutionary determinants. Food source mixing models and energy budget estimates indicate that the strength of the missing linkage is dependent on predator traits (body mass and foraging action rate) and the environment that determines food density. Morphological analyses, showing that smaller bodied species possess more developed feeding apparatus to consume biofilm, suggest that the linkage is also phylogenetically dependent and affords a compelling re-interpretation of niche differentiation. We contend that exploring missing links is a necessity for revealing true network structure and dynamics. © 2012 Blackwell Publishing Ltd/CNRS.

MISSE Results Used for RF Plasma Ground Testing-To-Space-Exposure Correlation for Coated Kapton

NASA Technical Reports Server (NTRS)

Miller, Sharon K. R.; Banks, Bruce A.; Tollis, Greg

2008-01-01

The ability to predict the durability of materials in the low Earth orbit (LEO) environment by exposing them in ground-based facilities is important because one can achieve test results sooner, expose more types of materials, and do it much more cost effectively than to test them in flight. However, flight experiments to determine the durability of groups or classes of materials that behave similarly are needed in order to provide correlations of how much time in ground-based facilities represents certain durations in LEO for the material type of interest. An experiment was designed and flown on the Materials International Space Station Experiment (MISSE) 2 (3.95 yr in LEO) and MISSE 4 (1.04 yr in LEO) in order to develop this type of correlation between ground-based RF plasma exposure and LEO exposure for coated Kapton. The experiment consisted of a sample of Kapton H (DuPont) polyimide coated with 1300 of silicon dioxide by Sheldahl, Inc. The samples were exposed to atomic oxygen in a radio frequency (RF) generated atomic oxygen plasma. Mass change was measured for the samples and then the same samples were exposed in flight on MISSE and the mass change was again recorded post-flight. After documentation, the samples were exposed again in the ground-based RF plasma in order to determine if the erosion would be the same as it had been in the same facility pre-flight which would indicate whether or not the sample had been damaged during flight and if the defects on the surface were those that were there preflight. The slopes of the mass change versus fluence plots were then used to develop a correlation factor that can be used to help predict the durability of coated Kapton in ground-based isotropic atomic oxygen plasma systems. This paper describes the experiment and presents the correlation factor results.

Search for Dark Matter in Events with Missing Transverse Momentum and a Higgs Boson Decaying to Two Photons in pp Collisions at sqrt[s]=8 TeV with the ATLAS Detector.

PubMed

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Stark, J; Staroba, P; Starovoitov, P; Staszewski, R; Stavina, P; Steinberg, P; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stewart, G A; Stillings, J A; Stockton, M C; Stoebe, M; Stoicea, G; Stolte, P; Stonjek, S; Stradling, A R; Straessner, A; Stramaglia, M E; Strandberg, J; Strandberg, S; Strandlie, A; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Stroynowski, R; Strubig, A; Stucci, S A; Stugu, B; Styles, N A; Su, D; Su, J; Subramaniam, R; Succurro, A; Sugaya, Y; Suhr, C; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, S; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, S; Suzuki, Y; Svatos, M; Swedish, S; Swiatlowski, M; Sykora, I; Sykora, T; Ta, D; Taccini, C; Tackmann, K; Taenzer, J; Taffard, A; Tafirout, R; Taiblum, N; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A A; Tam, J Y C; Tan, K G; Tanaka, J; Tanaka, R; Tanaka, S; Tannenwald, B B; Tannoury, N; Tapprogge, S; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tashiro, T; Tassi, E; Tavares Delgado, A; Tayalati, Y; Taylor, F E; Taylor, G N; Taylor, W; Teischinger, F A; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Teoh, J J; Tepel, F; Terada, S; Terashi, K; Terron, J; Terzo, S; Testa, M; Teuscher, R J; Therhaag, J; Theveneaux-Pelzer, T; Thomas, J P; Thomas-Wilsker, J; Thompson, E N; Thompson, P D; Thompson, R J; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thun, R P; Tibbetts, M J; Ticse Torres, R E; Tikhomirov, V O; Tikhonov, Yu A; Timoshenko, S; Tiouchichine, E; Tipton, P; Tisserant, S; Todorov, T; Todorova-Nova, S; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tolley, E; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Trischuk, W; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trovatelli, M; True, P; Truong, L; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsirintanis, N; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsuno, S; Tsybychev, D; Tudorache, A; Tudorache, V; Tuna, A N; Tupputi, S A; Turchikhin, S; Turecek, D; Turra, R; Turvey, A J; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Ueda, I; Ueno, R; Ughetto, M; Ugland, M; Uhlenbrock, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Unverdorben, C; Urban, J; Urquijo, P; Urrejola, P; Usai, G; Usanova, A; Vacavant, L; Vacek, V; Vachon, B; Valderanis, C; Valencic, N; Valentinetti, S; Valero, A; Valery, L; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; Van Den Wollenberg, W; Van Der Deijl, P C; van der Geer, R; van der Graaf, H; Van Der Leeuw, R; van Eldik, N; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; van Woerden, M C; Vanadia, M; Vandelli, W; Vanguri, R; Vaniachine, A; Vannucci, F; Vardanyan, G; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vazeille, F; Vazquez Schroeder, T; Veatch, J; Veloso, F; Velz, T; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Venturini, A; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Viazlo, O; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Vigne, R; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinogradov, V B; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vogel, M; Vokac, P; Volpi, G; Volpi, M; von der Schmitt, H; von Radziewski, H; von Toerne, E; Vorobel, V; Vorobev, K; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vuillermet, R; Vukotic, I; Vykydal, Z; Wagner, P; Wagner, W; Wahlberg, H; Wahrmund, S; Wakabayashi, J; Walder, J; Walker, R; Walkowiak, W; Wang, C; Wang, F; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; Wang, X; Wanotayaroj, C; Warburton, A; Ward, C P; Wardrope, D R; Warsinsky, M; Washbrook, A; Wasicki, C; Watkins, P M; Watson, A T; Watson, I J; Watson, M F; Watts, G; Watts, S; Waugh, B M; Webb, S; Weber, M S; Weber, S W; Webster, J S; Weidberg, A R; Weinert, B; Weingarten, J; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, P; Wessels, M; Wetter, J; Whalen, K; Wharton, A M; White, A; White, M J; White, R; White, S; Whiteson, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wildauer, A; Wilkens, H G; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, A; Wilson, J A; Wingerter-Seez, I; Winklmeier, F; Winter, B T; Wittgen, M; Wittkowski, J; Wollstadt, S J; Wolter, M W; Wolters, H; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wu, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yakabe, R; Yamada, M; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yao, L; Yao, W-M; Yasu, Y; Yatsenko, E; Yau Wong, K H; Ye, J; Ye, S; Yeletskikh, I; Yen, A L; Yildirim, E; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yurkewicz, A; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zalieckas, J; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, J; Zhang, L; Zhang, R; Zhang, X; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, C; Zhou, L; Zhou, L; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zurzolo, G; Zwalinski, L

2015-09-25

Results of a search for new phenomena in events with large missing transverse momentum and a Higgs boson decaying to two photons are reported. Data from proton-proton collisions at a center-of-mass energy of 8 TeV and corresponding to an integrated luminosity of 20.3 fb^{-1} have been collected with the ATLAS detector at the LHC. The observed data are well described by the expected standard model backgrounds. Upper limits on the cross section of events with large missing transverse momentum and a Higgs boson candidate are also placed. Exclusion limits are presented for models of physics beyond the standard model featuring dark-matter candidates.

The Problem of Inertia in a Friedmann Universe

NASA Technical Reports Server (NTRS)

Kazanas, Demosthenes

2012-01-01

In this talk I will discuss the origin of inertia in a curved spacetime, particularly the spatially flat, open and closed Friedmann universes. This is done using Sciama's law of inertial induction, which is based on Mach's principle, and expresses the analogy between the retarded far fields of electrodynamics and those of gravitation. After obtaining covariant expressions for electromagnetic fields due to an accelerating point charge in Friedmann models, we adopt Sciama's law to obtain the inertial force on an accelerating mass $m$ by integrating over the contributions from all the matter in the universe. The resulting inertial force has the form $F = -kma$ where the constant $k < 1 $ depends on the choice of the cosmological parameters such as $\\Omega_{M},\\ \\Omega_{\\Lambda}, $ and $\\Omega_{R}$. The values of $k$ obtained suggest that inertial contribution from dark matter can be the source for the missing part of the inertial force.

Trends in New U.S. Marine Corps Accessions During the Recent Conflicts in Iraq and Afghanistan

DTIC Science & Technology

2014-01-01

modest changes over the study period. Favorable trends included recent (2009-2010) improvernents in body mass index and physical activity levels...height, body mass index (BMI) in kg/m^ was calculated. Frequency of physical activity before service entry was assessed from self-report. Initial run...Test; BMI, body mass index; mph, miles per hour; SD, standard deviation. "Numbers (n) may not add up to 131,961 because of missing self-reported data for

WIMP-less dark matter and meson decays with missing energy

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

McKeen, David

2009-06-01

WIMP-less dark matter [J. L. Feng and J. Kumar, Phys. Rev. Lett. 101, 231301 (2008).] offers an attractive framework in which dark matter can be very light. We investigate the implications of such scenarios on invisible decays of bottomonium states for dark matter with a mass less than around 5 GeV. We relate these decays to measurements of nucleon-dark matter elastic scattering. We also investigate the effect that a coupling to s quarks has on flavor changing b{yields}s processes involving missing energy.

The mean-square error optimal linear discriminant function and its application to incomplete data vectors

NASA Technical Reports Server (NTRS)

Walker, H. F.

1979-01-01

In many pattern recognition problems, data vectors are classified although one or more of the data vector elements are missing. This problem occurs in remote sensing when the ground is obscured by clouds. Optimal linear discrimination procedures for classifying imcomplete data vectors are discussed.

Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data*

PubMed Central

Cai, T. Tony; Zhang, Anru

2016-01-01

Missing data occur frequently in a wide range of applications. In this paper, we consider estimation of high-dimensional covariance matrices in the presence of missing observations under a general missing completely at random model in the sense that the missingness is not dependent on the values of the data. Based on incomplete data, estimators for bandable and sparse covariance matrices are proposed and their theoretical and numerical properties are investigated. Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity conditions. Simulation studies demonstrate that the estimators perform well numerically. The methods are also illustrated through an application to data from four ovarian cancer studies. The key technical tools developed in this paper are of independent interest and potentially useful for a range of related problems in high-dimensional statistical inference with missing data. PMID:27777471

Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data.

PubMed

Cai, T Tony; Zhang, Anru

2016-09-01

Missing data occur frequently in a wide range of applications. In this paper, we consider estimation of high-dimensional covariance matrices in the presence of missing observations under a general missing completely at random model in the sense that the missingness is not dependent on the values of the data. Based on incomplete data, estimators for bandable and sparse covariance matrices are proposed and their theoretical and numerical properties are investigated. Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity conditions. Simulation studies demonstrate that the estimators perform well numerically. The methods are also illustrated through an application to data from four ovarian cancer studies. The key technical tools developed in this paper are of independent interest and potentially useful for a range of related problems in high-dimensional statistical inference with missing data.

Getting patients in the door: medical appointment reminder preferences.

PubMed

Crutchfield, Trisha M; Kistler, Christine E

2017-01-01

Between 23% and 34% of outpatient appointments are missed annually. Patients who frequently miss medical appointments have poorer health outcomes and are less likely to use preventive health care services. Missed appointments result in unnecessary costs and organizational inefficiencies. Appointment reminders may help reduce missed appointments; particular types may be more effective than other types. We used a survey with a discrete choice experiment (DCE) to learn why individuals miss appointments and to assess appointment reminder preferences. We enrolled a national sample of adults from an online survey panel to complete demographic and appointment habit questions as well as a 16-task DCE designed in Sawtooth Software's Discover tool. We assessed preferences for four reminder attributes - initial reminder type, arrival of initial reminder, reminder content, and number of reminders. We derived utilities and importance scores. We surveyed 251 adults nationally, with a mean age of 43 (range 18-83) years: 51% female, 84% White, and 8% African American. Twenty-three percent of individuals missed one or more appointments in the past 12 months. Two primary reasons given for missing an appointment include transportation problems (28%) and forgetfulness (26%). Participants indicated the initial reminder type (21%) was the most important attribute, followed by the number of reminders (10%). Overall, individuals indicated a preference for a single reminder, arriving via email, phone call, or text message, delivered less than 2 weeks prior to an appointment. Preferences for reminder content were less clear. The number of missed appointments and reasons for missing appointments are consistent with prior research. Patient-centered appointment reminders may improve appointment attendance by addressing some of the reasons individuals report missing appointments and by meeting patients' needs. Future research is necessary to determine if preferred reminders used in practice will result in improved appointment attendance in clinical settings.

Informatively missing quality of life and unmet needs sex data for immigrant and Anglo-Australian cancer patients and survivors.

PubMed

Bell, Melanie L; Butow, Phyllis N; Goldstein, David

2013-12-01

Although cancer can seriously affect peoples' sexual well-being, survivors and patients may be reluctant to answer questions about sex. This reluctance may be stronger for immigrants. This study aimed to investigate missing sex data rates and predictors of missingness in two large studies on immigrants and Anglo-Australian controls with cancer and to investigate whether those with missing sex data may have worse sexual outcomes than those with complete data. We carried out two studies aimed at describing the quality of life (QoL) and unmet needs amongst Arabic, Chinese and Greek immigrants versus Anglo-Australians cancer survivors (n = 596, recruited from cancer registries) and patients (n = 845). Logistic regression was used to model the probability of having missing sex data in either of the questionnaires. We compared the mean of the unmet sex needs responses of those who had missing QoL sex data (but not needs) to those who had completed both, and vice versa. Missing sex data rates were as high as 65 %, with immigrants more likely to skip sex items than Anglo-Australians (p = 0.02 for registry study, p < 0.0001 for hospital study). Women, older participants and participants with more advanced disease had increased odds of missingness. There was evidence that data were informatively missing. Additionally, the questionnaire which stated that the sex questions are optional had higher missing data rates. High missing data rates and informatively missing data can lead to biased results. Using the questionnaires that state that they may skip sex items may lead to an underestimation of sexual problems or an overestimation of quality of life.

MISSE 6, 7 and 8 Materials Sample Experiments from the International Space Station Materials and Processes Team

NASA Technical Reports Server (NTRS)

Kravchenko, Michael; ORourke, Mary Jane; Golden, Johnny; Finckenor, Miria; Leatherwood, Michael; Alred, John

2010-01-01

The International Space Station Materials and Processes (ISS M&P) team has multiple material samples on MISSE 6, 7 and 8 to observe Low Earth Orbit (LEO) environmental effects on Space Station materials. Optical properties, thickness/mass loss, surface elemental analysis, visual and microscopic analysis for surface change are some of the techniques employed in this investigation. The ISS M&P team has participated in previous MISSE activities in order to better characterize the LEO effects on Space Station materials. This investigation will further this effort. Results for the following MISSE 6 samples materials will be presented: a comparison of anodize and chemical conversion coatings on various aluminum alloys, electroless nickel; AZ93 white ceramic thermal control coating with and without Teflon; Hyzod(TM) polycarbonate used to temporarily protect ISS windows; Russian quartz window material; reformulated Teflon (TM) coated Beta Cloth (Teflon TM without perfluorooctanoic acid (PFOA)) and a Dutch version of beta cloth. Discussion for current and future MISSE materials experiments will be presented. MISSE 7 samples are: deionized water sealed anodized aluminum Photofoil(TM); indium tin oxide (ITO)- coated Kapton(TM) used as thermo-optical surfaces; mechanically scribed tin-plated beryllium-copper samples for "tin pest" growth ( alpha/Beta transformation); Crew Exploration Vehicle (CEV) parachute soft goods. MISSE 8 sample: exposed "scrim cloth" (fiberglass weave) from the ISS solar array wing material, Davlyn fiberglass sleeve material, Permacel and Intertape protective tapes, and ITO-coated Kapton.

Identifying the missing proteins in human proteome by biological language model.

PubMed

Dong, Qiwen; Wang, Kai; Liu, Xuan

2016-12-23

With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins. Since there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the "uncertain" category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases. The analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.

Attrition Bias Related to Missing Outcome Data: A Longitudinal Simulation Study.

PubMed

Lewin, Antoine; Brondeel, Ruben; Benmarhnia, Tarik; Thomas, Frédérique; Chaix, Basile

2018-01-01

Most longitudinal studies do not address potential selection biases due to selective attrition. Using empirical data and simulating additional attrition, we investigated the effectiveness of common approaches to handle missing outcome data from attrition in the association between individual education level and change in body mass index (BMI). Using data from the two waves of the French RECORD Cohort Study (N = 7,172), we first examined how inverse probability weighting (IPW) and multiple imputation handled missing outcome data from attrition in the observed data (stage 1). Second, simulating additional missing data in BMI at follow-up under various missing-at-random scenarios, we quantified the impact of attrition and assessed how multiple imputation performed compared to complete case analysis and to a perfectly specified IPW model as a gold standard (stage 2). With the observed data in stage 1, we found an inverse association between individual education and change in BMI, with complete case analysis, as well as with IPW and multiple imputation. When we simulated additional attrition under a missing-at-random pattern (stage 2), the bias increased with the magnitude of selective attrition, and multiple imputation was useless to address it. Our simulations revealed that selective attrition in the outcome heavily biased the association of interest. The present article contributes to raising awareness that for missing outcome data, multiple imputation does not do better than complete case analysis. More effort is thus needed during the design phase to understand attrition mechanisms by collecting information on the reasons for dropout.

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach.

PubMed

Guruceaga, Elizabeth; Garin-Muga, Alba; Prieto, Gorka; Bejarano, Bartolomé; Marcilla, Miguel; Marín-Vicente, Consuelo; Perez-Riverol, Yasset; Casal, J Ignacio; Vizcaíno, Juan Antonio; Corrales, Fernando J; Segura, Victor

2017-12-01

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations.

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach

PubMed Central

2017-01-01

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations. PMID:28960077

An alternative empirical likelihood method in missing response problems and causal inference.

PubMed

Ren, Kaili; Drummond, Christopher A; Brewster, Pamela S; Haller, Steven T; Tian, Jiang; Cooper, Christopher J; Zhang, Biao

2016-11-30

Missing responses are common problems in medical, social, and economic studies. When responses are missing at random, a complete case data analysis may result in biases. A popular debias method is inverse probability weighting proposed by Horvitz and Thompson. To improve efficiency, Robins et al. proposed an augmented inverse probability weighting method. The augmented inverse probability weighting estimator has a double-robustness property and achieves the semiparametric efficiency lower bound when the regression model and propensity score model are both correctly specified. In this paper, we introduce an empirical likelihood-based estimator as an alternative to Qin and Zhang (2007). Our proposed estimator is also doubly robust and locally efficient. Simulation results show that the proposed estimator has better performance when the propensity score is correctly modeled. Moreover, the proposed method can be applied in the estimation of average treatment effect in observational causal inferences. Finally, we apply our method to an observational study of smoking, using data from the Cardiovascular Outcomes in Renal Atherosclerotic Lesions clinical trial. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

1.688 g/cm(3) satellite-related repeats: a missing link to dosage compensation and speciation.

PubMed

Gallach, Miguel

2015-09-01

Despite the important progress that has been made on dosage compensation (DC), a critical link in our understanding of the X chromosome recognition mechanisms is still missing. Recent studies in Drosophila indicate that the missing link could be a family of DNA repeats populating the euchromatin of the X chromosome. In this opinion article, I discuss how these findings add a new fresh twist on the DC problem. In the following sections, I first summarize our understanding of DC in Drosophila and integrate these recent discoveries into our knowledge of the X chromosome recognition problem. Next, I introduce a model according to which, 1.688 g/cm(3) satellite-related (SR) repeats would be the primary recognition elements for the dosage compensation complex. Contrary to the current belief, I suggest that the DC system in Drosophila is not conserved and static, but it is continuously co-evolving with the target SR repeats. The potential role of the SR repeats in hybrid incompatibilities and speciation is also discussed. © 2015 John Wiley & Sons Ltd.

[Health status, use of health services and reported morbidity: application of correspondence analysis].

PubMed

Espinàs, J A; Riba, M D; Borràs, J M; Sánchez, V

1995-01-01

The study of the relationship between self-reported morbidity, health status and health care utilization presents methodological problems due to the variety of illnesses and medical conditions that one individual may report. In this article, correspondence analysis was use to analyse these relationships. Data from the Spanish National Health Survey pertaining to the region of Catalonia was studied. Statistical analysis included multi-way correspondence analysis (MCA) followed by cluster analysis. The first factor extracted is defined by self-assessed health perception; the second, by limitation of activities, and the third is related to self-reported morbidity caused by chronic and acute health problems. Fourth and fifth factors, capture residual variability and missing values. Acute problems are more related to perception of poor health while chronic problems are related to perception of fair health. Also, it may be possible to distinguish self-reported morbidity due to relapses of chronic diseases from true acute health problems. Cluster analysis classified individuals into four groups: 1) healthy people; 2) people who assess their health as being poor and those with acute health problems; 3) people with chronic health problems, limited activity and a perception of fair health; and 4) missing values. Correspondence analysis is a useful tool when analyzing qualitative variables like those in a health survey.

Explicating the Conditions Under Which Multilevel Multiple Imputation Mitigates Bias Resulting from Random Coefficient-Dependent Missing Longitudinal Data.

PubMed

Gottfredson, Nisha C; Sterba, Sonya K; Jackson, Kristina M

2017-01-01

Random coefficient-dependent (RCD) missingness is a non-ignorable mechanism through which missing data can arise in longitudinal designs. RCD, for which we cannot test, is a problematic form of missingness that occurs if subject-specific random effects correlate with propensity for missingness or dropout. Particularly when covariate missingness is a problem, investigators typically handle missing longitudinal data by using single-level multiple imputation procedures implemented with long-format data, which ignores within-person dependency entirely, or implemented with wide-format (i.e., multivariate) data, which ignores some aspects of within-person dependency. When either of these standard approaches to handling missing longitudinal data is used, RCD missingness leads to parameter bias and incorrect inference. We explain why multilevel multiple imputation (MMI) should alleviate bias induced by a RCD missing data mechanism under conditions that contribute to stronger determinacy of random coefficients. We evaluate our hypothesis with a simulation study. Three design factors are considered: intraclass correlation (ICC; ranging from .25 to .75), number of waves (ranging from 4 to 8), and percent of missing data (ranging from 20 to 50%). We find that MMI greatly outperforms the single-level wide-format (multivariate) method for imputation under a RCD mechanism. For the MMI analyses, bias was most alleviated when the ICC is high, there were more waves of data, and when there was less missing data. Practical recommendations for handling longitudinal missing data are suggested.

Quantitative Analysis of the Contributing Factors Affecting Specialty Care No-Show Rates at Brooke Army Medical Center

DTIC Science & Technology

2007-03-30

2002). In the Vein Treatment Surgery Center in Texas, failure to properly cancel cosmetic appointments will result in forfeiture of the patients’ $100...appointments. This problem affects more than just the United States. Missed appointments cost the National Healthcare System ( NHS ) in England a...significant amount of money last year. Official figures from the NHS showed 5.7 million appointments were missed in 2004-2005 (Carvel, 2006). When patients

Neonatal screening for glutaric aciduria type I: strategies to proceed.

PubMed

Lindner, M; Ho, S; Fang-Hoffmann, J; Hoffmann, G F; Kölker, S

2006-01-01

Acute encephalopathic crisis in glutaric aciduria type I results in an unfavourable disease course and poor outcome, dominated by dystonia, feeding problems, seizures and reduced life expectancy. A conditio sine qua non for the prevention of irreversible brain damage is timely diagnosis and start of therapy, i.e. before the onset of neurological disease. As there are no specific clinical signs or symptoms that allow a reliable detection of these patients before the manifestation of encephalopathic crises, neonatal screening programmes for glutaric aciduria type I have been established in some countries using analysis of glutarylcarnitine in dried blood spots by tandem mass spectrometry. This article summarizes recent strategies, pitfalls and shortcomings of mass screening for glutaric aciduria type I, focusing on the relevant risk of missing patients with a mild biochemical phenotype (i.e. low excretors). Furthermore, it evaluates a binary strategy--using glutarylcarnitine as primary variable and glutarylcarnitine/acylcarnitine ratios as secondary variable--to improve the diagnostic sensitivity and specificity of neonatal screening for glutaric aciduria type I. An optimization of diagnostic as well as therapeutic procedures must be achieved before screening for glutaric aciduria type I can be regarded as reliable and beneficial for all patients.

Missing mass or missing light?

NASA Astrophysics Data System (ADS)

Davies, J. I.

1990-07-01

Disney et al. (1989) have argued that the observational data are consistent with disk galaxies being optically thick, particularly in their inner regions. Here, these results are used to reinterpret the radial surface-brightness distributions of spiral galaxies. It is found that the fitting of a profile with an absorbed disk plus bulge leads to both disk and bulge masses (mass in luminous material) that are larger than previously assumed. In addition, it is shown how the rotation velocity, as determined from optical data in the central regions, may systematically underestimate the true rotational velocity in an optically thick disk. If the bulges of late-type galaxies are as large as is hypothesized, then this has important implications in models of galaxy evolution and galaxy dynamics. The model greatly reduces or even eliminates the need for dark matter within the optical radius; it removes a major argument against S0 evolution from later-type galaxies; it accounts for the similarity of rotation curve forms among galaxies of different morphological types; and it leads to a further reappraisal of the observed constancy of the extrapolated central surface brightness of galactic disks.

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

DOE PAGES

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

2016-10-21

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

Factors Associated with Missed Vaccination during Mass Immunization Campaigns

PubMed Central

Winch, Peter J.; Burnham, Gilbert

2009-01-01

Achieving a high percentage of vaccination coverage with polio vaccine, while necessary, is not sufficient to eliminate or eradicate polio. The existence of pockets of under-vaccinated children has allowed outbreaks of polio in countries that have achieved high levels of vaccination coverage and in countries with no cases for many years. In a literature review, 35 articles were identified that described factors associated with missed vaccination in mass immunization campaigns. An annotated bibliography was developed for each article; these were then coded using the AnSWR program, and codes were organized into three larger thematic categories. These thematic areas were: (a) organization and implementation of mass campaigns; (b) population characteristics; and (c) knowledge and practices of caretakers. If these factors were geographically clustered, it was suspected that these clusters might have higher likelihood of becoming pockets of unvaccinated children. Immunization programme managers can target resources to identify if such clusters exist. If so, they can then ensure supervision of vaccination efforts in those sites and take further action, if indicated, to prevent or mitigate pockets of unvaccinated children. PMID:19507751

Anthropometric analysis of waist-to-hip ratio in Asian women.

PubMed

Hong, Young Jun; Park, Heung Sik; Lee, Eun Sang; Suh, Young Ju

2009-03-01

The universally accepted attractive female figure has a waist-to-hip ratio (WHR) of 0.7 or 0.68 (WHR of the Venus de Milo). Using WHR and other parameters, the authors attempted to investigate chronologic changes in perceptions of the attractive female figure in Korean society, differences between Asian and Western societies in this respect, and changes in attractiveness with respect to body mass index (BMI) and age in the general female Korean population. The authors analyzed the anthropometric measurements of 227 Miss Korea winners between 1971 and 2007, 60 candidates of the 2007 Miss Korea contest, 36 candidates of the 2007 Miss France contest, and 1785 normal women in the general population. In the Miss Korea winners' group, the WHR tended toward 0.7. The WHR of the 2007 Miss Korea candidates was statistically smaller than the WHR of the 2007 Miss France candidates. The WHR of normal women was statistically larger than WHR of the 2000s Miss Korea winners. In all age groups of normal women, subjects with a low BMI were not significantly different from the 2000s Miss Koreas in terms of waist circumference, but they had a relatively larger hip circumference. Moreover, subjects with a normal BMI had waist circumferences that were similar to those of the 2000s Miss Koreas but relatively larger hip circumferences, and subjects with high BMI had larger waist and hip circumferences than the 2000s Miss Koreas. The perceived attractive female figure in Asia has moved toward the universally accepted ideal WHR. However, there were still some differences between Asian and Western societies in the concept of ideal body figure. Also, a significant difference in body contour was observed between normal women and the ideal figure. This is because hip volume decreases and waist volume increases with age, although waist and hip volumes increase with BMI.

Sixteen years of ICPC use in Norwegian primary care: looking through the facts

PubMed Central

2010-01-01

Background The International Classification for Primary Care (ICPC) standard aims to facilitate simultaneous and longitudinal comparisons of clinical primary care practice within and across country borders; it is also used for administrative purposes. This study evaluates the use of the original ICPC-1 and the more complete ICPC-2 Norwegian versions in electronic patient records. Methods We performed a retrospective study of approximately 1.5 million ICPC codes and diagnoses that were collected over a 16-year period at 12 primary care sites in Norway. In the first phase of this period (transition phase, 1992-1999) physicians were allowed to not use an ICPC code in their practice while in the second phase (regular phase, 2000-2008) the use of an ICPC code was mandatory. The ICPC codes and diagnoses defined a problem event for each patient in the PROblem-oriented electronic MEDical record (PROMED). The main outcome measure of our analysis was the percentage of problem events in PROMEDs with inappropriate (or missing) ICPC codes and of diagnoses that did not map the latest ICPC-2 classification. Specific problem areas (pneumonia, anaemia, tonsillitis and diabetes) were examined in the same context. Results Codes were missing in 6.2% of the problem events; incorrect codes were observed in 4.0% of the problem events and text mismatch between the diagnoses and the expected ICPC-2 diagnoses text in 53.8% of the problem events. Missing codes were observed only during the transition phase while incorrect and inappropriate codes were used all over the 16-year period. The physicians created diagnoses that did not exist in ICPC. These 'new' diagnoses were used with varying frequency; many of them were used only once. Inappropriate ICPC-2 codes were also observed in the selected problem areas and for both phases. Conclusions Our results strongly suggest that physicians did not adhere to the ICPC standard due to its incompleteness, i.e. lack of many clinically important diagnoses. This indicates that ICPC is inappropriate for the classification of problem events and the clinical practice in primary care. PMID:20181271

Search for new phenomena in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum in pp collisions at $$ \\sqrt{s}=13 $$ TeV

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

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

Search results are presented for physics beyond the standard model in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 35.9 fb –1 of proton-proton collisions at √s = 13 TeV collected with the CMS detector at the LHC in 2016. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. The search for a kinematic edge targets production of particles sensitive to the strong force, while the resonance search targets both stronglymore » and electroweakly produced new physics. The observed yields are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry. In a gauge mediated supersymmetry breaking (GMSB) model of gluino pair production with decay chains including Z bosons, gluino masses up to 1500–1770 GeV are excluded at the 95% confidence level depending on the lightest neutralino mass. In a model of electroweak chargino-neutralino production, chargino masses as high as 610 GeV are excluded when the lightest neutralino is massless. In GMSB models of electroweak neutralino-neutralino production, neutralino masses up to 500-650 GeV are excluded depending on the decay mode assumed. Lastly, in a model with bottom squark pair production and decay chains resulting in a kinematic edge in the dilepton invariant mass distribution, bottom squark masses up to 980–1200 GeV are excluded depending on the mass of the next-to-lightest neutralino.« less

Search for new phenomena in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum in pp collisions at $$ \\sqrt{s}=13 $$ TeV

DOE PAGES

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

2018-03-13

Search results are presented for physics beyond the standard model in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 35.9 fb –1 of proton-proton collisions at √s = 13 TeV collected with the CMS detector at the LHC in 2016. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. The search for a kinematic edge targets production of particles sensitive to the strong force, while the resonance search targets both stronglymore » and electroweakly produced new physics. The observed yields are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry. In a gauge mediated supersymmetry breaking (GMSB) model of gluino pair production with decay chains including Z bosons, gluino masses up to 1500–1770 GeV are excluded at the 95% confidence level depending on the lightest neutralino mass. In a model of electroweak chargino-neutralino production, chargino masses as high as 610 GeV are excluded when the lightest neutralino is massless. In GMSB models of electroweak neutralino-neutralino production, neutralino masses up to 500-650 GeV are excluded depending on the decay mode assumed. Lastly, in a model with bottom squark pair production and decay chains resulting in a kinematic edge in the dilepton invariant mass distribution, bottom squark masses up to 980–1200 GeV are excluded depending on the mass of the next-to-lightest neutralino.« less

Search for new phenomena in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum in pp collisions at √{s}=13 TeV

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; 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.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; 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.; Ellithi Kamel, A.; Khalil, 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.; 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.; Rurua, L.; 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.; 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.; 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.; Karathanasis, G.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Kousouris, K.; Evangelou, I.; Foudas, C.; Kokkas, P.; Mallios, S.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Csanad, M.; Filipovic, N.; Pasztor, G.; Veres, G. I.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Bhawandeep, U.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhattacharya, S.; Chatterjee, S.; Das, P.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Pandey, S.; Rane, A.; Sharma, S.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Lezki, S.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. 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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.; 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.; 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.; 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.

2018-03-01

Search results are presented for physics beyond the standard model in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 35.9 fb-1 of proton-proton collisions at √{s}=13 TeV collected with the CMS detector at the LHC in 2016. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. The search for a kinematic edge targets production of particles sensitive to the strong force, while the resonance search targets both strongly and electroweakly produced new physics. The observed yields are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry. In a gauge mediated supersymmetry breaking (GMSB) model of gluino pair production with decay chains including Z bosons, gluino masses up to 1500-1770 GeV are excluded at the 95% confidence level depending on the lightest neutralino mass. In a model of electroweak chargino-neutralino production, chargino masses as high as 610 GeV are excluded when the lightest neutralino is massless. In GMSB models of electroweak neutralino-neutralino production, neutralino masses up to 500-650 GeV are excluded depending on the decay mode assumed. Finally, in a model with bottom squark pair production and decay chains resulting in a kinematic edge in the dilepton invariant mass distribution, bottom squark masses up to 980-1200 GeV are excluded depending on the mass of the next-to-lightest neutralino. [Figure not available: see fulltext.

Search for new phenomena in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum in pp collisions at $$ \\sqrt{s}=13 $$ TeV

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

Sirunyan, Albert M; et al.

2018-03-13

Search results are presented for physics beyond the standard model in final states with two opposite-charge, same-flavor leptons, jets, and missing transverse momentum. The data sample corresponds to an integrated luminosity of 35.9 fbmore » $$^{-1}$$ of proton-proton collisions at $$\\sqrt{s} = $$ 13 TeV collected with the CMS detector at the LHC in 2016. The analysis uses the invariant mass of the lepton pair, searching for a kinematic edge or a resonant-like excess compatible with the Z boson mass. The search for a kinematic edge targets production of particles sensitive to the strong force, while the resonance search targets both strongly and electroweakly produced new physics. The observed yields are consistent with the expectations from the standard model, and the results are interpreted in the context of simplified models of supersymmetry. In a gauge mediated supersymmetry breaking (GMSB) model of gluino pair production with decay chains including Z bosons, gluino masses up to 1500-1770 GeV are excluded at the 95% confidence level depending on the lightest neutralino mass. In a model of electroweak chargino-neutralino production, chargino masses as high as 610 GeV are excluded when the lightest neutralino is massless. In GMSB models of electroweak neutralino-neutralino production, neutralino masses up to 500-650 GeV are excluded depending on the decay mode assumed. Finally, in a model with bottom squark pair production and decay chains resulting in a kinematic edge in the dilepton invariant mass distribution, bottom squark masses up to 980-1200 GeV are excluded depending on the mass of the next-to-lightest neutralino.« less

MISS-Prot: web server for self/non-self discrimination of protein residue networks in parasites; theory and experiments in Fasciola peptides and Anisakis allergens.

PubMed

González-Díaz, Humberto; Muíño, Laura; Anadón, Ana M; Romaris, Fernanda; Prado-Prado, Francisco J; Munteanu, Cristian R; Dorado, Julián; Sierra, Alejandro Pazos; Mezo, Mercedes; González-Warleta, Marta; Gárate, Teresa; Ubeira, Florencio M

2011-06-01

Infections caused by human parasites (HPs) affect the poorest 500 million people worldwide but chemotherapy has become expensive, toxic, and/or less effective due to drug resistance. On the other hand, many 3D structures in Protein Data Bank (PDB) remain without function annotation. We need theoretical models to quickly predict biologically relevant Parasite Self Proteins (PSP), which are expressed differentially in a given parasite and are dissimilar to proteins expressed in other parasites and have a high probability to become new vaccines (unique sequence) or drug targets (unique 3D structure). We present herein a model for PSPs in eight different HPs (Ascaris, Entamoeba, Fasciola, Giardia, Leishmania, Plasmodium, Trypanosoma, and Toxoplasma) with 90% accuracy for 15 341 training and validation cases. The model combines protein residue networks, Markov Chain Models (MCM) and Artificial Neural Networks (ANN). The input parameters are the spectral moments of the Markov transition matrix for electrostatic interactions associated with the protein residue complex network calculated with the MARCH-INSIDE software. We implemented this model in a new web-server called MISS-Prot (MARCH-INSIDE Scores for Self-Proteins). MISS-Prot was programmed using PHP/HTML/Python and MARCH-INSIDE routines and is freely available at: . This server is easy to use by non-experts in Bioinformatics who can carry out automatic online upload and prediction with 3D structures deposited at PDB (mode 1). We can also study outcomes of Peptide Mass Fingerprinting (PMFs) and MS/MS for query proteins with unknown 3D structures (mode 2). We illustrated the use of MISS-Prot in experimental and/or theoretical studies of peptides from Fasciola hepatica cathepsin proteases or present on 10 Anisakis simplex allergens (Ani s 1 to Ani s 10). In doing so, we combined electrophoresis (1DE), MALDI-TOF Mass Spectroscopy, and MASCOT to seek sequences, Molecular Mechanics + Molecular Dynamics (MM/MD) to generate 3D structures and MISS-Prot to predict PSP scores. MISS-Prot also allows the prediction of PSP proteins in 16 additional species including parasite hosts, fungi pathogens, disease transmission vectors, and biotechnologically relevant organisms.

Reading Profiles in Multi-Site Data With Missingness.

PubMed

Eckert, Mark A; Vaden, Kenneth I; Gebregziabher, Mulugeta

2018-01-01

Children with reading disability exhibit varied deficits in reading and cognitive abilities that contribute to their reading comprehension problems. Some children exhibit primary deficits in phonological processing, while others can exhibit deficits in oral language and executive functions that affect comprehension. This behavioral heterogeneity is problematic when missing data prevent the characterization of different reading profiles, which often occurs in retrospective data sharing initiatives without coordinated data collection. Here we show that reading profiles can be reliably identified based on Random Forest classification of incomplete behavioral datasets, after the missForest method is used to multiply impute missing values. Results from simulation analyses showed that reading profiles could be accurately classified across degrees of missingness (e.g., ∼5% classification error for 30% missingness across the sample). The application of missForest to a real multi-site dataset with missingness ( n = 924) showed that reading disability profiles significantly and consistently differed in reading and cognitive abilities for cases with and without missing data. The results of validation analyses indicated that the reading profiles (cases with and without missing data) exhibited significant differences for an independent set of behavioral variables that were not used to classify reading profiles. Together, the results show how multiple imputation can be applied to the classification of cases with missing data and can increase the integrity of results from multi-site open access datasets.

Search for Dark Matter in Events with One Jet and Missing Transverse Energy in pp̄ Collisions at √s=1.96 TeV

DOE PAGES

Aaltonen, T.; Álvarez González, B.; Amerio, S.; ...

2012-05-23

We present the results of a search for dark matter production in the monojet signature. We analyze a sample of Tevatron pp̄ collisions at √s=1.96 TeV corresponding to an integrated luminosity of 6.7 fb⁻¹ recorded by the CDF II detector. In events with large missing transverse energy and one energetic jet, we find good agreement between the standard model prediction and the observed data. We set 90% confidence level upper limits on the dark matter production rate. The limits are translated into bounds on nucleon-dark matter scattering rates which are competitive with current direct detection bounds on spin-independent interaction belowmore » a dark matter candidate mass of 5 GeV/c², and on spin-dependent interactions up to masses of 200 GeV/c².« less

Search for dark matter in events with one jet and missing transverse energy in pp¯ collisions at √s=1.96 TeV.

PubMed

Aaltonen, T; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Auerbach, B; Aurisano, A; Azfar, F; Badgett, W; Bae, T; Bai, Y; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauce, M; Bedeschi, F; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Bisello, D; Bizjak, I; Bland, K R; Blumenfeld, B; Bocci, A; Bodek, A; Bortoletto, D; Boudreau, J; Boveia, A; Brigliadori, L; Bromberg, C; Brucken, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Calamba, A; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chung, W H; Chung, Y S; Ciocci, M A; Clark, A; Clarke, C; Compostella, G; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuevas, J; Culbertson, R; Dagenhart, D; d'Ascenzo, N; Datta, M; de Barbaro, P; Dell'Orso, M; Demortier, L; Deninno, M; Devoto, F; d'Errico, M; Di Canto, A; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, M; Dorigo, T; Ebina, K; Elagin, A; Eppig, A; Erbacher, R; Errede, S; Ershaidat, N; Eusebi, R; Farrington, S; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Forrest, R; Fox, P J; Frank, M J; Franklin, M; Freeman, J C; Funakoshi, Y; Furic, I; Gallinaro, M; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Grinstein, S; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Hahn, S R; Halkiadakis, E; Hamaguchi, A; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harnik, R; Harr, R F; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Hewamanage, S; Hocker, A; Hopkins, W; Horn, D; Hou, S; Hughes, R E; Hurwitz, M; Husemann, U; Hussain, N; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kim, Y J; Kimura, N; Kirby, M; Klimenko, S; Knoepfel, K; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Kruse, M; Krutelyov, V; Kuhr, T; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lecompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lin, C-J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, H; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maeshima, K; Maestro, P; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Martínez, M; Mastrandrea, P; Matera, K; Mattson, M E; Mazzacane, A; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Noh, S Y; Norniella, O; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Paramonov, A A; Patrick, J; Pauletta, G; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Prokoshin, F; Pranko, A; Ptohos, F; Punzi, G; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Rescigno, M; Riddick, T; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Safonov, A; Sakumoto, W K; Sakurai, Y; Santi, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Seidel, S; Seiya, Y; Semenov, A; Sforza, F; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shochet, M; Shreyber-Tecker, I; Simonenko, A; Sinervo, P; Sliwa, K; Smith, J R; Snider, F D; Soha, A; Sorin, V; Song, H; Squillacioti, P; Stancari, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Ukegawa, F; Uozumi, S; Varganov, A; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wagner, R L; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Wester, W C; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Wick, F; Williams, H H; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, H; Wright, T; Wu, X; Wu, Z; Yamamoto, K; Yamato, D; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zhou, C; Zucchelli, S

2012-05-25

We present the results of a search for dark matter production in the monojet signature. We analyze a sample of Tevatron pp[over ¯] collisions at √s=1.96 TeV corresponding to an integrated luminosity of 6.7 fb(-1) recorded by the CDF II detector. In events with large missing transverse energy and one energetic jet, we find good agreement between the standard model prediction and the observed data. We set 90% confidence level upper limits on the dark matter production rate. The limits are translated into bounds on nucleon-dark matter scattering rates which are competitive with current direct detection bounds on spin-independent interaction below a dark matter candidate mass of 5 GeV/c(2), and on spin-dependent interactions up to masses of 200 GeV/c(2).

Search for squarks and gluinos in events with an isolated lepton, jets, and missing transverse momentum at s = 13 TeV with the ATLAS detector

DOE PAGES

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

2017-12-26

Here, the results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a center-of-mass energy of √s=13 TeV are presented. The data set used was recorded during 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb –1. No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 TeV for gluino pairmore » production and up to 1.25 TeV for squark pair production.« less

Search for squarks and gluinos in events with an isolated lepton, jets, and missing transverse momentum at s = 13 TeV with the ATLAS detector

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

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

Here, the results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a center-of-mass energy of √s=13 TeV are presented. The data set used was recorded during 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb –1. No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 TeV for gluino pairmore » production and up to 1.25 TeV for squark pair production.« less

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.

PubMed

Van Gassen, Sofie; Callebaut, Britt; Van Helden, Mary J; Lambrecht, Bart N; Demeester, Piet; Dhaene, Tom; Saeys, Yvan

2015-07-01

The number of markers measured in both flow and mass cytometry keeps increasing steadily. Although this provides a wealth of information, it becomes infeasible to analyze these datasets manually. When using 2D scatter plots, the number of possible plots increases exponentially with the number of markers and therefore, relevant information that is present in the data might be missed. In this article, we introduce a new visualization technique, called FlowSOM, which analyzes Flow or mass cytometry data using a Self-Organizing Map. Using a two-level clustering and star charts, our algorithm helps to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise. R code is available at https://github.com/SofieVG/FlowSOM and will be made available at Bioconductor. © 2015 International Society for Advancement of Cytometry.

Streaming visualisation of quantitative mass spectrometry data based on a novel raw signal decomposition method

PubMed Central

Zhang, Yan; Bhamber, Ranjeet; Riba-Garcia, Isabel; Liao, Hanqing; Unwin, Richard D; Dowsey, Andrew W

2015-01-01

As data rates rise, there is a danger that informatics for high-throughput LC-MS becomes more opaque and inaccessible to practitioners. It is therefore critical that efficient visualisation tools are available to facilitate quality control, verification, validation, interpretation, and sharing of raw MS data and the results of MS analyses. Currently, MS data is stored as contiguous spectra. Recall of individual spectra is quick but panoramas, zooming and panning across whole datasets necessitates processing/memory overheads impractical for interactive use. Moreover, visualisation is challenging if significant quantification data is missing due to data-dependent acquisition of MS/MS spectra. In order to tackle these issues, we leverage our seaMass technique for novel signal decomposition. LC-MS data is modelled as a 2D surface through selection of a sparse set of weighted B-spline basis functions from an over-complete dictionary. By ordering and spatially partitioning the weights with an R-tree data model, efficient streaming visualisations are achieved. In this paper, we describe the core MS1 visualisation engine and overlay of MS/MS annotations. This enables the mass spectrometrist to quickly inspect whole runs for ionisation/chromatographic issues, MS/MS precursors for coverage problems, or putative biomarkers for interferences, for example. The open-source software is available from http://seamass.net/viz/. PMID:25663356

Controlling misses and false alarms in a machine learning framework for predicting uniformity of printed pages

NASA Astrophysics Data System (ADS)

Nguyen, Minh Q.; Allebach, Jan P.

2015-01-01

In our previous work1 , we presented a block-based technique to analyze printed page uniformity both visually and metrically. The features learned from the models were then employed in a Support Vector Machine (SVM) framework to classify the pages into one of the two categories of acceptable and unacceptable quality. In this paper, we introduce a set of tools for machine learning in the assessment of printed page uniformity. This work is primarily targeted to the printing industry, specifically the ubiquitous laser, electrophotographic printer. We use features that are well-correlated with the rankings of expert observers to develop a novel machine learning framework that allows one to achieve the minimum "false alarm" rate, subject to a chosen "miss" rate. Surprisingly, most of the research that has been conducted on machine learning does not consider this framework. During the process of developing a new product, test engineers will print hundreds of test pages, which can be scanned and then analyzed by an autonomous algorithm. Among these pages, most may be of acceptable quality. The objective is to find the ones that are not. These will provide critically important information to systems designers, regarding issues that need to be addressed in improving the printer design. A "miss" is defined to be a page that is not of acceptable quality to an expert observer that the prediction algorithm declares to be a "pass". Misses are a serious problem, since they represent problems that will not be seen by the systems designers. On the other hand, "false alarms" correspond to pages that an expert observer would declare to be of acceptable quality, but which are flagged by the prediction algorithm as "fails". In a typical printer testing and development scenario, such pages would be examined by an expert, and found to be of acceptable quality after all. "False alarm" pages result in extra pages to be examined by expert observers, which increases labor cost. But "false alarms" are not nearly as catastrophic as "misses", which represent potentially serious problems that are never seen by the systems developers. This scenario motivates us to develop a machine learning framework that will achieve the minimum "false alarm" rate subject to a specified "miss" rate. In order to construct such a set of receiver operating characteristic2 (ROC) curves, we examine various tools for the prediction, ranging from an exhaustive search over the space of the nonlinear discriminants to a Cost-Sentitive SVM3 framework. We then compare the curves gained from those methods. Our work shows promise for applying a standard framework to obtain a full ROC curve when it comes to tackling other machine learning problems in industry.

A Piezoelectrically Tuned RF-Cavity Search for Dark Matter Axions

NASA Astrophysics Data System (ADS)

Boutan, Christian

The Axion is a well motivated hypothetical elementary particle that must exist in nature if the strong CP problem of QCD is explained by the spontaneous breaking of a Peccei-Quinn symmetry. Not only would the discovery of the axion solve deep issues in QCD, an axion with a mass of mueV - meV could account for most or all of the missing mass in our galaxy and finally reveal the composition of dark matter. The Axion Dark Matter experiment (ADMX) seeks to resolve these two critical problems in physics by looking for the resonant conversion of dark-matter axions to microwave photons in a strong magnetic field. Utilizing state of the art electronics and dilution refrigerator cryogenics, ADMX is the world's leading haloscope search for axions - able to discover or rule out even the most pessimistically coupled QCD axions. With multi- TM0n0 functionality and with the commissioning of the new high-frequency Sidecar experiment, ADMX is also sensitive to a wide range of plausible axion masses. Here I motivate axions as ideal dark matter candidates, review techniques for detecting them and give a detailed description of the ADMX experiment. I discuss my contributions to the construction of the ADMX dual-channel receiver, which is the most sensitive microwave receiver on earth. I discuss the data acquisition, data taking and real-time analysis software. The primary focus of this work, however, is the ADMX Sidecar experiment which is a miniature axion haloscope that fits inside of the ADMX insert and has the capability of searching for axion masses between 16mueV - 24mueV on the TM0n0 and 26.4 - 30mueV on the TM 020. I discuss analysis of the Sidecar data and exclude axion-to-two-photon coupling gagammagamma < 6 x10 -12 GeV-1 over a mass range of 3mueV (Deltaƒ ˜708 MHz) from 21.05 - 23.98 mueV for axions that compose 100% of dark matter. Over a narrow subsection of this range, 22.89 - 22.95mueV (˜15 MHz) I set a stricter limit gagammagamma < 10-12 GeV-1.

Missing Oral Health-Related Data in the interRAI-HC - Associations with Selected Variables of General Health and the Effect of Multiple Imputation on the Relationship between Oral and General Health.

PubMed

Krausch-Hofmann, Stefanie; Bogaerts, Kris; Hofmann, Michael; de Almeida Mello, Johanna; Fávaro Moreira, Nádia Cristina; Lesaffre, Emmanuel; Declerck, Dominique; Declercq, Anja; Duyck, Joke

2015-01-01

Missing data within the comprehensive geriatric assessment of the interRAI suite of assessment instruments potentially imply the under-detection of conditions that require care as well as the risk of biased statistical results. Impaired oral health in older individuals has to be registered accurately as it causes pain and discomfort and is related to the general health status. This study was based on interRAI-Home Care (HC) baseline data from 7590 subjects (mean age 81.2 years, SD 6.9) in Belgium. It was investigated if missingness of the oral health-related items was associated with selected variables of general health. It was also determined if multiple imputation of missing data affected the associations between oral and general health. Multivariable logistic regression was used to determine if the prevalence of missingness in the oral health-related variables was associated with activities of daily life (ADLH), cognitive performance (CPS2) and depression (DRS). Associations between oral health and ADLH, CPS2 and DRS were determined, with missing data treated by 1. the complete-case technique and 2. by multiple imputation, and results were compared. The individual oral health-related variables had a similar proportion of missing values, ranging from 16.3% to 17.2%. The prevalence of missing data in all oral health-related variables was significantly associated with symptoms of depression (dental prosthesis use OR 1.66, CI 1.41-1.95; damaged teeth OR 1.74, CI 1.48-2.04; chewing problems OR 1.74, CI 1.47-2.05; dry mouth OR 1.65, CI 1.40-1.94). Missingness in damaged teeth (OR 1.27, CI 1.08-1.48), chewing problems (OR 1.22, CI 1.04-1.44) and dry mouth (OR 1.23, CI 1.05-1.44) occurred more frequently in cognitively impaired subjects. ADLH was not associated with the prevalence of missing data. When comparing the complete-case technique with the multiple imputation approach, nearly identical odds ratios characterized the associations between oral and general health. Cognitively impaired and depressive individuals had a higher risk of missing oral health-related information. Associations between oral health and ADLH, CPS2 and DRS were not influenced by multiple imputation of missing data. Further research should concentrate on the mechanisms that mediate the occurrence of missingness to develop preventative strategies.

Search for pair production of vector-like top quarks in events with one lepton, jets, and missing transverse momentum in √{s}=13 TeV pp collisions 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.; Verzini, M. J. Alconada; 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.; Gonzalez, B. Alvarez; Piqueras, D. Álvarez; Alviggi, M. G.; Amadio, B. T.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; 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.; Bella, L. Aperio; Arabidze, G.; Arai, Y.; Araque, J. P.; Ferraz, V. Araujo; 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.; Navarro, L. Barranco; Barreiro, F.; da Costa, J. Barreiro Guimarães; 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.; Noccioli, E. Benhar; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Kuutmann, E. Bergeaas; 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.; Bylund, O. Bessidskaia; 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.; Sola, J. D. Bossio; 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.; Madden, W. D. Breaden; 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.; de Renstrom, P. A. Bruckman; 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.; Urbán, S. Cabrera; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Lopez, S. Calvente; Calvet, D.; Calvet, S.; Calvet, T. P.; Toro, R. Camacho; Camarda, S.; Camarri, P.; Cameron, D.; Armadans, R. Caminal; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Bret, M. Cano; Cantero, J.; Cao, T.; Garrido, M. D. M. Capeans; 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.; Gimenez, V. Castillo; 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.; Alberich, L. Cerda; 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.; Barajas, C. A. Chavez; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; El Moursli, R. Cherkaoui; 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.; Muiño, P. Conde; 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.; Donszelmann, T. Cuhadar; 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.; Hoffmann, M. Dano; 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.; Pietra, M. Della; 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.; Cornell, S. Díez; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Pastor, O. Estrada; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Fabiani, V.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Giannelli, M. Faucci; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Martinez, P. Fernandez; Perez, S. Fernandez; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; de Lima, D. E. Ferreira; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Castillo, L. R. Flores; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Walls, F. M. Garay; García, C.; Navarro, J. E. García; Pascual, J. A. García; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Bravo, A. Gascon; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giangiacomi, N.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Gama, R. Goncalves; Da Costa, J. Goncalves Pinto Firmino; Gonella, G.; Gonella, L.; Gongadze, A.; de la Hoz, S. González; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. 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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.; Astigarraga, M. E. Pozo; 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.; Bosca, S. Rodriguez; Perez, A. Rodriguez; Rodriguez, D. Rodriguez; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Saez, S. M. Romano; Adam, E. Romero; 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.; Tehrani, F. Safai; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Loyola, J. E. Salazar; Salek, D.; De Bruin, P. H. Sales; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; Martinez, V. Sanchez; Pineda, A. Sanchez; 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.; Castillo, I. Santoyo; 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.; Saadi, D. Shoaleh; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Haddad, E. Sideras; 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.; Sanchez, C. A. Solans; 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.; Denis, R. D. St.; 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.; Araya, S. Tapia; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; 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.; Torres, R. E. Ticse; 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.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Santurio, E. Valdes; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Ferrer, J. A. Valls; 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.; Schroeder, T. Vazquez; 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.; Maira, N. Viaux; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Perez, M. Villaplana; 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.; Milosavljevic, M. Vranjes; 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.; 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.; Wong, K. H. Yau; 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.

2017-08-01

The results of a search for vector-like top quarks using events with exactly one lepton, at least four jets, and large missing transverse momentum are reported. The search is optimised for pair production of vector-like top quarks in the Z(→νν) t + X decay channel. LHC pp collision data at a centre-of-mass energy of √{s}=13 TeV recorded by the ATLAS detector in 2015 and 2016 are used, corresponding to an integrated luminosity of 36.1 fb-1. No significant excess over the Standard Model expectation is seen and upper limits on the production cross-section of a vector-like T quark pair as a function of the T quark mass are derived. The observed (expected) 95% CL lower limits on the T mass are 870 GeV (890 GeV) for the weak-isospin singlet model, 1.05 TeV (1.06 TeV) for the weak-isospin doublet model and 1.16 TeV (1.17 TeV) for the pure Zt decay mode. Limits are also set on the mass as a function of the decay branching ratios, excluding large parts of the parameter space for masses below 1 TeV. [Figure not available: see fulltext.

Search for pair production of vector-like top quarks in events with one lepton, jets, and missing transverse momentum in $$ \\sqrt{s}=13 $$ TeV pp collisions with the ATLAS detector

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

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

The results of a search for vector-like top quarks using events with exactly one lepton, at least four jets, and large missing transverse momentum are reported. The search is optimised for pair production of vector-like top quarks in the Z(→vv) t + X decay channel. LHC pp collision data at a centre-of-mass energy of √s=13 TeV recorded by the ATLAS detector in 2015 and 2016 are used, corresponding to an integrated luminosity of 36.1 fb -1 . No significant excess over the Standard Model expectation is seen and upper limits on the production cross-section of a vector-like T quark pairmore » as a function of the T quark mass are derived. The observed (expected) 95% CL lower limits on the T mass are 870 GeV (890 GeV) for the weak-isospin singlet model, 1.05 TeV (1.06 TeV) for the weak-isospin doublet model and 1.16 TeV (1.17 TeV) for the pure Zt decay mode. Limits are also set on the mass as a function of the decay branching ratios, excluding large parts of the parameter space for masses below 1 TeV.« less

Search for new phenomena in events containing a same-flavour opposite-sign dilepton pair, jets, and large missing transverse momentum in $${\\sqrt{s}=13}$$$\\text {TeV}$$ $${pp}$$ collisions with the ATLAS detector

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

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

Two searches for new phenomena in final states containing a same-flavour opposite-sign lepton (electron or muon) pair, jets, and large missing transverse momentum are presented. These searches make use of proton–proton collision data, collected during 2015 and 2016 at a centre-of-mass energy √s = 13 TeV by the ATLAS detector at the large hadron collider, which correspond to an integrated luminosity of 14.7 fb –1. Both searches target the pair production of supersymmetric particles, squarks or gluinos, which decay to final states containing a same-flavour opposite-sign lepton pair via one of two mechanisms: a leptonically decaying Z boson in themore » final state, leading to a peak in the dilepton invariant-mass distribution around the Z boson mass; and decays of neutralinos (e.g. χ ~0 2 → ℓ +ℓ –χ ~0 1), yielding a kinematic endpoint in the dilepton invariant-mass spectrum. The data are found to be consistent with the Standard Model expectation. Results are interpreted in simplified models of gluino-pair (squark-pair) production, and provide sensitivity to gluinos (squarks) with masses as large as 1.70 TeV (980 GeV).« less

Search for the direct production of charginos, neutralinos and staus in final states with at least two hadronically decaying taus and missing transverse momentum in pp collisions at $$ \\sqrt{s}=8 $$ TeV with the ATLAS detector

DOE PAGES

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

2014-10-16

We present results of a search for the electroweak associated production of charginos and next-to-lightest neutralinos, pairs of charginos or pairs of tau sleptons. These processes are characterised by final states with at least two hadronically decaying tau leptons, missing transverse momentum and low jet activity. The analysis is based on an integrated luminosity of 20.3 fb ₋1 of proton-proton collisions at √s = 8TeV recorded with the ATLAS experiment at the Large Hadron Collider. We observed no significant excess with respect to the predictions from Standard Model processes. Limits are set at 95% confidence level on the masses ofmore » the lighter chargino and next-to-lightest neutralino for various hypotheses for the lightest neutralino mass in simplified models. In the scenario of direct production of chargino pairs, with each chargino decaying into the lightest neutralino via an intermediate tau slepton, chargino masses up to 345 GeV are excluded for a massless lightest neutralino. For associated production of mass-degenerate charginos and next-tolightest neutralinos, both decaying into the lightest neutralino via an intermediate tau slepton, masses up to 410 GeV are excluded for a massless lightest neutralino.« less

XMM-NEWTON DETECTS A HOT GASEOUS HALO IN THE FASTEST ROTATING SPIRAL GALAXY UGC 12591

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

Dai Xinyu; Anderson, Michael E.; Bregman, Joel N.

2012-08-20

We present our XMM-Newton observation of the fastest rotating spiral galaxy UGC 12591. We detect hot gas halo emission out to 80 kpc from the galaxy center, and constrain the halo gas mass to be smaller than 4.5 Multiplication-Sign 10{sup 11} M{sub Sun }. We also measure the temperature of the hot gas as T = 0.64 {+-} 0.03 keV. Combining our x-ray constraints and the near-infrared and radio measurements in the literature, we find a baryon mass fraction of 0.03-0.05 in UGC 12591, suggesting a missing baryon mass of 70% compared with the cosmological mean value. Combined with anothermore » recent measurement in NGC 1961, the result strongly argues that the majority of missing baryons in spiral galaxies do not reside in their hot halos. We also find that UGC 12591 lies significantly below the baryonic Tully-Fisher relationship. Finally, we find that the baryon fractions of massive spiral galaxies are similar to those of galaxy groups with similar masses, indicating that the baryon loss is ultimately controlled by the gravitational potential well. The cooling radius of this gas halo is small, similar to NGC 1961, which argues that the majority of the stellar mass of this galaxy is not assembled as a result of cooling of this gas halo.« less

Search for pair production of vector-like top quarks in events with one lepton, jets, and missing transverse momentum in $$ \\sqrt{s}=13 $$ TeV pp collisions with the ATLAS detector

DOE PAGES

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

2017-08-16

The results of a search for vector-like top quarks using events with exactly one lepton, at least four jets, and large missing transverse momentum are reported. The search is optimised for pair production of vector-like top quarks in the Z(→vv) t + X decay channel. LHC pp collision data at a centre-of-mass energy of √s=13 TeV recorded by the ATLAS detector in 2015 and 2016 are used, corresponding to an integrated luminosity of 36.1 fb -1 . No significant excess over the Standard Model expectation is seen and upper limits on the production cross-section of a vector-like T quark pairmore » as a function of the T quark mass are derived. The observed (expected) 95% CL lower limits on the T mass are 870 GeV (890 GeV) for the weak-isospin singlet model, 1.05 TeV (1.06 TeV) for the weak-isospin doublet model and 1.16 TeV (1.17 TeV) for the pure Zt decay mode. Limits are also set on the mass as a function of the decay branching ratios, excluding large parts of the parameter space for masses below 1 TeV.« less

Search for new phenomena in events containing a same-flavour opposite-sign dilepton pair, jets, and large missing transverse momentum in $${\\sqrt{s}=13}$$$\\text {TeV}$$ $${pp}$$ collisions with the ATLAS detector

DOE PAGES

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

2017-03-04

Two searches for new phenomena in final states containing a same-flavour opposite-sign lepton (electron or muon) pair, jets, and large missing transverse momentum are presented. These searches make use of proton–proton collision data, collected during 2015 and 2016 at a centre-of-mass energy √s = 13 TeV by the ATLAS detector at the large hadron collider, which correspond to an integrated luminosity of 14.7 fb –1. Both searches target the pair production of supersymmetric particles, squarks or gluinos, which decay to final states containing a same-flavour opposite-sign lepton pair via one of two mechanisms: a leptonically decaying Z boson in themore » final state, leading to a peak in the dilepton invariant-mass distribution around the Z boson mass; and decays of neutralinos (e.g. χ ~0 2 → ℓ +ℓ –χ ~0 1), yielding a kinematic endpoint in the dilepton invariant-mass spectrum. The data are found to be consistent with the Standard Model expectation. Results are interpreted in simplified models of gluino-pair (squark-pair) production, and provide sensitivity to gluinos (squarks) with masses as large as 1.70 TeV (980 GeV).« less

Detection of Missing Proteins Using the PRIDE Database as a Source of Mass Spectrometry Evidence.

PubMed

Garin-Muga, Alba; Odriozola, Leticia; Martínez-Val, Ana; Del Toro, Noemí; Martínez, Rocío; Molina, Manuela; Cantero, Laura; Rivera, Rocío; Garrido, Nicolás; Dominguez, Francisco; Sanchez Del Pino, Manuel M; Vizcaíno, Juan Antonio; Corrales, Fernando J; Segura, Victor

2016-11-04

The current catalogue of the human proteome is not yet complete, as experimental proteomics evidence is still elusive for a group of proteins known as the missing proteins. The Human Proteome Project (HPP) has been successfully using technology and bioinformatic resources to improve the characterization of such challenging proteins. In this manuscript, we propose a pipeline starting with the mining of the PRIDE database to select a group of data sets potentially enriched in missing proteins that are subsequently analyzed for protein identification with a method based on the statistical analysis of proteotypic peptides. Spermatozoa and the HEK293 cell line were found to be a promising source of missing proteins and clearly merit further attention in future studies. After the analysis of the selected samples, we found 342 PSMs, suggesting the presence of 97 missing proteins in human spermatozoa or the HEK293 cell line, while only 36 missing proteins were potentially detected in the retina, frontal cortex, aorta thoracica, or placenta. The functional analysis of the missing proteins detected confirmed their tissue specificity, and the validation of a selected set of peptides using targeted proteomics (SRM/MRM assays) further supports the utility of the proposed pipeline. As illustrative examples, DNAH3 and TEPP in spermatozoa, and UNCX and ATAD3C in HEK293 cells were some of the more robust and remarkable identifications in this study. We provide evidence indicating the relevance to carefully analyze the ever-increasing MS/MS data available from PRIDE and other repositories as sources for missing proteins detection in specific biological matrices as revealed for HEK293 cells.

Detection of Missing Proteins Using the PRIDE Database as a Source of Mass Spectrometry Evidence

PubMed Central

2016-01-01

The current catalogue of the human proteome is not yet complete, as experimental proteomics evidence is still elusive for a group of proteins known as the missing proteins. The Human Proteome Project (HPP) has been successfully using technology and bioinformatic resources to improve the characterization of such challenging proteins. In this manuscript, we propose a pipeline starting with the mining of the PRIDE database to select a group of data sets potentially enriched in missing proteins that are subsequently analyzed for protein identification with a method based on the statistical analysis of proteotypic peptides. Spermatozoa and the HEK293 cell line were found to be a promising source of missing proteins and clearly merit further attention in future studies. After the analysis of the selected samples, we found 342 PSMs, suggesting the presence of 97 missing proteins in human spermatozoa or the HEK293 cell line, while only 36 missing proteins were potentially detected in the retina, frontal cortex, aorta thoracica, or placenta. The functional analysis of the missing proteins detected confirmed their tissue specificity, and the validation of a selected set of peptides using targeted proteomics (SRM/MRM assays) further supports the utility of the proposed pipeline. As illustrative examples, DNAH3 and TEPP in spermatozoa, and UNCX and ATAD3C in HEK293 cells were some of the more robust and remarkable identifications in this study. We provide evidence indicating the relevance to carefully analyze the ever-increasing MS/MS data available from PRIDE and other repositories as sources for missing proteins detection in specific biological matrices as revealed for HEK293 cells. PMID:27581094

Breast Cancer and Modifiable Lifestyle Factors in Argentinean Women: Addressing Missing Data in a Case-Control Study

PubMed Central

Coquet, Julia Becaria; Tumas, Natalia; Osella, Alberto Ruben; Tanzi, Matteo; Franco, Isabella; Diaz, Maria Del Pilar

2016-01-01

A number of studies have evidenced the effect of modifiable lifestyle factors such as diet, breastfeeding and nutritional status on breast cancer risk. However, none have addressed the missing data problem in nutritional epidemiologic research in South America. Missing data is a frequent problem in breast cancer studies and epidemiological settings in general. Estimates of effect obtained from these studies may be biased, if no appropriate method for handling missing data is applied. We performed Multiple Imputation for missing values on covariates in a breast cancer case-control study of Córdoba (Argentina) to optimize risk estimates. Data was obtained from a breast cancer case control study from 2008 to 2015 (318 cases, 526 controls). Complete case analysis and multiple imputation using chained equations were the methods applied to estimate the effects of a Traditional dietary pattern and other recognized factors associated with breast cancer. Physical activity and socioeconomic status were imputed. Logistic regression models were performed. When complete case analysis was performed only 31% of women were considered. Although a positive association of Traditional dietary pattern and breast cancer was observed from both approaches (complete case analysis OR=1.3, 95%CI=1.0-1.7; multiple imputation OR=1.4, 95%CI=1.2-1.7), effects of other covariates, like BMI and breastfeeding, were only identified when multiple imputation was considered. A Traditional dietary pattern, BMI and breastfeeding are associated with the occurrence of breast cancer in this Argentinean population when multiple imputation is appropriately performed. Multiple Imputation is suggested in Latin America’s epidemiologic studies to optimize effect estimates in the future. PMID:27892664

Harnessing data structure for recovery of randomly missing structural vibration responses time history: Sparse representation versus low-rank structure

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Nagarajaiah, Satish

2016-06-01

Randomly missing data of structural vibration responses time history often occurs in structural dynamics and health monitoring. For example, structural vibration responses are often corrupted by outliers or erroneous measurements due to sensor malfunction; in wireless sensing platforms, data loss during wireless communication is a common issue. Besides, to alleviate the wireless data sampling or communication burden, certain accounts of data are often discarded during sampling or before transmission. In these and other applications, recovery of the randomly missing structural vibration responses from the available, incomplete data, is essential for system identification and structural health monitoring; it is an ill-posed inverse problem, however. This paper explicitly harnesses the data structure itself-of the structural vibration responses-to address this (inverse) problem. What is relevant is an empirical, but often practically true, observation, that is, typically there are only few modes active in the structural vibration responses; hence a sparse representation (in frequency domain) of the single-channel data vector, or, a low-rank structure (by singular value decomposition) of the multi-channel data matrix. Exploiting such prior knowledge of data structure (intra-channel sparse or inter-channel low-rank), the new theories of ℓ1-minimization sparse recovery and nuclear-norm-minimization low-rank matrix completion enable recovery of the randomly missing or corrupted structural vibration response data. The performance of these two alternatives, in terms of recovery accuracy and computational time under different data missing rates, is investigated on a few structural vibration response data sets-the seismic responses of the super high-rise Canton Tower and the structural health monitoring accelerations of a real large-scale cable-stayed bridge. Encouraging results are obtained and the applicability and limitation of the presented methods are discussed.

Contribution of Equal-Sign Instruction beyond Word-Problem Tutoring for Third-Grade Students with Mathematics Difficulty

ERIC Educational Resources Information Center

Powell, Sarah R.; Fuchs, Lynn S.

2010-01-01

Elementary school students often misinterpret the equal sign (=) as an operational rather than a relational symbol. Such misunderstanding is problematic because solving equations with missing numbers may be important for the development of higher order mathematics skills, including solving word problems. Research indicates equal-sign instruction…

Language and Communication-Related Problems of Aviation Safety.

ERIC Educational Resources Information Center

Cushing, Steven

A study of the problems posed by the use of natural language in various aspects of aviation is presented. The study, part of a larger investigation of the feasibility of voice input/output interfaces for communication in aviation, looks at representative real examples of accidents and near misses resulting from language confusions and omissions.…

Addressing the Curriculum Problem in Doctoral Education

ERIC Educational Resources Information Center

Green, Bill

2012-01-01

How best to understand the curriculum problem in doctoral research education: that is the question that this paper engages. It begins by noting that curriculum as such is little referenced and inadequately theorised in higher education and certainly in doctoral education, and indeed has been described as a "missing term". The paper then…

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at s = 13 TeV

DOE PAGES

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

2017-01-27

Here, a search for supersymmetry is performed in events with a single electron or muon in proton-proton collisions at a center-of-mass energy of 13 TeV. The data were recorded by the CMS experiment at the LHC and correspond to an integrated luminosity of 2.3 fb –1. Several exclusive search regions are defined based on the number of jets and b-tagged jets, the scalar sum of the jet transverse momenta, and the scalar sum of the missing transverse momentum and the transverse momentum of the lepton. The observed event yields in data are consistent with the expected backgrounds from standard modelmore » processes. The results are interpreted using two simplified models of supersymmetric particle spectra, both of which describe gluino pair production. In the first model, each gluino decays via a three-body process to top quarks and a neutralino, which is associated with the observed missing transverse momentum in the event. Gluinos with masses up to 1.6 TeV are excluded for neutralino masses below 600 GeV. In the second model, each gluino decays via a three-body process to two light quarks and a chargino, which subsequently decays to a W boson and a neutralino. The mass of the chargino is taken to be midway between the gluino and neutralino masses. In this model, gluinos with masses below 1.4 TeV are excluded for neutralino masses below 700 GeV.« less

Persons with dementia missing in the community: is it wandering or something unique?

PubMed

Rowe, Meredeth A; Vandeveer, Sydney S; Greenblum, Catherine A; List, Cassandra N; Fernandez, Rachael M; Mixson, Natalie E; Ahn, Hyo C

2011-06-05

At some point in the disease process many persons with dementia (PWD) will have a missing incident and be unable to safely return to their care setting. In previous research studies, researchers have begun to question whether this phenomenon should continue to be called wandering since the antecedents and characteristics of a missing incident are dissimilar to accepted definitions of wandering in dementia. The purpose of this study was to confirm previous findings regarding the antecedents and characteristics of missing incidents, understand the differences between those found dead and alive, and compare the characteristics of a missing incident to that of wandering. A retrospective design was used to analyse 325 newspaper reports of PWD missing in the community. The primary antecedent to a missing incident, particularly in community-dwelling PWD, was becoming lost while conducting a normal and permitted activity alone in the community. The other common antecedent was a lapse in supervision with the expectation that the PWD would remain in a safe location but did not. Deaths most commonly occurred in unpopulated areas due to exposure and drowning. Those who died were found closer to the place last seen and took longer to find, but there were no significant differences in gender or age. The key characteristics of a missing incident were: unpredictable, non-repetitive, temporally appropriate but spatially-disordered, and while using multiple means of movement (walking, car, public transportation). Missing incidents occurred without the discernible pattern present in wandering such as lapping or pacing, repetitive and temporally-disordered. This research supports the mounting evidence that the concept of wandering, in its formal sense, and missing incidents are two distinct concepts. It will be important to further develop the concept of missing incidents by identifying the differences and similarities from wandering. This will allow a more targeted assessment and intervention strategy for each problem.

Persons with dementia missing in the community: Is it wandering or something unique?

PubMed Central

2011-01-01

Background At some point in the disease process many persons with dementia (PWD) will have a missing incident and be unable to safely return to their care setting. In previous research studies, researchers have begun to question whether this phenomenon should continue to be called wandering since the antecedents and characteristics of a missing incident are dissimilar to accepted definitions of wandering in dementia. The purpose of this study was to confirm previous findings regarding the antecedents and characteristics of missing incidents, understand the differences between those found dead and alive, and compare the characteristics of a missing incident to that of wandering. Methods A retrospective design was used to analyse 325 newspaper reports of PWD missing in the community. Results The primary antecedent to a missing incident, particularly in community-dwelling PWD, was becoming lost while conducting a normal and permitted activity alone in the community. The other common antecedent was a lapse in supervision with the expectation that the PWD would remain in a safe location but did not. Deaths most commonly occurred in unpopulated areas due to exposure and drowning. Those who died were found closer to the place last seen and took longer to find, but there were no significant differences in gender or age. The key characteristics of a missing incident were: unpredictable, non-repetitive, temporally appropriate but spatially-disordered, and while using multiple means of movement (walking, car, public transportation). Missing incidents occurred without the discernible pattern present in wandering such as lapping or pacing, repetitive and temporally-disordered. Conclusions This research supports the mounting evidence that the concept of wandering, in its formal sense, and missing incidents are two distinct concepts. It will be important to further develop the concept of missing incidents by identifying the differences and similarities from wandering. This will allow a more targeted assessment and intervention strategy for each problem. PMID:21639942

Developing a framework to review near-miss maternal morbidity in India: a structured review and key stakeholder analysis.

PubMed

Bhattacharyya, Sanghita; Srivastava, Aradhana; Knight, Marian

2014-11-13

In India there is a thrust towards promoting institutional delivery, resulting in problems of overcrowding and compromise to quality of care. Review of near-miss obstetric events has been suggested to be useful to investigate health system functioning, complementing maternal death reviews. The aim of this project was to identify the key elements required for a near-miss review programme for India. A structured review was conducted to identify methods used in assessing near-miss cases. The findings of the structured review were used to develop a suggested framework for conducting near-miss reviews in India. A pool of experts in near-miss review methods in low and middle income countries (LMICs) was identified for vetting the framework developed. Opinions were sought about the feasibility of implementing near-miss reviews in India, the processes to be followed, factors that made implementation successful and the associated challenges. A draft of the framework was revised based on the experts' opinions. Five broad methods of near-miss case review/audit were identified: Facility-based near-miss case review, confidential enquiries, criterion-based clinical audit, structured case review (South African Model) and home-based interviews. The opinion of the 11 stakeholders highlighted that the methods that a facility adopts should depend on the type and number of cases the facility handles, availability and maintenance of a good documentation system, and local leadership and commitment of staff. A proposed framework for conducting near-miss reviews was developed that included a combination of criterion-based clinical audit and near-miss review methods. The approach allowed for development of a framework for researchers and planners seeking to improve quality of maternal care not only at the facility level but also beyond, encompassing community health workers and referral. Further work is needed to evaluate the implementation of this framework to determine its efficacy in improving the quality of care and hence maternal and perinatal morbidity and mortality.

Design, implementation and reporting strategies to reduce the instance and impact of missing patient-reported outcome (PRO) data: a systematic review.

PubMed

Mercieca-Bebber, Rebecca; Palmer, Michael J; Brundage, Michael; Calvert, Melanie; Stockler, Martin R; King, Madeleine T

2016-06-15

Patient-reported outcomes (PROs) provide important information about the impact of treatment from the patients' perspective. However, missing PRO data may compromise the interpretability and value of the findings. We aimed to report: (1) a non-technical summary of problems caused by missing PRO data; and (2) a systematic review by collating strategies to: (A) minimise rates of missing PRO data, and (B) facilitate transparent interpretation and reporting of missing PRO data in clinical research. Our systematic review does not address statistical handling of missing PRO data. MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases (inception to 31 March 2015), and citing articles and reference lists from relevant sources. English articles providing recommendations for reducing missing PRO data rates, or strategies to facilitate transparent interpretation and reporting of missing PRO data were included. 2 reviewers independently screened articles against eligibility criteria. Discrepancies were resolved with the research team. Recommendations were extracted and coded according to framework synthesis. 117 sources (55% discussion papers, 26% original research) met the eligibility criteria. Design and methodological strategies for reducing rates of missing PRO data included: incorporating PRO-specific information into the protocol; carefully designing PRO assessment schedules and defining termination rules; minimising patient burden; appointing a PRO coordinator; PRO-specific training for staff; ensuring PRO studies are adequately resourced; and continuous quality assurance. Strategies for transparent interpretation and reporting of missing PRO data include utilising auxiliary data to inform analysis; transparently reporting baseline PRO scores, rates and reasons for missing data; and methods for handling missing PRO data. The instance of missing PRO data and its potential to bias clinical research can be minimised by implementing thoughtful design, rigorous methodology and transparent reporting strategies. All members of the research team have a responsibility in implementing such strategies. 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/

Searches for electroweak neutralino and chargino production in channels with Higgs, Z , and W bosons in p p collisions at 8 TeV

DOE PAGES

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

2014-11-21

Searches for supersymmetry (SUSY) are presented based on the electroweak pair production of neutralinos and charginos, leading to decay channels with Higgs, Z, and W bosons and undetected lightest SUSY particles (LSPs). The data sample corresponds to an integrated luminosity of about 19.5 fb -1 of proton-proton collisions at a center-of-mass energy of 8 TeV collected in 2012 with the CMS detector at the LHC. The main emphasis is neutralino pair production in which each neutralino decays either to a Higgs boson (h) and an LSP or to a Z boson and an LSP, leading to hh, hZ, and ZZ states with missing transverse energy (Emore » $$miss\\atop{T}$$). A second aspect is chargino-neutralino pair production, leading to hW states with E$$miss\\atop{T}$$. The decays of a Higgs boson to a bottom-quark pair, to a photon pair, and to final states with leptons are considered in conjunction with hadronic and leptonic decay modes of the Z and W bosons. As a result, no evidence is found for supersymmetric particles, and 95% confidence level upper limits are evaluated for the respective pair production cross sections and for neutralino and chargino mass values.« less

Search for new physics in events with opposite-sign leptons, jets, and missing transverse energy in pp collisions at √{ s} = 7 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.; Hammer, J.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Liko, D.; Mikulec, I.; Pernicka, M.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Wagner, P.; Waltenberger, W.; Walzel, G.; Widl, E.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Luyckx, S.; Maes, T.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Selvaggi, M.; Staykova, Z.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Gonzalez Suarez, R.; Kalogeropoulos, A.; Maes, M.; Olbrechts, A.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Charaf, O.; Clerbaux, B.; De Lentdecker, G.; Dero, V.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Reis, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Cimmino, A.; Costantini, S.; Garcia, G.; Grunewald, M.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Vanelderen, L.; Verwilligen, P.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Schul, N.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins Junior, M.; De Jesus Damiao, D.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá Júnior, W. L.; Carvalho, W.; Custódio, A.; Da Costa, E. M.; De Oliveira Martins, C.; Fonseca De Souza, S.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Oguri, V.; Prado Da Silva, W. L.; Santoro, A.; Soares Jorge, L.; Sznajder, A.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Marinho, F.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Tcholakov, V.; Trayanov, R.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Zang, J.; Zhang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, S.; Guo, Y.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Teng, H.; Wang, S.; Zhu, B.; Zou, W.; Avila, C.; Gomez, J. P.; Gomez Moreno, B.; Osorio Oliveros, A. F.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Plestina, R.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Duric, S.; Kadija, K.; Luetic, J.; Morovic, S.; Attikis, A.; Galanti, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Khalil, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Müntel, M.; Raidal, M.; Rebane, L.; Tiko, A.; Azzolini, V.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Heikkinen, A.; 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.; Ungaro, D.; Wendland, L.; Banzuzi, K.; Korpela, A.; Tuuva, T.; Besancon, M.; Choudhury, S.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Millischer, L.; Nayak, A.; Rander, J.; Rosowsky, A.; Shreyber, I.; Titov, M.; Baffioni, S.; Beaudette, F.; Benhabib, L.; Bianchini, L.; Bluj, M.; Broutin, C.; Busson, P.; Charlot, C.; Daci, N.; Dahms, T.; Dobrzynski, L.; Granier de Cassagnac, R.; Haguenauer, M.; Miné, P.; Mironov, C.; Ochando, C.; Paganini, P.; Sabes, D.; Salerno, R.; Sirois, Y.; Veelken, C.; Zabi, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Bodin, D.; Brom, J.-M.; Cardaci, M.; Chabert, E. C.; Collard, C.; Conte, E.; Drouhin, F.; Ferro, C.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Juillot, P.; Karim, M.; Le Bihan, A.-C.; Van Hove, P.; Fassi, F.; Mercier, D.; Beauceron, S.; Beaupere, N.; Bondu, O.; Boudoul, G.; Brun, H.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Sordini, V.; Tosi, S.; Tschudi, Y.; Verdier, P.; Viret, S.; Tsamalaidze, Z.; Anagnostou, G.; Beranek, S.; Edelhoff, M.; Feld, L.; Heracleous, N.; Hindrichs, O.; Jussen, R.; Klein, K.; Merz, J.; 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.; Kreuzer, P.; Lingemann, J.; Magass, C.; Merschmeyer, M.; Meyer, A.; Olschewski, M.; Papacz, P.; Pieta, H.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Steggemann, J.; Teyssier, D.; Weber, M.; Bontenackels, M.; Cherepanov, V.; Davids, M.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Linn, A.; Nowack, A.; Perchalla, L.; Pooth, O.; Rennefeld, J.; Sauerland, P.; Stahl, A.; Aldaya Martin, M.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Castro, E.; Costanza, F.; Dammann, D.; Eckerlin, G.; Eckstein, D.; Flucke, G.; Geiser, A.; Glushkov, I.; Gunnellini, P.; Habib, S.; Hauk, J.; Hellwig, G.; Jung, H.; Kasemann, M.; Katsas, P.; Kleinwort, C.; Kluge, H.; Knutsson, A.; Krämer, M.; Krücker, D.; Kuznetsova, E.; Lange, W.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Marienfeld, M.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Olzem, J.; Perrey, H.; Petrukhin, A.; Pitzl, D.; Raspereza, A.; Ribeiro Cipriano, P. M.; Riedl, C.; Rosin, M.; Salfeld-Nebgen, J.; Schmidt, R.; Schoerner-Sadenius, T.; Sen, N.; Spiridonov, A.; Stein, M.; Walsh, R.; Wissing, C.; Autermann, C.; Blobel, V.; Bobrovskyi, S.; Draeger, J.; Enderle, H.; Erfle, J.; Gebbert, U.; Görner, M.; Hermanns, T.; Höing, R. S.; Kaschube, K.; Kaussen, G.; Kirschenmann, H.; Klanner, R.; Lange, J.; Mura, B.; Nowak, F.; Peiffer, T.; Pietsch, N.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Schröder, M.; Schum, T.; Seidel, M.; Stadie, H.; Steinbrück, G.; Thomsen, J.; Barth, C.; Berger, J.; Böser, C.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Guthoff, M.; Hackstein, C.; Hartmann, F.; Hauth, T.; Heinrich, M.; Held, H.; Hoffmann, K. H.; Honc, S.; Katkov, I.; Komaragiri, J. R.; Martschei, D.; Mueller, S.; Müller, Th.; Niegel, M.; Nürnberg, A.; Oberst, O.; Oehler, A.; Ott, J.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Ratnikova, N.; Röcker, S.; Scheurer, A.; Schilling, F.-P.; Schott, G.; Simonis, H. J.; Stober, F. M.; Troendle, D.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Zeise, M.; Daskalakis, G.; Geralis, T.; Kesisoglou, S.; Kyriakis, A.; Loukas, D.; Manolakos, I.; Markou, A.; Markou, C.; Mavrommatis, C.; Ntomari, E.; Gouskos, L.; Mertzimekis, T. J.; Panagiotou, A.; Saoulidou, N.; Evangelou, I.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Patras, V.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Krajczar, K.; Radics, B.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Beni, N.; Czellar, S.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Karancsi, J.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Beri, S. B.; Bhatnagar, V.; Dhingra, N.; Gupta, R.; Jindal, M.; Kaur, M.; Kohli, J. M.; Mehta, M. Z.; Nishu, N.; Saini, L. 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G.; Barone, L.; Cavallari, F.; Del Re, D.; Diemoz, M.; Grassi, M.; Longo, E.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Sigamani, M.; Soffi, L.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Biino, C.; Botta, C.; Cartiglia, N.; Costa, M.; Demaria, N.; Graziano, A.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; Pastrone, N.; Pelliccioni, M.; Potenza, A.; Romero, A.; Ruspa, M.; Sacchi, R.; Sola, V.; Solano, A.; Staiano, A.; Vilela Pereira, A.; Belforte, S.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; Marone, M.; Montanino, D.; Penzo, A.; Schizzi, A.; Heo, S. G.; Kim, T. Y.; Nam, S. K.; Chang, S.; Chung, J.; Kim, D. H.; Kim, G. N.; Kong, D. J.; Park, H.; Ro, S. R.; Son, D. C.; Son, T.; Kim, J. Y.; Kim, Zero J.; Song, S.; Jo, H. Y.; Choi, S.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, T. J.; Lee, K. S.; Moon, D. H.; Park, S. K.; Seo, E.; Choi, M.; Kang, S.; Kim, H.; Kim, J. H.; Park, C.; Park, I. 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T.; Gaz, A.; Heyburn, B.; Luiggi Lopez, E.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Agostino, L.; Alexander, J.; Chatterjee, A.; Eggert, N.; Gibbons, L. K.; Heltsley, B.; 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.; Vaughan, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bloch, I.; Burkett, K.; Butler, J. N.; Chetluru, V.; Cheung, H. W. K.; Chlebana, F.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Green, D.; Gutsche, O.; Hahn, A.; Hanlon, J.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kilminster, B.; Klima, B.; Kunori, S.; Kwan, S.; Leonidopoulos, C.; Lincoln, D.; Lipton, R.; Lueking, L.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Spalding, W. J.; Spiegel, L.; Tan, P.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; 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.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Dobur, D.; Drozdetskiy, A.; Field, R. D.; Fisher, M.; Fu, Y.; Furic, I. K.; Gartner, J.; Hugon, J.; Kim, B.; Konigsberg, J.; Korytov, A.; Kropivnitskaya, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Remington, R.; Rinkevicius, A.; Sellers, P.; Skhirtladze, N.; Snowball, M.; Yelton, J.; Zakaria, M.; Gaultney, V.; Lebolo, L. M.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, J. R.; Adams, T.; Askew, A.; Bochenek, J.; Chen, J.; Diamond, B.; Gleyzer, S. V.; Haas, J.; Hagopian, S.; Hagopian, V.; Jenkins, M.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Dorney, B.; Hohlmann, M.; Kalakhety, H.; Vodopiyanov, I.; Adams, M. R.; Anghel, I. M.; Apanasevich, L.; Bai, Y.; Bazterra, V. E.; Betts, R. R.; Bucinskaite, I.; Callner, J.; Cavanaugh, R.; Dragoiu, C.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hamdan, S.; Hofman, D. J.; Khalatyan, S.; Lacroix, F.; Malek, M.; O'Brien, C.; Silkworth, C.; Strom, D.; Varelas, N.; Akgun, U.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Duru, F.; Griffiths, S.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Newsom, C. R.; Norbeck, E.; Onel, Y.; Ozok, F.; Sen, S.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Giurgiu, G.; Gritsan, A. V.; Guo, Z. J.; Hu, G.; Maksimovic, P.; Rappoccio, S.; Swartz, M.; Whitbeck, A.; Baringer, P.; Bean, A.; Benelli, G.; Grachov, O.; Kenny, R. P., Iii; Murray, M.; Noonan, D.; Sanders, S.; Stringer, R.; Tinti, G.; Wood, J. S.; Zhukova, V.; Barfuss, A. F.; Bolton, T.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Shrestha, S.; Svintradze, I.; Gronberg, J.; Lange, D.; Wright, D.; Baden, A.; Boutemeur, M.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kirn, M.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Peterman, A.; Skuja, A.; Temple, J.; Tonjes, M. B.; Tonwar, S. C.; Twedt, E.; Bauer, G.; Bendavid, J.; Busza, W.; Butz, E.; Cali, I. A.; Chan, M.; Dutta, V.; Gomez Ceballos, G.; Goncharov, M.; Hahn, K. A.; Kim, Y.; Klute, M.; Li, W.; 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.; Velicanu, D.; Wenger, E. A.; Wolf, R.; Wyslouch, B.; Xie, S.; Yang, M.; Yilmaz, Y.; Yoon, A. S.; Zanetti, M.; Cooper, S. I.; Cushman, P.; Dahmes, B.; De Benedetti, A.; Franzoni, G.; Gude, A.; Haupt, J.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Sasseville, M.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Cremaldi, L. M.; Kroeger, R.; Perera, L.; Rahmat, R.; Sanders, D. A.; Avdeeva, E.; Bloom, K.; Bose, S.; Butt, J.; Claes, D. R.; Dominguez, A.; Eads, M.; Jindal, P.; Keller, J.; 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.; Chasco, M.; Haley, J.; Nash, D.; Trocino, D.; Wood, D.; Zhang, J.; Anastassov, A.; Kubik, A.; Mucia, N.; Odell, N.; Ofierzynski, R. A.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Velasco, M.; Won, S.; Antonelli, L.; Berry, D.; Brinkerhoff, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kolb, J.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Morse, D. M.; Pearson, T.; Ruchti, R.; Slaunwhite, J.; Valls, N.; Wayne, M.; Wolf, M.; Bylsma, B.; Durkin, L. S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Vuosalo, C.; Williams, G.; Winer, B. L.; Adam, N.; Berry, E.; Elmer, P.; Gerbaudo, D.; Halyo, V.; Hebda, P.; Hegeman, J.; Hunt, A.; Laird, E.; Lopes Pegna, D.; 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.; Zuranski, A.; Acosta, J. G.; Brownson, E.; Huang, X. T.; Lopez, A.; Mendez, H.; Oliveros, S.; Ramirez Vargas, J. E.; Zatserklyaniy, A.; Alagoz, E.; Barnes, V. E.; Benedetti, D.; Bolla, G.; Bortoletto, D.; De Mattia, M.; Everett, A.; Hu, Z.; Jones, M.; Koybasi, O.; Kress, M.; Laasanen, A. T.; Leonardo, N.; Maroussov, V.; Merkel, P.; Miller, D. H.; Neumeister, N.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Vidal Marono, M.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Guragain, S.; Parashar, N.; Adair, A.; 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.; Garcia-Bellido, A.; Goldenzweig, P.; Gotra, Y.; Han, J.; Harel, A.; Korjenevski, S.; Miner, D. C.; 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.; Richards, A.; Robles, J.; Rose, K.; Salur, S.; Schnetzer, S.; Seitz, C.; Somalwar, S.; Stone, R.; Thomas, S.; Cerizza, G.; Hollingsworth, M.; Spanier, S.; Yang, Z. C.; York, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Safonov, A.; Sakuma, T.; Sengupta, S.; Suarez, I.; Tatarinov, A.; Toback, D.; Akchurin, N.; Damgov, J.; Dudero, P. R.; Jeong, C.; Kovitanggoon, K.; Lee, S. W.; Libeiro, T.; Roh, Y.; Volobouev, I.; Appelt, E.; Engh, D.; Florez, C.; Greene, S.; Gurrola, A.; Johns, W.; Johnston, C.; 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.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Lin, C.; Neu, C.; Wood, J.; Yohay, R.; Gollapinni, S.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sakharov, A.; Anderson, M.; Bachtis, M.; Belknap, D.; Borrello, L.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Gray, L.; Grogg, K. S.; Grothe, M.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Klukas, J.; Lanaro, A.; Lazaridis, C.; Leonard, J.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Pierro, G. A.; Ross, I.; Savin, A.; Smith, W. H.; Swanson, J.; CMS Collaboration

2013-01-01

A search is presented for physics beyond the standard model (BSM) in final states with a pair of opposite-sign isolated leptons accompanied by jets and missing transverse energy. The search uses LHC data recorded at a center-of-mass energy √{ s} = 7 TeV with the CMS detector, corresponding to an integrated luminosity of approximately 5 fb-1. Two complementary search strategies are employed. The first probes models with a specific dilepton production mechanism that leads to a characteristic kinematic edge in the dilepton mass distribution. The second strategy probes models of dilepton production with heavy, colored objects that decay to final states including invisible particles, leading to very large hadronic activity and missing transverse energy. No evidence for an event yield in excess of the standard model expectations is found. Upper limits on the BSM contributions to the signal regions are deduced from the results, which are used to exclude a region of the parameter space of the constrained minimal supersymmetric extension of the standard model. Additional information related to detector efficiencies and response is provided to allow testing specific models of BSM physics not considered in this Letter.

Search for Dark Matter in Events with Missing Transverse Momentum and a Higgs Boson Decaying to Two Photons in pp Collisions at s√=8 TeV with the ATLAS Detector

DOE PAGES

Aad, G.

2015-09-22

Results of a search for new phenomena in events with large missing transverse momentum and a Higgs boson decaying to two photons are reported. Data from proton-proton collisions at a center-of-mass energy of 8 TeV and corresponding to an integrated luminosity of 20.3 fb -1 have been collected with the ATLAS detector at the LHC. The observed data are well described by the expected standard model backgrounds. Upper limits on the cross section of events with large missing transverse momentum and a Higgs boson candidate are also placed. Exclusion limits are presented for models of physics beyond the standard modelmore » featuring dark-matter candidates.« less

A hybrid frame concealment algorithm for H.264/AVC.

PubMed

Yan, Bo; Gharavi, Hamid

2010-01-01

In packet-based video transmissions, packets loss due to channel errors may result in the loss of the whole video frame. Recently, many error concealment algorithms have been proposed in order to combat channel errors; however, most of the existing algorithms can only deal with the loss of macroblocks and are not able to conceal the whole missing frame. In order to resolve this problem, in this paper, we have proposed a new hybrid motion vector extrapolation (HMVE) algorithm to recover the whole missing frame, and it is able to provide more accurate estimation for the motion vectors of the missing frame than other conventional methods. Simulation results show that it is highly effective and significantly outperforms other existing frame recovery methods.

Are Expectations the Missing Link between Life History Strategies and Psychopathology?

PubMed

Kavanagh, Phillip S; Kahl, Bianca L

2018-01-01

Despite advances in knowledge and thinking about using life history theory to explain psychopathology there is still a missing link. That is, we all have a life history strategy, but not all of us develop mental health problems. We propose that the missing link is expectations - a mismatch between expected environmental conditions (including social) set by variations in life history strategies and the current environmental conditions. The mismatch hypothesis has been applied at the biological level in terms of health and disease and we believe that it can also be applied more broadly at the psychological level in terms of perceived expectations in the social environment and the resulting distress-psychopathology-that manifests when our expectations are not met.

Deuterium Abundance in Consciousness and Current Cosmology

NASA Astrophysics Data System (ADS)

Rauscher, Elizabeth A.

We utilize the deuterium-hydrogen abundances and their role in setting limits on the mass and other conditions of cosmogenesis and cosmological evolution. We calculate the dependence of a set of physical variables such as density, temperature, energy mass, entropy and other physical variable parameters through the evolution of the universe under the Schwarzschild conditions as a function from early to present time. Reconciliation with the 3°K and missing mass is made. We first examine the Schwarzschild condition; second, the geometrical constraints of a multidimensional Cartesian space on closed cosmologies, and third we will consider the cosmogenesis and evolution of the universe in a multidimensional Cartesian space, obeying the Schwarzschild condition. Implications of this model for matter creation are made. We also examine experimental evidence for closed versus open cosmologies; x-ray detection of the "missing mass" density. Also the interstellar deuterium abundance, along with the value of the Hubble constant set a general criterion on the value of the curvature constant, k. Once the value of the Hubble constant, H is determined, the deuterium abundance sets stringent restrictions on the value of the curvature constant k by an detailed discussion is presented. The experimental evidences for the determination of H and the primary set of coupled equations to determine D abundance is given. 'The value of k for an open, closed, or flat universe will be discussed in terms of the D abundance which will affect the interpretation of the Schwarzschild, black hole universe. We determine cosmology solutions to Einstein's field obeying the Schwarzschild solutions condition. With this model, we can form a reconciliation of the black hole, from galactic to cosmological scale. Continuous creation occurs at the dynamic blackhole plasma field. We term this new model the multiple big bang or "little whimper model". We utilize the deuteriumhydrogen abundances and their role in setting limits on the mass and other conditions of cosmogenesis and cosmological evolution. We calculate the dependence of a set of physical variables such as density, temperature, energy mass, entropy and other physical variable parameters through the evolution of the universe under the Schwarzschild conditions as a function from early to present time. Reconciliation with the 3°K background and missing mass is made.

On shock driven jetting of liquid from non-sinusoidal surfaces into a vacuum

DOE PAGES

Cherne, F. J.; Hammerberg, J. E.; Andrews, M. J.; ...

2015-11-09

Other work employed Richtmyer-Meshkov theory to describe the development of spikes and bubblesfrom shocked sinusoidal surfaces. Here, we discuss the effects of machining different two-dimensional shaped grooves in copper and examine the resulting flow of the material after being shocked into liquid on release. For these simulations, a high performance molecular dynamics code, SPaSM, was used with machined grooves of kh 0 = 1 and kh 0 = 1/8, where 2h 0 is the peak-to-valley height of the perturbation with wavelength λ, and k = 2π/λ. The surface morphologies studied include a Chevron, a Fly-Cut, a Square-Wave, and a Gaussian.more » Furthermore, we describe extensions to an existing ejecta source model that better captures the mass ejected from these surfaces. We also investigate the same profiles at length scales of order 1 cm for an idealized fluid equation of state using the FLASH continuum hydrodynamics code. Our findings indicate that the resulting mass can be scaled by the missing area of a sinusoidal curve with an effective wavelength, λeff , that has the same missing area. Finally, our extended ejecta mass formula works well for all the shapes considered and captures the corresponding time evolution and total mass.« less

Search for pair production of gluinos decaying via stop and sbottom in events with b -jets and large missing transverse momentum in p p collisions at s = 13 TeV with the ATLAS detector

DOE PAGES

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

2016-08-09

A search for supersymmetry involving the pair production of gluinos decaying via third-generation squarks to the lightest neutralino (χ˜ 0 1) is reported. It uses an LHC proton-proton data set at a center-of-mass energy √s = 13 TeV with an integrated luminosity of 3.2 fb –1 collected with the ATLAS detector in 2015. The signal is searched for in events containing several energetic jets, of which at least three must be identified as b jets, large missing transverse momentum, and, potentially, isolated electrons or muons. Large-radius jets with a high mass are also used to identify highly boosted top quarks.more » No excess is found above the predicted background. For χ˜ 0 1 masses below approximately 700 GeV, gluino masses of less than 1.78 TeV and 1.76 TeV are excluded at the 95% C.L. in simplified models of the pair production of gluinos decaying via sbottom and stop, respectively. Furthermore, these results significantly extend the exclusion limits obtained with the √s = 8 TeV data set.« less

Search for a scalar partner of the top quark in the jets plus missing transverse momentum final state at $$ \\sqrt{s}=13 $$ TeV with the ATLAS detector

DOE PAGES

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

2017-12-15

Here, a search for pair production of a scalar partner of the top quark in events with four or more jets plus missing transverse momentum is presented. An analysis of 36.1 fb –1 of √s=13 TeV proton-proton collisions collected using the ATLAS detector at the LHC yields no significant excess over the expected Standard Model background. To interpret the results a simplified supersymmetric model is used where the top squark is assumed to decay via t ~ 1→t (*)χ ~0 1 and t ~ 1→bχ ~ ± 1→bW (*)χ ~0 1, where χ 1 0 (χ 1 ± ) denotesmore » the lightest neutralino (chargino). Exclusion limits are placed in terms of the top-squark and neutralino masses. Assuming a branching ratio of 100% to tχ ~0 1, top-squark masses in the range 450–1000 GeV are excluded for χ ~0 1 masses below 160 GeV. In the case where m y-1 ~ m t+m -0χ1, top-squark masses in the range 235–590 GeV are excluded.« less

Search for a scalar partner of the top quark in the jets plus missing transverse momentum final state at √{s}=13 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S. C.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. 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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.; 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.

2017-12-01

A search for pair production of a scalar partner of the top quark in events with four or more jets plus missing transverse momentum is presented. An analysis of 36.1 fb-1 of √{s}=13 TeV proton-proton collisions collected using the ATLAS detector at the LHC yields no significant excess over the expected Standard Model background. To interpret the results a simplified supersymmetric model is used where the top squark is assumed to decay via {\\tilde{t}}_1\\to {t}^{(\\ast )}{\\tilde{\\upchi}}_1^0 and {\\tilde{t}}_1\\to b{\\tilde{\\upchi}}_1^{±}\\to b{W}^{(\\ast )}{\\tilde{\\upchi}}_1^0 , where χ 1 0 (χ 1 ± ) denotes the lightest neutralino (chargino). Exclusion limits are placed in terms of the top-squark and neutralino masses. Assuming a branching ratio of 100% to t{\\tilde{\\upchi}}_1^0 , top-squark masses in the range 450-1000 GeV are excluded for {\\tilde{\\upchi}}_1^0 masses below 160 GeV. In the case where {m}_{{\\tilde{t}}_1}˜ {m}_t+{m}_{{\\tilde{χ}}_1^0} , top-squark masses in the range 235-590 GeV are excluded.

Search for a scalar partner of the top quark in the jets plus missing transverse momentum final state at $$ \\sqrt{s}=13 $$ TeV with the ATLAS detector

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

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

Here, a search for pair production of a scalar partner of the top quark in events with four or more jets plus missing transverse momentum is presented. An analysis of 36.1 fb –1 of √s=13 TeV proton-proton collisions collected using the ATLAS detector at the LHC yields no significant excess over the expected Standard Model background. To interpret the results a simplified supersymmetric model is used where the top squark is assumed to decay via t ~ 1→t (*)χ ~0 1 and t ~ 1→bχ ~ ± 1→bW (*)χ ~0 1, where χ 1 0 (χ 1 ± ) denotesmore » the lightest neutralino (chargino). Exclusion limits are placed in terms of the top-squark and neutralino masses. Assuming a branching ratio of 100% to tχ ~0 1, top-squark masses in the range 450–1000 GeV are excluded for χ ~0 1 masses below 160 GeV. In the case where m y-1 ~ m t+m -0χ1, top-squark masses in the range 235–590 GeV are excluded.« less

Search for supersymmetry in events containing a same-flavour opposite-sign dilepton pair, jets, and large missing transverse momentum in √s = 8  TeV pp collisions with the ATLAS detector

DOE PAGES

Aad, G.

2015-07-08

Two searches for supersymmetric particles in final states containing a same-flavour opposite-sign lepton pair, jets and large missing transverse momentum are presented. The proton–proton collision data used in these searches were collected at a centre-of-mass energy √s=8 TeV by the ATLAS detector at the Large Hadron Collider and corresponds to an integrated luminosity of 20.3 fb -1. Two leptonic production mechanisms are considered: decays of squarks and gluinos with Z bosons in the final state, resulting in a peak in the dilepton invariant mass distribution around the Z-boson mass; and decays of neutralinos (e.g. χ ~0 2→ℓ +ℓ -χ ~0more » 1), resulting in a kinematic endpoint in the dilepton invariant mass distribution. For the former, an excess of events above the expected Standard Model background is observed, with a significance of three standard deviations. In the latter case, the data are well-described by the expected Standard Model background. Results from each channel are interpreted in the context of several supersymmetric models involving the production of squarks and gluinos.« less

Selection-Fusion Approach for Classification of Datasets with Missing Values

PubMed Central

Ghannad-Rezaie, Mostafa; Soltanian-Zadeh, Hamid; Ying, Hao; Dong, Ming

2010-01-01

This paper proposes a new approach based on missing value pattern discovery for classifying incomplete data. This approach is particularly designed for classification of datasets with a small number of samples and a high percentage of missing values where available missing value treatment approaches do not usually work well. Based on the pattern of the missing values, the proposed approach finds subsets of samples for which most of the features are available and trains a classifier for each subset. Then, it combines the outputs of the classifiers. Subset selection is translated into a clustering problem, allowing derivation of a mathematical framework for it. A trade off is established between the computational complexity (number of subsets) and the accuracy of the overall classifier. To deal with this trade off, a numerical criterion is proposed for the prediction of the overall performance. The proposed method is applied to seven datasets from the popular University of California, Irvine data mining archive and an epilepsy dataset from Henry Ford Hospital, Detroit, Michigan (total of eight datasets). Experimental results show that classification accuracy of the proposed method is superior to those of the widely used multiple imputations method and four other methods. They also show that the level of superiority depends on the pattern and percentage of missing values. PMID:20212921

Handling missing Mini-Mental State Examination (MMSE) values: Results from a cross-sectional long-term-care study.

PubMed

Godin, Judith; Keefe, Janice; Andrew, Melissa K

2017-04-01

Missing values are commonly encountered on the Mini Mental State Examination (MMSE), particularly when administered to frail older people. This presents challenges for MMSE scoring in research settings. We sought to describe missingness in MMSEs administered in long-term-care facilities (LTCF) and to compare and contrast approaches to dealing with missing items. As part of the Care and Construction project in Nova Scotia, Canada, LTCF residents completed an MMSE. Different methods of dealing with missing values (e.g., use of raw scores, raw scores/number of items attempted, scale-level multiple imputation [MI], and blended approaches) are compared to item-level MI. The MMSE was administered to 320 residents living in 23 LTCF. The sample was predominately female (73%), and 38% of participants were aged >85 years. At least one item was missing from 122 (38.2%) of the MMSEs. Data were not Missing Completely at Random (MCAR), χ 2 (1110) = 1,351, p < 0.001. Using raw scores for those missing <6 items in combination with scale-level MI resulted in the regression coefficients and standard errors closest to item-level MI. Patterns of missing items often suggest systematic problems, such as trouble with manual dexterity, literacy, or visual impairment. While these observations may be relatively easy to take into account in clinical settings, non-random missingness presents challenges for research and must be considered in statistical analyses. We present suggestions for dealing with missing MMSE data based on the extent of missingness and the goal of analyses. Copyright © 2016 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Evaluation of missing value methods for predicting ambient BTEX concentrations in two neighbouring cities in Southwestern Ontario Canada

NASA Astrophysics Data System (ADS)

Miller, Lindsay; Xu, Xiaohong; Wheeler, Amanda; Zhang, Tianchu; Hamadani, Mariam; Ejaz, Unam

2018-05-01

High density air monitoring campaigns provide spatial patterns of pollutant concentrations which are integral in exposure assessment. Such analysis can assist with the determination of links between air quality and health outcomes, however, problems due to missing data can threaten to compromise these studies. This research evaluates four methods; mean value imputation, inverse distance weighting (IDW), inter-species ratios, and regression, to address missing spatial concentration data ranging from one missing data point up to 50% missing data. BTEX (benzene, toluene, ethylbenzene, and xylenes) concentrations were measured in Windsor and Sarnia, Ontario in the fall of 2005. Concentrations and inter-species ratios were generally similar between the two cities. Benzene (B) was observed to be higher in Sarnia, whereas toluene (T) and the T/B ratios were higher in Windsor. Using these urban, industrialized cities as case studies, this research demonstrates that using inter-species ratios or regression of the data for which there is complete information, along with one measured concentration (i.e. benzene) to predict for missing concentrations (i.e. TEX) results in good agreement between predicted and measured values. In both cities, the general trend remains that best agreement is observed for the leave-one-out scenario, followed by 10% and 25% missing, and the least agreement for the 50% missing cases. In the absence of any known concentrations IDW can provide reasonable agreement between observed and estimated concentrations for the BTEX species, and was superior over mean value imputation which was not able to preserve the spatial trend. The proposed methods can be used to fill in missing data, while preserving the general characteristics and rank order of the data which are sufficient for epidemiologic studies.

A novel application of the Intent to Attend assessment to reduce bias due to missing data in a randomized controlled clinical trial

PubMed Central

Rabideau, Dustin J; Nierenberg, Andrew A; Sylvia, Louisa G; Friedman, Edward S.; Bowden, Charles L.; Thase, Michael E.; Ketter, Terence; Ostacher, Michael J.; Reilly-Harrington, Noreen; Iosifescu, Dan V.; Calabrese, Joseph R.; Leon, Andrew C.; Schoenfeld, David A

2014-01-01

Background Missing data are unavoidable in most randomized controlled clinical trials, especially when measurements are taken repeatedly. If strong assumptions about the missing data are not accurate, crude statistical analyses are biased and can lead to false inferences. Furthermore, if we fail to measure all predictors of missing data, we may not be able to model the missing data process sufficiently. In longitudinal randomized trials, measuring a patient's intent to attend future study visits may help to address both of these problems. Leon et al. developed and included the Intent to Attend assessment in the Lithium Treatment—Moderate dose Use Study (LiTMUS), aiming to remove bias due to missing data from the primary study hypothesis [1]. Purpose The purpose of this study is to assess the performance of the Intent to Attend assessment with regard to its use in a sensitivity analysis of missing data. Methods We fit marginal models to assess whether a patient's self-rated intent predicted actual study adherence. We applied inverse probability of attrition weighting (IPAW) coupled with patient intent to assess whether there existed treatment group differences in response over time. We compared the IPAW results to those obtained using other methods. Results Patient-rated intent predicted missed study visits, even when adjusting for other predictors of missing data. On average, the hazard of retention increased by 19% for every one-point increase in intent. We also found that more severe mania, male gender, and a previously missed visit predicted subsequent absence. Although we found no difference in response between the randomized treatment groups, IPAW increased the estimated group difference over time. Limitations LiTMUS was designed to limit missed study visits, which may have attenuated the effects of adjusting for missing data. Additionally, IPAW can be less efficient and less powerful than maximum likelihood or Bayesian estimators, given that the parametric model is well-specified. Conclusions In LiTMUS, the Intent to Attend assessment predicted missed study visits. This item was incorporated into our IPAW models and helped reduce bias due to informative missing data. This analysis should both encourage and facilitate future use of the Intent to Attend assessment along with IPAW to address missing data in a randomized trial. PMID:24872362

The treatment of missing data in a large cardiovascular clinical outcomes study.

PubMed

Little, Roderick J; Wang, Julia; Sun, Xiang; Tian, Hong; Suh, Eun-Young; Lee, Michael; Sarich, Troy; Oppenheimer, Leonard; Plotnikov, Alexei; Wittes, Janet; Cook-Bruns, Nancy; Burton, Paul; Gibson, C Michael; Mohanty, Surya

2016-06-01

The potential impact of missing data on the results of clinical trials has received heightened attention recently. A National Research Council study provides recommendations for limiting missing data in clinical trial design and conduct, and principles for analysis, including the need for sensitivity analyses to assess robustness of findings to alternative assumptions about the missing data. A Food and Drug Administration advisory committee raised missing data as a serious concern in their review of results from the ATLAS ACS 2 TIMI 51 study, a large clinical trial that assessed rivaroxaban for its ability to reduce the risk of cardiovascular death, myocardial infarction or stroke in patients with acute coronary syndrome. This case study describes a variety of measures that were taken to address concerns about the missing data. A range of analyses are described to assess the potential impact of missing data on conclusions. In particular, measures of the amount of missing data are discussed, and the fraction of missing information from multiple imputation is proposed as an alternative measure. The sensitivity analysis in the National Research Council study is modified in the context of survival analysis where some individuals are lost to follow-up. The impact of deviations from ignorable censoring is assessed by differentially increasing the hazard of the primary outcome in the treatment groups and multiply imputing events between dropout and the end of the study. Tipping-point analyses are described, where the deviation from ignorable censoring that results in a reversal of significance of the treatment effect is determined. A study to determine the vital status of participants lost to follow-up was also conducted, and the results of including this additional information are assessed. Sensitivity analyses suggest that findings of the ATLAS ACS 2 TIMI 51 study are robust to missing data; this robustness is reinforced by the follow-up study, since inclusion of data from this study had little impact on the study conclusions. Missing data are a serious problem in clinical trials. The methods presented here, namely, the sensitivity analyses, the follow-up study to determine survival of missing cases, and the proposed measurement of missing data via the fraction of missing information, have potential application in other studies involving survival analysis where missing data are a concern. © The Author(s) 2016.

Search for supersymmetry in events with soft leptons, low jet multiplicity, and missing transverse energy in proton–proton collisions at $$\\sqrt{s}$$ = 8 TeV

DOE PAGES

Khachatryan, Vardan

2016-05-16

Results are presented from a search for supersymmetric particles in scenarios with a compressed mass spectrum. The data sample corresponds to 19.7 inverse femtobarns of proton-proton collisions recorded by the CMS experiment at √s = 8 TeV. The search targets top squark (more » $$\\tilde{t}$$ pair production in scenarios with mass differences Δm = m($$\\tilde{t}$$ – m($$\\tilde{\\chi}$$ 1 0) below the W-boson mass and with top-squark decays in the four-body mode ($$\\tilde{t}$$ → blv$$\\tilde{\\chi}$$ 1 0), where the ($$\\tilde{\\chi}$$ 1 0) is assumed to be the lightest supersymmetric particle (LSP). The signature includes a high transverse momentum (p T) jet associated with initial-state radiation, one or two low-p T leptons, and significant missing transverse energy. The event yields observed in data are consistent with the expected background contributions from standard model processes. Limits are set on the cross section for top squark pair production as a function of the $$\\tilde{t}$$ and LSP masses. Assuming a 100% branching fraction for the four-body decay mode, top-squark masses below 316 GeV are excluded for Δm = 25 GeV at 95% CL. Furthermore, the dilepton data are also interpreted under the assumption of chargino-neutralino production, with subsequent decays to sleptons or sneutrinos. Assuming a difference between the common $$\\tilde{\\chi}$$ 1 +/$$\\tilde{\\chi}$$ 2 + mass and the LSP mass of 20 GeV and a τ-enriched decay scenario, masses in the range m( $$\\tilde{\\chi}$$ 1 +) <307 GeVare excluded at 95% CL.« less

Search for supersymmetry in events with soft leptons, low jet multiplicity, and missing transverse energy 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.; 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.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Fasanella, G.; Favart, L.; Grebenyuk, A.; Karapostoli, G.; 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.; 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.; Musich, M.; 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, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hamer, 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.; Hadjiiska, R.; Iaydjiev, P.; 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.; Spiezia, A.; 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.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, 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.; Abdelalim, A. A.; Awad, A.; El Sawy, M.; Mahrous, A.; Radi, 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.; Pigard, 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.; 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.; 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. 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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.; 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.; 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. 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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.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Passaseo, M.; Pazzini, J.; Pegoraro, M.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Vanini, S.; 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.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; 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.; 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.; 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.; 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.; 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.; Zanetti, A.; 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.; 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.; Ryu, M. S.; Choi, Y.; 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.; Pedraza, I.; Salazar Ibarguen, H. A.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. 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V.; Baskakov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Myagkov, 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.; 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.; Santaolalla, J.; Soares, M. S.; Albajar, C.; de Trocóniz, J. 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V.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Piparo, D.; Racz, A.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Simon, M.; Sphicas, P.; 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.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrozzi, L.; 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.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Yu, S. S.; Kumar, Arun; 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.; Demiroglu, Z. S.; Dozen, C.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Zorbilmez, C.; Akin, I. V.; 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.; 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.; 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.; 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.; 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.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Arcaro, D.; 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.; Hakala, J.; Heintz, U.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Syarif, R.; 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.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Derdzinski, M.; 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.; 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.; Mccoll, N.; Mullin, S. D.; Richman, J.; Stuart, D.; Suarez, I.; 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.; Andrews, M. B.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; 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.; 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.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; 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.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Di Giovanni, G. P.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Hugon, J.; Konigsberg, J.; Korytov, A.; Low, J. F.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Rossin, R.; Shchutska, L.; Snowball, M.; Sperka, D.; Terentyev, N.; Thomas, L.; 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.; Weinberg, M.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Kalakhety, H.; Noonan, 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.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Barnett, B. A.; Blumenfeld, B.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Osherson, M.; Roskes, J.; Sady, A.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P., III; Majumder, D.; Malek, M.; Murray, M.; Sanders, S.; Stringer, R.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; 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.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; 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.; Evans, A.; 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.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Roozbahani, B.; 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.; 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.; Ji, W.; 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.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; 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.; Eshaq, Y.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Harel, A.; Hindrichs, O.; Khukhunaishvili, A.; Petrillo, G.; Tan, P.; Verzetti, M.; 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.; Nash, K.; 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.; Gilmore, J.; Kamon, T.; Krutelyov, V.; Mueller, R.; Osipenkov, I.; Pakhotin, Y.; Patel, R.; Perloff, A.; 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.; Ni, H.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; 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.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Gomber, B.; Grothe, M.; 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.; Ruggles, T.; Sarangi, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2016-08-01

Results are presented from a search for supersymmetric particles in scenarios with small mass splittings. The data sample corresponds to 19.7 fb-1 of proton-proton collisions recorded by the CMS experiment at √{ s} = 8 TeV. The search targets top squark (t ˜) pair production in scenarios with mass differences Δm = m (t ˜) - m ( χ˜10) below the W-boson mass and with top-squark decays in the four-body mode (t ˜ → bℓν χ˜10), where the neutralino (χ˜10) is assumed to be the lightest supersymmetric particle (LSP). The signature includes a high transverse momentum (pT) jet associated with initial-state radiation, one or two low-pT leptons, and significant missing transverse energy. The event yields observed in data are consistent with the expected background contributions from standard model processes. Limits are set on the cross section for top squark pair production as a function of the t ˜ and LSP masses. Assuming a 100% branching fraction for the four-body decay mode, top-squark masses below 316 GeV are excluded for Δm = 25 GeV at 95% CL. The dilepton data are also interpreted under the assumption of chargino-neutralino production, with subsequent decays to sleptons or sneutrinos. Assuming a difference between the common χ˜1+/χ˜20 mass and the LSP mass of 20 GeV and a τ-enriched decay scenario, masses in the range m (χ˜1+) < 307 GeV are excluded at 95% CL.

Three challenges described for identifying participants with missing data in trials reports, and potential solutions suggested to systematic reviewers.

PubMed

Akl, Elie A; Kahale, Lara A; Ebrahim, Shanil; Alonso-Coello, Pablo; Schünemann, Holger J; Guyatt, Gordon H

2016-08-01

To categorize the challenges in determining the extent of missing participant data in randomized trials and suggest potential solutions for systematic review authors. During the process of updating a series of Cochrane systematic reviews on the topic of anticoagulation in patients with cancer, we identified challenges and used an iterative approach to improve, and a consensus process to agree on the challenges identified, and to suggest potential ways of dealing with them. The five systematic reviews included 58 trials and 75 meta-analyses for patient-important dichotomous outcomes with 27,037 randomized participants. We identified three categories of challenges: (1) Although systematic reviewers require information about missing data to be reported by outcome, trialists typically report the information by participant; (2) It is not always clear whether the trialists followed up participants in certain categories (e.g., noncompliers), that is, whether some categories of participants did or did not have missing data; (3) It is not always clear how the trialists dealt with missing data in their analysis (e.g., exclusion from the denominator vs. assumptions made for the numerator). We discuss potential solutions for each one of these challenges and suggest further research work. Current reporting of missing data is often not explicit and transparent, and although our potential solutions to problems of suboptimal reporting may be helpful, reliable and valid characterization of the extent and nature of missing data remains elusive. Reporting of missing data in trials needs further improvement. Copyright © 2016 Elsevier Inc. All rights reserved.

Striatal connectivity changes following gambling wins and near-misses: Associations with gambling severity.

PubMed

van Holst, Ruth J; Chase, Henry W; Clark, Luke

2014-01-01

Frontostriatal circuitry is implicated in the cognitive distortions associated with gambling behaviour. 'Near-miss' events, where unsuccessful outcomes are proximal to a jackpot win, recruit overlapping neural circuitry with actual monetary wins. Personal control over a gamble (e.g., via choice) is also known to increase confidence in one's chances of winning (the 'illusion of control'). Using psychophysiological interaction (PPI) analyses, we examined changes in functional connectivity as regular gamblers and non-gambling participants played a slot-machine game that delivered wins, near-misses and full-misses, and manipulated personal control. We focussed on connectivity with striatal seed regions, and associations with gambling severity, using voxel-wise regression. For the interaction term of near-misses (versus full-misses) by personal choice (participant-chosen versus computer-chosen), ventral striatal connectivity with the insula, bilaterally, was positively correlated with gambling severity. In addition, some effects for the contrast of wins compared to all non-wins were observed at an uncorrected (p < .001) threshold: there was an overall increase in connectivity between the striatal seeds and left orbitofrontal cortex and posterior insula, and a negative correlation for gambling severity with the connectivity between the right ventral striatal seed and left anterior cingulate cortex. These findings corroborate the 'non-categorical' nature of reward processing in gambling: near-misses and full-misses are objectively identical outcomes that are processed differentially. Ventral striatal connectivity with the insula correlated positively with gambling severity in the illusion of control contrast, which could be a risk factor for the cognitive distortions and loss-chasing that are characteristic of problem gambling.

Search for top and bottom squarks from gluino pair production in final states with missing transverse energy and at least three b-jets with the ATLAS detector

DOE PAGES

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

2012-10-06

This letter reports the results of a search for top and bottom squarks from gluino pair production in 4.7 fb -1 of pp collisions at √s = 7 TeV using the ATLAS detector at the LHC. The search is performed in events with large missing transverse momentum and at least three jets identified as originating from a b-quark. Exclusion limits are presented for a variety of gluino-mediated models with gluino masses up to 1 TeV excluded.

Dealing with Divorce

MedlinePlus

... to a serious problem like drinking , abuse, or gambling. Sometimes nothing bad happens, but parents just decide ... distance. Even a quick email saying "I'm thinking of you" helps ease the feelings of missing ...

Search for High-Mass States with One Lepton Plus Missing Transverse Momentum in Proton-Proton Collisions at $\\sqrt{s} with the ATLAS Detector

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

Aad, Georges; Abbott, Brad; Abdallah, Jalal

2012-06-20

The ATLAS detector is used to search for high-mass states, such as heavy charged gauge bosons (W{prime},W*), decaying to a charged lepton (electron or muon) and a neutrino. Results are presented based on the analysis of ppcollisions at a center-of-mass energy of 7 TeV corresponding to an integrated luminosity of 36 pb{sup -1}. No excess beyond standard model expectations is observed. A W{prime} with sequential standard model couplings is excluded at 95% confidence level for masses below 1.49 TeV, and a W* (charged chiral boson) for masses below 1.35 TeV.

Search for high-mass states with one lepton plus missing transverse momentum in proton-proton collisions at √{ s} = 7 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

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

2011-06-01

The ATLAS detector is used to search for high-mass states, such as heavy charged gauge bosons (W‧ ,W*), decaying to a charged lepton (electron or muon) and a neutrino. Results are presented based on the analysis of pp collisions at a center-of-mass energy of 7 TeV corresponding to an integrated luminosity of 36 pb-1. No excess beyond standard model expectations is observed. A W‧ with sequential standard model couplings is excluded at 95% confidence level for masses below 1.49 TeV, and a W* (charged chiral boson) for masses below 1.35 TeV.

The predicted luminous satellite populations around SMC- and LMC-mass galaxies - a missing satellite problem around the LMC?

NASA Astrophysics Data System (ADS)

Dooley, Gregory A.; Peter, Annika H. G.; Carlin, Jeffrey L.; Frebel, Anna; Bechtol, Keith; Willman, Beth

2017-11-01

Recent discovery of many dwarf satellite galaxies in the direction of the Small and Large Magellanic Clouds (SMC and LMC) provokes questions of their origins, and what they can reveal about galaxy evolution theory. Here, we predict the satellite stellar mass function of Magellanic Cloud-mass host galaxies using abundance matching and reionization models applied to the Caterpillar simulations. Specifically focusing on the volume within 50 kpc of the LMC, we predict a mean of four to eight satellites with stellar mass M* > 104 M⊙, and three to four satellites with 80 < M* ≤ 3000 M⊙. Surprisingly, all 12 currently known satellite candidates have stellar masses of 80 < M* ≤ 3000 M⊙. Reconciling the dearth of large satellites and profusion of small satellites is challenging and may require a combination of a major modification of the M*-Mhalo relationship (steep, but with an abrupt flattening at 103 M⊙), late reionization for the Local Group (zreion ≲ 9 preferred) and/or strong tidal stripping. We can more robustly predict that ∼53 per cent of satellites within this volume were accreted together with the LMC and SMC and ∼47 per cent were only ever Milky Way satellites. Observing satellites of isolated LMC-sized field galaxies is essential to place the LMC in context, and to better constrain the M*-Mhalo relationship. Modelling known LMC-sized galaxies within 8 Mpc, we predict 1-6 (2-12) satellites with M* > 105 M⊙ (M* > 104 M⊙) within the virial volume of each, and 1-3 (1-7) within a single 1.5° diameter field of view, making their discovery likely.

Globular Cluster Formation at High Density: A Model for Elemental Enrichment with Fast Recycling of Massive-star Debris

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

Elmegreen, Bruce G., E-mail: bge@us.ibm.com

The self-enrichment of massive star clusters by p -processed elements is shown to increase significantly with increasing gas density as a result of enhanced star formation rates and stellar scatterings compared to the lifetime of a massive star. Considering the type of cloud core where a globular cluster (GC) might have formed, we follow the evolution and enrichment of the gas and the time dependence of stellar mass. A key assumption is that interactions between massive stars are important at high density, including interactions between massive stars and massive-star binaries that can shred stellar envelopes. Massive-star interactions should also scattermore » low-mass stars out of the cluster. Reasonable agreement with the observations is obtained for a cloud-core mass of ∼4 × 10{sup 6} M {sub ⊙} and a density of ∼2 × 10{sup 6} cm{sup −3}. The results depend primarily on a few dimensionless parameters, including, most importantly, the ratio of the gas consumption time to the lifetime of a massive star, which has to be low, ∼10%, and the efficiency of scattering low-mass stars per unit dynamical time, which has to be relatively large, such as a few percent. Also for these conditions, the velocity dispersions of embedded GCs should be comparable to the high gas dispersions of galaxies at that time, so that stellar ejection by multistar interactions could cause low-mass stars to leave a dwarf galaxy host altogether. This could solve the problem of missing first-generation stars in the halos of Fornax and WLM.« less

Search for new and unusual strangeonia in photoproduction using CLAS

NASA Astrophysics Data System (ADS)

Saini, Mukesh S.

We perform a survey of the proton, K+, K - , - 3 charged track data, taken by the CLAS detector for the HyCLAS experiment [1] during the g12 run-period at Jefferson Lab. We aim to study the strong decay amplitudes, partial widths and production channels of strangeonia from the CLAS g12 dataset. HyCLAS was motivated by the experimental results for gluonic hybrid meson candidates, theoretical Lattice QCD, and Flux-tube Model calculations and predictions. The experiment was designed and conducted to search and observe new forms of hadronic matter through photoproduction. Crucial among the various channels explored in HyCLAS are those for strangeonia,resonances such as φ(1680), φ3(1850) and Y(2175) [2] decaying to φ eta. A meson decay via φ eta is the signature that unequivocally identifies a strangeonium (ss¯ ) state and is the main focus of this thesis. A strangeonium decay via φ eta is considered the premier decay mode to cleanly establish the strangeonia spectrum [3]. This is due to negligible interference of the φ eta decay mode with the non-strange nn¯ (n ∈ {u, d}) meson decay modes, on account of the fact that φ(1020) is an almost pure ss¯ vector meson and the eta meson possesses a strong component of ss¯ in it as well. Another analysis explored was the φ pio decay channel, which is an exotic decay mode for a meson. Decay of an initial ss¯ meson via this channel is forbidden on account of the conservation of isotopic spin whereas the decay of a nn¯ via the φ pi o decay mode is also forbidden by the Okubo - Zweig - Iizuka (OZI) rule. Thus, observation of a resonance decaying to φ pi o will provide strong evidence of mesons beyond qq¯, probably of a gluonic excitation - qq¯g or a tetraquark state - qq¯qq¯ [4]. A final state of proton, K + and K - is selected from the g12 dataset. An intermediate φ state is identified by its decay to K+ K-. Using Energy-Momentum conservation, missing mass in an event is calculated. Depending on the analyses, suitable missing mass cuts for the missing eta mass or the pio mass is implemented to identify the particular missing particle. Invariant mass for the φ and the missing eta/pi o system is reconstructed to observe possible resonances. [Special characters omitted. See original document] The yield and the cross section for the photoproduction of φ eta mesons off of protons is calculated for Egamma ∈ [4.40, 5.45} GeV/c2 using elliptical sideband subtraction. Upper and lower limits on the photoproduction cross section for possible strangeonium resonances and their subsequent decay via the φ eta intermediate state are calculated using the FeldMan-Cousins approach with a 90% confidence interval limit. A partial wave analysis is also performed on the φ eta intermediate state to explore for discernable resonances. The yield and the cross sectionfor the photoproduction of φ mesons off of protons is calculated for Egamma ∈ {4.40, 5.45} GeV/c2. Yield is estimated for the intermediate state φ pio and its invariant mass distributions analyzed for possible resonances. The ( proton K + K- ) final state is also explored for the rare φ o events and the yield for the channel is measured.

Do the methods used to analyse missing data really matter? An examination of data from an observational study of Intermediate Care patients.

PubMed

Kaambwa, Billingsley; Bryan, Stirling; Billingham, Lucinda

2012-06-27

Missing data is a common statistical problem in healthcare datasets from populations of older people. Some argue that arbitrarily assuming the mechanism responsible for the missingness and therefore the method for dealing with this missingness is not the best option-but is this always true? This paper explores what happens when extra information that suggests that a particular mechanism is responsible for missing data is disregarded and methods for dealing with the missing data are chosen arbitrarily. Regression models based on 2,533 intermediate care (IC) patients from the largest evaluation of IC done and published in the UK to date were used to explain variation in costs, EQ-5D and Barthel index. Three methods for dealing with missingness were utilised, each assuming a different mechanism as being responsible for the missing data: complete case analysis (assuming missing completely at random-MCAR), multiple imputation (assuming missing at random-MAR) and Heckman selection model (assuming missing not at random-MNAR). Differences in results were gauged by examining the signs of coefficients as well as the sizes of both coefficients and associated standard errors. Extra information strongly suggested that missing cost data were MCAR. The results show that MCAR and MAR-based methods yielded similar results with sizes of most coefficients and standard errors differing by less than 3.4% while those based on MNAR-methods were statistically different (up to 730% bigger). Significant variables in all regression models also had the same direction of influence on costs. All three mechanisms of missingness were shown to be potential causes of the missing EQ-5D and Barthel data. The method chosen to deal with missing data did not seem to have any significant effect on the results for these data as they led to broadly similar conclusions with sizes of coefficients and standard errors differing by less than 54% and 322%, respectively. Arbitrary selection of methods to deal with missing data should be avoided. Using extra information gathered during the data collection exercise about the cause of missingness to guide this selection would be more appropriate.

Determination of the masses of globular clusters using proper motions

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

Ninkovich, S.

1984-09-01

Published proper motions of stars in the fields of the globular clusters M 15, M 92, and M 13 (Cudworth, 1976 Cudworth and Monet, 1979) are compiled in tables and used to estimate the masses of the clusters by the method of Naumova and Ogorodnikov (1973). Masses of the order of 10 to the 8th solar mass are calculated, as compared to an M 13 mass of about 10 to the 6th solar mass determined by the virial theorem. The higher masses are considered indicative of the actual cluster masses despite the distortion introduced by the presence in the fieldmore » of stars not belonging to the clusters. It is suggested that the difference between these estimates and the smaller masses proposed by previous authors may represent unobservable peripheral dwarf stars or some invisible mass (like the so-called missing mass of the Galaxy).« less

How to deal with missing longitudinal data in cost of illness analysis in Alzheimer's disease-suggestions from the GERAS observational study.

PubMed

Belger, Mark; Haro, Josep Maria; Reed, Catherine; Happich, Michael; Kahle-Wrobleski, Kristin; Argimon, Josep Maria; Bruno, Giuseppe; Dodel, Richard; Jones, Roy W; Vellas, Bruno; Wimo, Anders

2016-07-18

Missing data are a common problem in prospective studies with a long follow-up, and the volume, pattern and reasons for missing data may be relevant when estimating the cost of illness. We aimed to evaluate the effects of different methods for dealing with missing longitudinal cost data and for costing caregiver time on total societal costs in Alzheimer's disease (AD). GERAS is an 18-month observational study of costs associated with AD. Total societal costs included patient health and social care costs, and caregiver health and informal care costs. Missing data were classified as missing completely at random (MCAR), missing at random (MAR) or missing not at random (MNAR). Simulation datasets were generated from baseline data with 10-40 % missing total cost data for each missing data mechanism. Datasets were also simulated to reflect the missing cost data pattern at 18 months using MAR and MNAR assumptions. Naïve and multiple imputation (MI) methods were applied to each dataset and results compared with complete GERAS 18-month cost data. Opportunity and replacement cost approaches were used for caregiver time, which was costed with and without supervision included and with time for working caregivers only being costed. Total costs were available for 99.4 % of 1497 patients at baseline. For MCAR datasets, naïve methods performed as well as MI methods. For MAR, MI methods performed better than naïve methods. All imputation approaches were poor for MNAR data. For all approaches, percentage bias increased with missing data volume. For datasets reflecting 18-month patterns, a combination of imputation methods provided more accurate cost estimates (e.g. bias: -1 % vs -6 % for single MI method), although different approaches to costing caregiver time had a greater impact on estimated costs (29-43 % increase over base case estimate). Methods used to impute missing cost data in AD will impact on accuracy of cost estimates although varying approaches to costing informal caregiver time has the greatest impact on total costs. Tailoring imputation methods to the reason for missing data will further our understanding of the best analytical approach for studies involving cost outcomes.

Teachers' and Students' Perceptions of Students' Problem-Solving Difficulties in Physics: Implications for Remediation

ERIC Educational Resources Information Center

Ogunleye, Ayodele O.

2009-01-01

In recent times, science education researchers have identified a lot of instruments for evaluating conceptual understanding as well as students' attitudes and beliefs about physics; unfortunately however, there are no broad based evaluation instruments in the field of problem-solving in physics. This missing tool is an indication of the complexity…

Factors Contributing to the Problem of Student Absenteeism in a Rural School

ERIC Educational Resources Information Center

Durborow, Angela

2017-01-01

Student attendance would seem to be a vital link in measuring student success in school. If students are not in school, they miss instruction from the teacher. Without instruction it seems incredibly difficult to complete the work needed to pass classes and be successful in school. The research explored the problem of practice of student…

Correlation of Electronic Health Records Use and Reduced Prevalence of Diabetes Co-Morbidities

ERIC Educational Resources Information Center

Eller, James D.

2013-01-01

The general problem is Native American tribes have high prevalence rates of diabetes. The specific problem is the failure of IHS sites to adopt EHR may cause health care providers to miss critical opportunities to improve screening and triage processes that result in quality improvement. The purpose of the quantitative correlational study was to…

Mental health workers. Graduation daze.

PubMed

Lewis, Carol

2003-09-11

PCTs are likely to miss the national target on employment of graduate mental health workers. Pilots are showing success in reducing referrals. Managers must address career progression problems and define roles more clearly.

Dentistry to the rescue of missing children: A review.

PubMed

Vij, Nitika; Kochhar, Gulsheen Kaur; Chachra, Sanjay; Kaur, Taranjot

2016-01-01

Today's society is becoming increasingly unsafe for children: we frequently hear about new incidents of missing children, which lead to emotional trauma for the loved ones and expose systemic failures of law and order. Parents can take extra precautions to ensure the safety of their children by educating them about ways to protect themselves and keep important records of the child such as updated color photographs, fingerprints, deoxyribonucleic acid (DNA) samples, etc., handy. However, in spite of all efforts, the problem of missing children still remains. Developments in the field of dentistry have empowered dentists with various tools and techniques to play a pivotal role in tracing a missing child. One such tool is Toothprints, a patented arch-shaped thermoplastic dental impression wafer developed by Dr. David Tesini, a paediatric dentist from Massachusetts. Toothprints enables a unique identification of the missing children not only through the bite impression but also through salivary DNA. Besides the use of Toothprints, a dentist can assist investigating agencies in identifying the missing children in multiple ways, including postmortem dental profiling, labeled dental fixtures, DNA extraction from teeth, and serial number engraving on the children's teeth. More importantly, all these tools cause minimal inconvenience to the individual, making a dentist's role in tracking a missing child even more significant. Thus, the simple discipline of maintaining timely dental records with the help of their dentists can save potential hassles for the parents in the future.

Congenitally missing teeth (hypodontia): A review of the literature concerning the etiology, prevalence, risk factors, patterns and treatment

PubMed Central

Rakhshan, Vahid

2015-01-01

Congenitally missing teeth (CMT), or as usually called hypodontia, is a highly prevalent and costly dental anomaly. Besides an unfavorable appearance, patients with missing teeth may suffer from malocclusion, periodontal damage, insufficient alveolar bone growth, reduced chewing ability, inarticulate pronunciation and other problems. Treatment might be usually expensive and multidisciplinary. This highly frequent and yet expensive anomaly is of interest to numerous clinical, basic science and public health fields such as orthodontics, pediatric dentistry, prosthodontics, periodontics, maxillofacial surgery, anatomy, anthropology and even the insurance industry. This essay reviews the findings on the etiology, prevalence, risk factors, occurrence patterns, skeletal changes and treatments of congenitally missing teeth. It seems that CMT usually appears in females and in the permanent dentition. It is not conclusive whether it tends to occur more in the maxilla or mandible and also in the anterior versus posterior segments. It can accompany various complications and should be attended by expert teams as soon as possible. PMID:25709668

On the Use of Local Assessments for Monitoring Centrally Reviewed Endpoints with Missing Data in Clinical Trials*

PubMed Central

Brummel, Sean S.; Gillen, Daniel L.

2014-01-01

Due to ethical and logistical concerns it is common for data monitoring committees to periodically monitor accruing clinical trial data to assess the safety, and possibly efficacy, of a new experimental treatment. When formalized, monitoring is typically implemented using group sequential methods. In some cases regulatory agencies have required that primary trial analyses should be based solely on the judgment of an independent review committee (IRC). The IRC assessments can produce difficulties for trial monitoring given the time lag typically associated with receiving assessments from the IRC. This results in a missing data problem wherein a surrogate measure of response may provide useful information for interim decisions and future monitoring strategies. In this paper, we present statistical tools that are helpful for monitoring a group sequential clinical trial with missing IRC data. We illustrate the proposed methodology in the case of binary endpoints under various missingness mechanisms including missing completely at random assessments and when missingness depends on the IRC’s measurement. PMID:25540717

Estimating Interaction Effects With Incomplete Predictor Variables

PubMed Central

Enders, Craig K.; Baraldi, Amanda N.; Cham, Heining

2014-01-01

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques. PMID:24707955

Cosmological simulations of decaying dark matter: implications for small-scale structure of dark matter haloes

NASA Astrophysics Data System (ADS)

Wang, Mei-Yu; Peter, Annika H. G.; Strigari, Louis E.; Zentner, Andrew R.; Arant, Bryan; Garrison-Kimmel, Shea; Rocha, Miguel

2014-11-01

We present a set of N-body simulations of a class of models in which an unstable dark matter particle decays into a stable dark matter particle and a non-interacting light particle with decay lifetime comparable to the Hubble time. We study the effects of the recoil kick velocity (Vk) received by the stable dark matter on the structures of dark matter haloes ranging from galaxy-cluster to Milky Way-mass scales. For Milky Way-mass haloes, we use high-resolution, zoom-in simulations to explore the effects of decays on Galactic substructure. In general, haloes with circular velocities comparable to the magnitude of kick velocity are most strongly affected by decays. We show that models with lifetimes Γ-1 ˜ H_0^{-1} and recoil speeds Vk ˜ 20-40 km s-1 can significantly reduce both the abundance of Galactic subhaloes and their internal densities. We find that decaying dark matter models that do not violate current astrophysical constraints can significantly mitigate both the `missing satellites problem' and the more recent `too big to fail problem'. These decaying models predict significant time evolution of haloes, and this implies that at high redshifts decaying models exhibit the similar sequence of structure formation as cold dark matter. Thus, decaying dark matter models are significantly less constrained by high-redshift phenomena than warm dark matter models. We conclude that models of decaying dark matter make predictions that are relevant for the interpretation of small galaxies observations in the Local Group and can be tested as well as by forthcoming large-scale surveys.

Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis

PubMed Central

Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

2016-01-01

The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. PMID:27104948

Search for top squark pair production in compressed-mass-spectrum scenarios in proton–proton collisions at s = 8  TeV using the α T variable

DOE PAGES

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

2017-02-10

An inclusive search is performed for supersymmetry in final states containing jets and an apparent imbalance in transverse momentum,more » $$→\\atop{p}$$ $$miss\\atop{T}$$, due to the production of unobserved weakly interacting particles in pp collisions at a centre-of-mass energy of 8 TeV. The data, recorded with the CMS detector at the CERN LHC, correspond to an integrated luminosity of 18.5 fb $-$1 . The dimensionless kinematic variable α T is used to discriminate between events with genuine $$→\\atop{p}$$ $$miss\\atop{T}$$ associated with unobserved particles and spurious values of $$→\\atop{p}$$ $$miss\\atop{T}$$ arising from jet energy mismeasurements. No excess of event yields above the expected standard model backgrounds is observed. The results are interpreted in terms of constraints on the parameter space of several simplified models of supersymmetry that assume the pair production of top squarks. The search provides sensitivity to a broad range of top squark ($$\\sim\\atop{t}$$) decay modes, including the two-body decay $$\\sim\\atop{t}$$→c$$\\sim\\atop{\\chi}$$$0\\atop{1}$$ , where c is a charm quark and$$\\sim\\atop{\\chi}$$$0\\atop{1}$$ is the lightest neutralino, as well as the four-body decay $$\\sim\\atop{t}$$→bf$$\\bar{f}$$'χ$$\\sim\\atop{\\chi}$$$0\\atop{1}$$ , where b is a bottom quark and f and$$\\bar{f}$$' are fermions produced in the decay of an intermediate off-shell W boson. Furthermore, these modes dominate in scenarios in which the top squark and lightest neutralino are nearly degenerate in mass. For these modes, top squarks with masses as large as 260 and 225 GeV are excluded, respectively, for the two- and four-body decays.« less

Search for top squark pair production in compressed-mass-spectrum scenarios in proton–proton collisions at s = 8  TeV using the α T variable

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

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

An inclusive search is performed for supersymmetry in final states containing jets and an apparent imbalance in transverse momentum,more » $$→\\atop{p}$$ $$miss\\atop{T}$$, due to the production of unobserved weakly interacting particles in pp collisions at a centre-of-mass energy of 8 TeV. The data, recorded with the CMS detector at the CERN LHC, correspond to an integrated luminosity of 18.5 fb $-$1 . The dimensionless kinematic variable α T is used to discriminate between events with genuine $$→\\atop{p}$$ $$miss\\atop{T}$$ associated with unobserved particles and spurious values of $$→\\atop{p}$$ $$miss\\atop{T}$$ arising from jet energy mismeasurements. No excess of event yields above the expected standard model backgrounds is observed. The results are interpreted in terms of constraints on the parameter space of several simplified models of supersymmetry that assume the pair production of top squarks. The search provides sensitivity to a broad range of top squark ($$\\sim\\atop{t}$$) decay modes, including the two-body decay $$\\sim\\atop{t}$$→c$$\\sim\\atop{\\chi}$$$0\\atop{1}$$ , where c is a charm quark and$$\\sim\\atop{\\chi}$$$0\\atop{1}$$ is the lightest neutralino, as well as the four-body decay $$\\sim\\atop{t}$$→bf$$\\bar{f}$$'χ$$\\sim\\atop{\\chi}$$$0\\atop{1}$$ , where b is a bottom quark and f and$$\\bar{f}$$' are fermions produced in the decay of an intermediate off-shell W boson. Furthermore, these modes dominate in scenarios in which the top squark and lightest neutralino are nearly degenerate in mass. For these modes, top squarks with masses as large as 260 and 225 GeV are excluded, respectively, for the two- and four-body decays.« less

Search for top squarks and dark matter particles in opposite-charge dilepton final states at s = 13 TeV

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

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

A search for new physics is presented in final states with two oppositely charged leptons (electrons or muons), jets identified as originating from b quarks, and missing transverse momentum (more » $$p_\\mathrm{T}^\\text{miss}$$). The search uses proton-proton collision data at $$\\sqrt{s}=$$ 13 TeV amounting to 35.9 fb$$^{-1}$$ of integrated luminosity collected using the CMS detector in 2016. Hypothetical signal events are efficiently separated from the dominant $$\\mathrm{t}\\overline{\\mathrm{t}}$$ background with requirements on $$p_\\mathrm{T}^\\text{miss}$$ and transverse mass variables. No significant deviation is observed from the expected background. Exclusion limits are set in the context of simplified supersymmetric models with pair-produced top squarks. For top squarks, decaying exclusively to a top quark and a neutralino, exclusion limits are placed at 95\\% confidence level on the mass of the lightest top squark up to 800 GeV and on the lightest neutralino up to 360 GeV. These results, combined with searches in the single-lepton and all-jet final states, raise the exclusion limits up to 1050 GeV for the lightest top squark and up to 500 GeV for the lightest neutralino. For top squarks undergoing a cascade decay through charginos and sleptons, the mass limits reach up to 1300 GeV for top squarks and up to 800 GeV for the lightest neutralino. The results are also interpreted in a simplified model with a dark matter (DM) particle coupled to the top quark through a scalar or pseudoscalar mediator. For light DM, mediator masses up to 100 (50) GeV are excluded for scalar (pseudoscalar) mediators. The result for the scalar mediator achieves some of the most stringent limits to date in this model.« less

Search for top squarks and dark matter particles in opposite-charge dilepton final states at s = 13 TeV

DOE PAGES

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

2018-02-15

A search for new physics is presented in final states with two oppositely charged leptons (electrons or muons), jets identified as originating from b quarks, and missing transverse momentum (more » $$p_\\mathrm{T}^\\text{miss}$$). The search uses proton-proton collision data at $$\\sqrt{s}=$$ 13 TeV amounting to 35.9 fb$$^{-1}$$ of integrated luminosity collected using the CMS detector in 2016. Hypothetical signal events are efficiently separated from the dominant $$\\mathrm{t}\\overline{\\mathrm{t}}$$ background with requirements on $$p_\\mathrm{T}^\\text{miss}$$ and transverse mass variables. No significant deviation is observed from the expected background. Exclusion limits are set in the context of simplified supersymmetric models with pair-produced top squarks. For top squarks, decaying exclusively to a top quark and a neutralino, exclusion limits are placed at 95\\% confidence level on the mass of the lightest top squark up to 800 GeV and on the lightest neutralino up to 360 GeV. These results, combined with searches in the single-lepton and all-jet final states, raise the exclusion limits up to 1050 GeV for the lightest top squark and up to 500 GeV for the lightest neutralino. For top squarks undergoing a cascade decay through charginos and sleptons, the mass limits reach up to 1300 GeV for top squarks and up to 800 GeV for the lightest neutralino. The results are also interpreted in a simplified model with a dark matter (DM) particle coupled to the top quark through a scalar or pseudoscalar mediator. For light DM, mediator masses up to 100 (50) GeV are excluded for scalar (pseudoscalar) mediators. The result for the scalar mediator achieves some of the most stringent limits to date in this model.« less

Getting patients in the door: medical appointment reminder preferences

PubMed Central

Crutchfield, Trisha M; Kistler, Christine E

2017-01-01

Purpose Between 23% and 34% of outpatient appointments are missed annually. Patients who frequently miss medical appointments have poorer health outcomes and are less likely to use preventive health care services. Missed appointments result in unnecessary costs and organizational inefficiencies. Appointment reminders may help reduce missed appointments; particular types may be more effective than other types. We used a survey with a discrete choice experiment (DCE) to learn why individuals miss appointments and to assess appointment reminder preferences. Methods We enrolled a national sample of adults from an online survey panel to complete demographic and appointment habit questions as well as a 16-task DCE designed in Sawtooth Software’s Discover tool. We assessed preferences for four reminder attributes – initial reminder type, arrival of initial reminder, reminder content, and number of reminders. We derived utilities and importance scores. Results We surveyed 251 adults nationally, with a mean age of 43 (range 18–83) years: 51% female, 84% White, and 8% African American. Twenty-three percent of individuals missed one or more appointments in the past 12 months. Two primary reasons given for missing an appointment include transportation problems (28%) and forgetfulness (26%). Participants indicated the initial reminder type (21%) was the most important attribute, followed by the number of reminders (10%). Overall, individuals indicated a preference for a single reminder, arriving via email, phone call, or text message, delivered less than 2 weeks prior to an appointment. Preferences for reminder content were less clear. Conclusion The number of missed appointments and reasons for missing appointments are consistent with prior research. Patient-centered appointment reminders may improve appointment attendance by addressing some of the reasons individuals report missing appointments and by meeting patients’ needs. Future research is necessary to determine if preferred reminders used in practice will result in improved appointment attendance in clinical settings. PMID:28182131

Multiple imputation to deal with missing EQ-5D-3L data: Should we impute individual domains or the actual index?

PubMed

Simons, Claire L; Rivero-Arias, Oliver; Yu, Ly-Mee; Simon, Judit

2015-04-01

Missing data are a well-known and widely documented problem in cost-effectiveness analyses alongside clinical trials using individual patient-level data. Current methodological research recommends multiple imputation (MI) to deal with missing health outcome data, but there is little guidance on whether MI for multi-attribute questionnaires, such as the EQ-5D-3L, should be carried out at domain or at summary score level. In this paper, we evaluated the impact of imputing individual domains versus imputing index values to deal with missing EQ-5D-3L data using a simulation study and developed recommendations for future practice. We simulated missing data in a patient-level dataset with complete EQ-5D-3L data at one point in time from a large multinational clinical trial (n = 1,814). Different proportions of missing data were generated using a missing at random (MAR) mechanism and three different scenarios were studied. The performance of using each method was evaluated using root mean squared error and mean absolute error of the actual versus predicted EQ-5D-3L indices. In large sample sizes (n > 500) and a missing data pattern that follows mainly unit non-response, imputing domains or the index produced similar results. However, domain imputation became more accurate than index imputation with pattern of missingness following an item non-response. For smaller sample sizes (n < 100), index imputation was more accurate. When MI models were misspecified, both domain and index imputations were inaccurate for any proportion of missing data. The decision between imputing the domains or the EQ-5D-3L index scores depends on the observed missing data pattern and the sample size available for analysis. Analysts conducting this type of exercises should also evaluate the sensitivity of the analysis to the MAR assumption and whether the imputation model is correctly specified.

Search for faint nearby stars

NASA Astrophysics Data System (ADS)

Ruiz, M. T.; Maza, J.; Mendez, R.; Wischnjewsky, M.

1988-09-01

The possibility that the 'missing mass' in the solar neighborhood may be accounted for by the existence in sufficiently great numbers of such very low mass stars as brown dwarfs, as well as very old dead stars now observable as cold, low-luminosity degenerates, is presently addressed observationally with a search through ESO R Survey plates using a stereocomparator. Attention is given to ESO area 439, where four low-luminosity degenerates have been discovered by the present study.

Comparison of methods for dealing with missing values in the EPV-R.

PubMed

Paniagua, David; Amor, Pedro J; Echeburúa, Enrique; Abad, Francisco J

2017-08-01

The development of an effective instrument to assess the risk of partner violence is a topic of great social relevance. This study evaluates the scale of “Predicción del Riesgo de Violencia Grave Contra la Pareja” –Revisada– (EPV-R - Severe Intimate Partner Violence Risk Prediction Scale-Revised), a tool developed in Spain, which is facing the problem of how to treat the high rate of missing values, as is usual in this type of scale. First, responses to the EPV-R in a sample of 1215 male abusers who were reported to the police were used to analyze the patterns of occurrence of missing values, as well as the factor structure. Second, we analyzed the performance of various imputation methods using simulated data that emulates the missing data mechanism found in the empirical database. The imputation procedure originally proposed by the authors of the scale provides acceptable results, although the application of a method based on the Item Response Theory could provide greater accuracy and offers some additional advantages. Item Response Theory appears to be a useful tool for imputing missing data in this type of questionnaire.

A stochastic multiple imputation algorithm for missing covariate data in tree-structured survival analysis.

PubMed

Wallace, Meredith L; Anderson, Stewart J; Mazumdar, Sati

2010-12-20

Missing covariate data present a challenge to tree-structured methodology due to the fact that a single tree model, as opposed to an estimated parameter value, may be desired for use in a clinical setting. To address this problem, we suggest a multiple imputation algorithm that adds draws of stochastic error to a tree-based single imputation method presented by Conversano and Siciliano (Technical Report, University of Naples, 2003). Unlike previously proposed techniques for accommodating missing covariate data in tree-structured analyses, our methodology allows the modeling of complex and nonlinear covariate structures while still resulting in a single tree model. We perform a simulation study to evaluate our stochastic multiple imputation algorithm when covariate data are missing at random and compare it to other currently used methods. Our algorithm is advantageous for identifying the true underlying covariate structure when complex data and larger percentages of missing covariate observations are present. It is competitive with other current methods with respect to prediction accuracy. To illustrate our algorithm, we create a tree-structured survival model for predicting time to treatment response in older, depressed adults. Copyright © 2010 John Wiley & Sons, Ltd.

An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data.

PubMed

Liu, Yuzhe; Gopalakrishnan, Vanathi

2017-03-01

Many clinical research datasets have a large percentage of missing values that directly impacts their usefulness in yielding high accuracy classifiers when used for training in supervised machine learning. While missing value imputation methods have been shown to work well with smaller percentages of missing values, their ability to impute sparse clinical research data can be problem specific. We previously attempted to learn quantitative guidelines for ordering cardiac magnetic resonance imaging during the evaluation for pediatric cardiomyopathy, but missing data significantly reduced our usable sample size. In this work, we sought to determine if increasing the usable sample size through imputation would allow us to learn better guidelines. We first review several machine learning methods for estimating missing data. Then, we apply four popular methods (mean imputation, decision tree, k-nearest neighbors, and self-organizing maps) to a clinical research dataset of pediatric patients undergoing evaluation for cardiomyopathy. Using Bayesian Rule Learning (BRL) to learn ruleset models, we compared the performance of imputation-augmented models versus unaugmented models. We found that all four imputation-augmented models performed similarly to unaugmented models. While imputation did not improve performance, it did provide evidence for the robustness of our learned models.

Artificial Limbs

MedlinePlus

... a number of reasons. Common ones include Circulation problems from atherosclerosis or diabetes. They may cause you to need an amputation. Traumatic injuries, including from traffic accidents and military combat Cancer Birth defects If you are missing ...

Search for new phenomena in events with a photon and missing transverse momentum in p p collisions at s = 8 TeV with the ATLAS detector

DOE PAGES

Aad, G.

2015-01-27

Results of a search for new phenomena in events with an energetic photon and large missing transverse momentum with the ATLAS experiment at the LHC are reported. Data were collected in proton-proton collisions at a center-of-mass energy of 8 TeV and correspond to an integrated luminosity of 20.3 fb -1. The observed data are well described by the expected Standard Model backgrounds. The expected (observed) upper limit on the fiducial cross section for the production of events with a photon and large missing transverse momentum is 6.1 (5.3) fb at 95% confidence level. The exclusion limits are presented on modelsmore » of new phenomena with large extra spatial dimensions, super-symmetric quarks, and direct pair production of dark-matter candidates.« less

Search for supersymmetry in the multijet and missing transverse momentum final state in pp collisions at 13 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.; 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.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; 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.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Mccartin, J.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; Ceard, L.; De Visscher, S.; Delaere, C.; Delcourt, M.; Forthomme, L.; 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.; 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.; 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.; Du, R.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Zhao, J.; Asawatangtrakuldee, C.; Ban, Y.; 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.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Luetic, J.; Micanovic, S.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Abdelalim, A. A.; El-khateeb, E.; 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.; Peltola, T.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; 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.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Merlin, J. A.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulte, J. F.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; 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.; Künsken, A.; Lingemann, J.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asin, I.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; 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.; Kieseler, J.; Kleinwort, C.; Korol, I.; 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.; Trippkewitz, K. D.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Erfle, J.; Garutti, E.; Goebel, K.; Gonzalez, D.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Ott, J.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Sander, C.; Scharf, C.; Schleper, P.; Schlieckau, E.; 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.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; 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.; Schröder, M.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Szillasi, Z.; Bartók, M.; Makovec, A.; 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.; Gupta, 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.; Kumar, A.; 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.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Guchait, M.; Gurtu, A.; Jain, Sa.; Kole, G.; Kumar, S.; Mahakud, B.; Maity, M.; Majumder, G.; Mazumdar, K.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sarkar, T.; Sur, N.; Sutar, B.; Wickramage, N.; Chauhan, S.; Dube, S.; Kapoor, A.; Kothekar, K.; Rane, A.; Sharma, S.; Bakhshiansohi, H.; 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.; 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.; 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. 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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.; 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.; 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.; 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.; Jorda, C.; 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.; 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.; Ruspa, M.; Sacchi, R.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Candelise, V.; 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. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Kim, H.; Brochero Cifuentes, J. A.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, B.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Seo, S. H.; Yang, U.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Yu, I.; Dudenas, V.; 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.; Zolkapli, Z.; Casimiro Linares, E.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; 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.; Khan, W. A.; Khurshid, T.; 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.; 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.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Chtchipounov, L.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Murzin, V.; Oreshkin, V.; Sulimov, V.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Chadeeva, M.; Markin, O.; 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.; 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.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; 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.; Palencia Cortezon, E.; Sanchez Cruz, S.; 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. H.; Barney, D.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Guio, F.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dordevic, M.; Dorney, B.; du Pree, T.; Duggan, D.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Fartoukh, S.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Girone, M.; Glege, F.; Gundacker, S.; Guthoff, M.; Hammer, J.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kirschenmann, H.; Knünz, V.; Kortelainen, M. J.; Kousouris, K.; Krammer, M.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Magini, N.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Sauvan, J. B.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Simon, M.; Sphicas, P.; Steggemann, J.; Stoye, M.; Takahashi, Y.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Wardle, N.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lecomte, P.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; 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.; Rauco, G.; Robmann, P.; Salerno, D.; Yang, Y.; Chen, K. H.; 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.; Tsai, J. f.; Tzeng, Y. M.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Sunar Cerci, D.; Tali, B.; 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.; Vardarlı, F. I.; 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.; 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.; 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.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; 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.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; 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. I.; Henderson, C.; Rumerio, P.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Berry, E.; Cutts, D.; Ferapontov, A.; Garabedian, A.; Hakala, J.; Heintz, U.; Jesus, O.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Breto, G.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Florent, A.; 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.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Malberti, M.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Derdzinski, M.; Gerosa, R.; 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.; 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.; West, C.; Yoo, J.; Anderson, D.; Apresyan, A.; Bendavid, J.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; 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.; Sun, W.; Tan, S. M.; Tao, Z.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; 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.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Diamond, B.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Santra, A.; Weinberg, M.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Kalakhety, H.; Noonan, 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.; Turner, P.; Varelas, N.; Wu, Z.; Zakaria, M.; 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.; Anderson, I.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Osherson, M.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Bruner, C.; Castle, J.; Kenny, R. P., III; Kropivnitskaya, A.; Majumder, D.; Malek, M.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; 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.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. 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.; Dahmes, B.; Evans, A.; 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.; Bartek, R.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Knowlton, D.; Kravchenko, I.; 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.; Chasco, M.; 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.; 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.; Rupprecht, N.; Smith, G.; Taroni, S.; Valls, N.; 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.; Rodenburg, M.; Winer, B. L.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Benedetti, D.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. 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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.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Krutelyov, V.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Woods, N.; CMS Collaboration

2016-07-01

A search for new physics is performed based on all-hadronic events with large missing transverse momentum produced in proton-proton collisions at √{ s} = 13 TeV. The data sample, corresponding to an integrated luminosity of 2.3 fb-1, was collected with the CMS detector at the CERN LHC in 2015. The data are examined in search regions of jet multiplicity, tagged bottom quark jet multiplicity, missing transverse momentum, and the scalar sum of jet transverse momenta. The observed numbers of events in all search regions are found to be consistent with the expectations from standard model processes. Exclusion limits are presented for simplified supersymmetric models of gluino pair production. Depending on the assumed gluino decay mechanism, and for a massless, weakly interacting, lightest neutralino, lower limits on the gluino mass from 1440 to 1600 GeV are obtained, significantly extending previous limits.

Search for supersymmetry in pp collisions at √7 TeV in events with two photons and missing transverse energy.

PubMed

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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

Search for squarks and gluinos with the ATLAS detector in final states with jets and missing transverse momentum using TeV proton-proton collision data

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Khalek, S. Abdel; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Almond, J.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Gonzalez, B. Alvarez; Alviggi, M. G.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baas, A.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Mayes, J. Backus; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, M.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Garcia, J. A. Benitez; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Berghaus, F.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertsche, D.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Bessner, M. F.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; De Mendizabal, J. Bilbao; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boddy, C. R.; Boehler, M.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. 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C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Urbán, S. Cabrera; Caforio, D.; Cakir, O.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Toro, R. Camacho; Camarda, S.; Cameron, D.; Caminada, L. M.; Armadans, R. Caminal; Campana, S.; Campanelli, M.; Campoverde, A.; Canale, V.; Canepa, A.; Bret, M. Cano; Cantero, J.; Cantrill, R.; Cao, T.; Garrido, M. D. M. Capeans; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Castaneda-Miranda, E.; Castelli, A.; Gimenez, V. Castillo; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Chau, C. C.; Barajas, C. A. Chavez; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; El Moursli, R. Cherkaoui; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Cole, B.; Cole, S.; Colijn, A. P.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Muiño, P. Conde; Coniavitis, E.; Conidi, M. C.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Ortuzar, M. Crispin; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuciuc, C.-M.; Donszelmann, T. Cuhadar; Cummings, J.; Curatolo, M.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Hoffmann, M. Dano; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J. A.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Nooij, L.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Deliot, F.; Delitzsch, C. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Pietra, M. 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A.; Duda, D.; Dudarev, A.; Dudziak, F.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Durglishvili, A.; Dwuznik, M.; Dyndal, M.; Ebke, J.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernis, G.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. 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2014-09-01

A search for squarks and gluinos in final states containing high- p T jets, missing transverse momentum and no electrons or muons is presented. The data were recorded in 2012 by the ATLAS experiment in TeV proton-proton collisions at the Large Hadron Collider, with a total integrated luminosity of 20 .3 fb-1. Results are interpreted in a variety of simplified and specific supersymmetry-breaking models assuming that R-parity is conserved and that the lightest neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 1330 GeV for a simplified model incorporating only a gluino and the lightest neutralino. For a simplified model involving the strong production of first- and second-generation squarks, squark masses below 850 GeV (440 GeV) are excluded for a massless lightest neutralino, assuming mass degenerate (single light-flavour) squarks. In mSUGRA/CMSSM models with tan β = 30, A 0 = -2 m 0 and μ > 0, squarks and gluinos of equal mass are excluded for masses below 1700 GeV. Additional limits are set for non-universal Higgs mass models with gaugino mediation and for simplified models involving the pair production of gluinos, each decaying to a top squark and a top quark, with the top squark decaying to a charm quark and a neutralino. These limits extend the region of supersymmetric parameter space excluded by previous searches with the ATLAS detector. [Figure not available: see fulltext.

Genetic identification of missing persons: DNA analysis of human remains and compromised samples.

PubMed

Alvarez-Cubero, M J; Saiz, M; Martinez-Gonzalez, L J; Alvarez, J C; Eisenberg, A J; Budowle, B; Lorente, J A

2012-01-01

Human identification has made great strides over the past 2 decades due to the advent of DNA typing. Forensic DNA typing provides genetic data from a variety of materials and individuals, and is applied to many important issues that confront society. Part of the success of DNA typing is the generation of DNA databases to help identify missing persons and to develop investigative leads to assist law enforcement. DNA databases house DNA profiles from convicted felons (and in some jurisdictions arrestees), forensic evidence, human remains, and direct and family reference samples of missing persons. These databases are essential tools, which are becoming quite large (for example the US Database contains 10 million profiles). The scientific, governmental and private communities continue to work together to standardize genetic markers for more effective worldwide data sharing, to develop and validate robust DNA typing kits that contain the reagents necessary to type core identity genetic markers, to develop technologies that facilitate a number of analytical processes and to develop policies to make human identity testing more effective. Indeed, DNA typing is integral to resolving a number of serious criminal and civil concerns, such as solving missing person cases and identifying victims of mass disasters and children who may have been victims of human trafficking, and provides information for historical studies. As more refined capabilities are still required, novel approaches are being sought, such as genetic testing by next-generation sequencing, mass spectrometry, chip arrays and pyrosequencing. Single nucleotide polymorphisms offer the potential to analyze severely compromised biological samples, to determine the facial phenotype of decomposed human remains and to predict the bioancestry of individuals, a new focus in analyzing this type of markers. Copyright © 2012 S. Karger AG, Basel.

Problems related to menstruation amongst adolescent girls.

PubMed

Sharma, Pragya; Malhotra, Chetna; Taneja, D K; Saha, Renuka

2008-02-01

To study the types and frequency of problems related to menstruation in adolescent girls and the effect of these problems on daily routine. Girls in the age group 13-19 years who had had menarche for at least one year at the time of study. 198 adolescent girls have been studied. Data was collected by personal interviews on a pre-tested, semi-structured questionnaire. The questions covered menstrual problems, regularity of menses in last three cycles of menstruation and the effect of these problems on the daily routine. Analysis was done using SPSS version 12. Percentages were calculated for drawing inferences. More than a third (35.9%) of the study subjects were in the age group 13-15 years followed by 17-19 years, 15-17 years respectively. Mean age of study participants was calculated to be 16.2 years. Dysmenorrhea (67.2%) was the commonest problem and (63.1%) had one or the other symptoms of Pre-menstrual syndrome (PMS). Other related problems were present in 55.1% of study subjects. Daily routine of 60% girls was affected due to prolonged bed rest, missed social activities/commitments, disturbed sleep and decreased appetite. 17.24% had to miss a class and 25% had to abstain from work. Mothers and friends were the most common source of information on the issue. Screen adolescent girls for menstruation related problems and provide them with counseling services and relevant information on possible treatment options. Besides, there is a need to emphasize on designing menstrual health programmes for adolescents.

Search for physics beyond the standard model in events with two leptons of same sign, missing transverse momentum, and jets in proton-proton collisions at √{s} = 13 {TeV}

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; 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.; Gonzalez, J. Suarez; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Zeid, S. Abu; 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.; Velde, C. Vander; 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.; Marono, M. Vidal; Wertz, S.; Beliy, N.; Júnior, W. L. Aldá; Alves, F. L.; Alves, G. A.; Brito, L.; Junior, M. Correa Martins; Hensel, C.; Moraes, A.; Pol, M. E.; Teles, P. Rebello; Chagas, E. Belchior Batista Das; Carvalho, W.; Chinellato, J.; Custódio, A.; Costa, E. M. Da; Silveira, G. G. Da; Damiao, D. De Jesus; De Souza, S. Fonseca; Guativa, L. M. Huertas; Malbouisson, H.; De Almeida, M. Melo; Herrera, C. Mora; Mundim, L.; Nogima, H.; Santoro, A.; Sznajder, A.; Manganote, E. J. Tonelli; De Araujo, F. Torres Da E. Silva; Pereira, A. Vilela; Ahuja, S.; Bernardes, C. A.; Tomei, T. R. Fernandez Perez; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Abad, D. Romero; Vargas, J. C. Ruiz; 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.; 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.; Sierra, L. F. Chaparro; Florez, C.; Hernández, C. F. González; Alvarez, J. D. Ruiz; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Cipriano, P. M. Ribeiro; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Jarrin, E. Carrera; Assran, Y.; Elgammal, S.; Mahrous, A.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; de Monchenault, G. Hamel; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Davignon, O.; de Cassagnac, R. Granier; Jo, M.; Lisniak, S.; Lobanov, A.; Blanco, J. Martin; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Leiton, A. G. Stahl; Strebler, T.; Yilmaz, Y.; Zabi, 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.; Bihan, A.-C. Le; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; Depasse, P.; Mamouni, H. El; 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.; Donckt, M. Vander; Viret, S.; Khvedelidze, A.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Albert, A.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; 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.; Martin, M. Aldaya; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Anuar, A. A. Bin; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Pardos, C. Diez; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garcia, J. Garay; Geiser, A.; Gizhko, A.; Luyando, J. M. Grados; 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.; Vignali, M. Centis; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; 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.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Csanad, M.; Filipovic, N.; Pasztor, G.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Dhingra, N.; Bhawandeep, U.; 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.; Chowdhury, S. Roy; 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.; Parida, 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.; Tadavani, E. Eskandari; Etesami, S. M.; Khakzad, M.; Najafabadi, M. Mohammadi; Naseri, M.; Mehdiabadi, S. Paktinat; Hosseinabadi, F. Rezaei; 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.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Guiducci, L.; Marcellini, S.; Masetti, G.; 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.; de Fatis, T. Tabarelli; Buontempo, S.; Cavallo, N.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Khan, W. A.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; De Oliveira, A. Carvalho Antunes; Checchia, P.; Manzano, P. De Castro; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Fallavollita, F.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Solestizi, L. Alunni; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Mariani, V.; Menichelli, M.; Saha, 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.; Angioni, G. L. Pinna; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, J.; Lee, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Kim, H.; Moon, D. H.; Oh, G.; Cifuentes, J. A. Brochero; 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.; Ali, M. A. B. Md; Idris, F. Mohamad; Abdullah, W. A. T. Wan; Yusli, M. N.; Zolkapli, Z.; Castilla-Valdez, H.; Cruz-Burelo, E. De La; Cruz, I. Heredia-De La; Lopez-Fernandez, R.; Guisao, J. Mejia; Sanchez-Hernandez, A.; Moreno, S. Carrillo; Barrera, C. Oropeza; Valencia, F. Vazquez; Pedraza, I.; Ibarguen, H. A. Salazar; Estrada, C. Uribe; Pineda, A. Morelos; 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.; Silva, C. Beirão Da Cruz E.; Calpas, B.; Di Francesco, A.; Faccioli, P.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Iglesias, L. Lloret; Nemallapudi, M. V.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Afanasiev, S.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Palichik, V.; Perelygin, V.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Stepennov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Bylinkin, A.; Chistov, R.; Danilov, M.; Parygin, P.; Philippov, D.; Polikarpov, S.; Tarkovskii, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Blinov, V.; Skovpen, Y.; Shtol, D.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Maestre, J. Alcaraz; Luna, M. Barrio; Cerrada, M.; Colino, N.; Cruz, B. De La; Peris, A. Delgado; Del Valle, A. Escalante; Bedoya, C. Fernandez; Ramos, J. P. Fernández; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Lopez, O. Gonzalez; Lopez, S. Goy; Hernandez, J. M.; Josa, M. I.; Yzquierdo, A. Pérez-Calero; Pelayo, J. Puerta; Olmeda, A. Quintario; Redondo, I.; Romero, L.; Soares, M. S.; Fernández, A. lvarez; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Erice, C.; Menendez, J. Fernandez; Caballero, I. Gonzalez; Fernández, J. R. González; Cortezon, E. Palencia; Cruz, S. Sanchez; Andrés, I. Suárez; Vischia, P.; Garcia, J. M. Vizan; Cabrillo, I. J.; Calderon, A.; Quero, B. Chazin; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Virto, A. Lopez; Marco, J.; Rivero, C. Martinez; Arbol, P. Martinez Ruiz del; Matorras, F.; Gomez, J. Piedra; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Cortabitarte, R. Vilar; Abbaneo, D.; Auffray, E.; Baillon, P.; Ball, A. H.; Barney, D.; Bianco, M.; Bloch, P.; Bocci, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; Chapon, E.; Chen, Y.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Karacheban, O.; Kieseler, J.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. 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2017-09-01

A data sample of events from proton-proton collisions with two isolated same-sign leptons, missing transverse momentum, and jets is studied in a search for signatures of new physics phenomena by the CMS Collaboration at the LHC. The data correspond to an integrated luminosity of 35.9 {fb}^{- {1}}, and a center-of-mass energy of 13 {TeV}. The properties of the events are consistent with expectations from standard model processes, and no excess yield is observed. Exclusion limits at 95% confidence level are set on cross sections for the pair production of gluinos, squarks, and same-sign top quarks, as well as top-quark associated production of a heavy scalar or pseudoscalar boson decaying to top quarks, and on the standard model production of events with four top quarks. The observed lower mass limits are as high as 1500 {GeV} for gluinos, 830 {GeV} for bottom squarks. The excluded mass range for heavy (pseudo)scalar bosons is 350-360 (350-410) {GeV}. Additionally, model-independent limits in several topological regions are provided, allowing for further interpretations of the results.

Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV

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

Sirunyan, Albert M; et al.

A search for supersymmetry is presented based on multijet events with large missing transverse momentum produced in proton-proton collisions at a center-of-mass energy of sqrt(s)=13 TeV. The data, corresponding to an integrated luminosity of 35.9 inverse femtobarns, were collected with the CMS detector at the CERN LHC in 2016. The analysis utilizes four-dimensional exclusive search regions defined in terms of the number of jets, the number of tagged bottom quark jets, the scalar sum of jet transverse momenta, and the magnitude of the vector sum of jet transverse momenta. No evidence for a significant excess of events is observed relativemore » to the expectation from the standard model. Limits on the cross sections for the pair production of gluinos and squarks are derived in the context of simplified models. Assuming the lightest supersymmetric particle to be a weakly interacting neutralino, 95% confidence level lower limits on the gluino mass as large as 1800 to 1960 GeV are derived, and on the squark mass as large as 960 to 1390 GeV, depending on the production and decay scenario.« less

Search for supersymmetry in a final state containing two photons and missing transverse momentum in [Formula: see text] = 13 TeV [Formula: see text] collisions at the LHC using the ATLAS detector.

PubMed

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2016-01-01

A search has been made for supersymmetry in a final state containing two photons and missing transverse momentum using the ATLAS detector at the Large Hadron Collider. The search makes use of [Formula: see text] of proton-proton collision data collected at a centre-of-mass energy of 13 TeV in 2015. Using a combination of data-driven and Monte-Carlo-based approaches, the Standard Model background is estimated to be [Formula: see text] events. No events are observed in the signal region; considering the expected background and its uncertainty, this observation implies a model-independent 95 % CL upper limit of 0.93 fb (3.0 events) on the visible cross section due to physics beyond the Standard Model. In the context of a generalized model of gauge-mediated supersymmetry breaking with a bino-like next-to-lightest supersymmetric particle, this leads to a lower limit of 1650 GeV on the mass of a degenerate octet of gluino states, independent of the mass of the lighter bino-like neutralino.

Search for supersymmetry in a final state containing two photons and missing transverse momentum in \\varvec{√{s}} = 13 TeV \\varvec{pp} collisions at the LHC using the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; 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.; Gonzalez, B. Alvarez; Piqueras, D. Álvarez; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Navarro, L. Barranco; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bylund, O. Bessidskaia; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; De Mendizabal, J. Bilbao; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; 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.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Sola, J. D. Bossio; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Madden, W. D. Breaden; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; de Renstrom, P. A. Bruckman; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Urbán, S. Cabrera; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Lopez, S. Calvente; Calvet, D.; Calvet, S.; Calvet, T. P.; Toro, R. Camacho; Camarda, S.; Camarri, P.; Cameron, D.; Armadans, R. Caminal; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Bret, M. Cano; Cantero, J.; Cao, T.; Garrido, M. D. M. Capeans; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Gimenez, V. Castillo; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Alberich, L. Cerda; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Barajas, C. A. Chavez; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Moursli, R. Cherkaoui El; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Muiño, P. Conde; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Ortuzar, M. Crispin; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Donszelmann, T. Cuhadar; Cummings, J.; Curatolo, M.; Cúth, J.; Czirr, H.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'Onofrio, M.; De Sousa, M. J. Da Cunha Sargedas; Via, C. Da; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Hoffmann, M. Dano; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, M.; 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 Regie, J. B. De Vivie; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Cornell, S. Díez; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; Kacimi, M. El; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Giannelli, M. 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2016-09-01

A search has been made for supersymmetry in a final state containing two photons and missing transverse momentum using the ATLAS detector at the Large Hadron Collider. The search makes use of 3.2{ fb^{-1}} of proton-proton collision data collected at a centre-of-mass energy of 13 TeV in 2015. Using a combination of data-driven and Monte-Carlo-based approaches, the Standard Model background is estimated to be 0.27^{+0.22}_{-0.10} events. No events are observed in the signal region; considering the expected background and its uncertainty, this observation implies a model-independent 95 % CL upper limit of 0.93 fb (3.0 events) on the visible cross section due to physics beyond the Standard Model. In the context of a generalized model of gauge-mediated supersymmetry breaking with a bino-like next-to-lightest supersymmetric particle, this leads to a lower limit of 1650 GeV on the mass of a degenerate octet of gluino states, independent of the mass of the lighter bino-like neutralino.

Search for dark matter in events with heavy quarks and missing transverse momentum in [Formula: see text] collisions with the ATLAS detector.

PubMed

Aad, G; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Agatonovic-Jovin, T; Aguilar-Saavedra, J A; Agustoni, M; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimoto, G; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Alimonti, G; Alio, L; Alison, J; Allbrooke, B M M; Allison, L J; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Altheimer, A; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amaral Coutinho, Y; Amelung, C; Amidei, D; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amram, N; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Anduaga, X S; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; 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This article reports on a search for dark matter pair production in association with bottom or top quarks in [Formula: see text] of [Formula: see text] collisions collected at [Formula: see text] TeV by the ATLAS detector at the LHC. Events with large missing transverse momentum are selected when produced in association with high-momentum jets of which one or more are identified as jets containing [Formula: see text]-quarks. Final states with top quarks are selected by requiring a high jet multiplicity and in some cases a single lepton. The data are found to be consistent with the Standard Model expectations and limits are set on the mass scale of effective field theories that describe scalar and tensor interactions between dark matter and Standard Model particles. Limits on the dark-matter-nucleon cross-section for spin-independent and spin-dependent interactions are also provided. These limits are particularly strong for low-mass dark matter. Using a simplified model, constraints are set on the mass of dark matter and of a coloured mediator suitable to explain a possible signal of annihilating dark matter.

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)

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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 dark matter in events with heavy quarks and missing transverse momentum in pp collisions with the ATLAS detector

DOE PAGES

Aad, G.

2015-02-24

This article reports on a search for dark matter pair production in association with bottom or top quarks in 20.3 fb –1 of pp collisions collected at √s=8 TeV by the ATLAS detector at the LHC. Events with large missing transverse momentum are selected when produced in association with high-momentum jets of which one or more are identified as jets containing b-quarks. Final states with top quarks are selected by requiring a high jet multiplicity and in some cases a single lepton. The data are found to be consistent with the Standard Model expectations and limits are set on themore » mass scale of effective field theories that describe scalar and tensor interactions between dark matter and Standard Model particles. Limits on the dark-matter–nucleon cross-section for spin-independent and spin-dependent interactions are also provided. These limits are particularly strong for low-mass dark matter. Using a simplified model, constraints are set on the mass of dark matter and of a colored mediator suitable to explain a possible signal of annihilating dark matter.« 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

Hard matching for boosted tops at two loops

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

Hoang, Andre H.; Pathak, Aditya; Pietrulewicz, Piotr

2015-12-10

Here, cross sections for top quarks provide very interesting physics opportunities, being both sensitive to new physics and also perturbatively tractable due to the large top quark mass. Rigorous factorization theorems for top cross sections can be derived in several kinematic scenarios, including the boosted regime in the peak region that we consider here. In the context of the corresponding factorization theorem for e +e – collisions we extract the last missing ingredient that is needed to evaluate the cross section differential in the jet-mass at two-loop order, namely the matching coefficient at the scale μ≃m t. Our extraction alsomore » yields the final ingredients needed to carry out logarithmic re-summation at next-to-next-to-leading logarithmic order (or N 3LL if we ignore the missing 4-loop cusp anomalous dimension). This coefficient exhibits an amplitude level rapidity logarithm starting at O(α 2 s) due to virtual top quark loops, which we treat using rapidity renormalization group (RG) evolution. Interestingly, this rapidity RG evolution appears in the matching coefficient between two effective theories around the heavy quark mass scale μ ≃ m t.« less

Albinism

MedlinePlus

... normal skin and hair Patches of missing skin color Many forms of albinism are associated with the following symptoms: Crossed eyes Light sensitivity Rapid eye movements Vision problems, or functional blindness Exams and Tests Genetic testing offers the most ...

Tooth formation - delayed or absent

MedlinePlus

... missing teeth they never developed. Cosmetic or orthodontic dentistry can correct this problem. Causes Specific diseases can ... process. In: Dean JA, ed. McDonald and Avery's Dentistry for the Child and Adolescent . 10th ed. St. ...

Multi-view non-negative tensor factorization as relation learning in healthcare data.

PubMed

Hang Wu; Wang, May D

2016-08-01

Discovering patterns in co-occurrences data between objects and groups of concepts is a useful task in many domains, such as healthcare data analysis, information retrieval, and recommender systems. These relational representations come from objects' behaviors in different views, posing a challenging task of integrating information from these views to uncover the shared latent structures. The problem is further complicated by the high dimension of data and the large ratio of missing data. We propose a new paradigm of learning semantic relations using tensor factorization, by jointly factorizing multi-view tensors and searching for a consistent underlying semantic space across each views. We formulate the idea as an optimization problem and propose efficient optimization algorithms, with a special treatment of missing data as well as high-dimensional data. Experiments results show the potential and effectiveness of our algorithms.

Case report of unexplained hypocalcaemia in a slightly haemolysed sample.

PubMed

Cornes, Michael

2017-06-15

The case presented highlights a common pre-analytical problem identified in the laboratory that was initially missed. It concerns a young, generally healthy adult patient with no significant medical history and no significant family history. They presented with common flu like symptoms to their primary care clinician who considered this was most likely a viral problem that would pass with time. The clinician, however, did some routine bloods to reassure the patient despite a lack of clinical indication. When the sample was analysed the sample was haemolysed with strikingly low calcium. This led to the patient being called into hospital for urgent repeat investigations, all of which turned out to be within normal ranges. On further investigation the original sample was found to be contaminated. This result would normally have been flagged but was missed due to the complication of haemolysis.

Accelerating electron tomography reconstruction algorithm ICON with GPU.

PubMed

Chen, Yu; Wang, Zihao; Zhang, Jingrong; Li, Lun; Wan, Xiaohua; Sun, Fei; Zhang, Fa

2017-01-01

Electron tomography (ET) plays an important role in studying in situ cell ultrastructure in three-dimensional space. Due to limited tilt angles, ET reconstruction always suffers from the "missing wedge" problem. With a validation procedure, iterative compressed-sensing optimized NUFFT reconstruction (ICON) demonstrates its power in the restoration of validated missing information for low SNR biological ET dataset. However, the huge computational demand has become a major problem for the application of ICON. In this work, we analyzed the framework of ICON and classified the operations of major steps of ICON reconstruction into three types. Accordingly, we designed parallel strategies and implemented them on graphics processing units (GPU) to generate a parallel program ICON-GPU. With high accuracy, ICON-GPU has a great acceleration compared to its CPU version, up to 83.7×, greatly relieving ICON's dependence on computing resource.

Analyzing partially missing confounder information in comparative effectiveness and safety research of therapeutics.

PubMed

Toh, Sengwee; García Rodríguez, Luis A; Hernán, Miguel A

2012-05-01

Electronic healthcare databases are commonly used in comparative effectiveness and safety research of therapeutics. Many databases now include additional confounder information in a subset of the study population through data linkage or data collection. We described and compared existing methods for analyzing such datasets. Using data from The Health Improvement Network and the relation between non-steroidal anti-inflammatory drugs and upper gastrointestinal bleeding as an example, we employed several methods to handle partially missing confounder information. The crude odds ratio (OR) of upper gastrointestinal bleeding was 1.50 (95% confidence interval: 0.98, 2.28) among selective cyclo-oxygenase-2 inhibitor initiators (n = 43 569) compared with traditional non-steroidal anti-inflammatory drug initiators (n = 411 616). The OR dropped to 0.81 (0.52, 1.27) upon adjustment for confounders recorded for all patients. When further considering three additional variables missing in 22% of the study population (smoking, alcohol consumption, body mass index), the OR was between 0.80 and 0.83 for the missing-category approach, the missing-indicator approach, single imputation by the most common category, multiple imputation by chained equations, and propensity score calibration. The OR was 0.65 (0.39, 1.09) and 0.67 (0.38, 1.16) for the unweighted and the inverse probability weighted complete-case analysis, respectively. Existing methods for handling partially missing confounder data require different assumptions and may produce different results. The unweighted complete-case analysis, the missing-category/indicator approach, and single imputation require often unrealistic assumptions and should be avoided. In this study, differences across methods were not substantial, likely due to relatively low proportion of missingness and weak confounding effect by the three additional variables upon adjustment for other variables. Copyright © 2012 John Wiley & Sons, Ltd.

Injury risk and noise exposure in firefighter training operations

PubMed Central

Neitzel, Richard L.; Long, Rachel; Sun, Kan; Sayler, Stephanie; von Thaden, Terry L.

2016-01-01

Introduction Firefighters have high rate of injuries and illnesses, as well as exposures to high levels of noise. This study explored the relationship between noise exposure and injury among firefighters. Methods We recruited firefighters undergoing vehicle extrication and structural collapse emergency response training at a highly realistic training facility. Demographics, health status, body mass index, and history of serious injuries (i.e., injuries requiring first aid treatment, treatment in a medical clinic or office, or treatment at a hospital) were assessed at baseline, and daily activities, injury events, and near-misses were assessed daily using surveys. Participants' noise exposures were monitored for one 24-hour period using noise dosimeters. We used a mixed-effects logistic regression model to estimate the odds of injury events and near-misses associated with noise exposure as an independent variable. Results Of 56 subjects, twenty (36%) reported that they had ever suffered a serious injury during firefighting activities, and nine (16%) reported a serious injury within the past year. We estimated rates of 6.6 lifetime serious injuries per 100 FTE 16.1 serious injuries per 100 FTE within the past year. Our models indicated a significant increase in injury events and near misses among those with higher BMI, and as well as a dose-response relationship between near-misses/injuries and increasing noise levels. Noise levels >90 dBA in the 30 min prior to time of injury or near-miss were associated with substantially increased odds ratios for injury or near-miss. Our models further indicated that perceived job demands were significantly associated with increased risk of injury or near-miss. Conclusion Our results suggest that noise exposures may need to be incorporated into injury prevention programs for firefighters to reduce injuries among this high-risk occupational group. PMID:26712895

Network reconstruction via graph blending

NASA Astrophysics Data System (ADS)

Estrada, Rolando

2016-05-01

Graphs estimated from empirical data are often noisy and incomplete due to the difficulty of faithfully observing all the components (nodes and edges) of the true graph. This problem is particularly acute for large networks where the number of components may far exceed available surveillance capabilities. Errors in the observed graph can render subsequent analyses invalid, so it is vital to develop robust methods that can minimize these observational errors. Errors in the observed graph may include missing and spurious components, as well fused (multiple nodes are merged into one) and split (a single node is misinterpreted as many) nodes. Traditional graph reconstruction methods are only able to identify missing or spurious components (primarily edges, and to a lesser degree nodes), so we developed a novel graph blending framework that allows us to cast the full estimation problem as a simple edge addition/deletion problem. Armed with this framework, we systematically investigate the viability of various topological graph features, such as the degree distribution or the clustering coefficients, and existing graph reconstruction methods for tackling the full estimation problem. Our experimental results suggest that incorporating any topological feature as a source of information actually hinders reconstruction accuracy. We provide a theoretical analysis of this phenomenon and suggest several avenues for improving this estimation problem.

From Addition to Multiplication ... and Back: The Development of Students' Additive and Multiplicative Reasoning Skills

ERIC Educational Resources Information Center

Van Dooren, Wim; De Bock, Dirk; Verschaffel, Lieven

2010-01-01

This study builds on two lines of research that have so far developed largely separately: the use of additive methods to solve proportional word problems and the use of proportional methods to solve additive word problems. We investigated the development with age of both kinds of erroneous solution methods. We gave a test containing missing-value…

Pairing Nurses and Social Workers in Schools: North Carolina's School-Based Child and Family Support Teams

ERIC Educational Resources Information Center

Gifford, Elizabeth J.; Wells, Rebecca; Bai, Yu; Troop, Tony O.; Miller, Shari; Babinski, Leslie M.

2010-01-01

When children are struggling in school, underlying causes often include physical or behavioral health problems, poverty, abuse, and/or neglect. Children's poor physical health status has been linked to deficits in memory and reading ability. Children with behavioral problems are much more likely than others to have lower grades, miss school, be…

The Mainz Neutrino Mass Experiment - New Results and Perspectives

NASA Astrophysics Data System (ADS)

Bonn, J.; Bornschein, B.; Bornschein, L.; Fickinger, L.; Flatt, B.; Kraus, Ch.; Otten, E. W.; Schall, J. P.; Ulrich, H.; Weinheimer, Ch.; Kazachenko, O.; Kovalik, A.

2002-12-01

Non-zero neutrino masses, strongly favoured by the recent atmospheric and solar neutrino experiments, have strong consequences for particle physics as well as for astrophysics and cosmology. The investigation of the tritium β spectrum near its endpoint measures the mass of the "electron neutrino m(νe)" (m2 (ν e ) = Σ |Uei |2 mi2 with neutrino mixing matrix U and neutrino mass eigenstates mi) and is the most sensitive of these so-called direct methods providing information complementary to the searches for neutrinoless double β decay. Tritium β decay is the ideal method to distinguish between hierarchical and degenerate neutrino mass models. Furthermore, neutrino masses up to about 1 eV/c2 are especially interesting for cosmology because of their contribution to the missing dark matter in the universe...

Search for dark matter at √{s}=13 TeV in final states containing an energetic photon and large missing transverse momentum with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; 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.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; 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.; Aubry, L.; 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.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-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.; 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.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; 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.; Burckhart, H.; 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, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; 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.; Czirr, H.; 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.; Davies, M.; 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.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Bello, F. A.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. 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2017-06-01

Results of a search for physics beyond the Standard Model in events containing an energetic photon and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider are reported. As the number of events observed in data, corresponding to an integrated luminosity of 36.1 fb^{-1} of proton-proton collisions at a centre-of-mass energy of 13 TeV, is in agreement with the Standard Model expectations, model-independent limits are set on the fiducial cross section for the production of events in this final state. Exclusion limits are also placed in models where dark-matter candidates are pair-produced. For dark-matter production via an axial-vector or a vector mediator in the s-channel, this search excludes mediator masses below 750-1200 GeV for dark-matter candidate masses below 230-480 GeV at 95% confidence level, depending on the couplings. In an effective theory of dark-matter production, the limits restrict the value of the suppression scale M_{*} to be above 790 GeV at 95% confidence level. A limit is also reported on the production of a high-mass scalar resonance by processes beyond the Standard Model, in which the resonance decays to Zγ and the Z boson subsequently decays into neutrinos.

Search for dark matter at [Formula: see text] in final states containing an energetic photon and large missing transverse momentum with the ATLAS detector.

PubMed

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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; 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; 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

2017-01-01

Results of a search for physics beyond the Standard Model in events containing an energetic photon and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider are reported. As the number of events observed in data, corresponding to an integrated luminosity of 36.1 fb[Formula: see text]  of proton-proton collisions at a centre-of-mass energy of [Formula: see text], is in agreement with the Standard Model expectations, model-independent limits are set on the fiducial cross section for the production of events in this final state. Exclusion limits are also placed in models where dark-matter candidates are pair-produced. For dark-matter production via an axial-vector or a vector mediator in the s -channel, this search excludes mediator masses below 750-[Formula: see text] for dark-matter candidate masses below 230-[Formula: see text] at 95% confidence level, depending on the couplings. In an effective theory of dark-matter production, the limits restrict the value of the suppression scale [Formula: see text] to be above [Formula: see text] at 95% confidence level. A limit is also reported on the production of a high-mass scalar resonance by processes beyond the Standard Model, in which the resonance decays to [Formula: see text] and the Z boson subsequently decays into neutrinos.

Search for a scalar partner of the top quark in the jets plus missing transverse momentum final state at $$\\sqrt{s}=13 $$ TeV with the ATLAS detector

DOE PAGES

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

2017-12-15

A search for pair production of a scalar partner of the top quark in events with four or more jets plus missing transverse momentum is presented. Here, an analysis of 36.1 fb -1 ofmore » $$ \\sqrt{s}=13 $$ TeV proton-proton collisions collected using the ATLAS detector at the LHC yields no significant excess over the expected Standard Model background. To interpret the results a simplified supersymmetric model is used where the top squark is assumed to decay via $$\\sim\\atop{t}$$ 1→t(*)$$\\sim\\atop{χ}$$ $$0\\atop{1}$$ and $$\\sim\\atop{t}$$ 1→b$$\\sim\\atop{χ}$$ $$±\\atop{1}$$→bW(*)$$\\sim\\atop{χ}$$ $$0\\atop{1}$$, where χ 1 0 (χ 1 ± ) denotes the lightest neutralino (chargino). Exclusion limits are placed in terms of the top-squark and neutralino masses. Assuming a branching ratio of 100% to t$$\\sim\\atop{χ}$$ $$0\\atop{1}$$, top-squark masses in the range 450–1000 GeV are excluded for $$\\sim\\atop{χ}$$ $$0\\atop{1}$$ masses below 160 GeV. In the case where m$$\\sim\\atop{t}$$ 1-m t+m $$\\sim\\atop{χ}$$ $$0\\atop{1}$$ , top-squark masses in the range 235–590 GeV are excluded.« less

Search for a scalar partner of the top quark in the jets plus missing transverse momentum final state at $$\\sqrt{s}=13 $$ TeV with the ATLAS detector

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

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

A search for pair production of a scalar partner of the top quark in events with four or more jets plus missing transverse momentum is presented. Here, an analysis of 36.1 fb -1 ofmore » $$ \\sqrt{s}=13 $$ TeV proton-proton collisions collected using the ATLAS detector at the LHC yields no significant excess over the expected Standard Model background. To interpret the results a simplified supersymmetric model is used where the top squark is assumed to decay via $$\\sim\\atop{t}$$ 1→t(*)$$\\sim\\atop{χ}$$ $$0\\atop{1}$$ and $$\\sim\\atop{t}$$ 1→b$$\\sim\\atop{χ}$$ $$±\\atop{1}$$→bW(*)$$\\sim\\atop{χ}$$ $$0\\atop{1}$$, where χ 1 0 (χ 1 ± ) denotes the lightest neutralino (chargino). Exclusion limits are placed in terms of the top-squark and neutralino masses. Assuming a branching ratio of 100% to t$$\\sim\\atop{χ}$$ $$0\\atop{1}$$, top-squark masses in the range 450–1000 GeV are excluded for $$\\sim\\atop{χ}$$ $$0\\atop{1}$$ masses below 160 GeV. In the case where m$$\\sim\\atop{t}$$ 1-m t+m $$\\sim\\atop{χ}$$ $$0\\atop{1}$$ , top-squark masses in the range 235–590 GeV are excluded.« less

Transverse polarization of Σ+(1189) in photoproduction on a hydrogen target in CLAS

NASA Astrophysics Data System (ADS)

Nepali, C. S.; Amaryan, M.; Adhikari, K. P.; Aghasyan, M.; Anefalos Pereira, S.; Baghdasaryan, H.; Ball, J.; Battaglieri, M.; Batourine, V.; Bedlinskiy, I.; Biselli, A. S.; Bono, J.; Boiarinov, S.; Briscoe, W. J.; Bültmann, S.; Burkert, V. D.; Carman, D. S.; Celentano, A.; Chandavar, S.; Charles, G.; Cole, P. L.; Collins, P.; Contalbrigo, M.; Crede, V.; Dashyan, N.; De Vita, R.; De Sanctis, E.; Deur, A.; Djalali, C.; Doughty, D.; Dupre, R.; Alaoui, A. El; Fassi, L. El; Fedotov, G.; Fegan, S.; Fersch, R.; Fleming, J. A.; Gabrielyan, M. Y.; Gevorgyan, N.; Giovanetti, K. L.; Girod, F. X.; Glazier, D. I.; Goetz, J. T.; Gohn, W.; Golovatch, E.; Gothe, R. W.; Griffioen, K. A.; Guidal, M.; Guler, N.; Hafidi, K.; Hakobyan, H.; Hanretty, C.; Harrison, N.; Heddle, D.; Hicks, K.; Ho, D.; Holtrop, M.; Hyde, C. E.; Ilieva, Y.; Ireland, D. G.; Ishkhanov, B. S.; Isupov, E. L.; Jo, H. S.; Keller, D.; Khandaker, M.; Khetarpal, P.; Kim, A.; Kim, W.; Klein, A.; Klein, F. J.; Koirala, S.; Kubarovsky, V.; Kuhn, S. E.; Kuleshov, S. V.; Kvaltine, N. D.; Lu, H. Y.; MacGregor, I. J. D.; Markov, N.; Mayer, M.; McKinnon, B.; Mineeva, T.; Mirazita, M.; Mokeev, V.; Montgomery, R. A.; Munevar, E.; Munoz Camacho, C.; Nadel-Turonski, P.; Niccolai, S.; Niculescu, G.; Niculescu, I.; Osipenko, M.; Ostrovidov, A. I.; Pappalardo, L. L.; Paremuzyan, R.; Park, K.; Park, S.; Pasyuk, E.; Phelps, E.; Phillips, J. J.; Pisano, S.; Pogorelko, O.; Pozdniakov, S.; Price, J. W.; Procureur, S.; Protopopescu, D.; Puckett, A. J. R.; Raue, B. A.; Rimal, D.; Ripani, M.; Ritchie, B. G.; Rosner, G.; Rossi, P.; Sabatié, F.; Saini, M. S.; Salgado, C.; Schott, D.; Schumacher, R. A.; Seder, E.; Seraydaryan, H.; Sharabian, Y. G.; Smith, G. D.; Sober, D. I.; Sokhan, D.; Stepanyan, S. S.; Stepanyan, S.; Strakovsky, I. I.; Strauch, S.; Taiuti, M.; Tang, W.; Taylor, C. E.; Tian, Ye; Tkachenko, S.; Torayev, B.; Vernarsky, B.; Vlassov, A. V.; Voskanyan, H.; Voutier, E.; Walford, N. K.; Watts, D. P.; Weinstein, L. B.; Weygand, D. P.; Zachariou, N.; Zana, L.; Zhang, J.; Zhao, Z. W.; Zonta, I.

2013-04-01

Experimental results on the Σ+(1189) hyperon transverse polarization in photoproduction on a hydrogen target using the CLAS detector at Jefferson Laboratory are presented. The Σ+(1189) was reconstructed in the exclusive reaction γ+p→KS0+Σ+(1189) via the Σ+→pπ0 decay mode. The KS0 was reconstructed in the invariant mass of two oppositely charged pions with the π0 identified in the missing mass of the detected pπ+π- final state. Experimental data were collected in the photon energy range Eγ=1.0-3.5 GeV (s range 1.66-2.73 GeV). We observe a large negative polarization of up to 95%. As the mechanism of transverse polarization of hyperons produced in unpolarized photoproduction experiments is still not well understood, these results will help to distinguish between different theoretical models on hyperon production and provide valuable information for the searches of missing baryon resonances.

Search for direct top squark pair production in events with a boson, -jets and missing transverse momentum in TeV collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Khalek, S. Abdel; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmad, A.; Ahmadov, F.; Aielli, G.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Backus Mayes, J.; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, S.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Guimarães da Costa, J. Barreiro; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belloni, A.; Beloborodova, O. L.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Garcia, J. A. Benitez; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertolucci, F.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Bousson, N.; Boutouil, S.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozovic-Jelisavcic, I.; Bracinik, J.; Branchini, P.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brazzale, S. F.; Brelier, B.; Brendlinger, K.; Brennan, A. J.; Brenner, R.; Bressler, S.; Bristow, K.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Bromberg, C.; Bronner, J.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Brown, G.; Brown, J.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Toro, R. Camacho; Camarda, S.; Cameron, D.; Caminada, L. M.; Armadans, R. Caminal; Campana, S.; Campanelli, M.; Campoverde, A.; Canale, V.; Canepa, A.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Castaneda-Miranda, E.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chan, K.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Chau, C. C.; Barajas, C. A. Chavez; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Christidi, I. A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Cole, B.; Cole, S.; Colijn, A. P.; Collins-Tooth, C.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Côté, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuciuc, C.-M.; Cuenca Almenar, C.; Donszelmann, T. Cuhadar; Cummings, J.; Curatolo, M.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Hoffmann, M. Dano; Dao, V.; Darbo, G.; Darlea, G. L.; Darmora, S.; Dassoulas, J. A.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. 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2014-06-01

A search is presented for direct top squark pair production using events with at least two leptons including a same-flavour opposite-sign pair with invariant mass consistent with the boson mass, jets tagged as originating from -quarks and missing transverse momentum. The analysis is performed with proton-proton collision data at collected with the ATLAS detector at the LHC in 2012 corresponding to an integrated luminosity of 20.3 fb. No excess beyond the Standard Model expectation is observed. Interpretations of the results are provided in models based on the direct pair production of the heavier top squark state () followed by the decay to the lighter top squark state () via , and for pair production in natural gauge-mediated supersymmetry breaking scenarios where the neutralino () is the next-to-lightest supersymmetric particle and decays producing a boson and a gravitino () via the process.

Search for strong production of supersymmetric particles in final states with missing transverse momentum and at least three b-jets at $$ \\sqrt{s} = 8 $$ TeV proton-proton collisions with the ATLAS detector

DOE PAGES

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

2014-10-03

We report the results of a search for strong production of supersymmetric particles in 20.1 fb ₋1 of proton-proton collisions at a centre-of-mass energy of 8TeV using the ATLAS detector at the LHC. The search is performed separately in events with either zero or at least one high-p T lepton (electron or muon), large missing transverse momentum, high jet multiplicity and at least three jets identified as originated from the fragmentation of a b-quark. No excess is observed with respect to the Standard Model predictions. The results are interpreted in the context of several supersymmetric models involving gluinos and scalarmore » top and bottom quarks, as well as a mSUGRA/CMSSM model. Lastly, gluino masses up to 1340 GeV are excluded, depending on the model, significantly extending the previous ATLAS limits.« less

Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index

PubMed Central

Yang, Jian; Bakshi, Andrew; Zhu, Zhihong; Hemani, Gibran; Vinkhuyzen, Anna A.E.; Lee, Sang Hong; Robinson, Matthew R.; Perry, John R.B.; Nolte, Ilja M.; van Vliet-Ostaptchouk, Jana V.; Snieder, Harold; Esko, Tonu; Milani, Lili; Mägi, Reedik; Metspalu, Andres; Hamsten, Anders; Magnusson, Patrik K.E.; Pedersen, Nancy L.; Ingelsson, Erik; Soranzo, Nicole; Keller, Matthew C.; Wray, Naomi R.; Goddard, Michael E.; Visscher, Peter M.

2015-01-01

We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing (WGS) data. We demonstrate using simulations based on WGS data that ~97% and ~68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ~17M imputed variants explain 56% (s.e. = 2.3%) of variance for height and 27% (s.e. = 2.5%) for body mass index (BMI), and find evidence that height- and BMI-associated variants have been under natural selection. Considering imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60–70% for height and 30–40% for BMI. Therefore, missing heritability is small for both traits. For further gene discovery of complex traits, a design with SNP arrays followed by imputation is more cost-effective than WGS at current prices. PMID:26323059

Search for new phenomena in final states with large jet multiplicities and missing transverse momentum with ATLAS using s = 13   TeV proton–proton collisions

DOE PAGES

Aad, G.

2016-04-06

Results are reported of a search for new phenomena, such as supersymmetric particle production, that could be observed in high-energy proton–proton collisions. Events with large numbers of jets, together with missing transverse momentum from unobserved particles, are selected. The data analysed were recorded by the ATLAS experiment during 2015 using the 13 TeV centre-of-mass proton–proton collisions at the Large Hadron Collider, and correspond to an integrated luminosity of 3.2 fb -1. The search selected events with various jet multiplicities from ≥7 to ≥10 jets, and with various b-jet multiplicity requirements to enhance sensitivity. Furthermore, no excess above Standard Model expectationsmore » is observed. The results are interpreted within two supersymmetry models, where gluino masses up to 1400 GeV are excluded at 95% confidence level, significantly extending previous limits.« less

Search for diphoton events with large missing transverse energy with 36 pb-1 of 7 TeV proton-proton collision data with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdelalim, A. A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abramowicz, H.; Abreu, H.; Acerbi, E.; Acharya, B. S.; Adams, D. L.; Addy, T. N.; Adelman, J.; Aderholz, M.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Akiyama, A.; Alam, M. S.; Alam, M. A.; 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.; Aliyev, M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alviggi, M. G.; Amako, K.; Amaral, P.; Amelung, C.; Ammosov, V. V.; Amorim, A.; Amorós, G.; Amram, N.; Anastopoulos, C.; Andari, N.; Andeen, T.; Anders, C. F.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angerami, A.; Anghinolfi, F.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoun, S.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Archambault, J. P.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Asfandiyarov, R.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Atoian, G.; Aubert, B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Austin, N.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Bachy, G.; Backes, M.; Backhaus, M.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Dos Santos Pedrosa, F. Baltasar; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barashkou, A.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, D.; Bartsch, V.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Battistoni, G.; Bauer, F.; Bawa, H. S.; Beare, B.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Begel, M.; Harpaz, S. Behar; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Ami, S. Ben; Benary, O.; Benchekroun, D.; Benchouk, C.; Bendel, M.; Benedict, B. H.; Benekos, N.; Benhammou, Y.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernardet, K.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertin, A.; Bertinelli, F.; Bertolucci, F.; Besana, M. I.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blazek, T.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boelaert, N.; Böser, S.; Bogaerts, J. A.; Bogdanchikov, A.; Bogouch, A.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Bolnet, N. M.; Bona, M.; Bondarenko, V. G.; Boonekamp, M.; Boorman, G.; Booth, C. N.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borroni, S.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Botterill, D.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E. V.; Boulahouache, C.; Bourdarios, C.; Bousson, N.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozhko, N. I.; Bozovic-Jelisavcic, I.; Bracinik, J.; Braem, A.; Branchini, P.; Brandenburg, G. W.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brelier, B.; Bremer, J.; Brenner, R.; Bressler, S.; Breton, D.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brodbeck, T. J.; Brodet, E.; Broggi, F.; Bromberg, C.; Brooijmans, G.; Brooks, W. K.; Brown, G.; Brown, H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Buanes, T.; Bucci, F.; Buchanan, J.; Buchanan, N. J.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Budick, B.; Büscher, V.; Bugge, L.; Buira-Clark, D.; Bulekov, O.; Bunse, M.; Buran, T.; Burckhart, H.; Burdin, S.; Burgess, T.; Burke, S.; Busato, E.; Bussey, P.; Buszello, C. P.; Butin, F.; Butler, B.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Buttinger, W.; Byatt, T.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Caloi, R.; Calvet, D.; Calvet, S.; Camacho Toro, R.; Camarri, P.; Cambiaghi, M.; Cameron, D.; Campana, S.; Campanelli, M.; Canale, V.; Canelli, F.; Canepa, A.; Cantero, J.; Capasso, L.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capriotti, D.; Capua, M.; Caputo, R.; Caramarcu, C.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, B.; Caron, S.; Carrillo Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Cascella, M.; Caso, C.; Castaneda Hernandez, A. M.; Castaneda-Miranda, E.; Castillo Gimenez, V.; Castro, N. F.; Cataldi, G.; Cataneo, F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cauz, D.; Cavalleri, P.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cetin, S. A.; Cevenini, F.; Chafaq, A.; Chakraborty, D.; Chan, K.; Chapleau, B.; Chapman, J. D.; Chapman, J. W.; Chareyre, E.; Charlton, D. G.; Chavda, V.; Barajas, C. A. Chavez; Cheatham, S.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, T.; Chen, X.; Cheng, S.; Cheplakov, A.; Chepurnov, V. F.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Cheung, S. L.; Chevalier, L.; Chiefari, G.; Chikovani, L.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chizhov, M. V.; Choudalakis, G.; Chouridou, S.; Christidi, I. A.; Christov, A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Ciapetti, G.; Ciba, K.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciobotaru, M. D.; Ciocca, C.; Ciocio, A.; Cirilli, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Clifft, R. W.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coe, P.; Cogan, J. G.; Coggeshall, J.; Cogneras, E.; Cojocaru, C. D.; Colas, J.; Colijn, A. P.; Collard, C.; Collins, N. J.; Collins-Tooth, C.; Collot, J.; Colon, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Consonni, M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conventi, F.; Cook, J.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Costin, T.; Côté, D.; Coura Torres, R.; Courneyea, L.; Cowan, G.; Cowden, C.; Cox, B. E.; Cranmer, K.; Crescioli, F.; Cristinziani, M.; Crosetti, G.; Crupi, R.; Crépé-Renaudin, S.; Cuciuc, C.-M.; Almenar, C. Cuenca; Cuhadar Donszelmann, T.; Cuneo, S.; Curatolo, M.; Curtis, C. J.; Cwetanski, P.; Czirr, H.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; D'Orazio, A.; Da Silva, P. V. M.; Da Via, C.; Dabrowski, W.; Dai, T.; Dallapiccola, C.; Dam, M.; Dameri, M.; Damiani, D. S.; Danielsson, H. O.; Dannheim, D.; Dao, V.; Darbo, G.; Darlea, G. L.; Daum, C.; Dauvergne, J. P.; Davey, W.; Davidek, T.; Davidson, N.; Davidson, R.; Davies, E.; Davies, M.; Davison, A. R.; Davygora, Y.; Dawe, E.; Dawson, I.; Dawson, J. W.; Daya, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Castro Faria Salgado, P. E.; De Cecco, S.; de Graat, J.; De Groot, N.; de Jong, P.; De La Taille, C.; De la Torre, H.; De Lotto, B.; De Mora, L.; De Nooij, L.; De Oliveira Branco, M.; De Pedis, D.; de Saintignon, P.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; Dean, S.; Dedovich, D. V.; Degenhardt, J.; Dehchar, M.; Deile, M.; Del Papa, C.; Del Peso, J.; Del Prete, T.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delpierre, P.; Delruelle, N.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demirkoz, B.; Deng, J.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Devetak, E.; Deviveiros, P. O.; Dewhurst, A.; DeWilde, B.; Dhaliwal, S.; Dhullipudi, R.; Di Ciaccio, A.; Di Ciaccio, L.; Di Girolamo, A.; Di Girolamo, B.; Di Luise, S.; Di Mattia, A.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Diaz, M. A.; Diblen, F.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dindar Yagci, K.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; do Vale, M. A. B.; Do Valle Wemans, A.; Doan, T. K. O.; Dobbs, M.; Dobinson, R.; Dobos, D.; Dobson, E.; Dobson, M.; Dodd, J.; Doglioni, C.; Doherty, T.; Doi, Y.; Dolejsi, J.; Dolenc, I.; Dolezal, Z.; Dolgoshein, B. A.; Dohmae, T.; Donadelli, M.; Donega, M.; Donini, J.; Dopke, J.; Doria, A.; Dos Anjos, A.; Dosil, M.; Dotti, A.; Dova, M. T.; Dowell, J. D.; Doxiadis, A. D.; Doyle, A. T.; Drasal, Z.; Drees, J.; Dressnandt, N.; Drevermann, H.; Driouichi, C.; Dris, M.; Dubbert, J.; Dubbs, T.; Dube, S.; Duchovni, E.; Duckeck, G.; Dudarev, A.; Dudziak, F.; Dührssen, M.; Duerdoth, I. P.; Duflot, L.; Dufour, M.-A.; Dunford, M.; Yildiz, H. Duran; Duxfield, R.; Dwuznik, M.; Dydak, F.; Dzahini, D.; Düren, M.; Ebenstein, W. L.; Ebke, J.; Eckert, S.; Eckweiler, S.; Edmonds, K.; Edwards, C. A.; Edwards, N. C.; Ehrenfeld, W.; Ehrich, T.; Eifert, T.; Eigen, G.; Einsweiler, K.; Eisenhandler, E.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, K.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Ely, R.; Emeliyanov, D.; Engelmann, R.; Engl, A.; Epp, B.; Eppig, A.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Escobar, C.; Espinal Curull, X.; Esposito, B.; Etienne, F.; Etienvre, A. I.; Etzion, E.; Evangelakou, D.; Evans, H.; Fabbri, L.; Fabre, C.; Fakhrutdinov, R. M.; Falciano, S.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farley, J.; Farooque, T.; Farrington, S. M.; Farthouat, P.; Fassnacht, P.; Fassouliotis, D.; Fatholahzadeh, B.; Favareto, A.; Fayard, L.; Fazio, S.; Febbraro, R.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feligioni, L.; Fellmann, D.; Felzmann, C. U.; Feng, C.; Feng, E. J.; Fenyuk, A. B.; Ferencei, J.; Ferland, J.; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferrer, A.; Ferrer, M. L.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filippas, A.; Filthaut, F.; Fincke-Keeler, M.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, G.; Fischer, P.; Fisher, M. J.; Fisher, S. M.; Flechl, M.; Fleck, I.; Fleckner, J.; Fleischmann, P.; Fleischmann, S.; Flick, T.; Flores Castillo, L. R.; Flowerdew, M. J.; Föhlisch, F.; Fokitis, M.; Martin, T. Fonseca; Forbush, D. A.; Formica, A.; Forti, A.; Fortin, D.; Foster, J. M.; Fournier, D.; Foussat, A.; Fowler, A. J.; Fowler, K.; Fox, H.; Francavilla, P.; Franchino, S.; Francis, D.; Frank, T.; Franklin, M.; Franz, S.; Fraternali, M.; Fratina, S.; French, S. T.; Froeschl, R.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gadfort, T.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Gallas, E. J.; Gallas, M. V.; Gallo, V.; Gallop, B. J.; Gallus, P.; Galyaev, E.; Gan, K. K.; Gao, Y. S.; Gapienko, V. A.; Gaponenko, A.; Garberson, F.; Garcia-Sciveres, M.; García, C.; Navarro, J. E. García; Gardner, R. W.; Garelli, N.; Garitaonandia, H.; Garonne, V.; Garvey, J.; Gatti, C.; Gaudio, G.; Gaumer, O.; Gaur, B.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gayde, J.-C.; Gazis, E. N.; Ge, P.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Gemmell, A.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerlach, P.; Gershon, A.; Geweniger, C.; Ghazlane, H.; Ghez, P.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giakoumopoulou, V.; Giangiobbe, V.; Gianotti, F.; Gibbard, B.; Gibson, A.; Gibson, S. M.; Gilbert, L. M.; Gilchriese, M.; Gilewsky, V.; Gillberg, D.; Gillman, A. R.; Gingrich, D. M.; Ginzburg, J.; Giokaris, N.; Giordano, R.; Giorgi, F. M.; Giovannini, P.; Giraud, P. F.; Giugni, D.; Giunta, M.; Giusti, P.; Gjelsten, B. K.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glazov, A.; Glitza, K. W.; Glonti, G. L.; Godfrey, J.; Godlewski, J.; Goebel, M.; Göpfert, T.; Goeringer, C.; Gössling, C.; Göttfert, T.; Goldfarb, S.; Goldin, D.; Golling, T.; Golovnia, S. N.; Gomes, A.; Fajardo, L. S. Gomez; Gonçalo, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, L.; Gonidec, A.; Gonzalez, S.; González de la Hoz, S.; Silva, M. L. Gonzalez; Gonzalez-Sevilla, S.; Goodson, J. J.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorfine, G.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Gorokhov, S. A.; Goryachev, V. N.; Gosdzik, B.; Gosselink, M.; Gostkin, M. I.; Gouanère, M.; Eschrich, I. Gough; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Grabowska-Bold, I.; Grabski, V.; Grafström, P.; Grah, C.; Grahn, K.-J.; Grancagnolo, F.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Grau, N.; Gray, H. M.; Gray, J. A.; Graziani, E.; Grebenyuk, O. G.; Greenfield, D.; Greenshaw, T.; Greenwood, Z. D.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grigalashvili, N.; Grillo, A. A.; Grinstein, S.; Grishkevich, Y. V.; Grivaz, J.-F.; Grognuz, J.; Groh, M.; Gross, E.; Grosse-Knetter, J.; Groth-Jensen, J.; Grybel, K.; Guarino, V. J.; Guest, D.; Guicheney, C.; Guida, A.; Guillemin, T.; Guindon, S.; Guler, H.; Gunther, J.; Guo, B.; Guo, J.; Gupta, A.; Gusakov, Y.; Gushchin, V. N.; Gutierrez, A.; Gutierrez, P.; Guttman, N.; Gutzwiller, O.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haas, S.; Haber, C.; Hackenburg, R.; Hadavand, H. K.; Hadley, D. R.; Haefner, P.; Hahn, F.; Haider, S.; Hajduk, Z.; Hakobyan, H.; Haller, J.; Hamacher, K.; Hamal, P.; Hamilton, A.; Hamilton, S.; Han, H.; Han, L.; Hanagaki, K.; Hance, M.; Handel, C.; Hanke, P.; Hansen, J. R.; Hansen, J. B.; Hansen, J. D.; Hansen, P. H.; Hansson, P.; Hara, K.; Hare, G. A.; Harenberg, T.; Harkusha, S.; Harper, D.; Harrington, R. D.; Harris, O. M.; Harrison, K.; Hartert, J.; Hartjes, F.; Haruyama, T.; Harvey, A.; Hasegawa, S.; Hasegawa, Y.; Hassani, S.; Hatch, M.; Hauff, D.; Haug, S.; Hauschild, M.; Hauser, R.; Havranek, M.; Hawes, B. M.; Hawkes, C. M.; Hawkings, R. J.; Hawkins, D.; Hayakawa, T.; Hayden, D.; Hayward, H. S.; Haywood, S. J.; Hazen, E.; He, M.; Head, S. J.; Hedberg, V.; Heelan, L.; Heim, S.; Heinemann, B.; Heisterkamp, S.; Helary, L.; Heller, M.; Hellman, S.; Hellmich, D.; Helsens, C.; Henderson, R. C. W.; Henke, M.; Henrichs, A.; Correia, A. M. Henriques; Henrot-Versille, S.; Henry-Couannier, F.; Hensel, C.; Henß, T.; Hernandez, C. M.; Hernández Jiménez, Y.; Herrberg, R.; Hershenhorn, A. D.; Herten, G.; Hertenberger, R.; Hervas, L.; Hessey, N. P.; Hidvegi, A.; Higón-Rodriguez, E.; Hill, D.; Hill, J. C.; Hill, N.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirsch, F.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoffman, J.; Hoffmann, D.; Hohlfeld, M.; Holder, M.; Holmes, A.; Holmgren, S. O.; Holy, T.; Holzbauer, J. L.; Homma, Y.; Hong, T. M.; Hooft van Huysduynen, L.; Horazdovsky, T.; Horn, C.; Horner, S.; Horton, K.; Hostachy, J.-Y.; Hou, S.; Houlden, M. A.; Hoummada, A.; Howarth, J.; Howell, D. F.; Hristova, I.; Hrivnac, J.; Hruska, I.; Hryn'ova, T.; Hsu, P. J.; Hsu, S.-C.; Huang, G. S.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Hughes-Jones, R. 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L.; Renaud, A.; Renkel, P.; Rescigno, M.; Resconi, S.; Resende, B.; Reznicek, P.; Rezvani, R.; Richards, A.; Richter, R.; Richter-Was, E.; Ridel, M.; Rieke, S.; Rijpstra, M.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Rios, R. R.; Riu, I.; Rivoltella, G.; Rizatdinova, F.; Rizvi, E.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robinson, M.; Robson, A.; Rocha de Lima, J. G.; Roda, C.; Dos Santos, D. Roda; Rodier, S.; Rodriguez, D.; Garcia, Y. Rodriguez; Roe, A.; Roe, S.; Røhne, O.; Rojo, V.; Rolli, S.; Romaniouk, A.; Romanov, V. M.; Romeo, G.; Romero Maltrana, D.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, M.; Rosenbaum, G. A.; Rosenberg, E. I.; Rosendahl, P. L.; Rosselet, L.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rossi, L.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubinskiy, I.; Ruckert, B.; Ruckstuhl, N.; Rud, V. I.; Rudolph, C.; Rudolph, G.; Rühr, F.; Ruggieri, F.; Ruiz-Martinez, A.; Rulikowska-Zarebska, E.; Rumiantsev, V.; Rumyantsev, L.; Runge, K.; Runolfsson, O.; Rurikova, Z.; Rusakovich, N. A.; Rust, D. R.; Rutherfoord, J. P.; Ruwiedel, C.; Ruzicka, P.; Ryabov, Y. F.; Ryadovikov, V.; Ryan, P.; Rybar, M.; Rybkin, G.; Ryder, N. C.; Rzaeva, S.; Saavedra, A. F.; Sadeh, I.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Sakamoto, H.; Salamanna, G.; Salamon, A.; Saleem, M.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvachua Ferrando, B. M.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sampsonidis, D.; Samset, B. H.; Sanchez, A.; Sandaker, H.; Sander, H. G.; Sanders, M. P.; Sandhoff, M.; Sandoval, T.; Sandstroem, R.; Sandvoss, S.; Sankey, D. P. C.; Sansoni, A.; Santamarina Rios, C.; Santoni, C.; Santonico, R.; Santos, H.; Saraiva, J. G.; Sarangi, T.; Sarkisyan-Grinbaum, E.; Sarri, F.; Sartisohn, G.; Sasaki, O.; Sasaki, T.; Sasao, N.; Satsounkevitch, I.; Sauvage, G.; Sauvan, E.; Sauvan, J. B.; Savard, P.; Savinov, V.; Savu, D. O.; Savva, P.; Sawyer, L.; Saxon, D. H.; Says, L. P.; Sbarra, C.; Sbrizzi, A.; Scallon, O.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schäfer, U.; Schaepe, S.; Schaetzel, S.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schamov, A. G.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schioppa, M.; Schlenker, S.; Schlereth, J. L.; Schmidt, E.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, M.; Schöning, A.; Schott, M.; Schouten, D.; Schovancova, J.; Schram, M.; Schroeder, C.; Schroer, N.; Schuh, S.; Schuler, G.; Schultes, J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, J. W.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwemling, Ph.; Schwienhorst, R.; Schwierz, R.; Schwindling, J.; Schwindt, T.; Scott, W. G.; Searcy, J.; Sedykh, E.; Segura, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Seliverstov, D. M.; Sellden, B.; Sellers, G.; Seman, M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Seuster, R.; Severini, H.; Sevior, M. E.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shank, J. T.; Shao, Q. T.; Shapiro, M.; Shatalov, P. B.; Shaver, L.; Shaw, C.; Shaw, K.; Sherman, D.; Sherwood, P.; Shibata, A.; Shichi, H.; Shimizu, S.; Shimojima, M.; Shin, T.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shupe, M. A.; Sicho, P.; Sidoti, A.; Siebel, A.; Siegert, F.; Siegrist, J.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simmons, B.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skovpen, K.; Skubic, P.; Skvorodnev, N.; Slater, M.; Slavicek, T.; Sliwa, K.; Sloan, T. J.; Sloper, J.; Smakhtin, V.; Smirnov, S. Yu.; Smirnova, L. N.; Smirnova, O.; Smith, B. C.; Smith, D.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snow, S. W.; Snow, J.; Snuverink, J.; Snyder, S.; Soares, M.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E.; Soldevila, U.; Solfaroli Camillocci, E.; Solodkov, A. A.; Solovyanov, O. V.; Sondericker, J.; Soni, N.; Sopko, V.; Sopko, B.; Sorbi, M.; Sosebee, M.; Soukharev, A.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spila, F.; Spiriti, E.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; Denis, R. D. St.; Stahl, T.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staude, A.; Stavina, P.; Stavropoulos, G.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, K.; Stewart, G. A.; Stillings, J. A.; Stockmanns, T.; Stockton, M. C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Strube, J.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Soh, D. A.; Su, D.; Subramania, H. S.; Succurro, A.; Sugaya, Y.; Sugimoto, T.; Suhr, C.; Suita, K.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Sushkov, S.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Sviridov, Yu. M.; Swedish, S.; Sykora, I.; Sykora, T.; Szeless, B.; Sánchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taga, A.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Talby, M.; Talyshev, A.; Tamsett, M. C.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanaka, Y.; Tani, K.; Tannoury, N.; Tappern, G. P.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tatarkhanov, M.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Castanheira, M. Teixeira Dias; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terwort, M.; Testa, M.; Teuscher, R. J.; Thadome, J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thioye, M.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomson, E.; Thomson, M.; Thun, R. P.; Tic, T.; Tikhomirov, V. O.; Tikhonov, Y. A.; Timmermans, C. J. W. P.; Tipton, P.; Tique Aires Viegas, F. J.; Tisserant, S.; Tobias, J.; Toczek, B.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokunaga, K.; Tokushuku, K.; Tollefson, K.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, G.; Tonoyan, A.; Topfel, C.; Topilin, N. D.; Torchiani, I.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Traynor, D.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Trinh, T. N.; Tripiana, M. F.; Trischuk, W.; Trivedi, A.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiakiris, M.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsung, J.-W.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tuggle, J. M.; Turala, M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Tyrvainen, H.; Tzanakos, G.; Uchida, K.; Ueda, I.; Ueno, R.; Ugland, M.; Uhlenbrock, M.; Uhrmacher, M.; Ukegawa, F.; Unal, G.; Underwood, D. G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Urkovsky, E.; Urrejola, P.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valenta, J.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; van der Graaf, H.; van der Kraaij, E.; Van Der Leeuw, R.; van der Poel, E.; van der Ster, D.; Van Eijk, B.; van Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vandelli, W.; Vandoni, G.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Varela Rodriguez, F.; Vari, R.; Varnes, E. W.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Vegni, G.; Veillet, J. J.; Vellidis, C.; Veloso, F.; Veness, R.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Vichou, I.; Vickey, T.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinek, E.; Vinogradov, V. B.; Virchaux, M.; Virzi, J.; Vitells, O.; Viti, M.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobiev, A. P.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T. T.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Anh, T. Vu; Vuillermet, R.; Vukotic, I.; Wagner, W.; Wagner, P.; Wahlen, H.; Wakabayashi, J.; Walbersloh, J.; Walch, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Wang, C.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, J. C.; Wang, R.; Wang, S. M.; Warburton, A.; Ward, C. P.; Warsinsky, M.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, A. T.; Waugh, B. M.; Weber, J.; Weber, M.; Weber, M. S.; Weber, P.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P. S.; Wen, M.; Wenaus, T.; Wendler, S.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Wessels, M.; Weydert, C.; Whalen, K.; Wheeler-Ellis, S. J.; Whitaker, S. P.; White, A.; White, M. J.; White, S.; Whitehead, S. R.; Whiteson, D.; Whittington, D.; Wicek, F.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilhelm, I.; Wilkens, H. G.; Will, J. Z.; Williams, E.; Williams, H. H.; Willis, W.; Willocq, S.; Wilson, J. A.; Wilson, M. G.; Wilson, A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wolter, M. W.; Wolters, H.; Wooden, G.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wraight, K.; Wright, C.; Wrona, B.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wunstorf, R.; Wynne, B. M.; Xaplanteris, L.; Xella, S.; Xie, S.; Xie, Y.; Xu, C.; Xu, D.; Xu, G.; Yabsley, B.; Yamada, M.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U. K.; Yang, Y.; Yang, Y.; Yang, Z.; Yanush, S.; Yao, W.-M.; Yao, Y.; Yasu, Y.; Ybeles Smit, G. V.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Youssef, S.; Yu, D.; Yu, J.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zaets, V. G.; Zaidan, R.; Zaitsev, A. M.; Zajacova, Z.; Zalite, Yo. K.; Zanello, L.; Zarzhitsky, P.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zemla, A.; Zendler, C.; Zenin, A. V.; Zenin, O.; Ženiš, T.; Zenonos, Z.; Zenz, S.; Zerwas, D.; della Porta, G. Zevi; Zhan, Z.; Zhang, D.; Zhang, H.; Zhang, J.; Zhang, X.; Zhang, Z.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zheng, S.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zieminska, D.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; Zolnierowski, Y.; Zsenei, A.; zur Nedden, M.; Zutshi, V.; Zwalinski, L.

2011-10-01

Making use of 36 pb-1 of proton-proton collision data at sqrt{s} =7 TeV, the ATLAS Collaboration has performed a search for diphoton events with large missing transverse energy. Observing no excess of events above the Standard Model prediction, a 95% Confidence Level (CL) upper limit is set on the cross section for new physics of σ<0.38-0.65 pb in the context of a generalised model of gauge-mediated supersymmetry breaking (GGM) with a bino-like lightest neutralino, and of σ<0.18-0.23 pb in the context of a specific model with one universal extra dimension (UED). A 95% CL lower limit of 560 GeV, for bino masses above 50 GeV, is set on the GGM gluino mass, while a lower limit of 1/ R>961 GeV is set on the UED compactification radius R. These limits provide the most stringent tests of these models to date.

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

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

The results of our search for new phenomena in events with large missing transverse momentum and a Higgs boson decaying to two photons are reported. Data from proton-proton collisions at a center-of-mass energy of 8 TeV and corresponding to an integrated luminosity of 20.3 fb -1 have been collected with the ATLAS detector at the LHC. Moreover the data we observed are well described by the expected standard model backgrounds. Upper limits on the cross section of events with large missing transverse momentum and a Higgs boson candidate are also placed. Exclusion limits are presented for models of physics beyondmore » the standard model featuring dark-matter candidates.« less

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

Aad, G.

Results of a search for new phenomena in events with large missing transverse momentum and a Higgs boson decaying to two photons are reported. Data from proton-proton collisions at a center-of-mass energy of 8 TeV and corresponding to an integrated luminosity of 20.3 fb -1 have been collected with the ATLAS detector at the LHC. The observed data are well described by the expected standard model backgrounds. Upper limits on the cross section of events with large missing transverse momentum and a Higgs boson candidate are also placed. Exclusion limits are presented for models of physics beyond the standard modelmore » featuring dark-matter candidates.« less

Galactic cosmic ray antiprotons and supersymmetry

NASA Technical Reports Server (NTRS)

Stecker, F. W.; Walsh, T.; Rudaz, S.

1985-01-01

The physics of the annihilation of photinos is considered as a function of mass in detail, in order to obtain the energy spectra of the cosmic ray antiprotons produced under the assumption that photinos make up the missing mass in the galactic halo. The modulated spectrum is at 1 a.w. with the cosmic ray antiprotons data. A very intriguing fit is obtained to all of the present antiprotons up to 13.4 GeV data for similar to 15 GeV. A cutoff is predicted in the antiprotons spectrum at E = photino mass above which only a small flux from secondary production should remain.

Order and anarchy hand in hand in 5D SO(10)

NASA Astrophysics Data System (ADS)

Feruglio, Ferruccio; Patel, Ketan M.; Vicino, Denise

2014-09-01

We update a five-dimensional SO(10) grand unified model of fermion masses and mixing angles originally proposed by Kitano and Li. In our setup Yukawa couplings are anarchical and quark and lepton sectors are diversified by the profiles of the fermion zero modes in the extra dimension. The breaking of SO(10) down to SU(5)×U(1)X provides the key parameter that distinguishes the profiles of the different SU(5) components inside the same 16 representation. With respect to the original version of the model, we extend the Higgs sector to explicitly solve the doublet-triplet splitting problem through the missing partner mechanism and we perform a fit to an idealized set of data. By scanning the Yukawa couplings of the model we find that, for large tan β, both normal and inverted ordered neutrino spectrum can be accommodated. However, while the case of inverted order requires a severe fine tuning of the Yukawa parameters, the normal ordering is compatible with an anarchical distribution of Yukawa couplings. Thus, in a natural portion of the parameter space, the model predicts a normal ordered neutrino spectrum, the lightest neutrino mass below 5 meV, and | m ββ | in the range 0.1-5 meV. No particular preference is found for the Dirac CP phase in the lepton sector while the right-handed neutrino masses are too small to explain the baryon asymmetry of the universe through thermal leptogenesis.

Helping a loved one with a drinking problem

MedlinePlus

... school because of alcohol use Have trouble with relationships because of drinking Miss important work, school, or ... Call Your Doctor If you feel that your relationship with this person is becoming dangerous or is ...

Streaming PCA with many missing entries.

DOT National Transportation Integrated Search

2015-12-01

This paper considers the problem of matrix completion when some number of the columns are : completely and arbitrarily corrupted, potentially by a malicious adversary. It is well-known that standard : algorithms for matrix completion can return arbit...

A metric space for Type Ia supernova spectra: a new method to assess explosion scenarios

NASA Astrophysics Data System (ADS)

Sasdelli, Michele; Hillebrandt, W.; Kromer, M.; Ishida, E. E. O.; Röpke, F. K.; Sim, S. A.; Pakmor, R.; Seitenzahl, I. R.; Fink, M.

2017-04-01

Over the past years, Type Ia supernovae (SNe Ia) have become a major tool to determine the expansion history of the Universe, and considerable attention has been given to, both, observations and models of these events. However, until now, their progenitors are not known. The observed diversity of light curves and spectra seems to point at different progenitor channels and explosion mechanisms. Here, we present a new way to compare model predictions with observations in a systematic way. Our method is based on the construction of a metric space for SN Ia spectra by means of linear principal component analysis, taking care of missing and/or noisy data, and making use of partial least-squares regression to find correlations between spectral properties and photometric data. We investigate realizations of the three major classes of explosion models that are presently discussed: delayed-detonation Chandrasekhar-mass explosions, sub-Chandrasekhar-mass detonations and double-degenerate mergers, and compare them with data. We show that in the principal component space, all scenarios have observed counterparts, supporting the idea that different progenitors are likely. However, all classes of models face problems in reproducing the observed correlations between spectral properties and light curves and colours. Possible reasons are briefly discussed.

Identification of Major Histocompatibility Complex-Regulated Body Odorants by Statistical Analysis of a Comparative Gas Chromatography/Mass Spectrometry Experiment

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

Willse, Alan R.; Belcher, Ann; Preti, George

2005-04-15

Gas chromatography (GC), combined with mass spectrometry (MS) detection, is a powerful analytical technique that can be used to separate, quantify, and identify volatile compounds in complex mixtures. This paper examines the application of GC-MS in a comparative experiment to identify volatiles that differ in concentration between two groups. A complex mixture might comprise several hundred or even thousands of volatile compounds. Because their number and location in a chromatogram generally are unknown, and because components overlap in populous chromatograms, the statistical problems offer significant challenges beyond traditional two-group screening procedures. We describe a statistical procedure to compare two-dimensional GC-MSmore » profiles between groups, which entails (1) signal processing: baseline correction and peak detection in single ion chromatograms; (2) aligning chromatograms in time; (3) normalizing differences in overall signal intensities; and (4) detecting chromatographic regions that differ between groups. Compared to existing approaches, the proposed method is robust to errors made at earlier stages of analysis, such as missed peaks or slightly misaligned chromatograms. To illustrate the method, we identify differences in GC-MS chromatograms of ether-extracted urine collected from two nearly identical inbred groups of mice, to investigate the relationship between odor and genetics of the major histocompatibility complex.« less

SpecOMS: A Full Open Modification Search Method Performing All-to-All Spectra Comparisons within Minutes.

PubMed

David, Matthieu; Fertin, Guillaume; Rogniaux, Hélène; Tessier, Dominique

2017-08-04

The analysis of discovery proteomics experiments relies on algorithms that identify peptides from their tandem mass spectra. The almost exhaustive interpretation of these spectra remains an unresolved issue. At present, an important number of missing interpretations is probably due to peptides displaying post-translational modifications and variants that yield spectra that are particularly difficult to interpret. However, the emergence of a new generation of mass spectrometers that provide high fragment ion accuracy has paved the way for more efficient algorithms. We present a new software, SpecOMS, that can handle the computational complexity of pairwise comparisons of spectra in the context of large volumes. SpecOMS can compare a whole set of experimental spectra generated by a discovery proteomics experiment to a whole set of theoretical spectra deduced from a protein database in a few minutes on a standard workstation. SpecOMS can ingeniously exploit those capabilities to improve the peptide identification process, allowing strong competition between all possible peptides for spectrum interpretation. Remarkably, this software resolves the drawbacks (i.e., efficiency problems and decreased sensitivity) that usually accompany open modification searches. We highlight this promising approach using results obtained from the analysis of a public human data set downloaded from the PRIDE (PRoteomics IDEntification) database.

MVIAeval: a web tool for comprehensively evaluating the performance of a new missing value imputation algorithm.

PubMed

Wu, Wei-Sheng; Jhou, Meng-Jhun

2017-01-13

Missing value imputation is important for microarray data analyses because microarray data with missing values would significantly degrade the performance of the downstream analyses. Although many microarray missing value imputation algorithms have been developed, an objective and comprehensive performance comparison framework is still lacking. To solve this problem, we previously proposed a framework which can perform a comprehensive performance comparison of different existing algorithms. Also the performance of a new algorithm can be evaluated by our performance comparison framework. However, constructing our framework is not an easy task for the interested researchers. To save researchers' time and efforts, here we present an easy-to-use web tool named MVIAeval (Missing Value Imputation Algorithm evaluator) which implements our performance comparison framework. MVIAeval provides a user-friendly interface allowing users to upload the R code of their new algorithm and select (i) the test datasets among 20 benchmark microarray (time series and non-time series) datasets, (ii) the compared algorithms among 12 existing algorithms, (iii) the performance indices from three existing ones, (iv) the comprehensive performance scores from two possible choices, and (v) the number of simulation runs. The comprehensive performance comparison results are then generated and shown as both figures and tables. MVIAeval is a useful tool for researchers to easily conduct a comprehensive and objective performance evaluation of their newly developed missing value imputation algorithm for microarray data or any data which can be represented as a matrix form (e.g. NGS data or proteomics data). Thus, MVIAeval will greatly expedite the progress in the research of missing value imputation algorithms.

Evaluation of methods to estimate missing days' supply within pharmacy data of the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN).

PubMed

Lum, Kirsten J; Newcomb, Craig W; Roy, Jason A; Carbonari, Dena M; Saine, M Elle; Cardillo, Serena; Bhullar, Harshvinder; Gallagher, Arlene M; Lo Re, Vincent

2017-01-01

The extent to which days' supply data are missing in pharmacoepidemiologic databases and effective methods for estimation is unknown. We determined the percentage of missing days' supply on prescription and patient levels for oral anti-diabetic drugs (OADs) and evaluated three methods for estimating days' supply within the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN). We estimated the percentage of OAD prescriptions and patients with missing days' supply in each database from 2009 to 2013. Within a random sample of prescriptions with known days' supply, we measured the accuracy of three methods to estimate missing days' supply by imputing the following: (1) 28 days' supply, (2) mode number of tablets/day by drug strength and number of tablets/prescription, and (3) number of tablets/day via a machine learning algorithm. We determined incidence rates (IRs) of acute myocardial infarction (AMI) using each method to evaluate the impact on ascertainment of exposure time and outcomes. Days' supply was missing for 24 % of OAD prescriptions in CPRD and 33 % in THIN (affecting 48 and 57 % of patients, respectively). Methods 2 and 3 were very accurate in estimating days' supply for OADs prescribed at a consistent number of tablets/day. Method 3 was more accurate for OADs prescribed at varying number of tablets/day. IRs of AMI were similar across methods for most OADs. Missing days' supply is a substantial problem in both databases. Method 2 is easy and very accurate for most OADs and results in IRs comparable to those from method 3.

Characterizing and Managing Missing Structured Data in Electronic Health Records: Data Analysis.

PubMed

Beaulieu-Jones, Brett K; Lavage, Daniel R; Snyder, John W; Moore, Jason H; Pendergrass, Sarah A; Bauer, Christopher R

2018-02-23

Missing data is a challenge for all studies; however, this is especially true for electronic health record (EHR)-based analyses. Failure to appropriately consider missing data can lead to biased results. While there has been extensive theoretical work on imputation, and many sophisticated methods are now available, it remains quite challenging for researchers to implement these methods appropriately. Here, we provide detailed procedures for when and how to conduct imputation of EHR laboratory results. The objective of this study was to demonstrate how the mechanism of missingness can be assessed, evaluate the performance of a variety of imputation methods, and describe some of the most frequent problems that can be encountered. We analyzed clinical laboratory measures from 602,366 patients in the EHR of Geisinger Health System in Pennsylvania, USA. Using these data, we constructed a representative set of complete cases and assessed the performance of 12 different imputation methods for missing data that was simulated based on 4 mechanisms of missingness (missing completely at random, missing not at random, missing at random, and real data modelling). Our results showed that several methods, including variations of Multivariate Imputation by Chained Equations (MICE) and softImpute, consistently imputed missing values with low error; however, only a subset of the MICE methods was suitable for multiple imputation. The analyses we describe provide an outline of considerations for dealing with missing EHR data, steps that researchers can perform to characterize missingness within their own data, and an evaluation of methods that can be applied to impute clinical data. While the performance of methods may vary between datasets, the process we describe can be generalized to the majority of structured data types that exist in EHRs, and all of our methods and code are publicly available. ©Brett K Beaulieu-Jones, Daniel R Lavage, John W Snyder, Jason H Moore, Sarah A Pendergrass, Christopher R Bauer. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 23.02.2018.

More missing stellar opacity?

NASA Technical Reports Server (NTRS)

Stothers, Richard B.; Chin, Chao-Wen

1994-01-01

Observational data for Population I stars have shown that blue loops on the Hertzsprung-Russell (H-R) diagram form for stellar masses as low as approximately 4 solar mass. However, current state-of-the-art stellar models, unlike the older ones that were based on smaller opacities, fail to loop out of the red-giant region during core helium burning for masses less than 7 solar mass. A possible explanation is that the currently used Livermore opacities need to be further increased, by at least 70%, at temperatures characteristic of the base of the outer convection zone, around 1 x 10(exp 6) K. Indeed, no other suggested remedy seems to yield a blue loop at the lowest observed loop luminosities.

Relations between Mass Change and Frequency Shift of a QCM Sensor in Contact with Viscoelastic Medium

NASA Astrophysics Data System (ADS)

Tan, Feng; Huang, Xian-He

2013-05-01

We investigate frequency shift of a quartz crystal microbalance (QCM) sensor introduced by mass effect, and properties of material of its coated viscoelastic film are discussed. The validity of the Sauerbrey relation cannot be held if the viscoelastic properties of the contacting medium are considered. When the QCM sensor with a viscoelastic film works in the gas phase, the viscoelastic properties will introduce an extra mass effect. While in the liquid phase, the missing mass effect can be observed. The experimental results demonstrate that the QCM sensor is sensitive to the viscoelastic properties of the coating film. Properties of the viscoelastic contacting medium should be considered.