Reducing Spatial Uncertainty Through Attentional Cueing Improves Contrast Sensitivity in Regions of the Visual Field With Glaucomatous Defects

PubMed Central

Phu, Jack; Kalloniatis, Michael; Khuu, Sieu K.

2018-01-01

Purpose Current clinical perimetric test paradigms present stimuli randomly to various locations across the visual field (VF), inherently introducing spatial uncertainty, which reduces contrast sensitivity. In the present study, we determined the extent to which spatial uncertainty affects contrast sensitivity in glaucoma patients by minimizing spatial uncertainty through attentional cueing. Methods Six patients with open-angle glaucoma and six healthy subjects underwent laboratory-based psychophysical testing to measure contrast sensitivity at preselected locations at two eccentricities (9.5° and 17.5°) with two stimulus sizes (Goldmann sizes III and V) under different cueing conditions: 1, 2, 4, or 8 points verbally cued. Method of Constant Stimuli and a single-interval forced-choice procedure were used to generate frequency of seeing (FOS) curves at locations with and without VF defects. Results At locations with VF defects, cueing minimizes spatial uncertainty and improves sensitivity under all conditions. The effect of cueing was maximal when one point was cued, and rapidly diminished when more points were cued (no change to baseline with 8 points cued). The slope of the FOS curve steepened with reduced spatial uncertainty. Locations with normal sensitivity in glaucomatous eyes had similar performance to that of healthy subjects. There was a systematic increase in uncertainty with the depth of VF loss. Conclusions Sensitivity measurements across the VF are negatively affected by spatial uncertainty, which increases with greater VF loss. Minimizing uncertainty can improve sensitivity at locations of deficit. Translational Relevance Current perimetric techniques introduce spatial uncertainty and may therefore underestimate sensitivity in regions of VF loss. PMID:29600116

A systematic framework for Monte Carlo simulation of remote sensing errors map in carbon assessments

Treesearch

S. Healey; P. Patterson; S. Urbanski

2014-01-01

Remotely sensed observations can provide unique perspective on how management and natural disturbance affect carbon stocks in forests. However, integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential remote sensing errors...

Projecting future air pollution-related mortality under a changing climate: progress, uncertainties and research needs.

PubMed

Madaniyazi, Lina; Guo, Yuming; Yu, Weiwei; Tong, Shilu

2015-02-01

Climate change may affect mortality associated with air pollutants, especially for fine particulate matter (PM2.5) and ozone (O3). Projection studies of such kind involve complicated modelling approaches with uncertainties. We conducted a systematic review of researches and methods for projecting future PM2.5-/O3-related mortality to identify the uncertainties and optimal approaches for handling uncertainty. A literature search was conducted in October 2013, using the electronic databases: PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 to September 2013. Fifteen studies fulfilled the inclusion criteria. Most studies reported that an increase of climate change-induced PM2.5 and O3 may result in an increase in mortality. However, little research has been conducted in developing countries with high emissions and dense populations. Additionally, health effects induced by PM2.5 may dominate compared to those caused by O3, but projection studies of PM2.5-related mortality are fewer than those of O3-related mortality. There is a considerable variation in approaches of scenario-based projection researches, which makes it difficult to compare results. Multiple scenarios, models and downscaling methods have been used to reduce uncertainties. However, few studies have discussed what the main source of uncertainties is and which uncertainty could be most effectively reduced. Projecting air pollution-related mortality requires a systematic consideration of assumptions and uncertainties, which will significantly aid policymakers in efforts to manage potential impacts of PM2.5 and O3 on mortality in the context of climate change. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Comprehension of Randomization and Uncertainty in Cancer Clinical Trials Decision Making Among Rural, Appalachian Patients.

PubMed

Krieger, Janice L; Palmer-Wackerly, Angela; Dailey, Phokeng M; Krok-Schoen, Jessica L; Schoenberg, Nancy E; Paskett, Electra D

2015-12-01

Comprehension of randomization is a vital, but understudied, component of informed consent to participate in cancer randomized clinical trials (RCTs). This study examines patient comprehension of the randomization process as well as sources of ongoing uncertainty that may inhibit a patient's ability to provide informed consent to participate in RCTs. Cancer patients living in rural Appalachia who were offered an opportunity to participate in a cancer treatment RCT completed in-depth interviews and a brief survey. No systematic differences in randomization comprehension between patients who consented and those who declined participation in a cancer RCT were detected. Comprehension is conceptually distinct from uncertainty, with patients who had both high and low comprehension experiencing randomization-related uncertainty. Uncertainty about randomization was found to have cognitive and affective dimensions. Not all patients enrolling in RCTs have a sufficient understanding of the randomization process to provide informed consent. Healthcare providers need to be aware of the different types of randomization-related uncertainty. Efforts to improve informed consent to participate in RCTs should focus on having patients teach back their understanding of randomization. This practice could yield valuable information about the patient's cognitive and affective understanding of randomization as well as opportunities to correct misperceptions. Education about RCTs should reflect patient expectations of individualized care by explaining how all treatments being compared are appropriate to the specifics of a patient's disease.

Forecasting eruption size: what we know, what we don't know

NASA Astrophysics Data System (ADS)

Papale, Paolo

2017-04-01

Any eruption forecast includes an evaluation of the expected size of the forthcoming eruption, usually expressed as the probability associated to given size classes. Such evaluation is mostly based on the previous volcanic history at the specific volcano, or it is referred to a broader class of volcanoes constituting "analogues" of the one under specific consideration. In any case, use of knowledge from past eruptions implies considering the completeness of the reference catalogue, and most importantly, the existence of systematic biases in the catalogue, that may affect probability estimates and translate into biased volcanic hazard forecasts. An analysis of existing catalogues, with major reference to the catalogue from the Smithsonian Global Volcanism Program, suggests that systematic biases largely dominate at global, regional and local scale: volcanic histories reconstructed at individual volcanoes, often used as a reference for volcanic hazard forecasts, are the result of systematic loss of information with time and poor sample representativeness. That situation strictly requires the use of techniques to complete existing catalogues, as well as careful consideration of the uncertainties deriving from inadequate knowledge and model-dependent data elaboration. A reconstructed global eruption size distribution, obtained by merging information from different existing catalogues, shows a mode in the VEI 1-2 range, <0.1% incidence of eruptions with VEI 7 or larger, and substantial uncertainties associated with individual VEI frequencies. Even larger uncertainties are expected to derive from application to individual volcanoes or classes of analogue volcanoes, suggesting large to very large uncertainties associated to volcanic hazard forecasts virtually at any individual volcano worldwide.

Assessing theoretical uncertainties in fission barriers of superheavy nuclei

DOE PAGES

Agbemava, S. E.; Afanasjev, A. V.; Ray, D.; ...

2017-05-26

Here, theoretical uncertainties in the predictions of inner fission barrier heights in superheavy elements have been investigated in a systematic way for a set of state-of-the-art covariant energy density functionals which represent major classes of the functionals used in covariant density functional theory. They differ in basic model assumptions and fitting protocols. Both systematic and statistical uncertainties have been quantified where the former turn out to be larger. Systematic uncertainties are substantial in superheavy elements and their behavior as a function of proton and neutron numbers contains a large random component. The benchmarking of the functionals to the experimental datamore » on fission barriers in the actinides allows to reduce the systematic theoretical uncertainties for the inner fission barriers of unknown superheavy elements. However, even then they on average increase on moving away from the region where benchmarking has been performed. In addition, a comparison with the results of non-relativistic approaches is performed in order to define full systematic theoretical uncertainties over the state-of-the-art models. Even for the models benchmarked in the actinides, the difference in the inner fission barrier height of some superheavy elements reaches $5-6$ MeV. This uncertainty in the fission barrier heights will translate into huge (many tens of the orders of magnitude) uncertainties in the spontaneous fission half-lives.« less

Analysis of determinations of the distance between the sun and the galactic center

NASA Astrophysics Data System (ADS)

Malkin, Z. M.

2013-02-01

The paper investigates the question of whether or not determinations of the distance between the Sun and the Galactic center R 0 are affected by the so-called "bandwagon effect", leading to selection effects in published data that tend to be close to expected values, as was suggested by some authors. It is difficult to estimate numerically a systematic uncertainty in R 0 due to the bandwagon effect; however, it is highly probable that, even if widely accepted values differ appreciably from the true value, the published results should eventually approach the true value despite the bandwagon effect. This should be manifest as a trend in the published R 0 data: if this trend is statistically significant, the presence of the bandwagon effect can be suspected in the data. Fifty two determinations of R 0 published over the last 20 years were analyzed. These data reveal no statistically significant trend, suggesting they are unlikely to involve any systematic uncertainty due to the bandwagon effect. At the same time, the published data show a gradual and statistically significant decrease in the uncertainties in the R 0 determinations with time.

Joint analysis of galaxy-galaxy lensing and galaxy clustering: Methodology and forecasts for Dark Energy Survey

DOE PAGES

Park, Y.; Krause, E.; Dodelson, S.; ...

2016-09-30

The joint analysis of galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth function of large scale structure. Our analysis will be carried out on data from the Dark Energy Survey (DES), with its measurements of both the distribution of galaxies and the tangential shears of background galaxies induced by these foreground lenses. We develop a practical approach to modeling the assumptions and systematic effects affecting small scale lensing, which provides halo masses, and large scale galaxy clustering. Introducing parameters that characterize the halo occupation distribution (HOD), photometric redshift uncertainties, and shear measurement errors, we studymore » how external priors on different subsets of these parameters affect our growth constraints. Degeneracies within the HOD model, as well as between the HOD and the growth function, are identified as the dominant source of complication, with other systematic effects sub-dominant. The impact of HOD parameters and their degeneracies necessitate the detailed joint modeling of the galaxy sample that we employ. Finally, we conclude that DES data will provide powerful constraints on the evolution of structure growth in the universe, conservatively/optimistically constraining the growth function to 7.9%/4.8% with its first-year data that covered over 1000 square degrees, and to 3.9%/2.3% with its full five-year data that will survey 5000 square degrees, including both statistical and systematic uncertainties.« less

Joint analysis of galaxy-galaxy lensing and galaxy clustering: Methodology and forecasts for Dark Energy Survey

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

Park, Y.; Krause, E.; Dodelson, S.

The joint analysis of galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth function of large scale structure. Our analysis will be carried out on data from the Dark Energy Survey (DES), with its measurements of both the distribution of galaxies and the tangential shears of background galaxies induced by these foreground lenses. We develop a practical approach to modeling the assumptions and systematic effects affecting small scale lensing, which provides halo masses, and large scale galaxy clustering. Introducing parameters that characterize the halo occupation distribution (HOD), photometric redshift uncertainties, and shear measurement errors, we studymore » how external priors on different subsets of these parameters affect our growth constraints. Degeneracies within the HOD model, as well as between the HOD and the growth function, are identified as the dominant source of complication, with other systematic effects sub-dominant. The impact of HOD parameters and their degeneracies necessitate the detailed joint modeling of the galaxy sample that we employ. Finally, we conclude that DES data will provide powerful constraints on the evolution of structure growth in the universe, conservatively/optimistically constraining the growth function to 7.9%/4.8% with its first-year data that covered over 1000 square degrees, and to 3.9%/2.3% with its full five-year data that will survey 5000 square degrees, including both statistical and systematic uncertainties.« less

Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses

DOE PAGES

Surman, Rebecca; Mumpower, Matthew; McLaughlin, Gail

2017-02-27

Unknown nuclear masses are a major source of nuclear physics uncertainty for r-process nucleosynthesis calculations. Here we examine the systematic and statistical uncertainties that arise in r-process abundance predictions due to uncertainties in the masses of nuclear species on the neutron-rich side of stability. There is a long history of examining systematic uncertainties by the application of a variety of different mass models to r-process calculations. Here we expand upon such efforts by examining six DFT mass models, where we capture the full impact of each mass model by updating the other nuclear properties — including neutron capture rates, β-decaymore » lifetimes, and β-delayed neutron emission probabilities — that depend on the masses. Unlike systematic effects, statistical uncertainties in the r-process pattern have just begun to be explored. Here we apply a global Monte Carlo approach, starting from the latest FRDM masses and considering random mass variations within the FRDM rms error. Here, we find in each approach that uncertain nuclear masses produce dramatic uncertainties in calculated r-process yields, which can be reduced in upcoming experimental campaigns.« less

Systematic and statistical uncertainties in simulated r-process abundances due to uncertain nuclear masses

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

Surman, Rebecca; Mumpower, Matthew; McLaughlin, Gail

Unknown nuclear masses are a major source of nuclear physics uncertainty for r-process nucleosynthesis calculations. Here we examine the systematic and statistical uncertainties that arise in r-process abundance predictions due to uncertainties in the masses of nuclear species on the neutron-rich side of stability. There is a long history of examining systematic uncertainties by the application of a variety of different mass models to r-process calculations. Here we expand upon such efforts by examining six DFT mass models, where we capture the full impact of each mass model by updating the other nuclear properties — including neutron capture rates, β-decaymore » lifetimes, and β-delayed neutron emission probabilities — that depend on the masses. Unlike systematic effects, statistical uncertainties in the r-process pattern have just begun to be explored. Here we apply a global Monte Carlo approach, starting from the latest FRDM masses and considering random mass variations within the FRDM rms error. Here, we find in each approach that uncertain nuclear masses produce dramatic uncertainties in calculated r-process yields, which can be reduced in upcoming experimental campaigns.« less

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

CFHTLenS revisited: assessing concordance with Planck including astrophysical systematics

NASA Astrophysics Data System (ADS)

Joudaki, Shahab; Blake, Chris; Heymans, Catherine; Choi, Ami; Harnois-Deraps, Joachim; Hildebrandt, Hendrik; Joachimi, Benjamin; Johnson, Andrew; Mead, Alexander; Parkinson, David; Viola, Massimo; van Waerbeke, Ludovic

2017-02-01

We investigate the impact of astrophysical systematics on cosmic shear cosmological parameter constraints from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS) and the concordance with cosmic microwave background measurements by Planck. We present updated CFHTLenS cosmic shear tomography measurements extended to degree scales using a covariance calibrated by a new suite of N-body simulations. We analyse these measurements with a new model fitting pipeline, accounting for key systematic uncertainties arising from intrinsic galaxy alignments, baryonic effects in the non-linear matter power spectrum, and photometric redshift uncertainties. We examine the impact of the systematic degrees of freedom on the cosmological parameter constraints, both independently and jointly. When the systematic uncertainties are considered independently, the intrinsic alignment amplitude is the only degree of freedom that is substantially preferred by the data. When the systematic uncertainties are considered jointly, there is no consistently strong preference in favour of the more complex models. We quantify the level of concordance between the CFHTLenS and Planck data sets by employing two distinct data concordance tests, grounded in Bayesian evidence and information theory. We find that the two data concordance tests largely agree with one another and that the level of concordance between the CFHTLenS and Planck data sets is sensitive to the exact details of the systematic uncertainties included in our analysis, ranging from decisive discordance to substantial concordance as the treatment of the systematic uncertainties becomes more conservative. The least conservative scenario is the one most favoured by the cosmic shear data, but it is also the one that shows the greatest degree of discordance with Planck. The data and analysis code are publicly available at https://github.com/sjoudaki/cfhtlens_revisited.

Can reduction of uncertainties in cervix cancer brachytherapy potentially improve clinical outcome?

PubMed

Nesvacil, Nicole; Tanderup, Kari; Lindegaard, Jacob C; Pötter, Richard; Kirisits, Christian

2016-09-01

The aim of this study was to quantify the impact of different types and magnitudes of dosimetric uncertainties in cervix cancer brachytherapy (BT) on tumour control probability (TCP) and normal tissue complication probability (NTCP) curves. A dose-response simulation study was based on systematic and random dose uncertainties and TCP/NTCP models for CTV and rectum. Large patient cohorts were simulated assuming different levels of dosimetric uncertainties. TCP and NTCP were computed, based on the planned doses, the simulated dose uncertainty, and an underlying TCP/NTCP model. Systematic uncertainties of 3-20% and random uncertainties with a 5-30% standard deviation per BT fraction were analysed. Systematic dose uncertainties of 5% lead to a 1% decrease/increase of TCP/NTCP, while random uncertainties of 10% had negligible impact on the dose-response curve at clinically relevant dose levels for target and OAR. Random OAR dose uncertainties of 30% resulted in an NTCP increase of 3-4% for planned doses of 70-80Gy EQD2. TCP is robust to dosimetric uncertainties when dose prescription is in the more flat region of the dose-response curve at doses >75Gy. For OARs, improved clinical outcome is expected by reduction of uncertainties via sophisticated dose delivery and treatment verification. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Analytical Algorithms to Quantify the Uncertainty in Remaining Useful Life Prediction

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Saxena, Abhinav; Daigle, Matthew; Goebel, Kai

2013-01-01

This paper investigates the use of analytical algorithms to quantify the uncertainty in the remaining useful life (RUL) estimate of components used in aerospace applications. The prediction of RUL is affected by several sources of uncertainty and it is important to systematically quantify their combined effect by computing the uncertainty in the RUL prediction in order to aid risk assessment, risk mitigation, and decisionmaking. While sampling-based algorithms have been conventionally used for quantifying the uncertainty in RUL, analytical algorithms are computationally cheaper and sometimes, are better suited for online decision-making. While exact analytical algorithms are available only for certain special cases (for e.g., linear models with Gaussian variables), effective approximations can be made using the the first-order second moment method (FOSM), the first-order reliability method (FORM), and the inverse first-order reliability method (Inverse FORM). These methods can be used not only to calculate the entire probability distribution of RUL but also to obtain probability bounds on RUL. This paper explains these three methods in detail and illustrates them using the state-space model of a lithium-ion battery.

Uncertainty Analysis of the NASA Glenn 8x6 Supersonic Wind Tunnel

NASA Technical Reports Server (NTRS)

Stephens, Julia; Hubbard, Erin; Walter, Joel; McElroy, Tyler

2016-01-01

This paper presents methods and results of a detailed measurement uncertainty analysis that was performed for the 8- by 6-foot Supersonic Wind Tunnel located at the NASA Glenn Research Center. The statistical methods and engineering judgments used to estimate elemental uncertainties are described. The Monte Carlo method of propagating uncertainty was selected to determine the uncertainty of calculated variables of interest. A detailed description of the Monte Carlo method as applied for this analysis is provided. Detailed uncertainty results for the uncertainty in average free stream Mach number as well as other variables of interest are provided. All results are presented as random (variation in observed values about a true value), systematic (potential offset between observed and true value), and total (random and systematic combined) uncertainty. The largest sources contributing to uncertainty are determined and potential improvement opportunities for the facility are investigated.

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

DOE PAGES

Old, L.; Wojtak, R.; Pearce, F. R.; ...

2017-12-20

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously withmore » commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5. Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.« less

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

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

Old, L.; Wojtak, R.; Pearce, F. R.

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously withmore » commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5. Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.« less

The effect of rainfall measurement uncertainties on rainfall-runoff processes modelling.

PubMed

Stransky, D; Bares, V; Fatka, P

2007-01-01

Rainfall data are a crucial input for various tasks concerning the wet weather period. Nevertheless, their measurement is affected by random and systematic errors that cause an underestimation of the rainfall volume. Therefore, the general objective of the presented work was to assess the credibility of measured rainfall data and to evaluate the effect of measurement errors on urban drainage modelling tasks. Within the project, the methodology of the tipping bucket rain gauge (TBR) was defined and assessed in terms of uncertainty analysis. A set of 18 TBRs was calibrated and the results were compared to the previous calibration. This enables us to evaluate the ageing of TBRs. A propagation of calibration and other systematic errors through the rainfall-runoff model was performed on experimental catchment. It was found that the TBR calibration is important mainly for tasks connected with the assessment of peak values and high flow durations. The omission of calibration leads to up to 30% underestimation and the effect of other systematic errors can add a further 15%. The TBR calibration should be done every two years in order to catch up the ageing of TBR mechanics. Further, the authors recommend to adjust the dynamic test duration proportionally to generated rainfall intensity.

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

NASA Astrophysics Data System (ADS)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

Parameter Uncertainty Analysis Using Monte Carlo Simulations for a Regional-Scale Groundwater Model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Pohlmann, K.

2016-12-01

Regional-scale grid-based groundwater models for flow and transport often contain multiple types of parameters that can intensify the challenge of parameter uncertainty analysis. We propose a Monte Carlo approach to systematically quantify the influence of various types of model parameters on groundwater flux and contaminant travel times. The Monte Carlo simulations were conducted based on the steady-state conversion of the original transient model, which was then combined with the PEST sensitivity analysis tool SENSAN and particle tracking software MODPATH. Results identified hydrogeologic units whose hydraulic conductivity can significantly affect groundwater flux, and thirteen out of 173 model parameters that can cause large variation in travel times for contaminant particles originating from given source zones.

Expected utility violations evolve under status-based selection mechanisms.

PubMed

Dickson, Eric S

2008-10-07

The expected utility theory of decision making under uncertainty, a cornerstone of modern economics, assumes that humans linearly weight "utilities" for different possible outcomes by the probabilities with which these outcomes occur. Despite the theory's intuitive appeal, both from normative and from evolutionary perspectives, many experiments demonstrate systematic, though poorly understood, patterns of deviation from EU predictions. This paper offers a novel theoretical account of such patterns of deviation by demonstrating that EU violations can emerge from evolutionary selection when individual "status" affects inclusive fitness. In humans, battles for resources and social standing involve high-stakes decision making, and assortative mating ensures that status matters for fitness outcomes. The paper therefore proposes grounding the study of decision making under uncertainty in an evolutionary game-theoretic framework.

Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals

NASA Astrophysics Data System (ADS)

Gorbunov, Michael E.; Kirchengast, Gottfried

2018-01-01

A new reference occultation processing system (rOPS) will include a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval chain with integrated uncertainty propagation. In this paper, we focus on wave-optics bending angle (BA) retrieval in the lower troposphere and introduce (1) an empirically estimated boundary layer bias (BLB) model then employed to reduce the systematic uncertainty of excess phases and bending angles in about the lowest 2 km of the troposphere and (2) the estimation of (residual) systematic uncertainties and their propagation together with random uncertainties from excess phase to bending angle profiles. Our BLB model describes the estimated bias of the excess phase transferred from the estimated bias of the bending angle, for which the model is built, informed by analyzing refractivity fluctuation statistics shown to induce such biases. The model is derived from regression analysis using a large ensemble of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) RO observations and concurrent European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields. It is formulated in terms of predictors and adaptive functions (powers and cross products of predictors), where we use six main predictors derived from observations: impact altitude, latitude, bending angle and its standard deviation, canonical transform (CT) amplitude, and its fluctuation index. Based on an ensemble of test days, independent of the days of data used for the regression analysis to establish the BLB model, we find the model very effective for bias reduction and capable of reducing bending angle and corresponding refractivity biases by about a factor of 5. The estimated residual systematic uncertainty, after the BLB profile subtraction, is lower bounded by the uncertainty from the (indirect) use of ECMWF analysis fields but is significantly lower than the systematic uncertainty without BLB correction. The systematic and random uncertainties are propagated from excess phase to bending angle profiles, using a perturbation approach and the wave-optical method recently introduced by Gorbunov and Kirchengast (2015), starting with estimated excess phase uncertainties. The results are encouraging and this uncertainty propagation approach combined with BLB correction enables a robust reduction and quantification of the uncertainties of excess phases and bending angles in the lower troposphere.

Erratum: Measurement of azimuthal asymmetries in inclusive production of hadron pairs in e⁺e⁻ annihilation at √s=10.58 GeV [Phys. Rev. D 78, 032011 (2008)

DOE PAGES

Seidl, R.; Grosse Perdekamp, M.; Ogawa, A.; ...

2012-08-09

In the original article, it was found in Monte Carlo simulations that the reconstructed A₀ results are roughly consistent with the generated asymmetries, while the A₁₂ results systematically underestimate the generated asymmetries. This underestimation can be attributed to the difference between the reconstructed thrust axis and the original quark-antiquark axis. The corresponding correction factors are 1.6 ± 0.04 for the A₁₂ results and 1.11 ± 0.05 for the A₀ results. Because of a flaw in the original analysis program, these correction factors were not applied to the A UC-type asymmetries in Table V as well as in some figures. Inmore » addition, a small mistake in the error propagation in the charm correction resulted in slightly underestimated statistical uncertainties. These omissions affect all but the charm asymmetry results. The correct central values are therefore given in Tables IV and V of this Erratum. The systematic uncertainties of the original publication remain unchanged.« less

A New Approach for Obtaining Cosmological Constraints from Type Ia Supernovae using Approximate Bayesian Computation

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

Jennings, Elise; Wolf, Rachel; Sako, Masao

2016-11-09

Cosmological parameter estimation techniques that robustly account for systematic measurement uncertainties will be crucial for the next generation of cosmological surveys. We present a new analysis method, superABC, for obtaining cosmological constraints from Type Ia supernova (SN Ia) light curves using Approximate Bayesian Computation (ABC) without any likelihood assumptions. The ABC method works by using a forward model simulation of the data where systematic uncertainties can be simulated and marginalized over. A key feature of the method presented here is the use of two distinct metrics, the `Tripp' and `Light Curve' metrics, which allow us to compare the simulated data to the observed data set. The Tripp metric takes as input the parameters of models fit to each light curve with the SALT-II method, whereas the Light Curve metric uses the measured fluxes directly without model fitting. We apply the superABC sampler to a simulated data set ofmore » $$\\sim$$1000 SNe corresponding to the first season of the Dark Energy Survey Supernova Program. Varying $$\\Omega_m, w_0, \\alpha$$ and $$\\beta$$ and a magnitude offset parameter, with no systematics we obtain $$\\Delta(w_0) = w_0^{\\rm true} - w_0^{\\rm best \\, fit} = -0.036\\pm0.109$$ (a $$\\sim11$$% 1$$\\sigma$$ uncertainty) using the Tripp metric and $$\\Delta(w_0) = -0.055\\pm0.068$$ (a $$\\sim7$$% 1$$\\sigma$$ uncertainty) using the Light Curve metric. Including 1% calibration uncertainties in four passbands, adding 4 more parameters, we obtain $$\\Delta(w_0) = -0.062\\pm0.132$$ (a $$\\sim14$$% 1$$\\sigma$$ uncertainty) using the Tripp metric. Overall we find a $17$% increase in the uncertainty on $$w_0$$ with systematics compared to without. We contrast this with a MCMC approach where systematic effects are approximately included. We find that the MCMC method slightly underestimates the impact of calibration uncertainties for this simulated data set.« less

Planck 2015 results. III. LFI systematic uncertainties

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Basak, S.; Battaglia, P.; Battaner, E.; Benabed, K.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Burigana, C.; Butler, R. C.; Calabrese, E.; Catalano, A.; Christensen, P. R.; Colombo, L. P. L.; Cruz, M.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Dickinson, C.; Diego, J. M.; Doré, O.; Ducout, A.; Dupac, X.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Frailis, M.; Franceschet, C.; Franceschi, E.; Galeotta, S.; Galli, S.; Ganga, K.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Harrison, D. L.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Keihänen, E.; Keskitalo, R.; Kiiveri, K.; Kisner, T. S.; Knoche, J.; Krachmalnicoff, N.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; Lindholm, V.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Meinhold, P. R.; Mennella, A.; Migliaccio, M.; Mitra, S.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Nati, F.; Natoli, P.; Noviello, F.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Pearson, T. J.; Perdereau, O.; Pettorino, V.; Piacentini, F.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Scott, D.; Stolyarov, V.; Stompor, R.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vassallo, T.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Watson, R.; Wehus, I. K.; Yvon, D.; Zacchei, A.; Zibin, J. P.; Zonca, A.

2016-09-01

We present the current accounting of systematic effect uncertainties for the Low Frequency Instrument (LFI) that are relevant to the 2015 release of the Planck cosmological results, showing the robustness and consistency of our data set, especially for polarization analysis. We use two complementary approaches: (I) simulations based on measured data and physical models of the known systematic effects; and (II) analysis of difference maps containing the same sky signal ("null-maps"). The LFI temperature data are limited by instrumental noise. At large angular scales the systematic effects are below the cosmic microwave background (CMB) temperature power spectrum by several orders of magnitude. In polarization the systematic uncertainties are dominated by calibration uncertainties and compete with the CMB E-modes in the multipole range 10-20. Based on our model of all known systematic effects, we show that these effects introduce a slight bias of around 0.2σ on the reionization optical depth derived from the 70GHz EE spectrum using the 30 and 353GHz channels as foreground templates. At 30GHz the systematic effects are smaller than the Galactic foreground at all scales in temperature and polarization, which allows us to consider this channel as a reliable template of synchrotron emission. We assess the residual uncertainties due to LFI effects on CMB maps and power spectra after component separation and show that these effects are smaller than the CMB amplitude at all scales. We also assess the impact on non-Gaussianity studies and find it to be negligible. Some residuals still appear in null maps from particular sky survey pairs, particularly at 30 GHz, suggesting possible straylight contamination due to an imperfect knowledge of the beam far sidelobes.

Planck 2015 results: III. LFI systematic uncertainties

DOE PAGES

Ade, P. A. R.; Aumont, J.; Baccigalupi, C.; ...

2016-09-20

In this paper, we present the current accounting of systematic effect uncertainties for the Low Frequency Instrument (LFI) that are relevant to the 2015 release of the Planck cosmological results, showing the robustness and consistency of our data set, especially for polarization analysis. We use two complementary approaches: (i) simulations based on measured data and physical models of the known systematic effects; and (ii) analysis of difference maps containing the same sky signal (“null-maps”). The LFI temperature data are limited by instrumental noise. At large angular scales the systematic effects are below the cosmic microwave background (CMB) temperature power spectrummore » by several orders of magnitude. In polarization the systematic uncertainties are dominated by calibration uncertainties and compete with the CMB E-modes in the multipole range 10–20. Based on our model of all known systematic effects, we show that these effects introduce a slight bias of around 0.2σ on the reionization optical depth derived from the 70GHz EE spectrum using the 30 and 353GHz channels as foreground templates. At 30GHz the systematic effects are smaller than the Galactic foreground at all scales in temperature and polarization, which allows us to consider this channel as a reliable template of synchrotron emission. We assess the residual uncertainties due to LFI effects on CMB maps and power spectra after component separation and show that these effects are smaller than the CMB amplitude at all scales. We also assess the impact on non-Gaussianity studies and find it to be negligible. Finally, some residuals still appear in null maps from particular sky survey pairs, particularly at 30 GHz, suggesting possible straylight contamination due to an imperfect knowledge of the beam far sidelobes.« less

Planck 2015 results: III. LFI systematic uncertainties

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

Ade, P. A. R.; Aumont, J.; Baccigalupi, C.

In this paper, we present the current accounting of systematic effect uncertainties for the Low Frequency Instrument (LFI) that are relevant to the 2015 release of the Planck cosmological results, showing the robustness and consistency of our data set, especially for polarization analysis. We use two complementary approaches: (i) simulations based on measured data and physical models of the known systematic effects; and (ii) analysis of difference maps containing the same sky signal (“null-maps”). The LFI temperature data are limited by instrumental noise. At large angular scales the systematic effects are below the cosmic microwave background (CMB) temperature power spectrummore » by several orders of magnitude. In polarization the systematic uncertainties are dominated by calibration uncertainties and compete with the CMB E-modes in the multipole range 10–20. Based on our model of all known systematic effects, we show that these effects introduce a slight bias of around 0.2σ on the reionization optical depth derived from the 70GHz EE spectrum using the 30 and 353GHz channels as foreground templates. At 30GHz the systematic effects are smaller than the Galactic foreground at all scales in temperature and polarization, which allows us to consider this channel as a reliable template of synchrotron emission. We assess the residual uncertainties due to LFI effects on CMB maps and power spectra after component separation and show that these effects are smaller than the CMB amplitude at all scales. We also assess the impact on non-Gaussianity studies and find it to be negligible. Finally, some residuals still appear in null maps from particular sky survey pairs, particularly at 30 GHz, suggesting possible straylight contamination due to an imperfect knowledge of the beam far sidelobes.« less

Uncertainty in monitoring E. coli concentrations in streams and stormwater runoff

NASA Astrophysics Data System (ADS)

Harmel, R. D.; Hathaway, J. M.; Wagner, K. L.; Wolfe, J. E.; Karthikeyan, R.; Francesconi, W.; McCarthy, D. T.

2016-03-01

Microbial contamination of surface waters, a substantial public health concern throughout the world, is typically identified by fecal indicator bacteria such as Escherichia coli. Thus, monitoring E. coli concentrations is critical to evaluate current conditions, determine restoration effectiveness, and inform model development and calibration. An often overlooked component of these monitoring and modeling activities is understanding the inherent random and systematic uncertainty present in measured data. In this research, a review and subsequent analysis was performed to identify, document, and analyze measurement uncertainty of E. coli data collected in stream flow and stormwater runoff as individual discrete samples or throughout a single runoff event. Data on the uncertainty contributed by sample collection, sample preservation/storage, and laboratory analysis in measured E. coli concentrations were compiled and analyzed, and differences in sampling method and data quality scenarios were compared. The analysis showed that: (1) manual integrated sampling produced the lowest random and systematic uncertainty in individual samples, but automated sampling typically produced the lowest uncertainty when sampling throughout runoff events; (2) sample collection procedures often contributed the highest amount of uncertainty, although laboratory analysis introduced substantial random uncertainty and preservation/storage introduced substantial systematic uncertainty under some scenarios; and (3) the uncertainty in measured E. coli concentrations was greater than that of sediment and nutrients, but the difference was not as great as may be assumed. This comprehensive analysis of uncertainty in E. coli concentrations measured in streamflow and runoff should provide valuable insight for designing E. coli monitoring projects, reducing uncertainty in quality assurance efforts, regulatory and policy decision making, and fate and transport modeling.

Insights on the impact of systematic model errors on data assimilation performance in changing catchments

NASA Astrophysics Data System (ADS)

Pathiraja, S.; Anghileri, D.; Burlando, P.; Sharma, A.; Marshall, L.; Moradkhani, H.

2018-03-01

The global prevalence of rapid and extensive land use change necessitates hydrologic modelling methodologies capable of handling non-stationarity. This is particularly true in the context of Hydrologic Forecasting using Data Assimilation. Data Assimilation has been shown to dramatically improve forecast skill in hydrologic and meteorological applications, although such improvements are conditional on using bias-free observations and model simulations. A hydrologic model calibrated to a particular set of land cover conditions has the potential to produce biased simulations when the catchment is disturbed. This paper sheds new light on the impacts of bias or systematic errors in hydrologic data assimilation, in the context of forecasting in catchments with changing land surface conditions and a model calibrated to pre-change conditions. We posit that in such cases, the impact of systematic model errors on assimilation or forecast quality is dependent on the inherent prediction uncertainty that persists even in pre-change conditions. Through experiments on a range of catchments, we develop a conceptual relationship between total prediction uncertainty and the impacts of land cover changes on the hydrologic regime to demonstrate how forecast quality is affected when using state estimation Data Assimilation with no modifications to account for land cover changes. This work shows that systematic model errors as a result of changing or changed catchment conditions do not always necessitate adjustments to the modelling or assimilation methodology, for instance through re-calibration of the hydrologic model, time varying model parameters or revised offline/online bias estimation.

Uncertainty Analysis of Seebeck Coefficient and Electrical Resistivity Characterization

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

In order to provide a complete description of a materials thermoelectric power factor, in addition to the measured nominal value, an uncertainty interval is required. The uncertainty may contain sources of measurement error including systematic bias error and precision error of a statistical nature. The work focuses specifically on the popular ZEM-3 (Ulvac Technologies) measurement system, but the methods apply to any measurement system. The analysis accounts for sources of systematic error including sample preparation tolerance, measurement probe placement, thermocouple cold-finger effect, and measurement parameters; in addition to including uncertainty of a statistical nature. Complete uncertainty analysis of a measurement system allows for more reliable comparison of measurement data between laboratories.

IGM CONSTRAINTS FROM THE SDSS-III/BOSS DR9 Lyα FOREST TRANSMISSION PROBABILITY DISTRIBUTION FUNCTION

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

Lee, Khee-Gan; Hennawi, Joseph F.; Spergel, David N.

2015-02-01

The Lyα forest transmission probability distribution function (PDF) is an established probe of the intergalactic medium (IGM) astrophysics, especially the temperature-density relationship of the IGM. We measure the transmission PDF from 3393 Baryon Oscillations Spectroscopic Survey (BOSS) quasars from Sloan Digital Sky Survey Data Release 9, and compare with mock spectra that include careful modeling of the noise, continuum, and astrophysical uncertainties. The BOSS transmission PDFs, measured at (z) = [2.3, 2.6, 3.0], are compared with PDFs created from mock spectra drawn from a suite of hydrodynamical simulations that sample the IGM temperature-density relationship, γ, and temperature at mean density,more » T {sub 0}, where T(Δ) = T {sub 0}Δ{sup γ} {sup –} {sup 1}. We find that a significant population of partial Lyman-limit systems (LLSs) with a column-density distribution slope of β{sub pLLS} ∼ – 2 are required to explain the data at the low-transmission end of transmission PDF, while uncertainties in the mean Lyα forest transmission affect the high-transmission end. After modeling the LLSs and marginalizing over mean transmission uncertainties, we find that γ = 1.6 best describes the data over our entire redshift range, although constraints on T {sub 0} are affected by systematic uncertainties. Within our model framework, isothermal or inverted temperature-density relationships (γ ≤ 1) are disfavored at a significance of over 4σ, although this could be somewhat weakened by cosmological and astrophysical uncertainties that we did not model.« less

Introducing uncertainty analysis of nucleation and crystal growth models in Process Analytical Technology (PAT) system design of crystallization processes.

PubMed

Samad, Noor Asma Fazli Abdul; Sin, Gürkan; Gernaey, Krist V; Gani, Rafiqul

2013-11-01

This paper presents the application of uncertainty and sensitivity analysis as part of a systematic model-based process monitoring and control (PAT) system design framework for crystallization processes. For the uncertainty analysis, the Monte Carlo procedure is used to propagate input uncertainty, while for sensitivity analysis, global methods including the standardized regression coefficients (SRC) and Morris screening are used to identify the most significant parameters. The potassium dihydrogen phosphate (KDP) crystallization process is used as a case study, both in open-loop and closed-loop operation. In the uncertainty analysis, the impact on the predicted output of uncertain parameters related to the nucleation and the crystal growth model has been investigated for both a one- and two-dimensional crystal size distribution (CSD). The open-loop results show that the input uncertainties lead to significant uncertainties on the CSD, with appearance of a secondary peak due to secondary nucleation for both cases. The sensitivity analysis indicated that the most important parameters affecting the CSDs are nucleation order and growth order constants. In the proposed PAT system design (closed-loop), the target CSD variability was successfully reduced compared to the open-loop case, also when considering uncertainty in nucleation and crystal growth model parameters. The latter forms a strong indication of the robustness of the proposed PAT system design in achieving the target CSD and encourages its transfer to full-scale implementation. Copyright © 2013 Elsevier B.V. All rights reserved.

Asteroseismic modelling of solar-type stars: internal systematics from input physics and surface correction methods

NASA Astrophysics Data System (ADS)

Nsamba, B.; Campante, T. L.; Monteiro, M. J. P. F. G.; Cunha, M. S.; Rendle, B. M.; Reese, D. R.; Verma, K.

2018-04-01

Asteroseismic forward modelling techniques are being used to determine fundamental properties (e.g. mass, radius, and age) of solar-type stars. The need to take into account all possible sources of error is of paramount importance towards a robust determination of stellar properties. We present a study of 34 solar-type stars for which high signal-to-noise asteroseismic data is available from multi-year Kepler photometry. We explore the internal systematics on the stellar properties, that is, associated with the uncertainty in the input physics used to construct the stellar models. In particular, we explore the systematics arising from: (i) the inclusion of the diffusion of helium and heavy elements; and (ii) the uncertainty in solar metallicity mixture. We also assess the systematics arising from (iii) different surface correction methods used in optimisation/fitting procedures. The systematics arising from comparing results of models with and without diffusion are found to be 0.5%, 0.8%, 2.1%, and 16% in mean density, radius, mass, and age, respectively. The internal systematics in age are significantly larger than the statistical uncertainties. We find the internal systematics resulting from the uncertainty in solar metallicity mixture to be 0.7% in mean density, 0.5% in radius, 1.4% in mass, and 6.7% in age. The surface correction method by Sonoi et al. and Ball & Gizon's two-term correction produce the lowest internal systematics among the different correction methods, namely, ˜1%, ˜1%, ˜2%, and ˜8% in mean density, radius, mass, and age, respectively. Stellar masses obtained using the surface correction methods by Kjeldsen et al. and Ball & Gizon's one-term correction are systematically higher than those obtained using frequency ratios.

Impact of systematic uncertainties for the CP violation measurement in superbeam experiments

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

Meloni, Davide

We present a three-flavour fit to the recent ν{sub µ} → ν{sub e} T2K oscillation data with different models for the neutrino-nucleus cross section. We show that, even for a limited statistics, the allowed regions and best fit points in the (θ{sub 13}, δ{sub CP}) plane are affected if, instead of using the Fermi Gas model to describe the quasielastic cross section, we employ a model including the multinucleon emission channel [1].

Global 3ν oscillation analysis: Status of unknown parameters and future systematic challenges for ORCA and PINGU

NASA Astrophysics Data System (ADS)

Capozzi, Francesco; Lisi, Eligio; Marrone, Antonio

2016-04-01

Within the standard 3ν oscillation framework, we illustrate the status of currently unknown oscillation parameters: the θ23 octant, the mass hierarchy (normal or inverted), and the possible CP-violating phase δ, as derived by a (preliminary) global analysis of oscillation data available in 2015. We then discuss some challenges that will be faced by future, high-statistics analyses of spectral data, starting with one-dimensional energy spectra in reactor experiments, and concluding with two-dimensional energy-angle spectra in large-volume atmospheric experiments. It is shown that systematic uncertainties in the spectral shapes can noticeably affect the prospective sensitivities to unknown oscillation parameters, in particular to the mass hierarchy.

Instrumentation-related uncertainty of reflectance and transmittance measurements with a two-channel spectrophotometer.

PubMed

Peest, Christian; Schinke, Carsten; Brendel, Rolf; Schmidt, Jan; Bothe, Karsten

2017-01-01

Spectrophotometers are operated in numerous fields of science and industry for a variety of applications. In order to provide confidence for the measured data, analyzing the associated uncertainty is valuable. However, the uncertainty of the measurement results is often unknown or reduced to sample-related contributions. In this paper, we describe our approach for the systematic determination of the measurement uncertainty of the commercially available two-channel spectrophotometer Agilent Cary 5000 in accordance with the Guide to the expression of uncertainty in measurements. We focus on the instrumentation-related uncertainty contributions rather than the specific application and thus outline a general procedure which can be adapted for other instruments. Moreover, we discover a systematic signal deviation due to the inertia of the measurement amplifier and develop and apply a correction procedure. Thereby we increase the usable dynamic range of the instrument by more than one order of magnitude. We present methods for the quantification of the uncertainty contributions and combine them into an uncertainty budget for the device.

HZETRN radiation transport validation using balloon-based experimental data

NASA Astrophysics Data System (ADS)

Warner, James E.; Norman, Ryan B.; Blattnig, Steve R.

2018-05-01

The deterministic radiation transport code HZETRN (High charge (Z) and Energy TRaNsport) was developed by NASA to study the effects of cosmic radiation on astronauts and instrumentation shielded by various materials. This work presents an analysis of computed differential flux from HZETRN compared with measurement data from three balloon-based experiments over a range of atmospheric depths, particle types, and energies. Model uncertainties were quantified using an interval-based validation metric that takes into account measurement uncertainty both in the flux and the energy at which it was measured. Average uncertainty metrics were computed for the entire dataset as well as subsets of the measurements (by experiment, particle type, energy, etc.) to reveal any specific trends of systematic over- or under-prediction by HZETRN. The distribution of individual model uncertainties was also investigated to study the range and dispersion of errors beyond just single scalar and interval metrics. The differential fluxes from HZETRN were generally well-correlated with balloon-based measurements; the median relative model difference across the entire dataset was determined to be 30%. The distribution of model uncertainties, however, revealed that the range of errors was relatively broad, with approximately 30% of the uncertainties exceeding ± 40%. The distribution also indicated that HZETRN systematically under-predicts the measurement dataset as a whole, with approximately 80% of the relative uncertainties having negative values. Instances of systematic bias for subsets of the data were also observed, including a significant underestimation of alpha particles and protons for energies below 2.5 GeV/u. Muons were found to be systematically over-predicted at atmospheric depths deeper than 50 g/cm2 but under-predicted for shallower depths. Furthermore, a systematic under-prediction of alpha particles and protons was observed below the geomagnetic cutoff, suggesting that improvements to the light ion production cross sections in HZETRN should be investigated.

Uncertainty Analysis and Order-by-Order Optimization of Chiral Nuclear Interactions

DOE PAGES

Carlsson, Boris; Forssen, Christian; Fahlin Strömberg, D.; ...

2016-02-24

Chiral effective field theory ( ΧEFT) provides a systematic approach to describe low-energy nuclear forces. Moreover, EFT is able to provide well-founded estimates of statistical and systematic uncertainties | although this unique advantage has not yet been fully exploited. We ll this gap by performing an optimization and statistical analysis of all the low-energy constants (LECs) up to next-to-next-to-leading order. Our optimization protocol corresponds to a simultaneous t to scattering and bound-state observables in the pion-nucleon, nucleon-nucleon, and few-nucleon sectors, thereby utilizing the full model capabilities of EFT. Finally, we study the effect on other observables by demonstrating forward-error-propagation methodsmore » that can easily be adopted by future works. We employ mathematical optimization and implement automatic differentiation to attain e cient and machine-precise first- and second-order derivatives of the objective function with respect to the LECs. This is also vital for the regression analysis. We use power-counting arguments to estimate the systematic uncertainty that is inherent to EFT and we construct chiral interactions at different orders with quantified uncertainties. Statistical error propagation is compared with Monte Carlo sampling showing that statistical errors are in general small compared to systematic ones. In conclusion, we find that a simultaneous t to different sets of data is critical to (i) identify the optimal set of LECs, (ii) capture all relevant correlations, (iii) reduce the statistical uncertainty, and (iv) attain order-by-order convergence in EFT. Furthermore, certain systematic uncertainties in the few-nucleon sector are shown to get substantially magnified in the many-body sector; in particlar when varying the cutoff in the chiral potentials. The methodology and results presented in this Paper open a new frontier for uncertainty quantification in ab initio nuclear theory.« less

Confronting dynamics and uncertainty in optimal decision making for conservation

USGS Publications Warehouse

Williams, Byron K.; Johnson, Fred A.

2013-01-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making--a careful consideration of values, actions, and outcomes.

Confronting dynamics and uncertainty in optimal decision making for conservation

NASA Astrophysics Data System (ADS)

Williams, Byron K.; Johnson, Fred A.

2013-06-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making—a careful consideration of values, actions, and outcomes.

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

NASA Astrophysics Data System (ADS)

Lissner, T. K.; Reusser, D. E.; Schewe, J.; Lakes, T.; Kropp, J. P.

2014-10-01

Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models, as well as greenhouse gas scenarios, are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure what is referred to here as AHEAD (Adequate Human livelihood conditions for wEll-being And Development). Based on a trans-disciplinary sample of concepts addressing human well-being and livelihoods, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows for the uncertainty of climate and impact model projections to be identified and differentiated. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that livelihood conditions are compromised by water scarcity in 34 countries. However, more often, AHEAD fulfilment is limited through other elements. The analysis shows that the water-specific uncertainty ranges of the model output are outside relevant thresholds for AHEAD for 65 out of 111 countries, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. In 46 of the countries in the analysis, water-specific uncertainty is relevant to AHEAD. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy decisions.

PTV margin determination in conformal SRT of intracranial lesions

PubMed Central

Parker, Brent C.; Shiu, Almon S.; Maor, Moshe H.; Lang, Frederick F.; Liu, H. Helen; White, R. Allen; Antolak, John A.

2002-01-01

The planning target volume (PTV) includes the clinical target volume (CTV) to be irradiated and a margin to account for uncertainties in the treatment process. Uncertainties in miniature multileaf collimator (mMLC) leaf positioning, CT scanner spatial localization, CT‐MRI image fusion spatial localization, and Gill‐Thomas‐Cosman (GTC) relocatable head frame repositioning were quantified for the purpose of determining a minimum PTV margin that still delivers a satisfactory CTV dose. The measured uncertainties were then incorporated into a simple Monte Carlo calculation for evaluation of various margin and fraction combinations. Satisfactory CTV dosimetric criteria were selected to be a minimum CTV dose of 95% of the PTV dose and at least 95% of the CTV receiving 100% of the PTV dose. The measured uncertainties were assumed to be Gaussian distributions. Systematic errors were added linearly and random errors were added in quadrature assuming no correlation to arrive at the total combined error. The Monte Carlo simulation written for this work examined the distribution of cumulative dose volume histograms for a large patient population using various margin and fraction combinations to determine the smallest margin required to meet the established criteria. The program examined 5 and 30 fraction treatments, since those are the only fractionation schemes currently used at our institution. The fractionation schemes were evaluated using no margin, a margin of just the systematic component of the total uncertainty, and a margin of the systematic component plus one standard deviation of the total uncertainty. It was concluded that (i) a margin of the systematic error plus one standard deviation of the total uncertainty is the smallest PTV margin necessary to achieve the established CTV dose criteria, and (ii) it is necessary to determine the uncertainties introduced by the specific equipment and procedures used at each institution since the uncertainties may vary among locations. PACS number(s): 87.53.Kn, 87.53.Ly PMID:12132939

Geodetic imaging of tectonic deformation with InSAR

NASA Astrophysics Data System (ADS)

Fattahi, Heresh

Precise measurements of ground deformation across the plate boundaries are crucial observations to evaluate the location of strain localization and to understand the pattern of strain accumulation at depth. Such information can be used to evaluate the possible location and magnitude of future earthquakes. Interferometric Synthetic Aperture Radar (InSAR) potentially can deliver small-scale (few mm/yr) ground displacement over long distances (hundreds of kilometers) across the plate boundaries and over continents. However, Given the ground displacement as our signal of interest, the InSAR observations of ground deformation are usually affected by several sources of systematic and random noises. In this dissertation I identify several sources of systematic and random noise, develop new methods to model and mitigate the systematic noise and to evaluate the uncertainty of the ground displacement measured with InSAR. I use the developed approach to characterize the tectonic deformation and evaluate the rate of strain accumulation along the Chaman fault system, the western boundary of the India with Eurasia tectonic plates. I evaluate the bias due to the topographic residuals in the InSAR range-change time-series and develope a new method to estimate the topographic residuals and mitigate the effect from the InSAR range-change time-series (Chapter 2). I develop a new method to evaluate the uncertainty of the InSAR velocity field due to the uncertainty of the satellite orbits (Chapter 3) and a new algorithm to automatically detect and correct the phase unwrapping errors in a dense network of interferograms (Chapter 4). I develop a new approach to evaluate the impact of systematic and stochastic components of the tropospheric delay on the InSAR displacement time-series and its uncertainty (Chapter 5). Using the new InSAR time-series approach developed in the previous chapters, I study the tectonic deformation across the western boundary of the India plate with Eurasia and evaluated the rate of strain accumulation along the Chaman fault system (Chapter 5). I also evaluate the co-seismic and post-seismic displacement of a moderate M5.5 earthquake on the Ghazaband fault (Chapter 6). The developed methods to mitigate the systematic noise from InSAR time-series, significantly improve the accuracy of the InSAR displacement time-series and velocity. The approaches to evaluate the effect of the stochastic components of noise in InSAR displacement time-series enable us to obtain the variance-covariance matrix of the InSAR displacement time-series and to express their uncertainties. The effect of the topographic residuals in the InSAR range-change time-series is proportional to the perpendicular baseline history of the set of SAR acquisitions. The proposed method for topographic residual correction, efficiently corrects the displacement time-series. Evaluation of the uncertainty of velocity due to the orbital errors shows that for modern SAR satellites with precise orbits such as TerraSAR-X and Sentinel-1, the uncertainty of 0.2 mm/yr per 100 km and for older satellites with less accurate orbits such as ERS and Envisat, the uncertainty of 1.5 and 0.5mm/yr per 100 km, respectively are achievable. However, the uncertainty due to the orbital errors depends on the orbital uncertainties, the number and time span of SAR acquisitions. Contribution of the tropospheric delay to the InSAR range-change time-series can be subdivided to systematic (seasonal delay) and stochastic components. The systematic component biases the displacement times-series and velocity field as a function of the acquisition time and the non-seasonal component significantly contributes to the InSAR uncertainty. Both components are spatially correlated and therefore the covariance of noise between pixels should be considered for evaluating the uncertainty due to the random tropospheric delay. The relative velocity uncertainty due to the random tropospheric delay depends on the scatter of the random tropospheric delay, and is inversely proportional to the number of acquisitions, and the total time span covered by the SAR acquisitions. InSAR observations across the Chaman fault system shows that relative motion between India and Eurasia in the western boundary is distributed among different faults. The InSAR velocity field indicates strain localization on the Chaman fault and Ghazaband fault with slip rates of ~8 and ~16 mm/yr, respectively. High rate of strain accumulation on the Ghazaband fault and lack of evidence for rupturing the fault during the 1935 Quetta earthquake indicates that enough strain has been accumulated for large (M>7) earthquake, which threatens Balochistan and the City of Quetta. Chaman fault from latitudes ~29.5 N to ~32.5 N is creeping with a maximum surface creep rate of 8 mm/yr, which indicates that Chaman fault is only partially locked and therefore moderate earthquakes (M<7) similar to what has been recorded in last 100 years are expected.

Prevalence of Pseudobulbar Affect following Stroke: A Systematic Review and Meta-Analysis.

PubMed

Gillespie, David C; Cadden, Amy P; Lees, Rosalind; West, Robert M; Broomfield, Niall M

2016-03-01

Several studies have reported that emotional lability is a common consequence of stroke. However, there is uncertainty about the "true" prevalence of the condition because, across these studies, patients have been recruited at different stages of recovery, from different settings, and using different diagnostic methods. There have been no systematic reviews of the published evidence to ascertain how the prevalence of poststroke pseudobulbar affect (PBA) might vary according to these factors. A systematic review and meta-analysis of the published literature were undertaken. A total of 15 studies (n = 3391 participants) met inclusion criteria for the review. Meta-analysis estimated that the prevalence of PBA was 17% (95% confidence interval 12%-24%) acutely (<1 month post stroke), 20% (14%-29%) post acutely (1-6 months post stroke), and 12% (8%-17%) in the medium to longer term (>6 months post stroke). The evidence from the published literature, although limited, is that crying is a more common PBA presentation following stroke than laughter. PBA is a common condition that affects approximately 1 in 5 stroke survivors at the acute and postacute phases, and 1 in 8 survivors beyond 6 months post stroke. These prevalence data are very important for clinicians and the commissioners of services. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Ensemble-based uncertainty quantification for coordination and control of thermostatically controlled loads

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

Li, Weixuan; Lian, Jianming; Engel, Dave

2017-07-27

This paper presents a general uncertainty quantification (UQ) framework that provides a systematic analysis of the uncertainty involved in the modeling of a control system, and helps to improve the performance of a control strategy.

Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization

NASA Astrophysics Data System (ADS)

Gatti, M.; Vielzeuf, P.; Davis, C.; Cawthon, R.; Rau, M. M.; DeRose, J.; De Vicente, J.; Alarcon, A.; Rozo, E.; Gaztanaga, E.; Hoyle, B.; Miquel, R.; Bernstein, G. M.; Bonnett, C.; Carnero Rosell, A.; Castander, F. J.; Chang, C.; da Costa, L. N.; Gruen, D.; Gschwend, J.; Hartley, W. G.; Lin, H.; MacCrann, N.; Maia, M. A. G.; Ogando, R. L. C.; Roodman, A.; Sevilla-Noarbe, I.; Troxel, M. A.; Wechsler, R. H.; Asorey, J.; Davis, T. M.; Glazebrook, K.; Hinton, S. R.; Lewis, G.; Lidman, C.; Macaulay, E.; Möller, A.; O'Neill, C. R.; Sommer, N. E.; Uddin, S. A.; Yuan, F.; Zhang, B.; Abbott, T. M. C.; Allam, S.; Annis, J.; Bechtol, K.; Brooks, D.; Burke, D. L.; Carollo, D.; Carrasco Kind, M.; Carretero, J.; Cunha, C. E.; D'Andrea, C. B.; DePoy, D. L.; Desai, S.; Eifler, T. F.; Evrard, A. E.; Flaugher, B.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gerdes, D. W.; Goldstein, D. A.; Gruendl, R. A.; Gutierrez, G.; Honscheid, K.; Hoormann, J. K.; Jain, B.; James, D. J.; Jarvis, M.; Jeltema, T.; Johnson, M. W. G.; Johnson, M. D.; Krause, E.; Kuehn, K.; Kuhlmann, S.; Kuropatkin, N.; Li, T. S.; Lima, M.; Marshall, J. L.; Melchior, P.; Menanteau, F.; Nichol, R. C.; Nord, B.; Plazas, A. A.; Reil, K.; Rykoff, E. S.; Sako, M.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Sheldon, E.; Smith, M.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Thomas, D.; Tucker, B. E.; Tucker, D. L.; Vikram, V.; Walker, A. R.; Weller, J.; Wester, W.; Wolf, R. C.

2018-06-01

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing source galaxies from the Dark Energy Survey Year 1 sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We apply the method to two photo-z codes run in our simulated data: Bayesian Photometric Redshift and Directional Neighbourhood Fitting. We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering versus photo-zs. The systematic uncertainty in the mean redshift bias of the source galaxy sample is Δz ≲ 0.02, though the precise value depends on the redshift bin under consideration. We discuss possible ways to mitigate the impact of our dominant systematics in future analyses.

Bias analysis applied to Agricultural Health Study publications to estimate non-random sources of uncertainty.

PubMed

Lash, Timothy L

2007-11-26

The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a qualitative description of study limitations. The latter approach is likely to lead to overconfidence regarding the potential for causal associations, whereas the former safeguards against such overinterpretations. Furthermore, such analyses, once programmed, allow rapid implementation of alternative assignments of probability distributions to the bias parameters, so elevate the plane of discussion regarding study bias from characterizing studies as "valid" or "invalid" to a critical and quantitative discussion of sources of uncertainty.

Time-delay test of general relativity and Earth-Mars ephemeris improvement from analysis of Mariner 9 tracking data

NASA Technical Reports Server (NTRS)

Shapiro, I. I.; Reasenberg, R. D.

1973-01-01

Because of the large systematic errors that accompany the conversion of spacecraft ranging data to equivalent Earth-Mars time delays, the corresponding determination of gamma does not now allow the predictions of general relativity to be distinguished from those of the Brans-Dicke scalar-tensor theory with the fraction s of scalar field admixture being 0.06. The uncertainty in the determination of (1 plus gamma)/2 at the present stage of the Mariner 9 data analysis is at about the 10% level. The ephemeris of Mars suffers from the same problem: Only with the elimination of a major fraction of the systematic errors affecting the Mariner 9 pseudo observables will a truly substantial improvement be possible in the determination of the orbit.

ACCOUNTING FOR CALIBRATION UNCERTAINTIES IN X-RAY ANALYSIS: EFFECTIVE AREAS IN SPECTRAL FITTING

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

Lee, Hyunsook; Kashyap, Vinay L.; Drake, Jeremy J.

2011-04-20

While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This can be crucial to a proper interpretation of analysis results because instrumental calibration uncertainty is a form of systematic uncertainty. Ignoring it can underestimate error bars and introduce bias into the fitted values of model parameters. Accounting for such uncertainties currently requires extensive case-specific simulations if using existing analysis packages. Here, we present general statistical methods that incorporate calibration uncertainties into spectral analysis of high-energy data. We first present a method based on multiple imputation that can bemore » applied with any fitting method, but is necessarily approximate. We then describe a more exact Bayesian approach that works in conjunction with a Markov chain Monte Carlo based fitting. We explore methods for improving computational efficiency, and in particular detail a method of summarizing calibration uncertainties with a principal component analysis of samples of plausible calibration files. This method is implemented using recently codified Chandra effective area uncertainties for low-resolution spectral analysis and is verified using both simulated and actual Chandra data. Our procedure for incorporating effective area uncertainty is easily generalized to other types of calibration uncertainties.« less

On the use of the covariance matrix to fit correlated data

NASA Astrophysics Data System (ADS)

D'Agostini, G.

1994-07-01

Best fits to data which are affected by systematic uncertainties on the normalization factor have the tendency to produce curves lower than expected if the covariance matrix of the data points is used in the definition of the χ2. This paper shows that the effect is a direct consequence of the hypothesis used to estimate the empirical covariance matrix, namely the linearization on which the usual error propagation relies. The bias can become unacceptable if the normalization error is large, or a large number of data points are fitted.

Bio-physical vs. Economic Uncertainty in the Analysis of Climate Change Impacts on World Agriculture

NASA Astrophysics Data System (ADS)

Hertel, T. W.; Lobell, D. B.

2010-12-01

Accumulating evidence suggests that agricultural production could be greatly affected by climate change, but there remains little quantitative understanding of how these agricultural impacts would affect economic livelihoods in poor countries. The recent paper by Hertel, Burke and Lobell (GEC, 2010) considers three scenarios of agricultural impacts of climate change, corresponding to the fifth, fiftieth, and ninety fifth percentiles of projected yield distributions for the world’s crops in 2030. They evaluate the resulting changes in global commodity prices, national economic welfare, and the incidence of poverty in a set of 15 developing countries. Although the small price changes under the medium scenario are consistent with previous findings, their low productivity scenario reveals the potential for much larger food price changes than reported in recent studies which have hitherto focused on the most likely outcomes. The poverty impacts of price changes under the extremely adverse scenario are quite heterogeneous and very significant in some population strata. They conclude that it is critical to look beyond central case climate shocks and beyond a simple focus on yields and highly aggregated poverty impacts. In this paper, we conduct a more formal, systematic sensitivity analysis (SSA) with respect to uncertainty in the biophysical impacts of climate change on agriculture, by explicitly specifying joint distributions for global yield changes - this time focusing on 2050. This permits us to place confidence intervals on the resulting price impacts and poverty results which reflect the uncertainty inherited from the biophysical side of the analysis. We contrast this with the economic uncertainty inherited from the global general equilibrium model (GTAP), by undertaking SSA with respect to the behavioral parameters in that model. This permits us to assess which type of uncertainty is more important for regional price and poverty outcomes. Finally, we undertake a combined SSA, wherein climate change-induced productivity shocks are permitted to interact with the uncertain economic parameters. This permits us to examine potential interactions between the two sources of uncertainty.

Jet energy measurement and its systematic uncertainty in proton-proton collisions at TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

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.; 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.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; 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.; Arce, A. T. H.; Arfaoui, S.; Arguin, J.-F.; Argyropoulos, S.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Astbury, A.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Backus Mayes, J.; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, S.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; 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.; 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.; 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.; Benhar Noccioli, E.; Benitez Garcia, J. A.; 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.; Bernhard, R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertolucci, F.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Besson, N.; 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.; Bittner, B.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blocki, J.; 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.; Boelaert, N.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. S.; Bolnet, N. M.; Bomben, M.; Bona, M.; Boonekamp, M.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borri, M.; Borroni, S.; Bortfeldt, J.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Bouchami, J.; Boudreau, 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.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Broggi, F.; 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.; Budick, B.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Bunse, M.; Burckhart, H.; Burdin, S.; Burgess, T.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Buttinger, W.; Buzatu, A.; Byszewski, M.; 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.; 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.; Caso, C.; 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.; 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.; Chavda, V.; Chavez Barajas, C. A.; Cheatham, S.; 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, 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.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirilli, M.; Cirkovic, P.; Citron, Z. H.; 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.; Coelli, S.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Colas, 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.; 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.; Courneyea, L.; Cowan, G.; Cox, B. E.; Cranmer, K.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Crispin Ortuzar, M.; Cristinziani, M.; Crosetti, G.; Cuciuc, C.-M.; Cuenca Almenar, C.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cuthbert, C.; 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.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darlea, G. L.; Darmora, S.; Dassoulas, J. A.; Davey, W.; David, C.; Davidek, T.; 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 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 Peso, J.; Del Prete, T.; Delemontex, T.; Deliot, F.; 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.; Demilly, A.; Demirkoz, B.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deviveiros, P. O.; Dewhurst, A.; DeWilde, B.; Dhaliwal, S.; Dhullipudi, R.; 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.; 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.; Dobos, D.; Dobson, E.; Dodd, J.; 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.; Dos Anjos, A.; Dotti, A.; 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.; Duran Yildiz, H.; Düren, M.; Dwuznik, M.; Ebke, J.; Edson, W.; Edwards, C. A.; Edwards, N. C.; Ehrenfeld, W.; 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.; 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.; Espinal Curull, X.; Esposito, B.; Etienne, F.; Etienvre, A. I.; Etzion, E.; Evangelakou, D.; 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.; Fatholahzadeh, B.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; 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, M. J.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Florez Bustos, A. C.; Flowerdew, M. J.; Fonseca Martin, T.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fox, H.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franklin, M.; Franz, S.; Fraternali, M.; Fratina, S.; French, S. T.; Friedrich, C.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fulsom, B. G.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gadatsch, S.; Gadfort, T.; 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.; Garay Walls, F. M.; Garberson, F.; García, C.; García Navarro, J. E.; 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.; Gillman, A. R.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giordano, R.; Giorgi, F. M.; Giovannini, P.; Giraud, P. F.; Giugni, D.; Giuliani, C.; Giunta, M.; Gjelsten, B. K.; Gkialas, I.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; 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.; Gomez Fajardo, L. S.; Gonçalo, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, L.; González de la Hoz, S.; Gonzalez Parra, G.; Gonzalez Silva, M. L.; 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.; 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, F.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Gray, H. M.; Gray, J. A.; 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.; 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.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guttman, N.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haefner, P.; Hageboeck, S.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Hall, D.; Halladjian, G.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamer, M.; Hamilton, A.; Hamilton, S.; Han, L.; Hanagaki, K.; Hanawa, K.; Hance, M.; Hanke, P.; Hansen, J. R.; Hansen, J. B.; Hansen, J. D.; Hansen, P. H.; Hansson, P.; Hara, K.; Hard, A. S.; Harenberg, T.; Harkusha, S.; Harper, D.; Harrington, R. D.; Harris, O. M.; Harrison, P. F.; Hartjes, F.; Harvey, A.; Hasegawa, S.; Hasegawa, Y.; Hassani, S.; Haug, S.; Hauschild, M.; Hauser, R.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hawkins, A. D.; Hayashi, T.; Hayden, D.; Hays, C. P.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heinemann, B.; Heisterkamp, S.; Hejbal, J.; Helary, L.; Heller, C.; Heller, M.; Hellman, S.; Hellmich, D.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Henrichs, A.; Henriques Correia, A. M.; Henrot-Versille, S.; Hensel, C.; Herbert, G. H.; Hernandez, C. M.; Hernández Jiménez, Y.; Herrberg-Schubert, R.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hickling, R.; Higón-Rodriguez, E.; Hill, J. C.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoffman, J.; Hoffmann, D.; Hofmann, J. I.; Hohlfeld, M.; Holmes, T. R.; Hong, T. M.; Hooft van Huysduynen, L.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howard, J.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, X.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huettmann, A.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Hülsing, T. A.; Hurwitz, M.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idarraga, J.; Ideal, E.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikematsu, K.; Ikeno, M.; Iliadis, D.; Ilic, N.; Inamaru, Y.; Ince, T.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Irles Quiles, A.; Isaksson, C.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ivashin, A. V.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jackson, B.; Jackson, J. N.; Jackson, M.; Jackson, P.; Jaekel, M. R.; Jain, V.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jakubek, J.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansen, H.; Janssen, J.; Janus, M.; Jared, R. C.; Jarlskog, G.; Jeanty, L.; Jeng, G.-Y.; Jen-La Plante, I.; Jennens, D.; Jenni, P.; Jentzsch, J.; Jeske, C.; Jézéquel, S.; Jha, M. K.; Ji, H.; Ji, W.; Jia, J.; Jiang, Y.; Jimenez Belenguer, M.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Joergensen, M. D.; Joffe, D.; Johansson, K. E.; Johansson, P.; Johns, K. A.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, T. J.; Jorge, P. M.; Joshi, K. D.; Jovicevic, J.; Ju, X.; Jung, C. A.; Jungst, R. M.; Jussel, P.; Juste Rozas, A.; Kaci, M.; Kaczmarska, A.; Kadlecik, P.; Kado, M.; Kagan, H.; Kagan, M.; Kajomovitz, E.; Kalinin, S.; Kama, S.; Kanaya, N.; Kaneda, M.; Kaneti, S.; Kanno, T.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kapliy, A.; Kar, D.; Karakostas, K.; Karastathis, N.; Karnevskiy, M.; Karpov, S. N.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kashif, L.; Kasieczka, G.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Katre, A.; Katzy, J.; Kaushik, V.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazama, S.; Kazanin, V. F.; Kazarinov, M. Y.; Keeler, R.; Keener, P. T.; Kehoe, R.; Keil, M.; Keller, J. S.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Kessoku, K.; Keung, J.; Khalil-zada, F.; Khandanyan, H.; Khanov, A.; Kharchenko, D.; Khodinov, A.; Khomich, A.; Khoo, T. J.; Khoriauli, G.; Khoroshilov, A.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kim, H.; Kim, S. H.; Kimura, N.; Kind, O.; King, B. T.; King, M.; King, R. S. B.; King, S. B.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kitamura, T.; Kittelmann, T.; Kiuchi, K.; Kladiva, E.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klinger, J. A.; Klinkby, E. B.; Klioutchnikova, T.; Klok, P. F.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koenig, S.; Koevesarki, P.; Koffas, T.; Koffeman, E.; Kogan, L. A.; Kohlmann, S.; Kohout, Z.; Kohriki, T.; Koi, T.; Kolanoski, H.; Koletsou, I.; Koll, J.; Komar, A. A.; Komori, Y.; Kondo, T.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Köpke, L.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Korotkov, V. A.; Kortner, O.; Kortner, S.; Kostyukhin, V. V.; Kotov, S.; Kotov, V. M.; Kotwal, A.; Kourkoumelis, C.; Kouskoura, V.; Koutsman, A.; Kowalewski, R.; Kowalski, T. Z.; Kozanecki, W.; Kozhin, A. S.; Kral, V.; Kramarenko, V. A.; Kramberger, G.; Krasny, M. W.; Krasznahorkay, A.; Kraus, J. K.; Kravchenko, A.; Kreiss, S.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, N.; Krieger, P.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Kruker, T.; Krumnack, N.; Krumshteyn, Z. V.; Kruse, A.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kuday, S.; Kuehn, S.; Kugel, A.; Kuhl, T.; Kukhtin, V.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunkle, J.; Kupco, A.; Kurashige, H.; Kurata, M.; Kurochkin, Y. A.; Kurumida, R.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwee, R.; La Rosa, A.; La Rotonda, L.; Labarga, L.; Lablak, S.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Laier, H.; Laisne, E.; Lambourne, L.; Lampen, C. L.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lang, V. S.; Lange, C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Larner, A.; Lassnig, M.; Laurelli, P.; Lavorini, V.; Lavrijsen, W.; Laycock, P.; Le, B. T.; Le Dortz, O.; Le Guirriec, E.; Le Menedeu, E.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, H.; Lee, J. S. H.; Lee, S. C.; Lee, L.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmacher, M.; Lehmann Miotto, G.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Lendermann, V.; Leney, K. J. C.; Lenz, T.; Lenzen, G.; Lenzi, B.; Leone, R.; Leonhardt, K.; Leontsinis, S.; Leroy, C.; Lessard, J.-R.; Lester, C. G.; Lester, C. M.; Levêque, J.; Levin, D.; Levinson, L. J.; Lewis, A.; Lewis, G. H.; Leyko, A. M.; Leyton, M.; Li, B.; Li, B.; Li, H.; Li, H. L.; Li, S.; Li, X.; Liang, Z.; Liao, H.; Liberti, B.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limbach, C.; Limosani, A.; Limper, M.; Lin, S. C.; Linde, F.; Lindquist, B. E.; Linnemann, J. T.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lissauer, D.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, M.; Liu, Y.; Livan, M.; Livermore, S. S. A.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo Sterzo, F.; Lobodzinska, E.; Loch, P.; Lockman, W. S.; Loddenkoetter, T.; Loebinger, F. K.; Loevschall-Jensen, A. E.; Loginov, A.; Loh, C. W.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Lombardo, V. P.; Long, J. D.; Long, R. E.; Lopes, L.; Lopez Mateos, D.; Lopez Paredes, B.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Loscutoff, P.; Losty, M. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lowe, A. J.; Lu, F.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Ludwig, D.; Ludwig, I.; Luehring, F.; Lukas, W.; Luminari, L.; Lund, E.; Lundberg, J.; Lundberg, O.; Lund-Jensen, B.; Lungwitz, M.; Lynn, D.; Lysak, R.; Lytken, E.; Ma, H.; Ma, L. L.; Maccarrone, G.; Macchiolo, A.; Maček, B.; Machado Miguens, J.; Macina, D.; Mackeprang, R.; Madar, R.; Madaras, R. J.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeno, M.; Maeno, T.; Magnoni, L.; Magradze, E.; Mahboubi, K.; Mahlstedt, J.; Mahmoud, S.; Mahout, G.; Maiani, C.; Maidantchik, C.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Mal, P.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyshev, V. M.; Malyukov, S.; Mamuzic, J.; Mandelli, L.; Mandić, I.; Mandrysch, R.; Maneira, J.; Manfredini, A.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J. A.; Mann, A.; Manning, P. M.; Manousakis-Katsikakis, A.; Mansoulie, B.; Mantifel, R.; Mapelli, L.; March, L.; Marchand, J. F.; Marchese, F.; Marchiori, G.; Marcisovsky, M.; Marino, C. P.; Marques, C. N.; Marroquim, F.; Marshall, Z.; Marti, L. F.; Marti-Garcia, S.; Martin, B.; Martin, B.; Martin, J. P.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martinez, H.; Martinez, M.; Martin-Haugh, S.; Martyniuk, A. C.; Marx, M.; Marzano, F.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massol, N.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Matsunaga, H.; Matsushita, T.; Mättig, P.; Mättig, S.; Mattmann, J.; Mattravers, C.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Mazzaferro, L.; Mazzanti, M.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McCubbin, N. A.; McFarlane, K. W.; Mcfayden, J. A.; Mchedlidze, G.; Mclaughlan, T.; McMahon, S. J.; McPherson, R. A.; Meade, A.; Mechnich, J.; Mechtel, M.; Medinnis, M.; Meehan, S.; Meera-Lebbai, R.; Mehlhase, S.; Mehta, A.; Meier, K.; Meineck, C.; Meirose, B.; Melachrinos, C.; Mellado Garcia, B. R.; Meloni, F.; Mendoza Navas, L.; Mengarelli, A.; Menke, S.; Meoni, E.; Mercurio, K. M.; Mergelmeyer, S.; Meric, N.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Merritt, H.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer, J.; Michal, S.; Middleton, R. P.; Migas, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Milstein, D.; Minaenko, A. A.; Miñano Moya, M.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mirabelli, G.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Mitsui, S.; Miyagawa, P. S.; Mjörnmark, J. U.; Moa, T.; Moeller, V.; Mohapatra, S.; Mohr, W.; Molander, S.; Moles-Valls, R.; Molfetas, A.; Mönig, K.; Monini, C.; Monk, J.; Monnier, E.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Mora Herrera, C.; Moraes, A.; Morange, N.; Morel, J.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, M.; Morii, M.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moser, H. G.; Mosidze, M.; Moss, J.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, K.; Mueller, T.; Mueller, T.; Muenstermann, D.; Munwes, Y.; Murillo Quijada, J. A.; Murray, W. J.; Mussche, I.; Musto, E.; Myagkov, A. G.; Myska, M.; Nackenhorst, O.; Nadal, J.; Nagai, K.; Nagai, R.; Nagai, Y.; Nagano, K.; Nagarkar, A.; Nagasaka, Y.; Nagel, M.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Namasivayam, H.; Nanava, G.; Napier, A.; Narayan, R.; Nash, M.; Nattermann, T.; Naumann, T.; Navarro, G.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negri, G.; Negrini, M.; Nektarijevic, S.; Nelson, A.; Nelson, T. K.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neusiedl, A.; Neves, R. M.; Nevski, P.; Newcomer, F. M.; Newman, P. R.; Nguyen, D. H.; Nguyen Thi Hong, V.; Nickerson, R. B.; Nicolaidou, R.; Nicquevert, B.; Nielsen, J.; Nikiforou, N.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolics, K.; Nikolopoulos, K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Norberg, S.; Nordberg, M.; Novakova, J.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nuncio-Quiroz, A.-E.; Nunes Hanninger, G.; Nunnemann, T.; Nurse, E.; O'Brien, B. J.; O'Grady, F.; O'Neil, D. C.; O'Shea, V.; Oakes, L. B.; Oakham, F. G.; Oberlack, H.; Ocariz, J.; Ochi, A.; Ochoa, M. I.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohshima, T.; Okamura, W.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Olchevski, A. G.; Olivares Pino, S. A.; Oliveira, M.; Oliveira Damazio, D.; Oliver Garcia, E.; Olivito, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onyisi, P. U. E.; Oram, C. J.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Oropeza Barrera, C.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ouellette, E. A.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Ovcharova, A.; Owen, M.; Owen, S.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Padilla Aranda, C.; Pagan Griso, S.; Paganis, E.; Pahl, C.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palestini, S.; Pallin, D.; Palma, A.; Palmer, J. D.; Pan, Y. B.; Panagiotopoulou, E.; Panduro Vazquez, J. G.; Pani, P.; Panikashvili, N.; Panitkin, S.; Pantea, D.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, M. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pashapour, S.; Pasqualucci, E.; Passaggio, S.; Passeri, A.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Patel, N. D.; Pater, J. R.; Patricelli, S.; Pauly, T.; Pearce, J.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Peng, H.; Penning, B.; Penwell, J.; Perepelitsa, D. V.; Perez Cavalcanti, T.; Perez Codina, E.; Pérez García-Estañ, M. T.; Perez Reale, V.; Perini, L.; Pernegger, H.; Perrino, R.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, J.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petrolo, E.; Petrucci, F.; Petteni, M.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Piec, S. M.; Piegaia, R.; Pignotti, D. T.; Pilcher, J. E.; Pilkington, A. D.; Pina, J.; Pinamonti, M.; Pinder, A.; Pinfold, J. L.; Pingel, A.; Pinto, B.; Pizio, C.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Poddar, S.; Podlyski, F.; Poettgen, R.; Poggioli, L.; Pohl, D.; Pohl, M.; Polesello, G.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pomeroy, D.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Portell Bueso, X.; Pospelov, G. E.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Prabhu, R.; Pralavorio, P.; Pranko, A.; Prasad, S.; Pravahan, R.; Prell, S.; Price, D.; Price, J.; Price, L. E.; Prieur, D.; Primavera, M.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopapadaki, E.; Protopopescu, S.; Proudfoot, J.; Prudent, X.; Przybycien, M.; Przysiezniak, H.; Psoroulas, S.; Ptacek, E.; Pueschel, E.; Puldon, D.; Purohit, M.; Puzo, P.; Pylypchenko, Y.; Qian, J.; Quadt, A.; Quarrie, D. R.; Quayle, W. B.; Quilty, D.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Ragusa, F.; Rahal, G.; Rajagopalan, S.; Rammensee, M.; Rammes, M.; Randle-Conde, A. S.; Rangel-Smith, C.; Rao, K.; Rauscher, F.; Rave, T. C.; Ravenscroft, T.; Raymond, M.; Read, A. L.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Reinsch, A.; Reisin, H.; Reisinger, I.; Relich, M.; Rembser, C.; Ren, Z. L.; Renaud, A.; Rescigno, M.; Resconi, S.; Resende, B.; Reznicek, P.; Rezvani, R.; Richter, R.; Ridel, M.; Rieck, P.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; 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, 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.; Sacerdoti, S.; 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.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvachua Ferrando, B. M.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sander, H. G.; Sanders, M. P.; Sandhoff, M.; Sandoval, T.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarkisyan-Grinbaum, E.; Sarrazin, B.; Sartisohn, G.; Sasaki, O.; Sasaki, Y.; Sasao, N.; Satsounkevitch, I.; Sauvage, G.; Sauvan, E.; Sauvan, J. B.; Savard, P.; Savinov, V.; Savu, D. O.; Sawyer, C.; Sawyer, L.; Saxon, D. H.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Schaarschmidt, J.; Schacht, P.; Schaefer, D.; Schaelicke, A.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt, E.; Schmieden, K.; Schmitt, C.; Schmitt, C.; Schmitt, S.; 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, Ph.; Schwartzman, A.; Schwegler, Ph.; Schwemling, Ph.; 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, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; 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. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skottowe, H. P.; Skovpen, K. Yu.; Skubic, P.; Slater, M.; Slavicek, T.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; 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. Yu.; 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.; Su, J.; Subramania, HS.; 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, Yu. 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.; 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. C.-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.; 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.; Vardanyan, G.; 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.; 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.; 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, 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.; 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.; Zengel, K.; 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.; Zimine, N. I.; Zimmermann, C.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Zinonos, Z.; Ziolkowski, M.; Zitoun, R.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zutshi, V.; Zwalinski, L.

2015-01-01

The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton-proton collision data with a centre-of-mass energy of TeV corresponding to an integrated luminosity of . Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti- algorithm with distance parameters or , and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a boson, for and pseudorapidities . The effect of multiple proton-proton interactions is corrected for, and an uncertainty is evaluated using in situ techniques. The smallest JES uncertainty of less than 1 % is found in the central calorimeter region () for jets with . For central jets at lower , the uncertainty is about 3 %. A consistent JES estimate is found using measurements of the calorimeter response of single hadrons in proton-proton collisions and test-beam data, which also provide the estimate for TeV. The calibration of forward jets is derived from dijet balance measurements. The resulting uncertainty reaches its largest value of 6 % for low- jets at . Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5-3 %.

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

NASA Astrophysics Data System (ADS)

Lissner, T. K.; Reusser, D. E.; Schewe, J.; Lakes, T.; Kropp, J. P.

2014-03-01

Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target-measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models as well as greenhouse gas scenarios are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure Adequate Human livelihood conditions for wEll-being And Development (AHEAD). Based on a transdisciplinary sample of influential concepts addressing human well-being, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows identifying and differentiating uncertainty of climate and impact model projections. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that in many countries today, livelihood conditions are compromised by water scarcity. However, more often, AHEAD fulfilment is limited through other elements. Moreover, the analysis shows that for 44 out of 111 countries, the water-specific uncertainty ranges are outside relevant thresholds for AHEAD, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy-decisions.

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: theoretical systematics and Baryon Acoustic Oscillations in the galaxy correlation function

NASA Astrophysics Data System (ADS)

Vargas-Magaña, Mariana; Ho, Shirley; Cuesta, Antonio J.; O'Connell, Ross; Ross, Ashley J.; Eisenstein, Daniel J.; Percival, Will J.; Grieb, Jan Niklas; Sánchez, Ariel G.; Tinker, Jeremy L.; Tojeiro, Rita; Beutler, Florian; Chuang, Chia-Hsun; Kitaura, Francisco-Shu; Prada, Francisco; Rodríguez-Torres, Sergio A.; Rossi, Graziano; Seo, Hee-Jong; Brownstein, Joel R.; Olmstead, Matthew; Thomas, Daniel

2018-06-01

We investigate the potential sources of theoretical systematics in the anisotropic Baryon Acoustic Oscillation (BAO) distance scale measurements from the clustering of galaxies in configuration space using the final Data Release (DR12) of the Baryon Oscillation Spectroscopic Survey (BOSS). We perform a detailed study of the impact on BAO measurements from choices in the methodology such as fiducial cosmology, clustering estimators, random catalogues, fitting templates, and covariance matrices. The theoretical systematic uncertainties in BAO parameters are found to be 0.002 in the isotropic dilation α and 0.003 in the quadrupolar dilation ɛ. The leading source of systematic uncertainty is related to the reconstruction techniques. Theoretical uncertainties are sub-dominant compared with the statistical uncertainties for BOSS survey, accounting 0.2σstat for α and 0.25σstat for ɛ (σα, stat ˜ 0.010 and σɛ, stat ˜ 0.012, respectively). We also present BAO-only distance scale constraints from the anisotropic analysis of the correlation function. Our constraints on the angular diameter distance DA(z) and the Hubble parameter H(z), including both statistical and theoretical systematic uncertainties, are 1.5 per cent and 2.8 per cent at zeff = 0.38, 1.4 per cent and 2.4 per cent at zeff = 0.51, and 1.7 per cent and 2.6 per cent at zeff = 0.61. This paper is part of a set that analyses the final galaxy clustering data set from BOSS. The measurements and likelihoods presented here are cross-checked with other BAO analysis in Alam et al. The systematic error budget concerning the methodology on post-reconstruction BAO analysis presented here is used in Alam et al. to produce the final cosmological constraints from BOSS.

Quantification and propagation of disciplinary uncertainty via Bayesian statistics

NASA Astrophysics Data System (ADS)

Mantis, George Constantine

2002-08-01

Several needs exist in the military, commercial, and civil sectors for new hypersonic systems. These needs remain unfulfilled, due in part to the uncertainty encountered in designing these systems. This uncertainty takes a number of forms, including disciplinary uncertainty, that which is inherent in the analytical tools utilized during the design process. Yet, few efforts to date empower the designer with the means to account for this uncertainty within the disciplinary analyses. In the current state-of-the-art in design, the effects of this unquantifiable uncertainty significantly increase the risks associated with new design efforts. Typically, the risk proves too great to allow a given design to proceed beyond the conceptual stage. To that end, the research encompasses the formulation and validation of a new design method, a systematic process for probabilistically assessing the impact of disciplinary uncertainty. The method implements Bayesian Statistics theory to quantify this source of uncertainty, and propagate its effects to the vehicle system level. Comparison of analytical and physical data for existing systems, modeled a priori in the given analysis tools, leads to quantification of uncertainty in those tools' calculation of discipline-level metrics. Then, after exploration of the new vehicle's design space, the quantified uncertainty is propagated probabilistically through the design space. This ultimately results in the assessment of the impact of disciplinary uncertainty on the confidence in the design solution: the final shape and variability of the probability functions defining the vehicle's system-level metrics. Although motivated by the hypersonic regime, the proposed treatment of uncertainty applies to any class of aerospace vehicle, just as the problem itself affects the design process of any vehicle. A number of computer programs comprise the environment constructed for the implementation of this work. Application to a single-stage-to-orbit (SSTO) reusable launch vehicle concept, developed by the NASA Langley Research Center under the Space Launch Initiative, provides the validation case for this work, with the focus placed on economics, aerothermodynamics, propulsion, and structures metrics. (Abstract shortened by UMI.)

Estimates of global and regional prevalence of neural tube defects for 2015: a systematic analysis.

PubMed

Blencowe, Hannah; Kancherla, Vijaya; Moorthie, Sowmiya; Darlison, Matthew W; Modell, Bernadette

2018-02-01

Neural tube defects (NTDs) are associated with substantial mortality, morbidity, disability, and psychological and economic costs. Many are preventable with folic acid, and access to appropriate services for those affected can improve survival and quality of life. We used a compartmental model to estimate global and regional birth prevalence of NTDs (live births, stillbirths, and elective terminations of pregnancy) and subsequent under-5 mortality. Data were identified through web-based reviews of birth defect registry databases and systematic literature reviews. Meta-analyses were undertaken where appropriate. For 2015, our model estimated 260,100 (uncertainty interval (UI): 213,800-322,000) NTD-affected birth outcomes worldwide (prevalence 18.6 (15.3-23.0)/10,000 live births). Approximately 50% of cases were elective terminations of pregnancy for fetal anomalies (UI: 59,300 (47,900-74,500)) or stillbirths (57,800 (UI: 35,000-88,600)). Of NTD-affected live births, 117,900 (∼75%) (UI: 105,500-186,600) resulted in under-5 deaths. Our systematic review showed a paucity of high-quality data in the regions of the world with the highest burden. Despite knowledge about prevention, NTDs remain highly prevalent worldwide. Lack of surveillance and incomplete ascertainment of affected pregnancies make NTDs invisible to policy makers. Improved surveillance of all adverse outcomes is needed to improve the robustness of total NTD prevalence estimation, evaluate effectiveness of prevention through folic acid fortification, and improve outcomes through care and rehabilitation. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of New York Academy of Sciences.

Addressing health literacy in patient decision aids

PubMed Central

2013-01-01

Background Effective use of a patient decision aid (PtDA) can be affected by the user’s health literacy and the PtDA’s characteristics. Systematic reviews of the relevant literature can guide PtDA developers to attend to the health literacy needs of patients. The reviews reported here aimed to assess: 1. a) the effects of health literacy / numeracy on selected decision-making outcomes, and b) the effects of interventions designed to mitigate the influence of lower health literacy on decision-making outcomes, and 2. the extent to which existing PtDAs a) account for health literacy, and b) are tested in lower health literacy populations. Methods We reviewed literature for evidence relevant to these two aims. When high-quality systematic reviews existed, we summarized their evidence. When reviews were unavailable, we conducted our own systematic reviews. Results Aim 1: In an existing systematic review of PtDA trials, lower health literacy was associated with lower patient health knowledge (14 of 16 eligible studies). Fourteen studies reported practical design strategies to improve knowledge for lower health literacy patients. In our own systematic review, no studies reported on values clarity per se, but in 2 lower health literacy was related to higher decisional uncertainty and regret. Lower health literacy was associated with less desire for involvement in 3 studies, less question-asking in 2, and less patient-centered communication in 4 studies; its effects on other measures of patient involvement were mixed. Only one study assessed the effects of a health literacy intervention on outcomes; it showed that using video to improve the salience of health states reduced decisional uncertainty. Aim 2: In our review of 97 trials, only 3 PtDAs overtly addressed the needs of lower health literacy users. In 90% of trials, user health literacy and readability of the PtDA were not reported. However, increases in knowledge and informed choice were reported in those studies in which health literacy needs were addressed. Conclusion Lower health literacy affects key decision-making outcomes, but few existing PtDAs have addressed the needs of lower health literacy users. The specific effects of PtDAs designed to mitigate the influence of low health literacy are unknown. More attention to the needs of patients with lower health literacy is indicated, to ensure that PtDAs are appropriate for lower as well as higher health literacy patients. PMID:24624970

Asteroseismic modelling of solar-type stars: internal systematics from input physics and surface correction methods

NASA Astrophysics Data System (ADS)

Nsamba, B.; Campante, T. L.; Monteiro, M. J. P. F. G.; Cunha, M. S.; Rendle, B. M.; Reese, D. R.; Verma, K.

2018-07-01

Asteroseismic forward modelling techniques are being used to determine fundamental properties (e.g. mass, radius, and age) of solar-type stars. The need to take into account all possible sources of error is of paramount importance towards a robust determination of stellar properties. We present a study of 34 solar-type stars for which high signal-to-noise asteroseismic data are available from multiyear Kepler photometry. We explore the internal systematics on the stellar properties, that is associated with the uncertainty in the input physics used to construct the stellar models. In particular, we explore the systematics arising from (i) the inclusion of the diffusion of helium and heavy elements; (ii) the uncertainty in solar metallicity mixture; and (iii) different surface correction methods used in optimization/fitting procedures. The systematics arising from comparing results of models with and without diffusion are found to be 0.5 per cent, 0.8 per cent, 2.1 per cent, and 16 per cent in mean density, radius, mass, and age, respectively. The internal systematics in age are significantly larger than the statistical uncertainties. We find the internal systematics resulting from the uncertainty in solar metallicity mixture to be 0.7 per cent in mean density, 0.5 per cent in radius, 1.4 per cent in mass, and 6.7 per cent in age. The surface correction method by Sonoi et al. and Ball & Gizon's two-term correction produce the lowest internal systematics among the different correction methods, namely, ˜1 per cent, ˜1 per cent, ˜2 per cent, and ˜8 per cent in mean density, radius, mass, and age, respectively. Stellar masses obtained using the surface correction methods by Kjeldsen et al. and Ball & Gizon's one-term correction are systematically higher than those obtained using frequency ratios.

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

NASA Technical Reports Server (NTRS)

Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

2013-01-01

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

Uncertainty Quantification for Ice Sheet Science and Sea Level Projections

NASA Astrophysics Data System (ADS)

Boening, C.; Schlegel, N.; Limonadi, D.; Schodlok, M.; Seroussi, H. L.; Larour, E. Y.; Watkins, M. M.

2017-12-01

In order to better quantify uncertainties in global mean sea level rise projections and in particular upper bounds, we aim at systematically evaluating the contributions from ice sheets and potential for extreme sea level rise due to sudden ice mass loss. Here, we take advantage of established uncertainty quantification tools embedded within the Ice Sheet System Model (ISSM) as well as sensitivities to ice/ocean interactions using melt rates and melt potential derived from MITgcm/ECCO2. With the use of these tools, we conduct Monte-Carlo style sampling experiments on forward simulations of the Antarctic ice sheet, by varying internal parameters and boundary conditions of the system over both extreme and credible worst-case ranges. Uncertainty bounds for climate forcing are informed by CMIP5 ensemble precipitation and ice melt estimates for year 2100, and uncertainty bounds for ocean melt rates are derived from a suite of regional sensitivity experiments using MITgcm. Resulting statistics allow us to assess how regional uncertainty in various parameters affect model estimates of century-scale sea level rise projections. The results inform efforts to a) isolate the processes and inputs that are most responsible for determining ice sheet contribution to sea level; b) redefine uncertainty brackets for century-scale projections; and c) provide a prioritized list of measurements, along with quantitative information on spatial and temporal resolution, required for reducing uncertainty in future sea level rise projections. Results indicate that ice sheet mass loss is dependent on the spatial resolution of key boundary conditions - such as bedrock topography and melt rates at the ice-ocean interface. This work is performed at and supported by the California Institute of Technology's Jet Propulsion Laboratory. Supercomputing time is also supported through a contract with the National Aeronautics and Space Administration's Cryosphere program.

Decision making under uncertainty and information processing in positive and negative mood states.

PubMed

Mohanty, Sachi Nandan; Suar, Damodar

2014-08-01

This study examines whether mood states (a) influence decision making under uncertainty and (b) affect information processing. 200 students at the Indian Institute of Technology Kharagpur participated in this study. Positive mood was induced by showing comedy movie clips to 100 participants and negative mood was induced by showing tragedy movie clips to another 100 participants. The participants were administered a questionnaire containing hypothetical situations of financial gains and losses, and a health risk problem. The participants selected a choice for each situation, and stated the reasons for their choice. Results suggested that the participants preferred cautious choices in the domain of gain and in health risk problems and risky choices in the domain of loss. Analysis of the reasons for the participants' choices suggested more fluency, originality, and flexibility of information in a negative mood compared to a positive mood. A negative (positive) mood state facilitated systematic (heuristic) information processing.

Novel test of modified Newtonian dynamics with gas rich galaxies.

PubMed

McGaugh, Stacy S

2011-03-25

The current cosmological paradigm, the cold dark matter model with a cosmological constant, requires that the mass-energy of the Universe be dominated by invisible components: dark matter and dark energy. An alternative to these dark components is that the law of gravity be modified on the relevant scales. A test of these ideas is provided by the baryonic Tully-Fisher relation (BTFR), an empirical relation between the observed mass of a galaxy and its rotation velocity. Here, I report a test using gas rich galaxies for which both axes of the BTFR can be measured independently of the theories being tested and without the systematic uncertainty in stellar mass that affects the same test with star dominated spirals. The data fall precisely where predicted a priori by the modified Newtonian dynamics. The scatter in the BTFR is attributable entirely to observational uncertainty, consistent with a single effective force law.

The older worker with osteoarthritis of the knee.

PubMed

Palmer, Keith T

2012-06-01

Changing demographics mean that many patients with large joint arthritis will work beyond traditional retirement age. This review considers the impact of knee osteoarthritis (OA) on work participation and the relation between work and total knee replacement (TKR). Two systematic searches in Embase and Medline, supplemented by three systematic reviews. Probably, although evidence is limited, knee OA considerably impairs participation in work (labour force participation, work attendance and work productivity). AREAS OF UNCERTAINTY/RESEARCH NEED: Little is known about effective interventions (treatments, work changes and policies) to improve vocational participation in patients with knee OA; or how type of work affects long-term clinical outcomes (e.g. pain, function and the need for revision surgery) in patients with TKRs. The need for such research is pressing and opportune, as increasing numbers of patients with knee OA or TKR expect to work on.

Combined influence of CT random noise and HU-RSP calibration curve nonlinearities on proton range systematic errors

NASA Astrophysics Data System (ADS)

Brousmiche, S.; Souris, K.; Orban de Xivry, J.; Lee, J. A.; Macq, B.; Seco, J.

2017-11-01

Proton range random and systematic uncertainties are the major factors undermining the advantages of proton therapy, namely, a sharp dose falloff and a better dose conformality for lower doses in normal tissues. The influence of CT artifacts such as beam hardening or scatter can easily be understood and estimated due to their large-scale effects on the CT image, like cupping and streaks. In comparison, the effects of weakly-correlated stochastic noise are more insidious and less attention is drawn on them partly due to the common belief that they only contribute to proton range uncertainties and not to systematic errors thanks to some averaging effects. A new source of systematic errors on the range and relative stopping powers (RSP) has been highlighted and proved not to be negligible compared to the 3.5% uncertainty reference value used for safety margin design. Hence, we demonstrate that the angular points in the HU-to-RSP calibration curve are an intrinsic source of proton range systematic error for typical levels of zero-mean stochastic CT noise. Systematic errors on RSP of up to 1% have been computed for these levels. We also show that the range uncertainty does not generally vary linearly with the noise standard deviation. We define a noise-dependent effective calibration curve that better describes, for a given material, the RSP value that is actually used. The statistics of the RSP and the range continuous slowing down approximation (CSDA) have been analytically derived for the general case of a calibration curve obtained by the stoichiometric calibration procedure. These models have been validated against actual CSDA simulations for homogeneous and heterogeneous synthetical objects as well as on actual patient CTs for prostate and head-and-neck treatment planning situations.

Development of a novel method for surgical implant design optimization through noninvasive assessment of local bone properties.

PubMed

Schiuma, D; Brianza, S; Tami, A E

2011-03-01

A method was developed to improve the design of locking implants by finding the optimal paths for the anchoring elements, based on a high resolution pQCT assessment of local bone mineral density (BMD) distribution and bone micro-architecture (BMA). The method consists of three steps: (1) partial fixation of the implant to the bone and creation of a reference system, (2) implant removal and pQCT scan of the bone, and (3) determination of BMD and BMA of all implant-anchoring locations along the actual and alternative directions. Using a PHILOS plate, the method uncertainty was tested on an artificial humerus bone model. A cadaveric humerus was used to quantify how the uncertainty of the method affects the assessment of bone parameters. BMD and BMA were determined along four possible alternative screw paths as possible criteria for implant optimization. The method is biased by a 0.87 ± 0.12 mm systematic uncertainty and by a 0.44 ± 0.09 mm random uncertainty in locating the virtual screw position. This study shows that this method can be used to find alternative directions for the anchoring elements, which may possess better bone properties. This modification will thus produce an optimized implant design. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

Challenges in the determination of the interstellar flow longitude from the pickup ion cutoff

NASA Astrophysics Data System (ADS)

Taut, A.; Berger, L.; Möbius, E.; Drews, C.; Heidrich-Meisner, V.; Keilbach, D.; Lee, M. A.; Wimmer-Schweingruber, R. F.

2018-03-01

Context. The interstellar flow longitude corresponds to the Sun's direction of movement relative to the local interstellar medium. Thus, it constitutes a fundamental parameter for our understanding of the heliosphere and, in particular, its interaction with its surroundings, which is currently investigated by the Interstellar Boundary EXplorer (IBEX). One possibility to derive this parameter is based on pickup ions (PUIs) that are former neutral ions that have been ionized in the inner heliosphere. The neutrals enter the heliosphere as an interstellar wind from the direction of the Sun's movement against the partially ionized interstellar medium. PUIs carry information about the spatial variation of their neutral parent population (density and flow vector field) in their velocity distribution function. From the symmetry of the longitudinal flow velocity distribution, the interstellar flow longitude can be derived. Aim. The aim of this paper is to identify and eliminate systematic errors that are connected to this approach of measuring the interstellar flow longitude; we want to minimize any systematic influences on the result of this analysis and give a reasonable estimate for the uncertainty. Methods: We use He+ data measured by the PLAsma and SupraThermal Ion Composition (PLASTIC) sensor on the Solar TErrestrial RElations Observatory Ahead (STEREO A) spacecraft. We analyze a recent approach, identify sources of systematic errors, and propose solutions to eliminate them. Furthermore, a method is introduced to estimate the error associated with this approach. Additionally, we investigate how the selection of interplanetary magnetic field angles, which is closely connected to the pickup ion velocity distribution function, affects the result for the interstellar flow longitude. Results: We find that the revised analysis used to address part of the expected systematic effects obtains significantly different results than presented in the previous study. In particular, the derived uncertainties are considerably larger. Furthermore, an unexpected systematic trend of the resulting interstellar flow longitude with the selection of interplanetary magnetic field orientation is uncovered.

An Assessment of the Systematic Uncertainty in Present and Future Tests of the Lense-Thirring Effect with Satellite Laser Ranging

NASA Astrophysics Data System (ADS)

Iorio, Lorenzo

2009-12-01

We deal with the attempts to measure the Lense-Thirring effect with the Satellite Laser Ranging (SLR) technique applied to the existing LAGEOS and LAGEOS II terrestrial satellites and to the recently approved LARES spacecraft. According to general relativity, a central spinning body of mass M and angular momentum S like the Earth generates a gravitomagnetic field which induces small secular precessions of the orbit of a test particle geodesically moving around it. Extracting this signature from the data is a demanding task because of many classical orbital perturbations having the same pattern as the gravitomagnetic one, like those due to the centrifugal oblateness of the Earth which represents a major source of systematic bias. The first issue addressed here is: are the so far published evaluations of the systematic uncertainty induced by the bad knowledge of the even zonal harmonic coefficients J ℓ of the multipolar expansion of the Earth’s geopotential reliable and realistic? Our answer is negative. Indeed, if the differences Δ J ℓ among the even zonals estimated in different Earth’s gravity field global solutions from the dedicated GRACE mission are assumed for the uncertainties δ J ℓ instead of using their covariance sigmas σ_{J_{ell}} , it turns out that the systematic uncertainty δ μ in the Lense-Thirring test with the nodes Ω of LAGEOS and LAGEOS II may be up to 3 to 4 times larger than in the evaluations so far published (5-10%) based on the use of the sigmas of one model at a time separately. The second issue consists of the possibility of using a different approach in extracting the relativistic signature of interest from the LAGEOS-type data. The third issue is the possibility of reaching a realistic total accuracy of 1% with LAGEOS, LAGEOS II and LARES, which should be launched in November 2009 with a VEGA rocket. While LAGEOS and LAGEOS II fly at altitudes of about 6000 km, LARES will be likely placed at an altitude of 1450 km. Thus, it will be sensitive to much more even zonals than LAGEOS and LAGEOS II. Their corrupting impact has been evaluated with the standard Kaula’s approach up to degree ℓ=60 by using Δ J ℓ and σ_{J_{ell }} ; it turns out that it may be as large as some tens percent. The different orbit of LARES may also have some consequences on the non-gravitational orbital perturbations affecting it which might further degrade the obtainable accuracy in the Lense-Thirring test.

Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization

DOE PAGES

Gatti, M.

2018-02-22

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1 (DES Y1) sample with redMaGiC galaxies (luminous red galaxies with secure photometric red- shifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We also apply the method to three photo-z codes run in our simulated data: Bayesian Photometric Redshift (BPZ), Directional Neighborhoodmore » Fitting (DNF), and Random Forest-based photo-z (RF). We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering vs photo-z's. The systematic uncertainty in the mean redshift bias of the source galaxy sample is z ≲ 0.02, though the precise value depends on the redshift bin under consideration. Here, we discuss possible ways to mitigate the impact of our dominant systematics in future analyses.« less

Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization

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

Gatti, M.

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1 (DES Y1) sample with redMaGiC galaxies (luminous red galaxies with secure photometric red- shifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We also apply the method to three photo-z codes run in our simulated data: Bayesian Photometric Redshift (BPZ), Directional Neighborhoodmore » Fitting (DNF), and Random Forest-based photo-z (RF). We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering vs photo-z's. The systematic uncertainty in the mean redshift bias of the source galaxy sample is z ≲ 0.02, though the precise value depends on the redshift bin under consideration. Here, we discuss possible ways to mitigate the impact of our dominant systematics in future analyses.« less

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

Bao, C.; Hanany, S.; Baccigalupi, C.

We extend a general maximum likelihood foreground estimation for cosmic microwave background (CMB) polarization data to include estimation of instrumental systematic effects. We focus on two particular effects: frequency band measurement uncertainty and instrumentally induced frequency dependent polarization rotation. We assess the bias induced on the estimation of the B-mode polarization signal by these two systematic effects in the presence of instrumental noise and uncertainties in the polarization and spectral index of Galactic dust. Degeneracies between uncertainties in the band and polarization angle calibration measurements and in the dust spectral index and polarization increase the uncertainty in the extracted CMBmore » B-mode power, and may give rise to a biased estimate. We provide a quantitative assessment of the potential bias and increased uncertainty in an example experimental configuration. For example, we find that with 10% polarized dust, a tensor to scalar ratio of r = 0.05, and the instrumental configuration of the E and B experiment balloon payload, the estimated CMB B-mode power spectrum is recovered without bias when the frequency band measurement has 5% uncertainty or less, and the polarization angle calibration has an uncertainty of up to 4°.« less

Improving Photometric Calibration of Meteor Video Camera Systems

NASA Technical Reports Server (NTRS)

Ehlert, Steven; Kingery, Aaron; Suggs, Robert

2016-01-01

We present the results of new calibration tests performed by the NASA Meteoroid Environment Oce (MEO) designed to help quantify and minimize systematic uncertainties in meteor photometry from video camera observations. These systematic uncertainties can be categorized by two main sources: an imperfect understanding of the linearity correction for the MEO's Watec 902H2 Ultimate video cameras and uncertainties in meteor magnitudes arising from transformations between the Watec camera's Sony EX-View HAD bandpass and the bandpasses used to determine reference star magnitudes. To address the rst point, we have measured the linearity response of the MEO's standard meteor video cameras using two independent laboratory tests on eight cameras. Our empirically determined linearity correction is critical for performing accurate photometry at low camera intensity levels. With regards to the second point, we have calculated synthetic magnitudes in the EX bandpass for reference stars. These synthetic magnitudes enable direct calculations of the meteor's photometric ux within the camera band-pass without requiring any assumptions of its spectral energy distribution. Systematic uncertainties in the synthetic magnitudes of individual reference stars are estimated at 0:20 mag, and are limited by the available spectral information in the reference catalogs. These two improvements allow for zero-points accurate to 0:05 ?? 0:10 mag in both ltered and un ltered camera observations with no evidence for lingering systematics.

First Year Wilkinson Microwave Anisotropy Probe(WMAP) Observations: Data Processing Methods and Systematic Errors Limits

NASA Technical Reports Server (NTRS)

Hinshaw, G.; Barnes, C.; Bennett, C. L.; Greason, M. R.; Halpern, M.; Hill, R. S.; Jarosik, N.; Kogut, A.; Limon, M.; Meyer, S. S.

2003-01-01

We describe the calibration and data processing methods used to generate full-sky maps of the cosmic microwave background (CMB) from the first year of Wilkinson Microwave Anisotropy Probe (WMAP) observations. Detailed limits on residual systematic errors are assigned based largely on analyses of the flight data supplemented, where necessary, with results from ground tests. The data are calibrated in flight using the dipole modulation of the CMB due to the observatory's motion around the Sun. This constitutes a full-beam calibration source. An iterative algorithm simultaneously fits the time-ordered data to obtain calibration parameters and pixelized sky map temperatures. The noise properties are determined by analyzing the time-ordered data with this sky signal estimate subtracted. Based on this, we apply a pre-whitening filter to the time-ordered data to remove a low level of l/f noise. We infer and correct for a small (approx. 1 %) transmission imbalance between the two sky inputs to each differential radiometer, and we subtract a small sidelobe correction from the 23 GHz (K band) map prior to further analysis. No other systematic error corrections are applied to the data. Calibration and baseline artifacts, including the response to environmental perturbations, are negligible. Systematic uncertainties are comparable to statistical uncertainties in the characterization of the beam response. Both are accounted for in the covariance matrix of the window function and are propagated to uncertainties in the final power spectrum. We characterize the combined upper limits to residual systematic uncertainties through the pixel covariance matrix.

SU-E-T-292: Sensitivity of Fractionated Lung IMPT Treatments to Setup Uncertainties and Motion Effects

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

Dowdell, S; Grassberger, C; Paganetti, H

2014-06-01

Purpose: Evaluate the sensitivity of intensity-modulated proton therapy (IMPT) lung treatments to systematic and random setup uncertainties combined with motion effects. Methods: Treatment plans with single-field homogeneity restricted to ±20% (IMPT-20%) were compared to plans with no restriction (IMPT-full). 4D Monte Carlo simulations were performed for 10 lung patients using the patient CT geometry with either ±5mm systematic or random setup uncertainties applied over a 35 × 2.5Gy(RBE) fractionated treatment course. Intra-fraction, inter-field and inter-fraction motions were investigated. 50 fractionated treatments with systematic or random setup uncertainties applied to each fraction were generated for both IMPT delivery methods and threemore » energy-dependent spot sizes (big spots - BS σ=18-9mm, intermediate spots - IS σ=11-5mm, small spots - SS σ=4-2mm). These results were compared to a Monte Carlo recalculation of the original treatment plan, with results presented as the difference in EUD (ΔEUD), V{sub 95} (ΔV{sub 95}) and target homogeneity (ΔD{sub 1}–D{sub 99}) between the 4D simulations and the Monte Carlo calculation on the planning CT. Results: The standard deviations in the ΔEUD were 1.95±0.47(BS), 1.85±0.66(IS) and 1.31±0.35(SS) times higher in IMPT-full compared to IMPT-20% when ±5mm systematic setup uncertainties were applied. The ΔV{sub 95} variations were also 1.53±0.26(BS), 1.60±0.50(IS) and 1.38±0.38(SS) times higher for IMPT-full. For random setup uncertainties, the standard deviations of the ΔEUD from 50 simulated fractionated treatments were 1.94±0.90(BS), 2.13±1.08(IS) and 1.45±0.57(SS) times higher in IMPTfull compared to IMPT-20%. For all spot sizes considered, the ΔD{sub 1}-D{sub 99} coincided within the uncertainty limits for the two IMPT delivery methods, with the mean value always higher for IMPT-full. Statistical analysis showed significant differences between the IMPT-full and IMPT-20% dose distributions for the majority of scenarios studied. Conclusion: Lung IMPT-full treatments are more sensitive to both systematic and random setup uncertainties compared to IMPT-20%. This work was supported by the NIH R01 CA111590.« less

Assessment of the risk of introduction of H5N1 HPAI virus from affected countries to the U.K.

PubMed

Sabirovic, M; Hall, S; Wilesmith, J; Grimley, P; Coulson, N; Landeg, F

2007-03-01

The Department for Environment, Food and Rural Affairs (Defra) has monitored epidemiologic developments following outbreaks of H5N1 in Asia since the beginning of 2004 and publishes risk assessments as the situation evolves. The U.K. applies safeguard measures that reflect EU rules to enable imports to continue when they present negligible risk. Defra risk assessments (RA) identify possible pathways by which the H5N1 virus may be introduced to the U.K. These assessments provide a basis for identifying appropriate surveillance activities to ensure early detection, should the virus be introduced, and disease control measures to be taken, should the virus be detected in the U.K. Nevertheless, these assessments have highlighted that many fundamental uncertainties still remain. These uncertainties center on the geographic and species distribution of infection outside Asia and the means of dissemination of the virus. However, the evolving developments demonstrated that regulatory decisions had to be made despite these uncertainties. Improvements in our current RA abilities would greatly benefit from systematic studies to provide more information on the species susceptibility, dynamics of infection, pathogenesis, and ecology of the virus along with possible pathways by which the H5N1 virus may be disseminated. Such an approach would assist in reducing uncertainties and ensuring that regulatory risk management measures are regularly reviewed by taking into account the most recent scientific evidence. The likelihood of the persistence of H5N1 outside Asia in the coming years and the effects of control programs in Asia and other affected regions to reduce the prevalence of infection are also important factors.

Uncertainty quantification of effective nuclear interactions

DOE PAGES

Pérez, R. Navarro; Amaro, J. E.; Arriola, E. Ruiz

2016-03-02

We give a brief review on the development of phenomenological NN interactions and the corresponding quanti cation of statistical uncertainties. We look into the uncertainty of effective interactions broadly used in mean eld calculations through the Skyrme parameters and effective eld theory counter-terms by estimating both statistical and systematic uncertainties stemming from the NN interaction. We also comment on the role played by different tting strategies on the light of recent developments.

Uncertainty quantification of effective nuclear interactions

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

Pérez, R. Navarro; Amaro, J. E.; Arriola, E. Ruiz

We give a brief review on the development of phenomenological NN interactions and the corresponding quanti cation of statistical uncertainties. We look into the uncertainty of effective interactions broadly used in mean eld calculations through the Skyrme parameters and effective eld theory counter-terms by estimating both statistical and systematic uncertainties stemming from the NN interaction. We also comment on the role played by different tting strategies on the light of recent developments.

A general model-based design of experiments approach to achieve practical identifiability of pharmacokinetic and pharmacodynamic models.

PubMed

Galvanin, Federico; Ballan, Carlo C; Barolo, Massimiliano; Bezzo, Fabrizio

2013-08-01

The use of pharmacokinetic (PK) and pharmacodynamic (PD) models is a common and widespread practice in the preliminary stages of drug development. However, PK-PD models may be affected by structural identifiability issues intrinsically related to their mathematical formulation. A preliminary structural identifiability analysis is usually carried out to check if the set of model parameters can be uniquely determined from experimental observations under the ideal assumptions of noise-free data and no model uncertainty. However, even for structurally identifiable models, real-life experimental conditions and model uncertainty may strongly affect the practical possibility to estimate the model parameters in a statistically sound way. A systematic procedure coupling the numerical assessment of structural identifiability with advanced model-based design of experiments formulations is presented in this paper. The objective is to propose a general approach to design experiments in an optimal way, detecting a proper set of experimental settings that ensure the practical identifiability of PK-PD models. Two simulated case studies based on in vitro bacterial growth and killing models are presented to demonstrate the applicability and generality of the methodology to tackle model identifiability issues effectively, through the design of feasible and highly informative experiments.

Erratum: Evidence of b -jet quenching in PbPb collisions at s N N = 2.76 TeV [Phys. Rev. Lett. 113 , 132301 (2014)

DOE PAGES

Chatrchyan, S.

2015-07-10

In our Letter, there was a component of the statistical uncertainty from the simulated PbPb Monte Carlo samples. This uncertainty was not propagated to all of the results. Figures 3 and 4 have been updated to reflect this source of uncertainty. In this case, the statistical uncertainties remain smaller than the systematic uncertainties in all cases such that the conclusions of the Letter are unaltered.

Systematic errors in long baseline oscillation experiments

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

Harris, Deborah A.; /Fermilab

This article gives a brief overview of long baseline neutrino experiments and their goals, and then describes the different kinds of systematic errors that are encountered in these experiments. Particular attention is paid to the uncertainties that come about because of imperfect knowledge of neutrino cross sections and more generally how neutrinos interact in nuclei. Near detectors are planned for most of these experiments, and the extent to which certain uncertainties can be reduced by the presence of near detectors is also discussed.

Leaf area index uncertainty estimates for model-data fusion applications

Treesearch

Andrew D. Richardson; D. Bryan Dail; D.Y. Hollinger

2011-01-01

Estimates of data uncertainties are required to integrate different observational data streams as model constraints using model-data fusion. We describe an approach with which random and systematic uncertainties in optical measurements of leaf area index [LAI] can be quantified. We use data from a measurement campaign at the spruce-dominated Howland Forest AmeriFlux...

Modeling for waste management associated with environmental-impact abatement under uncertainty.

PubMed

Li, P; Li, Y P; Huang, G H; Zhang, J L

2015-04-01

Municipal solid waste (MSW) treatment can generate significant amounts of pollutants, and thus pose a risk on human health. Besides, in MSW management, various uncertainties exist in the related costs, impact factors, and objectives, which can affect the optimization processes and the decision schemes generated. In this study, a life cycle assessment-based interval-parameter programming (LCA-IPP) method is developed for MSW management associated with environmental-impact abatement under uncertainty. The LCA-IPP can effectively examine the environmental consequences based on a number of environmental impact categories (i.e., greenhouse gas equivalent, acid gas emissions, and respiratory inorganics), through analyzing each life cycle stage and/or major contributing process related to various MSW management activities. It can also tackle uncertainties existed in the related costs, impact factors, and objectives and expressed as interval numbers. Then, the LCA-IPP method is applied to MSW management for the City of Beijing, the capital of China, where energy consumptions and six environmental parameters [i.e., CO2, CO, CH4, NOX, SO2, inhalable particle (PM10)] are used as systematic tool to quantify environmental releases in entire life cycle stage of waste collection, transportation, treatment, and disposal of. Results associated with system cost, environmental impact, and the related policy implication are generated and analyzed. Results can help identify desired alternatives for managing MSW flows, which has advantages in providing compromised schemes under an integrated consideration of economic efficiency and environmental impact under uncertainty.

Uncertainty in geocenter estimates in the context of ITRF2014

NASA Astrophysics Data System (ADS)

Riddell, Anna R.; King, Matt A.; Watson, Christopher S.; Sun, Yu; Riva, Riccardo E. M.; Rietbroek, Roelof

2017-05-01

Uncertainty in the geocenter position and its subsequent motion affects positioning estimates on the surface of the Earth and downstream products such as site velocities, particularly the vertical component. The current version of the International Terrestrial Reference Frame, ITRF2014, derives its origin as the long-term averaged center of mass as sensed by satellite laser ranging (SLR), and by definition, it adopts only linear motion of the origin with uncertainty determined using a white noise process. We compare weekly SLR translations relative to the ITRF2014 origin, with network translations estimated from station displacements from surface mass transport models. We find that the proportion of variance explained in SLR translations by the model-derived translations is on average less than 10%. Time-correlated noise and nonlinear rates, particularly evident in the Y and Z components of the SLR translations with respect to the ITRF2014 origin, are not fully replicated by the model-derived translations. This suggests that translation-related uncertainties are underestimated when a white noise model is adopted and that substantial systematic errors remain in the data defining the ITRF origin. When using a white noise model, we find uncertainties in the rate of SLR X, Y, and Z translations of ±0.03, ±0.03, and ±0.06, respectively, increasing to ±0.13, ±0.17, and ±0.33 (mm/yr, 1 sigma) when a power law and white noise model is adopted.

Interstellar Flow and Temperature Determination with IBEX: Robustness and Sensitivity to Systematic Effects

NASA Astrophysics Data System (ADS)

Möbius, E.; Bzowski, M.; Frisch, P. C.; Fuselier, S. A.; Heirtzler, D.; Kubiak, M. A.; Kucharek, H.; Lee, M. A.; Leonard, T.; McComas, D. J.; Schwadron, N. A.; Sokół, J. M.; Swaczyna, P.; Wurz, P.

2015-10-01

The Interstellar Boundary Explorer (IBEX) samples the interstellar neutral (ISN) gas flow of several species every year from December through late March when the Earth moves into the incoming flow. The first quantitative analyses of these data resulted in a narrow tube in four-dimensional interstellar parameter space, which couples speed, flow latitude, flow longitude, and temperature, and center values with approximately 3° larger longitude and 3 km s-1 lower speed, but with temperatures similar to those obtained from observations by the Ulysses spacecraft. IBEX has now recorded six years of ISN flow observations, providing a large database over increasing solar activity and using varying viewing strategies. In this paper, we evaluate systematic effects that are important for the ISN flow vector and temperature determination. We find that all models in use return ISN parameters well within the observational uncertainties and that the derived ISN flow direction is resilient against uncertainties in the ionization rate. We establish observationally an effective IBEX-Lo pointing uncertainty of ±0.°18 in spin angle and confirm an uncertainty of ±0.°1 in longitude. We also show that the IBEX viewing strategy with different spin-axis orientations minimizes the impact of several systematic uncertainties, and thus improves the robustness of the measurement. The Helium Warm Breeze has likely contributed substantially to the somewhat different center values of the ISN flow vector. By separating the flow vector and temperature determination, we can mitigate these effects on the analysis, which returns an ISN flow vector very close to the Ulysses results, but with a substantially higher temperature. Due to coupling with the ISN flow speed along the ISN parameter tube, we provide the temperature {T}{VISN∞ }=8710+440/-680 K for {V}{ISN∞ }=26 {km} {{{s}}}-1 for comparison, where most of the uncertainty is systematic and likely due to the presence of the Warm Breeze.

Characterizing spatial uncertainty when integrating social data in conservation planning.

PubMed

Lechner, A M; Raymond, C M; Adams, V M; Polyakov, M; Gordon, A; Rhodes, J R; Mills, M; Stein, A; Ives, C D; Lefroy, E C

2014-12-01

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches. © 2014 Society for Conservation Biology.

THE EVOLUTION OF THE STELLAR MASS FUNCTION OF GALAXIES FROM z = 4.0 AND THE FIRST COMPREHENSIVE ANALYSIS OF ITS UNCERTAINTIES: EVIDENCE FOR MASS-DEPENDENT EVOLUTION

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

Marchesini, Danilo; Van Dokkum, Pieter G.; Foerster Schreiber, Natascha M.

2009-08-20

We present the evolution of the stellar mass function (SMF) of galaxies from z = 4.0 to z = 1.3 measured from a sample constructed from the deep near-infrared Multi-wavelength Survey by Yale-Chile, the Faint Infrared Extragalactic Survey, and the Great Observatories Origins Deep Survey-Chandra Deep Field South surveys, all having very high-quality optical to mid-infrared data. This sample, unique in that it combines data from surveys with a large range of depths and areas in a self-consistent way, allowed us to (1) minimize the uncertainty due to cosmic variance and empirically quantify its contribution to the total error budget;more » (2) simultaneously probe the high-mass end and the low-mass end (down to {approx}0.05 times the characteristic stellar mass) of the SMF with good statistics; and (3) empirically derive the redshift-dependent completeness limits in stellar mass. We provide, for the first time, a comprehensive analysis of random and systematic uncertainties affecting the derived SMFs, including the effect of metallicity, extinction law, stellar population synthesis model, and initial mass function. We find that the mass density evolves by a factor of {approx}17{sup +7}{sub -10} since z = 4.0, mostly driven by a change in the normalization {phi}*. If only random errors are taken into account, we find evidence for mass-dependent evolution, with the low-mass end evolving more rapidly than the high-mass end. However, we show that this result is no longer robust when systematic uncertainties due to the SED-modeling assumptions are taken into account. Another significant uncertainty is the contribution to the overall stellar mass density of galaxies below our mass limit; future studies with WFC3 will provide better constraints on the SMF at masses below 10{sup 10} M{sub sun} at z>2. Taking our results at face value, we find that they are in conflict with semianalytic models of galaxy formation. The models predict SMFs that are in general too steep, with too many low-mass galaxies and too few high-mass galaxies. The discrepancy at the high-mass end is susceptible to uncertainties in the models and the data, but the discrepancy at the low-mass end may be more difficult to explain.« less

Control of systematic uncertainties in the storage ring search for an electric dipole moment by measuring the electric quadrupole moment

NASA Astrophysics Data System (ADS)

Magiera, Andrzej

2017-09-01

Measurements of electric dipole moment (EDM) for light hadrons with use of a storage ring have been proposed. The expected effect is very small, therefore various subtle effects need to be considered. In particular, interaction of particle's magnetic dipole moment and electric quadrupole moment with electromagnetic field gradients can produce an effect of a similar order of magnitude as that expected for EDM. This paper describes a very promising method employing an rf Wien filter, allowing to disentangle that contribution from the genuine EDM effect. It is shown that both these effects could be separated by the proper setting of the rf Wien filter frequency and phase. In the EDM measurement the magnitude of systematic uncertainties plays a key role and they should be under strict control. It is shown that particles' interaction with field gradients offers also the possibility to estimate global systematic uncertainties with the precision necessary for an EDM measurement with the planned accuracy.

Using PS1 and Type Ia Supernovae To Make Most Precise Measurement of Dark Energy To Date

NASA Astrophysics Data System (ADS)

Scolnic, Daniel; Pan-STARRS

2018-01-01

I will review recent results that present optical light curves, redshifts, and classifications for 361 spectroscopically confirmed Type Ia supernovae (SNeIa) discovered by the Pan-STARRS1 (PS1) Medium Deep Survey. I will go over improvements to the PS1 SN photometry, astrometry and calibration that reduce the systematic uncertainties in the PS1 SN Ia distances. We combined distances of PS1 SNe with distance estimates of SNIa from SDSS, SNLS, various low-z and HST samples to form the largest combined sample of SN Ia consisting of a total of ~1050 SN Ia ranging from 0.01 < z < 2.3, which we call the ‘Pantheon Sample’. Photometric calibration uncertainties have long dominated the systematic error budget of every major analysis of cosmological parameters with SNIa. Using the PS1 relative calibration, we have reduced these calibration systematics to the point where they are similar in magnitude to the other major sources of known systematic uncertainties: the nature of the intrinsic scatter of SNIa and modeling of selection effects. I will present measurements of dark energy which are now the most precise measurements of dark energy to date.

Integrating Solar PV in Utility System Operations: Analytical Framework and Arizona Case Study

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

Wu, Jing; Botterud, Audun; Mills, Andrew

2015-06-01

A systematic framework is proposed to estimate the impact on operating costs due to uncertainty and variability in renewable resources. The framework quantifies the integration costs associated with subhourly variability and uncertainty as well as day-ahead forecasting errors in solar PV (photovoltaics) power. A case study illustrates how changes in system operations may affect these costs for a utility in the southwestern United States (Arizona Public Service Company). We conduct an extensive sensitivity analysis under different assumptions about balancing reserves, system flexibility, fuel prices, and forecasting errors. We find that high solar PV penetrations may lead to operational challenges, particularlymore » during low-load and high solar periods. Increased system flexibility is essential for minimizing integration costs and maintaining reliability. In a set of sensitivity cases where such flexibility is provided, in part, by flexible operations of nuclear power plants, the estimated integration costs vary between $1.0 and $4.4/MWh-PV for a PV penetration level of 17%. The integration costs are primarily due to higher needs for hour-ahead balancing reserves to address the increased sub-hourly variability and uncertainty in the PV resource. (C) 2015 Elsevier Ltd. All rights reserved.« less

Incorporating climate change into systematic conservation planning

USGS Publications Warehouse

Groves, Craig R.; Game, Edward T.; Anderson, Mark G.; Cross, Molly; Enquist, Carolyn; Ferdana, Zach; Girvetz, Evan; Gondor, Anne; Hall, Kimberly R.; Higgins, Jonathan; Marshall, Rob; Popper, Ken; Schill, Steve; Shafer, Sarah L.

2012-01-01

The principles of systematic conservation planning are now widely used by governments and non-government organizations alike to develop biodiversity conservation plans for countries, states, regions, and ecoregions. Many of the species and ecosystems these plans were designed to conserve are now being affected by climate change, and there is a critical need to incorporate new and complementary approaches into these plans that will aid species and ecosystems in adjusting to potential climate change impacts. We propose five approaches to climate change adaptation that can be integrated into existing or new biodiversity conservation plans: (1) conserving the geophysical stage, (2) protecting climatic refugia, (3) enhancing regional connectivity, (4) sustaining ecosystem process and function, and (5) capitalizing on opportunities emerging in response to climate change. We discuss both key assumptions behind each approach and the trade-offs involved in using the approach for conservation planning. We also summarize additional data beyond those typically used in systematic conservation plans required to implement these approaches. A major strength of these approaches is that they are largely robust to the uncertainty in how climate impacts may manifest in any given region.

Improving Photometric Calibration of Meteor Video Camera Systems.

PubMed

Ehlert, Steven; Kingery, Aaron; Suggs, Robert

2017-09-01

We present the results of new calibration tests performed by the NASA Meteoroid Environment Office (MEO) designed to help quantify and minimize systematic uncertainties in meteor photometry from video camera observations. These systematic uncertainties can be categorized by two main sources: an imperfect understanding of the linearity correction for the MEO's Watec 902H2 Ultimate video cameras and uncertainties in meteor magnitudes arising from transformations between the Watec camera's Sony EX-View HAD bandpass and the bandpasses used to determine reference star magnitudes. To address the first point, we have measured the linearity response of the MEO's standard meteor video cameras using two independent laboratory tests on eight cameras. Our empirically determined linearity correction is critical for performing accurate photometry at low camera intensity levels. With regards to the second point, we have calculated synthetic magnitudes in the EX bandpass for reference stars. These synthetic magnitudes enable direct calculations of the meteor's photometric flux within the camera band pass without requiring any assumptions of its spectral energy distribution. Systematic uncertainties in the synthetic magnitudes of individual reference stars are estimated at ∼ 0.20 mag, and are limited by the available spectral information in the reference catalogs. These two improvements allow for zero-points accurate to ∼ 0.05 - 0.10 mag in both filtered and unfiltered camera observations with no evidence for lingering systematics. These improvements are essential to accurately measuring photometric masses of individual meteors and source mass indexes.

Improving Photometric Calibration of Meteor Video Camera Systems

NASA Technical Reports Server (NTRS)

Ehlert, Steven; Kingery, Aaron; Suggs, Robert

2017-01-01

We present the results of new calibration tests performed by the NASA Meteoroid Environment Office (MEO) designed to help quantify and minimize systematic uncertainties in meteor photometry from video camera observations. These systematic uncertainties can be categorized by two main sources: an imperfect understanding of the linearity correction for the MEO's Watec 902H2 Ultimate video cameras and uncertainties in meteor magnitudes arising from transformations between the Watec camera's Sony EX-View HAD bandpass and the bandpasses used to determine reference star magnitudes. To address the first point, we have measured the linearity response of the MEO's standard meteor video cameras using two independent laboratory tests on eight cameras. Our empirically determined linearity correction is critical for performing accurate photometry at low camera intensity levels. With regards to the second point, we have calculated synthetic magnitudes in the EX bandpass for reference stars. These synthetic magnitudes enable direct calculations of the meteor's photometric flux within the camera bandpass without requiring any assumptions of its spectral energy distribution. Systematic uncertainties in the synthetic magnitudes of individual reference stars are estimated at approx. 0.20 mag, and are limited by the available spectral information in the reference catalogs. These two improvements allow for zero-points accurate to 0.05 - 0.10 mag in both filtered and unfiltered camera observations with no evidence for lingering systematics. These improvements are essential to accurately measuring photometric masses of individual meteors and source mass indexes.

Measuring the Properties of Dark Energy with Photometrically Classified Pan-STARRS Supernovae. I. Systematic Uncertainty from Core-collapse Supernova Contamination

NASA Astrophysics Data System (ADS)

Jones, D. O.; Scolnic, D. M.; Riess, A. G.; Kessler, R.; Rest, A.; Kirshner, R. P.; Berger, E.; Ortega, C. A.; Foley, R. J.; Chornock, R.; Challis, P. J.; Burgett, W. S.; Chambers, K. C.; Draper, P. W.; Flewelling, H.; Huber, M. E.; Kaiser, N.; Kudritzki, R.-P.; Metcalfe, N.; Wainscoat, R. J.; Waters, C.

2017-07-01

The Pan-STARRS (PS1) Medium Deep Survey discovered over 5000 likely supernovae (SNe) but obtained spectral classifications for just 10% of its SN candidates. We measured spectroscopic host galaxy redshifts for 3147 of these likely SNe and estimate that ˜1000 are Type Ia SNe (SNe Ia) with light-curve quality sufficient for a cosmological analysis. We use these data with simulations to determine the impact of core-collapse SN (CC SN) contamination on measurements of the dark energy equation of state parameter, w. Using the method of Bayesian Estimation Applied to Multiple Species (BEAMS), distances to SNe Ia and the contaminating CC SN distribution are simultaneously determined. We test light-curve-based SN classification priors for BEAMS as well as a new classification method that relies upon host galaxy spectra and the association of SN type with host type. By testing several SN classification methods and CC SN parameterizations on large SN simulations, we estimate that CC SN contamination gives a systematic error on w ({σ }w{CC}) of 0.014, 29% of the statistical uncertainty. Our best method gives {σ }w{CC}=0.004, just 8% of the statistical uncertainty, but could be affected by incomplete knowledge of the CC SN distribution. This method determines the SALT2 color and shape coefficients, α and β, with ˜3% bias. However, we find that some variants require α and β to be fixed to known values for BEAMS to yield accurate measurements of w. Finally, the inferred abundance of bright CC SNe in our sample is greater than expected based on measured CC SN rates and luminosity functions.

Neutrino mass hierarchy and precision physics with medium-baseline reactors: Impact of energy-scale and flux-shape uncertainties

NASA Astrophysics Data System (ADS)

Capozzi, F.; Lisi, E.; Marrone, A.

2015-11-01

Nuclear reactors provide intense sources of electron antineutrinos, characterized by few-MeV energy E and unoscillated spectral shape Φ (E ). High-statistics observations of reactor neutrino oscillations over medium-baseline distances L ˜O (50 ) km would provide unprecedented opportunities to probe both the long-wavelength mass-mixing parameters (δ m2 and θ12) and the short-wavelength ones (Δ mee 2 and θ13), together with the subtle interference effects associated with the neutrino mass hierarchy (either normal or inverted). In a given experimental setting—here taken as in the JUNO project for definiteness—the achievable hierarchy sensitivity and parameter accuracy depend not only on the accumulated statistics but also on systematic uncertainties, which include (but are not limited to) the mass-mixing priors and the normalizations of signals and backgrounds. We examine, in addition, the effect of introducing smooth deformations of the detector energy scale, E →E'(E ), and of the reactor flux shape, Φ (E )→Φ'(E ), within reasonable error bands inspired by state-of-the-art estimates. It turns out that energy-scale and flux-shape systematics can noticeably affect the performance of a JUNO-like experiment, both on the hierarchy discrimination and on precision oscillation physics. It is shown that a significant reduction of the assumed energy-scale and flux-shape uncertainties (by, say, a factor of 2) would be highly beneficial to the physics program of medium-baseline reactor projects. Our results also shed some light on the role of the inverse-beta decay threshold, of geoneutrino backgrounds, and of matter effects in the analysis of future reactor oscillation data.

Sunyaev-Zel'dovich Effect and X-ray Scaling Relations from Weak-Lensing Mass Calibration of 32 SPT Selected Galaxy Clusters

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

Dietrich, J.P.; et al.

Uncertainty in the mass-observable scaling relations is currently the limiting factor for galaxy cluster based cosmology. Weak gravitational lensing can provide a direct mass calibration and reduce the mass uncertainty. We present new ground-based weak lensing observations of 19 South Pole Telescope (SPT) selected clusters and combine them with previously reported space-based observations of 13 galaxy clusters to constrain the cluster mass scaling relations with the Sunyaev-Zel'dovich effect (SZE), the cluster gas massmore » $$M_\\mathrm{gas}$$, and $$Y_\\mathrm{X}$$, the product of $$M_\\mathrm{gas}$$ and X-ray temperature. We extend a previously used framework for the analysis of scaling relations and cosmological constraints obtained from SPT-selected clusters to make use of weak lensing information. We introduce a new approach to estimate the effective average redshift distribution of background galaxies and quantify a number of systematic errors affecting the weak lensing modelling. These errors include a calibration of the bias incurred by fitting a Navarro-Frenk-White profile to the reduced shear using $N$-body simulations. We blind the analysis to avoid confirmation bias. We are able to limit the systematic uncertainties to 6.4% in cluster mass (68% confidence). Our constraints on the mass-X-ray observable scaling relations parameters are consistent with those obtained by earlier studies, and our constraints for the mass-SZE scaling relation are consistent with the the simulation-based prior used in the most recent SPT-SZ cosmology analysis. We can now replace the external mass calibration priors used in previous SPT-SZ cosmology studies with a direct, internal calibration obtained on the same clusters.« less

Climateprediction.com: Public Involvement, Multi-Million Member Ensembles and Systematic Uncertainty Analysis

NASA Astrophysics Data System (ADS)

Stainforth, D. A.; Allen, M.; Kettleborough, J.; Collins, M.; Heaps, A.; Stott, P.; Wehner, M.

2001-12-01

The climateprediction.com project is preparing to carry out the first systematic uncertainty analysis of climate forecasts using large ensembles of GCM climate simulations. This will be done by involving schools, businesses and members of the public, and utilizing the novel technology of distributed computing. Each participant will be asked to run one member of the ensemble on their PC. The model used will initially be the UK Met Office's Unified Model (UM). It will be run under Windows and software will be provided to enable those involved to view their model output as it develops. The project will use this method to carry out large perturbed physics GCM ensembles and thereby analyse the uncertainty in the forecasts from such models. Each participant/ensemble member will therefore have a version of the UM in which certain aspects of the model physics have been perturbed from their default values. Of course the non-linear nature of the system means that it will be necessary to look not just at perturbations to individual parameters in specific schemes, such as the cloud parameterization, but also to the many combinations of perturbations. This rapidly leads to the need for very large, perhaps multi-million member ensembles, which could only be undertaken using the distributed computing methodology. The status of the project will be presented and the Windows client will be demonstrated. In addition, initial results will be presented from beta test runs using a demo release for Linux PCs and Alpha workstations. Although small by comparison to the whole project, these pilot results constitute a 20-50 member perturbed physics climate ensemble with results indicating how climate sensitivity can be substantially affected by individual parameter values in the cloud scheme.

Carnegie Hubble Program: A Mid-Infrared Calibration of the Hubble Constant

NASA Technical Reports Server (NTRS)

Freedman, Wendy L.; Madore, Barry F.; Scowcroft, Victoria; Burns, Chris; Monson, Andy; Persson, S. Eric; Seibert, Mark; Rigby, Jane

2012-01-01

Using a mid-infrared calibration of the Cepheid distance scale based on recent observations at 3.6 micrometers with the Spitzer Space Telescope, we have obtained a new, high-accuracy calibration of the Hubble constant. We have established the mid-IR zero point of the Leavitt law (the Cepheid period-luminosity relation) using time-averaged 3.6 micrometers data for 10 high-metallicity, MilkyWay Cepheids having independently measured trigonometric parallaxes. We have adopted the slope of the PL relation using time-averaged 3.6micrometers data for 80 long-period Large Magellanic Cloud (LMC) Cepheids falling in the period range 0.8 < log(P) < 1.8.We find a new reddening-corrected distance to the LMC of 18.477 +/- 0.033 (systematic) mag. We re-examine the systematic uncertainties in H(sub 0), also taking into account new data over the past decade. In combination with the new Spitzer calibration, the systematic uncertainty in H(sub 0) over that obtained by the Hubble Space Telescope Key Project has decreased by over a factor of three. Applying the Spitzer calibration to the Key Project sample, we find a value of H(sub 0) = 74.3 with a systematic uncertainty of +/-2.1 (systematic) kilometers per second Mpc(sup -1), corresponding to a 2.8% systematic uncertainty in the Hubble constant. This result, in combination with WMAP7measurements of the cosmic microwave background anisotropies and assuming a flat universe, yields a value of the equation of state for dark energy, w(sub 0) = -1.09 +/- 0.10. Alternatively, relaxing the constraints on flatness and the numbers of relativistic species, and combining our results with those of WMAP7, Type Ia supernovae and baryon acoustic oscillations yield w(sub 0) = -1.08 +/- 0.10 and a value of N(sub eff) = 4.13 +/- 0.67, mildly consistent with the existence of a fourth neutrino species.

Uncertainty characterization of HOAPS 3.3 latent heat-flux-related parameters

NASA Astrophysics Data System (ADS)

Liman, Julian; Schröder, Marc; Fennig, Karsten; Andersson, Axel; Hollmann, Rainer

2018-03-01

Latent heat flux (LHF) is one of the main contributors to the global energy budget. As the density of in situ LHF measurements over the global oceans is generally poor, the potential of remotely sensed LHF for meteorological applications is enormous. However, to date none of the available satellite products have included estimates of systematic, random, and sampling uncertainties, all of which are essential for assessing their quality. Here, the challenge is taken on by matching LHF-related pixel-level data of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS) climatology (version 3.3) to in situ measurements originating from a high-quality data archive of buoys and selected ships. Assuming the ground reference to be bias-free, this allows for deriving instantaneous systematic uncertainties as a function of four atmospheric predictor variables. The approach is regionally independent and therefore overcomes the issue of sparse in situ data densities over large oceanic areas. Likewise, random uncertainties are derived, which include not only a retrieval component but also contributions from in situ measurement noise and the collocation procedure. A recently published random uncertainty decomposition approach is applied to isolate the random retrieval uncertainty of all LHF-related HOAPS parameters. It makes use of two combinations of independent data triplets of both satellite and in situ data, which are analysed in terms of their pairwise variances of differences. Instantaneous uncertainties are finally aggregated, allowing for uncertainty characterizations on monthly to multi-annual timescales. Results show that systematic LHF uncertainties range between 15 and 50 W m-2 with a global mean of 25 W m-2. Local maxima are mainly found over the subtropical ocean basins as well as along the western boundary currents. Investigations indicate that contributions from qa (U) to the overall LHF uncertainty are on the order of 60 % (25 %). From an instantaneous point of view, random retrieval uncertainties are specifically large over the subtropics with a global average of 37 W m-2. In a climatological sense, their magnitudes become negligible, as do respective sampling uncertainties. Regional and seasonal analyses suggest that largest total LHF uncertainties are seen over the Gulf Stream and the Indian monsoon region during boreal winter. In light of the uncertainty measures, the observed continuous global mean LHF increase up to 2009 needs to be treated with caution. The demonstrated approach can easily be transferred to other satellite retrievals, which increases the significance of the present work.

Addressing Systematic Errors in Correlation Tracking on HMI Magnetograms

NASA Astrophysics Data System (ADS)

Mahajan, Sushant S.; Hathaway, David H.; Munoz-Jaramillo, Andres; Martens, Petrus C.

2017-08-01

Correlation tracking in solar magnetograms is an effective method to measure the differential rotation and meridional flow on the solar surface. However, since the tracking accuracy required to successfully measure meridional flow is very high, small systematic errors have a noticeable impact on measured meridional flow profiles. Additionally, the uncertainties of this kind of measurements have been historically underestimated, leading to controversy regarding flow profiles at high latitudes extracted from measurements which are unreliable near the solar limb.Here we present a set of systematic errors we have identified (and potential solutions), including bias caused by physical pixel sizes, center-to-limb systematics, and discrepancies between measurements performed using different time intervals. We have developed numerical techniques to get rid of these systematic errors and in the process improve the accuracy of the measurements by an order of magnitude.We also present a detailed analysis of uncertainties in these measurements using synthetic magnetograms and the quantification of an upper limit below which meridional flow measurements cannot be trusted as a function of latitude.

Revisiting Supernova 1987A constraints on dark photons

DOE PAGES

Chang, Jae Hyeok; Essig, Rouven; McDermott, Samuel D.

2017-01-25

We revisit constraints on dark photons with masses below ~ 100 MeV from the observations of Supernova 1987A. If dark photons are produced in sufficient quantity, they reduce the amount of energy emitted in the form of neutrinos, in conflict with observations. For the first time, we include the effects of finite temperature and density on the kinetic-mixing parameter,ϵ, in this environment. This causes the constraints on ϵ to weaken with the dark-photon mass below ~ 15 MeV. For large-enough values of ϵ, it is well known that dark photons can be reabsorbed within the supernova. Since the rates ofmore » reabsorption processes decrease as the dark-photon energy increases, we point out that dark photons with energies above the Wien peak can escape without scattering, contributing more to energy loss than is possible assuming a blackbody spectrum. Furthermore, we estimate the systematic uncertainties on the cooling bounds by deriving constraints assuming one analytic and four different simulated temperature and density profiles of the proto-neutron star. Finally, we estimate also the systematic uncertainty on the bound by varying the distance across which dark photons must propagate from their point of production to be able to affect the star. Finally, this work clarifies the bounds from SN1987A on the dark-photon parameter space.« less

Ubiquitous Log Odds: A Common Representation of Probability and Frequency Distortion in Perception, Action, and Cognition

PubMed Central

Zhang, Hang; Maloney, Laurence T.

2012-01-01

In decision from experience, the source of probability information affects how probability is distorted in the decision task. Understanding how and why probability is distorted is a key issue in understanding the peculiar character of experience-based decision. We consider how probability information is used not just in decision-making but also in a wide variety of cognitive, perceptual, and motor tasks. Very similar patterns of distortion of probability/frequency information have been found in visual frequency estimation, frequency estimation based on memory, signal detection theory, and in the use of probability information in decision-making under risk and uncertainty. We show that distortion of probability in all cases is well captured as linear transformations of the log odds of frequency and/or probability, a model with a slope parameter, and an intercept parameter. We then consider how task and experience influence these two parameters and the resulting distortion of probability. We review how the probability distortions change in systematic ways with task and report three experiments on frequency distortion where the distortions change systematically in the same task. We found that the slope of frequency distortions decreases with the sample size, which is echoed by findings in decision from experience. We review previous models of the representation of uncertainty and find that none can account for the empirical findings. PMID:22294978

Nonintrusive Temperature and Velocity Measurements in a Hypersonic Nozzle Flow

NASA Technical Reports Server (NTRS)

OByrne, S.; Danehy, P. M.; Houwing, A. F. P.

2002-01-01

Distributions of nitric oxide vibrational temperature, rotational temperature and velocity have been measured in the hypersonic freestream at the exit of a conical nozzle, using planar laser-induced fluorescence. Particular attention has been devoted to reducing the major sources of systematic error that can affect fluorescence tempera- ture measurements, including beam attenuation, transition saturation effects, laser mode fluctuations and transition choice. Visualization experiments have been performed to improve the uniformity of the nozzle flow. Comparisons of measured quantities with a simple one-dimensional computation are made, showing good agreement between measurements and theory given the uncertainty of the nozzle reservoir conditions and the vibrational relaxation rate.

[Ethical Dilemmas in Practice of Medicine Child].

PubMed

Ruiz López, Justo; Navarro Zaragoza, Javier; Carrillo Navarro, Francisco; Luna Maldonado, Aurelio

2017-01-01

After reviewing the existing bibliography in the last 20 years, we concluded that there is a lack of information regarding the ethical conflicts that affect to pediatrics in their daily practice. It produces certain degree of uncertainty in these professionals at the time of solving these problems. We made a systematic search in the main data bases, finding more than 150 articles related, of which 80 were considered outstanding. After studying them, we have found 40 ethical dilemmas, related to some principle of solution and that we described in this article. Through them we can find such important dilemmas as those related to physical disability, palliative care or consent from children.

OPTHYLIC: An Optimised Tool for Hybrid Limits Computation

NASA Astrophysics Data System (ADS)

Busato, Emmanuel; Calvet, David; Theveneaux-Pelzer, Timothée

2018-05-01

A software tool, computing observed and expected upper limits on Poissonian process rates using a hybrid frequentist-Bayesian CLs method, is presented. This tool can be used for simple counting experiments where only signal, background and observed yields are provided or for multi-bin experiments where binned distributions of discriminating variables are provided. It allows the combination of several channels and takes into account statistical and systematic uncertainties, as well as correlations of systematic uncertainties between channels. It has been validated against other software tools and analytical calculations, for several realistic cases.

Measurement of the $B^-$ lifetime using a simulation free approach for trigger bias correction

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

Aaltonen, T.; /Helsinki Inst. of Phys.; Adelman, J.

2010-04-01

The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. Inmore » this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B{sup -} using the mode B{sup -} {yields} D{sup 0}{pi}{sup -}. The B{sup -} lifetime is measured as {tau}{sub B{sup -}} = 1.663 {+-} 0.023 {+-} 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.« less

Spreadsheet for designing valid least-squares calibrations: A tutorial.

PubMed

Bettencourt da Silva, Ricardo J N

2016-02-01

Instrumental methods of analysis are used to define the price of goods, the compliance of products with a regulation, or the outcome of fundamental or applied research. These methods can only play their role properly if reported information is objective and their quality is fit for the intended use. If measurement results are reported with an adequately small measurement uncertainty both of these goals are achieved. The evaluation of the measurement uncertainty can be performed by the bottom-up approach, that involves a detailed description of the measurement process, or using a pragmatic top-down approach that quantify major uncertainty components from global performance data. The bottom-up approach is not so frequently used due to the need to master the quantification of individual components responsible for random and systematic effects that affect measurement results. This work presents a tutorial that can be easily used by non-experts in the accurate evaluation of the measurement uncertainty of instrumental methods of analysis calibrated using least-squares regressions. The tutorial includes the definition of the calibration interval, the assessments of instrumental response homoscedasticity, the definition of calibrators preparation procedure required for least-squares regression model application, the assessment of instrumental response linearity and the evaluation of measurement uncertainty. The developed measurement model is only applicable in calibration ranges where signal precision is constant. A MS-Excel file is made available to allow the easy application of the tutorial. This tool can be useful for cases where top-down approaches cannot produce results with adequately low measurement uncertainty. An example of the application of this tool to the determination of nitrate in water by ion chromatography is presented. Copyright © 2015 Elsevier B.V. All rights reserved.

Jet energy measurement and its systematic uncertainty in proton-proton collisions at [Formula: see text] 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; 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; Andrei, V; Anduaga, X S; Angelidakis, S; 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; Arce, A T H; Arfaoui, S; Arguin, J-F; Argyropoulos, S; Arik, E; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arslan, O; Artamonov, A; Artoni, G; Asai, S; Asbah, N; Ask, S; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Astbury, A; Atkinson, M; Atlay, N B; Auerbach, B; Auge, E; Augsten, K; Aurousseau, M; Avolio, G; Azuelos, G; Azuma, Y; Baak, M A; Bacci, C; Bach, A M; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Backus Mayes, J; Badescu, E; Bagiacchi, P; Bagnaia, P; Bai, Y; Bailey, D C; Bain, T; Baines, J T; Baker, O K; Baker, S; Balek, P; Balli, F; Banas, E; Banerjee, Sw; Banfi, D; Bangert, A; Bansal, V; Bansil, H S; Barak, L; Baranov, S P; Barber, T; Barberio, E L; Barberis, D; Barbero, M; 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; 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; 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; Benhar Noccioli, E; Benitez Garcia, J A; 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; Bernhard, R; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertolucci, F; Besana, M I; Besjes, G J; Bessidskaia, O; Besson, N; 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; Bittner, B; Black, C W; Black, J E; Black, K M; Blackburn, D; Blair, R E; Blanchard, J-B; Blazek, T; Bloch, I; Blocker, C; Blocki, J; 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; Boelaert, N; Bogaerts, J A; Bogdanchikov, A G; Bogouch, A; Bohm, C; Bohm, J; Boisvert, V; Bold, T; Boldea, V; Boldyrev, A S; Bolnet, N M; Bomben, M; Bona, M; Boonekamp, M; Bordoni, S; Borer, C; Borisov, A; Borissov, G; Borri, M; Borroni, S; Bortfeldt, J; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Boterenbrood, H; Bouchami, J; Boudreau, 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; Brenner, R; Bressler, S; Bristow, T M; Britton, D; Brochu, F M; Brock, I; Brock, R; Broggi, F; 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; Budick, B; Buehrer, F; Bugge, L; Bugge, M K; Bulekov, O; Bundock, A C; Bunse, M; Burckhart, H; Burdin, S; Burgess, T; Burghgrave, B; Burke, S; Burmeister, I; Busato, E; Büscher, V; Bussey, P; Buszello, C P; Butler, B; Butler, J M; Butt, A I; Buttar, C M; Butterworth, J M; Buttinger, W; Buzatu, A; Byszewski, M; 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; 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; Caso, C; 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; 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; Chavda, V; Chavez Barajas, C A; Cheatham, S; 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, 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; Ciapetti, G; Ciftci, A K; Ciftci, R; Cinca, D; Cindro, V; Ciocio, A; Cirilli, M; Cirkovic, P; Citron, Z H; 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; Coelli, S; Coffey, L; Cogan, J G; Coggeshall, J; Colas, 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; 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; Courneyea, L; Cowan, G; Cox, B E; Cranmer, K; Cree, G; Crépé-Renaudin, S; Crescioli, F; Crispin Ortuzar, M; Cristinziani, M; Crosetti, G; Cuciuc, C-M; Cuenca Almenar, C; Cuhadar Donszelmann, T; Cummings, J; Curatolo, M; Cuthbert, C; 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; Dallaire, F; Dallapiccola, C; Dam, M; Daniells, A C; Dano Hoffmann, M; Dao, V; Darbo, G; Darlea, G L; Darmora, S; Dassoulas, J A; Davey, W; David, C; Davidek, T; 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 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 Peso, J; Del Prete, T; Delemontex, T; Deliot, F; 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; Demilly, A; Demirkoz, B; Denisov, S P; Derendarz, D; Derkaoui, J E; Derue, F; Dervan, P; Desch, K; Deviveiros, P O; Dewhurst, A; DeWilde, B; Dhaliwal, S; Dhullipudi, R; 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; 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; Dobos, D; Dobson, E; Dodd, J; 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; Dos Anjos, A; Dotti, A; 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; Duran Yildiz, H; Düren, M; Dwuznik, M; Ebke, J; Edson, W; Edwards, C A; Edwards, N C; Ehrenfeld, W; 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; 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; Espinal Curull, X; Esposito, B; Etienne, F; Etienvre, A I; Etzion, E; Evangelakou, D; 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; Fatholahzadeh, B; Favareto, A; Fayard, L; Federic, P; Fedin, O L; Fedorko, W; Fehling-Kaschek, M; Feligioni, L; Feng, C; Feng, E J; Feng, H; Fenyuk, A B; Fernando, W; Ferrag, S; Ferrando, J; Ferrara, V; Ferrari, A; Ferrari, P; Ferrari, R; Ferreira de Lima, D E; Ferrer, A; Ferrere, D; Ferretti, C; Ferretto Parodi, A; 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, M J; Fitzgerald, E A; Flechl, M; Fleck, I; Fleischmann, P; Fleischmann, S; Fletcher, G T; Fletcher, G; Flick, T; Floderus, A; Flores Castillo, L R; Florez Bustos, A C; Flowerdew, M J; Fonseca Martin, T; Formica, A; Forti, A; Fortin, D; Fournier, D; Fox, H; Francavilla, P; Franchini, M; Franchino, S; Francis, D; Franklin, M; Franz, S; Fraternali, M; Fratina, S; French, S T; Friedrich, C; Friedrich, F; Froidevaux, D; Frost, J A; Fukunaga, C; Fullana Torregrosa, E; Fulsom, B G; Fuster, J; Gabaldon, C; Gabizon, O; Gabrielli, A; Gabrielli, A; Gadatsch, S; Gadfort, T; 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; Garay Walls, F M; Garberson, F; García, C; García Navarro, J E; 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; Gillman, A R; Gingrich, D M; Giokaris, N; Giordani, M P; Giordano, R; Giorgi, F M; Giovannini, P; Giraud, P F; Giugni, D; Giuliani, C; Giunta, M; Gjelsten, B K; Gkialas, I; Gladilin, L K; Glasman, C; Glatzer, J; 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; Gomez Fajardo, L S; Gonçalo, R; Goncalves Pinto Firmino Da Costa, J; Gonella, L; González de la Hoz, S; Gonzalez Parra, G; Gonzalez Silva, M L; 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; 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, F; Grancagnolo, S; Grassi, V; Gratchev, V; Gray, H M; Gray, J A; 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; 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; Gutierrez Ortiz, N G; Gutschow, C; Guttman, N; Guyot, C; Gwenlan, C; Gwilliam, C B; Haas, A; Haber, C; Hadavand, H K; Haefner, P; Hageboeck, S; Hajduk, Z; Hakobyan, H; Haleem, M; Hall, D; Halladjian, G; Hamacher, K; Hamal, P; Hamano, K; Hamer, M; Hamilton, A; Hamilton, S; Han, L; Hanagaki, K; Hanawa, K; Hance, M; Hanke, P; Hansen, J R; Hansen, J B; Hansen, J D; Hansen, P H; Hansson, P; Hara, K; Hard, A S; Harenberg, T; Harkusha, S; Harper, D; Harrington, R D; Harris, O M; Harrison, P F; Hartjes, F; Harvey, A; Hasegawa, S; Hasegawa, Y; Hassani, S; Haug, S; Hauschild, M; Hauser, R; Havranek, M; Hawkes, C M; Hawkings, R J; Hawkins, A D; Hayashi, T; Hayden, D; Hays, C P; Hayward, H S; Haywood, S J; Head, S J; Heck, T; Hedberg, V; Heelan, L; Heim, S; Heinemann, B; Heisterkamp, S; Hejbal, J; Helary, L; Heller, C; Heller, M; Hellman, S; Hellmich, D; Helsens, C; Henderson, J; Henderson, R C W; Henrichs, A; Henriques Correia, A M; Henrot-Versille, S; Hensel, C; Herbert, G H; Hernandez, C M; Hernández Jiménez, Y; Herrberg-Schubert, R; Herten, G; Hertenberger, R; Hervas, L; Hesketh, G G; Hessey, N P; Hickling, R; Higón-Rodriguez, E; Hill, J C; Hiller, K H; Hillert, S; Hillier, S J; Hinchliffe, I; Hines, E; Hirose, M; Hirschbuehl, D; Hobbs, J; Hod, N; Hodgkinson, M C; Hodgson, P; Hoecker, A; Hoeferkamp, M R; Hoffman, J; Hoffmann, D; Hofmann, J I; Hohlfeld, M; Holmes, T R; Hong, T M; Hooft van Huysduynen, L; Hostachy, J-Y; Hou, S; Hoummada, A; Howard, J; Howarth, J; Hrabovsky, M; Hristova, I; Hrivnac, J; Hryn'ova, T; Hsu, P J; Hsu, S-C; Hu, D; Hu, X; Huang, Y; Hubacek, Z; Hubaut, F; Huegging, F; Huettmann, A; Huffman, T B; Hughes, E W; Hughes, G; Huhtinen, M; Hülsing, T A; Hurwitz, M; Huseynov, N; Huston, J; Huth, J; Iacobucci, G; Iakovidis, G; Ibragimov, I; Iconomidou-Fayard, L; Idarraga, J; Ideal, E; Iengo, P; Igonkina, O; Iizawa, T; Ikegami, Y; Ikematsu, K; Ikeno, M; Iliadis, D; Ilic, N; Inamaru, Y; Ince, T; Ioannou, P; Iodice, M; Iordanidou, K; Ippolito, V; Irles Quiles, A; Isaksson, C; Ishino, M; Ishitsuka, M; Ishmukhametov, R; Issever, C; Istin, S; Ivashin, A V; Iwanski, W; Iwasaki, H; Izen, J M; Izzo, V; Jackson, B; Jackson, J N; Jackson, M; Jackson, P; Jaekel, M R; Jain, V; Jakobs, K; Jakobsen, S; Jakoubek, T; Jakubek, J; Jamin, D O; Jana, D K; Jansen, E; Jansen, H; Janssen, J; Janus, M; Jared, R C; Jarlskog, G; Jeanty, L; Jeng, G-Y; Jen-La Plante, I; Jennens, D; Jenni, P; Jentzsch, J; Jeske, C; Jézéquel, S; Jha, M K; Ji, H; Ji, W; Jia, J; Jiang, Y; Jimenez Belenguer, M; Jin, S; Jinaru, A; Jinnouchi, O; Joergensen, M D; Joffe, D; Johansson, K E; Johansson, P; Johns, K A; Jon-And, K; Jones, G; Jones, R W L; Jones, T J; Jorge, P M; Joshi, K D; Jovicevic, J; Ju, X; Jung, C A; Jungst, R M; Jussel, P; Juste Rozas, A; Kaci, M; Kaczmarska, A; Kadlecik, P; Kado, M; Kagan, H; Kagan, M; Kajomovitz, E; Kalinin, S; Kama, S; Kanaya, N; Kaneda, M; Kaneti, S; Kanno, T; Kantserov, V A; Kanzaki, J; Kaplan, B; Kapliy, A; Kar, D; Karakostas, K; Karastathis, N; Karnevskiy, M; Karpov, S N; Karthik, K; Kartvelishvili, V; Karyukhin, A N; Kashif, L; Kasieczka, G; Kass, R D; Kastanas, A; Kataoka, Y; Katre, A; Katzy, J; Kaushik, V; Kawagoe, K; Kawamoto, T; Kawamura, G; Kazama, S; Kazanin, V F; Kazarinov, M Y; Keeler, R; Keener, P T; Kehoe, R; Keil, M; Keller, J S; Keoshkerian, H; Kepka, O; Kerševan, B P; Kersten, S; Kessoku, K; Keung, J; Khalil-Zada, F; Khandanyan, H; Khanov, A; Kharchenko, D; Khodinov, A; Khomich, A; Khoo, T J; Khoriauli, G; Khoroshilov, A; Khovanskiy, V; Khramov, E; Khubua, J; Kim, H; Kim, S H; Kimura, N; Kind, O; King, B T; King, M; King, R S B; King, S B; Kirk, J; Kiryunin, A E; Kishimoto, T; Kisielewska, D; Kitamura, T; Kittelmann, T; Kiuchi, K; Kladiva, E; Klein, M; Klein, U; Kleinknecht, K; Klimek, P; Klimentov, A; Klingenberg, R; Klinger, J A; Klinkby, E B; Klioutchnikova, T; Klok, P F; Kluge, E-E; Kluit, P; Kluth, S; Kneringer, E; Knoops, E B F G; Knue, A; Kobayashi, T; Kobel, M; Kocian, M; Kodys, P; Koenig, S; Koevesarki, P; Koffas, T; Koffeman, E; Kogan, L A; Kohlmann, S; Kohout, Z; Kohriki, T; Koi, T; Kolanoski, H; Koletsou, I; Koll, J; Komar, A A; Komori, Y; Kondo, T; Köneke, K; König, A C; Kono, T; Konoplich, R; Konstantinidis, N; Kopeliansky, R; Koperny, S; Köpke, L; Kopp, A K; Korcyl, K; Kordas, K; Korn, A; Korol, A A; Korolkov, I; Korolkova, E V; Korotkov, V A; Kortner, O; Kortner, S; Kostyukhin, V V; Kotov, S; Kotov, V M; Kotwal, A; Kourkoumelis, C; Kouskoura, V; Koutsman, A; Kowalewski, R; Kowalski, T Z; Kozanecki, W; Kozhin, A S; Kral, V; Kramarenko, V A; Kramberger, G; Krasny, M W; Krasznahorkay, A; Kraus, J K; Kravchenko, A; Kreiss, S; Kretzschmar, J; Kreutzfeldt, K; Krieger, N; Krieger, P; Kroeninger, K; Kroha, H; Kroll, J; Kroseberg, J; Krstic, J; Kruchonak, U; Krüger, H; Kruker, T; Krumnack, N; Krumshteyn, Z V; Kruse, A; Kruse, M C; Kruskal, M; Kubota, T; Kuday, S; Kuehn, S; Kugel, A; Kuhl, T; Kukhtin, V; Kulchitsky, Y; Kuleshov, S; Kuna, M; Kunkle, J; Kupco, A; Kurashige, H; Kurata, M; Kurochkin, Y A; Kurumida, R; Kus, V; Kuwertz, E S; Kuze, M; Kvita, J; Kwee, R; La Rosa, A; La Rotonda, L; Labarga, L; Lablak, S; Lacasta, C; Lacava, F; Lacey, J; Lacker, H; Lacour, D; Lacuesta, V R; Ladygin, E; Lafaye, R; Laforge, B; Lagouri, T; Lai, S; Laier, H; Laisne, E; Lambourne, L; Lampen, C L; Lampl, W; Lançon, E; Landgraf, U; Landon, M P J; Lang, V S; Lange, C; Lankford, A J; Lanni, F; Lantzsch, K; Lanza, A; Laplace, S; Lapoire, C; Laporte, J F; Lari, T; Larner, A; Lassnig, M; Laurelli, P; Lavorini, V; Lavrijsen, W; Laycock, P; Le, B T; Le Dortz, O; Le Guirriec, E; Le Menedeu, E; LeCompte, T; Ledroit-Guillon, F; Lee, C A; Lee, H; Lee, J S H; Lee, S C; Lee, L; Lefebvre, G; Lefebvre, M; Legger, F; Leggett, C; Lehan, A; Lehmacher, M; Lehmann Miotto, G; Leister, A G; Leite, M A L; Leitner, R; Lellouch, D; Lemmer, B; Lendermann, V; Leney, K J C; Lenz, T; Lenzen, G; Lenzi, B; Leone, R; Leonhardt, K; Leontsinis, S; Leroy, C; Lessard, J-R; Lester, C G; Lester, C M; Levêque, J; Levin, D; Levinson, L J; Lewis, A; Lewis, G H; Leyko, A M; Leyton, M; Li, B; Li, B; Li, H; Li, H L; Li, S; Li, X; Liang, Z; Liao, H; Liberti, B; Lichard, P; Lie, K; Liebal, J; Liebig, W; Limbach, C; Limosani, A; Limper, M; Lin, S C; Linde, F; Lindquist, B E; Linnemann, J T; Lipeles, E; Lipniacka, A; Lisovyi, M; Liss, T M; Lissauer, D; Lister, A; Litke, A M; Liu, B; Liu, D; Liu, J B; Liu, K; Liu, L; Liu, M; Liu, M; Liu, Y; Livan, M; Livermore, S S A; Lleres, A; Llorente Merino, J; Lloyd, S L; Lo Sterzo, F; Lobodzinska, E; Loch, P; Lockman, W S; Loddenkoetter, T; Loebinger, F K; Loevschall-Jensen, A E; Loginov, A; Loh, C W; Lohse, T; Lohwasser, K; Lokajicek, M; Lombardo, V P; Long, J D; Long, R E; Lopes, L; Lopez Mateos, D; Lopez Paredes, B; Lorenz, J; Lorenzo Martinez, N; Losada, M; Loscutoff, P; Losty, M J; Lou, X; Lounis, A; Love, J; Love, P A; Lowe, A J; Lu, F; Lubatti, H J; Luci, C; Lucotte, A; Ludwig, D; Ludwig, I; Luehring, F; Lukas, W; Luminari, L; Lund, E; Lundberg, J; Lundberg, O; Lund-Jensen, B; Lungwitz, M; Lynn, D; Lysak, R; Lytken, E; Ma, H; Ma, L L; Maccarrone, G; Macchiolo, A; Maček, B; Machado Miguens, J; Macina, D; Mackeprang, R; Madar, R; Madaras, R J; Maddocks, H J; Mader, W F; Madsen, A; Maeno, M; Maeno, T; Magnoni, L; Magradze, E; Mahboubi, K; Mahlstedt, J; Mahmoud, S; Mahout, G; Maiani, C; Maidantchik, C; Maio, A; Majewski, S; Makida, Y; Makovec, N; Mal, P; Malaescu, B; Malecki, Pa; Maleev, V P; Malek, F; Mallik, U; Malon, D; Malone, C; Maltezos, S; Malyshev, V M; Malyukov, S; Mamuzic, J; Mandelli, L; Mandić, I; Mandrysch, R; Maneira, J; Manfredini, A; Manhaes de Andrade Filho, L; Manjarres Ramos, J A; Mann, A; Manning, P M; Manousakis-Katsikakis, A; Mansoulie, B; Mantifel, R; Mapelli, L; March, L; Marchand, J F; Marchese, F; Marchiori, G; Marcisovsky, M; Marino, C P; Marques, C N; Marroquim, F; Marshall, Z; Marti, L F; Marti-Garcia, S; Martin, B; Martin, B; Martin, J P; Martin, T A; Martin, V J; Martin Dit Latour, B; Martinez, H; Martinez, M; Martin-Haugh, S; Martyniuk, A C; Marx, M; Marzano, F; Marzin, A; Masetti, L; Mashimo, T; Mashinistov, R; Masik, J; Maslennikov, A L; Massa, I; Massol, N; Mastrandrea, P; Mastroberardino, A; Masubuchi, T; Matsunaga, H; Matsushita, T; Mättig, P; Mättig, S; Mattmann, J; Mattravers, C; Maurer, J; Maxfield, S J; Maximov, D A; Mazini, R; Mazzaferro, L; Mazzanti, M; Mc Goldrick, G; Mc Kee, S P; McCarn, A; McCarthy, R L; McCarthy, T G; McCubbin, N A; McFarlane, K W; Mcfayden, J A; Mchedlidze, G; Mclaughlan, T; McMahon, S J; McPherson, R A; Meade, A; Mechnich, J; Mechtel, M; Medinnis, M; Meehan, S; Meera-Lebbai, R; Mehlhase, S; Mehta, A; Meier, K; Meineck, C; Meirose, B; Melachrinos, C; Mellado Garcia, B R; Meloni, F; Mendoza Navas, L; Mengarelli, A; Menke, S; Meoni, E; Mercurio, K M; Mergelmeyer, S; Meric, N; Mermod, P; Merola, L; Meroni, C; Merritt, F S; Merritt, H; Messina, A; Metcalfe, J; Mete, A S; Meyer, C; Meyer, C; Meyer, J-P; Meyer, J; Meyer, J; Michal, S; Middleton, R P; Migas, S; Mijović, L; Mikenberg, G; Mikestikova, M; Mikuž, M; Miller, D W; Mills, C; Milov, A; Milstead, D A; Milstein, D; Minaenko, A A; Miñano Moya, M; Minashvili, I A; Mincer, A I; Mindur, B; Mineev, M; Ming, Y; Mir, L M; Mirabelli, G; Mitani, T; Mitrevski, J; Mitsou, V A; Mitsui, S; Miyagawa, P S; Mjörnmark, J U; Moa, T; Moeller, V; Mohapatra, S; Mohr, W; Molander, S; Moles-Valls, R; Molfetas, A; Mönig, K; Monini, C; Monk, J; Monnier, E; Montejo Berlingen, J; Monticelli, F; Monzani, S; Moore, R W; Mora Herrera, C; Moraes, A; Morange, N; Morel, J; Moreno, D; Moreno Llácer, M; Morettini, P; Morgenstern, M; Morii, M; Moritz, S; Morley, A K; Mornacchi, G; Morris, J D; Morvaj, L; Moser, H G; Mosidze, M; Moss, J; Mount, R; Mountricha, E; Mouraviev, S V; Moyse, E J W; Mudd, R D; Mueller, F; Mueller, J; Mueller, K; Mueller, T; Mueller, T; Muenstermann, D; Munwes, Y; Murillo Quijada, J A; Murray, W J; Mussche, I; Musto, E; Myagkov, A G; Myska, M; Nackenhorst, O; Nadal, J; Nagai, K; Nagai, R; Nagai, Y; Nagano, K; Nagarkar, A; Nagasaka, Y; Nagel, M; Nairz, A M; Nakahama, Y; Nakamura, K; Nakamura, T; Nakano, I; Namasivayam, H; Nanava, G; Napier, A; Narayan, R; Nash, M; Nattermann, T; Naumann, T; Navarro, G; Neal, H A; Nechaeva, P Yu; Neep, T J; Negri, A; Negri, G; Negrini, M; Nektarijevic, S; Nelson, A; Nelson, T K; Nemecek, S; Nemethy, P; Nepomuceno, A A; Nessi, M; Neubauer, M S; Neumann, M; Neusiedl, A; Neves, R M; Nevski, P; Newcomer, F M; Newman, P R; Nguyen, D H; Nguyen Thi Hong, V; Nickerson, R B; Nicolaidou, R; Nicquevert, B; Nielsen, J; Nikiforou, N; Nikiforov, A; Nikolaenko, V; Nikolic-Audit, I; Nikolics, K; Nikolopoulos, K; Nilsson, P; Ninomiya, Y; Nisati, A; Nisius, R; Nobe, T; Nodulman, L; Nomachi, M; Nomidis, I; Norberg, S; Nordberg, M; Novakova, J; Nozaki, M; Nozka, L; Ntekas, K; Nuncio-Quiroz, A-E; Nunes Hanninger, G; Nunnemann, T; Nurse, E; O'Brien, B J; O'Grady, F; O'Neil, D C; O'Shea, V; Oakes, L B; Oakham, F G; Oberlack, H; Ocariz, J; Ochi, A; Ochoa, M I; Oda, S; Odaka, S; Ogren, H; Oh, A; Oh, S H; Ohm, C C; Ohshima, T; Okamura, W; Okawa, H; Okumura, Y; Okuyama, T; Olariu, A; Olchevski, A G; Olivares Pino, S A; Oliveira, M; Oliveira Damazio, D; Oliver Garcia, E; Olivito, D; Olszewski, A; Olszowska, J; Onofre, A; Onyisi, P U E; Oram, C J; Oreglia, M J; Oren, Y; Orestano, D; Orlando, N; Oropeza Barrera, C; Orr, R S; Osculati, B; Ospanov, R; Otero Y Garzon, G; Otono, H; Ouchrif, M; Ouellette, E A; Ould-Saada, F; Ouraou, A; Oussoren, K P; Ouyang, Q; Ovcharova, A; Owen, M; Owen, S; Ozcan, V E; Ozturk, N; Pachal, K; Pacheco Pages, A; Padilla Aranda, C; Pagan Griso, S; Paganis, E; Pahl, C; Paige, F; Pais, P; Pajchel, K; Palacino, G; Palestini, S; Pallin, D; Palma, A; Palmer, J D; Pan, Y B; Panagiotopoulou, E; Panduro Vazquez, J G; Pani, P; Panikashvili, N; Panitkin, S; Pantea, D; Papadopoulou, Th D; Papageorgiou, K; Paramonov, A; Paredes Hernandez, D; Parker, M A; Parodi, F; Parsons, J A; Parzefall, U; Pashapour, S; Pasqualucci, E; Passaggio, S; Passeri, A; Pastore, F; Pastore, Fr; Pásztor, G; Pataraia, S; Patel, N D; Pater, J R; Patricelli, S; Pauly, T; Pearce, J; Pedersen, M; Pedraza Lopez, S; Pedro, R; Peleganchuk, S V; Pelikan, D; Peng, H; Penning, B; Penwell, J; Perepelitsa, D V; Perez Cavalcanti, T; Perez Codina, E; Pérez García-Estañ, M T; Perez Reale, V; Perini, L; Pernegger, H; Perrino, R; Peschke, R; Peshekhonov, V D; Peters, K; Peters, R F Y; Petersen, B A; Petersen, J; Petersen, T C; Petit, E; Petridis, A; Petridou, C; Petrolo, E; Petrucci, F; Petteni, M; Pezoa, R; Phillips, P W; Piacquadio, G; Pianori, E; Picazio, A; Piccaro, E; Piccinini, M; Piec, S M; Piegaia, R; Pignotti, D T; Pilcher, J E; Pilkington, A D; Pina, J; Pinamonti, M; Pinder, A; Pinfold, J L; Pingel, A; Pinto, B; Pizio, C; Pleier, M-A; Pleskot, V; Plotnikova, E; Plucinski, P; Poddar, S; Podlyski, F; Poettgen, R; Poggioli, L; Pohl, D; Pohl, M; Polesello, G; Policicchio, A; Polifka, R; Polini, A; Pollard, C S; Polychronakos, V; Pomeroy, D; Pommès, K; Pontecorvo, L; Pope, B G; Popeneciu, G A; Popovic, D S; Poppleton, A; Portell Bueso, X; Pospelov, G E; Pospisil, S; Potamianos, K; Potrap, I N; Potter, C J; Potter, C T; Poulard, G; Poveda, J; Pozdnyakov, V; Prabhu, R; Pralavorio, P; Pranko, A; Prasad, S; Pravahan, R; Prell, S; Price, D; Price, J; Price, L E; Prieur, D; Primavera, M; Proissl, M; Prokofiev, K; Prokoshin, F; Protopapadaki, E; Protopopescu, S; Proudfoot, J; Prudent, X; Przybycien, M; Przysiezniak, H; Psoroulas, S; Ptacek, E; Pueschel, E; Puldon, D; Purohit, M; Puzo, P; Pylypchenko, Y; Qian, J; Quadt, A; Quarrie, D R; Quayle, W B; Quilty, D; Radeka, V; Radescu, V; Radhakrishnan, S K; Radloff, P; Ragusa, F; Rahal, G; Rajagopalan, S; Rammensee, M; Rammes, M; Randle-Conde, A S; Rangel-Smith, C; Rao, K; Rauscher, F; Rave, T C; Ravenscroft, T; Raymond, M; Read, A L; Rebuzzi, D M; Redelbach, A; Redlinger, G; Reece, R; Reeves, K; Reinsch, A; Reisin, H; Reisinger, I; Relich, M; Rembser, C; Ren, Z L; Renaud, A; Rescigno, M; Resconi, S; Resende, B; Reznicek, P; Rezvani, R; Richter, R; Ridel, M; Rieck, P; Rijssenbeek, M; Rimoldi, A; Rinaldi, L; 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, 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; Sacerdoti, S; 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; Sales De Bruin, P H; Salihagic, D; Salnikov, A; Salt, J; Salvachua Ferrando, B M; Salvatore, D; Salvatore, F; Salvucci, A; Salzburger, A; Sampsonidis, D; Sanchez, A; Sánchez, J; Sanchez Martinez, V; Sandaker, H; Sander, H G; Sanders, M P; Sandhoff, M; Sandoval, T; Sandoval, C; Sandstroem, R; Sankey, D P C; Sansoni, A; Santoni, C; Santonico, R; Santos, H; Santoyo Castillo, I; Sapp, K; Sapronov, A; Saraiva, J G; Sarkisyan-Grinbaum, E; Sarrazin, B; Sartisohn, G; Sasaki, O; Sasaki, Y; Sasao, N; Satsounkevitch, I; Sauvage, G; Sauvan, E; Sauvan, J B; Savard, P; Savinov, V; Savu, D O; Sawyer, C; Sawyer, L; Saxon, D H; Saxon, J; Sbarra, C; Sbrizzi, A; Scanlon, T; Scannicchio, D A; Scarcella, M; Schaarschmidt, J; Schacht, P; Schaefer, D; Schaelicke, A; Schaepe, S; Schaetzel, S; Schäfer, U; Schaffer, A C; Schaile, D; Schamberger, R D; Scharf, V; Schegelsky, V A; Scheirich, D; Schernau, M; Scherzer, M I; Schiavi, C; Schieck, J; Schillo, C; Schioppa, M; Schlenker, S; Schmidt, E; Schmieden, K; Schmitt, C; Schmitt, C; Schmitt, S; 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, Ph; Schwartzman, A; Schwegler, Ph; Schwemling, Ph; 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, Dj; Silbert, O; Silva, J; Silver, Y; Silverstein, D; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; 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 Yu; Sjölin, J; Sjursen, T B; Skinnari, L A; Skottowe, H P; Skovpen, K Yu; Skubic, P; Slater, M; Slavicek, T; Sliwa, K; Smakhtin, V; Smart, B H; Smestad, L; Smirnov, S Yu; 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 Yu; 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; Su, J; Subramania, Hs; 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, Yu 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; 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 C-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; 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; Vardanyan, G; 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; 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; 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, 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; 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; Zengel, K; 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; Zimine, N I; Zimmermann, C; Zimmermann, R; Zimmermann, S; Zimmermann, S; Zinonos, Z; Ziolkowski, M; Zitoun, R; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zurzolo, G; Zutshi, V; Zwalinski, L

The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton-proton collision data with a centre-of-mass energy of [Formula: see text] TeV corresponding to an integrated luminosity of [Formula: see text][Formula: see text]. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti-[Formula: see text] algorithm with distance parameters [Formula: see text] or [Formula: see text], and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a [Formula: see text] boson, for [Formula: see text] and pseudorapidities [Formula: see text]. The effect of multiple proton-proton interactions is corrected for, and an uncertainty is evaluated using in situ techniques. The smallest JES uncertainty of less than 1 % is found in the central calorimeter region ([Formula: see text]) for jets with [Formula: see text]. For central jets at lower [Formula: see text], the uncertainty is about 3 %. A consistent JES estimate is found using measurements of the calorimeter response of single hadrons in proton-proton collisions and test-beam data, which also provide the estimate for [Formula: see text] TeV. The calibration of forward jets is derived from dijet [Formula: see text] balance measurements. The resulting uncertainty reaches its largest value of 6 % for low-[Formula: see text] jets at [Formula: see text]. Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5-3 %.

Jet energy measurement and its systematic uncertainty in proton–proton collisions at √s = 7 TeV with the ATLAS detector

DOE PAGES

Aad, G.

2015-01-15

The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton–proton collision data with a centre-of-mass energy of \\(\\sqrt{s}=7\\) TeV corresponding to an integrated luminosity of \\(4.7\\) \\(\\,\\,\\text{ fb }^{-1}\\). Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti-\\(k_{t}\\) algorithm with distance parameters \\(R=0.4\\) or \\(R=0.6\\), and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transversemore » momentum balance between a jet and a reference object such as a photon or a \\(Z\\) boson, for \\({20} \\le p_{\\mathrm {T}}^\\mathrm {jet}<{1000}\\, ~\\mathrm{GeV }\\) and pseudorapidities \\(|\\eta |<{4.5}\\). The effect of multiple proton–proton interactions is corrected for, and an uncertainty is evaluated using in situ techniques. The smallest JES uncertainty of less than 1 % is found in the central calorimeter region (\\(|\\eta |<{1.2}\\)) for jets with \\({55} \\le p_{\\mathrm {T}}^\\mathrm {jet}<{500}\\, ~\\mathrm{GeV }\\). For central jets at lower \\(p_{\\mathrm {T}}\\), the uncertainty is about 3 %. A consistent JES estimate is found using measurements of the calorimeter response of single hadrons in proton–proton collisions and test-beam data, which also provide the estimate for \\(p_{\\mathrm {T}}^\\mathrm {jet}> 1\\) TeV. The calibration of forward jets is derived from dijet \\(p_{\\mathrm {T}}\\) balance measurements. The resulting uncertainty reaches its largest value of 6 % for low-\\(p_{\\mathrm {T}}\\) jets at \\(|\\eta |=4.5\\). In addition, JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5–3 %.« less

Using high-throughput literature mining to support read-across predictions of toxicity (SOT)

EPA Science Inventory

Building scientific confidence in the development and evaluation of read-across remains an ongoing challenge. Approaches include establishing systematic frameworks to identify sources of uncertainty and ways to address them. One source of uncertainty is related to characterizing ...

High-throughput literature mining to support read-across predictions of toxicity (ASCCT meeting)

EPA Science Inventory

Building scientific confidence in the development and evaluation of read-across remains an ongoing challenge. Approaches include establishing systematic frameworks to identify sources of uncertainty and ways to address them. One source of uncertainty is related to characterizing ...

Systematic Uncertainties in High-Energy Hadronic Interaction Models

NASA Astrophysics Data System (ADS)

Zha, M.; Knapp, J.; Ostapchenko, S.

2003-07-01

Hadronic interaction models for cosmic ray energies are uncertain since our knowledge of hadronic interactions is extrap olated from accelerator experiments at much lower energies. At present most high-energy models are based on Grib ov-Regge theory of multi-Pomeron exchange, which provides a theoretical framework to evaluate cross-sections and particle production. While experimental data constrain some of the model parameters, others are not well determined and are therefore a source of systematic uncertainties. In this paper we evaluate the variation of results obtained with the QGSJET model, when modifying parameters relating to three ma jor sources of uncertainty: the form of the parton structure function, the role of diffractive interactions, and the string hadronisation. Results on inelastic cross sections, on secondary particle production and on the air shower development are discussed.

Systematic uncertainties in long-baseline neutrino-oscillation experiments

NASA Astrophysics Data System (ADS)

Ankowski, Artur M.; Mariani, Camillo

2017-05-01

Future neutrino-oscillation experiments are expected to bring definite answers to the questions of neutrino-mass hierarchy and violation of charge-parity symmetry in the lepton-sector. To realize this ambitious program it is necessary to ensure a significant reduction of uncertainties, particularly those related to neutrino-energy reconstruction. In this paper, we discuss different sources of systematic uncertainties, paying special attention to those arising from nuclear effects and detector response. By analyzing nuclear effects we show the importance of developing accurate theoretical models, capable of providing a quantitative description of neutrino cross sections, together with the relevance of their implementation in Monte Carlo generators and extensive testing against lepton-scattering data. We also point out the fundamental role of efforts aiming to determine detector responses in test-beam exposures.

Defining and Measuring Diagnostic Uncertainty in Medicine: A Systematic Review.

PubMed

Bhise, Viraj; Rajan, Suja S; Sittig, Dean F; Morgan, Robert O; Chaudhary, Pooja; Singh, Hardeep

2018-01-01

Physicians routinely encounter diagnostic uncertainty in practice. Despite its impact on health care utilization, costs and error, measurement of diagnostic uncertainty is poorly understood. We conducted a systematic review to describe how diagnostic uncertainty is defined and measured in medical practice. We searched OVID Medline and PsycINFO databases from inception until May 2017 using a combination of keywords and Medical Subject Headings (MeSH). Additional search strategies included manual review of references identified in the primary search, use of a topic-specific database (AHRQ-PSNet) and expert input. We specifically focused on articles that (1) defined diagnostic uncertainty; (2) conceptualized diagnostic uncertainty in terms of its sources, complexity of its attributes or strategies for managing it; or (3) attempted to measure diagnostic uncertainty. We identified 123 articles for full review, none of which defined diagnostic uncertainty. Three attributes of diagnostic uncertainty were relevant for measurement: (1) it is a subjective perception experienced by the clinician; (2) it has the potential to impact diagnostic evaluation-for example, when inappropriately managed, it can lead to diagnostic delays; and (3) it is dynamic in nature, changing with time. Current methods for measuring diagnostic uncertainty in medical practice include: (1) asking clinicians about their perception of uncertainty (surveys and qualitative interviews), (2) evaluating the patient-clinician encounter (such as by reviews of medical records, transcripts of patient-clinician communication and observation), and (3) experimental techniques (patient vignette studies). The term "diagnostic uncertainty" lacks a clear definition, and there is no comprehensive framework for its measurement in medical practice. Based on review findings, we propose that diagnostic uncertainty be defined as a "subjective perception of an inability to provide an accurate explanation of the patient's health problem." Methodological advancements in measuring diagnostic uncertainty can improve our understanding of diagnostic decision-making and inform interventions to reduce diagnostic errors and overuse of health care resources.

Our Sun IV: The Standard Model and Helioseismology: Consequences of Uncertainties in Input Physics and in Observed Solar Parameters

NASA Technical Reports Server (NTRS)

Boothroyd, Arnold I.; Sackmann, I.-Juliana

2001-01-01

Helioseismic frequency observations provide an extremely accurate window into the solar interior; frequencies from the Michaelson Doppler Imager (MDI) on the Solar and Heliospheric Observatory (SOHO) spacecraft, enable the adiabatic sound speed and adiabatic index to be inferred with an accuracy of a few parts in 10(exp 4) and the density with an accuracy of a few parts in 10(exp 3). This has become a Serious challenge to theoretical models of the Sun. Therefore, we have undertaken a self-consistent, systematic study of the sources of uncertainties in the standard solar models. We found that the largest effect on the interior structure arises from the observational uncertainties in the photospheric abundances of the elements, which affect the sound speed profile at the level of 3 parts in 10(exp 3). The estimated 4% uncertainty in the OPAL opacities could lead to effects of 1 part in 10(exp 3); the approximately 5%, uncertainty in the basic pp nuclear reaction rate would have a similar effect, as would uncertainties of approximately 15% in the diffusion constants for the gravitational settling of helium. The approximately 50% uncertainties in diffusion constants for the heavier elements would have nearly as large an effect. Different observational methods for determining the solar radius yield results differing by as much as 7 parts in 10(exp 4); we found that this leads to uncertainties of a few parts in 10(exp 3) in the sound speed int the solar convective envelope, but has negligible effect on the interior. Our reference standard solar model yielded a convective envelope position of 0.7135 solar radius, in excellent agreement with the observed value of 0.713 +/- 0.001 solar radius and was significantly affected only by Z/X, the pp rate, and the uncertainties in helium diffusion constants. Our reference model also yielded envelope helium abundance of 0.2424, in good agreement with the approximate range of 0.24 to 0.25 inferred from helioseismic observations; only extreme Z/X values yielded envelope helium abundance outside this range. We found that other current uncertainties, namely, in the solar age and luminosity, in nuclear rates other than the pp reaction, in the low-temperature molecular opacities, and in the low-density equation of state, have no significant effect on the quantities that can be inferred from helioseismic observations. The predicted pre-main-sequence lithium depletion is uncertain by a factor of 2. The predicted neutrino capture rate is uncertain by approximately 30% for the Cl-27 experiment and by approximately 3% for Ga-71 experiments, while the B-8 neutrino flux is uncertain by approximately 30%.

Radiologist Uncertainty and the Interpretation of Screening

PubMed Central

Carney, Patricia A.; Elmore, Joann G.; Abraham, Linn A.; Gerrity, Martha S.; Hendrick, R. Edward; Taplin, Stephen H.; Barlow, William E.; Cutter, Gary R.; Poplack, Steven P.; D’Orsi, Carl J.

2011-01-01

Objective To determine radiologists’ reactions to uncertainty when interpreting mammography and the extent to which radiologist uncertainty explains variability in interpretive performance. Methods The authors used a mailed survey to assess demographic and clinical characteristics of radiologists and reactions to uncertainty associated with practice. Responses were linked to radiologists’ actual interpretive performance data obtained from 3 regionally located mammography registries. Results More than 180 radiologists were eligible to participate, and 139 consented for a response rate of 76.8%. Radiologist gender, more years interpreting, and higher volume were associated with lower uncertainty scores. Positive predictive value, recall rates, and specificity were more affected by reactions to uncertainty than sensitivity or negative predictive value; however, none of these relationships was statistically significant. Conclusion Certain practice factors, such as gender and years of interpretive experience, affect uncertainty scores. Radiologists’ reactions to uncertainty do not appear to affect interpretive performance. PMID:15155014

Colorful Investigations of Supernovae for WFIRST-AFTA

NASA Astrophysics Data System (ADS)

Foley, Ryan

Type Ia supernovae (SNe Ia) are extremely good probes of dark energy, and WFIRST-AFTA is particularly well suited to make the best SN distance measurements possible. For conservative assumptions, the WFIRST SN survey is projected to have twice the impact as its other probes. Considering that Euclid will only have a minimal SN survey, but strong programs for other dark energy probes, the WFIRST SN survey is especially unique and important. With an initial simulation of the WFIRST-AFTA survey, we have determined that the largest statistical and systematic uncertainties are related to SN color. SN distances strongly depend on the precise measurement of SN colors since we must make a dust extinction correction that depends on the observed color. The details of how the correction is applied and the possibility that the correction evolves with redshift combine with potential calibration systematics to limit the current effectiveness of the SN component of WFIRST-AFTA. Here, we propose to support two graduate students to (1) investigate how intrinsic color variations will impact WFIRST-AFTA systematic uncertainties, (2) determine improved methods for reducing the systematic uncertainties related to SN color, and (3) simulate survey strategies incorporating our results to obtain the highest dark energy figure of merit (DE-FoM).

SPIDER. V. MEASURING SYSTEMATIC EFFECTS IN EARLY-TYPE GALAXY STELLAR MASSES FROM PHOTOMETRIC SPECTRAL ENERGY DISTRIBUTION FITTING

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

Swindle, R.; Gal, R. R.; La Barbera, F.

2011-10-15

We present robust statistical estimates of the accuracy of early-type galaxy stellar masses derived from spectral energy distribution (SED) fitting as functions of various empirical and theoretical assumptions. Using large samples consisting of {approx}40,000 galaxies from the Sloan Digital Sky Survey (SDSS; ugriz), of which {approx}5000 are also in the UKIRT Infrared Deep Sky Survey (YJHK), with spectroscopic redshifts in the range 0.05 {<=} z {<=} 0.095, we test the reliability of some commonly used stellar population models and extinction laws for computing stellar masses. Spectroscopic ages (t), metallicities (Z), and extinctions (A{sub V} ) are also computed from fitsmore » to SDSS spectra using various population models. These external constraints are used in additional tests to estimate the systematic errors in the stellar masses derived from SED fitting, where t, Z, and A{sub V} are typically left as free parameters. We find reasonable agreement in mass estimates among stellar population models, with variation of the initial mass function and extinction law yielding systematic biases on the mass of nearly a factor of two, in agreement with other studies. Removing the near-infrared bands changes the statistical bias in mass by only {approx}0.06 dex, adding uncertainties of {approx}0.1 dex at the 95% CL. In contrast, we find that removing an ultraviolet band is more critical, introducing 2{sigma} uncertainties of {approx}0.15 dex. Finally, we find that the stellar masses are less affected by the absence of metallicity and/or dust extinction knowledge. However, there is a definite systematic offset in the mass estimate when the stellar population age is unknown, up to a factor of 2.5 for very old (12 Gyr) stellar populations. We present the stellar masses for our sample, corrected for the measured systematic biases due to photometrically determined ages, finding that age errors produce lower stellar masses by {approx}0.15 dex, with errors of {approx}0.02 dex at the 95% CL for the median stellar age subsample.« less

Systematic uncertainties in RF-based measurement of superconducting cavity quality factors

DOE PAGES

Holzbauer, J. P.; Pischalnikov, Yu.; Sergatskov, D. A.; ...

2016-05-10

Q 0 determinations based on RF power measurements are subject to at least three potentially large systematic effects that have not been previously appreciated. Here, instrumental factors that can systematically bias RF based measurements of Q 0 are quantified and steps that can be taken to improve the determination of Q 0 are discussed.

PROBING X-RAY ABSORPTION AND OPTICAL EXTINCTION IN THE INTERSTELLAR MEDIUM USING CHANDRA OBSERVATIONS OF SUPERNOVA REMNANTS

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

Foight, Dillon R.; Slane, Patrick O.; Güver, Tolga

We present a comprehensive study of interstellar X-ray extinction using the extensive Chandra supernova remnant (SNR) archive and use our results to refine the empirical relation between the hydrogen column density and optical extinction. In our analysis, we make use of the large, uniform data sample to assess various systematic uncertainties in the measurement of the interstellar X-ray absorption. Specifically, we address systematic uncertainties that originate from (i) the emission models used to fit SNR spectra; (ii) the spatial variations within individual remnants; (iii) the physical conditions of the remnant such as composition, temperature, and non-equilibrium regions; and (iv) themore » model used for the absorption of X-rays in the interstellar medium. Using a Bayesian framework to quantify these systematic uncertainties, and combining the resulting hydrogen column density measurements with the measurements of optical extinction toward the same remnants, we find the empirical relation N {sub H} = (2.87 ± 0.12) × 10{sup 21} A {sub V} cm{sup 2}, which is significantly higher than the previous measurements.« less

Exploring Uncertainty with Projectile Launchers

ERIC Educational Resources Information Center

Orzel, Chad; Reich, Gary; Marr, Jonathan

2012-01-01

The proper choice of a measurement technique that minimizes systematic and random uncertainty is an essential part of experimental physics. These issues are difficult to teach in the introductory laboratory, though. Because most experiments involve only a single measurement technique, students are often unable to make a clear distinction between…

Proton elastic form factor ratios to Q2=3.5GeV2 by polarization transfer

NASA Astrophysics Data System (ADS)

Punjabi, V.; Perdrisat, C. F.; Aniol, K. A.; Baker, F. T.; Berthot, J.; Bertin, P. Y.; Bertozzi, W.; Besson, A.; Bimbot, L.; Boeglin, W. U.; Brash, E. J.; Brown, D.; Calarco, J. R.; Cardman, L. S.; Chai, Z.; Chang, C.-C.; Chen, J.-P.; Chudakov, E.; Churchwell, S.; Cisbani, E.; Dale, D. S.; Leo, R. De; Deur, A.; Diederich, B.; Domingo, J. J.; Epstein, M. B.; Ewell, L. A.; Fissum, K. G.; Fleck, A.; Fonvieille, H.; Frullani, S.; Gao, J.; Garibaldi, F.; Gasparian, A.; Gerstner, G.; Gilad, S.; Gilman, R.; Glamazdin, A.; Glashausser, C.; Gomez, J.; Gorbenko, V.; Green, A.; Hansen, J.-O.; Howell, C. R.; Huber, G. M.; Iodice, M.; de Jager, C. W.; Jaminion, S.; Jiang, X.; Jones, M. K.; Kahl, W.; Kelly, J. J.; Khayat, M.; Kramer, L. H.; Kumbartzki, G.; Kuss, M.; Lakuriki, E.; Laveissière, G.; Lerose, J. J.; Liang, M.; Lindgren, R. A.; Liyanage, N.; Lolos, G. J.; Macri, R.; Madey, R.; Malov, S.; Margaziotis, D. J.; Markowitz, P.; McCormick, K.; McIntyre, J. I.; Meer, R. L.; Michaels, R.; Milbrath, B. D.; Mougey, J. Y.; Nanda, S. K.; Offermann, E. A.; Papandreou, Z.; Pentchev, L.; Petratos, G. G.; Piskunov, N. M.; Pomatsalyuk, R. I.; Prout, D. L.; Quéméner, G.; Ransome, R. D.; Raue, B. A.; Roblin, Y.; Roche, R.; Rutledge, G.; Rutt, P. M.; Saha, A.; Saito, T.; Sarty, A. J.; Smith, T. P.; Sorokin, P.; Strauch, S.; Suleiman, R.; Takahashi, K.; Templon, J. A.; Todor, L.; Ulmer, P. E.; Urciuoli, G. M.; Vernin, P.; Vlahovic, B.; Voskanyan, H.; Wijesooriya, K.; Wojtsekhowski, B. B.; Woo, R. J.; Xiong, F.; Zainea, G. D.; Zhou, Z.-L.

2005-05-01

The ratio of the proton elastic electromagnetic form factors, GEp/GMp, was obtained by measuring Pt and Pℓ, the transverse and longitudinal recoil proton polarization components, respectively, for the elastic e→p→ep→reaction in the four-momentum transfer squared range of 0.5 to 3.5GeV2. In the single-photon exchange approximation, GEp/GMp is directly proportional to Pt/Pℓ. The simultaneous measurement of Pt and Pℓ in a polarimeter reduces systematic uncertainties. The results for GEp/GMp show a systematic decrease with increasing Q2, indicating for the first time a definite difference in the distribution of charge and magnetization in the proton. The data have been reanalyzed and their systematic uncertainties have become significantly smaller than those reported previously.

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

NASA Technical Reports Server (NTRS)

Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE PAGES

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; ...

2016-08-24

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

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

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

Erratum to: Measurement of jet multiplicity distributions in $$\\mathrm {t}\\overline{\\mathrm {t}}$$ production in pp collisions at $$\\sqrt{s} = 7\\,\\text {TeV} $$

DOE PAGES

Chatrchyan, Serguei

2015-05-19

Table 4 was incorrectly captioned in the originally published version. The correct caption is ‘Normalised differential tt - production cross section as a function of the number of additional jets with p T > 30 GeV in the lepton+jets channel. Furthermore, the statistical, systematic, and total uncertainties are also shown. Finally, the main experimental and model systematic uncertainties are displayed: JES and the combination of renormalisation and factorisation scales, jet-parton matching threshold, and hadronisation (in the table “Q 2/Match./Had.”)’.

An efficient energy response model for liquid scintillator detectors

NASA Astrophysics Data System (ADS)

Lebanowski, Logan; Wan, Linyan; Ji, Xiangpan; Wang, Zhe; Chen, Shaomin

2018-05-01

Liquid scintillator detectors are playing an increasingly important role in low-energy neutrino experiments. In this article, we describe a generic energy response model of liquid scintillator detectors that provides energy estimations of sub-percent accuracy. This model fits a minimal set of physically-motivated parameters that capture the essential characteristics of scintillator response and that can naturally account for changes in scintillator over time, helping to avoid associated biases or systematic uncertainties. The model employs a one-step calculation and look-up tables, yielding an immediate estimation of energy and an efficient framework for quantifying systematic uncertainties and correlations.

Individuals’ Uncertainty about Future Social Security Benefits and Portfolio Choice

PubMed Central

Delavande, Adeline

2013-01-01

Summary Little is known about the degree to which individuals are uncertain about their future Social Security benefits, how this varies within the U.S. population, and whether this uncertainty influences financial decisions related to retirement planning. To illuminate these issues, we present empirical evidence from the Health and Retirement Study Internet Survey and document systematic variation in respondents’ uncertainty about their future Social Security benefits by individual characteristics. We find that respondents with higher levels of uncertainty about future benefits hold a smaller share of their wealth in stocks. PMID:23914049

Quantification of model uncertainty in aerosol optical thickness retrieval from Ozone Monitoring Instrument (OMI) measurements

NASA Astrophysics Data System (ADS)

Määttä, A.; Laine, M.; Tamminen, J.; Veefkind, J. P.

2013-09-01

We study uncertainty quantification in remote sensing of aerosols in the atmosphere with top of the atmosphere reflectance measurements from the nadir-viewing Ozone Monitoring Instrument (OMI). Focus is on the uncertainty in aerosol model selection of pre-calculated aerosol models and on the statistical modelling of the model inadequacies. The aim is to apply statistical methodologies that improve the uncertainty estimates of the aerosol optical thickness (AOT) retrieval by propagating model selection and model error related uncertainties more realistically. We utilise Bayesian model selection and model averaging methods for the model selection problem and use Gaussian processes to model the smooth systematic discrepancies from the modelled to observed reflectance. The systematic model error is learned from an ensemble of operational retrievals. The operational OMI multi-wavelength aerosol retrieval algorithm OMAERO is used for cloud free, over land pixels of the OMI instrument with the additional Bayesian model selection and model discrepancy techniques. The method is demonstrated with four examples with different aerosol properties: weakly absorbing aerosols, forest fires over Greece and Russia, and Sahara dessert dust. The presented statistical methodology is general; it is not restricted to this particular satellite retrieval application.

Offsets in fiber-coupled diode laser hygrometers caused by parasitic absorption effects and their prevention

NASA Astrophysics Data System (ADS)

Buchholz, B.; Ebert, V.

2014-07-01

Large systematic errors in absorption spectrometers (AS) can be caused by ‘parasitic’ optical absorption (parA) outside the measurement region. In particular, calibration-free direct tunable diode laser AS (dTDLAS) can take advantage of an effective parA-compensation to provide correct absolute values. However, parA also negatively affects calibrated AS in calibration frequency and stability. A common strategy to suppress parA in TDLAS systems is to fiber-couple the light source and even the detector. However, this can be a critical approach if the TDL spectrometer is validated/calibrated under laboratory conditions in ambient humidity and used afterwards in much drier and variable conditions, for example in aircrafts. This paper shows that, e.g., ‘hermetically sealed’ butterfly packages, despite fiber coupling, can possess fixed as well as variable parA sections. Two new methods for absolute parA-quantification in dTDLAS were developed, including a novel, fiber-coupled, parA-free I0-detector for permanent parA-monitoring. Their dependences on ambient humidity/pressure and temporal behavior were studied. For the example of a 1.4 µm dTDLAS hygrometer SEALDH-II with a commercial DFB-laser module and an extractive 1.5 m path cell, we quantified the parA-induced signal offsets and their dependence on cell pressure. The conversion of parA-uncertainty into H2O signal uncertainty was studied and an updated uncertainty budget including parA-uncertainty was derived. The studies showed that parA in commercial laser modules can cause substantial, systematic concentration offsets of ≈25 ppmv fixed and ≈100 ppmv variable offsets for one meter absorption path. Applying our parA-quantification techniques these offsets could be compensated by a factor of 20 to an overall offset uncertainty of 4.5 ppmv m-1. Finally, we developed an innovative, integrated, µ-pumped closed-loop air drying unit for the parA minimization and temporal stabilization in airborne laser hygrometers. This compact and light weight dryer eliminates the variable parA by ambient humidity in less than 120 min and is well suited for airborne applications as it fulfils all airborne operation and safety restrictions.

Anatomy of the Higgs fits: A first guide to statistical treatments of the theoretical uncertainties

NASA Astrophysics Data System (ADS)

Fichet, Sylvain; Moreau, Grégory

2016-04-01

The studies of the Higgs boson couplings based on the recent and upcoming LHC data open up a new window on physics beyond the Standard Model. In this paper, we propose a statistical guide to the consistent treatment of the theoretical uncertainties entering the Higgs rate fits. Both the Bayesian and frequentist approaches are systematically analysed in a unified formalism. We present analytical expressions for the marginal likelihoods, useful to implement simultaneously the experimental and theoretical uncertainties. We review the various origins of the theoretical errors (QCD, EFT, PDF, production mode contamination…). All these individual uncertainties are thoroughly combined with the help of moment-based considerations. The theoretical correlations among Higgs detection channels appear to affect the location and size of the best-fit regions in the space of Higgs couplings. We discuss the recurrent question of the shape of the prior distributions for the individual theoretical errors and find that a nearly Gaussian prior arises from the error combinations. We also develop the bias approach, which is an alternative to marginalisation providing more conservative results. The statistical framework to apply the bias principle is introduced and two realisations of the bias are proposed. Finally, depending on the statistical treatment, the Standard Model prediction for the Higgs signal strengths is found to lie within either the 68% or 95% confidence level region obtained from the latest analyses of the 7 and 8 TeV LHC datasets.

INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING

PubMed Central

Kibira, Deogratias; Hatim, Qais; Kumara, Soundar; Shao, Guodong

2017-01-01

Modern manufacturing systems are installed with smart devices such as sensors that monitor system performance and collect data to manage uncertainties in their operations. However, multiple parameters and variables affect system performance, making it impossible for a human to make informed decisions without systematic methodologies and tools. Further, the large volume and variety of streaming data collected is beyond simulation analysis alone. Simulation models are run with well-prepared data. Novel approaches, combining different methods, are needed to use this data for making guided decisions. This paper proposes a methodology whereby parameters that most affect system performance are extracted from the data using data analytics methods. These parameters are used to develop scenarios for simulation inputs; system optimizations are performed on simulation data outputs. A case study of a machine shop demonstrates the proposed methodology. This paper also reviews candidate standards for data collection, simulation, and systems interfaces. PMID:28690363

Reproducibility of Automated Voice Range Profiles, a Systematic Literature Review.

PubMed

Printz, Trine; Rosenberg, Tine; Godballe, Christian; Dyrvig, Anne-Kirstine; Grøntved, Ågot Møller

2018-05-01

Reliable voice range profiles are of great importance when measuring effects and side effects from surgery affecting voice capacity. Automated recording systems are increasingly used, but the reproducibility of results is uncertain. Our objective was to identify and review the existing literature on test-retest accuracy of the automated voice range profile assessment. Systematic review. PubMed, Scopus, Cochrane Library, ComDisDome, Embase, and CINAHL (EBSCO). We conducted a systematic literature search of six databases from 1983 to 2016. The following keywords were used: phonetogram, voice range profile, and acoustic voice analysis. Inclusion criteria were automated recording procedure, healthy voices, and no intervention between test and retest. Test-retest values concerning fundamental frequency and voice intensity were reviewed. Of 483 abstracts, 231 full-text articles were read, resulting in six articles included in the final results. The studies found high reliability, but data are few and heterogeneous. The reviewed articles generally reported high reliability of the voice range profile, and thus clinical usefulness, but uncertainty remains because of low sample sizes and different procedures for selecting, collecting, and analyzing data. More data are needed, and clinical conclusions must be drawn with caution. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Evidence for a mixed mass composition at the 'ankle' in the cosmic-ray spectrum

NASA Astrophysics Data System (ADS)

Aab, A.; Abreu, P.; Aglietta, M.; Ahn, E. J.; Al Samarai, I.; Albuquerque, I. F. M.; Allekotte, I.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Ambrosio, M.; Anastasi, G. A.; Anchordoqui, L.; Andrada, B.; Andringa, S.; Aramo, C.; Arqueros, F.; Arsene, N.; Asorey, H.; Assis, P.; Aublin, J.; Avila, G.; Badescu, A. M.; Balaceanu, A.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellido, J. A.; Berat, C.; Bertaina, M. E.; Biermann, P. L.; Billoir, P.; Biteau, J.; Blaess, S. G.; Blanco, A.; Blazek, J.; Bleve, C.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Borodai, N.; Botti, A. M.; Brack, J.; Brancus, I.; Bretz, T.; Bridgeman, A.; Briechle, F. L.; Buchholz, P.; Bueno, A.; Buitink, S.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Cancio, A.; Canfora, F.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Chavez, A. G.; Chiavassa, A.; Chinellato, J. A.; Chudoba, J.; Clay, R. W.; Colalillo, R.; Coleman, A.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Cronin, J.; Dallier, R.; D'Amico, S.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; de Jong, S. J.; De Mauro, G.; de Mello Neto, J. R. T.; De Mitri, I.; de Oliveira, J.; de Souza, V.; Debatin, J.; del Peral, L.; Deligny, O.; Di Giulio, C.; Di Matteo, A.; Díaz Castro, M. L.; Diogo, F.; Dobrigkeit, C.; D'Olivo, J. C.; Dorofeev, A.; dos Anjos, R. C.; Dova, M. T.; Dundovic, A.; Ebr, J.; Engel, R.; Erdmann, M.; Erfani, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fratu, O.; Freire, M. M.; Fujii, T.; Fuster, A.; García, B.; Garcia-Pinto, D.; Gaté, F.; Gemmeke, H.; Gherghel-Lascu, A.; Ghia, P. L.; Giaccari, U.; Giammarchi, M.; Giller, M.; Głas, D.; Glaser, C.; Glass, H.; Golup, G.; Gómez Berisso, M.; Gómez Vitale, P. F.; González, N.; Gookin, B.; Gordon, J.; Gorgi, A.; Gorham, P.; Gouffon, P.; Grillo, A. F.; Grubb, T. D.; Guarino, F.; Guedes, G. P.; Hampel, M. R.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Hasankiadeh, Q.; Haungs, A.; Hebbeker, T.; Heck, D.; Heimann, P.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Holt, E.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huege, T.; Hulsman, J.; Insolia, A.; Isar, P. G.; Jandt, I.; Jansen, S.; Johnsen, J. A.; Josebachuili, M.; Kääpä, A.; Kambeitz, O.; Kampert, K. H.; Kasper, P.; Katkov, I.; Keilhauer, B.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Krause, R.; Krohm, N.; Kuempel, D.; Kukec Mezek, G.; Kunka, N.; Kuotb Awad, A.; LaHurd, D.; Latronico, L.; Lauscher, M.; Lautridou, P.; Lebrun, P.; Legumina, R.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; Lopes, L.; López, R.; López Casado, A.; Luce, Q.; Lucero, A.; Malacari, M.; Mallamaci, M.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Mariş, I. C.; Marsella, G.; Martello, D.; Martinez, H.; Martínez Bravo, O.; Masías Meza, J. J.; Mathes, H. J.; Mathys, S.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Mayotte, E.; Mazur, P. O.; Medina, C.; Medina-Tanco, G.; Melo, D.; Menshikov, A.; Messina, S.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Miramonti, L.; Mitrica, B.; Mockler, D.; Molina-Bueno, L.; Mollerach, S.; Montanet, F.; Morello, C.; Mostafá, M.; Müller, G.; Muller, M. A.; Müller, S.; Naranjo, I.; Navas, S.; Nellen, L.; Neuser, J.; Nguyen, P. H.; Niculescu-Oglinzanu, M.; Niechciol, M.; Niemietz, L.; Niggemann, T.; Nitz, D.; Nosek, D.; Novotny, V.; Nožka, H.; Núñez, L. A.; Ochilo, L.; Oikonomou, F.; Olinto, A.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Papenbreer, P.; Parente, G.; Parra, A.; Paul, T.; Pech, M.; Pedreira, F.; Pȩkala, J.; Pelayo, R.; Peña-Rodriguez, J.; Pereira, L. A. S.; Perrone, L.; Peters, C.; Petrera, S.; Phuntsok, J.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Porowski, C.; Prado, R. R.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Quinn, S.; Ramos-Pollant, R.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Reinert, D.; Revenu, B.; Ridky, J.; Risse, M.; Ristori, P.; Rizi, V.; Rodrigues de Carvalho, W.; Rodriguez Fernandez, G.; Rodriguez Rojo, J.; Rodríguez-Frías, M. D.; Rogozin, D.; Rosado, J.; Roth, M.; Roulet, E.; Rovero, A. C.; Saffi, S. J.; Saftoiu, A.; Salazar, H.; Saleh, A.; Salesa Greus, F.; Salina, G.; Sanabria Gomez, J. D.; Sánchez, F.; Sanchez-Lucas, P.; Santos, E. M.; Santos, E.; Sarazin, F.; Sarkar, B.; Sarmento, R.; Sarmiento-Cano, C.; Sato, R.; Scarso, C.; Schauer, M.; Scherini, V.; Schieler, H.; Schmidt, D.; Scholten, O.; Schovánek, P.; Schröder, F. G.; Schulz, A.; Schulz, J.; Schumacher, J.; Sciutto, S. J.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sigl, G.; Silli, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sonntag, S.; Sorokin, J.; Squartini, R.; Stanca, D.; Stanič, S.; Stasielak, J.; Strafella, F.; Suarez, F.; Suarez Durán, M.; Sudholz, T.; Suomijärvi, T.; Supanitsky, A. D.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Taborda, O. A.; Tapia, A.; Tepe, A.; Theodoro, V. M.; Timmermans, C.; Todero Peixoto, C. J.; Tomankova, L.; Tomé, B.; Tonachini, A.; Torralba Elipe, G.; Torres Machado, D.; Torri, M.; Travnicek, P.; Trini, M.; Ulrich, R.; Unger, M.; Urban, M.; Valbuena-Delgado, A.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van Bodegom, P.; van den Berg, A. M.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Varner, G.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Villaseñor, L.; Vorobiov, S.; Wahlberg, H.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weindl, A.; Wiencke, L.; Wilczyński, H.; Winchen, T.; Wittkowski, D.; Wundheiler, B.; Wykes, S.; Yang, L.; Yelos, D.; Younk, P.; Yushkov, A.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zepeda, A.; Zimmermann, B.; Ziolkowski, M.; Zong, Z.; Zuccarello, F.; Pierre Auger Collaboration

2016-11-01

We report a first measurement for ultrahigh energy cosmic rays of the correlation between the depth of shower maximum and the signal in the water Cherenkov stations of air-showers registered simultaneously by the fluorescence and the surface detectors of the Pierre Auger Observatory. Such a correlation measurement is a unique feature of a hybrid air-shower observatory with sensitivity to both the electromagnetic and muonic components. It allows an accurate determination of the spread of primary masses in the cosmic-ray flux. Up till now, constraints on the spread of primary masses have been dominated by systematic uncertainties. The present correlation measurement is not affected by systematics in the measurement of the depth of shower maximum or the signal in the water Cherenkov stations. The analysis relies on general characteristics of air showers and is thus robust also with respect to uncertainties in hadronic event generators. The observed correlation in the energy range around the 'ankle' at lg ⁡ (E /eV) = 18.5- 19.0 differs significantly from expectations for pure primary cosmic-ray compositions. A light composition made up of proton and helium only is equally inconsistent with observations. The data are explained well by a mixed composition including nuclei with mass A > 4. Scenarios such as the proton dip model, with almost pure compositions, are thus disfavored as the sole explanation of the ultrahigh-energy cosmic-ray flux at Earth.

Evidence for a mixed mass composition at the ‘ankle’ in the cosmic-ray spectrum

DOE PAGES

Aab, Alexander

2016-09-28

Here, we report a first measurement for ultra-high energy cosmic rays of the correlation between the depth of shower maximum and the signal in the water Cherenkov stations of air-showers registered simultaneously by the fluorescence and the surface detectors of the Pierre Auger Observatory. Such a correlation measurement is a unique feature of a hybrid air-shower observatory with sensitivity to both the electromagnetic and muonic components. It allows an accurate determination of the spread of primary masses in the cosmic-ray flux. Up till now, constraints on the spread of primary masses have been dominated by systematic uncertainties. The present correlation measurement is not affected by systematics in the measurement of the depth of shower maximum or the signal in the water Cherenkov stations. The analysis relies on general characteristics of air showers and is thus robust also with respect to uncertainties in hadronic event generators. The observed correlation in the energy range around the `ankle' atmore » $$\\lg(E/{\\rm eV})=18.5-19.0$$ differs significantly from expectations for pure primary cosmic-ray compositions. A light composition made up of proton and helium only is equally inconsistent with observations. The data are explained well by a mixed composition including nuclei with mass $A > 4$. Scenarios such as the proton dip model, with almost pure compositions, are thus disfavoured as the sole explanation of the ultrahigh-energy cosmic-ray flux at Earth.« less

Subaru Telescope limits on cosmological variations in the fine-structure constant

NASA Astrophysics Data System (ADS)

Murphy, Michael T.; Cooksey, Kathy L.

2017-11-01

Previous, large samples of quasar absorption spectra have indicated some evidence for relative variations in the fine-structure constant (Δα/α) across the sky. However, they were likely affected by long-range distortions of the wavelength calibration, so it is important to establish a statistical sample of more reliable results from multiple telescopes. Here we triple the sample of Δα/α measurements from the Subaru Telescope which have been `supercalibrated' to correct for long-range distortions. A blinded analysis of the metallic ions in six intervening absorption systems in two Subaru quasar spectra provides no evidence for α variation, with a weighted mean of Δα/α = 3.0 ± 2.8stat ± 2.0sys parts per million (1σ statistical and systematic uncertainties). The main remaining systematic effects are uncertainties in the long-range distortion corrections, absorption profile models, and errors from redispersing multiple quasar exposures on to a common wavelength grid. The results also assume that terrestrial isotopic abundances prevail in the absorbers; assuming only the dominant terrestrial isotope is present significantly lowers Δα/α, though it is still consistent with zero. Given the location of the two quasars on the sky, our results do not support the evidence for spatial α variation, especially when combined with the 21 other recent measurements which were corrected for, or resistant to, long-range distortions. Our spectra and absorption profile fits are publicly available.

Uncertainties and Systematic Effects on the estimate of stellar masses in high z galaxies

NASA Astrophysics Data System (ADS)

Salimbeni, S.; Fontana, A.; Giallongo, E.; Grazian, A.; Menci, N.; Pentericci, L.; Santini, P.

2009-05-01

We discuss the uncertainties and the systematic effects that exist in the estimates of the stellar masses of high redshift galaxies, using broad band photometry, and how they affect the deduced galaxy stellar mass function. We use at this purpose the latest version of the GOODS-MUSIC catalog. In particular, we discuss the impact of different synthetic models, of the assumed initial mass function and of the selection band. Using Chariot & Bruzual 2007 and Maraston 2005 models we find masses lower than those obtained from Bruzual & Chariot 2003 models. In addition, we find a slight trend as a function of the mass itself comparing these two mass determinations with that from Bruzual & Chariot 2003 models. As consequence, the derived galaxy stellar mass functions show diverse shapes, and their slope depends on the assumed models. Despite these differences, the overall results and scenario is observed in all these cases. The masses obtained with the assumption of the Chabrier initial mass function are in average 0.24 dex lower than those from the Salpeter assumption, at all redshifts, causing a shift of galaxy stellar mass function of the same amount. Finally, using a 4.5 μm-selected sample instead of a Ks-selected one, we add a new population of highly absorbed, dusty galaxies at z~=2-3 of relatively low masses, yielding stronger constraints on the slope of the galaxy stellar mass function at lower masses.

Systematic in J-PARC/Hyper-K

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

Minamino, Akihiro

The Hyper-Kamiokande (Hyper-K) detector is a next generation underground water Chrenkov detector. The J-PARC to Hyper-K experiment has good potential for precision measurements of neutrino oscillation parameters and discovery reach for CP violation in the lepton sector. With a total exposure of 10 years to a neutrino beam produced by the 750 kW J-PARC proton synchrotron, it is expected that the CP phase δ can be determined to better than 18 degree for all possible values of δ if sin{sup 2} 2θ{sub 13} > 0.03 and the mass hierarchy is known. Control of systematic uncertainties is critical to make maximummore » use of the Hyper-K potential. Based on learning from T2K experience, a strategy to reduce systematic uncertainties in J-PARC/Hyper-K are developed.« less

Space based inverse modeling of anthropogenic and natural emissions of nitrogen oxides over China: seasonal and interannual variability

NASA Astrophysics Data System (ADS)

Lin, J.-T.

2012-04-01

Nitrogen oxides (NOx ≡ NO + NO2) are important atmospheric constituents affecting the tropospheric chemistry and climate. They are emitted both from anthropogenic and from natural (soil, lightning, biomass burning, etc.) sources, and China has become a major region of increasing importance for anthropogenic sources. In a series of studies, satellite remote sensing for the vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) is used to estimate anthropogenic and natural emissions of NOx over China. Focus is set on variations of emissions over a variety of time scales in response to the economic development of China, from the general growth in recent years to the economic downturn during late 2008 - mid 2009 to the holiday associated with the Chinese New Year. An attempt is made to reduce the effect of potential systematic errors in satellite retrievals by coupling data from multiple satellite instruments flying over China at different time of day. For 2006, anthropogenic emissions are separated from lightning and soil sources over East China by exploiting their different seasonality. For the first time, a systematic evaluation is conducted to quantify uncertainties in various aspects of model meteorology and chemistry affecting emission inversion for China and implications for simulations of other air pollution (e.g., near-surface ozone).

Task uncertainty and communication during nursing shift handovers.

PubMed

Mayor, Eric; Bangerter, Adrian; Aribot, Myriam

2012-09-01

We explore variations in handover duration and communication in nursing units. We hypothesize that duration per patient is higher in units facing high task uncertainty. We expect both topics and functions of communication to vary depending on task uncertainty. Handovers are changing in modern healthcare organizations, where standardized procedures are increasingly advocated for efficiency and reliability reasons. However, redesign of handover should take environmental contingencies of different clinical unit types into account. An important contingency in institutions is task uncertainty, which may affect how communicative routines like handover are accomplished. Nurse unit managers of 80 care units in 18 hospitals were interviewed in 2008 about topics and functions of handover communication and duration in their unit. Interviews were content-analysed. Clinical units were classified into a theory-based typology (unit type) that gradually increases on task uncertainty. Quantitative analyses were performed. Unit type affected resource allocation. Unit types facing higher uncertainty had higher handover duration per patient. As expected, unit type also affected communication content. Clinical units facing higher uncertainty discussed fewer topics, discussing treatment and care and organization of work less frequently. Finally, unit type affected functions of handover: sharing emotions was less often mentioned in unit types facing higher uncertainty. Task uncertainty and its relationship with functions and topics of handover should be taken into account during the design of handover procedures. © 2011 Blackwell Publishing Ltd.

Summary of long-baseline systematics session at CETUP*2014

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

Cherdack, Daniel; Worcester, Elizabeth

2015-10-15

A session studying systematics in long-baseline neutrino oscillation physics was held July 14-18, 2014 as part of CETUP* 2014. Systematic effects from flux normalization and modeling, modeling of cross sections and nuclear interactions, and far detector effects were addressed. Experts presented the capabilities of existing and planned tools. A program of study to determine estimates of and requirements for the size of these effects was designed. This document summarizes the results of the CETUP* systematics workshop and the current status of systematic uncertainty studies in long-baseline neutrino oscillation measurements.

Transportable Optical Lattice Clock with 7×10^{-17} Uncertainty.

PubMed

Koller, S B; Grotti, J; Vogt, St; Al-Masoudi, A; Dörscher, S; Häfner, S; Sterr, U; Lisdat, Ch

2017-02-17

We present a transportable optical clock (TOC) with ^{87}Sr. Its complete characterization against a stationary lattice clock resulted in a systematic uncertainty of 7.4×10^{-17}, which is currently limited by the statistics of the determination of the residual lattice light shift, and an instability of 1.3×10^{-15}/sqrt[τ] with an averaging time τ in seconds. Measurements confirm that the systematic uncertainty can be reduced to below the design goal of 1×10^{-17}. To our knowledge, these are the best uncertainties and instabilities reported for any transportable clock to date. For autonomous operation, the TOC has been installed in an air-conditioned car trailer. It is suitable for chronometric leveling with submeter resolution as well as for intercontinental cross-linking of optical clocks, which is essential for a redefinition of the International System of Units (SI) second. In addition, the TOC will be used for high precision experiments for fundamental science that are commonly tied to precise frequency measurements and its development is an important step to space-borne optical clocks.

Transportable Optical Lattice Clock with 7 ×10-17 Uncertainty

NASA Astrophysics Data System (ADS)

Koller, S. B.; Grotti, J.; Vogt, St.; Al-Masoudi, A.; Dörscher, S.; Häfner, S.; Sterr, U.; Lisdat, Ch.

2017-02-01

We present a transportable optical clock (TOC) with Sr 87 . Its complete characterization against a stationary lattice clock resulted in a systematic uncertainty of 7.4 ×10-17, which is currently limited by the statistics of the determination of the residual lattice light shift, and an instability of 1.3 ×10-15/√{τ } with an averaging time τ in seconds. Measurements confirm that the systematic uncertainty can be reduced to below the design goal of 1 ×10-17. To our knowledge, these are the best uncertainties and instabilities reported for any transportable clock to date. For autonomous operation, the TOC has been installed in an air-conditioned car trailer. It is suitable for chronometric leveling with submeter resolution as well as for intercontinental cross-linking of optical clocks, which is essential for a redefinition of the International System of Units (SI) second. In addition, the TOC will be used for high precision experiments for fundamental science that are commonly tied to precise frequency measurements and its development is an important step to space-borne optical clocks.

Calibration of the Microwave Limb Sounder on the Upper Atmosphere Research Satellite

NASA Technical Reports Server (NTRS)

Jarnot, R. F.; Cofield, R. E.; Waters, J. W.; Flower, D. A.; Peckham, G. E.

1996-01-01

The Microwave Limb Sounder (MLS) is a three-radiometer, passive, limb emission instrument onboard the Upper Atmosphere Research Satellite (UARS). Radiometric, spectral and field-of-view calibrations of the MLS instrument are described in this paper. In-orbit noise performance, gain stability, spectral baseline and dynamic range are described, as well as use of in-flight data for validation and refinement of prelaunch calibrations. Estimated systematic scaling uncertainties (3 sigma) on calibrated limb radiances from prelaunch calibrations are 2.6% in bands 1 through 3, 3.4% in band 4, and 6% in band 5. The observed systematic errors in band 6 are about 15%, consistent with prelaunch calibration uncertainties. Random uncertainties on individual limb radiance measurements are very close to the levels predicted from measured radiometer noise temperature, with negligible contribution from noise and drifts on the regular in-flight gain calibration measurements.

Phase shifts in I = 2 ππ-scattering from two lattice approaches

NASA Astrophysics Data System (ADS)

Kurth, T.; Ishii, N.; Doi, T.; Aoki, S.; Hatsuda, T.

2013-12-01

We present a lattice QCD study of the phase shift of I = 2 ππ scattering on the basis of two different approaches: the standard finite volume approach by Lüscher and the recently introduced HAL QCD potential method. Quenched QCD simulations are performed on lattices with extents N s = 16 , 24 , 32 , 48 and N t = 128 as well as lattice spacing a ~ 0 .115 fm and a pion mass of m π ~ 940 MeV. The phase shift and the scattering length are calculated in these two methods. In the potential method, the error is dominated by the systematic uncertainty associated with the violation of rotational symmetry due to finite lattice spacing. In Lüscher's approach, such systematic uncertainty is difficult to be evaluated and thus is not included in this work. A systematic uncertainty attributed to the quenched approximation, however, is not evaluated in both methods. In case of the potential method, the phase shift can be calculated for arbitrary energies below the inelastic threshold. The energy dependence of the phase shift is also obtained from Lüscher's method using different volumes and/or nonrest-frame extension of it. The results are found to agree well with the potential method.

The Significance of an Excess in a Counting Experiment: Assessing the Impact of Systematic Uncertainties and the Case with a Gaussian Background

NASA Astrophysics Data System (ADS)

Vianello, Giacomo

2018-05-01

Several experiments in high-energy physics and astrophysics can be treated as on/off measurements, where an observation potentially containing a new source or effect (“on” measurement) is contrasted with a background-only observation free of the effect (“off” measurement). In counting experiments, the significance of the new source or effect can be estimated with a widely used formula from Li & Ma, which assumes that both measurements are Poisson random variables. In this paper we study three other cases: (i) the ideal case where the background measurement has no uncertainty, which can be used to study the maximum sensitivity that an instrument can achieve, (ii) the case where the background estimate b in the off measurement has an additional systematic uncertainty, and (iii) the case where b is a Gaussian random variable instead of a Poisson random variable. The latter case applies when b comes from a model fitted on archival or ancillary data, or from the interpolation of a function fitted on data surrounding the candidate new source/effect. Practitioners typically use a formula that is only valid when b is large and when its uncertainty is very small, while we derive a general formula that can be applied in all regimes. We also develop simple methods that can be used to assess how much an estimate of significance is sensitive to systematic uncertainties on the efficiency or on the background. Examples of applications include the detection of short gamma-ray bursts and of new X-ray or γ-ray sources. All the techniques presented in this paper are made available in a Python code that is ready to use.

Alternate methods for FAAT S-curve generation

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

Kaufman, A.M.

The FAAT (Foreign Asset Assessment Team) assessment methodology attempts to derive a probability of effect as a function of incident field strength. The probability of effect is the likelihood that the stress put on a system exceeds its strength. In the FAAT methodology, both the stress and strength are random variables whose statistical properties are estimated by experts. Each random variable has two components of uncertainty: systematic and random. The systematic uncertainty drives the confidence bounds in the FAAT assessment. Its variance can be reduced by improved information. The variance of the random uncertainty is not reducible. The FAAT methodologymore » uses an assessment code called ARES to generate probability of effect curves (S-curves) at various confidence levels. ARES assumes log normal distributions for all random variables. The S-curves themselves are log normal cumulants associated with the random portion of the uncertainty. The placement of the S-curves depends on confidence bounds. The systematic uncertainty in both stress and strength is usually described by a mode and an upper and lower variance. Such a description is not consistent with the log normal assumption of ARES and an unsatisfactory work around solution is used to obtain the required placement of the S-curves at each confidence level. We have looked into this situation and have found that significant errors are introduced by this work around. These errors are at least several dB-W/cm{sup 2} at all confidence levels, but they are especially bad in the estimate of the median. In this paper, we suggest two alternate solutions for the placement of S-curves. To compare these calculational methods, we have tabulated the common combinations of upper and lower variances and generated the relevant S-curves offsets from the mode difference of stress and strength.« less

Quantifying Mixed Uncertainties in Cyber Attacker Payoffs

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

Chatterjee, Samrat; Halappanavar, Mahantesh; Tipireddy, Ramakrishna

Representation and propagation of uncertainty in cyber attacker payoffs is a key aspect of security games. Past research has primarily focused on representing the defender’s beliefs about attacker payoffs as point utility estimates. More recently, within the physical security domain, attacker payoff uncertainties have been represented as Uniform and Gaussian probability distributions, and intervals. Within cyber-settings, continuous probability distributions may still be appropriate for addressing statistical (aleatory) uncertainties where the defender may assume that the attacker’s payoffs differ over time. However, systematic (epistemic) uncertainties may exist, where the defender may not have sufficient knowledge or there is insufficient information aboutmore » the attacker’s payoff generation mechanism. Such epistemic uncertainties are more suitably represented as probability boxes with intervals. In this study, we explore the mathematical treatment of such mixed payoff uncertainties.« less

Solute Concentration at a Pumping Well in Non-Gaussian Random Aquifers under Time-Varying Operational Schedules

NASA Astrophysics Data System (ADS)

Libera, A.; de Barros, F.; Riva, M.; Guadagnini, A.

2016-12-01

Managing contaminated groundwater systems is an arduous task for multiple reasons. First, subsurface hydraulic properties are heterogeneous and the high costs associated with site characterization leads to data scarcity (therefore, model predictions are uncertain). Second, it is common for water agencies to schedule groundwater extraction through a temporal sequence of pumping rates to maximize the benefits to anthropogenic activities and minimize the environmental footprint of the withdrawal operations. The temporal variability in pumping rates and aquifer heterogeneity affect dilution rates of contaminant plumes and chemical concentration breakthrough curves (BTCs) at the well. While contaminant transport under steady-state pumping is widely studied, the manner in which a given time-varying pumping schedule affects contaminant plume behavior is tackled only marginally. At the same time, most studies focus on the impact of Gaussian random hydraulic conductivity (K) fields on transport. Here, we systematically analyze the significance of the random space function (RSF) model characterizing K in the presence of distinct pumping operations on the uncertainty of the concentration BTC at the operating well. We juxtapose Monte Carlo based numerical results associated with two models: (a) a recently proposed Generalized Sub-Gaussian model which allows capturing non-Gaussian statistical scaling features of RSFs such as hydraulic conductivity, and (b) the commonly used Gaussian field approximation. Our novel results include an appraisal of the coupled effect of (a) the model employed to depict the random spatial variability of K and (b) transient flow regime, as induced by a temporally varying pumping schedule, on the concentration BTC at the operating well. We systematically quantify the sensitivity of the uncertainty in the contaminant BTC to the RSF model adopted for K (non-Gaussian or Gaussian) in the presence of diverse well pumping schedules. Results contribute to determine conditions under which any of these two key factors prevails on the other.

Results and Error Estimates from GRACE Forward Modeling over Greenland, Canada, and Alaska

NASA Astrophysics Data System (ADS)

Bonin, J. A.; Chambers, D. P.

2012-12-01

Forward modeling using a weighted least squares technique allows GRACE information to be projected onto a pre-determined collection of local basins. This decreases the impact of spatial leakage, allowing estimates of mass change to be better localized. The technique is especially valuable where models of current-day mass change are poor, such as over Greenland and Antarctica. However, the accuracy of the forward model technique has not been determined, nor is it known how the distribution of the local basins affects the results. We use a "truth" model composed of hydrology and ice-melt slopes as an example case, to estimate the uncertainties of this forward modeling method and expose those design parameters which may result in an incorrect high-resolution mass distribution. We then apply these optimal parameters in a forward model estimate created from RL05 GRACE data. We compare the resulting mass slopes with the expected systematic errors from the simulation, as well as GIA and basic trend-fitting uncertainties. We also consider whether specific regions (such as Ellesmere Island and Baffin Island) can be estimated reliably using our optimal basin layout.

A confirmation of the general relativistic prediction of the Lense-Thirring effect.

PubMed

Ciufolini, I; Pavlis, E C

2004-10-21

An important early prediction of Einstein's general relativity was the advance of the perihelion of Mercury's orbit, whose measurement provided one of the classical tests of Einstein's theory. The advance of the orbital point-of-closest-approach also applies to a binary pulsar system and to an Earth-orbiting satellite. General relativity also predicts that the rotation of a body like Earth will drag the local inertial frames of reference around it, which will affect the orbit of a satellite. This Lense-Thirring effect has hitherto not been detected with high accuracy, but its detection with an error of about 1 per cent is the main goal of Gravity Probe B--an ongoing space mission using orbiting gyroscopes. Here we report a measurement of the Lense-Thirring effect on two Earth satellites: it is 99 +/- 5 per cent of the value predicted by general relativity; the uncertainty of this measurement includes all known random and systematic errors, but we allow for a total +/- 10 per cent uncertainty to include underestimated and unknown sources of error.

Spectroscopy Made Easy: Evolution

NASA Astrophysics Data System (ADS)

Piskunov, Nikolai; Valenti, Jeff A.

2017-01-01

Context. The Spectroscopy Made Easy (SME) package has become a popular tool for analyzing stellar spectra, often in connection with large surveys or exoplanet research. SME has evolved significantly since it was first described in 1996, but many of the original caveats and potholes still haunt users. The main drivers for this paper are complexity of the modeling task, the large user community, and the massive effort that has gone into SME. Aims: We do not intend to give a comprehensive introduction to stellar atmospheres, but will describe changes to key components of SME: the equation of state, opacities, and radiative transfer. We will describe the analysis and fitting procedure and investigate various error sources that affect inferred parameters. Methods: We review the current status of SME, emphasizing new algorithms and methods. We describe some best practices for using the package, based on lessons learned over two decades of SME usage. We present a new way to assess uncertainties in derived stellar parameters. Results: Improvements made to SME, better line data, and new model atmospheres yield more realistic stellar spectra, but in many cases systematic errors still dominate over measurement uncertainty. Future enhancements are outlined.

Bayesian Estimation of Thermonuclear Reaction Rates for Deuterium+Deuterium Reactions

NASA Astrophysics Data System (ADS)

Gómez Iñesta, Á.; Iliadis, C.; Coc, A.

2017-11-01

The study of d+d reactions is of major interest since their reaction rates affect the predicted abundances of D, 3He, and 7Li. In particular, recent measurements of primordial D/H ratios call for reduced uncertainties in the theoretical abundances predicted by Big Bang nucleosynthesis (BBN). Different authors have studied reactions involved in BBN by incorporating new experimental data and a careful treatment of systematic and probabilistic uncertainties. To analyze the experimental data, Coc et al. used results of ab initio models for the theoretical calculation of the energy dependence of S-factors in conjunction with traditional statistical methods based on χ 2 minimization. Bayesian methods have now spread to many scientific fields and provide numerous advantages in data analysis. Astrophysical S-factors and reaction rates using Bayesian statistics were calculated by Iliadis et al. Here we present a similar analysis for two d+d reactions, d(d, n)3He and d(d, p)3H, that has been translated into a total decrease of the predicted D/H value by 0.16%.

Jet energy measurement with the ATLAS detector in proton-proton collisions at √{s}=7 TeV

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.; Aktas, 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.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; 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.; Asner, D.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Atoian, G.; Aubert, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Austin, N.; Avolio, G.; 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.; 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.; Beck, G. A.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Begel, M.; Behar Harpaz, S.; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Ben Ami, S.; Benary, O.; Benchekroun, D.; Benchouk, C.; Bendel, M.; Benekos, N.; Benhammou, Y.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Beretta, M.; 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.; Bierwagen, K.; 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.; Bondioli, M.; 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.; 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.; Caballero, J.; 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.; Chavez Barajas, C. A.; 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.; Citterio, 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.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; 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.; Cranshaw, J.; Crescioli, F.; Cristinziani, M.; Crosetti, G.; Crupi, R.; Crépé-Renaudin, S.; Cuciuc, C.-M.; Cuenca Almenar, C.; Cuhadar Donszelmann, T.; 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.; Daly, C. H.; 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-Ishmukhametova, 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 Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; Dean, S.; Debbe, R.; Dedovich, D. V.; Degenhardt, J.; Dehchar, 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.; Deng, W.; 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.; Duran Yildiz, H.; Duxfield, R.; Dwuznik, M.; Dydak, F.; 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.; 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.; Fokitis, M.; Fonseca Martin, T.; Fopma, J.; 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.; Freestone, J.; French, S. T.; Friedrich, F.; 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.; 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.; García Navarro, J. E.; Gardner, R. W.; Garelli, N.; Garitaonandia, H.; Garonne, V.; Garvey, J.; Gatti, C.; Gaudio, G.; Gaumer, O.; Gaur, B.; Gauthier, L.; Gauzzi, P.; 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.; 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.; Giordani, M. P.; 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.; Golling, T.; Golovnia, S. N.; Gomes, A.; Gomez Fajardo, L. S.; Gonçalo, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, L.; Gonidec, A.; Gonzalez, S.; González de la Hoz, S.; Gonzalez Silva, M. L.; 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.; Gough Eschrich, I.; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Grabowska-Bold, I.; 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.; Green, B.; Greenfield, D.; Greenshaw, T.; Greenwood, Z. D.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grigalashvili, N.; Grillo, A. A.; Grinstein, S.; Grishkevich, Y. V.; Grivaz, J.-F.; Groh, M.; Gross, E.; Grosse-Knetter, J.; Groth-Jensen, J.; Grybel, K.; Guarino, V. J.; Guest, D.; Guicheney, C.; Guida, A.; 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.; Hayashi, 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.; Hemperek, T.; Henderson, R. C. W.; Henke, M.; Henrichs, A.; Henriques Correia, A. M.; 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.; 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. E.; Huhtinen, M.; Hurst, P.; Hurwitz, M.; Husemann, U.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibbotson, M.; Ibragimov, I.; Ichimiya, R.; Iconomidou-Fayard, L.; Idarraga, J.; Iengo, P.; Igonkina, O.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Imbault, D.; Imori, M.; Ince, T.; Inigo-Golfin, J.; Ioannou, P.; Iodice, M.; Irles Quiles, A.; Ishikawa, A.; Ishino, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ivashin, A. V.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jackson, B.; Jackson, J. N.; Jackson, P.; Jaekel, M. R.; Jain, V.; Jakobs, K.; Jakobsen, S.; Jakubek, J.; Jana, D. K.; Jankowski, E.; Jansen, E.; Jantsch, A.; Janus, M.; Jarlskog, G.; Jeanty, L.; Jelen, K.; Jen-La Plante, I.; Jenni, P.; Jeremie, A.; Jež, P.; Jézéquel, S.; Jha, M. K.; Ji, H.; Ji, W.; Jia, J.; Jiang, Y.; Jimenez Belenguer, M.; Jin, G.; Jin, S.; Jinnouchi, O.; Joergensen, M. D.; Joffe, D.; Johansen, L. G.; Johansen, M.; Johansson, K. E.; Johansson, P.; Johnert, S.; Johns, K. A.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, T. W.; Jones, T. J.; Jonsson, O.; Joram, C.; Jorge, P. M.; Joseph, J.; Jovin, T.; Ju, X.; Jung, C. A.; Juranek, V.; Jussel, P.; Juste Rozas, A.; Kabachenko, V. V.; Kabana, S.; Kaci, M.; Kaczmarska, A.; Kadlecik, P.; Kado, M.; Kagan, H.; Kagan, M.; Kaiser, S.; Kajomovitz, E.; Kalinin, S.; Kalinovskaya, L. V.; Kama, S.; Kanaya, N.; Kaneda, M.; Kanno, T.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kapliy, A.; Kaplon, J.; Kar, D.; Karagounis, M.; Karagoz, M.; Karnevskiy, M.; Karr, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kashif, L.; Kasmi, A.; Kass, R. D.; Kastanas, A.; Kataoka, M.; Kataoka, Y.; Katsoufis, E.; Katzy, J.; Kaushik, V.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kayl, M. S.; Kazanin, V. A.; Kazarinov, M. Y.; Keates, J. R.; Keeler, R.; Kehoe, R.; Keil, M.; Kekelidze, G. D.; Kelly, M.; Kennedy, J.; Kenney, C. J.; Kenyon, M.; Kepka, O.; Kerschen, N.; Kerševan, B. P.; Kersten, S.; Kessoku, K.; Ketterer, C.; Keung, J.; Khakzad, M.; Khalil-zada, F.; Khandanyan, H.; Khanov, A.; Kharchenko, D.; Khodinov, A.; Kholodenko, A. G.; Khomich, A.; Khoo, T. J.; Khoriauli, G.; Khoroshilov, A.; Khovanskiy, N.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kim, H.; Kim, M. S.; Kim, P. C.; Kim, S. H.; Kimura, N.; Kind, O.; King, B. T.; King, M.; King, R. S. B.; Kirk, J.; Kirsch, L. E.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kittelmann, T.; Kiver, A. M.; Kladiva, E.; Klaiber-Lodewigs, J.; Klein, M.; Klein, U.; Kleinknecht, K.; Klemetti, M.; Klier, A.; Klimentov, A.; Klingenberg, R.; Klinkby, E. B.; Klioutchnikova, T.; Klok, P. F.; Klous, S.; Kluge, E.-E.; Kluge, T.; Kluit, P.; Kluth, S.; Knecht, N. S.; Kneringer, E.; Knobloch, J.; Knoops, E. B. F. G.; Knue, A.; Ko, B. R.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kocnar, A.; Kodys, P.; Köneke, K.; König, A. C.; Koenig, S.; Köpke, L.; Koetsveld, F.; Koevesarki, P.; Koffas, T.; Koffeman, E.; Kohn, F.; Kohout, Z.; Kohriki, T.; Koi, T.; Kokott, T.; Kolachev, G. M.; Kolanoski, H.; Kolesnikov, V.; Koletsou, I.; Koll, J.; Kollar, D.; Kollefrath, M.; Kolya, S. D.; Komar, A. A.; Komori, Y.; Kondo, T.; Kono, T.; Kononov, A. I.; Konoplich, R.; Konstantinidis, N.; Kootz, A.; Koperny, S.; Kopikov, S. V.; Korcyl, K.; Kordas, K.; Koreshev, V.; Korn, A.; Korol, A.; Korolkov, I.; Korolkova, E. V.; Korotkov, V. A.; Kortner, O.; Kortner, S.; Kostyukhin, V. V.; Kotamäki, M. J.; Kotov, S.; Kotov, V. M.; Kotwal, A.; Kourkoumelis, C.; Kouskoura, V.; Koutsman, A.; Kowalewski, R.; Kowalski, T. Z.; Kozanecki, W.; Kozhin, A. S.; Kral, V.; Kramarenko, V. A.; Kramberger, G.; Krasny, M. W.; Krasznahorkay, A.; Kraus, J.; Kraus, J. K.; Kreisel, A.; Krejci, F.; Kretzschmar, J.; Krieger, N.; Krieger, P.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Kruker, T.; Krumshteyn, Z. V.; Kruth, A.; Kubota, T.; Kuehn, S.; Kugel, A.; Kuhl, T.; Kuhn, D.; Kukhtin, V.; Kulchitsky, Y.; Kuleshov, S.; Kummer, C.; Kuna, M.; Kundu, N.; Kunkle, J.; Kupco, A.; Kurashige, H.; Kurata, M.; Kurochkin, Y. A.; Kus, V.; Kuze, M.; Kuzhir, P.; Kvita, J.; Kwee, R.; La Rosa, A.; La Rotonda, L.; Labarga, L.; Labbe, J.; Lablak, S.; Lacasta, C.; Lacava, F.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Laisne, E.; Lamanna, M.; Lampen, C. L.; Lampl, W.; Lancon, E.; Landgraf, U.; Landon, M. P. J.; Landsman, H.; Lane, J. L.; Lange, C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Larionov, A. V.; Larner, A.; Lasseur, C.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Laycock, P.; Lazarev, A. B.; Le Dortz, O.; Le Guirriec, E.; Le Maner, C.; Le Menedeu, E.; Lebel, C.; LeCompte, T.; Ledroit-Guillon, F.; Lee, H.; Lee, J. S. H.; Lee, S. C.; Lee, L.; Lefebvre, M.; Legendre, M.; Leger, A.; LeGeyt, B. C.; Legger, F.; Leggett, C.; Lehmacher, M.; Lehmann Miotto, G.; Lei, X.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Leltchouk, M.; Lemmer, B.; Lendermann, V.; Leney, K. J. C.; Lenz, T.; Lenzen, G.; Lenzi, B.; Leonhardt, K.; Leontsinis, S.; Leroy, C.; Lessard, J.-R.; Lesser, J.; Lester, C. G.; Leung Fook Cheong, A.; Levêque, J.; Levin, D.; Levinson, L. J.; Levitski, M. S.; Lewandowska, M.; Lewis, A.; Lewis, G. H.; Leyko, A. M.; Leyton, M.; Li, B.; Li, H.; Li, S.; Li, X.; Liang, Z.; Liang, Z.; Liao, H.; Liberti, B.; Lichard, P.; Lichtnecker, M.; Lie, K.; Liebig, W.; Lifshitz, R.; Lilley, J. N.; Limbach, C.; Limosani, A.; Limper, M.; Lin, S. C.; Linde, F.; Linnemann, J. T.; Lipeles, E.; Lipinsky, L.; Lipniacka, A.; Liss, T. M.; Lissauer, D.; Lister, A.; Litke, A. M.; Liu, C.; Liu, D.; Liu, H.; Liu, J. B.; Liu, M.; Liu, S.; Liu, Y.; Livan, M.; Livermore, S. S. A.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lobodzinska, E.; Loch, P.; Lockman, W. S.; Loddenkoetter, T.; Loebinger, F. K.; Loginov, A.; Loh, C. W.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Loken, J.; Lombardo, V. P.; Long, R. E.; Lopes, L.; Lopez Mateos, D.; Losada, M.; Loscutoff, P.; Lo Sterzo, F.; Losty, M. J.; Lou, X.; Lounis, A.; Loureiro, K. F.; Love, J.; Love, P. A.; Lowe, A. J.; Lu, F.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Ludwig, A.; Ludwig, D.; Ludwig, I.; Ludwig, J.; Luehring, F.; Luijckx, G.; Lumb, D.; Luminari, L.; Lund, E.; Lund-Jensen, B.; Lundberg, B.; Lundberg, J.; Lundquist, J.; Lungwitz, M.; Lupi, A.; Lutz, G.; Lynn, D.; Lys, J.; Lytken, E.; Ma, H.; Ma, L. L.; Macana Goia, J. A.; Maccarrone, G.; Macchiolo, A.; Maček, B.; Machado Miguens, J.; Mackeprang, R.; Madaras, R. J.; Mader, W. F.; Maenner, R.; Maeno, T.; Mättig, P.; Mättig, S.; Magnoni, L.; Magradze, E.; Mahalalel, Y.; Mahboubi, K.; Mahout, G.; Maiani, C.; Maidantchik, C.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Mal, P.; Malaescu, B.; Malecki, Pa.; Malecki, P.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyshev, V.; Malyukov, S.; Mameghani, R.; Mamuzic, J.; Manabe, A.; Mandelli, L.; Mandić, I.; Mandrysch, R.; Maneira, J.; Mangeard, P. S.; Manjavidze, I. D.; Mann, A.; Manning, P. M.; Manousakis-Katsikakis, A.; Mansoulie, B.; Manz, A.; Mapelli, A.; Mapelli, L.; March, L.; Marchand, J. F.; Marchese, F.; Marchiori, G.; Marcisovsky, M.; Marin, A.; Marino, C. P.; Marroquim, F.; Marshall, R.; Marshall, Z.; Martens, F. K.; Marti-Garcia, S.; Martin, A. J.; Martin, B.; Martin, B.; Martin, F. F.; Martin, J. P.; Martin, Ph.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martin-Haugh, S.; Martinez, M.; Martinez Outschoorn, V.; Martyniuk, A. C.; Marx, M.; Marzano, F.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massaro, G.; Massol, N.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mathes, M.; Matricon, P.; Matsumoto, H.; Matsunaga, H.; Matsushita, T.; Mattravers, C.; Maugain, J. M.; Maxfield, S. J.; Maximov, D. A.; May, E. N.; Mayne, A.; Mazini, R.; Mazur, M.; Mazzanti, M.; Mazzoni, E.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McCubbin, N. A.; McFarlane, K. W.; Mcfayden, J. A.; McGlone, H.; Mchedlidze, G.; McLaren, R. A.; Mclaughlan, T.; McMahon, S. J.; McPherson, R. A.; Meade, A.; Mechnich, J.; Mechtel, M.; Medinnis, M.; Meera-Lebbai, R.; Meguro, T.; Mehdiyev, R.; Mehlhase, S.; Mehta, A.; Meier, K.; Meinhardt, J.; Meirose, B.; Melachrinos, C.; Mellado Garcia, B. R.; Mendoza Navas, L.; Meng, Z.; Mengarelli, A.; Menke, S.; Menot, C.; Meoni, E.; Mercurio, K. M.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer, J.; Meyer, T. C.; Meyer, W. T.; Miao, J.; Michal, S.; Micu, L.; Middleton, R. P.; Miele, P.; Migas, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Miller, D. W.; Miller, R. J.; Mills, W. J.; Mills, C.; Milov, A.; Milstead, D. A.; Milstein, D.; Minaenko, A. A.; Miñano Moya, M.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mirabelli, G.; Miralles Verge, L.; Misawa, S.; Misiejuk, A.; Mitrevski, J.; Mitrofanov, G. Y.; Mitsou, V. A.; Mitsui, S.; Miyagawa, P. S.; Miyazaki, K.; Mjörnmark, J. U.; Moa, T.; Mockett, P.; Moed, S.; Moeller, V.; Mönig, K.; Möser, N.; Mohapatra, S.; Mohr, W.; Mohrdieck-Möck, S.; Moisseev, A. M.; Moles-Valls, R.; Molina-Perez, J.; Monk, J.; Monnier, E.; Montesano, S.; Monticelli, F.; Monzani, S.; Moore, R. W.; Moorhead, G. F.; Mora Herrera, C.; Moraes, A.; Morange, N.; Morel, J.; Morello, G.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morii, M.; Morin, J.; Morley, A. K.; Mornacchi, G.; Morozov, S. V.; Morris, J. D.; Morvaj, L.; Moser, H. G.; Mosidze, M.; Moss, J.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Mudrinic, M.; Mueller, F.; Mueller, J.; Mueller, K.; Müller, T. A.; Muenstermann, D.; Muir, A.; Munwes, Y.; Murray, W. J.; Mussche, I.; Musto, E.; Myagkov, A. G.; Myska, M.; Nadal, J.; Nagai, K.; Nagano, K.; Nagasaka, Y.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Nanava, G.; Napier, A.; Nash, M.; Nation, N. R.; Nattermann, T.; Naumann, T.; Navarro, G.; Neal, H. A.; Nebot, E.; Nechaeva, P. Yu.; Negri, A.; Negri, G.; Nektarijevic, S.; Nelson, A.; Nelson, S.; Nelson, T. K.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Nesterov, S. Y.; Neubauer, M. S.; Neusiedl, A.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen Thi Hong, V.; Nickerson, R. B.; Nicolaidou, R.; Nicolas, L.; Nicoletti, G.; Nicquevert, B.; Niedercorn, F.; Nielsen, J.; Niinikoski, T.; Nikiforou, N.; Nikiforov, A.; Nikolaenko, V.; Nikolaev, K.; Nikolic-Audit, I.; Nikolics, K.; Nikolopoulos, K.; Nilsen, H.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishiyama, T.; Nisius, R.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Nordberg, M.; Nordkvist, B.; Norton, P. R.; Notz, D.; Novakova, J.; Nozaki, M.; Nozka, L.; Nugent, I. M.; Nuncio-Quiroz, A.-E.; Nunes Hanninger, G.; Nunnemann, T.; Nurse, E.; Nyman, T.; O'Brien, B. J.; O'Neale, S. W.; O'Neil, D. C.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Ocariz, J.; Ochi, A.; Oda, S.; Odaka, S.; Odier, J.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohshima, T.; Ohshita, H.; Ohsugi, T.; Okada, S.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olcese, M.; Olchevski, A. G.; Oliveira, M.; Oliveira Damazio, D.; Oliver Garcia, E.; Olivito, D.; Olszewski, A.; Olszowska, J.; Omachi, C.; Onofre, A.; Onyisi, P. U. E.; Oram, C. J.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlov, I.; Oropeza Barrera, C.; Orr, R. S.; Osculati, B.; Ospanov, R.; Osuna, C.; Otero y Garzon, G.; Ottersbach, J. P.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Ouyang, Q.; Owen, M.; Owen, S.; Ozcan, V. E.; Ozturk, N.; Pacheco Pages, A.; Padilla Aranda, C.; Pagan Griso, S.; Paganis, E.; Paige, F.; Pajchel, K.; Palacino, G.; Paleari, C. P.; Palestini, S.; Pallin, D.; Palma, A.; Palmer, J. D.; Pan, Y. B.; Panagiotopoulou, E.; Panes, B.; Panikashvili, N.; Panitkin, S.; Pantea, D.; Panuskova, M.; Paolone, V.; Papadelis, A.; Papadopoulou, Th. D.; Paramonov, A.; Park, W.; Parker, M. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pasqualucci, E.; Passeri, A.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Patel, N.; Pater, J. R.; Patricelli, S.; Pauly, T.; Pecsy, M.; Pedraza Morales, M. I.; Peleganchuk, S. V.; Peng, H.; Pengo, R.; Penson, A.; Penwell, J.; Perantoni, M.; Perez, K.; Perez Cavalcanti, T.; Perez Codina, E.; Pérez García-Estañ, M. T.; Perez Reale, V.; Perini, L.; Pernegger, H.; Perrino, R.; Perrodo, P.; Persembe, S.; Perus, A.; Peshekhonov, V. D.; Petersen, B. A.; Petersen, J.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petrolo, E.; Petrucci, F.; Petschull, D.; Petteni, M.; Pezoa, R.; Pfeifer, B.; Phan, A.; Phillips, A. W.; Phillips, P. W.; Piacquadio, G.; Piccaro, E.; Piccinini, M.; Pickford, A.; Piec, S. M.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pina, J.; Pinamonti, M.; Pinder, A.; Pinfold, J. L.; Ping, J.; Pinto, B.; Pirotte, O.; Pizio, C.; Placakyte, R.; Plamondon, M.; Pleier, M.-A.; Pleskach, A. V.; Poblaguev, A.; Poddar, S.; Podlyski, F.; Poggioli, L.; Poghosyan, T.; Pohl, M.; Polci, F.; Polesello, G.; Policicchio, A.; Polini, A.; Poll, J.; Polychronakos, V.; Pomarede, D. M.; Pomeroy, D.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Portell Bueso, X.; Posch, C.; Pospelov, G. E.; Pospisil, S.; Potekhin, M.; Potrap, I. N.; Potter, C. J.; Potter, K. P.; Potter, C. T.; Poulard, G.; Poveda, J.; Prabhu, R.; Pralavorio, P.; Prasad, S.; Pravahan, R.; Prell, S.; Pretzl, K.; Pribyl, L.; Price, D.; Price, L. E.; Price, M. J.; Prichard, P. M.; Prieur, D.; Primavera, M.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Prudent, X.; Przysiezniak, H.; Psoroulas, S.; Ptacek, E.; Pueschel, E.; Purdham, J.; Purohit, M.; Puzo, P.; Pylypchenko, Y.; Qian, J.; Qian, W.; Qian, Z.; Qin, Z.; Quadt, A.; Quarrie, D. R.; Quayle, W. B.; Quinonez, F.; Raas, M.; Radeka, V.; Radescu, V.; Radics, B.; Rador, T.; Ragusa, F.; Rahal, G.; Rahimi, A. M.; Rahm, D.; Rajagopalan, S.; Rammensee, M.; Rammes, M.; Ramstedt, M.; Randle-Conde, A. S.; Randrianarivony, K.; Ratoff, P. N.; Rauscher, F.; Rauter, E.; Raymond, M.; Read, A. L.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Reichold, A.; Reinherz-Aronis, E.; Reinsch, A.; Reisinger, I.; Reljic, D.; Rembser, C.; Ren, Z. L.; Renaud, A.; Renkel, P.; Rescia, S.; 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.; Roda Dos Santos, D.; Rodier, S.; Rodriguez, D.; Rodriguez Garcia, Y.; Roe, A.; Roe, S.; Røhne, O.; Rojo, V.; Rolli, S.; Romaniouk, A.; Romano, M.; Romanov, V. M.; Romeo, G.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, A.; Rose, M.; Rosenbaum, G. A.; Rosenberg, E. I.; Rosendahl, P. L.; Rosenthal, O.; 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.; Sandoval, C.; 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.; Savine, A. Y.; 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.; Schernau, M.; 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.; Sedov, G.; 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, 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.; Sircar, A.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skottowe, H. P.; Skovpen, K.; Skubic, P.; Skvorodnev, N.; Slater, M.; Slavicek, T.; Sliwa, K.; Sloper, J.; Smakhtin, V.; Smirnov, S. Yu.; Smirnov, Y.; 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.; Soualah, R.; Soukharev, A.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spila, F.; Spiriti, E.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R. D.; Stahl, T.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staude, A.; Stavina, P.; Stavropoulos, G.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, K.; Stewart, G. A.; Stillings, J. A.; Stockmanns, T.; Stockton, M. C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Strube, J.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Soh, D. A.; Su, D.; Subramania, HS.; Succurro, A.; Sugaya, Y.; Sugimoto, T.; Suhr, C.; Suita, K.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Sushkov, S.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; 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.; 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.; Tayalati, Y.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teinturier, M.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terwort, M.; Testa, M.; Teuscher, R. J.; Thadome, J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thioye, M.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomson, E.; Thomson, M.; Thompson, R. J.; Thun, R. P.; Tian, F.; 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.; Tudorache, A.; Tudorache, V.; Tuggle, J. M.; Turala, M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Turra, R.; Tuts, P. M.; Twomey, M. S.; 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 Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vanadia, M.; 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.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villani, E. G.; 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.; Vladoiu, D.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobiev, A. P.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T. T.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vujicic, M.; 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.; Wastie, R.; 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-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.; 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.; Wraight, K.; Wright, C.; Wright, M.; Wright, D.; 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.; 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, Y.; Yang, Z.; Yanush, S.; 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.; Zeman, M.; Zemla, A.; Zendler, C.; 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.; Zhang, Q.; 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.; Zinonos, Z.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; Zolnierowski, Y.; Zsenei, A.; zur Nedden, M.; Zutshi, V.; Zwalinski, L.

2013-03-01

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of sqrt{s}=7 TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti- k t algorithm with distance parameters R=0.4 or R=0.6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta p T≥20 GeV and pseudorapidities | η|<4.5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2.5 % in the central calorimeter region (| η|<0.8) for jets with 60≤ p T<800 GeV, and is maximally 14 % for p T<30 GeV in the most forward region 3.2≤| η|<4.5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon p T, the sum of the transverse momenta of tracks associated to the jet, or a system of low- p T jets recoiling against a high- p T jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high- p T jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined.

Jet energy measurement with the ATLAS detector in proton-proton collisions at $$\\sqrt{\\mathrm{s}}=7\\ \\mathrm{TeV}$$

DOE PAGES

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

2013-03-02

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7 TeV corresponding to an integrated luminosity of 38 pb -1. Jets are reconstructed with the anti-k t algorithm with distance parameters R = 0.4 or R = 0.6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta p T ≥ 20 GeV and pseudorapidities |η| < 4.5. The jet energy systematic uncertainty is estimated using the single isolated hadron responsemore » measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2.5 % in the central calorimeter region (|η| < 0.8) for jets with 60 ≤ p T < 800 GeV, and is maximally 14 % for p T ≤ 30 GeV in the most forward region 3.2 ≤ |η| < 4.5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon p T, the sum of the transverse momenta of tracks associated to the jet, or a system of low-p T jets recoiling against a high-p T jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-p T jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined.« less

Environmental Scanning in Educational Planning: Establishing a Strategic Trend Information System.

ERIC Educational Resources Information Center

Morrison, James L.

The systematic evaluation of the macroenvironment is sometimes referred to as a strategic trend information system. Strategic trend intelligence systems are highly developed, systematic intelligence programs that focus on trends and events in the external environment and provide institutions with knowledge to reduce areas of uncertainty and with…

Key comparison CCPR-K1.a as an interlaboratory comparison of correlated color temperature

NASA Astrophysics Data System (ADS)

Kärhä, P.; Vaskuri, A.; Pulli, T.; Ikonen, E.

2018-02-01

We analyze the results of spectral irradiance key comparison CCPR-K1.a for correlated color temperature (CCT). For four participants out of 13, the uncertainties of CCT, calculated using traditional methods, not accounting for correlations, would be too small. The reason for the failure of traditional uncertainty calculation is spectral correlations, producing systematic deviations of the same sign over certain wavelength regions. The results highlight the importance of accounting for such correlations when calculating uncertainties of spectrally integrated quantities.

Uncertainties in climate data sets

NASA Technical Reports Server (NTRS)

Mcguirk, James P.

1992-01-01

Climate diagnostics are constructed from either analyzed fields or from observational data sets. Those that have been commonly used are normally considered ground truth. However, in most of these collections, errors and uncertainties exist which are generally ignored due to the consistency of usage over time. Examples of uncertainties and errors are described in NMC and ECMWF analyses and in satellite observational sets-OLR, TOVS, and SMMR. It is suggested that these errors can be large, systematic, and not negligible in climate analysis.

Accounting for baryonic effects in cosmic shear tomography: Determining a minimal set of nuisance parameters using PCA

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

Eifler, Tim; Krause, Elisabeth; Dodelson, Scott

2014-05-28

Systematic uncertainties that have been subdominant in past large-scale structure (LSS) surveys are likely to exceed statistical uncertainties of current and future LSS data sets, potentially limiting the extraction of cosmological information. Here we present a general framework (PCA marginalization) to consistently incorporate systematic effects into a likelihood analysis. This technique naturally accounts for degeneracies between nuisance parameters and can substantially reduce the dimension of the parameter space that needs to be sampled. As a practical application, we apply PCA marginalization to account for baryonic physics as an uncertainty in cosmic shear tomography. Specifically, we use CosmoLike to run simulatedmore » likelihood analyses on three independent sets of numerical simulations, each covering a wide range of baryonic scenarios differing in cooling, star formation, and feedback mechanisms. We simulate a Stage III (Dark Energy Survey) and Stage IV (Large Synoptic Survey Telescope/Euclid) survey and find a substantial bias in cosmological constraints if baryonic physics is not accounted for. We then show that PCA marginalization (employing at most 3 to 4 nuisance parameters) removes this bias. Our study demonstrates that it is possible to obtain robust, precise constraints on the dark energy equation of state even in the presence of large levels of systematic uncertainty in astrophysical processes. We conclude that the PCA marginalization technique is a powerful, general tool for addressing many of the challenges facing the precision cosmology program.« less

Prospective Architectures for Onboard vs Cloud-Based Decision Making for Unmanned Aerial Systems

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Teubert, Christopher

2017-01-01

This paper investigates propsective architectures for decision-making in unmanned aerial systems. When these unmanned vehicles operate in urban environments, there are several sources of uncertainty that affect their behavior, and decision-making algorithms need to be robust to account for these different sources of uncertainty. It is important to account for several risk-factors that affect the flight of these unmanned systems, and facilitate decision-making by taking into consideration these various risk-factors. In addition, there are several technical challenges related to autonomous flight of unmanned aerial systems; these challenges include sensing, obstacle detection, path planning and navigation, trajectory generation and selection, etc. Many of these activities require significant computational power and in many situations, all of these activities need to be performed in real-time. In order to efficiently integrate these activities, it is important to develop a systematic architecture that can facilitate real-time decision-making. Four prospective architectures are discussed in this paper; on one end of the spectrum, the first architecture considers all activities/computations being performed onboard the vehicle whereas on the other end of the spectrum, the fourth and final architecture considers all activities/computations being performed in the cloud, using a new service known as Prognostics as a Service that is being developed at NASA Ames Research Center. The four different architectures are compared, their advantages and disadvantages are explained and conclusions are presented.

Uncertainties in the deprojection of the observed bar properties

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

Zou, Yanfei; Shen, Juntai; Li, Zhao-Yu, E-mail: jshen@shao.ac.cn

2014-08-10

In observations, it is important to deproject the two fundamental quantities characterizing a bar, i.e., its length (a) and ellipticity (e), to face-on values before any careful analyses. However, systematic estimation on the uncertainties of the commonly used deprojection methods is still lacking. Simulated galaxies are well suited in this study. We project two simulated barred galaxies onto a two-dimensional (2D) plane with different bar orientations and disk inclination angles (i). Bar properties are measured and deprojected with the popular deprojection methods in the literature. Generally speaking, deprojection uncertainties increase with increasing i. All of the deprojection methods behave badlymore » when i is larger than 60°, due to the vertical thickness of the bar. Thus, future statistical studies of barred galaxies should exclude galaxies more inclined than 60°. At moderate inclination angles (i ≤ 60°), 2D deprojection methods (analytical and image stretching), and Fourier-based methods (Fourier decomposition and bar-interbar contrast) perform reasonably well with uncertainties ∼10% in both the bar length and ellipticity, whereas the uncertainties of the one-dimensional (1D) analytical deprojection can be as high as 100% in certain extreme cases. We find that different bar measurement methods show systematic differences in the deprojection uncertainties. We further discuss the deprojection uncertainty factors with the emphasis on the most important one, i.e., the three-dimensional structure of the bar itself. We construct two triaxial toy bar models that can qualitatively reproduce the results of the 1D and 2D analytical deprojections; they confirm that the vertical thickness of the bar is the main source of uncertainties.« less

A fresh look at Jupiter's synchrotron from the Cassini RADAR flyby

NASA Astrophysics Data System (ADS)

Moeckel, Chris; Janssen, Michael A.; de Pater, Imke

2017-10-01

The temporal variability is one of the big remaining questions in synchrotron radiation. Most known processes affect the radiation belts on time scales of month and years, whereas variations on shorter time scales are still a subject of scientific debate. In this light, the extreme depletion of energetic electrons as revealed by the 2001 Cassini radio measurements during its flyby of Jupiter is very surprising. The obtained estimate of the ultra-relativistic electron number density is considerably lower when compared to model calculations and similar observation. It has long been suspected that the measurements suffered from large systematic uncertainties. The uncertainties were reduced by recalibrating the raw data the Cassini RADAR measurements based on an improved understanding of the instrument after a decade of operation at Titan. The uncertainties pertaining to spacecraft pointing and the Jovian thermal radiation were solved for by applying a Markov-Chain Monte-Carlo optimization to the full set of 20 Jupiter scans. The synchrotron radiation was then recovered by subtracting the thermal radiation extending from Jupiter’s upper atmosphere, which comprises up to 97% of the total signal strength in the Cassini frequency band. The excellent knowledge of the instrument allows for constraining the disk-averaged brightness temperature of 158.6K ± 2.4K and can be used to improve the calibration of radio telescope such as the Very Large Array. The new retrieval confirmed that systematic artifacts propagated into the initial analysis. The synchrotron radio flux was revised upwards to agree with model predictions of a depleted magnetosphere. Radio maps indicated an enhancement at higher latitudes of electrons, requiring processes to scatter particles to higher latitudes. Comparison with other radio maps demonstrated a positive correlation between the energy of the electrons and the scattering they experienced. This behavior is indicative of wave-particle interactions, which are known to be acting in the terrestrial van-Allen belts but have not so far been considered in the Jupiter models.

The effect of the geomagnetic field on cosmic ray energy estimates and large scale anisotropy searches on data from the Pierre Auger Observatory

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

Abreu, P.; /Lisbon, IST; Aglietta, M.

2011-11-01

We present a comprehensive study of the influence of the geomagnetic field on the energy estimation of extensive air showers with a zenith angle smaller than 60{sup o}, detected at the Pierre Auger Observatory. The geomagnetic field induces an azimuthal modulation of the estimated energy of cosmic rays up to the {approx} 2% level at large zenith angles. We present a method to account for this modulation of the reconstructed energy. We analyse the effect of the modulation on large scale anisotropy searches in the arrival direction distributions of cosmic rays. At a given energy, the geomagnetic effect is shownmore » to induce a pseudo-dipolar pattern at the percent level in the declination distribution that needs to be accounted for. In this work, we have identified and quantified a systematic uncertainty affecting the energy determination of cosmic rays detected by the surface detector array of the Pierre Auger Observatory. This systematic uncertainty, induced by the influence of the geomagnetic field on the shower development, has a strength which depends on both the zenith and the azimuthal angles. Consequently, we have shown that it induces distortions of the estimated cosmic ray event rate at a given energy at the percent level in both the azimuthal and the declination distributions, the latter of which mimics an almost dipolar pattern. We have also shown that the induced distortions are already at the level of the statistical uncertainties for a number of events N {approx_equal} 32 000 (we note that the full Auger surface detector array collects about 6500 events per year with energies above 3 EeV). Accounting for these effects is thus essential with regard to the correct interpretation of large scale anisotropy measurements taking explicitly profit from the declination distribution.« less

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

NASA Astrophysics Data System (ADS)

Schwarz, Jakob; Kirchengast, Gottfried; Schwaerz, Marc

2018-05-01

Global Navigation Satellite System (GNSS) radio occultation (RO) observations are highly accurate, long-term stable data sets and are globally available as a continuous record from 2001. Essential climate variables for the thermodynamic state of the free atmosphere - such as pressure, temperature, and tropospheric water vapor profiles (involving background information) - can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS) at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte Carlo ensemble methods. The algorithm performance is demonstrated using test day ensembles of simulated data as well as real RO event data from the satellite missions CHAllenging Minisatellite Payload (CHAMP); Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and Meteorological Operational Satellite A (MetOp). The results of the Monte Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs robustly. Together with the other parts of the rOPS processing chain this part is thus ready to provide integrated uncertainty propagation through the whole RO retrieval chain for the benefit of climate monitoring and other applications.

Interfraction and intrafraction performance of the Gamma Knife Extend system for patient positioning and immobilization.

PubMed

Schlesinger, David; Xu, Zhiyuan; Taylor, Frances; Yen, Chun-Po; Sheehan, Jason

2012-12-01

The Extend system for the Gamma Knife Perfexion makes possible multifractional Gamma Knife treatments. The Extend system consists of a vacuum-monitored immobilization frame and a positioning measurement system used to determine the location of the patient's head within the frame at the time of simulation imaging and before each treatment fraction. The measurement system consists of a repositioning check tool (RCT), which attaches to the Extend frame, and associated digital measuring gauges. The purpose of this study is to evaluate the performance of the Extend system for patient repositioning before each treatment session (fraction) and patient immobilization between (interfraction) and during (intrafraction) each session in the first 10 patients (36 fractional treatments) treated at the University of Virginia. The RCT was used to acquire a set of reference measurements for each patient position at the time of CT simulation. Repositioning measurements were acquired before each fraction, and the patient position was adjusted until the residual radial difference from the reference position measurements was less than 1 mm. After treatment, patient position measurements were acquired, and the difference between those measurements and the ones obtained for patient position before the fraction was calculated as a measure of immobilization capability. Analysis of patient setup and immobilization performance included calculation of the group mean, standard deviation (SD), and distribution of systematic (components affecting all fractions) and random (per fraction) uncertainty components. Across all patients and fractions, the mean radial setup difference from the reference measurements was 0.64 mm, with an SD of 0.24 mm. The distribution of systematic uncertainty (Σ) was 0.17 mm, and the distribution of random uncertainty (σ) was 0.16 mm. The root mean square (RMS) differences for each plate of the RCT were as follows: right = 0.35 mm; left = 0.41 mm; superior = 0.28 mm; and anterior = 0.20 mm. The mean intrafractional positional difference across all treatments was 0.47 mm, with an SD of 0.30 mm. The distribution of systematic uncertainty was 0.18 mm, and the distribution of random uncertainty was 0.22 mm. The RMS differences for each plate of the RCT were 0.24 mm for the right plate, 0.22 mm for the left plate, 0.24 mm for the superior plate, and 0.34 mm for the anterior plate. Data from 1 fraction were excluded from the analysis because the vacuum-monitoring interlock detected patient motion, which in turn required repositioning in the middle of the fraction. The Extend system can be used to reposition and immobilize patients in a radiosurgical setting. However, care should be taken to acquire measurements that can implicitly account for rotations of the patient's head. Further work is required to determine the sensitivity of the vacuum interlock to detect patient motion.

Reducing patients' anxiety and uncertainty, and improving recall in bad news consultations.

PubMed

van Osch, Mara; Sep, Milou; van Vliet, Liesbeth M; van Dulmen, Sandra; Bensing, Jozien M

2014-11-01

Patients' recall of provided information during bad news consultations is poor. According to the attentional narrowing hypothesis, the emotional arousal caused by the bad news might be responsible for this hampered information processing. Because affective communication has proven to be effective in tempering patients' emotional reactions, the current study used an experimental design to explore whether physician's affective communication in bad news consultations decreases patients' anxiety and uncertainty and improves information recall. Two scripted video-vignettes of a bad news consultation were used in which the physician's verbal communication was manipulated (standard vs. affective condition). Fifty healthy women (i.e., analogue patients) randomly watched 1 of the 2 videos. The effect of communication on participants' anxiety, uncertainty, and recall was assessed by self-report questionnaires. Additionally, a moderator analysis was performed. Affective communication reduced anxiety (p = .01) and uncertainty (p = .04), and improved recall (p = .05), especially for information about prognosis (p = .04) and, to some extent, for treatment options (p = .07). The moderating effect of (reduced) anxiety and uncertainty on recall could not be confirmed and showed a trend for uncertainty. Physicians' affective communication can temper patients' anxiety and uncertainty during bad news consultations, and enhance their ability to recall medical information. The reduction of anxiety and uncertainty could not explain patients' enhanced recall, which leaves the underlying mechanism unspecified. Our findings underline the importance of addressing patients' emotions and provide empirical support to incorporate this in clinical guidelines and recommendations. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Uncertainty in flood forecasting: A distributed modeling approach in a sparse data catchment

NASA Astrophysics Data System (ADS)

Mendoza, Pablo A.; McPhee, James; Vargas, Ximena

2012-09-01

Data scarcity has traditionally precluded the application of advanced hydrologic techniques in developing countries. In this paper, we evaluate the performance of a flood forecasting scheme in a sparsely monitored catchment based on distributed hydrologic modeling, discharge assimilation, and numerical weather predictions with explicit validation uncertainty analysis. For the hydrologic component of our framework, we apply TopNet to the Cautin River basin, located in southern Chile, using a fully distributed a priori parameterization based on both literature-suggested values and data gathered during field campaigns. Results obtained from this step indicate that the incremental effort spent in measuring directly a set of model parameters was insufficient to represent adequately the most relevant hydrologic processes related to spatiotemporal runoff patterns. Subsequent uncertainty validation performed over a six month ensemble simulation shows that streamflow uncertainty is better represented during flood events, due to both the increase of state perturbation introduced by rainfall and the flood-oriented calibration strategy adopted here. Results from different assimilation configurations suggest that the upper part of the basin is the major source of uncertainty in hydrologic process representation and hint at the usefulness of interpreting assimilation results in terms of model input and parameterization inadequacy. Furthermore, in this case study the violation of Markovian state properties by the Ensemble Kalman filter did affect the numerical results, showing that an explicit treatment of the time delay between the generation of surface runoff and the arrival at the basin outlet is required in the assimilation scheme. Peak flow forecasting results demonstrate that there is a major problem with the Weather Research and Forecasting model outputs, which systematically overestimate precipitation over the catchment. A final analysis performed for a large flooding event that occurred in July 2006 shows that, in the absence of bias introduced by an incorrect model calibration, the updating of both model states and meteorological forecasts contributes to a better representation of streamflow uncertainty and to better hydrologic forecasts.

Estimating the Health Effects of Greenhouse Gas Mitigation Strategies: Addressing Parametric, Model, and Valuation Challenges

PubMed Central

Hess, Jeremy J.; Ebi, Kristie L.; Markandya, Anil; Balbus, John M.; Wilkinson, Paul; Haines, Andy; Chalabi, Zaid

2014-01-01

Background: Policy decisions regarding climate change mitigation are increasingly incorporating the beneficial and adverse health impacts of greenhouse gas emission reduction strategies. Studies of such co-benefits and co-harms involve modeling approaches requiring a range of analytic decisions that affect the model output. Objective: Our objective was to assess analytic decisions regarding model framework, structure, choice of parameters, and handling of uncertainty when modeling health co-benefits, and to make recommendations for improvements that could increase policy uptake. Methods: We describe the assumptions and analytic decisions underlying models of mitigation co-benefits, examining their effects on modeling outputs, and consider tools for quantifying uncertainty. Discussion: There is considerable variation in approaches to valuation metrics, discounting methods, uncertainty characterization and propagation, and assessment of low-probability/high-impact events. There is also variable inclusion of adverse impacts of mitigation policies, and limited extension of modeling domains to include implementation considerations. Going forward, co-benefits modeling efforts should be carried out in collaboration with policy makers; these efforts should include the full range of positive and negative impacts and critical uncertainties, as well as a range of discount rates, and should explicitly characterize uncertainty. We make recommendations to improve the rigor and consistency of modeling of health co-benefits. Conclusion: Modeling health co-benefits requires systematic consideration of the suitability of model assumptions, of what should be included and excluded from the model framework, and how uncertainty should be treated. Increased attention to these and other analytic decisions has the potential to increase the policy relevance and application of co-benefits modeling studies, potentially helping policy makers to maximize mitigation potential while simultaneously improving health. Citation: Remais JV, Hess JJ, Ebi KL, Markandya A, Balbus JM, Wilkinson P, Haines A, Chalabi Z. 2014. Estimating the health effects of greenhouse gas mitigation strategies: addressing parametric, model, and valuation challenges. Environ Health Perspect 122:447–455; http://dx.doi.org/10.1289/ehp.1306744 PMID:24583270

Numerical Uncertainty Quantification for Radiation Analysis Tools

NASA Technical Reports Server (NTRS)

Anderson, Brooke; Blattnig, Steve; Clowdsley, Martha

2007-01-01

Recently a new emphasis has been placed on engineering applications of space radiation analyses and thus a systematic effort of Verification, Validation and Uncertainty Quantification (VV&UQ) of the tools commonly used for radiation analysis for vehicle design and mission planning has begun. There are two sources of uncertainty in geometric discretization addressed in this paper that need to be quantified in order to understand the total uncertainty in estimating space radiation exposures. One source of uncertainty is in ray tracing, as the number of rays increase the associated uncertainty decreases, but the computational expense increases. Thus, a cost benefit analysis optimizing computational time versus uncertainty is needed and is addressed in this paper. The second source of uncertainty results from the interpolation over the dose vs. depth curves that is needed to determine the radiation exposure. The question, then, is what is the number of thicknesses that is needed to get an accurate result. So convergence testing is performed to quantify the uncertainty associated with interpolating over different shield thickness spatial grids.

Analysis of uncertainties in the estimates of nitrous oxide and methane emissions in the UK's greenhouse gas inventory for agriculture

NASA Astrophysics Data System (ADS)

Milne, Alice E.; Glendining, Margaret J.; Bellamy, Pat; Misselbrook, Tom; Gilhespy, Sarah; Rivas Casado, Monica; Hulin, Adele; van Oijen, Marcel; Whitmore, Andrew P.

2014-01-01

The UK's greenhouse gas inventory for agriculture uses a model based on the IPCC Tier 1 and Tier 2 methods to estimate the emissions of methane and nitrous oxide from agriculture. The inventory calculations are disaggregated at country level (England, Wales, Scotland and Northern Ireland). Before now, no detailed assessment of the uncertainties in the estimates of emissions had been done. We used Monte Carlo simulation to do such an analysis. We collated information on the uncertainties of each of the model inputs. The uncertainties propagate through the model and result in uncertainties in the estimated emissions. Using a sensitivity analysis, we found that in England and Scotland the uncertainty in the emission factor for emissions from N inputs (EF1) affected uncertainty the most, but that in Wales and Northern Ireland, the emission factor for N leaching and runoff (EF5) had greater influence. We showed that if the uncertainty in any one of these emission factors is reduced by 50%, the uncertainty in emissions of nitrous oxide reduces by 10%. The uncertainty in the estimate for the emissions of methane emission factors for enteric fermentation in cows and sheep most affected the uncertainty in methane emissions. When inventories are disaggregated (as that for the UK is) correlation between separate instances of each emission factor will affect the uncertainty in emissions. As more countries move towards inventory models with disaggregation, it is important that the IPCC give firm guidance on this topic.

Probabilistic fatigue life prediction of metallic and composite materials

NASA Astrophysics Data System (ADS)

Xiang, Yibing

Fatigue is one of the most common failure modes for engineering structures, such as aircrafts, rotorcrafts and aviation transports. Both metallic materials and composite materials are widely used and affected by fatigue damage. Huge uncertainties arise from material properties, measurement noise, imperfect models, future anticipated loads and environmental conditions. These uncertainties are critical issues for accurate remaining useful life (RUL) prediction for engineering structures in service. Probabilistic fatigue prognosis considering various uncertainties is of great importance for structural safety. The objective of this study is to develop probabilistic fatigue life prediction models for metallic materials and composite materials. A fatigue model based on crack growth analysis and equivalent initial flaw size concept is proposed for metallic materials. Following this, the developed model is extended to include structural geometry effects (notch effect), environmental effects (corroded specimens) and manufacturing effects (shot peening effects). Due to the inhomogeneity and anisotropy, the fatigue model suitable for metallic materials cannot be directly applied to composite materials. A composite fatigue model life prediction is proposed based on a mixed-mode delamination growth model and a stiffness degradation law. After the development of deterministic fatigue models of metallic and composite materials, a general probabilistic life prediction methodology is developed. The proposed methodology combines an efficient Inverse First-Order Reliability Method (IFORM) for the uncertainty propogation in fatigue life prediction. An equivalent stresstransformation has been developed to enhance the computational efficiency under realistic random amplitude loading. A systematical reliability-based maintenance optimization framework is proposed for fatigue risk management and mitigation of engineering structures.

Disentangling dark energy and cosmic tests of gravity from weak lensing systematics

NASA Astrophysics Data System (ADS)

Laszlo, Istvan; Bean, Rachel; Kirk, Donnacha; Bridle, Sarah

2012-06-01

We consider the impact of key astrophysical and measurement systematics on constraints on dark energy and modifications to gravity on cosmic scales. We focus on upcoming photometric ‘stage III’ and ‘stage IV’ large-scale structure surveys such as the Dark Energy Survey (DES), the Subaru Measurement of Images and Redshifts survey, the Euclid survey, the Large Synoptic Survey Telescope (LSST) and Wide Field Infra-Red Space Telescope (WFIRST). We illustrate the different redshift dependencies of gravity modifications compared to intrinsic alignments, the main astrophysical systematic. The way in which systematic uncertainties, such as galaxy bias and intrinsic alignments, are modelled can change dark energy equation-of-state parameter and modified gravity figures of merit by a factor of 4. The inclusion of cross-correlations of cosmic shear and galaxy position measurements helps reduce the loss of constraining power from the lensing shear surveys. When forecasts for Planck cosmic microwave background and stage IV surveys are combined, constraints on the dark energy equation-of-state parameter and modified gravity model are recovered, relative to those from shear data with no systematic uncertainties, provided fewer than 36 free parameters in total are used to describe the galaxy bias and intrinsic alignment models as a function of scale and redshift. While some uncertainty in the intrinsic alignment (IA) model can be tolerated, it is going to be important to be able to parametrize IAs well in order to realize the full potential of upcoming surveys. To facilitate future investigations, we also provide a fitting function for the matter power spectrum arising from the phenomenological modified gravity model we consider.

Oscillator strengths of the Si II 181 nanometer resonance multiplet

NASA Technical Reports Server (NTRS)

Bergeson, S. D.; Lawler, J. E.

1993-01-01

We report Si II experimental log (gf)-values of -2.38(4) for the 180.801 nm line, of -2.18(4) for the 181.693 nm line, and of -3.29(5) for the 181.745 nm line, where the number in parentheses is the uncertainty in the last digit. The overall uncertainties (about 10 percent) include the 1 sigma random uncertainty (about 6 percent) and an estimate of the systematic uncertainty. The oscillator strengths are determined by combining branching fractions and radiative lifetimes. The branching fractions are measured using standard spectroradiometry on an optically thin source; the radiative lifetimes are measured using time-resolved laser-induced fluorescence.

Error modelling of quantum Hall array resistance standards

NASA Astrophysics Data System (ADS)

Marzano, Martina; Oe, Takehiko; Ortolano, Massimo; Callegaro, Luca; Kaneko, Nobu-Hisa

2018-04-01

Quantum Hall array resistance standards (QHARSs) are integrated circuits composed of interconnected quantum Hall effect elements that allow the realization of virtually arbitrary resistance values. In recent years, techniques were presented to efficiently design QHARS networks. An open problem is that of the evaluation of the accuracy of a QHARS, which is affected by contact and wire resistances. In this work, we present a general and systematic procedure for the error modelling of QHARSs, which is based on modern circuit analysis techniques and Monte Carlo evaluation of the uncertainty. As a practical example, this method of analysis is applied to the characterization of a 1 MΩ QHARS developed by the National Metrology Institute of Japan. Software tools are provided to apply the procedure to other arrays.

Application of radiosonde data to VERITAS simulations

NASA Astrophysics Data System (ADS)

Daniel, M. K.

The atmosphere is a vital component of the detector in an atmospheric Cherenkov telescope. In order to understand observations from these instruments and reduce systematic uncertainties and biases in their data it is important to correctly model the atmosphere in simulations of the extensive air showers they detect. The Very High Energy Telescope Array (VERITAS) is a system of 4 such telescopes located at the Whipple Observatory in Southern Arizona. Daily radiosonde measurements from the nearby Tucson airport allow an accurate model of the atmosphere for the VERITAS experiment to be constructed. Comparison of the radiosonde data to existing atmospheric models is performed and the expected effects on the systematic uncertainties are summarised here.

Multivariate analysis techniques

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

Bendavid, Josh; Fisher, Wade C.; Junk, Thomas R.

2016-01-01

The end products of experimental data analysis are designed to be simple and easy to understand: hypothesis tests and measurements of parameters. But, the experimental data themselves are voluminous and complex. Furthermore, in modern collider experiments, many petabytes of data must be processed in search of rare new processes which occur together with much more copious background processes that are of less interest to the task at hand. The systematic uncertainties on the background may be larger than the expected signal in many cases. The statistical power of an analysis and its sensitivity to systematic uncertainty can therefore usually bothmore » be improved by separating signal events from background events with higher efficiency and purity.« less

Mapping the absolute magnetic field and evaluating the quadratic Zeeman-effect-induced systematic error in an atom interferometer gravimeter

NASA Astrophysics Data System (ADS)

Hu, Qing-Qing; Freier, Christian; Leykauf, Bastian; Schkolnik, Vladimir; Yang, Jun; Krutzik, Markus; Peters, Achim

2017-09-01

Precisely evaluating the systematic error induced by the quadratic Zeeman effect is important for developing atom interferometer gravimeters aiming at an accuracy in the μ Gal regime (1 μ Gal =10-8m /s2 ≈10-9g ). This paper reports on the experimental investigation of Raman spectroscopy-based magnetic field measurements and the evaluation of the systematic error in the gravimetric atom interferometer (GAIN) due to quadratic Zeeman effect. We discuss Raman duration and frequency step-size-dependent magnetic field measurement uncertainty, present vector light shift and tensor light shift induced magnetic field measurement offset, and map the absolute magnetic field inside the interferometer chamber of GAIN with an uncertainty of 0.72 nT and a spatial resolution of 12.8 mm. We evaluate the quadratic Zeeman-effect-induced gravity measurement error in GAIN as 2.04 μ Gal . The methods shown in this paper are important for precisely mapping the absolute magnetic field in vacuum and reducing the quadratic Zeeman-effect-induced systematic error in Raman transition-based precision measurements, such as atomic interferometer gravimeters.

Decision Making Under Uncertainty

DTIC Science & Technology

2010-11-01

A sound approach to rational decision making requires a decision maker to establish decision objectives, identify alternatives, and evaluate those...often violate the axioms of rationality when making decisions under uncertainty. The systematic description of such observations may lead to the...which leads to “anchoring” on the initial value. The fact that individuals have been shown to deviate from rationality when making decisions

Calibration and Validation of Landsat Tree Cover in the Taiga-Tundra Ecotone

NASA Technical Reports Server (NTRS)

Montesano, Paul Mannix; Neigh, Christopher S. R.; Sexton, Joseph; Feng, Min; Channan, Saurabh; Ranson, Kenneth J.; Townshend, John R.

2016-01-01

Monitoring current forest characteristics in the taiga-tundra ecotone (TTE) at multiple scales is critical for understanding its vulnerability to structural changes. A 30 m spatial resolution Landsat-based tree canopy cover map has been calibrated and validated in the TTE with reference tree cover data from airborne LiDAR and high resolution spaceborne images across the full range of boreal forest tree cover. This domain-specific calibration model used estimates of forest height to determine reference forest cover that best matched Landsat estimates. The model removed the systematic under-estimation of tree canopy cover greater than 80% and indicated that Landsat estimates of tree canopy cover more closely matched canopies at least 2 m in height rather than 5 m. The validation improved estimates of uncertainty in tree canopy cover in discontinuous TTE forests for three temporal epochs (2000, 2005, and 2010) by reducing systematic errors, leading to increases in tree canopy cover uncertainty. Average pixel-level uncertainties in tree canopy cover were 29.0%, 27.1% and 31.1% for the 2000, 2005 and 2010 epochs, respectively. Maps from these calibrated data improve the uncertainty associated with Landsat tree canopy cover estimates in the discontinuous forests of the circumpolar TTE.

Optimal integrated abundances for chemical tagging of extragalactic globular clusters

NASA Astrophysics Data System (ADS)

Sakari, Charli M.; Venn, Kim; Shetrone, Matthew; Dotter, Aaron; Mackey, Dougal

2014-09-01

High-resolution integrated light (IL) spectroscopy provides detailed abundances of distant globular clusters whose stars cannot be resolved. Abundance comparisons with other systems (e.g. for chemical tagging) require understanding the systematic offsets that can occur between clusters, such as those due to uncertainties in the underlying stellar population. This paper analyses high-resolution IL spectra of the Galactic globular clusters 47 Tuc, M3, M13, NGC 7006, and M15 to (1) quantify potential systematic uncertainties in Fe, Ca, Ti, Ni, Ba, and Eu and (2) identify the most stable abundance ratios that will be useful in future analyses of unresolved targets. When stellar populations are well modelled, uncertainties are ˜0.1-0.2 dex based on sensitivities to the atmospheric parameters alone; in the worst-case scenarios, uncertainties can rise to 0.2-0.4 dex. The [Ca I/Fe I] ratio is identified as the optimal integrated [α/Fe] indicator (with offsets ≲ 0.1 dex), while [Ni I/Fe I] is also extremely stable to within ≲ 0.1 dex. The [Ba II/Eu II] ratios are also stable when the underlying populations are well modelled and may also be useful for chemical tagging.

A systematic uncertainty analysis for liner impedance eduction technology

NASA Astrophysics Data System (ADS)

Zhou, Lin; Bodén, Hans

2015-11-01

The so-called impedance eduction technology is widely used for obtaining acoustic properties of liners used in aircraft engines. The measurement uncertainties for this technology are still not well understood though it is essential for data quality assessment and model validation. A systematic framework based on multivariate analysis is presented in this paper to provide 95 percent confidence interval uncertainty estimates in the process of impedance eduction. The analysis is made using a single mode straightforward method based on transmission coefficients involving the classic Ingard-Myers boundary condition. The multivariate technique makes it possible to obtain an uncertainty analysis for the possibly correlated real and imaginary parts of the complex quantities. The results show that the errors in impedance results at low frequency mainly depend on the variability of transmission coefficients, while the mean Mach number accuracy is the most important source of error at high frequencies. The effect of Mach numbers used in the wave dispersion equation and in the Ingard-Myers boundary condition has been separated for comparison of the outcome of impedance eduction. A local Mach number based on friction velocity is suggested as a way to reduce the inconsistencies found when estimating impedance using upstream and downstream acoustic excitation.

What is the clinical effectiveness and cost-effectiveness of conservative interventions for tendinopathy? An overview of systematic reviews of clinical effectiveness and systematic review of economic evaluations.

PubMed

Long, Linda; Briscoe, Simon; Cooper, Chris; Hyde, Chris; Crathorne, Louise

2015-01-01

Lateral elbow tendinopathy (LET) is a common complaint causing characteristic pain in the lateral elbow and upper forearm, and tenderness of the forearm extensor muscles. It is thought to be an overuse injury and can have a major impact on the patient's social and professional life. The condition is challenging to treat and prone to recurrent episodes. The average duration of a typical episode ranges from 6 to 24 months, with most (89%) reporting recovery by 1 year. This systematic review aims to summarise the evidence concerning the clinical effectiveness and cost-effectiveness of conservative interventions for LET. A comprehensive search was conducted from database inception to 2012 in a range of databases including MEDLINE, EMBASE and Cochrane Databases. We conducted an overview of systematic reviews to summarise the current evidence concerning the clinical effectiveness and a systematic review for the cost-effectiveness of conservative interventions for LET. We identified additional randomised controlled trials (RCTs) that could contribute further evidence to existing systematic reviews. We searched MEDLINE, EMBASE, Allied and Complementary Medicine Database, Cumulative Index to Nursing and Allied Health Literature, Web of Science, The Cochrane Library and other important databases from inception to January 2013. A total of 29 systematic reviews published since 2003 matched our inclusion criteria. These were quality appraised using the Assessment of Multiple Systematic Reviews (AMSTAR) checklist; five were considered high quality and evaluated using a Grading of Recommendations, Assessment, Development and Evaluation approach. A total of 36 RCTs were identified that were not included in a systematic review and 29 RCTs were identified that had only been evaluated in an included systematic review of intermediate/low quality. These were then mapped to existing systematic reviews where further evidence could provide updates. Two economic evaluations were identified. The summary of findings from the review was based only on high-quality evidence (scoring of > 5 AMSTAR). Other limitations were that identified RCTs were not quality appraised and dichotomous outcomes were also not considered. Economic evaluations took effectiveness estimates from trials that had small sample sizes leading to uncertainty surrounding the effect sizes reported. This, in turn, led to uncertainty of the reported cost-effectiveness and, as such, no robust recommendations could be made in this respect. Clinical effectiveness evidence from the high-quality systematic reviews identified in this overview continues to suggest uncertainty as to the effectiveness of many conservative interventions for the treatment of LET. Although new RCT evidence has been identified with either placebo or active controls, there is uncertainty as to the size of effects reported within them because of the small sample size. Conclusions regarding cost-effectiveness are also unclear. We consider that, although updated or new systematic reviews may also be of value, the primary focus of future work should be on conducting large-scale, good-quality clinical trials using a core set of outcome measures (for defined time points) and appropriate follow-up. Subgroup analysis of existing RCT data may be beneficial to ascertain whether or not certain patient groups are more likely to respond to treatments. This study is registered as PROSPERO CRD42013003593. The National Institute for Health Research Health Technology Assessment programme.

Uncertainties in scaling factors for ab initio vibrational zero-point energies

NASA Astrophysics Data System (ADS)

Irikura, Karl K.; Johnson, Russell D.; Kacker, Raghu N.; Kessel, Rüdiger

2009-03-01

Vibrational zero-point energies (ZPEs) determined from ab initio calculations are often scaled by empirical factors. An empirical scaling factor partially compensates for the effects arising from vibrational anharmonicity and incomplete treatment of electron correlation. These effects are not random but are systematic. We report scaling factors for 32 combinations of theory and basis set, intended for predicting ZPEs from computed harmonic frequencies. An empirical scaling factor carries uncertainty. We quantify and report, for the first time, the uncertainties associated with scaling factors for ZPE. The uncertainties are larger than generally acknowledged; the scaling factors have only two significant digits. For example, the scaling factor for B3LYP/6-31G(d) is 0.9757±0.0224 (standard uncertainty). The uncertainties in the scaling factors lead to corresponding uncertainties in predicted ZPEs. The proposed method for quantifying the uncertainties associated with scaling factors is based upon the Guide to the Expression of Uncertainty in Measurement, published by the International Organization for Standardization. We also present a new reference set of 60 diatomic and 15 polyatomic "experimental" ZPEs that includes estimated uncertainties.

Uncertainty Analysis in 3D Equilibrium Reconstruction

DOE PAGES

Cianciosa, Mark R.; Hanson, James D.; Maurer, David A.

2018-02-21

Reconstruction is an inverse process where a parameter space is searched to locate a set of parameters with the highest probability of describing experimental observations. Due to systematic errors and uncertainty in experimental measurements, this optimal set of parameters will contain some associated uncertainty. This uncertainty in the optimal parameters leads to uncertainty in models derived using those parameters. V3FIT is a three-dimensional (3D) equilibrium reconstruction code that propagates uncertainty from the input signals, to the reconstructed parameters, and to the final model. Here in this paper, we describe the methods used to propagate uncertainty in V3FIT. Using the resultsmore » of whole shot 3D equilibrium reconstruction of the Compact Toroidal Hybrid, this propagated uncertainty is validated against the random variation in the resulting parameters. Two different model parameterizations demonstrate how the uncertainty propagation can indicate the quality of a reconstruction. As a proxy for random sampling, the whole shot reconstruction results in a time interval that will be used to validate the propagated uncertainty from a single time slice.« less

Uncertainty Analysis in 3D Equilibrium Reconstruction

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

Cianciosa, Mark R.; Hanson, James D.; Maurer, David A.

Reconstruction is an inverse process where a parameter space is searched to locate a set of parameters with the highest probability of describing experimental observations. Due to systematic errors and uncertainty in experimental measurements, this optimal set of parameters will contain some associated uncertainty. This uncertainty in the optimal parameters leads to uncertainty in models derived using those parameters. V3FIT is a three-dimensional (3D) equilibrium reconstruction code that propagates uncertainty from the input signals, to the reconstructed parameters, and to the final model. Here in this paper, we describe the methods used to propagate uncertainty in V3FIT. Using the resultsmore » of whole shot 3D equilibrium reconstruction of the Compact Toroidal Hybrid, this propagated uncertainty is validated against the random variation in the resulting parameters. Two different model parameterizations demonstrate how the uncertainty propagation can indicate the quality of a reconstruction. As a proxy for random sampling, the whole shot reconstruction results in a time interval that will be used to validate the propagated uncertainty from a single time slice.« less

A blinded determination of H0 from low-redshift Type Ia supernovae, calibrated by Cepheid variables

NASA Astrophysics Data System (ADS)

Zhang, Bonnie R.; Childress, Michael J.; Davis, Tamara M.; Karpenka, Natallia V.; Lidman, Chris; Schmidt, Brian P.; Smith, Mathew

2017-10-01

Presently, a >3σ tension exists between values of the Hubble constant H0 derived from analysis of fluctuations in the cosmic microwave background by Planck, and local measurements of the expansion using calibrators of Type Ia supernovae (SNe Ia). We perform a blinded re-analysis of Riess et al. (2011) to measure H0 from low-redshift SNe Ia, calibrated by Cepheid variables and geometric distances including to NGC 4258. This paper is a demonstration of techniques to be applied to the Riess et al. (2016) data. Our end-to-end analysis starts from available Harvard -Smithsonian Center for Astrophysics (CfA3) and Lick Observatory Supernova Search (LOSS) photometries, providing an independent validation of Riess et al. (2011). We obscure the value of H0 throughout our analysis and the first stage of the referee process, because calibration of SNe Ia requires a series of often subtle choices, and the potential for results to be affected by human bias is significant. Our analysis departs from that of Riess et al. (2011) by incorporating the covariance matrix method adopted in Supernova Legacy Survey and Joint Lightcurve Analysis to quantify SN Ia systematics, and by including a simultaneous fit of all SN Ia and Cepheid data. We find H_0 = 72.5 ± 3.1 ({stat}) ± 0.77 ({sys}) km s-1 Mpc-1with a three-galaxy (NGC 4258+LMC+MW) anchor. The relative uncertainties are 4.3 per cent statistical, 1.1 per cent systematic, and 4.4 per cent total, larger than in Riess et al. (2011) (3.3 per cent total) and the Efstathiou (2014) re-analysis (3.4 per cent total). Our error budget for H0 is dominated by statistical errors due to the small size of the SN sample, whilst the systematic contribution is dominated by variation in the Cepheid fits, and for the SNe Ia, uncertainties in the host galaxy mass dependence and Malmquist bias.

Approaches to Refining Estimates of Global Burden and Economics of Dengue

PubMed Central

Shepard, Donald S.; Undurraga, Eduardo A.; Betancourt-Cravioto, Miguel; Guzmán, María G.; Halstead, Scott B.; Harris, Eva; Mudin, Rose Nani; Murray, Kristy O.; Tapia-Conyer, Roberto; Gubler, Duane J.

2014-01-01

Dengue presents a formidable and growing global economic and disease burden, with around half the world's population estimated to be at risk of infection. There is wide variation and substantial uncertainty in current estimates of dengue disease burden and, consequently, on economic burden estimates. Dengue disease varies across time, geography and persons affected. Variations in the transmission of four different viruses and interactions among vector density and host's immune status, age, pre-existing medical conditions, all contribute to the disease's complexity. This systematic review aims to identify and examine estimates of dengue disease burden and costs, discuss major sources of uncertainty, and suggest next steps to improve estimates. Economic analysis of dengue is mainly concerned with costs of illness, particularly in estimating total episodes of symptomatic dengue. However, national dengue disease reporting systems show a great diversity in design and implementation, hindering accurate global estimates of dengue episodes and country comparisons. A combination of immediate, short-, and long-term strategies could substantially improve estimates of disease and, consequently, of economic burden of dengue. Suggestions for immediate implementation include refining analysis of currently available data to adjust reported episodes and expanding data collection in empirical studies, such as documenting the number of ambulatory visits before and after hospitalization and including breakdowns by age. Short-term recommendations include merging multiple data sources, such as cohort and surveillance data to evaluate the accuracy of reporting rates (by health sector, treatment, severity, etc.), and using covariates to extrapolate dengue incidence to locations with no or limited reporting. Long-term efforts aim at strengthening capacity to document dengue transmission using serological methods to systematically analyze and relate to epidemiologic data. As promising tools for diagnosis, vaccination, vector control, and treatment are being developed, these recommended steps should improve objective, systematic measures of dengue burden to strengthen health policy decisions. PMID:25412506

Approaches to refining estimates of global burden and economics of dengue.

PubMed

Shepard, Donald S; Undurraga, Eduardo A; Betancourt-Cravioto, Miguel; Guzmán, María G; Halstead, Scott B; Harris, Eva; Mudin, Rose Nani; Murray, Kristy O; Tapia-Conyer, Roberto; Gubler, Duane J

2014-11-01

Dengue presents a formidable and growing global economic and disease burden, with around half the world's population estimated to be at risk of infection. There is wide variation and substantial uncertainty in current estimates of dengue disease burden and, consequently, on economic burden estimates. Dengue disease varies across time, geography and persons affected. Variations in the transmission of four different viruses and interactions among vector density and host's immune status, age, pre-existing medical conditions, all contribute to the disease's complexity. This systematic review aims to identify and examine estimates of dengue disease burden and costs, discuss major sources of uncertainty, and suggest next steps to improve estimates. Economic analysis of dengue is mainly concerned with costs of illness, particularly in estimating total episodes of symptomatic dengue. However, national dengue disease reporting systems show a great diversity in design and implementation, hindering accurate global estimates of dengue episodes and country comparisons. A combination of immediate, short-, and long-term strategies could substantially improve estimates of disease and, consequently, of economic burden of dengue. Suggestions for immediate implementation include refining analysis of currently available data to adjust reported episodes and expanding data collection in empirical studies, such as documenting the number of ambulatory visits before and after hospitalization and including breakdowns by age. Short-term recommendations include merging multiple data sources, such as cohort and surveillance data to evaluate the accuracy of reporting rates (by health sector, treatment, severity, etc.), and using covariates to extrapolate dengue incidence to locations with no or limited reporting. Long-term efforts aim at strengthening capacity to document dengue transmission using serological methods to systematically analyze and relate to epidemiologic data. As promising tools for diagnosis, vaccination, vector control, and treatment are being developed, these recommended steps should improve objective, systematic measures of dengue burden to strengthen health policy decisions.

An optical lattice clock with accuracy and stability at the 10(-18) level.

PubMed

Bloom, B J; Nicholson, T L; Williams, J R; Campbell, S L; Bishof, M; Zhang, X; Zhang, W; Bromley, S L; Ye, J

2014-02-06

Progress in atomic, optical and quantum science has led to rapid improvements in atomic clocks. At the same time, atomic clock research has helped to advance the frontiers of science, affecting both fundamental and applied research. The ability to control quantum states of individual atoms and photons is central to quantum information science and precision measurement, and optical clocks based on single ions have achieved the lowest systematic uncertainty of any frequency standard. Although many-atom lattice clocks have shown advantages in measurement precision over trapped-ion clocks, their accuracy has remained 16 times worse. Here we demonstrate a many-atom system that achieves an accuracy of 6.4 × 10(-18), which is not only better than a single-ion-based clock, but also reduces the required measurement time by two orders of magnitude. By systematically evaluating all known sources of uncertainty, including in situ monitoring of the blackbody radiation environment, we improve the accuracy of optical lattice clocks by a factor of 22. This single clock has simultaneously achieved the best known performance in the key characteristics necessary for consideration as a primary standard-stability and accuracy. More stable and accurate atomic clocks will benefit a wide range of fields, such as the realization and distribution of SI units, the search for time variation of fundamental constants, clock-based geodesy and other precision tests of the fundamental laws of nature. This work also connects to the development of quantum sensors and many-body quantum state engineering (such as spin squeezing) to advance measurement precision beyond the standard quantum limit.

The GeV Excess Shining Through: Background Systematics for the Inner Galaxy Analysis

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

Calore, Francesca; Cholis, Ilias; Weniger, Christoph

2015-02-10

Recently, a spatially extended excess of gamma rays collected by the Fermi-LAT from the inner region of the Milky Way has been detected by different groups and with increasingly sophisticated techniques. Yet, any final conclusion about the morphology and spectral properties of such an extended diffuse emission are subject to a number of potentially critical uncertainties, related to the high density of cosmic rays, gas, magnetic fields and abundance of point sources. We will present a thorough study of the systematic uncertainties related to the modelling of diffuse background and to the propagation of cosmic rays in the inner partmore » of our Galaxy. We will test a large set of models for the Galactic diffuse emission, generated by varying the propagation parameters within extreme conditions. By using those models in the fit of Fermi-LAT data as Galactic foreground, we will show that the gamma-ray excess survives and we will quantify the uncertainties on the excess emission morphology and energy spectrum.« less

Resolving the neutron lifetime puzzle

NASA Astrophysics Data System (ADS)

Mumm, Pieter

2018-05-01

Free electrons and protons are stable, but outside atomic nuclei, free neutrons decay into a proton, electron, and antineutrino through the weak interaction, with a lifetime of ∼880 s (see the figure). The most precise measurements have stated uncertainties below 1 s (0.1%), but different techniques, although internally consistent, disagree by 4 standard deviations given the quoted uncertainties. Resolving this “neutron lifetime puzzle” has spawned much experimental effort as well as exotic theoretical mechanisms, thus far without a clear explanation. On page 627 of this issue, Pattie et al. (1) present the most precise measurement of the neutron lifetime to date. A new method of measuring trapped neutrons in situ allows a more detailed exploration of one of the more pernicious systematic effects in neutron traps, neutron phase-space evolution (the changing orbits of neutrons in the trap), than do previous methods. The precision achieved, combined with a very different set of systematic uncertainties, gives hope that experiments such as this one can help resolve the current situation with the neutron lifetime.

Systematic evaluation of an atomic clock at 2 × 10−18 total uncertainty

PubMed Central

Nicholson, T.L.; Campbell, S.L.; Hutson, R.B.; Marti, G.E.; Bloom, B.J.; McNally, R.L.; Zhang, W.; Barrett, M.D.; Safronova, M.S.; Strouse, G.F.; Tew, W.L.; Ye, J.

2015-01-01

The pursuit of better atomic clocks has advanced many research areas, providing better quantum state control, new insights in quantum science, tighter limits on fundamental constant variation and improved tests of relativity. The record for the best stability and accuracy is currently held by optical lattice clocks. Here we take an important step towards realizing the full potential of a many-particle clock with a state-of-the-art stable laser. Our 87Sr optical lattice clock now achieves fractional stability of 2.2 × 10−16 at 1 s. With this improved stability, we perform a new accuracy evaluation of our clock, reducing many systematic uncertainties that limited our previous measurements, such as those in the lattice ac Stark shift, the atoms' thermal environment and the atomic response to room-temperature blackbody radiation. Our combined measurements have reduced the total uncertainty of the JILA Sr clock to 2.1 × 10−18 in fractional frequency units. PMID:25898253

Quantifying Errors in TRMM-Based Multi-Sensor QPE Products Over Land in Preparation for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Tian, Yudong

2011-01-01

Determining uncertainties in satellite-based multi-sensor quantitative precipitation estimates over land of fundamental importance to both data producers and hydro climatological applications. ,Evaluating TRMM-era products also lays the groundwork and sets the direction for algorithm and applications development for future missions including GPM. QPE uncertainties result mostly from the interplay of systematic errors and random errors. In this work, we will synthesize our recent results quantifying the error characteristics of satellite-based precipitation estimates. Both systematic errors and total uncertainties have been analyzed for six different TRMM-era precipitation products (3B42, 3B42RT, CMORPH, PERSIANN, NRL and GSMap). For systematic errors, we devised an error decomposition scheme to separate errors in precipitation estimates into three independent components, hit biases, missed precipitation and false precipitation. This decomposition scheme reveals hydroclimatologically-relevant error features and provides a better link to the error sources than conventional analysis, because in the latter these error components tend to cancel one another when aggregated or averaged in space or time. For the random errors, we calculated the measurement spread from the ensemble of these six quasi-independent products, and thus produced a global map of measurement uncertainties. The map yields a global view of the error characteristics and their regional and seasonal variations, reveals many undocumented error features over areas with no validation data available, and provides better guidance to global assimilation of satellite-based precipitation data. Insights gained from these results and how they could help with GPM will be highlighted.

Optimization Under Uncertainty of Site-Specific Turbine Configurations

NASA Astrophysics Data System (ADS)

Quick, J.; Dykes, K.; Graf, P.; Zahle, F.

2016-09-01

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. If there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtained with increasing risk aversion on the part of the designer.

Efficiently estimating salmon escapement uncertainty using systematically sampled data

USGS Publications Warehouse

Reynolds, Joel H.; Woody, Carol Ann; Gove, Nancy E.; Fair, Lowell F.

2007-01-01

Fish escapement is generally monitored using nonreplicated systematic sampling designs (e.g., via visual counts from towers or hydroacoustic counts). These sampling designs support a variety of methods for estimating the variance of the total escapement. Unfortunately, all the methods give biased results, with the magnitude of the bias being determined by the underlying process patterns. Fish escapement commonly exhibits positive autocorrelation and nonlinear patterns, such as diurnal and seasonal patterns. For these patterns, poor choice of variance estimator can needlessly increase the uncertainty managers have to deal with in sustaining fish populations. We illustrate the effect of sampling design and variance estimator choice on variance estimates of total escapement for anadromous salmonids from systematic samples of fish passage. Using simulated tower counts of sockeye salmon Oncorhynchus nerka escapement on the Kvichak River, Alaska, five variance estimators for nonreplicated systematic samples were compared to determine the least biased. Using the least biased variance estimator, four confidence interval estimators were compared for expected coverage and mean interval width. Finally, five systematic sampling designs were compared to determine the design giving the smallest average variance estimate for total annual escapement. For nonreplicated systematic samples of fish escapement, all variance estimators were positively biased. Compared to the other estimators, the least biased estimator reduced bias by, on average, from 12% to 98%. All confidence intervals gave effectively identical results. Replicated systematic sampling designs consistently provided the smallest average estimated variance among those compared.

Accounting for Parameter Uncertainty in Complex Atmospheric Models, With an Application to Greenhouse Gas Emissions Evaluation

NASA Astrophysics Data System (ADS)

Swallow, B.; Rigby, M. L.; Rougier, J.; Manning, A.; Thomson, D.; Webster, H. N.; Lunt, M. F.; O'Doherty, S.

2016-12-01

In order to understand underlying processes governing environmental and physical phenomena, a complex mathematical model is usually required. However, there is an inherent uncertainty related to the parameterisation of unresolved processes in these simulators. Here, we focus on the specific problem of accounting for uncertainty in parameter values in an atmospheric chemical transport model. Systematic errors introduced by failing to account for these uncertainties have the potential to have a large effect on resulting estimates in unknown quantities of interest. One approach that is being increasingly used to address this issue is known as emulation, in which a large number of forward runs of the simulator are carried out, in order to approximate the response of the output to changes in parameters. However, due to the complexity of some models, it is often unfeasible to run large numbers of training runs that is usually required for full statistical emulators of the environmental processes. We therefore present a simplified model reduction method for approximating uncertainties in complex environmental simulators without the need for very large numbers of training runs. We illustrate the method through an application to the Met Office's atmospheric transport model NAME. We show how our parameter estimation framework can be incorporated into a hierarchical Bayesian inversion, and demonstrate the impact on estimates of UK methane emissions, using atmospheric mole fraction data. We conclude that accounting for uncertainties in the parameterisation of complex atmospheric models is vital if systematic errors are to be minimized and all relevant uncertainties accounted for. We also note that investigations of this nature can prove extremely useful in highlighting deficiencies in the simulator that might otherwise be missed.

Probabilistic risk assessment for CO2 storage in geological formations: robust design and support for decision making under uncertainty

NASA Astrophysics Data System (ADS)

Oladyshkin, Sergey; Class, Holger; Helmig, Rainer; Nowak, Wolfgang

2010-05-01

CO2 storage in geological formations is currently being discussed intensively as a technology for mitigating CO2 emissions. However, any large-scale application requires a thorough analysis of the potential risks. Current numerical simulation models are too expensive for probabilistic risk analysis and for stochastic approaches based on brute-force repeated simulation. Even single deterministic simulations may require parallel high-performance computing. The multiphase flow processes involved are too non-linear for quasi-linear error propagation and other simplified stochastic tools. As an alternative approach, we propose a massive stochastic model reduction based on the probabilistic collocation method. The model response is projected onto a orthogonal basis of higher-order polynomials to approximate dependence on uncertain parameters (porosity, permeability etc.) and design parameters (injection rate, depth etc.). This allows for a non-linear propagation of model uncertainty affecting the predicted risk, ensures fast computation and provides a powerful tool for combining design variables and uncertain variables into one approach based on an integrative response surface. Thus, the design task of finding optimal injection regimes explicitly includes uncertainty, which leads to robust designs of the non-linear system that minimize failure probability and provide valuable support for risk-informed management decisions. We validate our proposed stochastic approach by Monte Carlo simulation using a common 3D benchmark problem (Class et al. Computational Geosciences 13, 2009). A reasonable compromise between computational efforts and precision was reached already with second-order polynomials. In our case study, the proposed approach yields a significant computational speedup by a factor of 100 compared to Monte Carlo simulation. We demonstrate that, due to the non-linearity of the flow and transport processes during CO2 injection, including uncertainty in the analysis leads to a systematic and significant shift of predicted leakage rates towards higher values compared with deterministic simulations, affecting both risk estimates and the design of injection scenarios. This implies that, neglecting uncertainty can be a strong simplification for modeling CO2 injection, and the consequences can be stronger than when neglecting several physical phenomena (e.g. phase transition, convective mixing, capillary forces etc.). The authors would like to thank the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/1) at the University of Stuttgart. Keywords: polynomial chaos; CO2 storage; multiphase flow; porous media; risk assessment; uncertainty; integrative response surfaces

Dealing with uncertainties in environmental burden of disease assessment

PubMed Central

2009-01-01

Disability Adjusted Life Years (DALYs) combine the number of people affected by disease or mortality in a population and the duration and severity of their condition into one number. The environmental burden of disease is the number of DALYs that can be attributed to environmental factors. Environmental burden of disease estimates enable policy makers to evaluate, compare and prioritize dissimilar environmental health problems or interventions. These estimates often have various uncertainties and assumptions which are not always made explicit. Besides statistical uncertainty in input data and parameters – which is commonly addressed – a variety of other types of uncertainties may substantially influence the results of the assessment. We have reviewed how different types of uncertainties affect environmental burden of disease assessments, and we give suggestions as to how researchers could address these uncertainties. We propose the use of an uncertainty typology to identify and characterize uncertainties. Finally, we argue that uncertainties need to be identified, assessed, reported and interpreted in order for assessment results to adequately support decision making. PMID:19400963

Multivariate Probabilistic Analysis of an Hydrological Model

NASA Astrophysics Data System (ADS)

Franceschini, Samuela; Marani, Marco

2010-05-01

Model predictions derived based on rainfall measurements and hydrological model results are often limited by the systematic error of measuring instruments, by the intrinsic variability of the natural processes and by the uncertainty of the mathematical representation. We propose a means to identify such sources of uncertainty and to quantify their effects based on point-estimate approaches, as a valid alternative to cumbersome Montecarlo methods. We present uncertainty analyses on the hydrologic response to selected meteorological events, in the mountain streamflow-generating portion of the Brenta basin at Bassano del Grappa, Italy. The Brenta river catchment has a relatively uniform morphology and quite a heterogeneous rainfall-pattern. In the present work, we evaluate two sources of uncertainty: data uncertainty (the uncertainty due to data handling and analysis) and model uncertainty (the uncertainty related to the formulation of the model). We thus evaluate the effects of the measurement error of tipping-bucket rain gauges, the uncertainty in estimating spatially-distributed rainfall through block kriging, and the uncertainty associated with estimated model parameters. To this end, we coupled a deterministic model based on the geomorphological theory of the hydrologic response to probabilistic methods. In particular we compare the results of Monte Carlo Simulations (MCS) to the results obtained, in the same conditions, using Li's Point Estimate Method (LiM). The LiM is a probabilistic technique that approximates the continuous probability distribution function of the considered stochastic variables by means of discrete points and associated weights. This allows to satisfactorily reproduce results with only few evaluations of the model function. The comparison between the LiM and MCS results highlights the pros and cons of using an approximating method. LiM is less computationally demanding than MCS, but has limited applicability especially when the model response is highly nonlinear. Higher-order approximations can provide more accurate estimations, but reduce the numerical advantage of the LiM. The results of the uncertainty analysis identify the main sources of uncertainty in the computation of river discharge. In this particular case the spatial variability of rainfall and the model parameters uncertainty are shown to have the greatest impact on discharge evaluation. This, in turn, highlights the need to support any estimated hydrological response with probability information and risk analysis results in order to provide a robust, systematic framework for decision making.

Error and Uncertainty Quantification in the Numerical Simulation of Complex Fluid Flows

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2010-01-01

The failure of numerical simulation to predict physical reality is often a direct consequence of the compounding effects of numerical error arising from finite-dimensional approximation and physical model uncertainty resulting from inexact knowledge and/or statistical representation. In this topical lecture, we briefly review systematic theories for quantifying numerical errors and restricted forms of model uncertainty occurring in simulations of fluid flow. A goal of this lecture is to elucidate both positive and negative aspects of applying these theories to practical fluid flow problems. Finite-element and finite-volume calculations of subsonic and hypersonic fluid flow are presented to contrast the differing roles of numerical error and model uncertainty. for these problems.

The deuteron-radius puzzle is alive: A new analysis of nuclear structure uncertainties

NASA Astrophysics Data System (ADS)

Hernandez, O. J.; Ekström, A.; Nevo Dinur, N.; Ji, C.; Bacca, S.; Barnea, N.

2018-03-01

To shed light on the deuteron radius puzzle we analyze the theoretical uncertainties of the nuclear structure corrections to the Lamb shift in muonic deuterium. We find that the discrepancy between the calculated two-photon exchange correction and the corresponding experimentally inferred value by Pohl et al. [1] remain. The present result is consistent with our previous estimate, although the discrepancy is reduced from 2.6 σ to about 2 σ. The error analysis includes statistic as well as systematic uncertainties stemming from the use of nucleon-nucleon interactions derived from chiral effective field theory at various orders. We therefore conclude that nuclear theory uncertainty is more likely not the source of the discrepancy.

On the uncertainty of phenological responses to climate change and its implication for terrestrial biosphere models

NASA Astrophysics Data System (ADS)

Migliavacca, M.; Sonnentag, O.; Keenan, T. F.; Cescatti, A.; O'Keefe, J.; Richardson, A. D.

2012-01-01

Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate systems through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Land surface models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we analyzed the Harvard Forest phenology record to investigate and characterize the sources of uncertainty in phenological forecasts and the subsequent impacts on model forecasts of carbon and water cycling in the future. Using a model-data fusion approach, we combined information from 20 yr of phenological observations of 11 North American woody species with 12 phenological models of different complexity to predict leaf bud-burst. The evaluation of different phenological models indicated support for spring warming models with photoperiod limitations and, though to a lesser extent, to chilling models based on the alternating model structure. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2099 using 2 different IPCC climate scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% CI: 2.4 day century-1 for scenario B1 and 4.5 day century-1 for A1fi), whereas driver uncertainty was the largest (up to 8.4 day century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied somewhat among models (±7.7 day century-1 for A1fi, ±3.6 day century-1 for B1). The forecast sensitivity of bud-burst to temperature (i.e. days bud-burst advanced per degree of warming) varied between 2.2 day °C-1 and 5.2 day °C-1 depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated carbon and water fluxes using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of the seasonality of processes, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and evapotranspiration (ET) of 9.6% and 2.9% respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET. For phenology models, differences among future climate scenarios represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, uncertainties related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.

Onward through the Fog: Uncertainty and Management Adaptation in Systems Analysis and Design

DTIC Science & Technology

1990-07-01

has fallen into stereotyped problem formulations and analytical ap- proaches. In particular, treatments of uncertainty are typically quite incomplete...and often conceptually wrong. This report argues that these shortcomings produce pervasive systematic biases in analyses. Problem formulations ...capability were lost. The expected number of aircraft that would not be fully mission capable thirty days later was roughly twice the num - ber

Lidar backscattering measurements of background stratospheric aerosols

NASA Technical Reports Server (NTRS)

Remsberg, E. E.; Northam, G. B.; Butler, C. F.

1979-01-01

A comparative lidar-dustsonde experiment was conducted in San Angelo, Texas, in May 1974 in order to estimate the uncertainties in stratospheric-aerosol backscatter for the NASA Langley 48-inch lidar system. The lidar calibration and data-analysis procedures are discussed. Results from the Texas experiment indicate random and systematic uncertainties of 35 and 63 percent, respectively, in backscatter from a background stratospheric-aerosol layer at 20 km.

The propagation of wind errors through ocean wave hindcasts

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

Holthuijsen, L.H.; Booij, N.; Bertotti, L.

1996-08-01

To estimate uncertainties in wave forecast and hindcasts, computations have been carried out for a location in the Mediterranean Sea using three different analyses of one historic wind field. These computations involve a systematic sensitivity analysis and estimated wind field errors. This technique enables a wave modeler to estimate such uncertainties in other forecasts and hindcasts if only one wind analysis is available.

Conflict or Caveats? Effects of Media Portrayals of Scientific Uncertainty on Audience Perceptions of New Technologies.

PubMed

Binder, Andrew R; Hillback, Elliott D; Brossard, Dominique

2016-04-01

Research indicates that uncertainty in science news stories affects public assessment of risk and uncertainty. However, the form in which uncertainty is presented may also affect people's risk and uncertainty assessments. For example, a news story that features an expert discussing both what is known and what is unknown about a topic may convey a different form of scientific uncertainty than a story that features two experts who hold conflicting opinions about the status of scientific knowledge of the topic, even when both stories contain the same information about knowledge and its boundaries. This study focuses on audience uncertainty and risk perceptions regarding the emerging science of nanotechnology by manipulating whether uncertainty in a news story about potential risks is attributed to expert sources in the form of caveats (individual uncertainty) or conflicting viewpoints (collective uncertainty). Results suggest that the type of uncertainty portrayed does not impact audience feelings of uncertainty or risk perceptions directly. Rather, the presentation of the story influences risk perceptions only among those who are highly deferent to scientific authority. Implications for risk communication theory and practice are discussed. © 2015 Society for Risk Analysis.

Drought Persistence in Models and Observations

NASA Astrophysics Data System (ADS)

Moon, Heewon; Gudmundsson, Lukas; Seneviratne, Sonia

2017-04-01

Many regions of the world have experienced drought events that persisted several years and caused substantial economic and ecological impacts in the 20th century. However, it remains unclear whether there are significant trends in the frequency or severity of these prolonged drought events. In particular, an important issue is linked to systematic biases in the representation of persistent drought events in climate models, which impedes analysis related to the detection and attribution of drought trends. This study assesses drought persistence errors in global climate model (GCM) simulations from the 5th phase of Coupled Model Intercomparison Project (CMIP5), in the period of 1901-2010. The model simulations are compared with five gridded observational data products. The analysis focuses on two aspects: the identification of systematic biases in the models and the partitioning of the spread of drought-persistence-error into four possible sources of uncertainty: model uncertainty, observation uncertainty, internal climate variability and the estimation error of drought persistence. We use monthly and yearly dry-to-dry transition probabilities as estimates for drought persistence with drought conditions defined as negative precipitation anomalies. For both time scales we find that most model simulations consistently underestimated drought persistence except in a few regions such as India and Eastern South America. Partitioning the spread of the drought-persistence-error shows that at the monthly time scale model uncertainty and observation uncertainty are dominant, while the contribution from internal variability does play a minor role in most cases. At the yearly scale, the spread of the drought-persistence-error is dominated by the estimation error, indicating that the partitioning is not statistically significant, due to a limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current climate models and highlight the main contributors of uncertainty of drought-persistence-error. Future analyses will focus on investigating the temporal propagation of drought persistence to better understand the causes for the identified errors in the representation of drought persistence in state-of-the-art climate models.

Parameterization of Model Validating Sets for Uncertainty Bound Optimizations. Revised

NASA Technical Reports Server (NTRS)

Lim, K. B.; Giesy, D. P.

2000-01-01

Given measurement data, a nominal model and a linear fractional transformation uncertainty structure with an allowance on unknown but bounded exogenous disturbances, easily computable tests for the existence of a model validating uncertainty set are given. Under mild conditions, these tests are necessary and sufficient for the case of complex, nonrepeated, block-diagonal structure. For the more general case which includes repeated and/or real scalar uncertainties, the tests are only necessary but become sufficient if a collinearity condition is also satisfied. With the satisfaction of these tests, it is shown that a parameterization of all model validating sets of plant models is possible. The new parameterization is used as a basis for a systematic way to construct or perform uncertainty tradeoff with model validating uncertainty sets which have specific linear fractional transformation structure for use in robust control design and analysis. An illustrative example which includes a comparison of candidate model validating sets is given.

Improving the Calibration of the SN Ia Anchor Datasets with a Bayesian Hierarchal Model

NASA Astrophysics Data System (ADS)

Currie, Miles; Rubin, David

2018-01-01

Inter-survey calibration remains one of the largest systematic uncertainties in SN Ia cosmology today. Ideally, each survey would measure their system throughputs and observe well characterized spectrophotometric standard stars, but many important surveys have not done so. For these surveys, we calibrate using tertiary survey stars tied to SDSS and Pan-STARRS. We improve on previous efforts by taking the spatially variable response of each telescope/camera into account, and using improved color transformations in the surveys’ natural instrumental photometric system. We use a global hierarchical model of the data, automatically providing a covariance matrix of magnitude offsets and bandpass shifts which reduces the systematic uncertainty in inter-survey calibration, thereby providing better cosmological constraints.

Jet energy scale measurements and their systematic uncertainties in proton-proton collisions at √{s }=13 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; 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.; 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.; Blackburn, D.; 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.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; 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'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; 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 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.; Ertel, E.; 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, J.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; 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.; 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.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de La Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Grummer, A.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartjes, F.; Hartmann, N. M.; Hasegawa, M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; 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. J.; Jon-And, K.; Jones, R. W. L.; Jones, S. D.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kay, E. F.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kempster, J. J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-Zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khodinov, A.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; Kirchmeier, D.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiuchi, K.; Kivernyk, O.; Kladiva, E.; Klapdor-Kleingrothaus, T.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klingl, T.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Knapik, J.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolb, M.; Koletsou, I.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kourlitis, E.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Krauss, D.; Kremer, J. A.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kulinich, Y. P.; Kuna, M.; Kunigo, T.; Kupco, A.; Kuprash, O.; Kurashige, H.; Kurchaninov, L. L.; Kurochkin, Y. A.; Kurth, M. G.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; La Rosa Navarro, J. L.; La Rotonda, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Langenberg, R. J.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Lapertosa, A.; Laplace, S.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; Leblanc, M.; Lecompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, G. R.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Li, B.; Li, C.; Li, H.; Li, L.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, S. C.; Lin, T. H.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, H.; Liu, H.; Liu, J. K. K.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo, C. Y.; Lo Sterzo, F.; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loew, K. M.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopez, J. A.; Lopez Mateos, D.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lu, Y. J.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; MacDonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A. S.; Magradze, E.; Mahlstedt, J.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maier, T.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandelli, L.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchese, L.; Marchiori, G.; Marcisovsky, M.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Martensson, M. U. F.; Marti-Garcia, S.; Martin, C. B.; Martin, T. A.; Martin, V. J.; Martin Dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; McFayden, J. A.; McHedlidze, G.; McMahon, S. J.; McNamara, P. C.; McPherson, R. A.; Meehan, S.; Megy, T. J.; Mehlhase, S.; Mehta, A.; Meideck, T.; Meier, K.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Mellenthin, J. D.; Melo, M.; Meloni, F.; Menary, S. B.; Meng, L.; Meng, X. T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mkrtchyan, T.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moschovakos, P.; Mosidze, M.; Moss, H. J.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nelson, M. E.; Nemecek, S.; Nemethy, P.; Nessi, M.; Neubauer, M. 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.; Nobe, T.; Noguchi, Y.; Nomachi, M.; Nomidis, I.; Nomura, M. A.; Nooney, T.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'Connor, K.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; 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.; 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.; 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.; Pope, B. G.; 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.; Price, L. E.; 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.; Roth, I.; 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.; Sansoni, A.; Santoni, C.; Santonico, R.; 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.; 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.; 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.; 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.; 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.; 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.; 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.; 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.; 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.; 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.; 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.; 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.; 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, 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.; Vlasak, M.; 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.; 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.; 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, D. R.; 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.; Atlas Collaboration

2017-10-01

Jet energy scale measurements and their systematic uncertainties are reported for jets measured with the ATLAS detector using proton-proton collision data with a center-of-mass energy of √{s }=13 TeV , corresponding to an integrated luminosity of 3.2 fb-1 collected during 2015 at the LHC. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells, using the anti-kt algorithm with radius parameter R =0.4 . Jets are calibrated with a series of simulation-based corrections and in situ techniques. In situ techniques exploit the transverse momentum balance between a jet and a reference object such as a photon, Z boson, or multijet system for jets with 20 0.8 ) is derived from dijet pT balance measurements. For jets of pT=80 GeV , the additional uncertainty for the forward jet calibration reaches its largest value of about 2% in the range |η |>3.5 and in a narrow slice of 2.2 <|η |<2.4 .

Jet energy scale measurements and their systematic uncertainties in proton-proton collisions at s = 13 TeV with the ATLAS detector

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

Aaboud, M.

Jet energy scale measurements and their systematic uncertainties are reported for jets measured with the ATLAS detector using proton-proton collision data with a center-of-mass energy of √ s = 13 TeV , corresponding to an integrated luminosity of 3.2 fb -1 collected during 2015 at the LHC. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells, using the anti- k t algorithm with radius parameter R = 0.4 . We calibrate jets with a series of simulation-based corrections and in situ techniques. In situ techniques exploit the transverse momentum balance between a jet and a reference objectmore » such as a photon, Z boson, or multijet system for jets with 20 < p T < 2000 GeV and pseudorapidities of | η | < 4.5 , using both data and simulation. An uncertainty in the jet energy scale of less than 1% is found in the central calorimeter region ( | η | < 1.2 ) for jets with 100 < p T < 500 GeV . An uncertainty of about 4.5% is found for low- p T jets with p T = 20 GeV in the central region, dominated by uncertainties in the corrections for multiple proton-proton interactions. The calibration of forward jets ( | η | > 0.8 ) is derived from dijet p T balance measurements. Furthermore, for jets of p T = 80 GeV , the additional uncertainty for the forward jet calibration reaches its largest value of about 2% in the range | η | > 3.5 and in a narrow slice of 2.2 < | η | < 2.4 .« less

Jet energy scale measurements and their systematic uncertainties in proton-proton collisions at s = 13 TeV with the ATLAS detector

DOE PAGES

Aaboud, M.

2017-10-13

Jet energy scale measurements and their systematic uncertainties are reported for jets measured with the ATLAS detector using proton-proton collision data with a center-of-mass energy of √ s = 13 TeV , corresponding to an integrated luminosity of 3.2 fb -1 collected during 2015 at the LHC. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells, using the anti- k t algorithm with radius parameter R = 0.4 . We calibrate jets with a series of simulation-based corrections and in situ techniques. In situ techniques exploit the transverse momentum balance between a jet and a reference objectmore » such as a photon, Z boson, or multijet system for jets with 20 < p T < 2000 GeV and pseudorapidities of | η | < 4.5 , using both data and simulation. An uncertainty in the jet energy scale of less than 1% is found in the central calorimeter region ( | η | < 1.2 ) for jets with 100 < p T < 500 GeV . An uncertainty of about 4.5% is found for low- p T jets with p T = 20 GeV in the central region, dominated by uncertainties in the corrections for multiple proton-proton interactions. The calibration of forward jets ( | η | > 0.8 ) is derived from dijet p T balance measurements. Furthermore, for jets of p T = 80 GeV , the additional uncertainty for the forward jet calibration reaches its largest value of about 2% in the range | η | > 3.5 and in a narrow slice of 2.2 < | η | < 2.4 .« less

A Systematic Review and Methodological Evaluation of Published Cost-Effectiveness Analyses of Aromatase Inhibitors versus Tamoxifen in Early Stage Breast Cancer

PubMed Central

John-Baptiste, Ava A.; Wu, Wei; Rochon, Paula; Anderson, Geoffrey M.; Bell, Chaim M.

2013-01-01

Background A key priority in developing policies for providing affordable cancer care is measuring the value for money of new therapies using cost-effectiveness analyses (CEAs). For CEA to be useful it should focus on relevant outcomes and include thorough investigation of uncertainty. Randomized controlled trials (RCTs) of five years of aromatase inhibitors (AI) versus five years of tamoxifen in the treatment of post-menopausal women with early stage breast cancer, show benefit of AI in terms of disease free survival (DFS) but not overall survival (OS) and indicate higher risk of fracture with AI. Policy-relevant CEA of AI versus tamoxifen should focus on OS and include analysis of uncertainty over key assumptions. Methods We conducted a systematic review of published CEAs comparing an AI to tamoxifen. We searched Ovid MEDLINE, EMBASE, PsychINFO, and the Cochrane Database of Systematic Reviews without language restrictions. We selected CEAs with outcomes expressed as cost per life year or cost per quality adjusted life year (QALY). We assessed quality using the Neumann checklist. Using structured forms two abstractors collected descriptive information, sources of data, baseline assumptions on effectiveness and adverse events, and recorded approaches to assessing parameter uncertainty, methodological uncertainty, and structural uncertainty. Results We identified 1,622 citations and 18 studies met inclusion criteria. All CE estimates assumed a survival benefit for aromatase inhibitors. Twelve studies performed sensitivity analysis on the risk of adverse events and 7 assumed no additional mortality risk with any adverse event. Sub-group analysis was limited; 6 studies examined older women, 2 examined women with low recurrence risk, and 1 examined women with multiple comorbidities. Conclusion Published CEAs comparing AIs to tamoxifen assumed an OS benefit though none has been shown in RCTs, leading to an overestimate of the cost-effectiveness of AIs. Results of these CEA analyses may be suboptimal for guiding policy. PMID:23671612

A systematic review and methodological evaluation of published cost-effectiveness analyses of aromatase inhibitors versus tamoxifen in early stage breast cancer.

PubMed

John-Baptiste, Ava A; Wu, Wei; Rochon, Paula; Anderson, Geoffrey M; Bell, Chaim M

2013-01-01

A key priority in developing policies for providing affordable cancer care is measuring the value for money of new therapies using cost-effectiveness analyses (CEAs). For CEA to be useful it should focus on relevant outcomes and include thorough investigation of uncertainty. Randomized controlled trials (RCTs) of five years of aromatase inhibitors (AI) versus five years of tamoxifen in the treatment of post-menopausal women with early stage breast cancer, show benefit of AI in terms of disease free survival (DFS) but not overall survival (OS) and indicate higher risk of fracture with AI. Policy-relevant CEA of AI versus tamoxifen should focus on OS and include analysis of uncertainty over key assumptions. We conducted a systematic review of published CEAs comparing an AI to tamoxifen. We searched Ovid MEDLINE, EMBASE, PsychINFO, and the Cochrane Database of Systematic Reviews without language restrictions. We selected CEAs with outcomes expressed as cost per life year or cost per quality adjusted life year (QALY). We assessed quality using the Neumann checklist. Using structured forms two abstractors collected descriptive information, sources of data, baseline assumptions on effectiveness and adverse events, and recorded approaches to assessing parameter uncertainty, methodological uncertainty, and structural uncertainty. We identified 1,622 citations and 18 studies met inclusion criteria. All CE estimates assumed a survival benefit for aromatase inhibitors. Twelve studies performed sensitivity analysis on the risk of adverse events and 7 assumed no additional mortality risk with any adverse event. Sub-group analysis was limited; 6 studies examined older women, 2 examined women with low recurrence risk, and 1 examined women with multiple comorbidities. Published CEAs comparing AIs to tamoxifen assumed an OS benefit though none has been shown in RCTs, leading to an overestimate of the cost-effectiveness of AIs. Results of these CEA analyses may be suboptimal for guiding policy.

Systematic uncertainties in the Monte Carlo calculation of ion chamber replacement correction factors

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

Wang, L. L. W.; La Russa, D. J.; Rogers, D. W. O.

In a previous study [Med. Phys. 35, 1747-1755 (2008)], the authors proposed two direct methods of calculating the replacement correction factors (P{sub repl} or p{sub cav}p{sub dis}) for ion chambers by Monte Carlo calculation. By ''direct'' we meant the stopping-power ratio evaluation is not necessary. The two methods were named as the high-density air (HDA) and low-density water (LDW) methods. Although the accuracy of these methods was briefly discussed, it turns out that the assumption made regarding the dose in an HDA slab as a function of slab thickness is not correct. This issue is reinvestigated in the current study,more » and the accuracy of the LDW method applied to ion chambers in a {sup 60}Co photon beam is also studied. It is found that the two direct methods are in fact not completely independent of the stopping-power ratio of the two materials involved. There is an implicit dependence of the calculated P{sub repl} values upon the stopping-power ratio evaluation through the choice of an appropriate energy cutoff {Delta}, which characterizes a cavity size in the Spencer-Attix cavity theory. Since the {Delta} value is not accurately defined in the theory, this dependence on the stopping-power ratio results in a systematic uncertainty on the calculated P{sub repl} values. For phantom materials of similar effective atomic number to air, such as water and graphite, this systematic uncertainty is at most 0.2% for most commonly used chambers for either electron or photon beams. This uncertainty level is good enough for current ion chamber dosimetry, and the merits of the two direct methods of calculating P{sub repl} values are maintained, i.e., there is no need to do a separate stopping-power ratio calculation. For high-Z materials, the inherent uncertainty would make it practically impossible to calculate reliable P{sub repl} values using the two direct methods.« less

Optimization Under Uncertainty of Site-Specific Turbine Configurations

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

Quick, J.; Dykes, K.; Graf, P.

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. Lastly, if there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtainedmore » with increasing risk aversion on the part of the designer.« less

Optimization under Uncertainty of Site-Specific Turbine Configurations: Preprint

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

Quick, Julian; Dykes, Katherine; Graf, Peter

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. If there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtained withmore » increasing risk aversion on the part of the designer.« less

Optimization Under Uncertainty of Site-Specific Turbine Configurations

DOE PAGES

Quick, J.; Dykes, K.; Graf, P.; ...

2016-10-03

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. Lastly, if there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtainedmore » with increasing risk aversion on the part of the designer.« less

Understanding the trends in HIV and hepatitis C prevalence amongst injecting drug users in different settings--implications for intervention impact.

PubMed

Vickerman, Peter; Martin, Natasha K; Hickman, Matthew

2012-06-01

A recent systematic review observed that HIV prevalence amongst injectors is negligible (<1%) below a threshold HCV prevalence of 30%, but thereafter increases with HCV prevalence. We explore whether a model can reproduce these trends, what determines different epidemiological profiles and how this affects intervention impact. An HIV/HCV transmission model was developed. Univariate sensitivity analyses determined whether the model projected a HCV prevalence threshold below which HIV is negligible, and how different behavioural and epidemiological factors affect the threshold. Multivariate uncertainty analyses considered whether the model could reproduce the observed breadth of HIV/HCV epidemics, how specific behavioural patterns produce different epidemic profiles, and how this affects an intervention's impact (reduces injecting risk by 30%). The model projected a HCV prevalence threshold, which varied depending on the heterogeneity in risk, mixing, and injecting duration in a setting. Multivariate uncertainty analyses showed the model could produce the same range of observed HIV/HCV epidemics. Variability in injecting transmission risk, degree of heterogeneity and injecting duration mainly determined different epidemic profiles. The intervention resulted in 50%/28% reduction in HIV incidence/prevalence and 37%/10% reduction in HCV incidence/prevalence over five years. For either infection, greater impact occurred in settings with lower prevalence of that infection and higher prevalence of the other infection. There are threshold levels of HCV prevalence below which HIV risk is negligible but these thresholds are likely to vary by setting. A setting's HIV and HCV prevalence may give insights into IDU risk behaviour and intervention impact. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Constituent quarks and systematic errors in mid-rapidity charged multiplicity dNch/dη distributions

NASA Astrophysics Data System (ADS)

Tannenbaum, M. J.

2018-01-01

Centrality definition in A + A collisions at colliders such as RHIC and LHC suffers from a correlated systematic uncertainty caused by the efficiency of detecting a p + p collision (50 ± 5% for PHENIX at RHIC). In A + A collisions where centrality is measured by the number of nucleon collisions, Ncoll, or the number of nucleon participants, Npart, or the number of constituent quark participants, Nqp, the error in the efficiency of the primary interaction trigger (Beam-Beam Counters) for a p + p collision leads to a correlated systematic uncertainty in Npart, Ncoll or Nqp which reduces binomially as the A + A collisions become more central. If this is not correctly accounted for in projections of A + A to p + p collisions, then mistaken conclusions can result. A recent example is presented in whether the mid-rapidity charged multiplicity per constituent quark participant (dNch/dη)/Nqp in Au + Au at RHIC was the same as the value in p + p collisions.

On the uncertainty of phenological responses to climate change, and implications for a terrestrial biosphere model

NASA Astrophysics Data System (ADS)

Migliavacca, M.; Sonnentag, O.; Keenan, T. F.; Cescatti, A.; O'Keefe, J.; Richardson, A. D.

2012-06-01

Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate system through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Terrestrial biosphere models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we used the Harvard Forest phenology record to investigate and characterize sources of uncertainty in predicting phenology, and the subsequent impacts on model forecasts of carbon and water cycling. Using a model-data fusion approach, we combined information from 20 yr of phenological observations of 11 North American woody species, with 12 leaf bud-burst models that varied in complexity. Akaike's Information Criterion indicated support for spring warming models with photoperiod limitations and, to a lesser extent, models that included chilling requirements. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2099 using 2 different IPCC climate scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% Confidence Interval - CI: 2.4 days century-1 for scenario B1 and 4.5 days century-1 for A1fi), whereas driver uncertainty was the largest (up to 8.4 days century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied among models (±7.7 days century-1 for A1fi, ±3.6 days century-1 for B1). The forecast sensitivity of bud-burst to temperature (i.e. days bud-burst advanced per degree of warming) varied between 2.2 days °C-1 and 5.2 days °C-1 depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated photosynthetic CO2 uptake and evapotranspiration (ET) using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of forest seasonality, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and ET of 9.6% and 2.9%, respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET. For phenology models, differences among future climate scenarios (i.e. driver) represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of ecosystem processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.

Mitigating Provider Uncertainty in Service Provision Contracts

NASA Astrophysics Data System (ADS)

Smith, Chris; van Moorsel, Aad

Uncertainty is an inherent property of open, distributed and multiparty systems. The viability of the mutually beneficial relationships which motivate these systems relies on rational decision-making by each constituent party under uncertainty. Service provision in distributed systems is one such relationship. Uncertainty is experienced by the service provider in his ability to deliver a service with selected quality level guarantees due to inherent non-determinism, such as load fluctuations and hardware failures. Statistical estimators utilized to model this non-determinism introduce additional uncertainty through sampling error. Inability of the provider to accurately model and analyze uncertainty in the quality level guarantees can result in the formation of sub-optimal service provision contracts. Emblematic consequences include loss of revenue, inefficient resource utilization and erosion of reputation and consumer trust. We propose a utility model for contract-based service provision to provide a systematic approach to optimal service provision contract formation under uncertainty. Performance prediction methods to enable the derivation of statistical estimators for quality level are introduced, with analysis of their resultant accuracy and cost.

Ensembles vs. information theory: supporting science under uncertainty

NASA Astrophysics Data System (ADS)

Nearing, Grey S.; Gupta, Hoshin V.

2018-05-01

Multi-model ensembles are one of the most common ways to deal with epistemic uncertainty in hydrology. This is a problem because there is no known way to sample models such that the resulting ensemble admits a measure that has any systematic (i.e., asymptotic, bounded, or consistent) relationship with uncertainty. Multi-model ensembles are effectively sensitivity analyses and cannot - even partially - quantify uncertainty. One consequence of this is that multi-model approaches cannot support a consistent scientific method - in particular, multi-model approaches yield unbounded errors in inference. In contrast, information theory supports a coherent hypothesis test that is robust to (i.e., bounded under) arbitrary epistemic uncertainty. This paper may be understood as advocating a procedure for hypothesis testing that does not require quantifying uncertainty, but is coherent and reliable (i.e., bounded) in the presence of arbitrary (unknown and unknowable) uncertainty. We conclude by offering some suggestions about how this proposed philosophy of science suggests new ways to conceptualize and construct simulation models of complex, dynamical systems.

Remaining Useful Life Estimation in Prognosis: An Uncertainty Propagation Problem

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Goebel, Kai

2013-01-01

The estimation of remaining useful life is significant in the context of prognostics and health monitoring, and the prediction of remaining useful life is essential for online operations and decision-making. However, it is challenging to accurately predict the remaining useful life in practical aerospace applications due to the presence of various uncertainties that affect prognostic calculations, and in turn, render the remaining useful life prediction uncertain. It is challenging to identify and characterize the various sources of uncertainty in prognosis, understand how each of these sources of uncertainty affect the uncertainty in the remaining useful life prediction, and thereby compute the overall uncertainty in the remaining useful life prediction. In order to achieve these goals, this paper proposes that the task of estimating the remaining useful life must be approached as an uncertainty propagation problem. In this context, uncertainty propagation methods which are available in the literature are reviewed, and their applicability to prognostics and health monitoring are discussed.

Ground Motion Uncertainty and Variability (single-station sigma): Insights from Euroseistest, Greece

NASA Astrophysics Data System (ADS)

Ktenidou, O. J.; Roumelioti, Z.; Abrahamson, N. A.; Cotton, F.; Pitilakis, K.

2014-12-01

Despite recent improvements in networks and data, the global aleatory uncertainty (sigma) in GMPEs is still large. One reason is the ergodic approach, where we combine data in space to make up for lack of data in time. By estimating the systematic site response, we can make site-specific GMPEs and use a lower, site-specific uncertainty: single-station sigma. In this study we use the EUROSEISTEST database (http://euroseisdb.civil.auth.gr), which has two distinct advantages: good existing knowledge of site conditions at all stations, and careful relocation of the recorded events. Constraining the site and source parameters as best we can, we minimise the within- and between-events components of the global, ergodic sigma. Following that, knowledge of the site response from empirical and theoretical approaches permits us to move on to single-station sigma. The variability per site is not clearly correlated to the site class. We show that in some cases knowledge of Vs30 is not sufficient, and that site-specific data are needed to capture the response, possibly due to 2D/3D effects from complex geometry. Our values of single-station sigma are low compared to the literature. This may be due to the good ray coverage we have in all directions for small, nearby records. Indeed, our single-station sigma values are similar to published single-path values, which means that they may correspond to a fully -rather than partially- non-ergodic approach. We find larger ground motion variability for short distances and small magnitudes. This may be related to the uncertainty in the depth affecting nearby records more, or to stress drop and causing trade-offs between the source and site terms for small magnitudes.

Particle Therapy for Non-Small Cell Lung Tumors: Where Do We Stand? A Systematic Review of the Literature

PubMed Central

Wink, Krista C. J.; Roelofs, Erik; Solberg, Timothy; Lin, Liyong; Simone, Charles B.; Jakobi, Annika; Richter, Christian; Lambin, Philippe; Troost, Esther G. C.

2014-01-01

This review article provides a systematic overview of the currently available evidence on the clinical effectiveness of particle therapy for the treatment of non-small cell lung cancer and summarizes findings of in silico comparative planning studies. Furthermore, technical issues and dosimetric uncertainties with respect to thoracic particle therapy are discussed. PMID:25401087

Weak lensing measurement of the mass–richness relation of SDSS redMaPPer clusters

DOE PAGES

Simet, Melanie; McClintock, Tom; Mandelbaum, Rachel; ...

2016-12-15

Here, we perform a measurement of the mass–richness relation of the redMaPPer galaxy cluster catalogue using weak lensing data from the Sloan Digital Sky Survey. We carefully characterized a broad range of systematic uncertainties, including shear calibration errors, photo-zz biases, dilution by member galaxies, source obscuration, magnification bias, incorrect assumptions about cluster mass profiles, cluster centering, halo triaxiality, and projection effects. We then compare measurements of the lensing signal from two independently-produced shear and photometric redshift catalogues to characterize systematic errors in the lensing signal itself. Using a sample of 5,570 clusters from 0.1 ≤ zz ≤ 0.33, the normalization of our power-law mass vs. λ relation is log 10[M 200m/h -1 M ⊙] = 14.344 ± 0.021 (statistical) ±0.023 (systematic) at a richness λ = 40, a 7 per cent calibration uncertainty, with a power-law index of 1.33+0.09-0.101.33more » $$+0.09\\atop{-0.10}$$ (1σ). Finally, the detailed systematics characterization in this work renders it the definitive weak lensing mass calibration for SDSS redMaPPer clusters at this time.« less

Unveiling the decoherence effect of noise on the entropic uncertainty relation and its control by partially collapsed operations

NASA Astrophysics Data System (ADS)

Chen, Min-Nan; Sun, Wen-Yang; Huang, Ai-Jun; Ming, Fei; Wang, Dong; Ye, Liu

2018-01-01

In this work, we investigate the dynamics of quantum-memory-assisted entropic uncertainty relations under open systems, and how to steer the uncertainty under different types of decoherence. Specifically, we develop the dynamical behaviors of the uncertainty of interest under two typical categories of noise; bit flipping and depolarizing channels. It has been shown that the measurement uncertainty firstly increases and then decreases with the growth of the decoherence strength in bit flipping channels. In contrast, the uncertainty monotonically increases with the increase of the decoherence strength in depolarizing channels. Notably, and to a large degree, it is shown that the uncertainty depends on both the systematic quantum correlation and the minimal conditional entropy of the observed subsystem. Moreover, we present a possible physical interpretation for these distinctive behaviors of the uncertainty within such scenarios. Furthermore, we propose a simple and effective strategy to reduce the entropic uncertainty by means of a partially collapsed operation—quantum weak measurement. Therefore, our investigations might offer an insight into the dynamics of the measurment uncertainty under decoherence, and be of importance to quantum precision measurement in open systems.

Space based inverse modeling of seasonal variations of anthropogenic and natural emissions of nitrogen oxides over China and effects of uncertainties in model meteorology and chemistry

NASA Astrophysics Data System (ADS)

Lin, J.

2011-12-01

Nitrogen oxides (NOx ≡ NO + NO2) are important atmospheric constituents affecting the tropospheric chemistry, surface air quality and climatic forcing. They are emitted both from anthropogenic and from natural (soil, lightning, biomass burning, etc.) sources, which can be estimated inversely from satellite remote sensing of the vertical column densities (VCDs) of nitrogen dioxide (NO2) in the troposphere. Based on VCDs of NO2 retrieved from OMI, a novel approach is developed in this study to separate anthropogenic emissions of NOx from natural sources over East China for 2006. It exploits the fact that anthropogenic and natural emissions vary with seasons with distinctive patterns. The global chemical transport model (CTM) GEOS-Chem is used to establish the relationship between VCDs of NO2 and emissions of NOx for individual sources. Derived soil emissions are compared to results from a newly developed bottom-up approach. Effects of uncertainties in model meteorology and chemistry over China, an important source of errors in the emission inversion, are evaluated systematically for the first time. Meteorological measurements from space and the ground are used to analyze errors in meteorological parameters driving the CTM.

CHEERS: The chemical evolution RGS sample

NASA Astrophysics Data System (ADS)

de Plaa, J.; Kaastra, J. S.; Werner, N.; Pinto, C.; Kosec, P.; Zhang, Y.-Y.; Mernier, F.; Lovisari, L.; Akamatsu, H.; Schellenberger, G.; Hofmann, F.; Reiprich, T. H.; Finoguenov, A.; Ahoranta, J.; Sanders, J. S.; Fabian, A. C.; Pols, O.; Simionescu, A.; Vink, J.; Böhringer, H.

2017-11-01

Context. The chemical yields of supernovae and the metal enrichment of the intra-cluster medium (ICM) are not well understood. The hot gas in clusters of galaxies has been enriched with metals originating from billions of supernovae and provides a fair sample of large-scale metal enrichment in the Universe. High-resolution X-ray spectra of clusters of galaxies provide a unique way of measuring abundances in the hot intracluster medium (ICM). The abundance measurements can provide constraints on the supernova explosion mechanism and the initial-mass function of the stellar population. This paper introduces the CHEmical Enrichment RGS Sample (CHEERS), which is a sample of 44 bright local giant ellipticals, groups, and clusters of galaxies observed with XMM-Newton. Aims: The CHEERS project aims to provide the most accurate set of cluster abundances measured in X-rays using this sample. This paper focuses specifically on the abundance measurements of O and Fe using the reflection grating spectrometer (RGS) on board XMM-Newton. We aim to thoroughly discuss the cluster to cluster abundance variations and the robustness of the measurements. Methods: We have selected the CHEERS sample such that the oxygen abundance in each cluster is detected at a level of at least 5σ in the RGS. The dispersive nature of the RGS limits the sample to clusters with sharp surface brightness peaks. The deep exposures and the size of the sample allow us to quantify the intrinsic scatter and the systematic uncertainties in the abundances using spectral modeling techniques. Results: We report the oxygen and iron abundances as measured with RGS in the core regions of all 44 clusters in the sample. We do not find a significant trend of O/Fe as a function of cluster temperature, but we do find an intrinsic scatter in the O and Fe abundances from cluster to cluster. The level of systematic uncertainties in the O/Fe ratio is estimated to be around 20-30%, while the systematic uncertainties in the absolute O and Fe abundances can be as high as 50% in extreme cases. Thanks to the high statistics of the observations, we were able to identify and correct a systematic bias in the oxygen abundance determination that was due to an inaccuracy in the spectral model. Conclusions: The lack of dependence of O/Fe on temperature suggests that the enrichment of the ICM does not depend on cluster mass and that most of the enrichment likely took place before the ICM was formed. We find that the observed scatter in the O/Fe ratio is due to a combination of intrinsic scatter in the source and systematic uncertainties in the spectral fitting, which we are unable to separate. The astrophysical source of intrinsic scatter could be due to differences in active galactic nucleus activity and ongoing star formation in the brightest cluster galaxy. The systematic scatter is due to uncertainties in the spatial line broadening, absorption column, multi-temperature structure, and the thermal plasma models.

Uncertainty, God, and scrupulosity: Uncertainty salience and priming God concepts interact to cause greater fears of sin.

PubMed

Fergus, Thomas A; Rowatt, Wade C

2015-03-01

Difficulties tolerating uncertainty are considered central to scrupulosity, a moral/religious presentation of obsessive-compulsive disorder (OCD). We examined whether uncertainty salience (i.e., exposure to a state of uncertainty) caused fears of sin and fears of God, as well as whether priming God concepts affected the impact of uncertainty salience on those fears. An internet sample of community adults (N = 120) who endorsed holding a belief in God or a higher power were randomly assigned to an experimental manipulation of (1) salience (uncertainty or insecurity) and (2) prime (God concepts or neutral). As predicted, participants who received the uncertainty salience and God concept priming reported the greatest fears of sin. There were no mean-level differences in the other conditions. The effect was not attributable to religiosity and the manipulations did not cause negative affect. We used a nonclinical sample recruited from the internet. These results support cognitive-behavioral models suggesting that religious uncertainty is important to scrupulosity. Implications of these results for future research are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Bayesian belief network approach for assessing uncertainty in conceptual site models at contaminated sites

NASA Astrophysics Data System (ADS)

Thomsen, Nanna I.; Binning, Philip J.; McKnight, Ursula S.; Tuxen, Nina; Bjerg, Poul L.; Troldborg, Mads

2016-05-01

A key component in risk assessment of contaminated sites is in the formulation of a conceptual site model (CSM). A CSM is a simplified representation of reality and forms the basis for the mathematical modeling of contaminant fate and transport at the site. The CSM should therefore identify the most important site-specific features and processes that may affect the contaminant transport behavior at the site. However, the development of a CSM will always be associated with uncertainties due to limited data and lack of understanding of the site conditions. CSM uncertainty is often found to be a major source of model error and it should therefore be accounted for when evaluating uncertainties in risk assessments. We present a Bayesian belief network (BBN) approach for constructing CSMs and assessing their uncertainty at contaminated sites. BBNs are graphical probabilistic models that are effective for integrating quantitative and qualitative information, and thus can strengthen decisions when empirical data are lacking. The proposed BBN approach facilitates a systematic construction of multiple CSMs, and then determines the belief in each CSM using a variety of data types and/or expert opinion at different knowledge levels. The developed BBNs combine data from desktop studies and initial site investigations with expert opinion to assess which of the CSMs are more likely to reflect the actual site conditions. The method is demonstrated on a Danish field site, contaminated with chlorinated ethenes. Four different CSMs are developed by combining two contaminant source zone interpretations (presence or absence of a separate phase contamination) and two geological interpretations (fractured or unfractured clay till). The beliefs in each of the CSMs are assessed sequentially based on data from three investigation stages (a screening investigation, a more detailed investigation, and an expert consultation) to demonstrate that the belief can be updated as more information becomes available.

Uncertainty Propagation in OMFIT

NASA Astrophysics Data System (ADS)

Smith, Sterling; Meneghini, Orso; Sung, Choongki

2017-10-01

A rigorous comparison of power balance fluxes and turbulent model fluxes requires the propagation of uncertainties in the kinetic profiles and their derivatives. Making extensive use of the python uncertainties package, the OMFIT framework has been used to propagate covariant uncertainties to provide an uncertainty in the power balance calculation from the ONETWO code, as well as through the turbulent fluxes calculated by the TGLF code. The covariant uncertainties arise from fitting 1D (constant on flux surface) density and temperature profiles and associated random errors with parameterized functions such as a modified tanh. The power balance and model fluxes can then be compared with quantification of the uncertainties. No effort is made at propagating systematic errors. A case study will be shown for the effects of resonant magnetic perturbations on the kinetic profiles and fluxes at the top of the pedestal. A separate attempt at modeling the random errors with Monte Carlo sampling will be compared to the method of propagating the fitting function parameter covariant uncertainties. Work supported by US DOE under DE-FC02-04ER54698, DE-FG2-95ER-54309, DE-SC 0012656.

Uncertainty evaluation of mass values determined by electronic balances in analytical chemistry: a new method to correct for air buoyancy.

PubMed

Wunderli, S; Fortunato, G; Reichmuth, A; Richard, Ph

2003-06-01

A new method to correct for the largest systematic influence in mass determination-air buoyancy-is outlined. A full description of the most relevant influence parameters is given and the combined measurement uncertainty is evaluated according to the ISO-GUM approach [1]. A new correction method for air buoyancy using an artefact is presented. This method has the advantage that only a mass artefact is used to correct for air buoyancy. The classical approach demands the determination of the air density and therefore suitable equipment to measure at least the air temperature, the air pressure and the relative air humidity within the demanded uncertainties (i.e. three independent measurement tasks have to be performed simultaneously). The calculated uncertainty is lower for the classical method. However a field laboratory may not always be in possession of fully traceable measurement systems for these room climatic parameters.A comparison of three approaches applied to the calculation of the combined uncertainty of mass values is presented. Namely the classical determination of air buoyancy, the artefact method, and the neglecting of this systematic effect as proposed in the new EURACHEM/CITAC guide [2]. The artefact method is suitable for high-precision measurement in analytical chemistry and especially for the production of certified reference materials, reference values and analytical chemical reference materials. The method could also be used either for volume determination of solids or for air density measurement by an independent method.

Governing Laws of Complex System Predictability under Co-evolving Uncertainty Sources: Theory and Nonlinear Geophysical Applications

NASA Astrophysics Data System (ADS)

Perdigão, R. A. P.

2017-12-01

Predictability assessments are traditionally made on a case-by-case basis, often by running the particular model of interest with randomly perturbed initial/boundary conditions and parameters, producing computationally expensive ensembles. These approaches provide a lumped statistical view of uncertainty evolution, without eliciting the fundamental processes and interactions at play in the uncertainty dynamics. In order to address these limitations, we introduce a systematic dynamical framework for predictability assessment and forecast, by analytically deriving governing equations of predictability in terms of the fundamental architecture of dynamical systems, independent of any particular problem under consideration. The framework further relates multiple uncertainty sources along with their coevolutionary interplay, enabling a comprehensive and explicit treatment of uncertainty dynamics along time, without requiring the actual model to be run. In doing so, computational resources are freed and a quick and effective a-priori systematic dynamic evaluation is made of predictability evolution and its challenges, including aspects in the model architecture and intervening variables that may require optimization ahead of initiating any model runs. It further brings out universal dynamic features in the error dynamics elusive to any case specific treatment, ultimately shedding fundamental light on the challenging issue of predictability. The formulated approach, framed with broad mathematical physics generality in mind, is then implemented in dynamic models of nonlinear geophysical systems with various degrees of complexity, in order to evaluate their limitations and provide informed assistance on how to optimize their design and improve their predictability in fundamental dynamical terms.

Balancing certainty and uncertainty in clinical medicine.

PubMed

Hayward, Richard

2006-01-01

Nothing in clinical medicine is one hundred per cent certain. Part of a doctor's education involves learning how to cope with the anxiety that uncertainty in decisions affecting life and death inevitably produces. This paper examines: (1) the role of anxiety -- both rational and irrational -- in the provision of health care; (2) the effects of uncertainty upon the doctor-patient relationship; (3) the threat uncertainty poses to medical authority (and the assumption of infallibility that props it up); (4) the contribution of clinical uncertainty to the rising popularity of alternative therapies; and (5) the clash between the medical and the legal understanding of how certainty should be defined, particularly as it affects the paediatric community. It concludes by suggesting some strategies that might facilitate successful navigation between the opposing and ever-present forces of certainty and uncertainty.

Uncertainties in s -process nucleosynthesis in low mass stars determined from Monte Carlo variations

NASA Astrophysics Data System (ADS)

Cescutti, G.; Hirschi, R.; Nishimura, N.; den Hartogh, J. W.; Rauscher, T.; Murphy, A. St J.; Cristallo, S.

2018-05-01

The main s-process taking place in low mass stars produces about half of the elements heavier than iron. It is therefore very important to determine the importance and impact of nuclear physics uncertainties on this process. We have performed extensive nuclear reaction network calculations using individual and temperature-dependent uncertainties for reactions involving elements heavier than iron, within a Monte Carlo framework. Using this technique, we determined the uncertainty in the main s-process abundance predictions due to nuclear uncertainties link to weak interactions and neutron captures on elements heavier than iron. We also identified the key nuclear reactions dominating these uncertainties. We found that β-decay rate uncertainties affect only a few nuclides near s-process branchings, whereas most of the uncertainty in the final abundances is caused by uncertainties in neutron capture rates, either directly producing or destroying the nuclide of interest. Combined total nuclear uncertainties due to reactions on heavy elements are in general small (less than 50%). Three key reactions, nevertheless, stand out because they significantly affect the uncertainties of a large number of nuclides. These are 56Fe(n,γ), 64Ni(n,γ), and 138Ba(n,γ). We discuss the prospect of reducing uncertainties in the key reactions identified in this study with future experiments.

Energy prices will play an important role in determining global land use in the twenty first century

NASA Astrophysics Data System (ADS)

Steinbuks, Jevgenijs; Hertel, Thomas W.

2013-03-01

Global land use research to date has focused on quantifying uncertainty effects of three major drivers affecting competition for land: the uncertainty in energy and climate policies affecting competition between food and biofuels, the uncertainty of climate impacts on agriculture and forestry, and the uncertainty in the underlying technological progress driving efficiency of food, bioenergy and timber production. The market uncertainty in fossil fuel prices has received relatively less attention in the global land use literature. Petroleum and natural gas prices affect both the competitiveness of biofuels and the cost of nitrogen fertilizers. High prices put significant pressure on global land supply and greenhouse gas emissions from terrestrial systems, while low prices can moderate demands for cropland. The goal of this letter is to assess and compare the effects of these core uncertainties on the optimal profile for global land use and land-based GHG emissions over the coming century. The model that we develop integrates distinct strands of agronomic, biophysical and economic literature into a single, intertemporally consistent, analytical framework, at global scale. Our analysis accounts for the value of land-based services in the production of food, first- and second-generation biofuels, timber, forest carbon and biodiversity. We find that long-term uncertainty in energy prices dominates the climate impacts and climate policy uncertainties emphasized in prior research on global land use.

Use of SUSA in Uncertainty and Sensitivity Analysis for INL VHTR Coupled Codes

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

Gerhard Strydom

2010-06-01

The need for a defendable and systematic Uncertainty and Sensitivity approach that conforms to the Code Scaling, Applicability, and Uncertainty (CSAU) process, and that could be used for a wide variety of software codes, was defined in 2008.The GRS (Gesellschaft für Anlagen und Reaktorsicherheit) company of Germany has developed one type of CSAU approach that is particularly well suited for legacy coupled core analysis codes, and a trial version of their commercial software product SUSA (Software for Uncertainty and Sensitivity Analyses) was acquired on May 12, 2010. This interim milestone report provides an overview of the current status of themore » implementation and testing of SUSA at the INL VHTR Project Office.« less

Hybrid Gibbs Sampling and MCMC for CMB Analysis at Small Angular Scales

NASA Technical Reports Server (NTRS)

Jewell, Jeffrey B.; Eriksen, H. K.; Wandelt, B. D.; Gorski, K. M.; Huey, G.; O'Dwyer, I. J.; Dickinson, C.; Banday, A. J.; Lawrence, C. R.

2008-01-01

A) Gibbs Sampling has now been validated as an efficient, statistically exact, and practically useful method for "low-L" (as demonstrated on WMAP temperature polarization data). B) We are extending Gibbs sampling to directly propagate uncertainties in both foreground and instrument models to total uncertainty in cosmological parameters for the entire range of angular scales relevant for Planck. C) Made possible by inclusion of foreground model parameters in Gibbs sampling and hybrid MCMC and Gibbs sampling for the low signal to noise (high-L) regime. D) Future items to be included in the Bayesian framework include: 1) Integration with Hybrid Likelihood (or posterior) code for cosmological parameters; 2) Include other uncertainties in instrumental systematics? (I.e. beam uncertainties, noise estimation, calibration errors, other).

Evaluating BC and NOx emission inventories for the Paris region from MEGAPOLI aircraft measurements

NASA Astrophysics Data System (ADS)

Petetin, H.; Beekmann, M.; Colomb, A.; Denier van der Gon, H. A. C.; Dupont, J.-C.; Honoré, C.; Michoud, V.; Morille, Y.; Perrussel, O.; Schwarzenboeck, A.; Sciare, J.; Wiedensohler, A.; Zhang, Q. J.

2015-09-01

High uncertainties affect black carbon (BC) emissions, and, despite its important impact on air pollution and climate, very few BC emissions evaluations are found in the literature. This paper presents a novel approach, based on airborne measurements across the Paris, France, plume, developed in order to evaluate BC and NOx emissions at the scale of a whole agglomeration. The methodology consists in integrating, for each transect, across the plume observed and simulated concentrations above background. This allows for several error sources (e.g., representativeness, chemistry, plume lateral dispersion) to be minimized in the model used. The procedure is applied with the CHIMERE chemistry-transport model to three inventories - the EMEP inventory and the so-called TNO and TNO-MP inventories - over the month of July 2009. Various systematic uncertainty sources both in the model (e.g., boundary layer height, vertical mixing, deposition) and in observations (e.g., BC nature) are discussed and quantified, notably through sensitivity tests. Large uncertainty values are determined in our results, which limits the usefulness of the method to rather strongly erroneous emission inventories. A statistically significant (but moderate) overestimation is obtained for the TNO BC emissions and the EMEP and TNO-MP NOx emissions, as well as for the BC / NOx emission ratio in TNO-MP. The benefit of the airborne approach is discussed through a comparison with the BC / NOx ratio at a ground site in Paris, which additionally suggests a spatially heterogeneous error in BC emissions over the agglomeration.

State estimation bias induced by optimization under uncertainty and error cost asymmetry is likely reflected in perception.

PubMed

Shimansky, Y P

2011-05-01

It is well known from numerous studies that perception can be significantly affected by intended action in many everyday situations, indicating that perception and related decision-making is not a simple, one-way sequence, but a complex iterative cognitive process. However, the underlying functional mechanisms are yet unclear. Based on an optimality approach, a quantitative computational model of one such mechanism has been developed in this study. It is assumed in the model that significant uncertainty about task-related parameters of the environment results in parameter estimation errors and an optimal control system should minimize the cost of such errors in terms of the optimality criterion. It is demonstrated that, if the cost of a parameter estimation error is significantly asymmetrical with respect to error direction, the tendency to minimize error cost creates a systematic deviation of the optimal parameter estimate from its maximum likelihood value. Consequently, optimization of parameter estimate and optimization of control action cannot be performed separately from each other under parameter uncertainty combined with asymmetry of estimation error cost, thus making the certainty equivalence principle non-applicable under those conditions. A hypothesis that not only the action, but also perception itself is biased by the above deviation of parameter estimate is supported by ample experimental evidence. The results provide important insights into the cognitive mechanisms of interaction between sensory perception and planning an action under realistic conditions. Implications for understanding related functional mechanisms of optimal control in the CNS are discussed.

Intolerance of uncertainty correlates with insula activation during affective ambiguity

PubMed Central

Simmons, Alan; Matthews, Scott C.; Paulus, Martin P.; Stein, Murray B.

2009-01-01

Intolerance of uncertainty (IU), or the increased affective response to situations with uncertain outcomes, is an important component process of anxiety disorders. Increased IU is observed in panic disorder (PD), obsessive compulsive disorder (OCD) and generalized anxiety disorder (GAD), and is thought to relate to dysfunctional behaviors and thought patterns in these disorders. Identifying what brain systems are associated with IU would contribute to a comprehensive model of anxiety processing, and increase our understanding of the neurobiology of anxiety disorders. Here, we used a behavioral task, Wall of Faces (WOF), during functional magnetic resonance imaging (fMRI), which probes both affect and ambiguity, to examine the neural circuitry of IU in fourteen (10 females) college age (18.8 yrs) subjects. All subjects completed the Intolerance of Uncertainty Scale (IUS), Anxiety Sensitivity Index (ASI), and a measure of neuroticism (i.e. the NEO-N). IUS scores but neither ASI nor NEO-N scores, correlated positively with activation in bilateral insula during affective ambiguity. Thus, the experience of IU during certain types of emotion processing may relate to the degree to which bilateral insula processes uncertainty. Previously observed insula hyperactivity in anxiety disorder individuals may therefore be directly linked to altered processes of uncertainty. PMID:18079060

Nuclear Effects in Quasi-Elastic and Delta Resonance Production at Low Momentum Transfer

NASA Astrophysics Data System (ADS)

Demgen, John Gibney

Analysis of data collected by the MINERvA experiment is done by showing the distribution of charged hadron energy for interactions that have low momentum transfer. This distribution reveals major discrepancies between the detector data and the standard MINERvA interaction model with only a simple global Fermi gas model. Adding additional model elements, the random phase approximation (RPA), meson exchange current (MEC), and a reduction of resonance delta production improve this discrepancy. Special attention is paid to resonance delta production systematic uncertainties, which do not make up these discrepancies even when added with resolution and biasing systematic uncertainties. Eye- scanning of events in this region also show a discrepancy, but we were insensitive to two-proton events, the predicted signature of the MEC process.

Network planning under uncertainties

NASA Astrophysics Data System (ADS)

Ho, Kwok Shing; Cheung, Kwok Wai

2008-11-01

One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a generic framework for solving the network planning problem under uncertainties. In addition to reviewing the various network planning problems involving uncertainties, we also propose that a unified framework based on robust optimization can be used to solve a rather large segment of network planning problem under uncertainties. Robust optimization is first introduced in the operations research literature and is a framework that incorporates information about the uncertainty sets for the parameters in the optimization model. Even though robust optimization is originated from tackling the uncertainty in the optimization process, it can serve as a comprehensive and suitable framework for tackling generic network planning problems under uncertainties. In this paper, we begin by explaining the main ideas behind the robust optimization approach. Then we demonstrate the capabilities of the proposed framework by giving out some examples of how the robust optimization framework can be applied to the current common network planning problems under uncertain environments. Next, we list some practical considerations for solving the network planning problem under uncertainties with the proposed framework. Finally, we conclude this article with some thoughts on the future directions for applying this framework to solve other network planning problems.

Measurement of the W-boson mass in pp collisions at √{s}=7 TeV 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.; Adams, D. 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.; 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.; Anghinolfi, F.; 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.; Bagiacchi, P.; Bagnaia, P.; 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.; 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.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bianco, M.; 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.; 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.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; 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, B. H.; 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.; 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.; Carrillo-Montoya, G. D.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; 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.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; 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.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Cornelissen, T.; 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.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cúth, J.; Czirr, H.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; 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 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.; 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 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.; Duchovni, E.; Duckeck, G.; 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.; 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.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; 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.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Torregrosa, E. Fullana; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, J.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; 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.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de la Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Gui, B.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, W.; Guo, Y.; Gupta, R.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Guzik, M. P.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Hadef, A.; Hageböck, S.; Hagihara, M.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Han, S.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hanna, R.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartjes, F.; Hartmann, N. M.; Hasegawa, M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havener, L. B.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayakawa, D.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heidegger, K. K.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Held, A.; Hellman, S.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Herde, H.; Herget, V.; Hernández Jiménez, Y.; Herten, G.; Hertenberger, R.; Hervas, L.; Herwig, T. C.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Higashino, S.; Higón-Rodriguez, E.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; 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.; 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.; 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.; 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.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansky, R.; Janssen, J.; Janus, M.; Janus, P. A.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Javurkova, M.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jelinskas, A.; Jenni, P.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiang, Z.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Jivan, H.; Johansson, P.; Johns, K. A.; Johnson, C. A.; Johnson, W. J.; Jon-And, K.; Jones, R. W. L.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kaji, T.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kaneti, S.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kar, D.; Karakostas, K.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karnevskiy, M.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawade, K.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kay, E. F.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kempster, J. J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khader, M.; Khalil-zada, F.; Khanov, A.; Kharlamov, A. G.; Kharlamova, T.; Khodinov, A.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kilby, C. R.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; Kirchmeier, D.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiuchi, K.; Kivernyk, O.; Kladiva, E.; Klapdor-Kleingrothaus, T.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Knapik, J.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Köhler, N. M.; Koi, T.; Kolb, M.; Koletsou, I.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Koulouris, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Krauss, D.; Kravchenko, A.; Kremer, J. A.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kulinich, Y. P.; Kuna, M.; Kunigo, T.; Kupco, A.; Kuprash, O.; Kurashige, H.; Kurchaninov, L. L.; Kurochkin, Y. A.; Kurth, M. G.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; Navarro, J. L. La Rosa; La Rotonda, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lanfermann, M. C.; Lang, V. S.; Lange, J. C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Lapertosa, A.; Laplace, S.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; LeBlanc, M.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, S. C.; Lee, L.; Lefebvre, B.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Lewis, D.; Leyton, M.; Li, B.; Li, C.; Li, H.; Li, L.; Li, L.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, S. C.; Lin, T. H.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, H.; Liu, H.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo, C. Y.; Sterzo, F. Lo; Lobodzinska, E. M.; Loch, P.; Loebinger, F. K.; Loew, K. M.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopez, J. A.; Lopez Mateos, D.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lu, Y. J.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Luzi, P. M.; Lynn, D.; Lysak, R.; Lytken, E.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; Macdonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A.; Magradze, E.; Mahlstedt, J.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maier, T.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandelli, L.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mann, A.; Manousos, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchiori, G.; Marcisovsky, M.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Martensson, M. U. F.; Marti-Garcia, S.; Martin, C. B.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martinez, M.; Martinez Outschoorn, V. I.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Maznas, I.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; Mcfayden, J. A.; Mchedlidze, G.; McMahon, S. J.; McNamara, P. C.; McPherson, R. A.; Meehan, S.; Megy, T. J.; Mehlhase, S.; Mehta, A.; Meideck, T.; Meier, K.; Meineck, C.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Melo, M.; Meloni, F.; Menary, S. B.; Meng, L.; Meng, X. T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morgenstern, S.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Morvaj, L.; Moschovakos, P.; Mosidze, M.; Moss, H. J.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nelson, M. E.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; 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.; Nobe, T.; Noguchi, Y.; Nomachi, M.; Nomidis, I.; Nomura, M. A.; Nooney, T.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagan Griso, S.; Paganini, M.; Paige, F.; Pais, P.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; St. Panagiotopoulou, E.; 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.; Pearce, J.; Pearson, B.; Pedersen, L. E.; 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.; 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.; 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.; 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.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Puri, A.; 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.; 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.; 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.; 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.; 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.; 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.; 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, 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.; 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.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; 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.; 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.; 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.; 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.; 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.; 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.; Sopczak, A.; 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.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; 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.; 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.; 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.; 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.; 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.; 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.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; 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.; 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, 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.; 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.; 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, Q.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; 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, A. F.; 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.; 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, 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.; 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.; Yildirim, E.; Yorita, K.; 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.; Zou, R.; zur Nedden, M.; Zwalinski, L.

2018-02-01

A measurement of the mass of the W boson is presented based on proton-proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC, and corresponding to 4.6 fb^{-1} of integrated luminosity. The selected data sample consists of 7.8× 10^6 candidates in the W→ μ ν channel and 5.9× 10^6 candidates in the W→ e ν channel. The W-boson mass is obtained from template fits to the reconstructed distributions of the charged lepton transverse momentum and of the W boson transverse mass in the electron and muon decay channels, yielding m_W = 80370&± 7 ( {stat.}) ± 11 ( {exp. syst.}) ± 14 ( {mod. syst.}) {MeV} = 80370± 19 {MeV}, where the first uncertainty is statistical, the second corresponds to the experimental systematic uncertainty, and the third to the physics-modelling systematic uncertainty. A measurement of the mass difference between the W^+ and W^- bosons yields m_{W^+}-m_{W^-} = - 29 ± 28 MeV.

New Assignment of Mass Values and Uncertainties to NIST Working Standards

PubMed Central

Davis, Richard S.

1990-01-01

For some time it had been suspected that values assigned to NIST working standards of mass were some 0.17 mg/kg larger than mass values based on artifacts representing mass in the International System of Units (SI). This relatively small offset, now confirmed, has had minimal scientific or technological significance. The discrepancy was removed on January 1, 1990. We document the history of the discrepancy, the studies which allow its removal, and the methods in place to limit its effect and prevent its recurrence. For routine calibrations, we believe that our working standards now have a long-term stability of 0.033 mg/kg (3σ) with respect to the national prototype kilograms of the United States. We provisionally admit an additional uncertainty of 0.09 mg/kg (3σ), systematic to all NIST mass measurements, which represents the possible offset of our primary standards from standards maintained by the Bureau International des Poids et Mesures (BIPM). This systematic uncertainty may be significantly reduced after analysis of results from the 3rd verification of national prototype kilograms, which is now underway. PMID:28179759

SDRE controller for motion design of cable-suspended robot with uncertainties and moving obstacles

NASA Astrophysics Data System (ADS)

Behboodi, Ahad; Salehi, Seyedmohammad

2017-10-01

In this paper an optimal control approach for nonlinear dynamical systems was proposed based on State Dependent Riccati Equation (SDRE) and its robustness against uncertainties is shown by simulation results. The proposed method was applied on a spatial six-cable suspended robot, which was designed to carry loads or perform different tasks in huge workspaces. Motion planning for cable-suspended robots in such a big workspace is subjected to uncertainties and obstacles. First, we emphasized the ability of SDRE to construct a systematic basis and efficient design of controller for wide variety of nonlinear dynamical systems. Then we showed how this systematic design improved the robustness of the system and facilitated the integration of motion planning techniques with the controller. In particular, obstacle avoidance technique based on artificial potential field (APF) can be easily combined with SDRE controller with efficient performance. Due to difficulties of exact solution for SDRE, an approximation method was used based on power series expansion. The efficiency and robustness of the SDRE controller was illustrated on a six-cable suspended robot with proper simulations.

Large Uncertainty in Estimating pCO2 From Carbonate Equilibria in Lakes

NASA Astrophysics Data System (ADS)

Golub, Malgorzata; Desai, Ankur R.; McKinley, Galen A.; Remucal, Christina K.; Stanley, Emily H.

2017-11-01

Most estimates of carbon dioxide (CO2) evasion from freshwaters rely on calculating partial pressure of aquatic CO2 (pCO2) from two out of three CO2-related parameters using carbonate equilibria. However, the pCO2 uncertainty has not been systematically evaluated across multiple lake types and equilibria. We quantified random errors in pH, dissolved inorganic carbon, alkalinity, and temperature from the North Temperate Lakes Long-Term Ecological Research site in four lake groups across a broad gradient of chemical composition. These errors were propagated onto pCO2 calculated from three carbonate equilibria, and for overlapping observations, compared against uncertainties in directly measured pCO2. The empirical random errors in CO2-related parameters were mostly below 2% of their median values. Resulting random pCO2 errors ranged from ±3.7% to ±31.5% of the median depending on alkalinity group and choice of input parameter pairs. Temperature uncertainty had a negligible effect on pCO2. When compared with direct pCO2 measurements, all parameter combinations produced biased pCO2 estimates with less than one third of total uncertainty explained by random pCO2 errors, indicating that systematic uncertainty dominates over random error. Multidecadal trend of pCO2 was difficult to reconstruct from uncertain historical observations of CO2-related parameters. Given poor precision and accuracy of pCO2 estimates derived from virtually any combination of two CO2-related parameters, we recommend direct pCO2 measurements where possible. To achieve consistently robust estimates of CO2 emissions from freshwater components of terrestrial carbon balances, future efforts should focus on improving accuracy and precision of CO2-related parameters (including direct pCO2) measurements and associated pCO2 calculations.

Reviews and syntheses: Revisiting the boron systematics of aragonite and their application to coral calcification

NASA Astrophysics Data System (ADS)

DeCarlo, Thomas M.; Holcomb, Michael; McCulloch, Malcolm T.

2018-05-01

The isotopic and elemental systematics of boron in aragonitic coral skeletons have recently been developed as a proxy for the carbonate chemistry of the coral extracellular calcifying fluid. With knowledge of the boron isotopic fractionation in seawater and the B/Ca partition coefficient (KD) between aragonite and seawater, measurements of coral skeleton δ11B and B/Ca can potentially constrain the full carbonate system. Two sets of abiogenic aragonite precipitation experiments designed to quantify KD have recently made possible the application of this proxy system. However, while different KD formulations have been proposed, there has not yet been a comprehensive analysis that considers both experimental datasets and explores the implications for interpreting coral skeletons. Here, we evaluate four potential KD formulations: three previously presented in the literature and one newly developed. We assess how well each formulation reconstructs the known fluid carbonate chemistry from the abiogenic experiments, and we evaluate the implications for deriving the carbonate chemistry of coral calcifying fluid. Three of the KD formulations performed similarly when applied to abiogenic aragonites precipitated from seawater and to coral skeletons. Critically, we find that some uncertainty remains in understanding the mechanism of boron elemental partitioning between aragonite and seawater, and addressing this question should be a target of additional abiogenic precipitation experiments. Despite this, boron systematics can already be applied to quantify the coral calcifying fluid carbonate system, although uncertainties associated with the proxy system should be carefully considered for each application. Finally, we present a user-friendly computer code that calculates coral calcifying fluid carbonate chemistry, including propagation of uncertainties, given inputs of boron systematics measured in coral skeleton.

A new method for detecting velocity shifts and distortions between optical spectra

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

Evans, Tyler M.; Murphy, Michael T., E-mail: tevans@astro.swin.edu.au

2013-12-01

Recent quasar spectroscopy from the Very Large Telescope (VLT) and Keck suggests that fundamental constants may not actually be constant. To better confirm or refute this result, systematic errors between telescopes must be minimized. We present a new method to directly compare spectra of the same object and measure any velocity shifts between them. This method allows for the discovery of wavelength-dependent velocity shifts between spectra, i.e., velocity distortions, that could produce spurious detections of cosmological variations in fundamental constants. This 'direct comparison' method has several advantages over alternative techniques: it is model-independent (cf. line-fitting approaches), blind, in that spectralmore » features do not need to be identified beforehand, and it produces meaningful uncertainty estimates for the velocity shift measurements. In particular, we demonstrate that, when comparing echelle-resolution spectra with unresolved absorption features, the uncertainty estimates are reliable for signal-to-noise ratios ≳7 per pixel. We apply this method to spectra of quasar J2123–0050 observed with Keck and the VLT and find no significant distortions over long wavelength ranges (∼1050 Å) greater than ≈180 m s{sup –1}. We also find no evidence for systematic velocity distortions within echelle orders greater than 500 m s{sup –1}. Moreover, previous constraints on cosmological variations in the proton-electron mass ratio should not have been affected by velocity distortions in these spectra by more than 4.0 ± 4.2 parts per million. This technique may also find application in measuring stellar radial velocities in search of extra-solar planets and attempts to directly observe the expansion history of the universe using quasar absorption spectra.« less

Uncertainty estimates of a GRACE inversion modelling technique over Greenland using a simulation

NASA Astrophysics Data System (ADS)

Bonin, Jennifer; Chambers, Don

2013-07-01

The low spatial resolution of GRACE causes leakage, where signals in one location spread out into nearby regions. Because of this leakage, using simple techniques such as basin averages may result in an incorrect estimate of the true mass change in a region. A fairly simple least squares inversion technique can be used to more specifically localize mass changes into a pre-determined set of basins of uniform internal mass distribution. However, the accuracy of these higher resolution basin mass amplitudes has not been determined, nor is it known how the distribution of the chosen basins affects the results. We use a simple `truth' model over Greenland as an example case, to estimate the uncertainties of this inversion method and expose those design parameters which may result in an incorrect high-resolution mass distribution. We determine that an appropriate level of smoothing (300-400 km) and process noise (0.30 cm2 of water) gets the best results. The trends of the Greenland internal basins and Iceland can be reasonably estimated with this method, with average systematic errors of 3.5 cm yr-1 per basin. The largest mass losses found from GRACE RL04 occur in the coastal northwest (-19.9 and -33.0 cm yr-1) and southeast (-24.2 and -27.9 cm yr-1), with small mass gains (+1.4 to +7.7 cm yr-1) found across the northern interior. Acceleration of mass change is measurable at the 95 per cent confidence level in four northwestern basins, but not elsewhere in Greenland. Due to an insufficiently detailed distribution of basins across internal Canada, the trend estimates of Baffin and Ellesmere Islands are expected to be incorrect due to systematic errors caused by the inversion technique.

How Do Type Ia Supernova Nebular Spectra Depend on Explosion Properties? Insights from Systematic Non-LTE Modeling

NASA Astrophysics Data System (ADS)

Botyánszki, János; Kasen, Daniel

2017-08-01

We present a radiative transfer code to model the nebular phase spectra of supernovae (SNe) in non-LTE (NLTE). We apply it to a systematic study of SNe Ia using parameterized 1D models and show how nebular spectral features depend on key physical parameters, such as the time since explosion, total ejecta mass, kinetic energy, radial density profile, and the masses of 56Ni, intermediate-mass elements, and stable iron-group elements. We also quantify the impact of uncertainties in atomic data inputs. We find the following. (1) The main features of SN Ia nebular spectra are relatively insensitive to most physical parameters. Degeneracy among parameters precludes a unique determination of the ejecta properties from spectral fitting. In particular, features can be equally well fit with generic Chandrasekhar mass ({M}{ch}), sub-{M}{Ch}, and super-{M}{Ch} models. (2) A sizable (≳0.1 {M}⊙ ) central region of stable iron-group elements, often claimed as evidence for {M}{Ch} models, is not essential to fit the optical spectra and may produce an unusual flat-top [Co III] profile. (3) The strength of [S III] emission near 9500 Å can provide a useful diagnostic of explosion nucleosynthesis. (4) Substantial amounts (≳0.1 {M}⊙ ) of unburned C/O mixed throughout the ejecta produce [O III] emission not seen in observations. (5) Shifts in the wavelength of line peaks can arise from line-blending effects. (6) The steepness of the ejecta density profile affects the line shapes, offering a constraint on explosion models. (7) Uncertainties in atomic data limit the ability to infer physical parameters.

Sensitivity Analysis of Expected Wind Extremes over the Northwestern Sahara and High Atlas Region.

NASA Astrophysics Data System (ADS)

Garcia-Bustamante, E.; González-Rouco, F. J.; Navarro, J.

2017-12-01

A robust statistical framework in the scientific literature allows for the estimation of probabilities of occurrence of severe wind speeds and wind gusts, but does not prevent however from large uncertainties associated with the particular numerical estimates. An analysis of such uncertainties is thus required. A large portion of this uncertainty arises from the fact that historical observations are inherently shorter that the timescales of interest for the analysis of return periods. Additional uncertainties stem from the different choices of probability distributions and other aspects related to methodological issues or physical processes involved. The present study is focused on historical observations over the Ouarzazate Valley (Morocco) and in a high-resolution regional simulation of the wind in the area of interest. The aim is to provide extreme wind speed and wind gust return values and confidence ranges based on a systematic sampling of the uncertainty space for return periods up to 120 years.

Optimal design and uncertainty quantification in blood flow simulations for congenital heart disease

NASA Astrophysics Data System (ADS)

Marsden, Alison

2009-11-01

Recent work has demonstrated substantial progress in capabilities for patient-specific cardiovascular flow simulations. Recent advances include increasingly complex geometries, physiological flow conditions, and fluid structure interaction. However inputs to these simulations, including medical image data, catheter-derived pressures and material properties, can have significant uncertainties associated with them. For simulations to predict clinically useful and reliable output information, it is necessary to quantify the effects of input uncertainties on outputs of interest. In addition, blood flow simulation tools can now be efficiently coupled to shape optimization algorithms for surgery design applications, and these tools should incorporate uncertainty information. We present a unified framework to systematically and efficient account for uncertainties in simulations using adaptive stochastic collocation. In addition, we present a framework for derivative-free optimization of cardiovascular geometries, and layer these tools to perform optimization under uncertainty. These methods are demonstrated using simulations and surgery optimization to improve hemodynamics in pediatric cardiology applications.

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: testing gravity with redshift space distortions using the power spectrum multipoles

NASA Astrophysics Data System (ADS)

Beutler, Florian; Saito, Shun; Seo, Hee-Jong; Brinkmann, Jon; Dawson, Kyle S.; Eisenstein, Daniel J.; Font-Ribera, Andreu; Ho, Shirley; McBride, Cameron K.; Montesano, Francesco; Percival, Will J.; Ross, Ashley J.; Ross, Nicholas P.; Samushia, Lado; Schlegel, David J.; Sánchez, Ariel G.; Tinker, Jeremy L.; Weaver, Benjamin A.

2014-09-01

We analyse the anisotropic clustering of the Baryon Oscillation Spectroscopic Survey (BOSS) CMASS Data Release 11 (DR11) sample, which consists of 690 827 galaxies in the redshift range 0.43 < z < 0.7 and has a sky coverage of 8498 deg2. We perform our analysis in Fourier space using a power spectrum estimator suggested by Yamamoto et al. We measure the multipole power spectra in a self-consistent manner for the first time in the sense that we provide a proper way to treat the survey window function and the integral constraint, without the commonly used assumption of an isotropic power spectrum and without the need to split the survey into subregions. The main cosmological signals exploited in our analysis are the baryon acoustic oscillations and the signal of redshift space distortions, both of which are distorted by the Alcock-Paczynski effect. Together, these signals allow us to constrain the distance ratio DV(zeff)/rs(zd) = 13.89 ± 0.18, the Alcock-Paczynski parameter FAP(zeff) = 0.679 ± 0.031 and the growth rate of structure f (zeff)σ8(zeff) = 0.419 ± 0.044 at the effective redshift zeff = 0.57. We emphasize that our constraints are robust against possible systematic uncertainties. In order to ensure this, we perform a detailed systematics study against CMASS mock galaxy catalogues and N-body simulations. We find that such systematics will lead to 3.1 per cent uncertainty for fσ8 if we limit our fitting range to k = 0.01-0.20 h Mpc-1, where the statistical uncertainty is expected to be three times larger. We did not find significant systematic uncertainties for DV/rs or FAP. Combining our data set with Planck to test General Relativity (GR) through the simple γ-parametrization, where the growth rate is given by f(z) = Ω ^{γ }_m(z), reveals a ˜2σ tension between the data and the prediction by GR. The tension between our result and GR can be traced back to a tension in the clustering amplitude σ8 between CMASS and Planck.

SU-E-CAMPUS-J-05: Quantitative Investigation of Random and Systematic Uncertainties From Hardware and Software Components in the Frameless 6DBrainLAB ExacTrac System

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

Keeling, V; Jin, H; Hossain, S

2014-06-15

Purpose: To evaluate setup accuracy and quantify individual systematic and random errors for the various hardware and software components of the frameless 6D-BrainLAB ExacTrac system. Methods: 35 patients with cranial lesions, some with multiple isocenters (50 total lesions treated in 1, 3, 5 fractions), were investigated. All patients were simulated with a rigid head-and-neck mask and the BrainLAB localizer. CT images were transferred to the IPLAN treatment planning system where optimized plans were generated using stereotactic reference frame based on the localizer. The patients were setup initially with infrared (IR) positioning ExacTrac system. Stereoscopic X-ray images (XC: X-ray Correction) weremore » registered to their corresponding digitally-reconstructed-radiographs, based on bony anatomy matching, to calculate 6D-translational and rotational (Lateral, Longitudinal, Vertical, Pitch, Roll, Yaw) shifts. XC combines systematic errors of the mask, localizer, image registration, frame, and IR. If shifts were below tolerance (0.7 mm translational and 1 degree rotational), treatment was initiated; otherwise corrections were applied and additional X-rays were acquired to verify patient position (XV: X-ray Verification). Statistical analysis was used to extract systematic and random errors of the different components of the 6D-ExacTrac system and evaluate the cumulative setup accuracy. Results: Mask systematic errors (translational; rotational) were the largest and varied from one patient to another in the range (−15 to 4mm; −2.5 to 2.5degree) obtained from mean of XC for each patient. Setup uncertainty in IR positioning (0.97,2.47,1.62mm;0.65,0.84,0.96degree) was extracted from standard-deviation of XC. Combined systematic errors of the frame and localizer (0.32,−0.42,−1.21mm; −0.27,0.34,0.26degree) was extracted from mean of means of XC distributions. Final patient setup uncertainty was obtained from the standard deviations of XV (0.57,0.77,0.67mm,0.39,0.35,0.30degree). Conclusion: Statistical analysis was used to calculate cumulative and individual systematic errors from the different hardware and software components of the 6D-ExacTrac-system. Patients were treated with cumulative errors (<1mm,<1degree) with XV image guidance.« less

Detailed Uncertainty Analysis for Ares I Ascent Aerodynamics Wind Tunnel Database

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Hanke, Jeremy L.; Walker, Eric L.; Houlden, Heather P.

2008-01-01

A detailed uncertainty analysis for the Ares I ascent aero 6-DOF wind tunnel database is described. While the database itself is determined using only the test results for the latest configuration, the data used for the uncertainty analysis comes from four tests on two different configurations at the Boeing Polysonic Wind Tunnel in St. Louis and the Unitary Plan Wind Tunnel at NASA Langley Research Center. Four major error sources are considered: (1) systematic errors from the balance calibration curve fits and model + balance installation, (2) run-to-run repeatability, (3) boundary-layer transition fixing, and (4) tunnel-to-tunnel reproducibility.

Using spatial uncertainty to manipulate the size of the attention focus.

PubMed

Huang, Dan; Xue, Linyan; Wang, Xin; Chen, Yao

2016-09-01

Preferentially processing behaviorally relevant information is vital for primate survival. In visuospatial attention studies, manipulating the spatial extent of attention focus is an important question. Although many studies have claimed to successfully adjust attention field size by either varying the uncertainty about the target location (spatial uncertainty) or adjusting the size of the cue orienting the attention focus, no systematic studies have assessed and compared the effectiveness of these methods. We used a multiple cue paradigm with 2.5° and 7.5° rings centered around a target position to measure the cue size effect, while the spatial uncertainty levels were manipulated by changing the number of cueing positions. We found that spatial uncertainty had a significant impact on reaction time during target detection, while the cue size effect was less robust. We also carefully varied the spatial scope of potential target locations within a small or large region and found that this amount of variation in spatial uncertainty can also significantly influence target detection speed. Our results indicate that adjusting spatial uncertainty is more effective than varying cue size when manipulating attention field size.

The health economics of ankle and foot sprains and fractures: A systematic review of English-language published papers. Part 1: Overview and critical appraisal.

PubMed

Bielska, Iwona A; Wang, Xiang; Lee, Raymond; Johnson, Ana P

2017-07-01

Ankle and foot sprains and fractures are common injuries affecting many individuals, often requiring considerable and costly medical interventions. The objectives of this systematic review are to collect, assess, and critically appraise the published literature on the health economics of ankle and foot injury (sprain and fracture) treatment. A systematic literature review of Ovid MEDLINE, EMBASE, Cochrane DSR, ACP Journal Club, AMED, Ovid Healthstar, and CINAHL was conducted for English-language studies on the costs of treating ankle and foot sprains and fractures published from January 1980 to December 2014. Two reviewers assessed the articles for study quality and abstracted data. The literature search identified 2047 studies of which 32 were analyzed. A majority of the studies were published in the last decade. A number of the studies did not report full economic information, including the sources of the direct and indirect costs, as suggested in the guidelines. The perspective used in the analysis was missing in numerous studies, as was the follow-up time period of participants. Only five of the studies undertook a sensitivity analysis which is required whenever there are uncertainties regarding cost data. This systematic review found that publications do not consistently report on the components of health economics methodology, which in turn limits the quality of information. Future studies undertaking economic evaluations should ensure that their methods are transparent and understandable so as to yield accurate interpretation for assistance in forthcoming economic evaluations and policy decision-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

The new g-2 experiment at Fermilab

NASA Astrophysics Data System (ADS)

Anastasi, A.

2017-04-01

There is a long standing discrepancy between the Standard Model prediction for the muon g-2 and the value measured by the Brookhaven E821 Experiment. At present the discrepancy stands at about three standard deviations, with an uncertainty dominated by the theoretical error. Two new proposals - at Fermilab and J-PARC - plan to improve the experimental uncertainty by a factor of 4, and it is expected that there will be a significant reduction in the uncertainty of the Standard Model prediction. I will review the status of the planned experiment at Fermilab, E989, which will analyse 21 times more muons than the BNL experiment and discuss how the systematic uncertainty will be reduced by a factor of 3 such that a precision of 0.14 ppm can be achieved.

Robust control of the DC-DC boost converter based on the uncertainty and disturbance estimator

NASA Astrophysics Data System (ADS)

Oucheriah, Said

2017-11-01

In this paper, a robust non-linear controller based on the uncertainty and disturbance estimator (UDE) scheme is successfully developed and implemented for the output voltage regulation of the DC-DC boost converter. System uncertainties, external disturbances and unknown non-linear dynamics are lumped as a signal that is accurately estimated using a low-pass filter and their effects are cancelled by the controller. This methodology forms the basis of the UDE-based controller. A simple procedure is also developed that systematically determines the parameters of the controller to meet certain specifications. Using simulation, the effectiveness of the proposed controller is compared against the sliding-mode control (SMC). Experimental tests also show that the proposed controller is robust to system uncertainties, large input and load perturbations.

Constituent quarks and systematic errors in mid-rapidity charged multiplicity dN ch/dη distributions

DOE PAGES

Tannenbaum, M. J.

2018-01-10

Centrality definition in A + A collisions at colliders such as RHIC and LHC suffers from a correlated systematic uncertainty caused by the efficiency of detecting a p + p collision (50 ± 5% for PHENIX at RHIC). In A + A collisions where centrality is measured by the number of nucleon collisions, N coll, or the number of nucleon participants, N part, or the number of constituent quark participants, N qp, the error in the efficiency of the primary interaction trigger (Beam–Beam Counters) for a p + p collision leads to a correlated systematic uncertainty in N part, Nmore » coll or N qp which reduces binomially as the A + A collisions become more central. If this is not correctly accounted for in projections of A + A to p + p collisions, then mistaken conclusions can result. Finally, a recent example is presented in whether the mid-rapidity charged multiplicity per constituent quark participant d(N ch/dη)/N qp in Au + Au at RHIC was the same as the value in p + p collisions.« less

Constituent quarks and systematic errors in mid-rapidity charged multiplicity dN ch/dη distributions

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

Tannenbaum, M. J.

Centrality definition in A + A collisions at colliders such as RHIC and LHC suffers from a correlated systematic uncertainty caused by the efficiency of detecting a p + p collision (50 ± 5% for PHENIX at RHIC). In A + A collisions where centrality is measured by the number of nucleon collisions, N coll, or the number of nucleon participants, N part, or the number of constituent quark participants, N qp, the error in the efficiency of the primary interaction trigger (Beam–Beam Counters) for a p + p collision leads to a correlated systematic uncertainty in N part, Nmore » coll or N qp which reduces binomially as the A + A collisions become more central. If this is not correctly accounted for in projections of A + A to p + p collisions, then mistaken conclusions can result. Finally, a recent example is presented in whether the mid-rapidity charged multiplicity per constituent quark participant d(N ch/dη)/N qp in Au + Au at RHIC was the same as the value in p + p collisions.« less

Reduction and Uncertainty Analysis of Chemical Mechanisms Based on Local and Global Sensitivities

NASA Astrophysics Data System (ADS)

Esposito, Gaetano

Numerical simulations of critical reacting flow phenomena in hypersonic propulsion devices require accurate representation of finite-rate chemical kinetics. The chemical kinetic models available for hydrocarbon fuel combustion are rather large, involving hundreds of species and thousands of reactions. As a consequence, they cannot be used in multi-dimensional computational fluid dynamic calculations in the foreseeable future due to the prohibitive computational cost. In addition to the computational difficulties, it is also known that some fundamental chemical kinetic parameters of detailed models have significant level of uncertainty due to limited experimental data available and to poor understanding of interactions among kinetic parameters. In the present investigation, local and global sensitivity analysis techniques are employed to develop a systematic approach of reducing and analyzing detailed chemical kinetic models. Unlike previous studies in which skeletal model reduction was based on the separate analysis of simple cases, in this work a novel strategy based on Principal Component Analysis of local sensitivity values is presented. This new approach is capable of simultaneously taking into account all the relevant canonical combustion configurations over different composition, temperature and pressure conditions. Moreover, the procedure developed in this work represents the first documented inclusion of non-premixed extinction phenomena, which is of great relevance in hypersonic combustors, in an automated reduction algorithm. The application of the skeletal reduction to a detailed kinetic model consisting of 111 species in 784 reactions is demonstrated. The resulting reduced skeletal model of 37--38 species showed that the global ignition/propagation/extinction phenomena of ethylene-air mixtures can be predicted within an accuracy of 2% of the full detailed model. The problems of both understanding non-linear interactions between kinetic parameters and identifying sources of uncertainty affecting relevant reaction pathways are usually addressed by resorting to Global Sensitivity Analysis (GSA) techniques. In particular, the most sensitive reactions controlling combustion phenomena are first identified using the Morris Method and then analyzed under the Random Sampling -- High Dimensional Model Representation (RS-HDMR) framework. The HDMR decomposition shows that 10% of the variance seen in the extinction strain rate of non-premixed flames is due to second-order effects between parameters, whereas the maximum concentration of acetylene, a key soot precursor, is affected by mostly only first-order contributions. Moreover, the analysis of the global sensitivity indices demonstrates that improving the accuracy of the reaction rates including the vinyl radical, C2H3, can drastically reduce the uncertainty of predicting targeted flame properties. Finally, the back-propagation of the experimental uncertainty of the extinction strain rate to the parameter space is also performed. This exercise, achieved by recycling the numerical solutions of the RS-HDMR, shows that some regions of the parameter space have a high probability of reproducing the experimental value of the extinction strain rate between its own uncertainty bounds. Therefore this study demonstrates that the uncertainty analysis of bulk flame properties can effectively provide information on relevant chemical reactions.

Exploring the Efficacy and Limitations of Shock-cooling Models: New Analysis of Type II Supernovae Observed by the Kepler Mission

NASA Astrophysics Data System (ADS)

Rubin, Adam; Gal-Yam, Avishay

2017-10-01

Modern transient surveys have begun discovering and following supernovae (SNe) shortly after first light—providing systematic measurements of the rise of Type II SNe. We explore how analytic models of early shock-cooling emission from core-collapse SNe can constrain the progenitor’s radius, explosion velocity, and local host extinction. We simulate synthetic photometry in several realistic observing scenarios; assuming the models describe the typical explosions well, we find that ultraviolet observations can constrain the progenitor’s radius to a statistical uncertainty of ±10%-15%, with a systematic uncertainty of ±20%. With these observations the local host extinction (A V ) can be constrained to a factor of two and the shock velocity to ±5% with a systematic uncertainty of ±10%. We also reanalyze the SN light curves presented by Garnavich et al. (2016) and find that KSN 2011a can be fit by a blue supergiant model with a progenitor radius of {R}s< 7.7+8.8({stat})+1.9({sys}) {R}⊙ , while KSN 2011d can be fit with a red supergiant model with a progenitor radius of {R}s={111}-21({stat)-1({sys})}+89({stat)+49({sys})} {R}⊙ . Our results do not agree with those of Garnavich et al. Moreover, we re-evaluate their claims and find that there is no statistically significant evidence for a shock-breakout flare in the light curve of KSN 2011d.

Error Detection and Recovery for Robot Motion Planning with Uncertainty.

DTIC Science & Technology

1987-07-01

plans for these problems . This intuition-which is a heuristic claim, so the reader is advised to proceed with caution--should be verified or disproven...that might work. but fail in a --reasonable" way when they cannot. While EDR is largely motivated by the problems of uncertainty and model error. its...definition for EDR strategies and show how they can be computed. This theory represents what is perhaps the first systematic attack on the problem of

Factors affecting measurement of channel thickness in asymmetrical flow field-flow fractionation.

PubMed

Dou, Haiyang; Jung, Euo Chang; Lee, Seungho

2015-05-08

Asymmetrical flow field-flow fractionation (AF4) has been considered to be a useful tool for simultaneous separation and characterization of polydisperse macromolecules or colloidal nanoparticles. AF4 analysis requires the knowledge of the channel thickness (w), which is usually measured by injecting a standard with known diffusion coefficient (D) or hydrodynamic diameter (dh). An accurate w determination is a challenge due to its uncertainties arising from the membrane's compressibility, which may vary with experimental condition. In the present study, influence of factors including the size and type of the standard on the measurement of w was systematically investigated. The results revealed that steric effect and the particles-membrane interaction by van der Waals or electrostatic force may result in an error in w measurement. Copyright © 2015 Elsevier B.V. All rights reserved.

Drought Persistence Errors in Global Climate Models

NASA Astrophysics Data System (ADS)

Moon, H.; Gudmundsson, L.; Seneviratne, S. I.

2018-04-01

The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, but the capability of current global climate models (GCMs) to simulate such events is subject to large uncertainties. In this study, the representation of drought persistence in GCMs is assessed by comparing state-of-the-art GCM model simulations to observation-based data sets. For doing so, we consider dry-to-dry transition probabilities at monthly and annual scales as estimates for drought persistence, where a dry status is defined as negative precipitation anomaly. Though there is a substantial spread in the drought persistence bias, most of the simulations show systematic underestimation of drought persistence at global scale. Subsequently, we analyzed to which degree (i) inaccurate observations, (ii) differences among models, (iii) internal climate variability, and (iv) uncertainty of the employed statistical methods contribute to the spread in drought persistence errors using an analysis of variance approach. The results show that at monthly scale, model uncertainty and observational uncertainty dominate, while the contribution from internal variability is small in most cases. At annual scale, the spread of the drought persistence error is dominated by the statistical estimation error of drought persistence, indicating that the partitioning of the error is impaired by the limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current GCMs and suggest directions for further model improvement.

Target position uncertainty during visually guided deep-inspiration breath-hold radiotherapy in locally advanced lung cancer.

PubMed

Scherman Rydhög, Jonas; Riisgaard de Blanck, Steen; Josipovic, Mirjana; Irming Jølck, Rasmus; Larsen, Klaus Richter; Clementsen, Paul; Lars Andersen, Thomas; Poulsen, Per Rugaard; Fredberg Persson, Gitte; Munck Af Rosenschold, Per

2017-04-01

The purpose of this study was to estimate the uncertainty in voluntary deep-inspiration breath-hold (DIBH) radiotherapy for locally advanced non-small cell lung cancer (NSCLC) patients. Perpendicular fluoroscopic movies were acquired in free breathing (FB) and DIBH during a course of visually guided DIBH radiotherapy of nine patients with NSCLC. Patients had liquid markers injected in mediastinal lymph nodes and primary tumours. Excursion, systematic- and random errors, and inter-breath-hold position uncertainty were investigated using an image based tracking algorithm. A mean reduction of 2-6mm in marker excursion in DIBH versus FB was seen in the anterior-posterior (AP), left-right (LR) and cranio-caudal (CC) directions. Lymph node motion during DIBH originated from cardiac motion. The systematic- (standard deviation (SD) of all the mean marker positions) and random errors (root-mean-square of the intra-BH SD) during DIBH were 0.5 and 0.3mm (AP), 0.5 and 0.3mm (LR), 0.8 and 0.4mm (CC), respectively. The mean inter-breath-hold shifts were -0.3mm (AP), -0.2mm (LR), and -0.2mm (CC). Intra- and inter-breath-hold uncertainty of tumours and lymph nodes were small in visually guided breath-hold radiotherapy of NSCLC. Target motion could be substantially reduced, but not eliminated, using visually guided DIBH. Copyright © 2017 Elsevier B.V. All rights reserved.

Theoretical basis for operational ensemble forecasting of coronal mass ejections

NASA Astrophysics Data System (ADS)

Pizzo, V. J.; de Koning, C.; Cash, M.; Millward, G.; Biesecker, D. A.; Puga, L.; Codrescu, M.; Odstrcil, D.

2015-10-01

We lay out the theoretical underpinnings for the application of the Wang-Sheeley-Arge-Enlil modeling system to ensemble forecasting of coronal mass ejections (CMEs) in an operational environment. In such models, there is no magnetic cloud component, so our results pertain only to CME front properties, such as transit time to Earth. Within this framework, we find no evidence that the propagation is chaotic, and therefore, CME forecasting calls for different tactics than employed for terrestrial weather or hurricane forecasting. We explore a broad range of CME cone inputs and ambient states to flesh out differing CME evolutionary behavior in the various dynamical domains (e.g., large, fast CMEs launched into a slow ambient, and the converse; plus numerous permutations in between). CME propagation in both uniform and highly structured ambient flows is considered to assess how much the solar wind background affects the CME front properties at 1 AU. Graphical and analytic tools pertinent to an ensemble approach are developed to enable uncertainties in forecasting CME impact at Earth to be realistically estimated. We discuss how uncertainties in CME pointing relative to the Sun-Earth line affects the reliability of a forecast and how glancing blows become an issue for CME off-points greater than about the half width of the estimated input CME. While the basic results appear consistent with established impressions of CME behavior, the next step is to use existing records of well-observed CMEs at both Sun and Earth to verify that real events appear to follow the systematic tendencies presented in this study.

Global statistics of microphysical properties of cloud-top ice crystals

NASA Astrophysics Data System (ADS)

van Diedenhoven, B.; Fridlind, A. M.; Cairns, B.; Ackerman, A. S.; Riedi, J.

2017-12-01

Ice crystals in clouds are highly complex. Their sizes, macroscale shape (i.e., habit), mesoscale shape (i.e., aspect ratio of components) and microscale shape (i.e., surface roughness) determine optical properties and affect physical properties such as fall speeds, growth rates and aggregation efficiency. Our current understanding on the formation and evolution of ice crystals under various conditions can be considered poor. Commonly, ice crystal size and shape are related to ambient temperature and humidity, but global observational statistics on the variation of ice crystal size and particularly shape have not been available. Here we show results of a project aiming to infer ice crystal size, shape and scattering properties from a combination of MODIS measurements and POLDER-PARASOL multi-angle polarimetry. The shape retrieval procedure infers the mean aspect ratios of components of ice crystals and the mean microscale surface roughness levels, which are quantifiable parameters that mostly affect the scattering properties, in contrast to "habit". We present global statistics on the variation of ice effective radius, component aspect ratio, microscale surface roughness and scattering asymmetry parameter as a function of cloud top temperature, latitude, location, cloud type, season, etc. Generally, with increasing height, sizes decrease, roughness increases, asymmetry parameters decrease and aspect ratios increase towards unity. Some systematic differences are observed for clouds warmer and colder than the homogeneous freezing level. Uncertainties in the retrievals will be discussed. These statistics can be used as observational targets for modeling efforts and to better constrain other satellite remote sensing applications and their uncertainties.

Global Statistics of Microphysical Properties of Cloud-Top Ice Crystals

NASA Technical Reports Server (NTRS)

Van Diedenhoven, Bastiaan; Fridlind, Ann; Cairns, Brian; Ackerman, Andrew; Riedl, Jerome

2017-01-01

Ice crystals in clouds are highly complex. Their sizes, macroscale shape (i.e., habit), mesoscale shape (i.e., aspect ratio of components) and microscale shape (i.e., surface roughness) determine optical properties and affect physical properties such as fall speeds, growth rates and aggregation efficiency. Our current understanding on the formation and evolution of ice crystals under various conditions can be considered poor. Commonly, ice crystal size and shape are related to ambient temperature and humidity, but global observational statistics on the variation of ice crystal size and particularly shape have not been available. Here we show results of a project aiming to infer ice crystal size, shape and scattering properties from a combination of MODIS measurements and POLDER-PARASOL multi-angle polarimetry. The shape retrieval procedure infers the mean aspect ratios of components of ice crystals and the mean microscale surface roughness levels, which are quantifiable parameters that mostly affect the scattering properties, in contrast to a habit. We present global statistics on the variation of ice effective radius, component aspect ratio, microscale surface roughness and scattering asymmetry parameter as a function of cloud top temperature, latitude, location, cloud type, season, etc. Generally, with increasing height, sizes decrease, roughness increases, asymmetry parameters decrease and aspect ratios increase towards unity. Some systematic differences are observed for clouds warmer and colder than the homogeneous freezing level. Uncertainties in the retrievals will be discussed. These statistics can be used as observational targets for modeling efforts and to better constrain other satellite remote sensing applications and their uncertainties.

Surrogate gas prediction model as a proxy for Δ14C-based measurements of fossil fuel-CO2.

PubMed

Coakley, Kevin J; Miller, John B; Montzka, Stephen A; Sweeney, Colm; Miller, Ben R

2016-06-27

The measured 14 C: 12 C isotopic ratio of atmospheric CO 2 (and its associated derived Δ 14 C value) is an ideal tracer for determination of the fossil fuel derived CO 2 enhancement contributing to any atmospheric CO 2 measurement ( C ff ). Given enough such measurements, independent top-down estimation of US fossil fuel-CO 2 emissions should be possible. However, the number of Δ 14 C measurements is presently constrained by cost, available sample volume, and availability of mass spectrometer measurement facilities. Δ 14 C is therefore measured in just a small fraction of samples obtained by ask air sampling networks around the world. Here, we develop a Projection Pursuit Regression (PPR) model to predict C ff as a function of multiple surrogate gases acquired within the NOAA/ESRL Global Greenhouse Gas Reference Network (GGGRN). The surrogates consist of measured enhancements of various anthropogenic trace gases, including CO, SF 6 , and halo- and hydrocarbons acquired in vertical airborne sampling profiles near Cape May, NJ and Portsmouth, NH from 2005 through 2010. Model performance for these sites is quantified based on predicted values corresponding to test data excluded from the model building process. Chi-square hypothesis test analysis indicates that these predictions and corresponding observations are consistent given our uncertainty budget which accounts for random effects and one particular systematic effect. However, quantification of the combined uncertainty of the prediction due to all relevant systematic effects is difficult because of the limited range of the observations and their relatively high fractional uncertainties at the sampling sites considered here. To account for the possibility of additional systematic effects, we incorporate another component of uncertainty into our budget. Expanding the number of Δ 14 C measurements in the NOAA GGGRN and building new PPR models at additional sites would improve our understanding of uncertainties and potentially increase the number of C ff estimates by approximately a factor of three. Provided that these estimates are of comparable quality to Δ 14 C-based estimates, we expect an improved determination of fossil fuel-CO 2 emissions.

Sources of uncertanity as a basis to fill the information gap in a response to flood

NASA Astrophysics Data System (ADS)

Kekez, Toni; Knezic, Snjezana

2016-04-01

Taking into account uncertainties in flood risk management remains a challenge due to difficulties in choosing adequate structural and/or non-structural risk management options. Despite stated measures wrong decisions are often being made when flood occurs. Parameter and structural uncertainties which include model and observation errors as well as lack of knowledge about system characteristics are the main considerations. Real time flood risk assessment methods are predominantly based on measured water level values and vulnerability as well as other relevant characteristics of flood affected area. The goal of this research is to identify sources of uncertainties and to minimize information gap between the point where the water level is measured and the affected area, taking into consideration main uncertainties that can affect risk value at the observed point or section of the river. Sources of uncertainties are identified and determined using system analysis approach and relevant uncertainties are included in the risk assessment model. With such methodological approach it is possible to increase response time with more effective risk assessment which includes uncertainty propagation model. Response phase could be better planned with adequate early warning systems resulting in more time and less costs to help affected areas and save human lives. Reliable and precise information is necessary to raise emergency operability level in order to enhance safety of citizens and reducing possible damage. The results of the EPISECC (EU funded FP7) project are used to validate potential benefits of this research in order to improve flood risk management and response methods. EPISECC aims at developing a concept of a common European Information Space for disaster response which, among other disasters, considers the floods.

Affect, Risk and Uncertainty in Decision-Marking an Integrated Computational-Empirical Approach

DTIC Science & Technology

2009-07-26

OF ABSTRACT UU 18. NUMBER O PAGES 61 19a. NAME OF RESPONSIBLE PERSON Eva Hudlicka, Ph.D. 19b. TELEPHONE NUMBER (include area code...developed by Hudlicka (2002; 2003). MAMID was designed with the explicit purpose to model the effects of affective states and personality traits on...influenced by risk and uncertainty? • How do personality traits and affective states facilitate or prevent the expression of particular types of

Acute stress affects risk taking but not ambiguity aversion

PubMed Central

Buckert, Magdalena; Schwieren, Christiane; Kudielka, Brigitte M.; Fiebach, Christian J.

2014-01-01

Economic decisions are often made in stressful situations (e.g., at the trading floor), but the effects of stress on economic decision making have not been systematically investigated so far. The present study examines how acute stress influences economic decision making under uncertainty (risk and ambiguity) using financially incentivized lotteries. We varied the domain of decision making as well as the expected value of the risky prospect. Importantly, no feedback was provided to investigate risk taking and ambiguity aversion independent from learning processes. In a sample of 75 healthy young participants, 55 of whom underwent a stress induction protocol (Trier Social Stress Test for Groups), we observed more risk seeking for gains. This effect was restricted to a subgroup of participants that showed a robust cortisol response to acute stress (n = 26). Gambling under ambiguity, in contrast to gambling under risk, was not influenced by the cortisol response to stress. These results show that acute psychosocial stress affects economic decision making under risk, independent of learning processes. Our results further point to the importance of cortisol as a mediator of this effect. PMID:24834024

Acute stress affects risk taking but not ambiguity aversion.

PubMed

Buckert, Magdalena; Schwieren, Christiane; Kudielka, Brigitte M; Fiebach, Christian J

2014-01-01

Economic decisions are often made in stressful situations (e.g., at the trading floor), but the effects of stress on economic decision making have not been systematically investigated so far. The present study examines how acute stress influences economic decision making under uncertainty (risk and ambiguity) using financially incentivized lotteries. We varied the domain of decision making as well as the expected value of the risky prospect. Importantly, no feedback was provided to investigate risk taking and ambiguity aversion independent from learning processes. In a sample of 75 healthy young participants, 55 of whom underwent a stress induction protocol (Trier Social Stress Test for Groups), we observed more risk seeking for gains. This effect was restricted to a subgroup of participants that showed a robust cortisol response to acute stress (n = 26). Gambling under ambiguity, in contrast to gambling under risk, was not influenced by the cortisol response to stress. These results show that acute psychosocial stress affects economic decision making under risk, independent of learning processes. Our results further point to the importance of cortisol as a mediator of this effect.

Charge exchange in galaxy clusters

NASA Astrophysics Data System (ADS)

Gu, Liyi; Mao, Junjie; de Plaa, Jelle; Raassen, A. J. J.; Shah, Chintan; Kaastra, Jelle S.

2018-03-01

Context. Though theoretically expected, the charge exchange emission from galaxy clusters has never been confidently detected. Accumulating hints were reported recently, including a rather marginal detection with the Hitomi data of the Perseus cluster. As previously suggested, a detection of charge exchange line emission from galaxy clusters would not only impact the interpretation of the newly discovered 3.5 keV line, but also open up a new research topic on the interaction between hot and cold matter in clusters. Aim. We aim to perform the most systematic search for the O VIII charge exchange line in cluster spectra using the RGS on board XMM-Newton. Methods: We introduce a sample of 21 clusters observed with the RGS. In order to search for O VIII charge exchange, the sample selection criterion is a >35σ detection of the O VIII Lyα line in the archival RGS spectra. The dominating thermal plasma emission is modeled and subtracted with a two-temperature thermal component, and the residuals are stacked for the line search. The systematic uncertainties in the fits are quantified by refitting the spectra with a varying continuum and line broadening. Results: By the residual stacking, we do find a hint of a line-like feature at 14.82 Å, the characteristic wavelength expected for oxygen charge exchange. This feature has a marginal significance of 2.8σ, and the average equivalent width is 2.5 × 10-4 keV. We further demonstrate that the putative feature can be barely affected by the systematic errors from continuum modeling and instrumental effects, or the atomic uncertainties of the neighboring thermal lines. Conclusions: Assuming a realistic temperature and abundance pattern, the physical model implied by the possible oxygen line agrees well with the theoretical model proposed previously to explain the reported 3.5 keV line. If the charge exchange source indeed exists, we expect that the oxygen abundance could have been overestimated by 8-22% in previous X-ray measurements that assumed pure thermal lines. These new RGS results bring us one step forward to understanding the charge exchange phenomenon in galaxy clusters.

Predicting the Earth encounters of (99942) Apophis

NASA Technical Reports Server (NTRS)

Giorgini, Jon D.; Benner, Lance A. M.; Ostro, Steven J.; Nolan, Michael C.; Busch, Michael W.

2007-01-01

Arecibo delay-Doppler measurements of (99942) Apophis in 2005 and 2006 resulted in a five standard-deviation trajectory correction to the optically predicted close approach distance to Earth in 2029. The radar measurements reduced the volume of the statistical uncertainty region entering the encounter to 7.3% of the pre-radar solution, but increased the trajectory uncertainty growth rate across the encounter by 800% due to the closer predicted approach to the Earth. A small estimated Earth impact probability remained for 2036. With standard-deviation plane-of-sky position uncertainties for 2007-2010 already less than 0.2 arcsec, the best near-term ground-based optical astrometry can only weakly affect the trajectory estimate. While the potential for impact in 2036 will likely be excluded in 2013 (if not 2011) using ground-based optical measurements, approximations within the Standard Dynamical Model (SDM) used to estimate and predict the trajectory from the current era are sufficient to obscure the difference between a predicted impact and a miss in 2036 by altering the dynamics leading into the 2029 encounter. Normal impact probability assessments based on the SDM become problematic without knowledge of the object's physical properties; impact could be excluded while the actual dynamics still permit it. Calibrated position uncertainty intervals are developed to compensate for this by characterizing the minimum and maximum effect of physical parameters on the trajectory. Uncertainty in accelerations related to solar radiation can cause between 82 and 4720 Earth-radii of trajectory change relative to the SDM by 2036. If an actionable hazard exists, alteration by 2-10% of Apophis' total absorption of solar radiation in 2018 could be sufficient to produce a six standard-deviation trajectory change by 2036 given physical characterization; even a 0.5% change could produce a trajectory shift of one Earth-radius by 2036 for all possible spin-poles and likely masses. Planetary ephemeris uncertainties are the next greatest source of systematic error, causing up to 23 Earth-radii of uncertainty. The SDM Earth point-mass assumption introduces an additional 2.9 Earth-radii of prediction error by 2036. Unmodeled asteroid perturbations produce as much as 2.3 Earth-radii of error. We find no future small-body encounters likely to yield an Apophis mass determination prior to 2029. However, asteroid (144898) 2004 VD17, itself having a statistical Earth impact in 2102, will probably encounter Apophis at 6.7 lunar distances in 2034, their uncertainty regions coming as close as 1.6 lunar distances near the center of both SDM probability distributions.

A Reassessment of the Precision of Carbonate Clumped Isotope Measurements: Implications for Calibrations and Paleoclimate Reconstructions

NASA Astrophysics Data System (ADS)

Fernandez, Alvaro; Müller, Inigo A.; Rodríguez-Sanz, Laura; van Dijk, Joep; Looser, Nathan; Bernasconi, Stefano M.

2017-12-01

Carbonate clumped isotopes offer a potentially transformational tool to interpret Earth's history, but the proxy is still limited by poor interlaboratory reproducibility. Here, we focus on the uncertainties that result from the analysis of only a few replicate measurements to understand the extent to which unconstrained errors affect calibration relationships and paleoclimate reconstructions. We find that highly precise data can be routinely obtained with multiple replicate analyses, but this is not always done in many laboratories. For instance, using published estimates of external reproducibilities we find that typical clumped isotope measurements (three replicate analyses) have margins of error at the 95% confidence level (CL) that are too large for many applications. These errors, however, can be systematically reduced with more replicate measurements. Second, using a Monte Carlo-type simulation we demonstrate that the degree of disagreement on published calibration slopes is about what we should expect considering the precision of Δ47 data, the number of samples and replicate analyses, and the temperature range covered in published calibrations. Finally, we show that the way errors are typically reported in clumped isotope data can be problematic and lead to the impression that data are more precise than warranted. We recommend that uncertainties in Δ47 data should no longer be reported as the standard error of a few replicate measurements. Instead, uncertainties should be reported as margins of error at a specified confidence level (e.g., 68% or 95% CL). These error bars are a more realistic indication of the reliability of a measurement.

239Pu(n,γ) from 10 eV to 1.3 MeV

DOE PAGES

Mosby, Shea Morgan; Bredeweg, Todd Allen; Couture, Aaron Joseph; ...

2018-02-01

In this study, the 239Pu(n,γ) cross section has been measured from 10 eV to 1.3 MeV as part of an experimental campaign using the Detector for Advanced Neutron Capture Experiments (DANCE). The work represents a significant advance in experimental technique, with improved systematic uncertainties in key regions in the keV to MeV regime. In general the results of prior work are confirmed with improved uncertainties, particularly at the highest incident neutron energies.

239Pu(n,γ) from 10 eV to 1.3 MeV

NASA Astrophysics Data System (ADS)

Mosby, S.; Bredeweg, T. A.; Couture, A.; Jandel, M.; Kawano, T.; Ullmann, J.; Henderson, R. A.; Wu, C. Y.

2018-02-01

The 239Pu(n,γ) cross section has been measured from 10 eV to 1.3 MeV as part of an experimental campaign using the Detector for Advanced Neutron Capture Experiments (DANCE). The work represents a significant advance in experimental technique, with improved systematic uncertainties in key regions in the keV to MeV regime. In general the results of prior work are confirmed with improved uncertainties, particularly at the highest incident neutron energies.

Certainty Equivalence M-MRAC for Systems with Unmatched Uncertainties

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

The paper presents a certainty equivalence state feedback indirect adaptive control design method for the systems of any relative degree with unmatched uncertainties. The approach is based on the parameter identification (estimation) model, which is completely separated from the control design and is capable of producing parameter estimates as fast as the computing power allows without generating high frequency oscillations. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters.

Recent progress in the studies of neutron-rich and high-$Z$ systems within the covariant density functional theory

DOE PAGES

Afanasjev, Anatoli V.; Agbemava, S. E.; Ray, D.; ...

2017-01-01

Here, the analysis of statistical and systematic uncertainties and their propagation to nuclear extremes has been performed. Two extremes of nuclear landscape (neutron-rich nuclei and superheavy nuclei) have been investigated. For the first extreme, we focus on the ground state properties. For the second extreme, we pay a particular attention to theoretical uncertainties in the description of fission barriers of superheavy nuclei and their evolution on going to neutron-rich nuclei.

Measurement of the W-boson mass in pp collisions at $$\\sqrt{s}=7 TeV$$ with the ATLAS detector

DOE PAGES

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

2018-02-06

A measurement of the mass of the W boson is presented based on proton–proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC, and corresponding to 4.6 fb -1 of integrated luminosity. The selected data sample consists of 7.8 × 10 6 candidates in the W→μν channel and 5.9×10 6 candidates in the W→eν channel. The W-boson mass is obtained from template fits to the reconstructed distributions of the charged lepton transverse momentum and of the W boson transverse mass in the electron and muon decay channels, yielding m Wmore » =80370 ± 7 (stat.) ± 11 (exp.syst.) ±14 (mod.syst.) MeV = 80370 ± 19 MeV where the first uncertainty is statistical, the second corresponds to the experimental systematic uncertainty, and the third to the physics-modelling systematic uncertainty. Finally, a measurement of the mass difference between the W + and W - bosons yields m W + -m W = -29 ± 28 MeV.« less

Measurement of the top quark mass using charged particles in pp collisions at √s = 8 TeV

DOE PAGES

Khachatryan, Vardan

2016-05-18

A novel technique for measuring the mass of the top quark that uses only the kinematic properties of its charged decay products is presented. Top quark pair events with final states with one or two charged leptons and hadronic jets are selected from the data set of 8 TeV proton-proton collisions, corresponding to an integrated luminosity of 19.7 fb -1. By reconstructing secondary vertices inside the selected jets and computing the invariant mass of the system formed by the secondary vertex and an isolated lepton, an observable is constructed that is sensitive to the top quark mass that is expected tomore » be robust against the energy scale of hadronic jets. The main theoretical systematic uncertainties, concerning the modeling of the fragmentation and hadronization of b quarks and the reconstruction of secondary vertices from the decays of b hadrons, are studied. A top quark mass of 173.68±0.20(stat) -0.97 +1.58(syst) GeV is measured. Furthermore, the overall systematic uncertainty is dominated by the uncertainty in the b quark fragmentation and the modeling of kinematic properties of the top quark.« less

An exacting transition probability measurement - a direct test of atomic many-body theories.

PubMed

Dutta, Tarun; De Munshi, Debashis; Yum, Dahyun; Rebhi, Riadh; Mukherjee, Manas

2016-07-19

A new protocol for measuring the branching fraction of hydrogenic atoms with only statistically limited uncertainty is proposed and demonstrated for the decay of the P3/2 level of the barium ion, with precision below 0.5%. Heavy hydrogenic atoms like the barium ion are test beds for fundamental physics such as atomic parity violation and they also hold the key to understanding nucleo-synthesis in stars. To draw definitive conclusion about possible physics beyond the standard model by measuring atomic parity violation in the barium ion it is necessary to measure the dipole transition probabilities of low-lying excited states with a precision better than 1%. Furthermore, enhancing our understanding of the barium puzzle in barium stars requires branching fraction data for proper modelling of nucleo-synthesis. Our measurements are the first to provide a direct test of quantum many-body calculations on the barium ion with a precision below one percent and more importantly with no known systematic uncertainties. The unique measurement protocol proposed here can be easily extended to any decay with more than two channels and hence paves the way for measuring the branching fractions of other hydrogenic atoms with no significant systematic uncertainties.

Measurement of the W-boson mass in pp collisions at $$\\sqrt{s}=7 TeV$$ with the ATLAS detector

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

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

A measurement of the mass of the W boson is presented based on proton–proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC, and corresponding to 4.6 fb -1 of integrated luminosity. The selected data sample consists of 7.8 × 10 6 candidates in the W→μν channel and 5.9×10 6 candidates in the W→eν channel. The W-boson mass is obtained from template fits to the reconstructed distributions of the charged lepton transverse momentum and of the W boson transverse mass in the electron and muon decay channels, yielding m Wmore » =80370 ± 7 (stat.) ± 11 (exp.syst.) ±14 (mod.syst.) MeV = 80370 ± 19 MeV where the first uncertainty is statistical, the second corresponds to the experimental systematic uncertainty, and the third to the physics-modelling systematic uncertainty. Finally, a measurement of the mass difference between the W + and W - bosons yields m W + -m W = -29 ± 28 MeV.« less

Impaired limb proprioception in adults with spasmodic dysphonia

PubMed Central

Konczak, Jürgen; Aman, Joshua E.; Chen, Yu-Wen; Li, Kuan-yi; Watson, Peter J.

2015-01-01

Objectives Focal dystonia of the head, neck are associated with a loss of kinaesthetic acuity at muscles distant from the dystonic sites. That is, while the motor deficits in focal dystonia are confined, the associated somatosensory deficits are generalized. This is the first systematic study to examine, if patients diagnosed with spasmodic dystonia (SD) show somatosensory impairments similar in scope to other forms of focal dystonia. Methods Proprioceptive acuity (ability to discriminate between two stimuli) for forearm position and motion sense was assessed in 14 spasmodic dystonia subjects and 28 age-matched controls using a passive motion apparatus. Psychophysical thresholds, uncertainty area and a proprioceptive acuity index were computed based on the subjects’ verbal responses. Results The main findings are: First, the SD group showed significantly elevated thresholds and uncertainty areas for forearm position sense when compared to the control group. Second, 9 out of 14 dystonia subjects (64%) exhibited an acuity index for position sense above the control group maximum. Three SD subjects had a motion sense acuity index above the control group maximum. Conclusion The results indicate that impaired limb proprioception is a common feature of SD. Like other forms of focal dystonia, spasmodic dystonia does affect the somatosensation of non-dystonic muscle systems. That is, SD is associated with a generalized somatosensory deficit. PMID:25737471

Reducing, Maintaining, or Escalating Uncertainty? The Development and Validation of Four Uncertainty Preference Scales Related to Cancer Information Seeking and Avoidance.

PubMed

Carcioppolo, Nick; Yang, Fan; Yang, Qinghua

2016-09-01

Uncertainty is a central characteristic of many aspects of cancer prevention, screening, diagnosis, and treatment. Brashers's (2001) uncertainty management theory details the multifaceted nature of uncertainty and describes situations in which uncertainty can both positively and negatively affect health outcomes. The current study extends theory on uncertainty management by developing four scale measures of uncertainty preferences in the context of cancer. Two national surveys were conducted to validate the scales and assess convergent and concurrent validity. Results support the factor structure of each measure and provide general support across multiple validity assessments. These scales can advance research on uncertainty and cancer communication by providing researchers with measures that address multiple aspects of uncertainty management.

Determination of the fine structure constant based on BLOCH oscillations of ultracold atoms in a vertical optical lattice.

PubMed

Cladé, Pierre; de Mirandes, Estefania; Cadoret, Malo; Guellati-Khélifa, Saïda; Schwob, Catherine; Nez, François; Julien, Lucile; Biraben, François

2006-01-27

We report an accurate measurement of the recoil velocity of 87Rb atoms based on Bloch oscillations in a vertical accelerated optical lattice. We transfer about 900 recoil momenta with an efficiency of 99.97% per recoil. A set of 72 measurements of the recoil velocity, each one with a relative uncertainty of about 33 ppb in 20 min integration time, leads to a determination of the fine structure constant with a statistical relative uncertainty of 4.4 ppb. The detailed analysis of the different systematic errors yields to a relative uncertainty of 6.7 ppb. The deduced value of alpha-1 is 137.035 998 78(91).

Work Uncertainty and the Promotion of Professional Women: The Case of Law Firm Partnership

ERIC Educational Resources Information Center

Gorman, Elizabeth H.

2006-01-01

Work uncertainty may affect gender disparities in professionals' upward mobility in organizational hierarchies. Professional work involves three forms of uncertainty--problem variability, strategic indeterminacy and dependence on autonomous actors--that weaken the association between performance and ability, leading organizational decision-makers…

Hard Constraints in Optimization Under Uncertainty

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Giesy, Daniel P.; Kenny, Sean P.

2008-01-01

This paper proposes a methodology for the analysis and design of systems subject to parametric uncertainty where design requirements are specified via hard inequality constraints. Hard constraints are those that must be satisfied for all parameter realizations within a given uncertainty model. Uncertainty models given by norm-bounded perturbations from a nominal parameter value, i.e., hyper-spheres, and by sets of independently bounded uncertain variables, i.e., hyper-rectangles, are the focus of this paper. These models, which are also quite practical, allow for a rigorous mathematical treatment within the proposed framework. Hard constraint feasibility is determined by sizing the largest uncertainty set for which the design requirements are satisfied. Analytically verifiable assessments of robustness are attained by comparing this set with the actual uncertainty model. Strategies that enable the comparison of the robustness characteristics of competing design alternatives, the description and approximation of the robust design space, and the systematic search for designs with improved robustness are also proposed. Since the problem formulation is generic and the tools derived only require standard optimization algorithms for their implementation, this methodology is applicable to a broad range of engineering problems.

Development of Probabilistic Socio-Economic Emissions Scenarios (2012)

EPA Pesticide Factsheets

The purpose of this analysis is to help overcome these limitations through the development of a publically available library of socio-economic-emissions projections derived from a systematic examination of uncertainty in key underlying model parameters, w

Systematics for T2K/Hyper-K (Review Talk)

NASA Astrophysics Data System (ADS)

Shah, Raj

Hyper-Kamiokande is a proposed next generation underground water Cherenkov detector. Presented here is a review of sensitivities and dominant uncertainties associated with measurements of CP violation and non-maximal mixing in the 2-3 sector.

UNITY: Confronting Supernova Cosmology's Statistical and Systematic Uncertainties in a Unified Bayesian Framework

NASA Astrophysics Data System (ADS)

Rubin, D.; Aldering, G.; Barbary, K.; Boone, K.; Chappell, G.; Currie, M.; Deustua, S.; Fagrelius, P.; Fruchter, A.; Hayden, B.; Lidman, C.; Nordin, J.; Perlmutter, S.; Saunders, C.; Sofiatti, C.; Supernova Cosmology Project, The

2015-11-01

While recent supernova (SN) cosmology research has benefited from improved measurements, current analysis approaches are not statistically optimal and will prove insufficient for future surveys. This paper discusses the limitations of current SN cosmological analyses in treating outliers, selection effects, shape- and color-standardization relations, unexplained dispersion, and heterogeneous observations. We present a new Bayesian framework, called UNITY (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to confront these effects. We apply the framework to real SN observations and demonstrate smaller statistical and systematic uncertainties. We verify earlier results that SNe Ia require nonlinear shape and color standardizations, but we now include these nonlinear relations in a statistically well-justified way. This analysis was primarily performed blinded, in that the basic framework was first validated on simulated data before transitioning to real data. We also discuss possible extensions of the method.

Community health nursing practices in contexts of poverty, uncertainty and unpredictability: a systematization of personal experiences.

PubMed

Laperrière, Hélène

2007-01-01

Several years of professional nursing practices, while living in the poorest neighbourhoods in the outlying areas of Brazil's Amazon region, have led the author to develop a better understanding of marginalized populations. Providing care to people with leprosy and sex workers in riverside communities has taken place in conditions of uncertainty, insecurity, unpredictability and institutional violence. The question raised is how we can develop community health nursing practices in this context. A systematization of personal experiences based on popular education is used and analyzed as a way of learning by obtaining scientific knowledge through critical analysis of field practices. Ties of solidarity and belonging developed in informal, mutual-help action groups are promising avenues for research and the development of knowledge in health promotion, prevention and community care and a necessary contribution to national public health programmers.

Sunyaev-Zel'dovich Effect Derived Distance to the High Redshift Clusters MS 0451.6-0305 and CL 0016+16

NASA Technical Reports Server (NTRS)

Reese, E. D.; Mohr, J. J.; Carlstrom, J. E.; Grego, L.; Holder, G. P.; Holzapfel, W. L.; Hughes, J. P.; Patel, S. K.

2000-01-01

We determine the distances to the z approximately equal to 0.55 galaxy clusters MS 0451.6-0305 and CL 0016+16 from a maximum likelihood joint fit to interferometric Sunyaev-Zel'dovich effect (SZE) and X-ray observations. We model the intracluster medium (ICM) using a spherical isothermal beta-model. We quantify the statistical and systematic uncertainties inherent to these direct distance measurements, and we determine constraints on the Hubble parameter for three different cosmologies. For an OmegaM = 0.3, OmegaL = 0.7 cosmology, these distances imply a Hubble constant of 63(exp 12)(sub -9)(exp +21)(sub -21) km/s/Mpc, where the uncertainties correspond to statistical followed by systematic at 68% confidence. The best fit H(sub o) is 57 km/sec/Mpc for an open OmegaM = 0.3 universe and 52 km/s/Mpc for a flat Omega = 1 universe.

Sunyaev-Zeldovich Effect-Derived Distances to the High-Redshift Clusters

NASA Technical Reports Server (NTRS)

Reese, Erik D.; Mohr, Joseph J.; Carlstrom, John E.; Joy, Marshall; Grego, Laura; Holder, Gilbert P.; Holzapfel, William L.; Hughes, John P.; Patel, Sandeep K.; Donahue, Megan

2000-01-01

We determine the distances to the z approximately equals 0.55 galaxy clusters MS 0451.6 - 0305 and Cl 0016 + 16 from a maximum-likelihood joint fit to interferometric Sunyaev-Zeldovich effect (SZE) and X-ray observations. We model the intracluster medium (ICM) using a spherical isothermal beta model. We quantify the statistical and systematic uncertainties inherent to these direct distance measurements, and we determine constraints on the Hubble parameter for three different cosmologies. For an Omega(sub M) = 0.3, Omega(sub lambda) = 0.7 cosmology, these distances imply a Hubble constant of 63(sup +12) (sub -9) (sup + 21) (sub -21) km/s Mp/c, where the uncertainties correspond to statistical followed by systematic at 68% confidence. The best-fit H(sub 0) is 57 km/s Mp/c for an open (Omega(sub M) = 0.3) universe and 52 km/s Mp/c for a flat (Omega(sub M) = 1) universe.

Uncertainty aggregation and reduction in structure-material performance prediction

NASA Astrophysics Data System (ADS)

Hu, Zhen; Mahadevan, Sankaran; Ao, Dan

2018-02-01

An uncertainty aggregation and reduction framework is presented for structure-material performance prediction. Different types of uncertainty sources, structural analysis model, and material performance prediction model are connected through a Bayesian network for systematic uncertainty aggregation analysis. To reduce the uncertainty in the computational structure-material performance prediction model, Bayesian updating using experimental observation data is investigated based on the Bayesian network. It is observed that the Bayesian updating results will have large error if the model cannot accurately represent the actual physics, and that this error will be propagated to the predicted performance distribution. To address this issue, this paper proposes a novel uncertainty reduction method by integrating Bayesian calibration with model validation adaptively. The observation domain of the quantity of interest is first discretized into multiple segments. An adaptive algorithm is then developed to perform model validation and Bayesian updating over these observation segments sequentially. Only information from observation segments where the model prediction is highly reliable is used for Bayesian updating; this is found to increase the effectiveness and efficiency of uncertainty reduction. A composite rotorcraft hub component fatigue life prediction model, which combines a finite element structural analysis model and a material damage model, is used to demonstrate the proposed method.

Not Normal: the uncertainties of scientific measurements

NASA Astrophysics Data System (ADS)

Bailey, David C.

2017-01-01

Judging the significance and reproducibility of quantitative research requires a good understanding of relevant uncertainties, but it is often unclear how well these have been evaluated and what they imply. Reported scientific uncertainties were studied by analysing 41 000 measurements of 3200 quantities from medicine, nuclear and particle physics, and interlaboratory comparisons ranging from chemistry to toxicology. Outliers are common, with 5σ disagreements up to five orders of magnitude more frequent than naively expected. Uncertainty-normalized differences between multiple measurements of the same quantity are consistent with heavy-tailed Student's t-distributions that are often almost Cauchy, far from a Gaussian Normal bell curve. Medical research uncertainties are generally as well evaluated as those in physics, but physics uncertainty improves more rapidly, making feasible simple significance criteria such as the 5σ discovery convention in particle physics. Contributions to measurement uncertainty from mistakes and unknown problems are not completely unpredictable. Such errors appear to have power-law distributions consistent with how designed complex systems fail, and how unknown systematic errors are constrained by researchers. This better understanding may help improve analysis and meta-analysis of data, and help scientists and the public have more realistic expectations of what scientific results imply.

Not Normal: the uncertainties of scientific measurements

PubMed Central

2017-01-01

Judging the significance and reproducibility of quantitative research requires a good understanding of relevant uncertainties, but it is often unclear how well these have been evaluated and what they imply. Reported scientific uncertainties were studied by analysing 41 000 measurements of 3200 quantities from medicine, nuclear and particle physics, and interlaboratory comparisons ranging from chemistry to toxicology. Outliers are common, with 5σ disagreements up to five orders of magnitude more frequent than naively expected. Uncertainty-normalized differences between multiple measurements of the same quantity are consistent with heavy-tailed Student’s t-distributions that are often almost Cauchy, far from a Gaussian Normal bell curve. Medical research uncertainties are generally as well evaluated as those in physics, but physics uncertainty improves more rapidly, making feasible simple significance criteria such as the 5σ discovery convention in particle physics. Contributions to measurement uncertainty from mistakes and unknown problems are not completely unpredictable. Such errors appear to have power-law distributions consistent with how designed complex systems fail, and how unknown systematic errors are constrained by researchers. This better understanding may help improve analysis and meta-analysis of data, and help scientists and the public have more realistic expectations of what scientific results imply. PMID:28280557

Mapping (dis)agreement in hydrologic projections

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Addor, Nans; Mizukami, Naoki; Newman, Andrew J.; Torfs, Paul J. J. F.; Clark, Martyn P.; Uijlenhoet, Remko; Teuling, Adriaan J.

2018-03-01

Hydrologic projections are of vital socio-economic importance. However, they are also prone to uncertainty. In order to establish a meaningful range of storylines to support water managers in decision making, we need to reveal the relevant sources of uncertainty. Here, we systematically and extensively investigate uncertainty in hydrologic projections for 605 basins throughout the contiguous US. We show that in the majority of the basins, the sign of change in average annual runoff and discharge timing for the period 2070-2100 compared to 1985-2008 differs among combinations of climate models, hydrologic models, and parameters. Mapping the results revealed that different sources of uncertainty dominate in different regions. Hydrologic model induced uncertainty in the sign of change in mean runoff was related to snow processes and aridity, whereas uncertainty in both mean runoff and discharge timing induced by the climate models was related to disagreement among the models regarding the change in precipitation. Overall, disagreement on the sign of change was more widespread for the mean runoff than for the discharge timing. The results demonstrate the need to define a wide range of quantitative hydrologic storylines, including parameter, hydrologic model, and climate model forcing uncertainty, to support water resource planning.

Explaining the justice-performance relationship: trust as exchange deepener or trust as uncertainty reducer?

PubMed

Colquitt, Jason A; Lepine, Jeffery A; Piccolo, Ronald F; Zapata, Cindy P; Rich, Bruce L

2012-01-01

Past research has revealed significant relationships between organizational justice dimensions and job performance, and trust is thought to be one mediator of those relationships. However, trust has been positioned in justice theorizing in 2 different ways, either as an indicator of the depth of an exchange relationship or as a variable that reflects levels of work-related uncertainty. Moreover, trust scholars distinguish between multiple forms of trust, including affect- and cognition-based trust, and it remains unclear which form is most relevant to justice effects. To explore these issues, we built and tested a more comprehensive model of trust mediation in which procedural, interpersonal, and distributive justice predicted affect- and cognition-based trust, with those trust forms predicting both exchange- and uncertainty-based mechanisms. The results of a field study in a hospital system revealed that the trust variables did indeed mediate the relationships between the organizational justice dimensions and job performance, with affect-based trust driving exchange-based mediation and cognition-based trust driving uncertainty-based mediation.

Using a Software Tool in Forecasting: a Case Study of Sales Forecasting Taking into Account Data Uncertainty

NASA Astrophysics Data System (ADS)

Fabianová, Jana; Kačmáry, Peter; Molnár, Vieroslav; Michalik, Peter

2016-10-01

Forecasting is one of the logistics activities and a sales forecast is the starting point for the elaboration of business plans. Forecast accuracy affects the business outcomes and ultimately may significantly affect the economic stability of the company. The accuracy of the prediction depends on the suitability of the use of forecasting methods, experience, quality of input data, time period and other factors. The input data are usually not deterministic but they are often of random nature. They are affected by uncertainties of the market environment, and many other factors. Taking into account the input data uncertainty, the forecast error can by reduced. This article deals with the use of the software tool for incorporating data uncertainty into forecasting. Proposals are presented of a forecasting approach and simulation of the impact of uncertain input parameters to the target forecasted value by this case study model. The statistical analysis and risk analysis of the forecast results is carried out including sensitivity analysis and variables impact analysis.

Uncertainties of optical parameters and their propagations in an analytical ocean color inversion algorithm.

PubMed

Lee, ZhongPing; Arnone, Robert; Hu, Chuanmin; Werdell, P Jeremy; Lubac, Bertrand

2010-01-20

Following the theory of error propagation, we developed analytical functions to illustrate and evaluate the uncertainties of inherent optical properties (IOPs) derived by the quasi-analytical algorithm (QAA). In particular, we evaluated the effects of uncertainties of these optical parameters on the inverted IOPs: the absorption coefficient at the reference wavelength, the extrapolation of particle backscattering coefficient, and the spectral ratios of absorption coefficients of phytoplankton and detritus/gelbstoff, respectively. With a systematically simulated data set (46,200 points), we found that the relative uncertainty of QAA-derived total absorption coefficients in the blue-green wavelengths is generally within +/-10% for oceanic waters. The results of this study not only establish theoretical bases to evaluate and understand the effects of the various variables on IOPs derived from remote-sensing reflectance, but also lay the groundwork to analytically estimate uncertainties of these IOPs for each pixel. These are required and important steps for the generation of quality maps of IOP products derived from satellite ocean color remote sensing.

How well do elderly people cope with uncertainty in a learning task?

PubMed

Chasseigne, G; Grau, S; Mullet, E; Cama, V

1999-11-01

The relation between age, task complexity and learning performance in a Multiple Cue Probability Learning task was studied by systematically varying the level of uncertainty present in the task, keeping constant the direction of relationships. Four age groups were constituted: young adults (mean age = 21), middle-aged adults (45), elderly people (69) and very elderly people (81). Five uncertainty levels were considered: predictability = 0.96, 0.80, 0.64, 0.48, and 0.32. All relationships involved were direct ones. A strong effect of uncertainty on 'control', a measure of the subject's consistency with respect to a linear model, was found. This effect was essentially a linear one. To each decrement in predictability of the task corresponded an equal decrement in participants' level of control. This level of decrement was the same, regardless of the age of the participant. It can be concluded that elderly people cope with uncertainty in probability learning tasks as well as young adults.

Impacts of Process and Prediction Uncertainties on Projected Hanford Waste Glass Amount

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

Gervasio, Vivianaluxa; Vienna, John D.; Kim, Dong-Sang

Analyses were performed to evaluate the impacts of using the advanced glass models, constraints (Vienna et al. 2016), and uncertainty descriptions on projected Hanford glass mass. The maximum allowable WOL was estimated for waste compositions while simultaneously satisfying all applicable glass property and composition constraints with sufficient confidence. Different components of prediction and composition/process uncertainties were systematically included in the calculations to evaluate their impacts on glass mass. The analyses estimated the production of 23,360 MT of IHLW glass when no uncertainties were taken into accound. Accounting for prediction and composition/process uncertainties resulted in 5.01 relative percent increase in estimatedmore » glass mass 24,531 MT. Roughly equal impacts were found for prediction uncertainties (2.58 RPD) and composition/process uncertainties (2.43 RPD). ILAW mass was predicted to be 282,350 MT without uncertainty and with weaste loading “line” rules in place. Accounting for prediction and composition/process uncertainties resulted in only 0.08 relative percent increase in estimated glass mass of 282,562 MTG. Without application of line rules the glass mass decreases by 10.6 relative percent (252,490 MT) for the case with no uncertainties. Addition of prediction uncertainties increases glass mass by 1.32 relative percent and the addition of composition/process uncertainties increase glass mass by an additional 7.73 relative percent (9.06 relative percent increase combined). The glass mass estimate without line rules (275,359 MT) was 2.55 relative percent lower than that with the line rules (282,562 MT), after accounting for all applicable uncertainties.« less

Social, institutional, and psychological factors affecting wildfire incident decision making

Treesearch

Matthew P. Thompson

2014-01-01

Managing wildland fire incidents can be fraught with complexity and uncertainty. Myriad human factors can exert significant influence on incident decision making, and can contribute additional uncertainty regarding programmatic evaluations of wildfire management and attainment of policy goals. This article develops a framework within which human sources of uncertainty...

Uncertainty quantification for optical model parameters

DOE PAGES

Lovell, A. E.; Nunes, F. M.; Sarich, J.; ...

2017-02-21

Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of our work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fitmore » and create corresponding 95% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. Here, we study a number of reactions involving neutron and deuteron projectiles with energies in the range of 5–25 MeV/u, on targets with mass A=12–208. We investigate the correlations between the parameters in the fit. The case of deuterons on 12C is discussed in detail: the elastic-scattering fit and the prediction of 12C(d,p) 13C transfer angular distributions, using both uncorrelated and correlated χ 2 minimization functions. The general features for all cases are compiled in a systematic manner to identify trends. This work shows that, in many cases, the correlated χ 2 functions (in comparison to the uncorrelated χ 2 functions) provide a more natural parameterization of the process. These correlated functions do, however, produce broader confidence bands. Further optimization may require improvement in the models themselves and/or more information included in the fit.« less

An algorithm for U-Pb isotope dilution data reduction and uncertainty propagation

NASA Astrophysics Data System (ADS)

McLean, N. M.; Bowring, J. F.; Bowring, S. A.

2011-06-01

High-precision U-Pb geochronology by isotope dilution-thermal ionization mass spectrometry is integral to a variety of Earth science disciplines, but its ultimate resolving power is quantified by the uncertainties of calculated U-Pb dates. As analytical techniques have advanced, formerly small sources of uncertainty are increasingly important, and thus previous simplifications for data reduction and uncertainty propagation are no longer valid. Although notable previous efforts have treated propagation of correlated uncertainties for the U-Pb system, the equations, uncertainties, and correlations have been limited in number and subject to simplification during propagation through intermediary calculations. We derive and present a transparent U-Pb data reduction algorithm that transforms raw isotopic data and measured or assumed laboratory parameters into the isotopic ratios and dates geochronologists interpret without making assumptions about the relative size of sample components. To propagate uncertainties and their correlations, we describe, in detail, a linear algebraic algorithm that incorporates all input uncertainties and correlations without limiting or simplifying covariance terms to propagate them though intermediate calculations. Finally, a weighted mean algorithm is presented that utilizes matrix elements from the uncertainty propagation algorithm to propagate random and systematic uncertainties for data comparison between other U-Pb labs and other geochronometers. The linear uncertainty propagation algorithms are verified with Monte Carlo simulations of several typical analyses. We propose that our algorithms be considered by the community for implementation to improve the collaborative science envisioned by the EARTHTIME initiative.

The Harm that Underestimation of Uncertainty Does to Our Community: A Case Study Using Sunspot Area Measurements

NASA Astrophysics Data System (ADS)

Munoz-Jaramillo, Andres

2017-08-01

Data products in heliospheric physics are very often provided without clear estimates of uncertainty. From helioseismology in the solar interior, all the way to in situ solar wind measurements beyond 1AU, uncertainty estimates are typically hard for users to find (buried inside long documents that are separate from the data products), or simply non-existent.There are two main reasons why uncertainty measurements are hard to find:1. Understanding instrumental systematic errors is given a much higher priority inside instrumental teams.2. The desire to perfectly understand all sources of uncertainty postpones indefinitely the actual quantification of uncertainty in our measurements.Using the cross calibration of 200 years of sunspot area measurements as a case study, in this presentation we will discuss the negative impact that inadequate measurements of uncertainty have on users, through the appearance of toxic and unnecessary controversies, and data providers, through the creation of unrealistic expectations regarding the information that can be extracted from their data. We will discuss how empirical estimates of uncertainty represent a very good alternative to not providing any estimates at all, and finalize by discussing the bare essentials that should become our standard practice for future instruments and surveys.

Responses to clinical uncertainty in Australian general practice trainees: a cross-sectional analysis.

PubMed

Cooke, Georga; Tapley, Amanda; Holliday, Elizabeth; Morgan, Simon; Henderson, Kim; Ball, Jean; van Driel, Mieke; Spike, Neil; Kerr, Rohan; Magin, Parker

2017-12-01

Tolerance for ambiguity is essential for optimal learning and professional competence. General practice trainees must be, or must learn to be, adept at managing clinical uncertainty. However, few studies have examined associations of intolerance of uncertainty in this group. The aim of this study was to establish levels of tolerance of uncertainty in Australian general practice trainees and associations of uncertainty with demographic, educational and training practice factors. A cross-sectional analysis was performed on the Registrar Clinical Encounters in Training (ReCEnT) project, an ongoing multi-site cohort study. Scores on three of the four independent subscales of the Physicians' Reaction to Uncertainty (PRU) instrument were analysed as outcome variables in linear regression models with trainee and practice factors as independent variables. A total of 594 trainees contributed data on a total of 1209 occasions. Trainees in earlier training terms had higher scores for 'Anxiety due to uncertainty', 'Concern about bad outcomes' and 'Reluctance to disclose diagnosis/treatment uncertainty to patients'. Beyond this, findings suggest two distinct sets of associations regarding reaction to uncertainty. Firstly, affective aspects of uncertainty (the 'Anxiety' and 'Concern' subscales) were associated with female gender, less experience in hospital prior to commencing general practice training, and graduation overseas. Secondly, a maladaptive response to uncertainty (the 'Reluctance to disclose' subscale) was associated with urban practice, health qualifications prior to studying medicine, practice in an area of higher socio-economic status, and being Australian-trained. This study has established levels of three measures of trainees' responses to uncertainty and associations with these responses. The current findings suggest differing 'phenotypes' of trainees with high 'affective' responses to uncertainty and those reluctant to disclose uncertainty to patients. More research is needed to examine the relationship between clinical uncertainty and clinical outcomes, temporal changes in tolerance for uncertainty, and strategies that might assist physicians in developing adaptive responses to clinical uncertainty. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Expected trace gas and aerosol retrieval accuracy of the Geostationary Environment Monitoring Spectrometer

NASA Astrophysics Data System (ADS)

Jeong, U.; Kim, J.; Liu, X.; Lee, K. H.; Chance, K.; Song, C. H.

2015-12-01

The predicted accuracy of the trace gases and aerosol retrievals from the geostationary environment monitoring spectrometer (GEMS) was investigated. The GEMS is one of the first sensors to monitor NO2, SO2, HCHO, O3, and aerosols onboard geostationary earth orbit (GEO) over Asia. Since the GEMS is not launched yet, the simulated measurements and its precision were used in this study. The random and systematic component of the measurement error was estimated based on the instrument design. The atmospheric profiles were obtained from Model for Ozone And Related chemical Tracers (MOZART) simulations and surface reflectances were obtained from climatology of OMI Lambertian equivalent reflectance. The uncertainties of the GEMS trace gas and aerosol products were estimated based on the OE method using the atmospheric profile and surface reflectance. Most of the estimated uncertainties of NO2, HCHO, stratospheric and total O3 products satisfied the user's requirements with sufficient margin. However, about 26% of the estimated uncertainties of SO2 and about 30% of the estimated uncertainties of tropospheric O3 do not meet the required precision. Particularly the estimated uncertainty of SO2 is high in winter, when the emission is strong in East Asia. Further efforts are necessary in order to improve the retrieval accuracy of SO2 and tropospheric O3 in order to reach the scientific goal of GEMS. Random measurement error of GEMS was important for the NO2, SO2, and HCHO retrieval, while both the random and systematic measurement errors were important for the O3 retrievals. The degree of freedom for signal of tropospheric O3 was 0.8 ± 0.2 and that for stratospheric O3 was 2.9 ± 0.5. The estimated uncertainties of the aerosol retrieval from GEMS measurements were predicted to be lower than the required precision for the SZA range of the trace gas retrievals.

The Crucial Role of Error Correlation for Uncertainty Modeling of CFD-Based Aerodynamics Increments

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Walker, Eric L.

2011-01-01

The Ares I ascent aerodynamics database for Design Cycle 3 (DAC-3) was built from wind-tunnel test results and CFD solutions. The wind tunnel results were used to build the baseline response surfaces for wind-tunnel Reynolds numbers at power-off conditions. The CFD solutions were used to build increments to account for Reynolds number effects. We calculate the validation errors for the primary CFD code results at wind tunnel Reynolds number power-off conditions and would like to be able to use those errors to predict the validation errors for the CFD increments. However, the validation errors are large compared to the increments. We suggest a way forward that is consistent with common practice in wind tunnel testing which is to assume that systematic errors in the measurement process and/or the environment will subtract out when increments are calculated, thus making increments more reliable with smaller uncertainty than absolute values of the aerodynamic coefficients. A similar practice has arisen for the use of CFD to generate aerodynamic database increments. The basis of this practice is the assumption of strong correlation of the systematic errors inherent in each of the results used to generate an increment. The assumption of strong correlation is the inferential link between the observed validation uncertainties at wind-tunnel Reynolds numbers and the uncertainties to be predicted for flight. In this paper, we suggest a way to estimate the correlation coefficient and demonstrate the approach using code-to-code differences that were obtained for quality control purposes during the Ares I CFD campaign. Finally, since we can expect the increments to be relatively small compared to the baseline response surface and to be typically of the order of the baseline uncertainty, we find that it is necessary to be able to show that the correlation coefficients are close to unity to avoid overinflating the overall database uncertainty with the addition of the increments.

RELICS: Strong Lens Models for Five Galaxy Clusters from the Reionization Lensing Cluster Survey

NASA Astrophysics Data System (ADS)

Cerny, Catherine; Sharon, Keren; Andrade-Santos, Felipe; Avila, Roberto J.; Bradač, Maruša; Bradley, Larry D.; Carrasco, Daniela; Coe, Dan; Czakon, Nicole G.; Dawson, William A.; Frye, Brenda L.; Hoag, Austin; Huang, Kuang-Han; Johnson, Traci L.; Jones, Christine; Lam, Daniel; Lovisari, Lorenzo; Mainali, Ramesh; Oesch, Pascal A.; Ogaz, Sara; Past, Matthew; Paterno-Mahler, Rachel; Peterson, Avery; Riess, Adam G.; Rodney, Steven A.; Ryan, Russell E.; Salmon, Brett; Sendra-Server, Irene; Stark, Daniel P.; Strolger, Louis-Gregory; Trenti, Michele; Umetsu, Keiichi; Vulcani, Benedetta; Zitrin, Adi

2018-06-01

Strong gravitational lensing by galaxy clusters magnifies background galaxies, enhancing our ability to discover statistically significant samples of galaxies at {\\boldsymbol{z}}> 6, in order to constrain the high-redshift galaxy luminosity functions. Here, we present the first five lens models out of the Reionization Lensing Cluster Survey (RELICS) Hubble Treasury Program, based on new HST WFC3/IR and ACS imaging of the clusters RXC J0142.9+4438, Abell 2537, Abell 2163, RXC J2211.7–0349, and ACT-CLJ0102–49151. The derived lensing magnification is essential for estimating the intrinsic properties of high-redshift galaxy candidates, and properly accounting for the survey volume. We report on new spectroscopic redshifts of multiply imaged lensed galaxies behind these clusters, which are used as constraints, and detail our strategy to reduce systematic uncertainties due to lack of spectroscopic information. In addition, we quantify the uncertainty on the lensing magnification due to statistical and systematic errors related to the lens modeling process, and find that in all but one cluster, the magnification is constrained to better than 20% in at least 80% of the field of view, including statistical and systematic uncertainties. The five clusters presented in this paper span the range of masses and redshifts of the clusters in the RELICS program. We find that they exhibit similar strong lensing efficiencies to the clusters targeted by the Hubble Frontier Fields within the WFC3/IR field of view. Outputs of the lens models are made available to the community through the Mikulski Archive for Space Telescopes.

A probabilistic approach to remote compositional analysis of planetary surfaces

USGS Publications Warehouse

Lapotre, Mathieu G.A.; Ehlmann, Bethany L.; Minson, Sarah E.

2017-01-01

Reflected light from planetary surfaces provides information, including mineral/ice compositions and grain sizes, by study of albedo and absorption features as a function of wavelength. However, deconvolving the compositional signal in spectra is complicated by the nonuniqueness of the inverse problem. Trade-offs between mineral abundances and grain sizes in setting reflectance, instrument noise, and systematic errors in the forward model are potential sources of uncertainty, which are often unquantified. Here we adopt a Bayesian implementation of the Hapke model to determine sets of acceptable-fit mineral assemblages, as opposed to single best fit solutions. We quantify errors and uncertainties in mineral abundances and grain sizes that arise from instrument noise, compositional end members, optical constants, and systematic forward model errors for two suites of ternary mixtures (olivine-enstatite-anorthite and olivine-nontronite-basaltic glass) in a series of six experiments in the visible-shortwave infrared (VSWIR) wavelength range. We show that grain sizes are generally poorly constrained from VSWIR spectroscopy. Abundance and grain size trade-offs lead to typical abundance errors of ≤1 wt % (occasionally up to ~5 wt %), while ~3% noise in the data increases errors by up to ~2 wt %. Systematic errors further increase inaccuracies by a factor of 4. Finally, phases with low spectral contrast or inaccurate optical constants can further increase errors. Overall, typical errors in abundance are <10%, but sometimes significantly increase for specific mixtures, prone to abundance/grain-size trade-offs that lead to high unmixing uncertainties. These results highlight the need for probabilistic approaches to remote determination of planetary surface composition.

Uncertainty in the Himalayan energy-water nexus: estimating regional exposure to glacial lake outburst floods

NASA Astrophysics Data System (ADS)

Schwanghart, Wolfgang; Worni, Raphael; Huggel, Christian; Stoffel, Markus; Korup, Oliver

2016-07-01

Himalayan water resources attract a rapidly growing number of hydroelectric power projects (HPP) to satisfy Asia’s soaring energy demands. Yet HPP operating or planned in steep, glacier-fed mountain rivers face hazards of glacial lake outburst floods (GLOFs) that can damage hydropower infrastructure, alter water and sediment yields, and compromise livelihoods downstream. Detailed appraisals of such GLOF hazards are limited to case studies, however, and a more comprehensive, systematic analysis remains elusive. To this end we estimate the regional exposure of 257 Himalayan HPP to GLOFs, using a flood-wave propagation model fed by Monte Carlo-derived outburst volumes of >2300 glacial lakes. We interpret the spread of thus modeled peak discharges as a predictive uncertainty that arises mainly from outburst volumes and dam-breach rates that are difficult to assess before dams fail. With 66% of sampled HPP are on potential GLOF tracks, up to one third of these HPP could experience GLOF discharges well above local design floods, as hydropower development continues to seek higher sites closer to glacial lakes. We compute that this systematic push of HPP into headwaters effectively doubles the uncertainty about GLOF peak discharge in these locations. Peak discharges farther downstream, in contrast, are easier to predict because GLOF waves attenuate rapidly. Considering this systematic pattern of regional GLOF exposure might aid the site selection of future Himalayan HPP. Our method can augment, and help to regularly update, current hazard assessments, given that global warming is likely changing the number and size of Himalayan meltwater lakes.

Debiasing Health-Related Judgments and Decision Making: A Systematic Review.

PubMed

Ludolph, Ramona; Schulz, Peter J

2018-01-01

Being confronted with uncertainty in the context of health-related judgments and decision making can give rise to the occurrence of systematic biases. These biases may detrimentally affect lay persons and health experts alike. Debiasing aims at mitigating these negative effects by eliminating or reducing the biases. However, little is known about its effectiveness. This study seeks to systematically review the research on health-related debiasing to identify new opportunities and challenges for successful debiasing strategies. A systematic search resulted in 2748 abstracts eligible for screening. Sixty-eight articles reporting 87 relevant studies met the predefined inclusion criteria and were categorized and analyzed with regard to content and quality. All steps were undertaken independently by 2 reviewers, and inconsistencies were resolved through discussion. The majority of debiasing interventions ( n = 60) was at least partially successful. Optimistic biases ( n = 25), framing effects ( n = 14), and base rate neglects ( n = 10) were the main targets of debiasing efforts. Cognitive strategies ( n = 36) such as "consider-the-opposite" and technological interventions ( n = 33) such as visual aids were mainly tested. Thirteen studies aimed at debiasing health care professionals' judgments, while 74 interventions addressed the general population. Studies' methodological quality ranged from 26.2% to 92.9%, with an average rating of 68.7%. In the past, the usefulness of debiasing was often debated. Yet most of the interventions reviewed here are found to be effective, pointing to the utility of debiasing in the health context. In particular, technological strategies offer a novel opportunity to pursue large-scale debiasing outside the laboratory. The need to strengthen the transfer of debiasing interventions to real-life settings and a lack of conceptual rigor are identified as the main challenges requiring further research.

The Evolution of the Stellar Mass Function of Galaxies from z = 4.0 and the First Comprehensive Analysis of its Uncertainties: Evidence for Mass-Dependent Evolution

NASA Astrophysics Data System (ADS)

Marchesini, Danilo; van Dokkum, Pieter G.; Förster Schreiber, Natascha M.; Franx, Marijn; Labbé, Ivo; Wuyts, Stijn

2009-08-01

We present the evolution of the stellar mass function (SMF) of galaxies from z = 4.0 to z = 1.3 measured from a sample constructed from the deep near-infrared Multi-wavelength Survey by Yale-Chile, the Faint Infrared Extragalactic Survey, and the Great Observatories Origins Deep Survey-Chandra Deep Field South surveys, all having very high-quality optical to mid-infrared data. This sample, unique in that it combines data from surveys with a large range of depths and areas in a self-consistent way, allowed us to (1) minimize the uncertainty due to cosmic variance and empirically quantify its contribution to the total error budget; (2) simultaneously probe the high-mass end and the low-mass end (down to ~0.05 times the characteristic stellar mass) of the SMF with good statistics; and (3) empirically derive the redshift-dependent completeness limits in stellar mass. We provide, for the first time, a comprehensive analysis of random and systematic uncertainties affecting the derived SMFs, including the effect of metallicity, extinction law, stellar population synthesis model, and initial mass function. We find that the mass density evolves by a factor of ~17+7 -10 since z = 4.0, mostly driven by a change in the normalization Φsstarf. If only random errors are taken into account, we find evidence for mass-dependent evolution, with the low-mass end evolving more rapidly than the high-mass end. However, we show that this result is no longer robust when systematic uncertainties due to the SED-modeling assumptions are taken into account. Another significant uncertainty is the contribution to the overall stellar mass density of galaxies below our mass limit; future studies with WFC3 will provide better constraints on the SMF at masses below 1010 M sun at z>2. Taking our results at face value, we find that they are in conflict with semianalytic models of galaxy formation. The models predict SMFs that are in general too steep, with too many low-mass galaxies and too few high-mass galaxies. The discrepancy at the high-mass end is susceptible to uncertainties in the models and the data, but the discrepancy at the low-mass end may be more difficult to explain. Based on observations with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory (JPL), California Institute of Technology under NASA contract 1407. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS5-26555. Based on observations collected at the European Southern Observatories, Chile (ESO Programme LP164.O-0612, 168.A-0485, 170.A-0788, 074.A-0709, 275.A-5060, and 171.A-3045). Based on observations obtained at the Cerro Tololo Inter-American Observatory, a division of the National Optical Astronomy Observatories, which is operated by the Association of Universities for Research in Astronomy, Inc., under cooperative agreement with the National Science Foundation.

Heterogeneous Distribution of Chromium on Mercury

NASA Astrophysics Data System (ADS)

Nittler, L. R.; Boujibar, A.; Crapster-Pregont, E.; Frank, E. A.; McCoy, T. J.; McCubbin, F. M.; Starr, R. D.; Vander Kaaden, K. E.; Vorburger, A.; Weider, S. Z.

2018-05-01

Mercury's surface has an average Cr/Si ratio of 0.003 (Cr 800 ppm), with at least a factor of 2 systematic uncertainty. Cr is heterogeneously distributed and correlated with Mg, Ca, S, and Fe and anti-correlated with Al.

Lost in Translation: Piloting a Novel Framework to Assess the Challenges in Translating Scientific Uncertainty From Empirical Findings to WHO Policy Statements

PubMed Central

Benmarhnia, Tarik; Huang, Jonathan Y.; Jones, Catherine M.

2017-01-01

Background: Calls for evidence-informed public health policy, with implicit promises of greater program effectiveness, have intensified recently. The methods to produce such policies are not self-evident, requiring a conciliation of values and norms between policy-makers and evidence producers. In particular, the translation of uncertainty from empirical research findings, particularly issues of statistical variability and generalizability, is a persistent challenge because of the incremental nature of research and the iterative cycle of advancing knowledge and implementation. This paper aims to assess how the concept of uncertainty is considered and acknowledged in World Health Organization (WHO) policy recommendations and guidelines. Methods: We selected four WHO policy statements published between 2008-2013 regarding maternal and child nutrient supplementation, infant feeding, heat action plans, and malaria control to represent topics with a spectrum of available evidence bases. Each of these four statements was analyzed using a novel framework to assess the treatment of statistical variability and generalizability. Results: WHO currently provides substantial guidance on addressing statistical variability through GRADE (Grading of Recommendations Assessment, Development, and Evaluation) ratings for precision and consistency in their guideline documents. Accordingly, our analysis showed that policy-informing questions were addressed by systematic reviews and representations of statistical variability (eg, with numeric confidence intervals). In contrast, the presentation of contextual or "background" evidence regarding etiology or disease burden showed little consideration for this variability. Moreover, generalizability or "indirectness" was uniformly neglected, with little explicit consideration of study settings or subgroups. Conclusion: In this paper, we found that non-uniform treatment of statistical variability and generalizability factors that may contribute to uncertainty regarding recommendations were neglected, including the state of evidence informing background questions (prevalence, mechanisms, or burden or distributions of health problems) and little assessment of generalizability, alternate interventions, and additional outcomes not captured by systematic review. These other factors often form a basis for providing policy recommendations, particularly in the absence of a strong evidence base for intervention effects. Consequently, they should also be subject to stringent and systematic evaluation criteria. We suggest that more effort is needed to systematically acknowledge (1) when evidence is missing, conflicting, or equivocal, (2) what normative considerations were also employed, and (3) how additional evidence may be accrued. PMID:29179291

Higher order net-proton number cumulants dependence on the centrality definition and other spurious effects

NASA Astrophysics Data System (ADS)

Sombun, S.; Steinheimer, J.; Herold, C.; Limphirat, A.; Yan, Y.; Bleicher, M.

2018-02-01

We study the dependence of the normalized moments of the net-proton multiplicity distributions on the definition of centrality in relativistic nuclear collisions at a beam energy of \\sqrt{{s}{NN}}=7.7 {GeV}. Using the ultra relativistic quantum molecular dynamics model as event generator we find that the centrality definition has a large effect on the extracted cumulant ratios. Furthermore we find that the finite efficiency for the determination of the centrality introduces an additional systematic uncertainty. Finally, we quantitatively investigate the effects of event-pile up and other possible spurious effects which may change the measured proton number. We find that pile-up alone is not sufficient to describe the data and show that a random double counting of events, adding significantly to the measured proton number, affects mainly the higher order cumulants in most central collisions.

Measuring the Hubble constant with Type Ia supernovae as near-infrared standard candles

NASA Astrophysics Data System (ADS)

Dhawan, Suhail; Jha, Saurabh W.; Leibundgut, Bruno

2018-01-01

The most precise local measurements of H0 rely on observations of Type Ia supernovae (SNe Ia) coupled with Cepheid distances to SN Ia host galaxies. Recent results have shown tension comparing H0 to the value inferred from CMB observations assuming ΛCDM, making it important to check for potential systematic uncertainties in either approach. To date, precise local H0 measurements have used SN Ia distances based on optical photometry, with corrections for light curve shape and colour. Here, we analyse SNe Ia as standard candles in the near-infrared (NIR), where luminosity variations in the supernovae and extinction by dust are both reduced relative to the optical. From a combined fit to 9 nearby calibrator SNe with host Cepheid distances from Riess et al. (2016) and 27 SNe in the Hubble flow, we estimate the absolute peak J magnitude MJ = -18.524 ± 0.041 mag and H0 = 72.8 ± 1.6 (statistical) ±2.7 (systematic) km s-1 Mpc-1. The 2.2% statistical uncertainty demonstrates that the NIR provides a compelling avenue to measuring SN Ia distances, and for our sample the intrinsic (unmodeled) peak J magnitude scatter is just 0.10 mag, even without light curve shape or colour corrections. Our results do not vary significantly with different sample selection criteria, though photometric calibration in the NIR may be a dominant systematic uncertainty. Our findings suggest that tension in the competing H0 distance ladders is likely not a result of supernova systematics that could be expected to vary between optical and NIR wavelengths, like dust extinction. We anticipate further improvements in H0 with a larger calibrator sample of SNe Ia with Cepheid distances, more Hubble flow SNe Ia with NIR light curves, and better use of the full NIR photometric data set beyond simply the peak J-band magnitude.

Simplified methods for real-time prediction of storm surge uncertainty: The city of Venice case study

NASA Astrophysics Data System (ADS)

Mel, Riccardo; Viero, Daniele Pietro; Carniello, Luca; Defina, Andrea; D'Alpaos, Luigi

2014-09-01

Providing reliable and accurate storm surge forecasts is important for a wide range of problems related to coastal environments. In order to adequately support decision-making processes, it also become increasingly important to be able to estimate the uncertainty associated with the storm surge forecast. The procedure commonly adopted to do this uses the results of a hydrodynamic model forced by a set of different meteorological forecasts; however, this approach requires a considerable, if not prohibitive, computational cost for real-time application. In the present paper we present two simplified methods for estimating the uncertainty affecting storm surge prediction with moderate computational effort. In the first approach we use a computationally fast, statistical tidal model instead of a hydrodynamic numerical model to estimate storm surge uncertainty. The second approach is based on the observation that the uncertainty in the sea level forecast mainly stems from the uncertainty affecting the meteorological fields; this has led to the idea to estimate forecast uncertainty via a linear combination of suitable meteorological variances, directly extracted from the meteorological fields. The proposed methods were applied to estimate the uncertainty in the storm surge forecast in the Venice Lagoon. The results clearly show that the uncertainty estimated through a linear combination of suitable meteorological variances nicely matches the one obtained using the deterministic approach and overcomes some intrinsic limitations in the use of a statistical tidal model.

Data analysis and systematic studies for the He-6 experiment

NASA Astrophysics Data System (ADS)

Bagdasarova, Yelena; Bailey, Kevin; Flechard, Xavier; Garcia, Alejandro; Hong, Ran; Leredde, Aranud; Mueller, Peter; Naviliat-Cuncic, Oscar; O'Connor, Tom P.; Sternberg, Matthew; Storm, Derek; Swanson, Erik; Wauters, Frederik; Zumwalt, David

2015-10-01

The He-6 experiment at the University of Washington aims to precisely measure the beta-neutrino angular correlation (aβν) in the beta decay of He-6, a parameter that is particularly sensitive to tensor-like currents in the electroweak interaction. The experiment is based on a coincidence detection of the beta and recoil ion emitted from laser trapped He-6 and seeks to ultimately measure aβν to the 0 . 1 % level. Monte-carlo simulations of the decay and detection scheme are essential to analyze the data and have been extensively used to quantify the effects of systematic uncertainties. Major efforts have been put in to limit their contributions to less than 1 % of aβν, the first goal of the experiment. This set of data will guide further improvements of the experiment towards the 0 . 1 % level measurement of aβν. The data analysis procedures and the current status of the experiment, including the achieved and projected systematic and statistical uncertainties, will be presented. This work is supported by DOE, Office of Nuclear Physics, under Contract Nos. DE-AC02-06CH11357 and DE-FG02-97ER41020. Done...processed 665 records...13:57:12

Don't know responses to cognitive and affective risk perception measures: Exploring prevalence and socio-demographic moderators.

PubMed

Janssen, Eva; Verduyn, Philippe; Waters, Erika A

2018-05-01

Many people report uncertainty when appraising their risk of cancer and other diseases, but prior research about the topic has focused solely on cognitive risk perceptions. We investigated uncertainty related to cognitive and affective risk questions. We also explored whether any differences in uncertainty between cognitive and affective questions varied in magnitude by item-specific or socio-demographic characteristics. Secondary analysis of data collected for a 2 × 2 × 3 full-factorial risk communication experiment (N = 835) that was embedded within an online survey. We investigated the frequency of 'don't know' responses (DKR) to eight perceived risk items that varied according to whether they assessed (1) cognitive versus affective perceived risk, (2) absolute versus comparative risk, and (3) colon cancer versus 'any exercise-related diseases'. Socio-demographics were as follows: sex, age, education, family history, and numeracy. We analysed the data using multilevel logistic regression. The odds of DKR were lower for affective than cognitive perceived risk (OR = 0.64, p < .001). This difference occurred for absolute but not comparative risk perceptions (interaction effect, p = .004), but no interactions for disease type or demographic characteristics were found (ps > .05). Lower uncertainty for affective (vs. cognitive) absolute perceived risk items is consistent with research stating: (1) Risk perceptions are grounded in people's feelings about a hazard, and (2) feelings are easier for people to access than facts. Including affective perceived risk items in health behaviour surveys may reduce missing data and improve data quality. Statement of contribution What is already known on this subject? Many people report that they don't know their risk (i.e., risk uncertainty). Evidence is growing for the importance of feelings of risk in explaining health behaviour. Feelings are easier for people to access than facts. What does this study add? Don't know responding is higher for absolute cognitive than absolute affective risk questions. This difference does not vary in magnitude by demographic characteristics. Affective perceived risk questions in surveys may reduce missing data and improve data quality. © 2018 The British Psychological Society.

A probabilistic approach for shallow rainfall-triggered landslide modeling at basin scale. A case study in the Luquillo Forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Dialynas, Y. G.; Arnone, E.; Noto, L. V.; Bras, R. L.

2013-12-01

Slope stability depends on geotechnical and hydrological factors that exhibit wide natural spatial variability, yet sufficient measurements of the related parameters are rarely available over entire study areas. The uncertainty associated with the inability to fully characterize hydrologic behavior has an impact on any attempt to model landslide hazards. This work suggests a way to systematically account for this uncertainty in coupled distributed hydrological-stability models for shallow landslide hazard assessment. A probabilistic approach for the prediction of rainfall-triggered landslide occurrence at basin scale was implemented in an existing distributed eco-hydrological and landslide model, tRIBS-VEGGIE -landslide (Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator - VEGetation Generator for Interactive Evolution). More precisely, we upgraded tRIBS-VEGGIE- landslide to assess the likelihood of shallow landslides by accounting for uncertainty related to geotechnical and hydrological factors that directly affect slope stability. Natural variability of geotechnical soil characteristics was considered by randomizing soil cohesion and friction angle. Hydrological uncertainty related to the estimation of matric suction was taken into account by considering soil retention parameters as correlated random variables. The probability of failure is estimated through an assumed theoretical Factor of Safety (FS) distribution, conditioned on soil moisture content. At each cell, the temporally variant FS statistics are approximated by the First Order Second Moment (FOSM) method, as a function of parameters statistical properties. The model was applied on the Rio Mameyes Basin, located in the Luquillo Experimental Forest in Puerto Rico, where previous landslide analyses have been carried out. At each time step, model outputs include the probability of landslide occurrence across the basin, and the most probable depth of failure at each soil column. The use of the proposed probabilistic approach for shallow landslide prediction is able to reveal and quantify landslide risk at slopes assessed as stable by simpler deterministic methods.

Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2 O emissions.

PubMed

Ehrhardt, Fiona; Soussana, Jean-François; Bellocchi, Gianni; Grace, Peter; McAuliffe, Russel; Recous, Sylvie; Sándor, Renáta; Smith, Pete; Snow, Val; de Antoni Migliorati, Massimiliano; Basso, Bruno; Bhatia, Arti; Brilli, Lorenzo; Doltra, Jordi; Dorich, Christopher D; Doro, Luca; Fitton, Nuala; Giacomini, Sandro J; Grant, Brian; Harrison, Matthew T; Jones, Stephanie K; Kirschbaum, Miko U F; Klumpp, Katja; Laville, Patricia; Léonard, Joël; Liebig, Mark; Lieffering, Mark; Martin, Raphaël; Massad, Raia S; Meier, Elizabeth; Merbold, Lutz; Moore, Andrew D; Myrgiotis, Vasileios; Newton, Paul; Pattey, Elizabeth; Rolinski, Susanne; Sharp, Joanna; Smith, Ward N; Wu, Lianhai; Zhang, Qing

2018-02-01

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield-scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed. © 2017 John Wiley & Sons Ltd.

A systems-based approach for integrated design of materials, products and design process chains

NASA Astrophysics Data System (ADS)

Panchal, Jitesh H.; Choi, Hae-Jin; Allen, Janet K.; McDowell, David L.; Mistree, Farrokh

2007-12-01

The concurrent design of materials and products provides designers with flexibility to achieve design objectives that were not previously accessible. However, the improved flexibility comes at a cost of increased complexity of the design process chains and the materials simulation models used for executing the design chains. Efforts to reduce the complexity generally result in increased uncertainty. We contend that a systems based approach is essential for managing both the complexity and the uncertainty in design process chains and simulation models in concurrent material and product design. Our approach is based on simplifying the design process chains systematically such that the resulting uncertainty does not significantly affect the overall system performance. Similarly, instead of striving for accurate models for multiscale systems (that are inherently complex), we rely on making design decisions that are robust to uncertainties in the models. Accordingly, we pursue hierarchical modeling in the context of design of multiscale systems. In this paper our focus is on design process chains. We present a systems based approach, premised on the assumption that complex systems can be designed efficiently by managing the complexity of design process chains. The approach relies on (a) the use of reusable interaction patterns to model design process chains, and (b) consideration of design process decisions using value-of-information based metrics. The approach is illustrated using a Multifunctional Energetic Structural Material (MESM) design example. Energetic materials store considerable energy which can be released through shock-induced detonation; conventionally, they are not engineered for strength properties. The design objectives for the MESM in this paper include both sufficient strength and energy release characteristics. The design is carried out by using models at different length and time scales that simulate different aspects of the system. Finally, by applying the method to the MESM design problem, we show that the integrated design of materials and products can be carried out more efficiently by explicitly accounting for design process decisions with the hierarchy of models.

Comparison between bottom-up and top-down approaches in the estimation of measurement uncertainty.

PubMed

Lee, Jun Hyung; Choi, Jee-Hye; Youn, Jae Saeng; Cha, Young Joo; Song, Woonheung; Park, Ae Ja

2015-06-01

Measurement uncertainty is a metrological concept to quantify the variability of measurement results. There are two approaches to estimate measurement uncertainty. In this study, we sought to provide practical and detailed examples of the two approaches and compare the bottom-up and top-down approaches to estimating measurement uncertainty. We estimated measurement uncertainty of the concentration of glucose according to CLSI EP29-A guideline. Two different approaches were used. First, we performed a bottom-up approach. We identified the sources of uncertainty and made an uncertainty budget and assessed the measurement functions. We determined the uncertainties of each element and combined them. Second, we performed a top-down approach using internal quality control (IQC) data for 6 months. Then, we estimated and corrected systematic bias using certified reference material of glucose (NIST SRM 965b). The expanded uncertainties at the low glucose concentration (5.57 mmol/L) by the bottom-up approach and top-down approaches were ±0.18 mmol/L and ±0.17 mmol/L, respectively (all k=2). Those at the high glucose concentration (12.77 mmol/L) by the bottom-up and top-down approaches were ±0.34 mmol/L and ±0.36 mmol/L, respectively (all k=2). We presented practical and detailed examples for estimating measurement uncertainty by the two approaches. The uncertainties by the bottom-up approach were quite similar to those by the top-down approach. Thus, we demonstrated that the two approaches were approximately equivalent and interchangeable and concluded that clinical laboratories could determine measurement uncertainty by the simpler top-down approach.

Top-pair production at hadron colliders with next-to-next-to-leading logarithmic soft-gluon resummation

NASA Astrophysics Data System (ADS)

Cacciari, Matteo; Czakon, Michał; Mangano, Michelangelo; Mitov, Alexander; Nason, Paolo

2012-04-01

Incorporating all recent theoretical advances, we resum soft-gluon corrections to the total ttbar cross-section at hadron colliders at the next-to-next-to-leading logarithmic (NNLL) order. We perform the resummation in the well established framework of Mellin N-space resummation. We exhaustively study the sources of systematic uncertainty like renormalization and factorization scale variation, power suppressed effects and missing two- and higher-loop corrections. The inclusion of soft-gluon resummation at NNLL brings only a minor decrease in the perturbative uncertainty with respect to the NLL approximation, and a small shift in the central value, consistent with the quoted uncertainties. These numerical predictions agree with the currently available measurements from the Tevatron and LHC and have uncertainty of similar size. We conclude that significant improvements in the ttbar cross-sections can potentially be expected only upon inclusion of the complete NNLO corrections.

First Observation of a Baryonic Bs0 Decay

NASA Astrophysics Data System (ADS)

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

2017-07-01

We report the first observation of a baryonic Bs0 decay, Bs0→p Λ ¯K- , using proton-proton collision data recorded by the LHCb experiment at center-of-mass energies of 7 and 8 TeV, corresponding to an integrated luminosity of 3.0 fb-1. The branching fraction is measured to be B (Bs0→p Λ ¯ K- )+B (Bs0→p ¯ Λ K+ )=[5.46 ±0.61 ±0.57 ±0.50 (B )±0.32 (fs/fd)] ×10-6 , where the first uncertainty is statistical and the second systematic, the third uncertainty accounts for the experimental uncertainty on the branching fraction of the B0→p Λ ¯π- decay used for normalization, and the fourth uncertainty relates to the knowledge of the ratio of b -quark hadronization probabilities fs/fd.

Estimating uncertainty of Full Waveform Inversion with Ensemble-based methods

NASA Astrophysics Data System (ADS)

Thurin, J.; Brossier, R.; Métivier, L.

2017-12-01

Uncertainty estimation is one key feature of tomographic applications for robust interpretation. However, this information is often missing in the frame of large scale linearized inversions, and only the results at convergence are shown, despite the ill-posed nature of the problem. This issue is common in the Full Waveform Inversion community.While few methodologies have already been proposed in the literature, standard FWI workflows do not include any systematic uncertainty quantifications methods yet, but often try to assess the result's quality through cross-comparison with other results from seismic or comparison with other geophysical data. With the development of large seismic networks/surveys, the increase in computational power and the more and more systematic application of FWI, it is crucial to tackle this problem and to propose robust and affordable workflows, in order to address the uncertainty quantification problem faced for near surface targets, crustal exploration, as well as regional and global scales.In this work (Thurin et al., 2017a,b), we propose an approach which takes advantage of the Ensemble Transform Kalman Filter (ETKF) proposed by Bishop et al., (2001), in order to estimate a low-rank approximation of the posterior covariance matrix of the FWI problem, allowing us to evaluate some uncertainty information of the solution. Instead of solving the FWI problem through a Bayesian inversion with the ETKF, we chose to combine a conventional FWI, based on local optimization, and the ETKF strategies. This scheme allows combining the efficiency of local optimization for solving large scale inverse problems and make the sampling of the local solution space possible thanks to its embarrassingly parallel property. References:Bishop, C. H., Etherton, B. J. and Majumdar, S. J., 2001. Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects. Monthly weather review, 129(3), 420-436.Thurin, J., Brossier, R. and Métivier, L. 2017,a.: Ensemble-Based Uncertainty Estimation in Full Waveform Inversion. 79th EAGE Conference and Exhibition 2017, (12 - 15 June, 2017)Thurin, J., Brossier, R. and Métivier, L. 2017,b.: An Ensemble-Transform Kalman Filter - Full Waveform Inversion scheme for Uncertainty estimation; SEG Technical Program Expanded Abstracts 2012

Theoretical Grounds for the Propagation of Uncertainties in Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

Saracco, Paolo; Pia, Maria Grazia; Batic, Matej

2014-04-01

We introduce a theoretical framework for the calculation of uncertainties affecting observables produced by Monte Carlo particle transport, which derive from uncertainties in physical parameters input into simulation. The theoretical developments are complemented by a heuristic application, which illustrates the method of calculation in a streamlined simulation environment.

Estimating Uncertainty in Annual Forest Inventory Estimates

Treesearch

Ronald E. McRoberts; Veronica C. Lessard

1999-01-01

The precision of annual forest inventory estimates may be negatively affected by uncertainty from a variety of sources including: (1) sampling error; (2) procedures for updating plots not measured in the current year; and (3) measurement errors. The impact of these sources of uncertainty on final inventory estimates is investigated using Monte Carlo simulation...

MAX-DOAS measurements of HONO slant column densities during the MAD-CAT campaign: inter-comparison, sensitivity studies on spectral analysis settings, and error budget

NASA Astrophysics Data System (ADS)

Wang, Yang; Beirle, Steffen; Hendrick, Francois; Hilboll, Andreas; Jin, Junli; Kyuberis, Aleksandra A.; Lampel, Johannes; Li, Ang; Luo, Yuhan; Lodi, Lorenzo; Ma, Jianzhong; Navarro, Monica; Ortega, Ivan; Peters, Enno; Polyansky, Oleg L.; Remmers, Julia; Richter, Andreas; Puentedura, Olga; Van Roozendael, Michel; Seyler, André; Tennyson, Jonathan; Volkamer, Rainer; Xie, Pinhua; Zobov, Nikolai F.; Wagner, Thomas

2017-10-01

In order to promote the development of the passive DOAS technique the Multi Axis DOAS - Comparison campaign for Aerosols and Trace gases (MAD-CAT) was held at the Max Planck Institute for Chemistry in Mainz, Germany, from June to October 2013. Here, we systematically compare the differential slant column densities (dSCDs) of nitrous acid (HONO) derived from measurements of seven different instruments. We also compare the tropospheric difference of SCDs (delta SCD) of HONO, namely the difference of the SCDs for the non-zenith observations and the zenith observation of the same elevation sequence. Different research groups analysed the spectra from their own instruments using their individual fit software. All the fit errors of HONO dSCDs from the instruments with cooled large-size detectors are mostly in the range of 0.1 to 0.3 × 1015 molecules cm-2 for an integration time of 1 min. The fit error for the mini MAX-DOAS is around 0.7 × 1015 molecules cm-2. Although the HONO delta SCDs are normally smaller than 6 × 1015 molecules cm-2, consistent time series of HONO delta SCDs are retrieved from the measurements of different instruments. Both fits with a sequential Fraunhofer reference spectrum (FRS) and a daily noon FRS lead to similar consistency. Apart from the mini-MAX-DOAS, the systematic absolute differences of HONO delta SCDs between the instruments are smaller than 0.63 × 1015 molecules cm-2. The correlation coefficients are higher than 0.7 and the slopes of linear regressions deviate from unity by less than 16 % for the elevation angle of 1°. The correlations decrease with an increase in elevation angle. All the participants also analysed synthetic spectra using the same baseline DOAS settings to evaluate the systematic errors of HONO results from their respective fit programs. In general the errors are smaller than 0.3 × 1015 molecules cm-2, which is about half of the systematic difference between the real measurements.The differences of HONO delta SCDs retrieved in the selected three spectral ranges 335-361, 335-373 and 335-390 nm are considerable (up to 0.57 × 1015 molecules cm-2) for both real measurements and synthetic spectra. We performed sensitivity studies to quantify the dominant systematic error sources and to find a recommended DOAS setting in the three spectral ranges. The results show that water vapour absorption, temperature and wavelength dependence of O4 absorption, temperature dependence of Ring spectrum, and polynomial and intensity offset correction all together dominate the systematic errors. We recommend a fit range of 335-373 nm for HONO retrievals. In such fit range the overall systematic uncertainty is about 0.87 × 1015 molecules cm-2, much smaller than those in the other two ranges. The typical random uncertainty is estimated to be about 0.16 × 1015 molecules cm-2, which is only 25 % of the total systematic uncertainty for most of the instruments in the MAD-CAT campaign. In summary for most of the MAX-DOAS instruments for elevation angle below 5°, half daytime measurements (usually in the morning) of HONO delta SCD can be over the detection limit of 0.2 × 1015 molecules cm-2 with an uncertainty of ˜ 0.9 × 1015 molecules cm-2.

Within-Tunnel Variations in Pressure Data for Three Transonic Wind Tunnels

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2014-01-01

This paper compares the results of pressure measurements made on the same test article with the same test matrix in three transonic wind tunnels. A comparison is presented of the unexplained variance associated with polar replicates acquired in each tunnel. The impact of a significance component of systematic (not random) unexplained variance is reviewed, and the results of analyses of variance are presented to assess the degree of significant systematic error in these representative wind tunnel tests. Total uncertainty estimates are reported for 140 samples of pressure data, quantifying the effects of within-polar random errors and between-polar systematic bias errors.

Managing uncertainty in collaborative robotics engineering projects: The influence of task structure and peer interaction

NASA Astrophysics Data System (ADS)

Jordan, Michelle

Uncertainty is ubiquitous in life, and learning is an activity particularly likely to be fraught with uncertainty. Previous research suggests that students and teachers struggle in their attempts to manage the psychological experience of uncertainty and that students often fail to experience uncertainty when uncertainty may be warranted. Yet, few educational researchers have explicitly and systematically observed what students do, their behaviors and strategies, as they attempt to manage the uncertainty they experience during academic tasks. In this study I investigated how students in one fifth grade class managed uncertainty they experienced while engaged in collaborative robotics engineering projects, focusing particularly on how uncertainty management was influenced by task structure and students' interactions with their peer collaborators. The study was initiated at the beginning of instruction related to robotics engineering and preceded through the completion of several long-term collaborative robotics projects, one of which was a design project. I relied primarily on naturalistic observation of group sessions, semi-structured interviews, and collection of artifacts. My data analysis was inductive and interpretive, using qualitative discourse analysis techniques and methods of grounded theory. Three theoretical frameworks influenced the conception and design of this study: community of practice, distributed cognition, and complex adaptive systems theory. Uncertainty was a pervasive experience for the students collaborating in this instructional context. Students experienced uncertainty related to the project activity and uncertainty related to the social system as they collaborated to fulfill the requirements of their robotics engineering projects. They managed their uncertainty through a diverse set of tactics for reducing, ignoring, maintaining, and increasing uncertainty. Students experienced uncertainty from more different sources and used more and different types of uncertainty management strategies in the less structured task setting than in the more structured task setting. Peer interaction was influential because students relied on supportive social response to enact most of their uncertainty management strategies. When students could not garner socially supportive response from their peers, their options for managing uncertainty were greatly reduced.

Judgment under Uncertainty: Heuristics and Biases.

PubMed

Tversky, A; Kahneman, D

1974-09-27

This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.

Calibration procedure for a laser triangulation scanner with uncertainty evaluation

NASA Astrophysics Data System (ADS)

Genta, Gianfranco; Minetola, Paolo; Barbato, Giulio

2016-11-01

Most of low cost 3D scanning devices that are nowadays available on the market are sold without a user calibration procedure to correct measurement errors related to changes in environmental conditions. In addition, there is no specific international standard defining a procedure to check the performance of a 3D scanner along time. This paper aims at detailing a thorough methodology to calibrate a 3D scanner and assess its measurement uncertainty. The proposed procedure is based on the use of a reference ball plate and applied to a triangulation laser scanner. Experimental results show that the metrological performance of the instrument can be greatly improved by the application of the calibration procedure that corrects systematic errors and reduces the device's measurement uncertainty.

Making framing of uncertainty in water management practice explicit by using a participant-structured approach.

PubMed

Isendahl, Nicola; Dewulf, Art; Pahl-Wostl, Claudia

2010-01-01

By now, the need for addressing uncertainty in the management of water resources is widely recognized, yet there is little expertise and experience how to effectively deal with uncertainty in practice. Uncertainties in water management practice so far are mostly dealt with intuitively or based on experience. That way decisions can be quickly taken but analytic processes of deliberate reasoning are bypassed. To meet the desire of practitioners for better guidance and tools how to deal with uncertainty more practice-oriented systematic approaches are needed. For that purpose we consider it important to understand how practitioners frame uncertainties. In this paper we present an approach where water managers developed criteria of relevance to understand and address uncertainties. The empirical research took place in the Doñana region of the Guadalquivir estuary in southern Spain making use of the method of card sorting. Through the card sorting exercise a broad range of criteria to make sense of and describe uncertainties was produced by different subgroups, which were then merged into a shared list of criteria. That way framing differences were made explicit and communication on uncertainty and on framing differences was enhanced. In that, the present approach constitutes a first step to enabling reframing and overcoming framing differences, which are important features on the way to robust decision-making. Moreover, the elaborated criteria build a basis for the development of more structured approaches to deal with uncertainties in water management practice. Copyright 2009 Elsevier Ltd. All rights reserved.

A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

PubMed

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2014-03-01

GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2014-03-01

GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

Entropic uncertainty for spin-1/2 XXX chains in the presence of inhomogeneous magnetic fields and its steering via weak measurement reversals

NASA Astrophysics Data System (ADS)

Wang, Dong; Ming, Fei; Huang, Ai-Jun; Sun, Wen-Yang; Ye, Liu

2017-09-01

The uncertainty principle configures a low bound to the measuring precision for a pair of non-commuting observables, and hence is considerably nontrivial to quantum precision measurement in the field of quantum information theory. In this letter, we consider the entropic uncertainty relation (EUR) in the context of quantum memory in a two-qubit isotropic Heisenberg spin chain. Specifically, we explore the dynamics of EUR in a practical scenario, where two associated nodes of a one-dimensional XXX-spin chain, under an inhomogeneous magnetic field, are connected to a thermal entanglement. We show that the temperature and magnetic field effect can lead to the inflation of the measuring uncertainty, stemming from the reduction of systematic quantum correlation. Notably, we reveal that, firstly, the uncertainty is not fully dependent on the observed quantum correlation of the system; secondly, the dynamical behaviors of the measuring uncertainty are relatively distinct with respect to ferromagnetism and antiferromagnetism chains. Meanwhile, we deduce that the measuring uncertainty is dramatically correlated with the mixedness of the system, implying that smaller mixedness tends to reduce the uncertainty. Furthermore, we propose an effective strategy to control the uncertainty of interest by means of quantum weak measurement reversal. Therefore, our work may shed light on the dynamics of the measuring uncertainty in the Heisenberg spin chain, and thus be important to quantum precision measurement in various solid-state systems.

Using scenarios of North Slope energy and resource development to assess research and monitoring needs

NASA Astrophysics Data System (ADS)

Payne, J. F.

2016-12-01

Significant Arctic environmental and socio-economic change has been observed on the North Slope of Alaska, presenting challenges for resident communities and management agencies that need to adapt to future changes that are difficult to model or predict. Continued climate change coupled with new or modified energy development could substantially alter the landscape and ecosystem in the future. The North Slope Science Initiative (NSSI) recognized the value of using a participatory scenarios process to consider plausible future energy and resource development scenarios through the year 2040 to help identify and prioritize research and monitoring needs on the North Slope. The scenarios process engaged diverse stakeholders, including subject matter experts and local knowledge holders. Through identification and ranking of key drivers and uncertainties relevant to the focus of the study, a series of spatially explicit scenarios was developed, analyzed in terms of low, medium and high development activities. Climate change and economic factors were key drivers affecting plausible energy development scenarios. The implications from each of the scenarios were then used to identify important research and monitoring activities and their relevant spatial scales. The scenarios project identified over 40 research and monitoring needs. The top five research needs addressed data gaps and key concerns related to how the scenarios could affect: hunting and trapping on land, health and community well-being, permafrost and hydrology, marine mammal subsistence and potential marine oil spills. The use of a participatory scenarios process was essential for identifying a range of plausible energy and resource development scenarios using a framework that involved a systematic assessment of complex interacting drivers of change, consideration of key uncertainties, and transparency throughout the project.

Selective Logging, Fire, and Biomass in Amazonia

NASA Technical Reports Server (NTRS)

Houghton, R. A.

1999-01-01

Biomass and rates of disturbance are major factors in determining the net flux of carbon between terrestrial ecosystems and the atmosphere, and neither of them is well known for most of the earth's surface. Satellite data over large areas are beginning to be used systematically to measure rates of two of the most important types of disturbance, deforestation and reforestation, but these are not the only types of disturbance that affect carbon storage. Other examples include selective logging and fire. In northern mid-latitude forests, logging and subsequent regrowth of forests have, in recent decades, contributed more to the net flux of carbon between terrestrial ecosystems and the atmosphere than any other type of land use. In the tropics logging is also becoming increasingly important. According to the FAO/UNEP assessment of tropical forests, about 25% of total area of productive forests have been logged one or more times in the 60-80 years before 1980. The fraction must be considerably greater at present. Thus, deforestation by itself accounts for only a portion of the emissions carbon from land. Furthermore, as rates of deforestation become more accurately measured with satellites, uncertainty in biomass will become the major factor accounting for the remaining uncertainty in estimates of carbon flux. An approach is needed for determining the biomass of terrestrial ecosystems. 3 Selective logging is increasingly important in Amazonia, yet it has not been included in region-wide, satellite-based assessments of land-cover change, in part because it is not as striking as deforestation. Nevertheless, logging affects terrestrial carbon storage both directly and indirectly. Besides the losses of carbon directly associated with selective logging, logging also increases the likelihood of fire.

Rising temperatures reduce global wheat production

USDA-ARS?s Scientific Manuscript database

Crop models are essential to assess the threat of climate change for food production but have not been systematically tested against temperature experiments, despite demonstrated uncertainty in temperature response. Herein, we compare 30 different wheat crop models against field experiments in which...

Impacts of Process and Prediction Uncertainties on Projected Hanford Waste Glass Amount

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

Gervasio, V.; Kim, D. S.; Vienna, J. D.

Analyses were performed to evaluate the impacts of using the advanced glass models, constraints, and uncertainty descriptions on projected Hanford glass mass. The maximum allowable waste oxide loading (WOL) was estimated for waste compositions while simultaneously satisfying all applicable glass property and composition constraints with sufficient confidence. Different components of prediction and composition/process uncertainties were systematically included in the calculations to evaluate their impacts on glass mass. The analyses estimated the production of 23,360 MT of immobilized high-level waste (IHLW) glass when no uncertainties were taken into account. Accounting for prediction and composition/process uncertainties resulted in 5.01 relative percent increasemore » in estimated glass mass of 24,531 MT. Roughly equal impacts were found for prediction uncertainties (2.58 RPD) and composition/process uncertainties (2.43 RPD). The immobilized low-activity waste (ILAW) mass was predicted to be 282,350 MT without uncertainty and with waste loading “line” rules in place. Accounting for prediction and composition/process uncertainties resulted in only 0.08 relative percent increase in estimated glass mass of 282,562 MT. Without application of line rules the glass mass decreases by 10.6 relative percent (252,490 MT) for the case with no uncertainties. Addition of prediction uncertainties increases glass mass by 1.32 relative percent and the addition of composition/process uncertainties increase glass mass by an additional 7.73 relative percent (9.06 relative percent increase combined). The glass mass estimate without line rules (275,359 MT) was 2.55 relative percent lower than that with the line rules (282,562 MT), after accounting for all applicable uncertainties.« less

Improved entrance optic for global irradiance measurements with a Brewer spectrophotometer.

PubMed

Gröbner, Julian

2003-06-20

A new entrance optic for a Brewer spectrophotometer has been designed and tested both in the laboratory and during solar measurements. The integrated cosine response deviates by 2.4% from the ideal, with an uncertainty of +/- 1%. The systematic uncertainties of global solar irradiance measurements with this new entrance optic are considerably reduced compared with measurements with the traditional design. Simultaneous solar irradiance measurements between the Brewer spectrophotometer and a spectroradiometer equipped with a state-of-the-art shaped diffuser agreed to within +/- 2% during a five-day measurement period.

Recent Results From MINERvA

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

Patrick, Cheryl

The MINERvA detector is situated in Fermilab's NuMI beam, which provides neutrinos and antineutrinos in the 1-20 GeV range. It is designed to make precision cross-section measurements for scattering processes on various nuclei. These proceedings summarize the differential cross-section distributions measured for several different processes. Comparison of these with various models hints at additional nuclear effects not included in common simulations. These results will help constrain generators' nuclear models and reduce systematic uncertainties on their predictions. An accurate cross-section model, with minimal uncertainties, is vital to oscillation experiments.

ON THE DISTANCE OF THE MAGELLANIC CLOUDS USING CEPHEID NIR AND OPTICAL-NIR PERIOD-WESENHEIT RELATIONS

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

Inno, L.; Bono, G.; Buonanno, R.

2013-02-10

We present the largest near-infrared (NIR) data sets, JHKs, ever collected for classical Cepheids in the Magellanic Clouds (MCs). We selected fundamental (FU) and first overtone (FO) pulsators, and found 4150 (2571 FU, 1579 FO) Cepheids for Small Magellanic Cloud (SMC) and 3042 (1840 FU, 1202 FO) for Large Magellanic Cloud (LMC). Current sample is 2-3 times larger than any sample used in previous investigations with NIR photometry. We also discuss optical VI photometry from OGLE-III. NIR and optical-NIR Period-Wesenheit (PW) relations are linear over the entire period range (0.0 < log P {sub FU} {<=} 1.65) and their slopesmore » are, within the intrinsic dispersions, common between the MCs. These are consistent with recent results from pulsation models and observations suggesting that the PW relations are minimally affected by the metal content. The new FU and FO PW relations were calibrated using a sample of Galactic Cepheids with distances based on trigonometric parallaxes and Cepheid pulsation models. By using FU Cepheids we found a true distance moduli of 18.45 {+-} 0.02(random) {+-} 0.10(systematic) mag (LMC) and 18.93 {+-} 0.02(random) {+-} 0.10(systematic) mag (SMC). These estimates are the weighted mean over 10 PW relations and the systematic errors account for uncertainties in the zero point and in the reddening law. We found similar distances using FO Cepheids (18.60 {+-} 0.03(random) {+-} 0.10(systematic) mag (LMC) and 19.12 {+-} 0.03(random) {+-} 0.10(systematic) mag (SMC)). These new MC distances lead to the relative distance, {Delta}{mu} = 0.48 {+-} 0.03 mag (FU, log P = 1) and {Delta}{mu} = 0.52 {+-} 0.03 mag (FO, log P = 0.5), which agrees quite well with previous estimates based on robust distance indicators.« less

When is enough evidence enough? - Using systematic decision analysis and value-of-information analysis to determine the need for further evidence.

PubMed

Siebert, Uwe; Rochau, Ursula; Claxton, Karl

2013-01-01

Decision analysis (DA) and value-of-information (VOI) analysis provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. In medical decision making under uncertainty, there are two fundamental questions: 1) What decision should be made now given the best available evidence (and its uncertainty)?; 2) Subsequent to the current decision and given the magnitude of the remaining uncertainty, should we gather further evidence (i.e., perform additional studies), and if yes, which studies should be undertaken (e.g., efficacy, side effects, quality of life, costs), and what sample sizes are needed? Using the currently best available evidence, VoI analysis focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which the additional information will reduce this uncertainty. A quantitative framework allows for the valuation of the additional information that is generated by further research, and considers the decision maker's objectives and resource constraints. Claxton et al. summarise: "Value of information analysis can be used to inform a range of policy questions including whether a new technology should be approved based on existing evidence, whether it should be approved but additional research conducted or whether approval should be withheld until the additional evidence becomes available." [Claxton K. Value of information entry in Encyclopaedia of Health Economics, Elsevier, forthcoming 2014.] The purpose of this tutorial is to introduce the framework of systematic VoI analysis to guide further research. In our tutorial article, we explain the theoretical foundations and practical methods of decision analysis and value-of-information analysis. To illustrate, we use a simple case example of a foot ulcer (e.g., with diabetes) as well as key references from the literature, including examples for the use of the decision-analytic VoI framework by health technology assessment agencies to guide further research. These concepts may guide stakeholders involved or interested in how to determine whether or not and, if so, which additional evidence is needed to make decisions. Copyright © 2013. Published by Elsevier GmbH.

Dealing with uncertainty in modeling intermittent water supply

NASA Astrophysics Data System (ADS)

Lieb, A. M.; Rycroft, C.; Wilkening, J.

2015-12-01

Intermittency in urban water supply affects hundreds of millions of people in cities around the world, impacting water quality and infrastructure. Building on previous work to dynamically model the transient flows in water distribution networks undergoing frequent filling and emptying, we now consider the hydraulic implications of uncertain input data. Water distribution networks undergoing intermittent supply are often poorly mapped, and household metering frequently ranges from patchy to nonexistent. In the face of uncertain pipe material, pipe slope, network connectivity, and outflow, we investigate how uncertainty affects dynamical modeling results. We furthermore identify which parameters exert the greatest influence on uncertainty, helping to prioritize data collection.

Measurement of high-energy neutron flux above ground utilizing a spallation based multiplicity technique

DOE PAGES

Roecker, Caleb; Bernstein, Adam; Marleau, Peter; ...

2016-11-14

Cosmogenic high-energy neutrons are a ubiquitous, difficult to shield, poorly measured background. Above ground the high-energy neutron energy-dependent flux has been measured, with significantly varying results. Below ground, high-energy neutron fluxes are largely unmeasured. Here we present a reconstruction algorithm to unfold the incident neutron energy-dependent flux measured using the Multiplicity and Recoil Spectrometer (MARS), simulated test cases to verify the algorithm, and provide a new measurement of the above ground high-energy neutron energy-dependent flux with a detailed systematic uncertainty analysis. Uncertainty estimates are provided based upon the measurement statistics, the incident angular distribution, the surrounding environment of the Montemore » Carlo model, and the MARS triggering efficiency. Quantified systematic uncertainty is dominated by the assumed incident neutron angular distribution and surrounding environment of the Monte Carlo model. The energy-dependent neutron flux between 90 MeV and 400 MeV is reported. Between 90 MeV and 250 MeV the MARS results are comparable to previous Bonner sphere measurements. Over the total energy regime measured, the MARS result are located within the span of previous measurements. Lastly, these results demonstrate the feasibility of future below ground measurements with MARS.« less

Measurement of high-energy neutron flux above ground utilizing a spallation based multiplicity technique

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

Roecker, Caleb; Bernstein, Adam; Marleau, Peter

Cosmogenic high-energy neutrons are a ubiquitous, difficult to shield, poorly measured background. Above ground the high-energy neutron energy-dependent flux has been measured, with significantly varying results. Below ground, high-energy neutron fluxes are largely unmeasured. Here we present a reconstruction algorithm to unfold the incident neutron energy-dependent flux measured using the Multiplicity and Recoil Spectrometer (MARS), simulated test cases to verify the algorithm, and provide a new measurement of the above ground high-energy neutron energy-dependent flux with a detailed systematic uncertainty analysis. Uncertainty estimates are provided based upon the measurement statistics, the incident angular distribution, the surrounding environment of the Montemore » Carlo model, and the MARS triggering efficiency. Quantified systematic uncertainty is dominated by the assumed incident neutron angular distribution and surrounding environment of the Monte Carlo model. The energy-dependent neutron flux between 90 MeV and 400 MeV is reported. Between 90 MeV and 250 MeV the MARS results are comparable to previous Bonner sphere measurements. Over the total energy regime measured, the MARS result are located within the span of previous measurements. Lastly, these results demonstrate the feasibility of future below ground measurements with MARS.« less

Assessing uncertainties in land cover projections.

PubMed

Alexander, Peter; Prestele, Reinhard; Verburg, Peter H; Arneth, Almut; Baranzelli, Claudia; Batista E Silva, Filipe; Brown, Calum; Butler, Adam; Calvin, Katherine; Dendoncker, Nicolas; Doelman, Jonathan C; Dunford, Robert; Engström, Kerstin; Eitelberg, David; Fujimori, Shinichiro; Harrison, Paula A; Hasegawa, Tomoko; Havlik, Petr; Holzhauer, Sascha; Humpenöder, Florian; Jacobs-Crisioni, Chris; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Lavalle, Carlo; Lenton, Tim; Liu, Jiayi; Meiyappan, Prasanth; Popp, Alexander; Powell, Tom; Sands, Ronald D; Schaldach, Rüdiger; Stehfest, Elke; Steinbuks, Jevgenijs; Tabeau, Andrzej; van Meijl, Hans; Wise, Marshall A; Rounsevell, Mark D A

2017-02-01

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover. © 2016 John Wiley & Sons Ltd.

Uncertainty Calculations in the First Introductory Physics Laboratory

NASA Astrophysics Data System (ADS)

Rahman, Shafiqur

2005-03-01

Uncertainty in a measured quantity is an integral part of reporting any experimental data. Consequently, Introductory Physics laboratories at many institutions require that students report the values of the quantities being measured as well as their uncertainties. Unfortunately, given that there are three main ways of calculating uncertainty, each suitable for particular situations (which is usually not explained in the lab manual), this is also an area that students feel highly confused about. It frequently generates large number of complaints in the end-of-the semester course evaluations. Students at some institutions are not asked to calculate uncertainty at all, which gives them a fall sense of the nature of experimental data. Taking advantage of the increased sophistication in the use of computers and spreadsheets that students are coming to college with, we have completely restructured our first Introductory Physics Lab to address this problem. Always in the context of a typical lab, we now systematically and sequentially introduce the various ways of calculating uncertainty including a theoretical understanding as opposed to a cookbook approach, all within the context of six three-hour labs. Complaints about the lab in student evaluations have dropped by 80%. * supported by a grant from A. V. Davis Foundation

Uncertainty Analysis of Sonic Boom Levels Measured in a Simulator at NASA Langley

NASA Technical Reports Server (NTRS)

Rathsam, Jonathan; Ely, Jeffry W.

2012-01-01

A sonic boom simulator has been constructed at NASA Langley Research Center for testing the human response to sonic booms heard indoors. Like all measured quantities, sonic boom levels in the simulator are subject to systematic and random errors. To quantify these errors, and their net influence on the measurement result, a formal uncertainty analysis is conducted. Knowledge of the measurement uncertainty, or range of values attributable to the quantity being measured, enables reliable comparisons among measurements at different locations in the simulator as well as comparisons with field data or laboratory data from other simulators. The analysis reported here accounts for acoustic excitation from two sets of loudspeakers: one loudspeaker set at the facility exterior that reproduces the exterior sonic boom waveform and a second set of interior loudspeakers for reproducing indoor rattle sounds. The analysis also addresses the effect of pressure fluctuations generated when exterior doors of the building housing the simulator are opened. An uncertainty budget is assembled to document each uncertainty component, its sensitivity coefficient, and the combined standard uncertainty. The latter quantity will be reported alongside measurement results in future research reports to indicate data reliability.

The Fermi Galactic Center GeV Excess and Implications for Dark Matter

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

Ackermann, M.; Buehler, R.; Ajello, M.

2017-05-01

The region around the Galactic Center (GC) is now well established to be brighter at energies of a few GeV than what is expected from conventional models of diffuse gamma-ray emission and catalogs of known gamma-ray sources. We study the GeV excess using 6.5 yr of data from the Fermi Large Area Telescope. We characterize the uncertainty of the GC excess spectrum and morphology due to uncertainties in cosmic-ray source distributions and propagation, uncertainties in the distribution of interstellar gas in the Milky Way, and uncertainties due to a potential contribution from the Fermi bubbles. We also evaluate uncertainties inmore » the excess properties due to resolved point sources of gamma rays. The GC is of particular interest, as it would be expected to have the brightest signal from annihilation of weakly interacting massive dark matter (DM) particles. However, control regions along the Galactic plane, where a DM signal is not expected, show excesses of similar amplitude relative to the local background. Based on the magnitude of the systematic uncertainties, we conservatively report upper limits for the annihilation cross-section as a function of particle mass and annihilation channel.« less

Sensitivity Analysis and Parameter Estimation for a Reactive Transport Model of Uranium Bioremediation

NASA Astrophysics Data System (ADS)

Meyer, P. D.; Yabusaki, S.; Curtis, G. P.; Ye, M.; Fang, Y.

2011-12-01

A three-dimensional, variably-saturated flow and multicomponent biogeochemical reactive transport model of uranium bioremediation was used to generate synthetic data . The 3-D model was based on a field experiment at the U.S. Dept. of Energy Rifle Integrated Field Research Challenge site that used acetate biostimulation of indigenous metal reducing bacteria to catalyze the conversion of aqueous uranium in the +6 oxidation state to immobile solid-associated uranium in the +4 oxidation state. A key assumption in past modeling studies at this site was that a comprehensive reaction network could be developed largely through one-dimensional modeling. Sensitivity analyses and parameter estimation were completed for a 1-D reactive transport model abstracted from the 3-D model to test this assumption, to identify parameters with the greatest potential to contribute to model predictive uncertainty, and to evaluate model structure and data limitations. Results showed that sensitivities of key biogeochemical concentrations varied in space and time, that model nonlinearities and/or parameter interactions have a significant impact on calculated sensitivities, and that the complexity of the model's representation of processes affecting Fe(II) in the system may make it difficult to correctly attribute observed Fe(II) behavior to modeled processes. Non-uniformity of the 3-D simulated groundwater flux and averaging of the 3-D synthetic data for use as calibration targets in the 1-D modeling resulted in systematic errors in the 1-D model parameter estimates and outputs. This occurred despite using the same reaction network for 1-D modeling as used in the data-generating 3-D model. Predictive uncertainty of the 1-D model appeared to be significantly underestimated by linear parameter uncertainty estimates.

Disease spread models to estimate highly uncertain emerging diseases losses for animal agriculture insurance policies: an application to the U.S. farm-raised catfish industry.

PubMed

Zagmutt, Francisco J; Sempier, Stephen H; Hanson, Terril R

2013-10-01

Emerging diseases (ED) can have devastating effects on agriculture. Consequently, agricultural insurance for ED can develop if basic insurability criteria are met, including the capability to estimate the severity of ED outbreaks with associated uncertainty. The U.S. farm-raised channel catfish (Ictalurus punctatus) industry was used to evaluate the feasibility of using a disease spread simulation modeling framework to estimate the potential losses from new ED for agricultural insurance purposes. Two stochastic models were used to simulate the spread of ED between and within channel catfish ponds in Mississippi (MS) under high, medium, and low disease impact scenarios. The mean (95% prediction interval (PI)) proportion of ponds infected within disease-impacted farms was 7.6% (3.8%, 22.8%), 24.5% (3.8%, 72.0%), and 45.6% (4.0%, 92.3%), and the mean (95% PI) proportion of fish mortalities in ponds affected by the disease was 9.8% (1.4%, 26.7%), 49.2% (4.7%, 60.7%), and 88.3% (85.9%, 90.5%) for the low, medium, and high impact scenarios, respectively. The farm-level mortality losses from an ED were up to 40.3% of the total farm inventory and can be used for insurance premium rate development. Disease spread modeling provides a systematic way to organize the current knowledge on the ED perils and, ultimately, use this information to help develop actuarially sound agricultural insurance policies and premiums. However, the estimates obtained will include a large amount of uncertainty driven by the stochastic nature of disease outbreaks, by the uncertainty in the frequency of future ED occurrences, and by the often sparse data available from past outbreaks. © 2013 Society for Risk Analysis.

Cued uncertainty modulates later recognition of emotional pictures: An ERP study.

PubMed

Lin, Huiyan; Xiang, Jing; Li, Saili; Liang, Jiafeng; Zhao, Dongmei; Yin, Desheng; Jin, Hua

2017-06-01

Previous studies have shown that uncertainty about the emotional content of an upcoming event modulates event-related potentials (ERPs) during the encoding of the event, and this modulation is affected by whether there are cues (i.e., cued uncertainty) or not (i.e., uncued uncertainty) prior to the encoding of the uncertain event. Recently, we showed that uncued uncertainty affected ERPs in later recognition of the emotional event. However, it is as yet unknown how the ERP effects of recognition are modulated by cued uncertainty. To address this issue, participants were asked to view emotional (negative and neutral) pictures that were presented after cues. The cues either indicated the emotional content of the pictures (the certain condition) or not (the cued uncertain condition). Subsequently, participants had to perform an unexpected old/new task in which old and novel pictures were shown without any cues. ERP data in the old/new task showed smaller P2 amplitudes for neutral pictures in the cued uncertain condition compared to the certain condition, but this uncertainty effect was not observed for negative pictures. Additionally, P3 amplitudes were generally enlarged for pictures in the cued uncertain condition. Taken together, the present findings indicate that cued uncertainty alters later recognition of emotional events in relevance to feature processing and attention allocation. Copyright © 2017. Published by Elsevier B.V.

Processing of higher count rates in Troitsk nu-mass experiment

NASA Astrophysics Data System (ADS)

Nozik, Alexander; Chernov, Vaslily

2018-04-01

In this article we give a short outline of current status of search for sterile neutrinos with masses up to 4 keV in "Troitsk nu-mass experiment". We also discuss major sources of systematic uncertainties and methods to lower them.

6th international conference on case histories in geotechnical engineering August 2008conference report.

DOT National Transportation Integrated Search

2009-01-01

Due to uncertainty in the nature of soils, a systematic study of the performance of geotechnical structures and its match with predictions is extremely important. Therefore, considerable research effort is being devoted to geotechnical engineering th...

Margaret Wheatley on Leadership for Change.

ERIC Educational Resources Information Center

Steinberger, Elizabeth Donohoe

1995-01-01

Wheatley's 1992 bestseller, "Leadership and the New Science," argues that across scientific disciplines, our rational, systematic quest for order, control, stability, and predictability are yielding to a deeper appreciation for chaos, complexity, uncertainty, and change. In this interview, Wheatley shows how breakthroughs in biology,…

Uncertainty of Comparative Judgments and Multidimensional Structure

ERIC Educational Resources Information Center

Sjoberg, Lennart

1975-01-01

An analysis of preferences with respect to silhouette drawings of nude females is presented. Systematic intransitivities were discovered. The dispersions of differences (comparatal dispersons) were shown to reflect the multidimensional structure of the stimuli, a finding expected on the basis of prior work. (Author)

Uncertainty estimation of a complex water quality model: The influence of Box-Cox transformation on Bayesian approaches and comparison with a non-Bayesian method

NASA Astrophysics Data System (ADS)

Freni, Gabriele; Mannina, Giorgio

In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised Likelihood Uncertainty Estimation (GLUE). One crucial point in the application of Bayesian method is the formulation of a likelihood function that is conditioned by the hypotheses made regarding model residuals. Statistical transformations, such as the use of Box-Cox equation, are generally used to ensure the homoscedasticity of residuals. However, this practice may affect the reliability of the analysis leading to a wrong uncertainty estimation. The present paper aims to explore the influence of the Box-Cox equation for environmental water quality models. To this end, five cases were considered one of which was the “real” residuals distributions (i.e. drawn from available data). The analysis was applied to the Nocella experimental catchment (Italy) which is an agricultural and semi-urbanised basin where two sewer systems, two wastewater treatment plants and a river reach were monitored during both dry and wet weather periods. The results show that the uncertainty estimation is greatly affected by residual transformation and a wrong assumption may also affect the evaluation of model uncertainty. The use of less formal methods always provide an overestimation of modelling uncertainty with respect to Bayesian method but such effect is reduced if a wrong assumption is made regarding the residuals distribution. If residuals are not normally distributed, the uncertainty is over-estimated if Box-Cox transformation is not applied or non-calibrated parameter is used.

Towards SI-traceable radio occultation excess phase processing with integrated uncertainty estimation for climate applications

NASA Astrophysics Data System (ADS)

Innerkofler, Josef; Pock, Christian; Kirchengast, Gottfried; Schwaerz, Marc; Jaeggi, Adrian; Schwarz, Jakob

2016-04-01

The GNSS Radio Occultation (RO) measurement technique is highly valuable for climate monitoring of the atmosphere as it provides accurate and precise measurements in the troposphere and stratosphere regions with global coverage, long-term stability, and virtually all-weather capability. The novel Reference Occultation Processing System (rOPS), currently under development at the WEGC at University of Graz aims to process raw RO measurements into essential climate variables, such as temperature, pressure, and tropospheric water vapor, in a way which is SI-traceable to the universal time standard and which includes rigorous uncertainty propagation. As part of this rOPS climate-quality processing system, accurate atmospheric excess phase profiles with new approaches integrating uncertainty propagation are derived from the raw occultation tracking data and orbit data. Regarding the latter, highly accurate orbit positions and velocities of the GNSS transmitter satellites and the RO receiver satellites in low Earth orbit (LEO) need to be determined, in order to enable high accuracy of the excess phase profiles. Using several representative test days of GPS orbit data from the CODE and IGS archives, which are available at accuracies of about 3 cm (position) / 0.03 mm/s (velocity), and employing Bernese 5.2 and Napeos 3.3.1 software packages for the LEO orbit determination of the CHAMP, GRACE, and MetOp RO satellites, we achieved robust SI-traced LEO orbit uncertainty estimates of about 5 cm (position) / 0.05 mm/s (velocity) for the daily orbits, including estimates of systematic uncertainty bounds and of propagated random uncertainties. For COSMIC RO satellites, we found decreased accuracy estimates near 10-15 cm (position) / 0.1-0.15 mm/s (velocity), since the characteristics of the small COSMIC satellite platforms and antennas provide somewhat less favorable orbit determination conditions. We present the setup of how we (I) used the Bernese and Napeos package in mutual cross-check for this purpose, (II) integrated satellite laser-ranging validation of the estimated systematic uncertainty bounds, (III) expanded the Bernese 5.2 software for propagating random uncertainties from the GPS orbit data and LEO navigation tracking data input to the LEO data output. Preliminary excess phase results including propagated uncertainty estimates will also be shown. Except for disturbed space weather conditions, we expect a robust performance at millimeter level for the derived excess phases, which after large-scale processing of the RO data of many years can provide a new SI-traced fundamental climate data record.

Uncertainty of rotating shadowband irradiometers and Si-pyranometers including the spectral irradiance error

NASA Astrophysics Data System (ADS)

Wilbert, Stefan; Kleindiek, Stefan; Nouri, Bijan; Geuder, Norbert; Habte, Aron; Schwandt, Marko; Vignola, Frank

2016-05-01

Concentrating solar power projects require accurate direct normal irradiance (DNI) data including uncertainty specifications for plant layout and cost calculations. Ground measured data are necessary to obtain the required level of accuracy and are often obtained with Rotating Shadowband Irradiometers (RSI) that use photodiode pyranometers and correction functions to account for systematic effects. The uncertainty of Si-pyranometers has been investigated, but so far basically empirical studies were published or decisive uncertainty influences had to be estimated based on experience in analytical studies. One of the most crucial estimated influences is the spectral irradiance error because Si-photodiode-pyranometers only detect visible and color infrared radiation and have a spectral response that varies strongly within this wavelength interval. Furthermore, analytic studies did not discuss the role of correction functions and the uncertainty introduced by imperfect shading. In order to further improve the bankability of RSI and Si-pyranometer data, a detailed uncertainty analysis following the Guide to the Expression of Uncertainty in Measurement (GUM) has been carried out. The study defines a method for the derivation of the spectral error and spectral uncertainties and presents quantitative values of the spectral and overall uncertainties. Data from the PSA station in southern Spain was selected for the analysis. Average standard uncertainties for corrected 10 min data of 2 % for global horizontal irradiance (GHI), and 2.9 % for DNI (for GHI and DNI over 300 W/m²) were found for the 2012 yearly dataset when separate GHI and DHI calibration constants were used. Also the uncertainty in 1 min resolution was analyzed. The effect of correction functions is significant. The uncertainties found in this study are consistent with results of previous empirical studies.

Uncertainty of Rotating Shadowband Irradiometers and Si-Pyranometers Including the Spectral Irradiance Error

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

Wilbert, Stefan; Kleindiek, Stefan; Nouri, Bijan

2016-05-31

Concentrating solar power projects require accurate direct normal irradiance (DNI) data including uncertainty specifications for plant layout and cost calculations. Ground measured data are necessary to obtain the required level of accuracy and are often obtained with Rotating Shadowband Irradiometers (RSI) that use photodiode pyranometers and correction functions to account for systematic effects. The uncertainty of Si-pyranometers has been investigated, but so far basically empirical studies were published or decisive uncertainty influences had to be estimated based on experience in analytical studies. One of the most crucial estimated influences is the spectral irradiance error because Si-photodiode-pyranometers only detect visible andmore » color infrared radiation and have a spectral response that varies strongly within this wavelength interval. Furthermore, analytic studies did not discuss the role of correction functions and the uncertainty introduced by imperfect shading. In order to further improve the bankability of RSI and Si-pyranometer data, a detailed uncertainty analysis following the Guide to the Expression of Uncertainty in Measurement (GUM) has been carried out. The study defines a method for the derivation of the spectral error and spectral uncertainties and presents quantitative values of the spectral and overall uncertainties. Data from the PSA station in southern Spain was selected for the analysis. Average standard uncertainties for corrected 10 min data of 2% for global horizontal irradiance (GHI), and 2.9% for DNI (for GHI and DNI over 300 W/m2) were found for the 2012 yearly dataset when separate GHI and DHI calibration constants were used. Also the uncertainty in 1 min resolution was analyzed. The effect of correction functions is significant. The uncertainties found in this study are consistent with results of previous empirical studies.« less

Measuring Dark Energy Properties with Photometrically Classified Pan-STARRS Supernovae. II. Cosmological Parameters

NASA Astrophysics Data System (ADS)

Jones, D. O.; Scolnic, D. M.; Riess, A. G.; Rest, A.; Kirshner, R. P.; Berger, E.; Kessler, R.; Pan, Y.-C.; Foley, R. J.; Chornock, R.; Ortega, C. A.; Challis, P. J.; Burgett, W. S.; Chambers, K. C.; Draper, P. W.; Flewelling, H.; Huber, M. E.; Kaiser, N.; Kudritzki, R.-P.; Metcalfe, N.; Tonry, J.; Wainscoat, R. J.; Waters, C.; Gall, E. E. E.; Kotak, R.; McCrum, M.; Smartt, S. J.; Smith, K. W.

2018-04-01

We use 1169 Pan-STARRS supernovae (SNe) and 195 low-z (z < 0.1) SNe Ia to measure cosmological parameters. Though most Pan-STARRS SNe lack spectroscopic classifications, in a previous paper we demonstrated that photometrically classified SNe can be used to infer unbiased cosmological parameters by using a Bayesian methodology that marginalizes over core-collapse (CC) SN contamination. Our sample contains nearly twice as many SNe as the largest previous SN Ia compilation. Combining SNe with cosmic microwave background (CMB) constraints from Planck, we measure the dark energy equation-of-state parameter w to be ‑0.989 ± 0.057 (stat+sys). If w evolves with redshift as w(a) = w 0 + w a (1 ‑ a), we find w 0 = ‑0.912 ± 0.149 and w a = ‑0.513 ± 0.826. These results are consistent with cosmological parameters from the Joint Light-curve Analysis and the Pantheon sample. We try four different photometric classification priors for Pan-STARRS SNe and two alternate ways of modeling CC SN contamination, finding that no variant gives a w differing by more than 2% from the baseline measurement. The systematic uncertainty on w due to marginalizing over CC SN contamination, {σ }wCC}=0.012, is the third-smallest source of systematic uncertainty in this work. We find limited (1.6σ) evidence for evolution of the SN color-luminosity relation with redshift, a possible systematic that could constitute a significant uncertainty in future high-z analyses. Our data provide one of the best current constraints on w, demonstrating that samples with ∼5% CC SN contamination can give competitive cosmological constraints when the contaminating distribution is marginalized over in a Bayesian framework.

A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

PubMed Central

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

Methods for Assessing Uncertainties in Climate Change, Impacts and Responses (Invited)

NASA Astrophysics Data System (ADS)

Manning, M. R.; Swart, R.

2009-12-01

Assessing the scientific uncertainties or confidence levels for the many different aspects of climate change is particularly important because of the seriousness of potential impacts and the magnitude of economic and political responses that are needed to mitigate climate change effectively. This has made the treatment of uncertainty and confidence a key feature in the assessments carried out by the Intergovernmental Panel on Climate Change (IPCC). Because climate change is very much a cross-disciplinary area of science, adequately dealing with uncertainties requires recognition of their wide range and different perspectives on assessing and communicating those uncertainties. The structural differences that exist across disciplines are often embedded deeply in the corresponding literature that is used as the basis for an IPCC assessment. The assessment of climate change science by the IPCC has from its outset tried to report the levels of confidence and uncertainty in the degree of understanding in both the underlying multi-disciplinary science and in projections for future climate. The growing recognition of the seriousness of this led to the formation of a detailed approach for consistent treatment of uncertainties in the IPCC’s Third Assessment Report (TAR) [Moss and Schneider, 2000]. However, in completing the TAR there remained some systematic differences between the disciplines raising concerns about the level of consistency. So further consideration of a systematic approach to uncertainties was undertaken for the Fourth Assessment Report (AR4). The basis for the approach used in the AR4 was developed at an expert meeting of scientists representing many different disciplines. This led to the introduction of a broader way of addressing uncertainties in the AR4 [Manning et al., 2004] which was further refined by lengthy discussions among many IPCC Lead Authors, for over a year, resulting in a short summary of a standard approach to be followed for that assessment [IPCC, 2005]. This paper extends a review of the treatment of uncertainty in the IPCC assessments by Swart et al [2009]. It is shown that progress towards consistency has been made but that there also appears to be a need for continued use of several complementary approaches in order to cover the wide range of circumstances across different disciplines involved in climate change. While this reflects the situation in the science community, it also raises the level of complexity for policymakers and other users of the assessments who would prefer one common consensus approach. References IPCC (2005), Guidance Notes for Lead Authors of the IPCC Fourth Assessment Report on Addressing Uncertainties, IPCC, Geneva. Manning, M., et al. (2004), IPCC Workshop on Describing Scientific Uncertainties in Climate Change to Support Analysis of Risk and of Options. IPCC Moss, R., and S. Schneider (2000), Uncertainties, in Guidance Papers on the Cross Cutting Issues of the Third Assessment Report of the IPCC, edited by R. Pachauri, et al., Intergovernmental Panel on Climate Change (IPCC), Geneva. Swart, R., et al. (2009), Agreeing to disagree: uncertainty management in assessing climate change, impacts and responses by the IPCC Climatic Change, 92(1-2), 1 - 29.

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 2: Appendices

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

Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M.

1998-04-01

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library ofmore » uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA internal dosimetry models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on internal dosimetry, (4) short biographies of the experts, and (5) the aggregated results of their responses.« less

Efficient Location Uncertainty Treatment for Probabilistic Modelling of Portfolio Loss from Earthquake Events

NASA Astrophysics Data System (ADS)

Scheingraber, Christoph; Käser, Martin; Allmann, Alexander

2017-04-01

Probabilistic seismic risk analysis (PSRA) is a well-established method for modelling loss from earthquake events. In the insurance industry, it is widely employed for probabilistic modelling of loss to a distributed portfolio. In this context, precise exposure locations are often unknown, which results in considerable loss uncertainty. The treatment of exposure uncertainty has already been identified as an area where PSRA would benefit from increased research attention. However, so far, epistemic location uncertainty has not been in the focus of a large amount of research. We propose a new framework for efficient treatment of location uncertainty. To demonstrate the usefulness of this novel method, a large number of synthetic portfolios resembling real-world portfolios is systematically analyzed. We investigate the effect of portfolio characteristics such as value distribution, portfolio size, or proportion of risk items with unknown coordinates on loss variability. Several sampling criteria to increase the computational efficiency of the framework are proposed and put into the wider context of well-established Monte-Carlo variance reduction techniques. The performance of each of the proposed criteria is analyzed.

Plans for a measurement of the neutron lifetime to better than 0.3s using a Penning trap and absolute measurement of neutron fluence

NASA Astrophysics Data System (ADS)

Mulholland, Jonathan; NBL3 Collaboration

2014-09-01

The decay of the free neutron is the prototypical charged current semi-leptonic weak process. A precise value for the neutron lifetime is required for consistency tests of the Standard Model and is needed to predict the primordial He4 abundance from the theory of Big Bang Nucleosynthesis. Plans are being made for an in-beam measurement of the neutron lifetime with an anticipated 0.3s of uncertainty or better. This effort is part of a phased campaign of neutron lifetime measurements based at the NIST Center for Neutron Research, using the Sussex-ILL-NIST technique. Advances in neutron fluence measurement, used in to provide the best existing in-beam determination of the neutron lifetime, as well as new silicon detector technology, in use now at LANSCE, address the two largest contributors to the uncertainty of in-beam measurements-the statistical uncertainty associated with proton counting and the systematic uncertainty in the neutron fluence measurement. The experimental design and projected uncertainties for the 0.3s measurement will be discussed.

Measurement time and statistics for a noise thermometer with a synthetic-noise reference

NASA Astrophysics Data System (ADS)

White, D. R.; Benz, S. P.; Labenski, J. R.; Nam, S. W.; Qu, J. F.; Rogalla, H.; Tew, W. L.

2008-08-01

This paper describes methods for reducing the statistical uncertainty in measurements made by noise thermometers using digital cross-correlators and, in particular, for thermometers using pseudo-random noise for the reference signal. First, a discrete-frequency expression for the correlation bandwidth for conventional noise thermometers is derived. It is shown how an alternative frequency-domain computation can be used to eliminate the spectral response of the correlator and increase the correlation bandwidth. The corresponding expressions for the uncertainty in the measurement of pseudo-random noise in the presence of uncorrelated thermal noise are then derived. The measurement uncertainty in this case is less than that for true thermal-noise measurements. For pseudo-random sources generating a frequency comb, an additional small reduction in uncertainty is possible, but at the cost of increasing the thermometer's sensitivity to non-linearity errors. A procedure is described for allocating integration times to further reduce the total uncertainty in temperature measurements. Finally, an important systematic error arising from the calculation of ratios of statistical variables is described.

Model uncertainty of various settlement estimation methods in shallow tunnels excavation; case study: Qom subway tunnel

NASA Astrophysics Data System (ADS)

Khademian, Amir; Abdollahipour, Hamed; Bagherpour, Raheb; Faramarzi, Lohrasb

2017-10-01

In addition to the numerous planning and executive challenges, underground excavation in urban areas is always followed by certain destructive effects especially on the ground surface; ground settlement is the most important of these effects for which estimation there exist different empirical, analytical and numerical methods. Since geotechnical models are associated with considerable model uncertainty, this study characterized the model uncertainty of settlement estimation models through a systematic comparison between model predictions and past performance data derived from instrumentation. To do so, the amount of surface settlement induced by excavation of the Qom subway tunnel was estimated via empirical (Peck), analytical (Loganathan and Poulos) and numerical (FDM) methods; the resulting maximum settlement value of each model were 1.86, 2.02 and 1.52 cm, respectively. The comparison of these predicted amounts with the actual data from instrumentation was employed to specify the uncertainty of each model. The numerical model outcomes, with a relative error of 3.8%, best matched the reality and the analytical method, with a relative error of 27.8%, yielded the highest level of model uncertainty.

Precision Measurement of the Beryllium-7 Solar Neutrino Interaction Rate in Borexino

NASA Astrophysics Data System (ADS)

Saldanha, Richard Nigel

Solar neutrinos, since their first detection nearly forty years ago, have revealed valuable information regarding the source of energy production in the Sun, and have demonstrated that neutrino oscillations are well described by the Large Mixing Angle (LMA) oscillation parameters with matter interactions due to the Mikheyev-Smirnov-Wolfenstein (MSW) effect. This thesis presents a precision measurement of the 7Be solar neutrino interaction rate within Borexino, an underground liquid scintillator detector that is designed to measure solar neutrino interactions through neutrino-electron elastic scattering. The thesis includes a detailed description of the analysis techniques developed and used for this measurement as well as an evaluation of the relevant systematic uncertainties that affect the precision of the result. The rate of neutrino-electron elastic scattering from 0.862 MeV 7Be neutrinos is determined to be 45.4 +/- 1.6 (stat) +/- 1.5 (sys) counts/day/100 ton. Due to extensive detector calibrations and improved analysis methods, the systematic uncertainty in the interaction rate has been reduced by more than a factor of two from the previous evaluation. In the no-oscillation hypothesis, the interaction rate corresponds to a 0.862 MeV 7Be electron neutrino flux of (2.75 +/- 0.13) x 10 9 cm-2 sec-1. Including the predicted neutrino flux from the Standard Solar Model yields an electron neutrino survival probability of Pee 0.51 +/- 0.07 and rules out the no-oscillation hypothesis at 5.1sigma The LMA-MSW neutrino oscillation model predicts a transition in the solar Pee value between low (< 1 MeV) and high (> 10 MeV) energies which has not yet been experimentally confirmed. This result, in conjunction with the Standard Solar Model, represents the most precise measurement of the electron neutrino survival probability for solar neutrinos at sub-MeV energies.

Do state-of-the-art CMIP5 ESMs accurately represent observed vegetation-rainfall feedbacks? Focus on the Sahel

NASA Astrophysics Data System (ADS)

Notaro, M.; Wang, F.; Yu, Y.; Mao, J.; Shi, X.; Wei, Y.

2017-12-01

The semi-arid Sahel ecoregion is an established hotspot of land-atmosphere coupling. Ocean-land-atmosphere interactions received considerable attention by modeling studies in response to the devastating 1970s-90s Sahel drought, which models suggest was driven by sea-surface temperature (SST) anomalies and amplified by local vegetation-atmosphere feedbacks. Vegetation affects the atmosphere through biophysical feedbacks by altering the albedo, roughness, and transpiration and thereby modifying exchanges of energy, momentum, and moisture with the atmosphere. The current understanding of these potentially competing processes is primarily based on modeling studies, with biophysical feedbacks serving as a key uncertainty source in regional climate change projections among Earth System Models (ESMs). In order to reduce this uncertainty, it is critical to rigorously evaluate the representation of vegetation feedbacks in ESMs against an observational benchmark in order to diagnose systematic biases and their sources. However, it is challenging to successfully isolate vegetation's feedbacks on the atmosphere, since the atmospheric control on vegetation growth dominates the atmospheric feedback response to vegetation anomalies and the atmosphere is simultaneously influenced by oceanic and terrestrial anomalies. In response to this challenge, a model-validated multivariate statistical method, Stepwise Generalized Equilibrium Feedback Assessment (SGEFA), is developed, which extracts the forcing of a slowly-evolving environmental variable [e.g. SST or leaf area index (LAI)] on the rapidly-evolving atmosphere. By applying SGEFA to observational and remotely-sensed data, an observational benchmark is established for Sahel vegetation feedbacks. In this work, the simulated responses in key atmospheric variables, including evapotranspiration, albedo, wind speed, vertical motion, temperature, stability, and rainfall, to Sahel LAI anomalies are statistically assessed in Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs through SGEFA. The dominant mechanism, such as albedo feedback, moisture recycling, or momentum feedback, in each ESM is evaluated against the observed benchmark. SGEFA facilitates a systematic assessment of model biases in land-atmosphere interactions.

VizieR Online Data Catalog: Distances of Gaia DR1 TGAS sources (Astraatmadja+, 2016)

NASA Astrophysics Data System (ADS)

Astraatmadja, T. L.; Bailer-Jones, C. A. L.

2016-09-01

This is a catalogue of distances and their asymmetric uncertainties inferred from the parallaxes published in the Gaia DR1 catalogue. Two priors are used: The exponentially decreasing space density and the Milky Way prior. For the exponentially decreasing space density prior, two scale lengths are used: 110pc and 1350pc. The former is based on a fitting of the true distance distribution of a subset of the GUMS catalogue (Robin et al., 2012, Cat. VI/137) which are limited to V<11. This is the magnitude at which Tycho-2 is 99% complete. The latter is based on the same procedure but limited to G=20.7, which is the expected limiting magnitude of Gaia. For the Milky Way prior, the parameters are described in the paper. We report the mode of the posterior PDF, the median, the 90% credible interval, and a standard deviation in distance which are calculated by scaling the 90% into 68.3%. The Cepheids data used for the validation of the results are included here as well. They are taken from Groenewegen (2013, Cat. J/A+A/550/A70) and cross-matched with Hipparcos and/or Tycho by making a Simbad query of each Cepheids and finding the corresponding Hipparcos and/or Tyho identifier. The distances are inferred either by neglecting the systematic uncertainties of 0.3mas (Gaia Collaboration et al., 2016, Cat. I/337) for reasons described in the paper, or by adding a systematic uncertainties of 0.3mas in quadrature with the random parallax uncertainties. We provide both results here. (4 data files).

Uncertainty and Decision Making

DTIC Science & Technology

1979-09-01

higher productivity and satisfaction than a nonsupportive co-worker and enriched tasks affected attitudes but not performance . The greatest uncertainty...leadership V- 4••,,. • , -9- style, goals, and task HLructure) on psychological uncertainty and the resultant effect on performance and satisfaction . People...turn related to satisfaction and performance . In general, a stric- turing leadership style, specific goals and a structured task result in lower unce

Managing Uncertainty during a Corporate Acquisition: A Longitudinal Study of Communication During an Airline Acquisition

ERIC Educational Resources Information Center

Kramer, Michael W.; Dougherty, Debbie S.; Pierce, Tamyra A.

2004-01-01

This study examined pilots' (N at T1 = 140; N at T2 = 126; N at T3 = 104) reactions to communication and uncertainty during the acquisition of their airline by another airline. Quantitative results indicate that communication helped to reduce uncertainty and was predictive of affective responses to the acquisition. However, contrary to…

Plural Forms of Evidence and Uncertainty in Environmental Health: A Comparison of Two Chinese Cases

ERIC Educational Resources Information Center

Lora-Wainwright, Anna

2013-01-01

This paper examines the plural forms of evidence of harm presented by the residents of two Chinese villages affected by severe pollution. Conversely, it scrutinises how and why the antonym to evidence--uncertainty--is emphasised and with what effects. It argues that their uncertainty surrounding environmental health harm is a result of the…

Evaluating critical uncertainty thresholds in a spatial model of forest pest invasion risk

Treesearch

Frank H. Koch; Denys Yemshanov; Daniel W. McKenney; William D. Smith

2009-01-01

Pest risk maps can provide useful decision support in invasive species management, but most do not adequately consider the uncertainty associated with predicted risk values. This study explores how increased uncertainty in a risk model’s numeric assumptions might affect the resultant risk map. We used a spatial stochastic model, integrating components for...

The effects of stochastic demand and expense preference behaviour on public hospital costs and excess capacity.

PubMed

Lovell, C A Knox; Rodríguez-Alvarez, Ana; Wall, Alan

2009-02-01

The literature to date on the effect of demand uncertainty on public hospital costs and excess capacity has not taken into account the role of expense preference behaviour. Similarly, the research on expense preference behaviour has not taken demand uncertainty into account. In this paper, we argue that both demand uncertainty and expense preference behaviour may affect public hospital costs and excess capacity and that ignoring either of these effects may lead to biased parameter estimates and misleading inference. To show this, we extend the analysis of Rodríguez-Alvarez and Lovell (Health Econ. 2004; 13: 157-169) by incorporating demand uncertainty into the technology to account for the hospital activity of providing standby capacity or insurance against the unexpected demand. We find that demand uncertainty in Spanish public hospitals affects hospital production decisions and increases costs. Our results also show that overcapitalization in these hospitals can be explained by hospitals providing insurance demand when faced with demand uncertainty. We also find evidence of expense preference behaviour. We conclude that both stochastic demand and expense preference behaviour should be taken into account when analysing hospital costs and production. Copyright (c) 2008 John Wiley & Sons, Ltd.

Hierarchical multi-scale approach to validation and uncertainty quantification of hyper-spectral image modeling

NASA Astrophysics Data System (ADS)

Engel, Dave W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David L.; Thompson, Sandra E.

2016-05-01

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

Numerical modelling of instantaneous plate tectonics

NASA Technical Reports Server (NTRS)

Minster, J. B.; Haines, E.; Jordan, T. H.; Molnar, P.

1974-01-01

Assuming lithospheric plates to be rigid, 68 spreading rates, 62 fracture zones trends, and 106 earthquake slip vectors are systematically inverted to obtain a self-consistent model of instantaneous relative motions for eleven major plates. The inverse problem is linearized and solved iteratively by a maximum-likelihood procedure. Because the uncertainties in the data are small, Gaussian statistics are shown to be adequate. The use of a linear theory permits (1) the calculation of the uncertainties in the various angular velocity vectors caused by uncertainties in the data, and (2) quantitative examination of the distribution of information within the data set. The existence of a self-consistent model satisfying all the data is strong justification of the rigid plate assumption. Slow movement between North and South America is shown to be resolvable.

A Probabilistic Framework for Quantifying Mixed Uncertainties in Cyber Attacker Payoffs

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

Chatterjee, Samrat; Tipireddy, Ramakrishna; Oster, Matthew R.

Quantification and propagation of uncertainties in cyber attacker payoffs is a key aspect within multiplayer, stochastic security games. These payoffs may represent penalties or rewards associated with player actions and are subject to various sources of uncertainty, including: (1) cyber-system state, (2) attacker type, (3) choice of player actions, and (4) cyber-system state transitions over time. Past research has primarily focused on representing defender beliefs about attacker payoffs as point utility estimates. More recently, within the physical security domain, attacker payoff uncertainties have been represented as Uniform and Gaussian probability distributions, and mathematical intervals. For cyber-systems, probability distributions may helpmore » address statistical (aleatory) uncertainties where the defender may assume inherent variability or randomness in the factors contributing to the attacker payoffs. However, systematic (epistemic) uncertainties may exist, where the defender may not have sufficient knowledge or there is insufficient information about the attacker’s payoff generation mechanism. Such epistemic uncertainties are more suitably represented as generalizations of probability boxes. This paper explores the mathematical treatment of such mixed payoff uncertainties. A conditional probabilistic reasoning approach is adopted to organize the dependencies between a cyber-system’s state, attacker type, player actions, and state transitions. This also enables the application of probabilistic theories to propagate various uncertainties in the attacker payoffs. An example implementation of this probabilistic framework and resulting attacker payoff distributions are discussed. A goal of this paper is also to highlight this uncertainty quantification problem space to the cyber security research community and encourage further advancements in this area.« less

Luminosity determination in pp collisions at $$\\sqrt{s} = 7$$ TeV using the ATLAS detector at the LHC

DOE PAGES

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

2011-04-27

Measurements of luminosity obtained using the ATLAS detector during early running of the Large Hadron Collider (LHC) at √s = 7 TeV are presented. The luminosity is independently determined using several detectors and multiple algorithms, each having different acceptances, systematic uncertainties and sensitivity to background. The ratios of the luminosities obtained from these methods are monitored as a function of time and of μ, the average number of inelastic interactions per bunch crossing. Residual time- and μ-dependence between the methods is less than 2% for 0 < μ < 2.5. Absolute luminosity calibrations, performed using beam separation scans, have amore » common systematic uncertainty of ±11%, dominated by the measurement of the LHC beam currents. After calibration, the luminosities obtained from the different methods differ by at most ±2%. The visible cross sections measured using the beam scans are compared to predictions obtained with the PYTHIA and PHOJET event generators and the ATLAS detector simulation.« less

Decorrelated jet substructure tagging using adversarial neural networks

NASA Astrophysics Data System (ADS)

Shimmin, Chase; Sadowski, Peter; Baldi, Pierre; Weik, Edison; Whiteson, Daniel; Goul, Edward; Søgaard, Andreas

2017-10-01

We describe a strategy for constructing a neural network jet substructure tagger which powerfully discriminates boosted decay signals while remaining largely uncorrelated with the jet mass. This reduces the impact of systematic uncertainties in background modeling while enhancing signal purity, resulting in improved discovery significance relative to existing taggers. The network is trained using an adversarial strategy, resulting in a tagger that learns to balance classification accuracy with decorrelation. As a benchmark scenario, we consider the case where large-radius jets originating from a boosted resonance decay are discriminated from a background of nonresonant quark and gluon jets. We show that in the presence of systematic uncertainties on the background rate, our adversarially trained, decorrelated tagger considerably outperforms a conventionally trained neural network, despite having a slightly worse signal-background separation power. We generalize the adversarial training technique to include a parametric dependence on the signal hypothesis, training a single network that provides optimized, interpolatable decorrelated jet tagging across a continuous range of hypothetical resonance masses, after training on discrete choices of the signal mass.

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

NASA Astrophysics Data System (ADS)

Brogniez, Helene; English, Stephen; Mahfouf, Jean-Francois; Behrendt, Andreas; Berg, Wesley; Boukabara, Sid; Buehler, Stefan Alexander; Chambon, Philippe; Gambacorta, Antonia; Geer, Alan; Ingram, William; Kursinski, E. Robert; Matricardi, Marco; Odintsova, Tatyana A.; Payne, Vivienne H.; Thorne, Peter W.; Tretyakov, Mikhail Yu.; Wang, Junhong

2016-05-01

Several recent studies have observed systematic differences between measurements in the 183.31 GHz water vapor line by space-borne sounders and calculations using radiative transfer models, with inputs from either radiosondes (radiosonde observations, RAOBs) or short-range forecasts by numerical weather prediction (NWP) models. This paper discusses all the relevant categories of observation-based or model-based data, quantifies their uncertainties and separates biases that could be common to all causes from those attributable to a particular cause. Reference observations from radiosondes, Global Navigation Satellite System (GNSS) receivers, differential absorption lidar (DIAL) and Raman lidar are thus overviewed. Biases arising from their calibration procedures, NWP models and data assimilation, instrument biases and radiative transfer models (both the models themselves and the underlying spectroscopy) are presented and discussed. Although presently no single process in the comparisons seems capable of explaining the observed structure of bias, recommendations are made in order to better understand the causes.

Precision Compton polarimetry for the QWeak experiment at Jefferson Lab

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

Wouter Deconinck

2011-10-01

The Q Weak experiment, scheduled to run in 2010-2012 in Hall C at Jefferson Lab, will measure the parity-violating asymmetry in elastic electron-proton scattering at 1.1 GeV to determine the weak charge of the proton, Q{sub Weak}{sup p} = 1 - 4 sin{sup 2} {theta}{sub W}. The dominant experimental systematic uncertainty will be the knowledge of the electron beam polarization. With a new Compton polarimeter we aim to measure the beam polarization with a statistical precision of 1% in one hour and a systematic uncertainty of 1%. A low-gain Fabry-Perot cavity laser system provides the circularly polarized photons. The scatteredmore » electrons are detected in radiation-hard diamond strip detectors, and form the basis for a coincidence trigger using distributed logic boards. The photon detector uses a fast, undoped CsI crystal with simultaneous sampling and integrating read-out. Coincident events are used to cross-calibrate the photon and electron detectors.« less

An update on the analysis of the Princeton 19Ne beta asymmetry measurement

NASA Astrophysics Data System (ADS)

Combs, Dustin; Calaprice, Frank; Jones, Gordon; Pattie, Robert; Young, Albert

2013-10-01

We report on the progress of a new analysis of the 1994 19Ne beta asymmetry measurement conducted at Princeton University. In this experiment, a beam of 19Ne atoms were polarized with a Stern-Gerlach magnet and then entered a thin-walled mylar cell through a slit fabricated from a piece of micro channel plate. A pair of Si(Li) detectors at either end of the apparatus were aligned with the direction of spin polarization (one parallel and one anti-parallel to the spin of the 19Ne) and detected positrons from the decays. The difference in the rate in the two detectors was used to calculate the asymmetry. A new analysis procedure has been undertaken using the Monte Carlo package PENELOPE with the goal of determining the systematic uncertainty due to positrons scattering from the face of the detectors causing the incorrect reconstruction of the initial direction of the positron momentum. This was a leading cause of systematic uncertainty in the experiment in 1994.

Cosmology with EMSS Clusters of Galaxies

NASA Technical Reports Server (NTRS)

Donahue, Megan; Voit, G. Mark

1999-01-01

We use ASCA observations of the Extended Medium Sensitivity Survey sample of clusters of galaxies to construct the first z = 0.5 - 0.8 cluster temperature function. This distant cluster temperature function, when compared to local z approximately 0 and to a similar moderate redshift (z = 0.3 - 0.4) temperature function strongly constrains the matter density of the universe. Best fits to the distributions of temperatures and redshifts of these cluster samples results in Omega(sub M) = 0.45 +/- 0.1 if Lambda = 0 and Omega = 0.27 +/- 0.1 if Lambda + Omega(sub M) = 1. The uncertainties are 1sigma statistical. We examine the systematics of our approach and find that systematics, stemming mainly from model assumptions and not measurement errors, are about the same size as the statistical uncertainty +/- 0.1. In this poster proceedings, we clarify the issue of a8 as reported in our paper Donahue & Voit (1999), since this was a matter of discussion at the meeting.

Tranexamic acid in epistaxis: a systematic review.

PubMed

Kamhieh, Y; Fox, H

2016-12-01

The role of tranexamic acid in the management of epistaxis remains unclear. There is uncertainty about its safety and about the contraindications for its use. We performed a systematic review of the use of systemic and topical tranexamic acid in epistaxis and a comparative review of its use in other specialties. This review assesses and summarises the existing evidence for the efficacy and safety of tranexamic acid in the management of epistaxis. Systematic review. MEDLINE and EMBASE were searched for 'epistaxis' and equivalent MESH terms, combined with the Boolean operator 'OR' and 'tranexamic acid'. The Cochrane library and society guidelines were reviewed for evidence regarding the use of tranexamic acid in other specialties. All five relevant RCTs were included in the review and were evaluated according to the recommendations of the Cochrane Handbook for Systematic Reviews. Three RCTS pertained to spontaneous epistaxis; of these, one trial found no benefit of oral tranexamic acid in acute epistaxis, one trial found no significant benefit of topical tranexamic acid, but the largest of the trials showed significant benefit of topical tranexamic acid in acute epistaxis management. Two RCTs examined oral tranexamic acid for prophylaxis of recurrent epistaxes in patients with hereditary haemorrhagic telangiectasia; both showed significant reduction in severity and frequency. Tranexamic acid, as a WHO 'essential medicine', is a powerful, readily available tool, the use of which in epistaxis has been limited by uncertainty over its efficacy and its safety profile. This systematic review summarises the existing evidence and extrapolates from the wealth of data for other specialties to address the clinical question - does TXA have a role in epistaxis management? © 2016 John Wiley & Sons Ltd.

Decision analysis of shoreline protection under climate change uncertainty

NASA Astrophysics Data System (ADS)

Chao, Philip T.; Hobbs, Benjamin F.

1997-04-01

If global warming occurs, it could significantly affect water resource distribution and availability. Yet it is unclear whether the prospect of such change is relevant to water resources management decisions being made today. We model a shoreline protection decision problem with a stochastic dynamic program (SDP) to determine whether consideration of the possibility of climate change would alter the decision. Three questions are addressed with the SDP: (l) How important is climate change compared to other uncertainties?, (2) What is the economic loss if climate change uncertainty is ignored?, and (3) How does belief in climate change affect the timing of the decision? In the case study, sensitivity analysis shows that uncertainty in real discount rates has a stronger effect upon the decision than belief in climate change. Nevertheless, a strong belief in climate change makes the shoreline protection project less attractive and often alters the decision to build it.

Faith-adapted psychological therapies for depression and anxiety: Systematic review and meta-analysis.

PubMed

Anderson, Naomi; Heywood-Everett, Suzanne; Siddiqi, Najma; Wright, Judy; Meredith, Jodi; McMillan, Dean

2015-05-01

Incorporating faith (religious or spiritual) perspectives into psychological treatments has attracted significant interest in recent years. However, previous suggestion that good psychiatric care should include spiritual components has provoked controversy. To try to address ongoing uncertainty in this field we present a systematic review and meta-analysis to assess the efficacy of faith-based adaptations of bona fide psychological therapies for depression or anxiety. A systematic review and meta-analysis of randomised controlled trials were performed. The literature search yielded 2274 citations of which 16 studies were eligible for inclusion. All studies used cognitive or cognitive behavioural models as the basis for their faith-adapted treatment (F-CBT). We identified statistically significant benefits of using F-CBT. However, quality assessment using the Cochrane risk of bias tool revealed methodological limitations that reduce the apparent strength of these findings. Whilst the effect sizes identified here were statistically significant, there were relatively a few relevant RCTs available, and those included were typically small and susceptible to significant biases. Biases associated with researcher or therapist allegiance were identified as a particular concern. Despite some suggestion that faith-adapted CBT may out-perform both standard CBT and control conditions (waiting list or "treatment as usual"), the effect sizes identified in this meta-analysis must be considered in the light of the substantial methodological limitations that affect the primary research data. Before firm recommendations about the value of faith-adapted treatments can be made, further large-scale, rigorously performed trials are required. Copyright © 2015 Elsevier B.V. All rights reserved.

Particle content, radio-galaxy morphology, and jet power: all radio-loud AGN are not equal

NASA Astrophysics Data System (ADS)

Croston, J. H.; Ineson, J.; Hardcastle, M. J.

2018-05-01

Ongoing and future radio surveys aim to trace the evolution of black hole growth and feedback from active galactic nuclei (AGNs) throughout cosmic time; however, there remain major uncertainties in translating radio luminosity functions into a reliable assessment of the energy input as a function of galaxy and/or dark matter halo mass. A crucial and long-standing problem is the composition of the radio-lobe plasma that traces AGN jet activity. In this paper, we carry out a systematic comparison of the plasma conditions in Fanaroff & Riley class I and II radio galaxies to demonstrate conclusively that their internal composition is systematically different. This difference is best explained by the presence of an energetically dominant proton population in the FRI, but not the FRII radio galaxies. We show that, as expected from this systematic difference in particle content, radio morphology also affects the jet-power/radio-luminosity relationship, with FRII radio galaxies having a significantly lower ratio of jet power to radio luminosity than the FRI cluster radio sources used to derive jet-power scaling relations via X-ray cavity measurements. Finally, we also demonstrate conclusively that lobe composition is unconnected to accretion mode (optical excitation class): the internal conditions of low- and high-excitation FRII radio lobes are indistinguishable. We conclude that inferences of population-wide AGN impact require careful assessment of the contribution of different jet subclasses, particularly given the increased diversity of jet evolutionary states expected to be present in deep, low-frequency radio surveys such as the LOFAR Two-Metre Sky Survey.

Anxiety, depression, and health-related quality of life in heterozygous familial hypercholesterolemia: A systematic review and meta-analysis.

PubMed

Akioyamen, Leo E; Genest, Jacques; Shan, Shubham D; Inibhunu, Happy; Chu, Anna; Tu, Jack V

2018-06-01

Heterozygous familial hypercholesterolemia (FH) is a common genetic disease predisposing affected individuals to a high risk of cardiovascular disease. Yet, considerable uncertainty exists regarding its impact on psychosocial wellbeing. We performed a systematic review and meta-analysis of the association between FH and symptoms of anxiety and depression, and health-related quality of life (HRQL). We searched MEDLINE, EMBASE, Global Health, the Cochrane Library, PsycINFO, and PubMed for peer-reviewed literature published in English between January 1, 1990 and January 1, 2018. Quantitative and qualitative studies were eligible if they included patients with confirmed FH and evaluated its association with symptoms of anxiety or depression, or HRQL. We performed a narrative synthesis of studies, including thematic analysis of qualitative studies, and where data permitted, random-effects meta-analysis reporting standardized mean differences (SMD) and 95% confidence intervals. We found 10 eligible studies measuring HRQL, depression and anxiety. Random-effects meta-analysis of 4 (n = 4293) and 5 studies (n = 5098), respectively, showed that patients with FH had slightly lower symptoms of anxiety (SMD: -0.29 [95% CI: -0.53, -0.04]) and mental HRQL (SMD: -0.10 [95% -0.20, -0.00]) relative to general population controls. No significant differences existed in depressive symptoms (SMD: 0.04 [95% CI: -0.12, 0.19]) or physical HRQL scores (SMD: 0.02 [95% CI: -0.09, 0.12]). Our systematic review suggests that patients with FH may report small but measurable differences in anxiety symptoms and mental HRQL. Copyright © 2018 Elsevier Inc. All rights reserved.

Computation and visualization of uncertainty in surgical navigation.

PubMed

Simpson, Amber L; Ma, Burton; Vasarhelyi, Edward M; Borschneck, Dan P; Ellis, Randy E; James Stewart, A

2014-09-01

Surgical displays do not show uncertainty information with respect to the position and orientation of instruments. Data is presented as though it were perfect; surgeons unaware of this uncertainty could make critical navigational mistakes. The propagation of uncertainty to the tip of a surgical instrument is described and a novel uncertainty visualization method is proposed. An extensive study with surgeons has examined the effect of uncertainty visualization on surgical performance with pedicle screw insertion, a procedure highly sensitive to uncertain data. It is shown that surgical performance (time to insert screw, degree of breach of pedicle, and rotation error) is not impeded by the additional cognitive burden imposed by uncertainty visualization. Uncertainty can be computed in real time and visualized without adversely affecting surgical performance, and the best method of uncertainty visualization may depend upon the type of navigation display. Copyright © 2013 John Wiley & Sons, Ltd.

Mapping extragalactic dark matter annihilation with galaxy surveys: A systematic study of stacked group searches

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

Lisanti, Mariangela; Mishra-Sharma, Siddharth; Rodd, Nicholas L.

Dark matter in the halos surrounding galaxy groups and clusters can annihilate to high-energy photons. Recent advancements in the construction of galaxy group catalogs provide many thousands of potential extragalactic targets for dark matter. In this paper, we outline a procedure to infer the dark matter signal associated with a given galaxy group. Applying this procedure to a catalog of sources, one can create a full-sky map of the brightest extragalactic dark matter targets in the nearby Universe (z≲0.03), supplementing sources of dark matter annihilation from within the local group. As with searches for dark matter in dwarf galaxies, thesemore » extragalactic targets can be stacked together to enhance the signals associated with dark matter. We validate this procedure on mock Fermi gamma-ray data sets using a galaxy catalog constructed from the DarkSky N-body cosmological simulation and demonstrate that the limits are robust, at O(1) levels, to systematic uncertainties on halo mass and concentration. We also quantify other sources of systematic uncertainty arising from the analysis and modeling assumptions. Lastly, our results suggest that a stacking analysis using galaxy group catalogs provides a powerful opportunity to discover extragalactic dark matter and complements existing studies of Milky Way dwarf galaxies.« less

Mapping extragalactic dark matter annihilation with galaxy surveys: A systematic study of stacked group searches

NASA Astrophysics Data System (ADS)

Lisanti, Mariangela; Mishra-Sharma, Siddharth; Rodd, Nicholas L.; Safdi, Benjamin R.; Wechsler, Risa H.

2018-03-01

Dark matter in the halos surrounding galaxy groups and clusters can annihilate to high-energy photons. Recent advancements in the construction of galaxy group catalogs provide many thousands of potential extragalactic targets for dark matter. In this paper, we outline a procedure to infer the dark matter signal associated with a given galaxy group. Applying this procedure to a catalog of sources, one can create a full-sky map of the brightest extragalactic dark matter targets in the nearby Universe (z ≲0.03 ), supplementing sources of dark matter annihilation from within the local group. As with searches for dark matter in dwarf galaxies, these extragalactic targets can be stacked together to enhance the signals associated with dark matter. We validate this procedure on mock Fermi gamma-ray data sets using a galaxy catalog constructed from the DarkSky N -body cosmological simulation and demonstrate that the limits are robust, at O (1 ) levels, to systematic uncertainties on halo mass and concentration. We also quantify other sources of systematic uncertainty arising from the analysis and modeling assumptions. Our results suggest that a stacking analysis using galaxy group catalogs provides a powerful opportunity to discover extragalactic dark matter and complements existing studies of Milky Way dwarf galaxies.

Photoneutron cross sections for 59Co : Systematic uncertainties of data from various experiments

NASA Astrophysics Data System (ADS)

Varlamov, V. V.; Davydov, A. I.; Ishkhanov, B. S.

2017-09-01

Data on partial photoneutron reaction cross sections (γ ,1n), (γ ,2n), and (γ ,3n) for 59Co obtained in two experiments carried out at Livermore (USA) were analyzed. The sources of radiation in both experiments were the monoenergetic photon beams from the annihilation in flight of relativistic positrons. The total yield was sorted by the neutron multiplicity, taking into account the difference in the neutron energy spectra for different multiplicity. The two quoted studies differ in the method of determining the neutron. Significant systematic disagreements between the results of the two experiments exist. They are considered to be caused by large systematic uncertainties in partial cross sections, since they do not satisfy physical criteria for reliability of the data. To obtain reliable cross sections of partial and total photoneutron reactions a new method combining experimental data and theoretical evaluation was used. It is based on the experimental neutron yield cross section which is rather independent of neutron multiplicity and the transitional neutron multiplicity functions of the combined photonucleon reaction model (CPNRM). The model transitional multiplicity functions were used for the decomposition of the neutron yield cross section into the contributions of partial reactions. The results of the new evaluation noticeably differ from the partial cross sections obtained in the two experimental studies are under discussion.

The impact of the orbital decay of the LAGEOS satellites on the frame-dragging tests

NASA Astrophysics Data System (ADS)

Iorio, Lorenzo

2016-01-01

The laser-tracked geodetic satellites LAGEOS, LAGEOS II and LARES are currently employed, among other things, to measure the general relativistic Lense-Thirring effect in the gravitomagnetic field of the spinning Earth with the hope of providing a more accurate test of such a prediction of the Einstein's theory of gravitation than the existing ones. The secular decay a ˙ of the semimajor axes a of such spacecrafts, recently measured in an independent way to a σȧ ≈ 0.1-0.01 m yr-1 accuracy level, may indirectly impact the proposed relativistic experiment through its connection with the classical orbital precessions induced by the Earth's oblateness J2 . Indeed, the systematic bias due to the current measurement errors σȧ is of the same order of magnitude of, or even larger than, the expected relativistic signal itself; moreover, it grows linearly with the time span T of the analysis. Therefore, the parameter-fitting algorithms must be properly updated in order to suitably cope with such a new source of systematic uncertainty. Otherwise, an improvement of one-two orders of magnitude in measuring the orbital decay of the satellites of the LAGEOS family would be required to reduce this source of systematic uncertainty to a percent fraction of the Lense-Thirring signature.

Comparison of two stochastic techniques for reliable urban runoff prediction by modeling systematic errors

NASA Astrophysics Data System (ADS)

Del Giudice, Dario; Löwe, Roland; Madsen, Henrik; Mikkelsen, Peter Steen; Rieckermann, Jörg

2015-07-01

In urban rainfall-runoff, commonly applied statistical techniques for uncertainty quantification mostly ignore systematic output errors originating from simplified models and erroneous inputs. Consequently, the resulting predictive uncertainty is often unreliable. Our objective is to present two approaches which use stochastic processes to describe systematic deviations and to discuss their advantages and drawbacks for urban drainage modeling. The two methodologies are an external bias description (EBD) and an internal noise description (IND, also known as stochastic gray-box modeling). They emerge from different fields and have not yet been compared in environmental modeling. To compare the two approaches, we develop a unifying terminology, evaluate them theoretically, and apply them to conceptual rainfall-runoff modeling in the same drainage system. Our results show that both approaches can provide probabilistic predictions of wastewater discharge in a similarly reliable way, both for periods ranging from a few hours up to more than 1 week ahead of time. The EBD produces more accurate predictions on long horizons but relies on computationally heavy MCMC routines for parameter inferences. These properties make it more suitable for off-line applications. The IND can help in diagnosing the causes of output errors and is computationally inexpensive. It produces best results on short forecast horizons that are typical for online applications.

Mapping extragalactic dark matter annihilation with galaxy surveys: A systematic study of stacked group searches

DOE PAGES

Lisanti, Mariangela; Mishra-Sharma, Siddharth; Rodd, Nicholas L.; ...

2018-03-09

Dark matter in the halos surrounding galaxy groups and clusters can annihilate to high-energy photons. Recent advancements in the construction of galaxy group catalogs provide many thousands of potential extragalactic targets for dark matter. In this paper, we outline a procedure to infer the dark matter signal associated with a given galaxy group. Applying this procedure to a catalog of sources, one can create a full-sky map of the brightest extragalactic dark matter targets in the nearby Universe (z≲0.03), supplementing sources of dark matter annihilation from within the local group. As with searches for dark matter in dwarf galaxies, thesemore » extragalactic targets can be stacked together to enhance the signals associated with dark matter. We validate this procedure on mock Fermi gamma-ray data sets using a galaxy catalog constructed from the DarkSky N-body cosmological simulation and demonstrate that the limits are robust, at O(1) levels, to systematic uncertainties on halo mass and concentration. We also quantify other sources of systematic uncertainty arising from the analysis and modeling assumptions. Lastly, our results suggest that a stacking analysis using galaxy group catalogs provides a powerful opportunity to discover extragalactic dark matter and complements existing studies of Milky Way dwarf galaxies.« less

Determination of electron beam polarization using electron detector in Compton polarimeter with less than 1% statistical and systematic uncertainty

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

Narayan, Amrendra

2015-05-01

The Q-weak experiment aims to measure the weak charge of proton with a precision of 4.2%. The proposed precision on weak charge required a 2.5% measurement of the parity violating asymmetry in elastic electron - proton scattering. Polarimetry was the largest experimental contribution to this uncertainty and a new Compton polarimeter was installed in Hall C at Jefferson Lab to make the goal achievable. In this polarimeter the electron beam collides with green laser light in a low gain Fabry-Perot Cavity; the scattered electrons are detected in 4 planes of a novel diamond micro strip detector while the back scatteredmore » photons are detected in lead tungstate crystals. This diamond micro-strip detector is the first such device to be used as a tracking detector in a nuclear and particle physics experiment. The diamond detectors are read out using custom built electronic modules that include a preamplifier, a pulse shaping amplifier and a discriminator for each detector micro-strip. We use field programmable gate array based general purpose logic modules for event selection and histogramming. Extensive Monte Carlo simulations and data acquisition simulations were performed to estimate the systematic uncertainties. Additionally, the Moller and Compton polarimeters were cross calibrated at low electron beam currents using a series of interleaved measurements. In this dissertation, we describe all the subsystems of the Compton polarimeter with emphasis on the electron detector. We focus on the FPGA based data acquisition system built by the author and the data analysis methods implemented by the author. The simulations of the data acquisition and the polarimeter that helped rigorously establish the systematic uncertainties of the polarimeter are also elaborated, resulting in the first sub 1% measurement of low energy (?1 GeV) electron beam polarization with a Compton electron detector. We have demonstrated that diamond based micro-strip detectors can be used for tracking in a high radiation environment and it has enabled us to achieve the desired precision in the measurement of the electron beam polarization which in turn has allowed the most precise determination of the weak charge of the proton.« less

Phobos laser ranging: Numerical Geodesy experiments for Martian system science

NASA Astrophysics Data System (ADS)

Dirkx, D.; Vermeersen, L. L. A.; Noomen, R.; Visser, P. N. A. M.

2014-09-01

Laser ranging is emerging as a technology for use over (inter)planetary distances, having the advantage of high (mm-cm) precision and accuracy and low mass and power consumption. We have performed numerical simulations to assess the science return in terms of geodetic observables of a hypothetical Phobos lander performing active two-way laser ranging with Earth-based stations. We focus our analysis on the estimation of Phobos and Mars gravitational, tidal and rotational parameters. We explicitly include systematic error sources in addition to uncorrelated random observation errors. This is achieved through the use of consider covariance parameters, specifically the ground station position and observation biases. Uncertainties for the consider parameters are set at 5 mm and at 1 mm for the Gaussian uncorrelated observation noise (for an observation integration time of 60 s). We perform the analysis for a mission duration up to 5 years. It is shown that a Phobos Laser Ranging (PLR) can contribute to a better understanding of the Martian system, opening the possibility for improved determination of a variety of physical parameters of Mars and Phobos. The simulations show that the mission concept is especially suited for estimating Mars tidal deformation parameters, estimating degree 2 Love numbers with absolute uncertainties at the 10-2 to 10-4 level after 1 and 4 years, respectively and providing separate estimates for the Martian quality factors at Sun and Phobos-forced frequencies. The estimation of Phobos libration amplitudes and gravity field coefficients provides an estimate of Phobos' relative equatorial and polar moments of inertia with an absolute uncertainty of 10-4 and 10-7, respectively, after 1 year. The observation of Phobos tidal deformation will be able to differentiate between a rubble pile and monolithic interior within 2 years. For all parameters, systematic errors have a much stronger influence (per unit uncertainty) than the uncorrelated Gaussian observation noise. This indicates the need for the inclusion of systematic errors in simulation studies and special attention to the mitigation of these errors in mission and system design.

Determination of electron beam polarization using electron detector in Compton polarimeter with less than 1% statistical and systematic uncertainty

NASA Astrophysics Data System (ADS)

Narayan, Amrendra

The Q-weak experiment aims to measure the weak charge of proton with a precision of 4.2%. The proposed precision on weak charge required a 2.5% measurement of the parity violating asymmetry in elastic electron - proton scattering. Polarimetry was the largest experimental contribution to this uncertainty and a new Compton polarimeter was installed in Hall C at Jefferson Lab to make the goal achievable. In this polarimeter the electron beam collides with green laser light in a low gain Fabry-Perot Cavity; the scattered electrons are detected in 4 planes of a novel diamond micro strip detector while the back scattered photons are detected in lead tungstate crystals. This diamond micro-strip detector is the first such device to be used as a tracking detector in a nuclear and particle physics experiment. The diamond detectors are read out using custom built electronic modules that include a preamplifier, a pulse shaping amplifier and a discriminator for each detector micro-strip. We use field programmable gate array based general purpose logic modules for event selection and histogramming. Extensive Monte Carlo simulations and data acquisition simulations were performed to estimate the systematic uncertainties. Additionally, the Moller and Compton polarimeters were cross calibrated at low electron beam currents using a series of interleaved measurements. In this dissertation, we describe all the subsystems of the Compton polarimeter with emphasis on the electron detector. We focus on the FPGA based data acquisition system built by the author and the data analysis methods implemented by the author. The simulations of the data acquisition and the polarimeter that helped rigorously establish the systematic uncertainties of the polarimeter are also elaborated, resulting in the first sub 1% measurement of low energy (~1GeV) electron beam polarization with a Compton electron detector. We have demonstrated that diamond based micro-strip detectors can be used for tracking in a high radiation environment and it has enabled us to achieve the desired precision in the measurement of the electron beam polarization which in turn has allowed the most precise determination of the weak charge of the proton.

A unified approach for squeal instability analysis of disc brakes with two types of random-fuzzy uncertainties

NASA Astrophysics Data System (ADS)

Lü, Hui; Shangguan, Wen-Bin; Yu, Dejie

2017-09-01

Automotive brake systems are always subjected to various types of uncertainties and two types of random-fuzzy uncertainties may exist in the brakes. In this paper, a unified approach is proposed for squeal instability analysis of disc brakes with two types of random-fuzzy uncertainties. In the proposed approach, two uncertainty analysis models with mixed variables are introduced to model the random-fuzzy uncertainties. The first one is the random and fuzzy model, in which random variables and fuzzy variables exist simultaneously and independently. The second one is the fuzzy random model, in which uncertain parameters are all treated as random variables while their distribution parameters are expressed as fuzzy numbers. Firstly, the fuzziness is discretized by using α-cut technique and the two uncertainty analysis models are simplified into random-interval models. Afterwards, by temporarily neglecting interval uncertainties, the random-interval models are degraded into random models, in which the expectations, variances, reliability indexes and reliability probabilities of system stability functions are calculated. And then, by reconsidering the interval uncertainties, the bounds of the expectations, variances, reliability indexes and reliability probabilities are computed based on Taylor series expansion. Finally, by recomposing the analysis results at each α-cut level, the fuzzy reliability indexes and probabilities can be obtained, by which the brake squeal instability can be evaluated. The proposed approach gives a general framework to deal with both types of random-fuzzy uncertainties that may exist in the brakes and its effectiveness is demonstrated by numerical examples. It will be a valuable supplement to the systematic study of brake squeal considering uncertainty.

Relative Gains, Losses, and Reference Points in Probabilistic Choice in Rats

PubMed Central

Marshall, Andrew T.; Kirkpatrick, Kimberly

2015-01-01

Theoretical reference points have been proposed to differentiate probabilistic gains from probabilistic losses in humans, but such a phenomenon in non-human animals has yet to be thoroughly elucidated. Three experiments evaluated the effect of reward magnitude on probabilistic choice in rats, seeking to determine reference point use by examining the effect of previous outcome magnitude(s) on subsequent choice behavior. Rats were trained to choose between an outcome that always delivered reward (low-uncertainty choice) and one that probabilistically delivered reward (high-uncertainty). The probability of high-uncertainty outcome receipt and the magnitudes of low-uncertainty and high-uncertainty outcomes were manipulated within and between experiments. Both the low- and high-uncertainty outcomes involved variable reward magnitudes, so that either a smaller or larger magnitude was probabilistically delivered, as well as reward omission following high-uncertainty choices. In Experiments 1 and 2, the between groups factor was the magnitude of the high-uncertainty-smaller (H-S) and high-uncertainty-larger (H-L) outcome, respectively. The H-S magnitude manipulation differentiated the groups, while the H-L magnitude manipulation did not. Experiment 3 showed that manipulating the probability of differential losses as well as the expected value of the low-uncertainty choice produced systematic effects on choice behavior. The results suggest that the reference point for probabilistic gains and losses was the expected value of the low-uncertainty choice. Current theories of probabilistic choice behavior have difficulty accounting for the present results, so an integrated theoretical framework is proposed. Overall, the present results have implications for understanding individual differences and corresponding underlying mechanisms of probabilistic choice behavior. PMID:25658448

Impacts of uncertainties in weather and streamflow observations in calibration and evaluation of an elevation distributed HBV-model

NASA Astrophysics Data System (ADS)

Engeland, K.; Steinsland, I.; Petersen-Øverleir, A.; Johansen, S.

2012-04-01

The aim of this study is to assess the uncertainties in streamflow simulations when uncertainties in both observed inputs (precipitation and temperature) and streamflow observations used in the calibration of the hydrological model are explicitly accounted for. To achieve this goal we applied the elevation distributed HBV model operating on daily time steps to a small catchment in high elevation in Southern Norway where the seasonal snow cover is important. The uncertainties in precipitation inputs were quantified using conditional simulation. This procedure accounts for the uncertainty related to the density of the precipitation network, but neglects uncertainties related to measurement bias/errors and eventual elevation gradients in precipitation. The uncertainties in temperature inputs were quantified using a Bayesian temperature interpolation procedure where the temperature lapse rate is re-estimated every day. The uncertainty in the lapse rate was accounted for whereas the sampling uncertainty related to network density was neglected. For every day a random sample of precipitation and temperature inputs were drawn to be applied as inputs to the hydrologic model. The uncertainties in observed streamflow were assessed based on the uncertainties in the rating curve model. A Bayesian procedure was applied to estimate the probability for rating curve models with 1 to 3 segments and the uncertainties in their parameters. This method neglects uncertainties related to errors in observed water levels. Note that one rating curve was drawn to make one realisation of a whole time series of streamflow, thus the rating curve errors lead to a systematic bias in the streamflow observations. All these uncertainty sources were linked together in both calibration and evaluation of the hydrologic model using a DREAM based MCMC routine. Effects of having less information (e.g. missing one streamflow measurement for defining the rating curve or missing one precipitation station) was also investigated.

Measures of GCM Performance as Functions of Model Parameters Affecting Clouds and Radiation

NASA Astrophysics Data System (ADS)

Jackson, C.; Mu, Q.; Sen, M.; Stoffa, P.

2002-05-01

This abstract is one of three related presentations at this meeting dealing with several issues surrounding optimal parameter and uncertainty estimation of model predictions of climate. Uncertainty in model predictions of climate depends in part on the uncertainty produced by model approximations or parameterizations of unresolved physics. Evaluating these uncertainties is computationally expensive because one needs to evaluate how arbitrary choices for any given combination of model parameters affects model performance. Because the computational effort grows exponentially with the number of parameters being investigated, it is important to choose parameters carefully. Evaluating whether a parameter is worth investigating depends on two considerations: 1) does reasonable choices of parameter values produce a large range in model response relative to observational uncertainty? and 2) does the model response depend non-linearly on various combinations of model parameters? We have decided to narrow our attention to selecting parameters that affect clouds and radiation, as it is likely that these parameters will dominate uncertainties in model predictions of future climate. We present preliminary results of ~20 to 30 AMIPII style climate model integrations using NCAR's CCM3.10 that show model performance as functions of individual parameters controlling 1) critical relative humidity for cloud formation (RHMIN), and 2) boundary layer critical Richardson number (RICR). We also explore various definitions of model performance that include some or all observational data sources (surface air temperature and pressure, meridional and zonal winds, clouds, long and short-wave cloud forcings, etc...) and evaluate in a few select cases whether the model's response depends non-linearly on the parameter values we have selected.

How measurement science can improve confidence in research results.

PubMed

Plant, Anne L; Becker, Chandler A; Hanisch, Robert J; Boisvert, Ronald F; Possolo, Antonio M; Elliott, John T

2018-04-01

The current push for rigor and reproducibility is driven by a desire for confidence in research results. Here, we suggest a framework for a systematic process, based on consensus principles of measurement science, to guide researchers and reviewers in assessing, documenting, and mitigating the sources of uncertainty in a study. All study results have associated ambiguities that are not always clarified by simply establishing reproducibility. By explicitly considering sources of uncertainty, noting aspects of the experimental system that are difficult to characterize quantitatively, and proposing alternative interpretations, the researcher provides information that enhances comparability and reproducibility.

Signal recognition efficiencies of artificial neural-network pulse-shape discrimination in HPGe -decay searches

NASA Astrophysics Data System (ADS)

Caldwell, A.; Cossavella, F.; Majorovits, B.; Palioselitis, D.; Volynets, O.

2015-07-01

A pulse-shape discrimination method based on artificial neural networks was applied to pulses simulated for different background, signal and signal-like interactions inside a germanium detector. The simulated pulses were used to investigate variations of efficiencies as a function of used training set. It is verified that neural networks are well-suited to identify background pulses in true-coaxial high-purity germanium detectors. The systematic uncertainty on the signal recognition efficiency derived using signal-like evaluation samples from calibration measurements is estimated to be 5 %. This uncertainty is due to differences between signal and calibration samples.

Assessment of a three‐dimensional (3D) water scanning system for beam commissioning and measurements on a helical tomotherapy unit

PubMed Central

Ashenafi, Michael S.; McDonald, Daniel G.; Vanek, Kenneth N.

2015-01-01

Beam scanning data collected on the tomotherapy linear accelerator using the TomoScanner water scanning system is primarily used to verify the golden beam profiles included in all Helical TomoTherapy treatment planning systems (TOMO TPSs). The user is not allowed to modify the beam profiles/parameters for beam modeling within the TOMO TPSs. The authors report the first feasibility study using the Blue Phantom Helix (BPH) as an alternative to the TomoScanner (TS) system. This work establishes a benchmark dataset using BPH for target commissioning and quality assurance (QA), and quantifies systematic uncertainties between TS and BPH. Reproducibility of scanning with BPH was tested by three experienced physicists taking five sets of measurements over a six‐month period. BPH provides several enhancements over TS, including a 3D scanning arm, which is able to acquire necessary beam‐data with one tank setup, a universal chamber mount, and the OmniPro software, which allows online data collection and analysis. Discrepancies between BPH and TS were estimated by acquiring datasets with each tank. In addition, data measured with BPH and TS was compared to the golden TOMO TPS beam data. The total systematic uncertainty, defined as the combination of scanning system and beam modeling uncertainties, was determined through numerical analysis and tabulated. OmniPro was used for all analysis to eliminate uncertainty due to different data processing algorithms. The setup reproducibility of BPH remained within 0.5 mm/0.5%. Comparing BPH, TS, and Golden TPS for PDDs beyond maximum depth, the total systematic uncertainties were within 1.4 mm/2.1%. Between BPH and TPS golden data, maximum differences in the field width and penumbra of in‐plane profiles were within 0.8 and 1.1 mm, respectively. Furthermore, in cross‐plane profiles, the field width differences increased at depth greater than 10 cm up to 2.5 mm, and maximum penumbra uncertainties were 5.6 mm and 4.6 mm from TS scanning system and TPS modeling, respectively. Use of BPH reduced measurement time by 1–2 hrs per session. The BPH has been assessed as an efficient, reproducible, and accurate scanning system capable of providing a reliable benchmark beam data. With this data, a physicist can utilize the BPH in a clinical setting with an understanding of the scan discrepancy that may be encountered while validating the TPS or during routine machine QA. Without the flexibility of modifying the TPS and without a golden beam dataset from the vendor or a TPS model generated from data collected with the BPH, this represents the best solution for current clinical use of the BPH. PACS number: 87.56.Fc

Do (un)certainty appraisal tendencies reverse the influence of emotions on risk taking in sequential tasks?

PubMed

Bagneux, Virginie; Bollon, Thierry; Dantzer, Cécile

2012-01-01

According to the Appraisal-Tendency Framework (Han, Lerner, & Keltner, 2007), certainty-associated emotions increase risk taking compared with uncertainty-associated emotions. To date, this general effect has only been shown in static judgement and decision-making paradigms; therefore, the present study tested the effect of certainty on risk taking in a sequential decision-making task. We hypothesised that the effect would be reversed due to the kind of processing involved, as certainty is considered to encourage heuristic processing that takes into account the emotional cues arising from previous decisions, whereas uncertainty leads to more systematic processing. One hundred and one female participants were induced to feel one of three emotions (film clips) before performing a decision-making task involving risk (Game of Dice Task; Brand et al., 2005). As expected, the angry and happy participants (certainty-associated emotions) were more likely than the fearful participants (uncertainty-associated emotion) to make safe decisions (vs. risky decisions).

Role of turbulence fluctuations on uncertainties of acoutic Doppler current profiler discharge measurements

USGS Publications Warehouse

Tarrab, Leticia; Garcia, Carlos M.; Cantero, Mariano I.; Oberg, Kevin

2012-01-01

This work presents a systematic analysis quantifying the role of the presence of turbulence fluctuations on uncertainties (random errors) of acoustic Doppler current profiler (ADCP) discharge measurements from moving platforms. Data sets of three-dimensional flow velocities with high temporal and spatial resolution were generated from direct numerical simulation (DNS) of turbulent open channel flow. Dimensionless functions relating parameters quantifying the uncertainty in discharge measurements due to flow turbulence (relative variance and relative maximum random error) to sampling configuration were developed from the DNS simulations and then validated with field-scale discharge measurements. The validated functions were used to evaluate the role of the presence of flow turbulence fluctuations on uncertainties in ADCP discharge measurements. The results of this work indicate that random errors due to the flow turbulence are significant when: (a) a low number of transects is used for a discharge measurement, and (b) measurements are made in shallow rivers using high boat velocity (short time for the boat to cross a flow turbulence structure).

First Observation of a Baryonic B_{s}^{0} Decay.

PubMed

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

2017-07-28

We report the first observation of a baryonic B_{s}^{0} decay, B_{s}^{0}→pΛ[over ¯]K^{-}, using proton-proton collision data recorded by the LHCb experiment at center-of-mass energies of 7 and 8 TeV, corresponding to an integrated luminosity of 3.0  fb^{-1}. The branching fraction is measured to be B(B_{s}^{0}→pΛ[over ¯]K^{-})+B(B_{s}^{0}→p[over ¯]ΛK^{+})=[5.46±0.61±0.57±0.50(B)±0.32(f_{s}/f_{d})]×10^{-6}, where the first uncertainty is statistical and the second systematic, the third uncertainty accounts for the experimental uncertainty on the branching fraction of the B^{0}→pΛ[over ¯]π^{-} decay used for normalization, and the fourth uncertainty relates to the knowledge of the ratio of b-quark hadronization probabilities f_{s}/f_{d}.

High-voltage measurements on the 5 ppm relative uncertainty level with collinear laser spectroscopy

NASA Astrophysics Data System (ADS)

Krämer, J.; König, K.; Geppert, Ch; Imgram, P.; Maaß, B.; Meisner, J.; Otten, E. W.; Passon, S.; Ratajczyk, T.; Ullmann, J.; Nörtershäuser, W.

2018-04-01

We present the results of high-voltage collinear laser spectroscopy measurements on the 5 ppm relative uncertainty level using a pump and probe scheme at the 4s ^2S1/2 → 4p ^2P3/2 transition of {\\hspace{0pt}}40Ca+ involving the 3d ^2D5/2 metastable state. With two-stage laser interaction and a reference measurement we can eliminate systematic effects such as differences in the contact potentials due to different electrode materials and thermoelectric voltages, and the unknown starting potential of the ions in the ion source. Voltage measurements were performed between  -5 kV and  -19 kV and parallel measurements with stable high-voltage dividers calibrated to 5 ppm relative uncertainty were used as a reference. Our measurements are compatible with the uncertainty limits of the high-voltage dividers and demonstrate an unprecedented (factor of 20) increase in the precision of direct laser-based high-voltage measurements.

How primary care physicians' attitudes toward risk and uncertainty affect their use of electronic information resources.

PubMed

McKibbon, K Ann; Fridsma, Douglas B; Crowley, Rebecca S

2007-04-01

The research sought to determine if primary care physicians' attitudes toward risk taking or uncertainty affected how they sought information and used electronic information resources when answering simulated clinical questions. Using physician-supplied data collected from existing risk and uncertainty scales, twenty-five physicians were classified as risk seekers (e.g., enjoying adventure), risk neutral, or risk avoiders (e.g., cautious) and stressed or unstressed by uncertainty. The physicians then answered twenty-three multiple-choice, clinically focused questions and selected two to pursue further using their own information resources. Think-aloud protocols were used to collect searching process and outcome data (e.g., searching time, correctness of answers, searching techniques). No differences in searching outcomes were observed between the groups. Physicians who were risk avoiding and those who reported stress when faced with uncertainty each showed differences in searching processes (e.g., actively analyzing retrieval, using searching heuristics or rules). Physicians who were risk avoiding tended to use resources that provided answers and summaries, such as Cochrane or UpToDate, less than risk-seekers did. Physicians who reported stress when faced with uncertainty showed a trend toward less frequent use of MEDLINE, when compared with physicians who were not stressed by uncertainty. Physicians' attitudes towards risk taking and uncertainty were associated with different searching processes but not outcomes. Awareness of differences in physician attitudes may be key in successful design and implementation of clinical information resources.

Importance of anthropogenic climate impact, sampling error and urban development in sewer system design.

PubMed

Egger, C; Maurer, M

2015-04-15

Urban drainage design relying on observed precipitation series neglects the uncertainties associated with current and indeed future climate variability. Urban drainage design is further affected by the large stochastic variability of precipitation extremes and sampling errors arising from the short observation periods of extreme precipitation. Stochastic downscaling addresses anthropogenic climate impact by allowing relevant precipitation characteristics to be derived from local observations and an ensemble of climate models. This multi-climate model approach seeks to reflect the uncertainties in the data due to structural errors of the climate models. An ensemble of outcomes from stochastic downscaling allows for addressing the sampling uncertainty. These uncertainties are clearly reflected in the precipitation-runoff predictions of three urban drainage systems. They were mostly due to the sampling uncertainty. The contribution of climate model uncertainty was found to be of minor importance. Under the applied greenhouse gas emission scenario (A1B) and within the period 2036-2065, the potential for urban flooding in our Swiss case study is slightly reduced on average compared to the reference period 1981-2010. Scenario planning was applied to consider urban development associated with future socio-economic factors affecting urban drainage. The impact of scenario uncertainty was to a large extent found to be case-specific, thus emphasizing the need for scenario planning in every individual case. The results represent a valuable basis for discussions of new drainage design standards aiming specifically to include considerations of uncertainty. Copyright © 2015 Elsevier Ltd. All rights reserved.

TU-EF-304-03: 4D Monte Carlo Robustness Test for Proton Therapy

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

Souris, K; Sterpin, E; Lee, J

Purpose: Breathing motion and approximate dose calculation engines may increase proton range uncertainties. We address these two issues using a comprehensive 4D robustness evaluation tool based on an efficient Monte Carlo (MC) engine, which can simulate breathing with no significant increase in computation time. Methods: To assess the robustness of the treatment plan, multiple scenarios of uncertainties are simulated, taking into account the systematic and random setup errors, range uncertainties, and organ motion. Our fast MC dose engine, called MCsquare, implements optimized models on a massively-parallel computation architecture and allows us to accurately simulate a scenario in less than onemore » minute. The deviations of the uncertainty scenarios are then reported on a DVH-band and compared to the nominal plan.The robustness evaluation tool is illustrated in a lung case by comparing three 60Gy treatment plans. First, a plan is optimized on a PTV obtained by extending the CTV with an 8mm margin, in order to take into account systematic geometrical uncertainties, like in our current practice in radiotherapy. No specific strategy is employed to correct for tumor and organ motions. The second plan involves a PTV generated from the ITV, which encompasses the tumor volume in all breathing phases. The last plan results from robust optimization performed on the ITV, with robustness parameters of 3% for tissue density and 8 mm for positioning errors. Results: The robustness test revealed that the first two plans could not properly cover the target in the presence of uncertainties. CTV-coverage (D95) in the three plans ranged respectively between 39.4–55.5Gy, 50.2–57.5Gy, and 55.1–58.6Gy. Conclusion: A realistic robustness verification tool based on a fast MC dose engine has been developed. This test is essential to assess the quality of proton therapy plan and very useful to study various planning strategies for mobile tumors. This work is partly funded by IBA (Louvain-la-Neuve, Belgium)« less

Quantifying confidence in density functional theory predictions of magnetic ground states

NASA Astrophysics Data System (ADS)

Houchins, Gregory; Viswanathan, Venkatasubramanian

2017-10-01

Density functional theory (DFT) simulations, at the generalized gradient approximation (GGA) level, are being routinely used for material discovery based on high-throughput descriptor-based searches. The success of descriptor-based material design relies on eliminating bad candidates and keeping good candidates for further investigation. While DFT has been widely successfully for the former, oftentimes good candidates are lost due to the uncertainty associated with the DFT-predicted material properties. Uncertainty associated with DFT predictions has gained prominence and has led to the development of exchange correlation functionals that have built-in error estimation capability. In this work, we demonstrate the use of built-in error estimation capabilities within the BEEF-vdW exchange correlation functional for quantifying the uncertainty associated with the magnetic ground state of solids. We demonstrate this approach by calculating the uncertainty estimate for the energy difference between the different magnetic states of solids and compare them against a range of GGA exchange correlation functionals as is done in many first-principles calculations of materials. We show that this estimate reasonably bounds the range of values obtained with the different GGA functionals. The estimate is determined as a postprocessing step and thus provides a computationally robust and systematic approach to estimating uncertainty associated with predictions of magnetic ground states. We define a confidence value (c-value) that incorporates all calculated magnetic states in order to quantify the concurrence of the prediction at the GGA level and argue that predictions of magnetic ground states from GGA level DFT is incomplete without an accompanying c-value. We demonstrate the utility of this method using a case study of Li-ion and Na-ion cathode materials and the c-value metric correctly identifies that GGA-level DFT will have low predictability for NaFePO4F . Further, there needs to be a systematic test of a collection of plausible magnetic states, especially in identifying antiferromagnetic (AFM) ground states. We believe that our approach of estimating uncertainty can be readily incorporated into all high-throughput computational material discovery efforts and this will lead to a dramatic increase in the likelihood of finding good candidate materials.

Unconscious Vigilance: Worldview Defense Without Adaptations for Terror, Coalition, or Uncertainty Management

PubMed Central

Holbrook, Colin; Sousa, Paulo; Hahn-Holbrook, Jennifer

2012-01-01

Individuals subtly reminded of death, coalitional challenges, or feelings of uncertainty display exaggerated preferences for affirmations and against criticisms of their cultural in-groups. Terror management, coalitional psychology, and uncertainty management theories postulate this “worldview defense” effect as the output of mechanisms evolved either to allay the fear of death, foster social support, or reduce anxiety by increasing adherence to cultural values. In 4 studies, we report evidence for an alternative perspective. We argue that worldview defense owes to unconscious vigilance, a state of accentuated reactivity to affective targets (which need not relate to cultural worldviews) that follows detection of subtle alarm cues (which need not pertain to death, coalitional challenges, or uncertainty). In Studies 1 and 2, death-primed participants produced exaggerated ratings of worldview-neutral affective targets. In Studies 3 and 4, subliminal threat manipulations unrelated to death, coalitional challenges, or uncertainty evoked worldview defense. These results are discussed as they inform evolutionary interpretations of worldview defense and future investigations of the influence of unconscious alarm on judgment. PMID:21644809

Uncertainty in assessing value of oncology treatments.

PubMed

Mullins, C Daniel; Montgomery, Russ; Tunis, Sean

2010-01-01

Patients, clinicians, payers, and policymakers face an environment of significant evidentiary uncertainty as they attempt to achieve maximum value, or the greatest level of benefit possible at a given level of cost in their respective health care decisions. This is particularly true in the area of oncology, for which published evidence from clinical trials is often incongruent with real-world patient care, and a substantial portion of clinical use is for off-label indications that have not been systematically evaluated. It is this uncertainty in the knowledge of the clinical harms and benefits associated with oncology treatments that prevents postregulatory decision makers from making accurate assessments of the value of these treatments. Because of the incentives inherent in the clinical research enterprise, randomized control trials (RCTs) are designed for the specific purpose of regulatory approval and maximizing market penetration. The pursuit of these goals results in RCT study designs that achieve maximal internal validity at the expense of generalizability to diverse real-world patient populations that may have significant comorbidities and other clinically mitigating factors. As such, systematic reviews for the purposes of coverage and treatment decisions often find relevant and high-quality evidence to be limited or nonexistent. For a number of reasons, including frequent off-label use of medications and the expedited approval process for cancer drugs by the U.S. Food and Drug Administration, this situation is exacerbated in the area of oncology. This paper investigates the convergence of incentives and circumstances that lead to widespread uncertainty in oncology and proposes new paradigms for clinical research, including pragmatic clinical trials, methodological guidance, and coverage with evidence development. Each of these initiatives would support the design of clinical research that is more informative for postregulatory decision makers, and would therefore reduce uncertainty and provide greater confidence in conclusions about the value of these treatments.

ISA implementation and uncertainty: a literature review and expert elicitation study.

PubMed

van der Pas, J W G M; Marchau, V A W J; Walker, W E; van Wee, G P; Vlassenroot, S H

2012-09-01

Each day, an average of over 116 people die from traffic accidents in the European Union. One out of three fatalities is estimated to be the result of speeding. The current state of technology makes it possible to make speeding more difficult, or even impossible, by placing intelligent speed limiters (so called ISA devices) in vehicles. Although the ISA technology has been available for some years now, and reducing the number of road traffic fatalities and injuries has been high on the European political agenda, implementation still seems to be far away. Experts indicate that there are still too many uncertainties surrounding ISA implementation, and dealing with these uncertainties is essential for implementing ISA. In this paper, a systematic and representative inventory of the uncertainties is made based upon the literature. Furthermore, experts in the field of ISA were surveyed and asked which uncertainties are barriers for ISA implementation, and how uncertain these uncertainties are. We found that the long-term effects and the effects of large-scale implementation of ISA are still uncertain and are the most important barriers for the implementation of the most effective types of ISA. One way to deal with these uncertainties would be to start implementation on a small scale and gradually expand the penetration, in order to learn how ISA influences the transport system over time. Copyright © 2010 Elsevier Ltd. All rights reserved.

A systematic uncertainty analysis of an evaluative fate and exposure model.

PubMed

Hertwich, E G; McKone, T E; Pease, W S

2000-08-01

Multimedia fate and exposure models are widely used to regulate the release of toxic chemicals, to set cleanup standards for contaminated sites, and to evaluate emissions in life-cycle assessment. CalTOX, one of these models, is used to calculate the potential dose, an outcome that is combined with the toxicity of the chemical to determine the Human Toxicity Potential (HTP), used to aggregate and compare emissions. The comprehensive assessment of the uncertainty in the potential dose calculation in this article serves to provide the information necessary to evaluate the reliability of decisions based on the HTP A framework for uncertainty analysis in multimedia risk assessment is proposed and evaluated with four types of uncertainty. Parameter uncertainty is assessed through Monte Carlo analysis. The variability in landscape parameters is assessed through a comparison of potential dose calculations for different regions in the United States. Decision rule uncertainty is explored through a comparison of the HTP values under open and closed system boundaries. Model uncertainty is evaluated through two case studies, one using alternative formulations for calculating the plant concentration and the other testing the steady state assumption for wet deposition. This investigation shows that steady state conditions for the removal of chemicals from the atmosphere are not appropriate and result in an underestimate of the potential dose for 25% of the 336 chemicals evaluated.

Approach to determine measurement uncertainty in complex nanosystems with multiparametric dependencies and multivariate output quantities

NASA Astrophysics Data System (ADS)

Hampel, B.; Liu, B.; Nording, F.; Ostermann, J.; Struszewski, P.; Langfahl-Klabes, J.; Bieler, M.; Bosse, H.; Güttler, B.; Lemmens, P.; Schilling, M.; Tutsch, R.

2018-03-01

In many cases, the determination of the measurement uncertainty of complex nanosystems provides unexpected challenges. This is in particular true for complex systems with many degrees of freedom, i.e. nanosystems with multiparametric dependencies and multivariate output quantities. The aim of this paper is to address specific questions arising during the uncertainty calculation of such systems. This includes the division of the measurement system into subsystems and the distinction between systematic and statistical influences. We demonstrate that, even if the physical systems under investigation are very different, the corresponding uncertainty calculation can always be realized in a similar manner. This is exemplarily shown in detail for two experiments, namely magnetic nanosensors and ultrafast electro-optical sampling of complex time-domain signals. For these examples the approach for uncertainty calculation following the guide to the expression of uncertainty in measurement (GUM) is explained, in which correlations between multivariate output quantities are captured. To illustate the versatility of the proposed approach, its application to other experiments, namely nanometrological instruments for terahertz microscopy, dimensional scanning probe microscopy, and measurement of concentration of molecules using surface enhanced Raman scattering, is shortly discussed in the appendix. We believe that the proposed approach provides a simple but comprehensive orientation for uncertainty calculation in the discussed measurement scenarios and can also be applied to similar or related situations.

Asteroid approach covariance analysis for the Clementine mission

NASA Technical Reports Server (NTRS)

Ionasescu, Rodica; Sonnabend, David

1993-01-01

The Clementine mission is designed to test Strategic Defense Initiative Organization (SDIO) technology, the Brilliant Pebbles and Brilliant Eyes sensors, by mapping the moon surface and flying by the asteroid Geographos. The capability of two of the instruments available on board the spacecraft, the lidar (laser radar) and the UV/Visible camera is used in the covariance analysis to obtain the spacecraft delivery uncertainties at the asteroid. These uncertainties are due primarily to asteroid ephemeris uncertainties. On board optical navigation reduces the uncertainty in the knowledge of the spacecraft position in the direction perpendicular to the incoming asymptote to a one-sigma value of under 1 km, at the closest approach distance of 100 km. The uncertainty in the knowledge of the encounter time is about 0.1 seconds for a flyby velocity of 10.85 km/s. The magnitude of these uncertainties is due largely to Center Finding Errors (CFE). These systematic errors represent the accuracy expected in locating the center of the asteroid in the optical navigation images, in the absence of a topographic model for the asteroid. The direction of the incoming asymptote cannot be estimated accurately until minutes before the asteroid flyby, and correcting for it would require autonomous navigation. Orbit determination errors dominate over maneuver execution errors, and the final delivery accuracy attained is basically the orbit determination uncertainty before the final maneuver.

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Nemani, Ramakrishma

2010-01-01

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Prioritizing Chemicals and Data Requirements for Screening-Level Exposure and Risk Assessment

PubMed Central

Brown, Trevor N.; Wania, Frank; Breivik, Knut; McLachlan, Michael S.

2012-01-01

Background: Scientists and regulatory agencies strive to identify chemicals that may cause harmful effects to humans and the environment; however, prioritization is challenging because of the large number of chemicals requiring evaluation and limited data and resources. Objectives: We aimed to prioritize chemicals for exposure and exposure potential and obtain a quantitative perspective on research needs to better address uncertainty in screening assessments. Methods: We used a multimedia mass balance model to prioritize > 12,000 organic chemicals using four far-field human exposure metrics. The propagation of variance (uncertainty) in key chemical information used as model input for calculating exposure metrics was quantified. Results: Modeled human concentrations and intake rates span approximately 17 and 15 orders of magnitude, respectively. Estimates of exposure potential using human concentrations and a unit emission rate span approximately 13 orders of magnitude, and intake fractions span 7 orders of magnitude. The actual chemical emission rate contributes the greatest variance (uncertainty) in exposure estimates. The human biotransformation half-life is the second greatest source of uncertainty in estimated concentrations. In general, biotransformation and biodegradation half-lives are greater sources of uncertainty in modeled exposure and exposure potential than chemical partition coefficients. Conclusions: Mechanistic exposure modeling is suitable for screening and prioritizing large numbers of chemicals. By including uncertainty analysis and uncertainty in chemical information in the exposure estimates, these methods can help identify and address the important sources of uncertainty in human exposure and risk assessment in a systematic manner. PMID:23008278

Quantifying errors without random sampling.

PubMed

Phillips, Carl V; LaPole, Luwanna M

2003-06-12

All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified. When a quantification does not involve sampling, error is almost never quantified and results are often reported in ways that dramatically overstate their precision. We argue that the precision implicit in typical reporting is problematic and sketch methods for quantifying the various sources of error, building up from simple examples that can be solved analytically to more complex cases. There are straightforward ways to partially quantify the uncertainty surrounding a parameter that is not characterized by random sampling, such as limiting reported significant figures. We present simple methods for doing such quantifications, and for incorporating them into calculations. More complicated methods become necessary when multiple sources of uncertainty must be combined. We demonstrate that Monte Carlo simulation, using available software, can estimate the uncertainty resulting from complicated calculations with many sources of uncertainty. We apply the method to the current estimate of the annual incidence of foodborne illness in the United States. Quantifying uncertainty from systematic errors is practical. Reporting this uncertainty would more honestly represent study results, help show the probability that estimated values fall within some critical range, and facilitate better targeting of further research.

Instrument Drift Uncertainties and the Long-Term TOMS/SBUV Total Ozone Record

NASA Technical Reports Server (NTRS)

Solarski, Richard S.; Frith, Stacey

2005-01-01

Long-term climate records from satellites are often constructed from the measurements of a sequence of instruments launched at different times. Each of these instruments is calibrated prior to launch. After launch they are subjected to potential offsets and slow drifts in calibration. We illustrate these issues in the construction of a merged total ozone record from two TOMS and three SBUV instruments. This record extends from late 1978 through the present. The question is "How good are these records?". We have examined the uncertainty in determining the relative calibration of two instruments during an overlap period in their measurements. When comparing a TOMS instrument, such as that on Nimbus 7, with an SBUV instrument, also on Nimbus 7, we find systematic differences and random differences. We have combined these findings with estimates of individual instrument drift into a monte- carlo uncertainty propagation model. We estimate an instrument drift uncertainty of a little larger than 1 percent per decade over the 25-year history of the TOMS/SBUV measurements. We make an independent estimate of the drift uncertainty in the ground-based network of total ozone measurements and find it to be of similar, but slightly smaller magnitude. The implications of these uncertainties for trend and recovery determination will be discussed.

Insights into water managers' perception and handling of uncertainties - a study of the role of uncertainty in practitioners' planning and decision-making

NASA Astrophysics Data System (ADS)

Höllermann, Britta; Evers, Mariele

2017-04-01

Planning and decision-making under uncertainty is common in water management due to climate variability, simplified models, societal developments, planning restrictions just to name a few. Dealing with uncertainty can be approached from two sites, hereby affecting the process and form of communication: Either improve the knowledge base by reducing uncertainties or apply risk-based approaches to acknowledge uncertainties throughout the management process. Current understanding is that science more strongly focusses on the former approach, while policy and practice are more actively applying a risk-based approach to handle incomplete and/or ambiguous information. The focus of this study is on how water managers perceive and handle uncertainties at the knowledge/decision interface in their daily planning and decision-making routines. How they evaluate the role of uncertainties for their decisions and how they integrate this information into the decision-making process. Expert interviews and questionnaires among practitioners and scientists provided an insight into their perspectives on uncertainty handling allowing a comparison of diverse strategies between science and practice as well as between different types of practitioners. Our results confirmed the practitioners' bottom up approach from potential measures upwards instead of impact assessment downwards common in science-based approaches. This science-practice gap may hinder effective uncertainty integration and acknowledgement in final decisions. Additionally, the implementation of an adaptive and flexible management approach acknowledging uncertainties is often stalled by rigid regulations favouring a predict-and-control attitude. However, the study showed that practitioners' level of uncertainty recognition varies with respect to his or her affiliation to type of employer and business unit, hence, affecting the degree of the science-practice-gap with respect to uncertainty recognition. The level of working experience was examined as a cross-cutting property of science and practice with increasing levels of uncertainty awareness and integration among more experienced researchers and practitioners. In conclusion, our study of water managers' perception and handling of uncertainties provides valuable insights for finding routines for uncertainty communication and integration into planning and decision-making processes by acknowledging the divers perceptions among producers, users and receivers of uncertainty information. These results can contribute to more effective integration of hydrological forecast and improved decisions.

The Scientific Basis of Uncertainty Factors Used in Setting Occupational Exposure Limits.

PubMed

Dankovic, D A; Naumann, B D; Maier, A; Dourson, M L; Levy, L S

2015-01-01

The uncertainty factor concept is integrated into health risk assessments for all aspects of public health practice, including by most organizations that derive occupational exposure limits. The use of uncertainty factors is predicated on the assumption that a sufficient reduction in exposure from those at the boundary for the onset of adverse effects will yield a safe exposure level for at least the great majority of the exposed population, including vulnerable subgroups. There are differences in the application of the uncertainty factor approach among groups that conduct occupational assessments; however, there are common areas of uncertainty which are considered by all or nearly all occupational exposure limit-setting organizations. Five key uncertainties that are often examined include interspecies variability in response when extrapolating from animal studies to humans, response variability in humans, uncertainty in estimating a no-effect level from a dose where effects were observed, extrapolation from shorter duration studies to a full life-time exposure, and other insufficiencies in the overall health effects database indicating that the most sensitive adverse effect may not have been evaluated. In addition, a modifying factor is used by some organizations to account for other remaining uncertainties-typically related to exposure scenarios or accounting for the interplay among the five areas noted above. Consideration of uncertainties in occupational exposure limit derivation is a systematic process whereby the factors applied are not arbitrary, although they are mathematically imprecise. As the scientific basis for uncertainty factor application has improved, default uncertainty factors are now used only in the absence of chemical-specific data, and the trend is to replace them with chemical-specific adjustment factors whenever possible. The increased application of scientific data in the development of uncertainty factors for individual chemicals also has the benefit of increasing the transparency of occupational exposure limit derivation. Improved characterization of the scientific basis for uncertainty factors has led to increasing rigor and transparency in their application as part of the overall occupational exposure limit derivation process.

Market Access Agreements for pharmaceuticals in Europe: diversity of approaches and underlying concepts.

PubMed

Jarosławski, Szymon; Toumi, Mondher

2011-10-08

Market Access Agreements (MAA) between pharmaceutical industry and health care payers have been proliferating in Europe in the last years. MAA can be simple discounts from the list price or very sophisticated schemes with inarguably high administrative burden. We distinguished and defined from the health care payer perspective three kinds of MAA: Commercial Agreements (CA), Payment for Performance Agreements (P4P) and Coverage with Evidence Development (CED). Apart from CA, the agreements assumed collection and analysis of real-life health outcomes data, either from a cohort of patients (CED) or on per patient basis (P4P). We argue that while P4P aim at reducing drug cost to payers without a systematic approach to addressing uncertainty about drugs' value, CED were implemented provisionally to reduce payer's uncertainty about value of a medicine within a defined time period. We are of opinion that while CA and P4P have a potential to reduce payers' expenditure on costly drugs while maintaining a high list price, CED address initial uncertainty related to assessing the real-life value of new drugs and enable a final HTA recommendation or reimbursement and pricing decisions. Further, we suggest that real cost to health care payers of drugs in CA and P4P should be made publicly available in a systematic manner, to avoid a perverse impact of these MAA types on the international reference pricing system.

Search for tensor-like couplings in the β-decay of laser trapped 6He

NASA Astrophysics Data System (ADS)

Leredde, Arnaud; Bailey, Kevin; Mueller, Peter; O'Connor, Tom; Bagdasarova, Yelena; Garcia, Alejandro; Hong, Ran; Sternberg, Matthew; Storm, Derek; Swanson, Erik; Wauters, Frederik; Zumwalt, David; Flechard, Xavier; Naviliat-Cuncic, Oscar

2015-10-01

The beta-neutrino angular correlation in nuclear beta decay can reveal the nature of the weak interaction. The case of 6He is particularly sensitive to test for tensor contributions by measuring the corresponding angular correlation parameter aβν. Trapping techniques such as magneto-optical traps (MOT) combined with recoil ion momentum spectroscopy are powerful tools which allow to measure aβν with high precision. The experiment, located at the University of Washington, takes advantage of the tandem Van de Graaff accelerator to produce up to 2×1010 6He/s. A double-MOT setup has been optimized to trap and detect beta-recoil-ion coincidences at a rate of a few Hertz. Systematic effects have been investigated in details and major effort has been put to limit their contribution to less than 1% of aβν. The first goal of this experiment is to measure aβν with this 1% uncertainty and use this set of data to guide further improvements with the goal to bring the uncertainty to the 0.1% level. The performances of the trap setup, preliminary coincidence data, and studies of systematic uncertainties will be presented. This work is supported by DOE, Office of Nuclear Physics, under Contract Nos. DE-AC02-06CH11357 and DE-FG02-97ER41020.

Uncertainty and Cognitive Control

PubMed Central

Mushtaq, Faisal; Bland, Amy R.; Schaefer, Alexandre

2011-01-01

A growing trend of neuroimaging, behavioral, and computational research has investigated the topic of outcome uncertainty in decision-making. Although evidence to date indicates that humans are very effective in learning to adapt to uncertain situations, the nature of the specific cognitive processes involved in the adaptation to uncertainty are still a matter of debate. In this article, we reviewed evidence suggesting that cognitive control processes are at the heart of uncertainty in decision-making contexts. Available evidence suggests that: (1) There is a strong conceptual overlap between the constructs of uncertainty and cognitive control; (2) There is a remarkable overlap between the neural networks associated with uncertainty and the brain networks subserving cognitive control; (3) The perception and estimation of uncertainty might play a key role in monitoring processes and the evaluation of the “need for control”; (4) Potential interactions between uncertainty and cognitive control might play a significant role in several affective disorders. PMID:22007181

Systematically evaluating read-across prediction and performance using a local validity approach characterized by chemical structure and bioactivity information

EPA Science Inventory

Read-across is a popular data gap filling technique within category and analogue approaches for regulatory purposes. Acceptance of read-across remains an ongoing challenge with several efforts underway for identifying and addressing uncertainties. Here we demonstrate an algorithm...

HYDROLOGIC MODEL CALIBRATION AND UNCERTAINTY IN SCENARIO ANALYSIS

EPA Science Inventory

A systematic analysis of model performance during simulations based on

observed land-cover/use change is used to quantify error associated with water-yield

simulations for a series of known landscape conditions over a 24-year period with the

goal of evaluatin...

Categorical Biases in Spatial Memory: The Role of Certainty

ERIC Educational Resources Information Center

Holden, Mark P.; Newcombe, Nora S.; Shipley, Thomas F.

2015-01-01

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. The Category Adjustment (CA) model suggests that this bias is due to a Bayesian combination of categorical and metric information, which offers an optimal solution under conditions of uncertainty (Huttenlocher, Hedges, & Duncan,…

Asymmetries in Predictive and Diagnostic Reasoning

ERIC Educational Resources Information Center

Fernbach, Philip M.; Darlow, Adam; Sloman, Steven A.

2011-01-01

In this article, we address the apparent discrepancy between causal Bayes net theories of cognition, which posit that judgments of uncertainty are generated from causal beliefs in a way that respects the norms of probability, and evidence that probability judgments based on causal beliefs are systematically in error. One purported source of bias…

The New Muon g₋2 experiment at Fermilab

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

Venanzoni, Graziano

2016-06-02

There is a long standing discrepancy between the Standard Model prediction for the muon g-2 and the value measured by the Brookhaven E821 Experiment. At present the discrepancy stands at about three standard deviations, with a comparable accuracy between experiment and theory. Two new proposals -- at Fermilab and J-PARC -- plan to improve the experimental uncertainty by a factor of 4, and it is expected that there will be a significant reduction in the uncertainty of the Standard Model prediction. I will review the status of the planned experiment at Fermilab, E989, which will analyse 21 times more muonsmore » than the BNL experiment and discuss how the systematic uncertainty will be reduced by a factor of 3 such that a precision of 0.14 ppm can be achieved.« less

Hierarchical Multi-Scale Approach To Validation and Uncertainty Quantification of Hyper-Spectral Image Modeling

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

Engel, David W.; Reichardt, Thomas A.; Kulp, Thomas J.

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensormore » level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.« less

Intrinsic uncertainty on the nature of dark energy

NASA Astrophysics Data System (ADS)

Valkenburg, Wessel; Kunz, Martin; Marra, Valerio

2013-12-01

We argue that there is an intrinsic noise on measurements of the equation of state parameter w = p/ρ from large-scale structure around us. The presence of the large-scale structure leads to an ambiguity in the definition of the background universe and thus there is a maximal precision with which we can determine the equation of state of dark energy. To study the uncertainty due to local structure, we model density perturbations stemming from a standard inflationary power spectrum by means of the exact Lemaître-Tolman-Bondi solution of Einstein’s equation, and show that the usual distribution of matter inhomogeneities in a ΛCDM cosmology causes a variation of w - as inferred from distance measures - of several percent. As we observe only one universe, or equivalently because of the cosmic variance, this uncertainty is systematic in nature.

VizieR Online Data Catalog: Spectral properties of 441 radio pulsars (Jankowski+, 2018)

NASA Astrophysics Data System (ADS)

Jankowski, F.; van Straten, W.; Keane, E. F.; Bailes, M.; Barr, E. D.; Johnston, S.; Kerr, M.

2018-03-01

We present spectral parameters for 441 radio pulsars. These were obtained from observations centred at 728, 1382 and 3100MHz using the 10-50cm and the 20cm multibeam receiver at the Parkes radio telescope. In particular, we list the pulsar names (J2000), the calibrated, band-integrated flux densities at 728, 1382 and 3100MHz, the spectral classifications, the frequency ranges the spectral classifications were performed over, the spectral indices for pulsars with simple power-law spectra and the robust modulation indices at all three centre frequencies for pulsars of which we have at least six measurement epochs. The flux density uncertainties include scintillation and a systematic contribution, in addition to the statistical uncertainty. Upper limits are reported at the 3σ level and all other uncertainties at the 1σ level. (1 data file).

Uncertainty in hydrological signatures

NASA Astrophysics Data System (ADS)

McMillan, Hilary; Westerberg, Ida

2015-04-01

Information that summarises the hydrological behaviour or flow regime of a catchment is essential for comparing responses of different catchments to understand catchment organisation and similarity, and for many other modelling and water-management applications. Such information types derived as an index value from observed data are known as hydrological signatures, and can include descriptors of high flows (e.g. mean annual flood), low flows (e.g. mean annual low flow, recession shape), the flow variability, flow duration curve, and runoff ratio. Because the hydrological signatures are calculated from observed data such as rainfall and flow records, they are affected by uncertainty in those data. Subjective choices in the method used to calculate the signatures create a further source of uncertainty. Uncertainties in the signatures may affect our ability to compare different locations, to detect changes, or to compare future water resource management scenarios. The aim of this study was to contribute to the hydrological community's awareness and knowledge of data uncertainty in hydrological signatures, including typical sources, magnitude and methods for its assessment. We proposed a generally applicable method to calculate these uncertainties based on Monte Carlo sampling and demonstrated it for a variety of commonly used signatures. The study was made for two data rich catchments, the 50 km2 Mahurangi catchment in New Zealand and the 135 km2 Brue catchment in the UK. For rainfall data the uncertainty sources included point measurement uncertainty, the number of gauges used in calculation of the catchment spatial average, and uncertainties relating to lack of quality control. For flow data the uncertainty sources included uncertainties in stage/discharge measurement and in the approximation of the true stage-discharge relation by a rating curve. The resulting uncertainties were compared across the different signatures and catchments, to quantify uncertainty magnitude and bias, and to test how uncertainty depended on the density of the raingauge network and flow gauging station characteristics. The uncertainties were sometimes large (i.e. typical intervals of ±10-40% relative uncertainty) and highly variable between signatures. Uncertainty in the mean discharge was around ±10% for both catchments, while signatures describing the flow variability had much higher uncertainties in the Mahurangi where there was a fast rainfall-runoff response and greater high-flow rating uncertainty. Event and total runoff ratios had uncertainties from ±10% to ±15% depending on the number of rain gauges used; precipitation uncertainty was related to interpolation rather than point uncertainty. Uncertainty distributions in these signatures were skewed, and meant that differences in signature values between these catchments were often not significant. We hope that this study encourages others to use signatures in a way that is robust to data uncertainty.

Optimal second order sliding mode control for nonlinear uncertain systems.

PubMed

Das, Madhulika; Mahanta, Chitralekha

2014-07-01

In this paper, a chattering free optimal second order sliding mode control (OSOSMC) method is proposed to stabilize nonlinear systems affected by uncertainties. The nonlinear optimal control strategy is based on the control Lyapunov function (CLF). For ensuring robustness of the optimal controller in the presence of parametric uncertainty and external disturbances, a sliding mode control scheme is realized by combining an integral and a terminal sliding surface. The resulting second order sliding mode can effectively reduce chattering in the control input. Simulation results confirm the supremacy of the proposed optimal second order sliding mode control over some existing sliding mode controllers in controlling nonlinear systems affected by uncertainty. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

On the prospects of cross-calibrating the Cherenkov Telescope Array with an airborne calibration platform

NASA Astrophysics Data System (ADS)

Brown, Anthony M.

2018-01-01

Recent advances in unmanned aerial vehicle (UAV) technology have made UAVs an attractive possibility as an airborne calibration platform for astronomical facilities. This is especially true for arrays of telescopes spread over a large area such as the Cherenkov Telescope Array (CTA). In this paper, the feasibility of using UAVs to calibrate CTA is investigated. Assuming a UAV at 1km altitude above CTA, operating on astronomically clear nights with stratified, low atmospheric dust content, appropriate thermal protection for the calibration light source and an onboard photodiode to monitor its absolute light intensity, inter-calibration of CTA's telescopes of the same size class is found to be achievable with a 6 - 8 % uncertainty. For cross-calibration of different telescope size classes, a systematic uncertainty of 8 - 10 % is found to be achievable. Importantly, equipping the UAV with a multi-wavelength calibration light source affords us the ability to monitor the wavelength-dependent degradation of CTA telescopes' optical system, allowing us to not only maintain this 6 - 10 % uncertainty after the first few years of telescope deployment, but also to accurately account for the effect of multi-wavelength degradation on the cross-calibration of CTA by other techniques, namely with images of air showers and local muons. A UAV-based system thus provides CTA with several independent and complementary methods of cross-calibrating the optical throughput of individual telescopes. Furthermore, housing environmental sensors on the UAV system allows us to not only minimise the systematic uncertainty associated with the atmospheric transmission of the calibration signal, it also allows us to map the dust content above CTA as well as monitor the temperature, humidity and pressure profiles of the first kilometre of atmosphere above CTA with each UAV flight.

Variability And Uncertainty Analysis Of Contaminant Transport Model Using Fuzzy Latin Hypercube Sampling Technique

NASA Astrophysics Data System (ADS)

Kumar, V.; Nayagum, D.; Thornton, S.; Banwart, S.; Schuhmacher2, M.; Lerner, D.

2006-12-01

Characterization of uncertainty associated with groundwater quality models is often of critical importance, as for example in cases where environmental models are employed in risk assessment. Insufficient data, inherent variability and estimation errors of environmental model parameters introduce uncertainty into model predictions. However, uncertainty analysis using conventional methods such as standard Monte Carlo sampling (MCS) may not be efficient, or even suitable, for complex, computationally demanding models and involving different nature of parametric variability and uncertainty. General MCS or variant of MCS such as Latin Hypercube Sampling (LHS) assumes variability and uncertainty as a single random entity and the generated samples are treated as crisp assuming vagueness as randomness. Also when the models are used as purely predictive tools, uncertainty and variability lead to the need for assessment of the plausible range of model outputs. An improved systematic variability and uncertainty analysis can provide insight into the level of confidence in model estimates, and can aid in assessing how various possible model estimates should be weighed. The present study aims to introduce, Fuzzy Latin Hypercube Sampling (FLHS), a hybrid approach of incorporating cognitive and noncognitive uncertainties. The noncognitive uncertainty such as physical randomness, statistical uncertainty due to limited information, etc can be described by its own probability density function (PDF); whereas the cognitive uncertainty such estimation error etc can be described by the membership function for its fuzziness and confidence interval by ?-cuts. An important property of this theory is its ability to merge inexact generated data of LHS approach to increase the quality of information. The FLHS technique ensures that the entire range of each variable is sampled with proper incorporation of uncertainty and variability. A fuzzified statistical summary of the model results will produce indices of sensitivity and uncertainty that relate the effects of heterogeneity and uncertainty of input variables to model predictions. The feasibility of the method is validated to assess uncertainty propagation of parameter values for estimation of the contamination level of a drinking water supply well due to transport of dissolved phenolics from a contaminated site in the UK.

Bayesian Methods for Effective Field Theories

NASA Astrophysics Data System (ADS)

Wesolowski, Sarah

Microscopic predictions of the properties of atomic nuclei have reached a high level of precision in the past decade. This progress mandates improved uncertainty quantification (UQ) for a robust comparison of experiment with theory. With the uncertainty from many-body methods under control, calculations are now sensitive to the input inter-nucleon interactions. These interactions include parameters that must be fit to experiment, inducing both uncertainty from the fit and from missing physics in the operator structure of the Hamiltonian. Furthermore, the implementation of the inter-nucleon interactions is not unique, which presents the additional problem of assessing results using different interactions. Effective field theories (EFTs) take advantage of a separation of high- and low-energy scales in the problem to form a power-counting scheme that allows the organization of terms in the Hamiltonian based on their expected contribution to observable predictions. This scheme gives a natural framework for quantification of uncertainty due to missing physics. The free parameters of the EFT, called the low-energy constants (LECs), must be fit to data, but in a properly constructed EFT these constants will be natural-sized, i.e., of order unity. The constraints provided by the EFT, namely the size of the systematic uncertainty from truncation of the theory and the natural size of the LECs, are assumed information even before a calculation is performed or a fit is done. Bayesian statistical methods provide a framework for treating uncertainties that naturally incorporates prior information as well as putting stochastic and systematic uncertainties on an equal footing. For EFT UQ Bayesian methods allow the relevant EFT properties to be incorporated quantitatively as prior probability distribution functions (pdfs). Following the logic of probability theory, observable quantities and underlying physical parameters such as the EFT breakdown scale may be expressed as pdfs that incorporate the prior pdfs. Problems of model selection, such as distinguishing between competing EFT implementations, are also natural in a Bayesian framework. In this thesis we focus on two complementary topics for EFT UQ using Bayesian methods--quantifying EFT truncation uncertainty and parameter estimation for LECs. Using the order-by-order calculations and underlying EFT constraints as prior information, we show how to estimate EFT truncation uncertainties. We then apply the result to calculating truncation uncertainties on predictions of nucleon-nucleon scattering in chiral effective field theory. We apply model-checking diagnostics to our calculations to ensure that the statistical model of truncation uncertainty produces consistent results. A framework for EFT parameter estimation based on EFT convergence properties and naturalness is developed which includes a series of diagnostics to ensure the extraction of the maximum amount of available information from data to estimate LECs with minimal bias. We develop this framework using model EFTs and apply it to the problem of extrapolating lattice quantum chromodynamics results for the nucleon mass. We then apply aspects of the parameter estimation framework to perform case studies in chiral EFT parameter estimation, investigating a possible operator redundancy at fourth order in the chiral expansion and the appropriate inclusion of truncation uncertainty in estimating LECs.

Optimal surveys for weak-lensing tomography

NASA Astrophysics Data System (ADS)

Amara, Adam; Réfrégier, Alexandre

2007-11-01

Weak-lensing surveys provide a powerful probe of dark energy through the measurement of the mass distribution of the local Universe. A number of ground-based and space-based surveys are being planned for this purpose. Here, we study the optimal strategy for these future surveys using the joint constraints on the equation-of-state parameter wn and its evolution wa as a figure of merit by considering power spectrum tomography. For this purpose, we first consider an `ideal' survey which is both wide and deep and exempt from systematics. We find that such a survey has great potential for dark energy studies, reaching 1σ precisions of 1 and 10 per cent on the two parameters, respectively. We then study the relative impact of various limitations by degrading this ideal survey. In particular, we consider the effect of sky coverage, survey depth, shape measurement systematics, photometric redshift systematics and uncertainties in the non-linear power spectrum predictions. We find that, for a given observing time, it is always advantageous to choose a wide rather than a deep survey geometry. We also find that the dark energy constraints from power spectrum tomography are robust to photometric redshift errors and catastrophic failures, if a spectroscopic calibration sample of 104-105 galaxies are available. The impact of these systematics is small compared to the limitations that come from potential uncertainties in the power spectrum, due to shear measurement and theoretical errors. To help the planning of future surveys, we summarize our results with comprehensive scaling relations which avoid the need for full Fisher matrix calculations.

SU-E-T-659: Quantitative Evaluation of Patient Setup Accuracy of Stereotactic Radiotherapy with the Frameless 6D-ExacTrac System Using Statistical Modeling

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

Keeling, V; Jin, H; Hossain, S

2015-06-15

Purpose: To evaluate patient setup accuracy and quantify individual and cumulative positioning uncertainties associated with different hardware and software components of the stereotactic radiotherapy (SRS/SRT) with the frameless-6D-ExacTrac system. Methods: A statistical model was used to evaluate positioning uncertainties of the different components of SRS/SRT treatment with the BrainLAB 6D-ExacTrac system using the positioning shifts of 35 patients having cranial lesions (49 total lesions treated in 1, 3, 5 fractions). All these patients were immobilized with rigid head-and-neck masks, simulated with BrainLAB-localizer and planned with iPlan treatment planning system. Infrared imaging (IR) was used initially to setup patients. Then, stereoscopicmore » x-ray images (XC) were acquired and registered to corresponding digitally-reconstructed-radiographs using bony-anatomy matching to calculate 6D-translational and rotational shifts. When the shifts were within tolerance (0.7mm and 1°), treatment was initiated. Otherwise corrections were applied and additional x-rays were acquired (XV) to verify that patient position was within tolerance. Results: The uncertainties from the mask, localizer, IR-frame, x-ray imaging, MV and kV isocentricity were quantified individually. Mask uncertainty (Translational: Lateral, Longitudinal, Vertical; Rotational: Pitch, Roll, Yaw) was the largest and varied with patients in the range (−1.05−1.50mm, −5.06–3.57mm, −5.51−3.49mm; −1.40−2.40°, −1.24−1.74°, and −2.43−1.90°) obtained from mean of XC shifts for each patient. Setup uncertainty in IR positioning (0.88,2.12,1.40mm, and 0.64,0.83,0.96°) was extracted from standard-deviation of XC. Systematic uncertainties of the localizer (−0.03,−0.01,0.03mm, and −0.03,0.00,−0.01°) and frame (0.18,0.25,−1.27mm,−0.32,0.18, and 0.47°) were extracted from means of all XV setups and mean of all XC distributions, respectively. Uncertainties in isocentricity of the MV radiotherapy machine were (0.27,0.24,0.34mm) and kV-imager (0.15,−0.4,0.21mm). Conclusion: A statistical model was developed to evaluate the individual and cumulative systematic and random uncertainties induced by the different hardware and software components of the 6D-ExacTrac-system. The immobilization mask was associated with the largest positioning uncertainty.« less

Uncertainty and Sensitivity Analyses of a Pebble Bed HTGR Loss of Cooling Event

DOE PAGES

Strydom, Gerhard

2013-01-01

The Very High Temperature Reactor Methods Development group at the Idaho National Laboratory identified the need for a defensible and systematic uncertainty and sensitivity approach in 2009. This paper summarizes the results of an uncertainty and sensitivity quantification investigation performed with the SUSA code, utilizing the International Atomic Energy Agency CRP 5 Pebble Bed Modular Reactor benchmark and the INL code suite PEBBED-THERMIX. Eight model input parameters were selected for inclusion in this study, and after the input parameters variations and probability density functions were specified, a total of 800 steady state and depressurized loss of forced cooling (DLOFC) transientmore » PEBBED-THERMIX calculations were performed. The six data sets were statistically analyzed to determine the 5% and 95% DLOFC peak fuel temperature tolerance intervals with 95% confidence levels. It was found that the uncertainties in the decay heat and graphite thermal conductivities were the most significant contributors to the propagated DLOFC peak fuel temperature uncertainty. No significant differences were observed between the results of Simple Random Sampling (SRS) or Latin Hypercube Sampling (LHS) data sets, and use of uniform or normal input parameter distributions also did not lead to any significant differences between these data sets.« less

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for deposited material and external doses. Volume 2: Appendices

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

Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M.

1997-12-01

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library ofmore » uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA deposited material and external dose models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on deposited material and external doses, (4) short biographies of the experts, and (5) the aggregated results of their responses.« less

Differentiating intolerance of uncertainty from three related but distinct constructs.

PubMed

Rosen, Natalie O; Ivanova, Elena; Knäuper, Bärbel

2014-01-01

Individual differences in uncertainty have been associated with heightened anxiety, stress and approach-oriented coping. Intolerance of uncertainty (IU) is a trait characteristic that arises from negative beliefs about uncertainty and its consequences. Researchers have established the central role of IU in the development of problematic worry and maladaptive coping, highlighting the importance of this construct to anxiety disorders. However, there is a need to improve our understanding of the phenomenology of IU. The goal of this paper was to present hypotheses regarding the similarities and differences between IU and three related constructs--intolerance of ambiguity, uncertainty orientation, and need for cognitive closure--and to call for future empirical studies to substantiate these hypotheses. To assist with achieving this goal, we conducted a systematic review of the literature, which also served to identify current gaps in knowledge. This paper differentiates these constructs by outlining each definition and general approaches to assessment, reviewing the existing empirical relations, and proposing theoretical similarities and distinctions. Findings may assist researchers in selecting the appropriate construct to address their research questions. Future research directions for the application of these constructs, particularly within the field of clinical and health psychology, are discussed.

The Fermi Galactic Center GeV excess and implications for dark matter

DOE PAGES

Ackermann, M.; Ajello, M.; Albert, A.; ...

2017-05-04

Here, the region around the Galactic Center (GC) is now well established to be brighter at energies of a few GeV than what is expected from conventional models of diffuse gamma-ray emission and catalogs of known gamma-ray sources. We study the GeV excess using 6.5 yr of data from the Fermi Large Area Telescope. We characterize the uncertainty of the GC excess spectrum and morphology due to uncertainties in cosmic-ray source distributions and propagation, uncertainties in the distribution of interstellar gas in the Milky Way, and uncertainties due to a potential contribution from the Fermi bubbles. We also evaluate uncertaintiesmore » in the excess properties due to resolved point sources of gamma rays. The GC is of particular interest, as it would be expected to have the brightest signal from annihilation of weakly interacting massive dark matter (DM) particles. However, control regions along the Galactic plane, where a DM signal is not expected, show excesses of similar amplitude relative to the local background. Furthermore, based on the magnitude of the systematic uncertainties, we conservatively report upper limits for the annihilation cross-section as a function of particle mass and annihilation channel.« less

VizieR Online Data Catalog: Atomic mass excesses (Schatz+, 2017)

NASA Astrophysics Data System (ADS)

Schatz, H.; Ong, W.-J.

2018-03-01

X-ray burst model predictions of light curves and the final composition of the nuclear ashes are affected by uncertain nuclear masses. However, not all of these masses are determined experimentally with sufficient accuracy. Here we identify the remaining nuclear mass uncertainties in X-ray burst models using a one-zone model that takes into account the changes in temperature and density evolution caused by changes in the nuclear physics. Two types of bursts are investigated-a typical mixed H/He burst with a limited rapid proton capture process (rp-process) and an extreme mixed H/He burst with an extended rp-process. When allowing for a 3σ variation, only three remaining nuclear mass uncertainties affect the light-curve predictions of a typical H/He burst (27P, 61Ga, and 65As), and only three additional masses affect the composition strongly (80Zr, 81Zr, and 82Nb). A larger number of mass uncertainties remain to be addressed for the extreme H/He burst, with the most important being 58Zn, 61Ga, 62Ge, 65As, 66Se, 78Y, 79Y, 79Zr, 80Zr, 81Zr, 82Zr, 82Nb, 83Nb, 86Tc, 91Rh, 95Ag, 98Cd, 99In, 100In, and 101In. The smallest mass uncertainty that still impacts composition significantly when varied by 3σ is 85Mo with 16keV uncertainty. For one of the identified masses, 27P, we use the isobaric mass multiplet equation to improve the mass uncertainty, obtaining an atomic mass excess of -716(7)keV. The results provide a roadmap for future experiments at advanced rare isotope beam facilities, where all the identified nuclides are expected to be within reach for precision mass measurements. (1 data file).

Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites

USGS Publications Warehouse

Chen, Mingshi; Senay, Gabriel B.; Singh, Ramesh K.; Verdin, James P.

2016-01-01

Evapotranspiration (ET) is an important component of the water cycle – ET from the land surface returns approximately 60% of the global precipitation back to the atmosphere. ET also plays an important role in energy transport among the biosphere, atmosphere, and hydrosphere. Current regional to global and daily to annual ET estimation relies mainly on surface energy balance (SEB) ET models or statistical and empirical methods driven by remote sensing data and various climatological databases. These models have uncertainties due to inevitable input errors, poorly defined parameters, and inadequate model structures. The eddy covariance measurements on water, energy, and carbon fluxes at the AmeriFlux tower sites provide an opportunity to assess the ET modeling uncertainties. In this study, we focused on uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model for ET estimation at multiple AmeriFlux tower sites with diverse land cover characteristics and climatic conditions. The 8-day composite 1-km MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) was used as input land surface temperature for the SSEBop algorithms. The other input data were taken from the AmeriFlux database. Results of statistical analysis indicated that the SSEBop model performed well in estimating ET with an R2 of 0.86 between estimated ET and eddy covariance measurements at 42 AmeriFlux tower sites during 2001–2007. It was encouraging to see that the best performance was observed for croplands, where R2 was 0.92 with a root mean square error of 13 mm/month. The uncertainties or random errors from input variables and parameters of the SSEBop model led to monthly ET estimates with relative errors less than 20% across multiple flux tower sites distributed across different biomes. This uncertainty of the SSEBop model lies within the error range of other SEB models, suggesting systematic error or bias of the SSEBop model is within the normal range. This finding implies that the simplified parameterization of the SSEBop model did not significantly affect the accuracy of the ET estimate while increasing the ease of model setup for operational applications. The sensitivity analysis indicated that the SSEBop model is most sensitive to input variables, land surface temperature (LST) and reference ET (ETo); and parameters, differential temperature (dT), and maximum ET scalar (Kmax), particularly during the non-growing season and in dry areas. In summary, the uncertainty assessment verifies that the SSEBop model is a reliable and robust method for large-area ET estimation. The SSEBop model estimates can be further improved by reducing errors in two input variables (ETo and LST) and two key parameters (Kmax and dT).

Rational decision-making in mental health: the role of systematic reviews.

PubMed

Gilbody, Simon M.; Petticrew, Mark

1999-09-01

BACKGROUND: "Systematic reviews" have come to be recognized as the most rigorous method of summarizing confusing and often contradictory primary research in a transparent and reproducible manner. Their greatest impact has been in the summarization of epidemiological literature - particularly that relating to clinical effectiveness. Systematic reviews also have a potential to inform rational decision-making in healthcare policy and to form a component of economic evaluation. AIMS OF THE STUDY: This article aims to introduce the rationale behind systematic reviews and, using examples from mental health, to introduce the strengths and limitations of systematic reviews, particularly in informing mental health policy and economic evaluation. METHODS: Examples are selected from recent controversies surrounding the introduction of new psychiatric drugs (anti-depressants and anti-schizophrenia drugs) and methods of delivering psychiatric care in the community (case management and assertive community treatment). The potential for systematic reviews to (i) produce best estimates of clinical efficacy and effectiveness, (ii) aid economic evaluation and policy decision-making and (iii) highlight gaps in the primary research knowledge base are discussed. Lastly examples are selected from outside mental health to show how systematic reviews have a potential to be explicitly used in economic and health policy evaluation. RESULTS: Systematic reviews produce the best estimates of clinical efficacy, which can form an important component of economic evaluation. Importantly, serious methodological flaws and areas of uncertainty in the primary research literature are identified within an explicit framework. Summary indices of clinical effectiveness can be produced, but it is difficult to produce such summary indices of cost effectiveness by pooling economic data from primary studies. Modelling is commonly used in economic and policy evaluation. Here, systematic reviews can provide the best estimates of effectiveness and, importantly, highlight areas of uncertainty that can be used in "sensitivity analysis". DISCUSSION: Systematic reviews are an important recent methodological advance, the potential for which has only begun to be realized in mental health. This use of systematic reviews is probably most advanced in producing critical summaries of clinical effectiveness data. Systematic reviews cannot produce valid and believable conclusions when the primary research literature is of poor quality. An important function of systematic reviews will be in highlighting this poor quality research which is of little use in mental health decision making. IMPLICATIONS FOR HEALTH PROVISION: Health care provision should be both clinically and cost effective. Systematic reviews are a key component in ensuring that this goal is achieved. IMPLICATIONS FOR HEALTH POLICIES: Systematic reviews have potential to inform health policy. Examples presented show that health policy is often made without due consideration of the research evidence. Systematic reviews can provide robust and believable answers, which can help inform rational decision-making. Importantly, systematic reviews can highlight the need for important primary research and can inform the design of this research such that it provides answers that will help in forming healthcare policy. IMPLICATIONS FOR FURTHER RESEARCH: Systematic reviews should precede costly (and often unnecessary) primary research. Many areas of health policy and practice have yet to be evaluated using systematic review methodology. Methods for the summarization of economic data are methodologically complex and deserve further research

Characterizing unknown systematics in large scale structure surveys

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

Agarwal, Nishant; Ho, Shirley; Myers, Adam D.

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data,more » we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.« less

Theory of choice in bandit, information sampling and foraging tasks.

PubMed

Averbeck, Bruno B

2015-03-01

Decision making has been studied with a wide array of tasks. Here we examine the theoretical structure of bandit, information sampling and foraging tasks. These tasks move beyond tasks where the choice in the current trial does not affect future expected rewards. We have modeled these tasks using Markov decision processes (MDPs). MDPs provide a general framework for modeling tasks in which decisions affect the information on which future choices will be made. Under the assumption that agents are maximizing expected rewards, MDPs provide normative solutions. We find that all three classes of tasks pose choices among actions which trade-off immediate and future expected rewards. The tasks drive these trade-offs in unique ways, however. For bandit and information sampling tasks, increasing uncertainty or the time horizon shifts value to actions that pay-off in the future. Correspondingly, decreasing uncertainty increases the relative value of actions that pay-off immediately. For foraging tasks the time-horizon plays the dominant role, as choices do not affect future uncertainty in these tasks.

Cosmic shear bias and calibration in dark energy studies

NASA Astrophysics Data System (ADS)

Taylor, A. N.; Kitching, T. D.

2018-07-01

With the advent of large-scale weak lensing surveys there is a need to understand how realistic, scale-dependent systematics bias cosmic shear and dark energy measurements, and how they can be removed. Here, we show how spatially varying image distortions are convolved with the shear field, mixing convergence E and B modes, and bias the observed shear power spectrum. In practise, many of these biases can be removed by calibration to data or simulations. The uncertainty in this calibration is marginalized over, and we calculate how this propagates into parameter estimation and degrades the dark energy Figure-of-Merit. We find that noise-like biases affect dark energy measurements the most, while spikes in the bias power have the least impact. We argue that, in order to remove systematic biases in cosmic shear surveys and maintain statistical power, effort should be put into improving the accuracy of the bias calibration rather than minimizing the size of the bias. In general, this appears to be a weaker condition for bias removal. We also investigate how to minimize the size of the calibration set for a fixed reduction in the Figure-of-Merit. Our results can be used to correctly model the effect of biases and calibration on a cosmic shear survey, assess their impact on the measurement of modified gravity and dark energy models, and to optimize survey and calibration requirements.

Attention Restoration Theory: A systematic review of the attention restoration potential of exposure to natural environments.

PubMed

Ohly, Heather; White, Mathew P; Wheeler, Benedict W; Bethel, Alison; Ukoumunne, Obioha C; Nikolaou, Vasilis; Garside, Ruth

2016-01-01

Attention Restoration Theory (ART) suggests the ability to concentrate may be restored by exposure to natural environments. Although widely cited, it is unclear as to the quantity of empirical evidence that supports this. A systematic review regarding the impact of exposure to natural environments on attention was conducted. Seven electronic databases were searched. Studies were included if (1) they were natural experiments, randomized investigations, or recorded "before and after" measurements; (2) compared natural and nonnatural/other settings; and (3) used objective measures of attention. Screening of articles for inclusion, data extraction, and quality appraisal were performed by one reviewer and checked by another. Where possible, random effects meta-analysis was used to pool effect sizes. Thirty-one studies were included. Meta-analyses provided some support for ART, with significant positive effects of exposure to natural environments for three measures (Digit Span Forward, Digit Span Backward, and Trail Making Test B). The remaining 10 meta-analyses did not show marked beneficial effects. Meta-analysis was limited by small numbers of investigations, small samples, heterogeneity in reporting of study quality indicators, and heterogeneity of outcomes. This review highlights the diversity of evidence around ART in terms of populations, study design, and outcomes. There is uncertainty regarding which aspects of attention may be affected by exposure to natural environments.

Relevance of hydro-climatic change projection and monitoring for assessment of water cycle changes in the Arctic.

PubMed

Bring, Arvid; Destouni, Georgia

2011-06-01

Rapid changes to the Arctic hydrological cycle challenge both our process understanding and our ability to find appropriate adaptation strategies. We have investigated the relevance and accuracy development of climate change projections for assessment of water cycle changes in major Arctic drainage basins. Results show relatively good agreement of climate model projections with observed temperature changes, but high model inaccuracy relative to available observation data for precipitation changes. Direct observations further show systematically larger (smaller) runoff than precipitation increases (decreases). This result is partly attributable to uncertainties and systematic bias in precipitation observations, but still indicates that some of the observed increase in Arctic river runoff is due to water storage changes, for example melting permafrost and/or groundwater storage changes, within the drainage basins. Such causes of runoff change affect sea level, in addition to ocean salinity, and inland water resources, ecosystems, and infrastructure. Process-based hydrological modeling and observations, which can resolve changes in evapotranspiration, and groundwater and permafrost storage at and below river basin scales, are needed in order to accurately interpret and translate climate-driven precipitation changes to changes in freshwater cycling and runoff. In contrast to this need, our results show that the density of Arctic runoff monitoring has become increasingly biased and less relevant by decreasing most and being lowest in river basins with the largest expected climatic changes.

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

EPA Science Inventory

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this stu...

Removal of Asperger's syndrome from the DSM V: community response to uncertainty.

PubMed

Parsloe, Sarah M; Babrow, Austin S

2016-01-01

The May 2013 release of the new version of the Diagnostic and Statistical Manual of Mental Disorders (DSM V) subsumed Asperger's syndrome under the wider diagnostic label of autism spectrum disorder (ASD). The revision has created much uncertainty in the community affected by this condition. This study uses problematic integration theory and thematic analysis to investigate how participants in Wrong Planet, a large online community associated with autism and Asperger's syndrome, have constructed these uncertainties. The analysis illuminates uncertainties concerning both the likelihood of diagnosis and value of diagnosis, and it details specific issues within these two general areas of uncertainty. The article concludes with both conceptual and practical implications.

Uncertainty Reduction using Bayesian Inference and Sensitivity Analysis: A Sequential Approach to the NASA Langley Uncertainty Quantification Challenge

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar

2016-01-01

This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.

[Jurisdictions on the reimbursement of new medical technologies by public health insurance: A systematic review].

PubMed

Ex, Patricia; Felgner, Susanne; Henschke, Cornelia

2018-04-01

In Germany reimbursement for new medical technologies is often enforced before a social court. It is likely that these judicial decisions also affect the sickness funds' decisions on requests for reimbursement and thus patient access to new technologies in general. The aim of this study was to identify the technologies that have repeatedly generated court actions and whether these actions have been successful. The focus was on differences between sectors, technology groups and indications. Based on this, we analysed in a case study whether judicial decisions on the reimbursement of the same technologies vary across the years. Based on a systematic review, we identified judicial decisions of German social courts on new technologies for the years 2011 to 2016. The analysis included social court decisions on reimbursements for technologies used in the treatment of individual patients. 284 judicial decisions on new technologies were considered in the analysis. In one third of the cases, the sickness funds were required to reimburse the costs, with a higher percentage in inpatient than in outpatient care. Technologies used in treatment of diseases of the eyes and the ears were granted most frequently. In cases involving similar circumstances the social courts sometimes came to conflicting decisions; these decisions are, in part, contradictory to subsequent assessments by the Joint Federal Committee (G-BA). Decisions as to whether reimbursement for new technologies is granted or not do not appear to follow a systematic approach. In the context of the seemingly innovation-friendly policy in inpatient care, there is uncertainty with regard to the "generally accepted state of medical knowledge." It is problematic for both patients and their treating physicians that over a number of years legal proceedings are being initiated for technologies that have not been subjected to a systematic assessment of their benefit. Copyright © 2018. Published by Elsevier GmbH.

An adaptive response surface method for crashworthiness optimization

NASA Astrophysics Data System (ADS)

Shi, Lei; Yang, Ren-Jye; Zhu, Ping

2013-11-01

Response surface-based design optimization has been commonly used for optimizing large-scale design problems in the automotive industry. However, most response surface models are built by a limited number of design points without considering data uncertainty. In addition, the selection of a response surface in the literature is often arbitrary. This article uses a Bayesian metric to systematically select the best available response surface among several candidates in a library while considering data uncertainty. An adaptive, efficient response surface strategy, which minimizes the number of computationally intensive simulations, was developed for design optimization of large-scale complex problems. This methodology was demonstrated by a crashworthiness optimization example.

Constraints on spin-dependent parton distributions at large x from global QCD analysis

DOE PAGES

Jimenez-Delgado, P.; Avakian, H.; Melnitchouk, W.

2014-09-28

This study investigate the behavior of spin-dependent parton distribution functions (PDFs) at large parton momentum fractions x in the context of global QCD analysis. We explore the constraints from existing deep-inelastic scattering data, and from theoretical expectations for the leading x → 1 behavior based on hard gluon exchange in perturbative QCD. Systematic uncertainties from the dependence of the PDFs on the choice of parametrization are studied by considering functional forms motivated by orbital angular momentum arguments. Finally, we quantify the reduction in the PDF uncertainties that may be expected from future high-x data from Jefferson Lab at 12 GeV.

Measurement of the absolute branching fraction of D + → $$\\bar{K}$$ 0 e + ν e via $$\\bar{K}$$0 → π0 π0

DOE PAGES

Ablikim, M.; Achasov, M. N.; Ai, X. C.; ...

2016-11-01

By analyzing 2.93 fb–1 data collected at the center-of-mass energy with the BESIII detector, we measure the absolute branching fraction of the semileptonic decay D+ →more » $$\\bar{K}$$0 e+νe to be Β(D + → $$\\bar{K}$$ 0 e +ν e) = (8.59 ± 0.14 ± 0.21)% using $$\\bar{K}$$ 0 → K 0 s → π 0π 0, where the first uncertainty is statistical and the second systematic. Finally, our result is consistent with previous measurements within uncertainties..« less

New Methods for B Decay Constants and Form Factors from Lattice NRQCD

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

Davies, Christine; Hughes, Ciaran; Monahan, Christopher

We determine the normalisation of scalar and pseudo scalar current operators made from NonRelativistic QCD (NRQCD) b quarks and Highly Improved Staggered (HISQ) light quarks through O(αs∧QCD/mb). We use matrix elements of these operators to extract B meson decay constants and form factors and compare to those obtained using the standard vector and axial vector operators. We work on MILC second-generation 2+1+1 gluon field configurations, including those with physical light quarks in the sea. This provides a test of systematic uncertainties in these calculations and we find agreement between the results to the 2% level of uncertainty previously quoted.

New methods for B decay constants and form factors from Lattice NRQCD

NASA Astrophysics Data System (ADS)

Davies, Christine; Hughes, Ciaran; Monahan, Christopher

2018-03-01

We determine the normalisation of scalar and pseudo scalar current operators made from NonRelativistic QCD (NRQCD) b quarks and Highly Improved Staggered (HISQ) light quarks through O(αs∧QCD/mb). We use matrix elements of these operators to extract B meson decay constants and form factors and compare to those obtained using the standard vector and axial vector operators. We work on MILC second-generation 2+1+1 gluon field configurations, including those with physical light quarks in the sea. This provides a test of systematic uncertainties in these calculations and we find agreement between the results to the 2% level of uncertainty previously quoted.

Measurement of the absolute branching fraction of D + → $$\\bar{K}$$ 0 e + ν e via $$\\bar{K}$$0 → π0 π0

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

Ablikim, M.; Achasov, M. N.; Ai, X. C.

By analyzing 2.93 fb–1 data collected at the center-of-mass energy with the BESIII detector, we measure the absolute branching fraction of the semileptonic decay D+ →more » $$\\bar{K}$$0 e+νe to be Β(D + → $$\\bar{K}$$ 0 e +ν e) = (8.59 ± 0.14 ± 0.21)% using $$\\bar{K}$$ 0 → K 0 s → π 0π 0, where the first uncertainty is statistical and the second systematic. Finally, our result is consistent with previous measurements within uncertainties..« less

QCD sum rules study of meson-baryon sigma terms

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

Erkol, Gueray; Oka, Makoto; Turan, Guersevil

2008-11-01

The pion-baryon sigma terms and the strange-quark condensates of the octet and the decuplet baryons are calculated by employing the method of QCD sum rules. We evaluate the vacuum-to-vacuum transition matrix elements of two baryon interpolating fields in an external isoscalar-scalar field and use a Monte Carlo-based approach to systematically analyze the sum rules and the uncertainties in the results. We extract the ratios of the sigma terms, which have rather high accuracy and minimal dependence on QCD parameters. We discuss the sources of uncertainties and comment on possible strangeness content of the nucleon and the Delta.