Science.gov

Sample records for address scientific uncertainties

  1. Research strategies for addressing uncertainties

    USGS Publications Warehouse

    Busch, David E.; Brekke, Levi D.; Averyt, Kristen; Jardine, Angela; Welling, Leigh; Garfin, Gregg; Jardine, Angela; Merideth, Robert; Black, Mary; LeRoy, Sarah

    2013-01-01

    Research Strategies for Addressing Uncertainties builds on descriptions of research needs presented elsewhere in the book; describes current research efforts and the challenges and opportunities to reduce the uncertainties of climate change; explores ways to improve the understanding of changes in climate and hydrology; and emphasizes the use of research to inform decision making.

  2. Assessment of Uncertainty-Infused Scientific Argumentation

    ERIC Educational Resources Information Center

    Lee, Hee-Sun; Liu, Ou Lydia; Pallant, Amy; Roohr, Katrina Crotts; Pryputniewicz, Sarah; Buck, Zoë E.

    2014-01-01

    Though addressing sources of uncertainty is an important part of doing science, it has largely been neglected in assessing students' scientific argumentation. In this study, we initially defined a scientific argumentation construct in four structural elements consisting of claim, justification, uncertainty qualifier, and uncertainty…

  3. Optimal regeneration planning for old-growth forest: addressing scientific uncertainty in endangered species recovery through adaptive management

    USGS Publications Warehouse

    Moore, C.T.; Conroy, M.J.

    2006-01-01

    Stochastic and structural uncertainties about forest dynamics present challenges in the management of ephemeral habitat conditions for endangered forest species. Maintaining critical foraging and breeding habitat for the endangered red-cockaded woodpecker (Picoides borealis) requires an uninterrupted supply of old-growth forest. We constructed and optimized a dynamic forest growth model for the Piedmont National Wildlife Refuge (Georgia, USA) with the objective of perpetuating a maximum stream of old-growth forest habitat. Our model accommodates stochastic disturbances and hardwood succession rates, and uncertainty about model structure. We produced a regeneration policy that was indexed by current forest state and by current weight of evidence among alternative model forms. We used adaptive stochastic dynamic programming, which anticipates that model probabilities, as well as forest states, may change through time, with consequent evolution of the optimal decision for any given forest state. In light of considerable uncertainty about forest dynamics, we analyzed a set of competing models incorporating extreme, but plausible, parameter values. Under any of these models, forest silviculture practices currently recommended for the creation of woodpecker habitat are suboptimal. We endorse fully adaptive approaches to the management of endangered species habitats in which predictive modeling, monitoring, and assessment are tightly linked.

  4. Communicating scientific uncertainty.

    PubMed

    Fischhoff, Baruch; Davis, Alex L

    2014-09-16

    All science has uncertainty. Unless that uncertainty is communicated effectively, decision makers may put too much or too little faith in it. The information that needs to be communicated depends on the decisions that people face. Are they (i) looking for a signal (e.g., whether to evacuate before a hurricane), (ii) choosing among fixed options (e.g., which medical treatment is best), or (iii) learning to create options (e.g., how to regulate nanotechnology)? We examine these three classes of decisions in terms of how to characterize, assess, and convey the uncertainties relevant to each. We then offer a protocol for summarizing the many possible sources of uncertainty in standard terms, designed to impose a minimal burden on scientists, while gradually educating those whose decisions depend on their work. Its goals are better decisions, better science, and better support for science.

  5. Communicating scientific uncertainty

    PubMed Central

    Fischhoff, Baruch; Davis, Alex L.

    2014-01-01

    All science has uncertainty. Unless that uncertainty is communicated effectively, decision makers may put too much or too little faith in it. The information that needs to be communicated depends on the decisions that people face. Are they (i) looking for a signal (e.g., whether to evacuate before a hurricane), (ii) choosing among fixed options (e.g., which medical treatment is best), or (iii) learning to create options (e.g., how to regulate nanotechnology)? We examine these three classes of decisions in terms of how to characterize, assess, and convey the uncertainties relevant to each. We then offer a protocol for summarizing the many possible sources of uncertainty in standard terms, designed to impose a minimal burden on scientists, while gradually educating those whose decisions depend on their work. Its goals are better decisions, better science, and better support for science. PMID:25225390

  6. Programmatic methods for addressing contaminated volume uncertainties.

    SciTech Connect

    DURHAM, L.A.; JOHNSON, R.L.; RIEMAN, C.R.; SPECTOR, H.L.; Environmental Science Division; U.S. ARMY CORPS OF ENGINEERS BUFFALO DISTRICT

    2007-01-01

    Accurate estimates of the volumes of contaminated soils or sediments are critical to effective program planning and to successfully designing and implementing remedial actions. Unfortunately, data available to support the preremedial design are often sparse and insufficient for accurately estimating contaminated soil volumes, resulting in significant uncertainty associated with these volume estimates. The uncertainty in the soil volume estimates significantly contributes to the uncertainty in the overall project cost estimates, especially since excavation and off-site disposal are the primary cost items in soil remedial action projects. The Army Corps of Engineers Buffalo District's experience has been that historical contaminated soil volume estimates developed under the Formerly Utilized Sites Remedial Action Program (FUSRAP) often underestimated the actual volume of subsurface contaminated soils requiring excavation during the course of a remedial activity. In response, the Buffalo District has adopted a variety of programmatic methods for addressing contaminated volume uncertainties. These include developing final status survey protocols prior to remedial design, explicitly estimating the uncertainty associated with volume estimates, investing in predesign data collection to reduce volume uncertainties, and incorporating dynamic work strategies and real-time analytics in predesign characterization and remediation activities. This paper describes some of these experiences in greater detail, drawing from the knowledge gained at Ashland1, Ashland2, Linde, and Rattlesnake Creek. In the case of Rattlesnake Creek, these approaches provided the Buffalo District with an accurate predesign contaminated volume estimate and resulted in one of the first successful FUSRAP fixed-price remediation contracts for the Buffalo District.

  7. Programmatic methods for addressing contaminated volume uncertainties

    SciTech Connect

    Rieman, C.R.; Spector, H.L.; Durham, L.A.; Johnson, R.L.

    2007-07-01

    Accurate estimates of the volumes of contaminated soils or sediments are critical to effective program planning and to successfully designing and implementing remedial actions. Unfortunately, data available to support the pre-remedial design are often sparse and insufficient for accurately estimating contaminated soil volumes, resulting in significant uncertainty associated with these volume estimates. The uncertainty in the soil volume estimates significantly contributes to the uncertainty in the overall project cost estimates, especially since excavation and off-site disposal are the primary cost items in soil remedial action projects. The U.S. Army Corps of Engineers Buffalo District's experience has been that historical contaminated soil volume estimates developed under the Formerly Utilized Sites Remedial Action Program (FUSRAP) often underestimated the actual volume of subsurface contaminated soils requiring excavation during the course of a remedial activity. In response, the Buffalo District has adopted a variety of programmatic methods for addressing contaminated volume uncertainties. These include developing final status survey protocols prior to remedial design, explicitly estimating the uncertainty associated with volume estimates, investing in pre-design data collection to reduce volume uncertainties, and incorporating dynamic work strategies and real-time analytics in pre-design characterization and remediation activities. This paper describes some of these experiences in greater detail, drawing from the knowledge gained at Ashland 1, Ashland 2, Linde, and Rattlesnake Creek. In the case of Rattlesnake Creek, these approaches provided the Buffalo District with an accurate pre-design contaminated volume estimate and resulted in one of the first successful FUSRAP fixed-price remediation contracts for the Buffalo District. (authors)

  8. Climate negotiations under scientific uncertainty

    PubMed Central

    Barrett, Scott; Dannenberg, Astrid

    2012-01-01

    How does uncertainty about “dangerous” climate change affect the prospects for international cooperation? Climate negotiations usually are depicted as a prisoners’ dilemma game; collectively, countries are better off reducing their emissions, but self-interest impels them to keep on emitting. We provide experimental evidence, grounded in an analytical framework, showing that the fear of crossing a dangerous threshold can turn climate negotiations into a coordination game, making collective action to avoid a dangerous threshold virtually assured. These results are robust to uncertainty about the impact of crossing a threshold, but uncertainty about the location of the threshold turns the game back into a prisoners’ dilemma, causing cooperation to collapse. Our research explains the paradox of why countries would agree to a collective goal, aimed at reducing the risk of catastrophe, but act as if they were blind to this risk. PMID:23045685

  9. Addressing biological uncertainties in engineering gene circuits.

    PubMed

    Zhang, Carolyn; Tsoi, Ryan; You, Lingchong

    2016-04-18

    Synthetic biology has grown tremendously over the past fifteen years. It represents a new strategy to develop biological understanding and holds great promise for diverse practical applications. Engineering of a gene circuit typically involves computational design of the circuit, selection of circuit components, and test and optimization of circuit functions. A fundamental challenge in this process is the predictable control of circuit function due to multiple layers of biological uncertainties. These uncertainties can arise from different sources. We categorize these uncertainties into incomplete quantification of parts, interactions between heterologous components and the host, or stochastic dynamics of chemical reactions and outline potential design strategies to minimize or exploit them.

  10. Addressing uncertainty in adaptation planning for agriculture

    PubMed Central

    Vermeulen, Sonja J.; Challinor, Andrew J.; Thornton, Philip K.; Campbell, Bruce M.; Eriyagama, Nishadi; Vervoort, Joost M.; Kinyangi, James; Jarvis, Andy; Läderach, Peter; Ramirez-Villegas, Julian; Nicklin, Kathryn J.; Hawkins, Ed; Smith, Daniel R.

    2013-01-01

    We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop–climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty. PMID:23674681

  11. Addressing uncertainty in adaptation planning for agriculture.

    PubMed

    Vermeulen, Sonja J; Challinor, Andrew J; Thornton, Philip K; Campbell, Bruce M; Eriyagama, Nishadi; Vervoort, Joost M; Kinyangi, James; Jarvis, Andy; Läderach, Peter; Ramirez-Villegas, Julian; Nicklin, Kathryn J; Hawkins, Ed; Smith, Daniel R

    2013-05-21

    We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop-climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.

  12. 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

  13. 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.

  14. Addressing submarine geohazards through scientific drilling

    NASA Astrophysics Data System (ADS)

    Camerlenghi, A.

    2009-04-01

    Natural submarine geohazards (earthquakes, volcanic eruptions, landslides, volcanic island flank collapses) are geological phenomena originating at or below the seafloor leading to a situation of risk for off-shore and on-shore structures and the coastal population. Addressing submarine geohazards means understanding their spatial and temporal variability, the pre-conditioning factors, their triggers, and the physical processes that control their evolution. Such scientific endeavour is nowadays considered by a large sector of the international scientific community as an obligation in order to contribute to the mitigation of the potentially destructive societal effects of submarine geohazards. The study of submarine geohazards requires a multi-disciplinary scientific approach: geohazards must be studied through their geological record; active processes must be monitored; geohazard evolution must be modelled. Ultimately, the information must be used for the assessment of vulnerability, risk analysis, and development of mitigation strategies. In contrast with the terrestrial environment, the oceanic environment is rather hostile to widespread and fast application of high-resolution remote sensing techniques, accessibility for visual inspection, sampling and installation of monitoring stations. Scientific Drilling through the IODP (including the related pre site-survey investigations, sampling, logging and in situ measurements capability, and as a platform for deployment of long term observatories at the surface and down-hole) can be viewed as the centre of gravity of an international, coordinated, multi-disciplinary scientific approach to address submarine geohazards. The IODP Initial Science Plan expiring in 2013 does not address openly geohazards among the program scientific objectives. Hazards are referred to mainly in relation to earthquakes and initiatives towards the understanding of seismogenesis. Notably, the only drilling initiative presently under way is the

  15. Uncertainty as a fundamental scientific value.

    PubMed

    Clegg, Joshua W

    2010-09-01

    The author argues that, though social scientists generally value tolerance for ambiguity, and some even assert a fundamental indeterminacy in human systems, there is still a discipline-wide discomfort with uncertainty and ambiguity. It is argued that this distaste for uncertainty derives from a distorted view of the classical physical sciences, a view that ignores the essentially critical and radical foundations of scientific practice. The drive for certainty, it is argued, is essentially unscientific, in that certain, or adequate, forms of knowledge can only recapitulate the already known and in their dogmatic and institutionalized forms prevent the development of genuinely new knowledge. In contrast, uncertainty is defended as a positive condition, generative of new knowledge because it is open to discovery and to the mystery of the other. The conclusion drawn from this analysis is that the social sciences can only progress if uncertainty, or mystery, is protected and cultivated through a scientific discourse constituted in local and concrete terms (rather than in general and universal ones) and through a self-reflective and self-critical research praxis.

  16. Addressing contrasting cognitive models in scientific collaboration

    NASA Astrophysics Data System (ADS)

    Diviacco, P.

    2012-04-01

    If the social aspects of scientific communities and their internal dynamics is starting to be recognized and acknowledged in the everyday lives of scientists, it is rather difficult for them to find tools that could support their activities consistently with this perspective. Issues span from gathering researchers to mutual awareness, from information sharing to building meaning, with the last one being particularly critical in research fields as the geo-sciences, that deal with the reconstruction of unique, often non-reproducible, and contingent processes. Reasoning here is, in fact, mainly abductive, allowing multiple and concurrent explanations for the same phenomenon to coexist. Scientists bias one hypothesis over another not only on strictly logical but also on sociological motivations. Following a vision, scientists tend to evolve and isolate themselves from other scientists creating communities characterized by different cognitive models, so that after some time these become incompatible and scientists stop understanding each other. We address these problems as a communication issue so that the classic distinction into three levels (syntactic, semantic and pragmatic) can be used. At the syntactic level, we highlight non-technical obstacles that condition interoperability and data availability and transparency. At the semantic level, possible incompatibilities of cognitive models are particularly evident, so that using ontologies, cross-domain reconciliation should be applied. This is a very difficult task to perform since the projection of knowledge by scientists, in the designated community, is political and thus can create a lot of tension. The strategy we propose to overcome these issues pertains to pragmatics, in the sense that it is intended to acknowledge the cultural and personal factors each partner brings into the collaboration and is based on the idea that meaning should remain a flexible and contingent representation of possibly divergent views

  17. Addressing uncertainty in rock properties through geostatistical simulation

    SciTech Connect

    McKenna, S.A.; Rautman, A.; Cromer, M.V.; Zelinski, W.P.

    1996-09-01

    Fracture and matrix properties in a sequence of unsaturated, welded tuffs at Yucca Mountain, Nevada, are modeled in two-dimensional cross-sections through geostatistical simulation. In the absence of large amounts of sample data, an n interpretive, deterministic, stratigraphic model is coupled with a gaussian simulation algorithm to constrain realizations of both matrix porosity and fracture frequency. Use of the deterministic, stratigraphic model imposes scientific judgment, in the form of a conceptual geologic model, onto the property realizations. Linear coregionalization and a regression relationship between matrix porosity and matrix hydraulic conductivity are used to generate realizations of matrix hydraulic conductivity. Fracture-frequency simulations conditioned on the stratigraphic model represent one class of fractures (cooling fractures) in the conceptual model of the geology. A second class of fractures (tectonic fractures) is conceptualized as fractures that cut across strata vertically and includes discrete features such as fault zones. Indicator geostatistical simulation provides locations of this second class of fractures. The indicator realizations are combined with the realizations of fracture spacing to create realizations of fracture frequency that are a combination of both classes of fractures. Evaluations of the resulting realizations include comparing vertical profiles of rock properties within the model to those observed in boreholes and checking intra-unit property distributions against collected data. Geostatistical simulation provides an efficient means of addressing spatial uncertainty in dual continuum rock properties.

  18. Addressing structural and observational uncertainty in resource management.

    PubMed

    Fackler, Paul; Pacifici, Krishna

    2014-01-15

    Most natural resource management and conservation problems are plagued with high levels of uncertainties, which make good decision making difficult. Although some kinds of uncertainties are easily incorporated into decision making, two types of uncertainty present more formidable difficulties. The first, structural uncertainty, represents our imperfect knowledge about how a managed system behaves. The second, observational uncertainty, arises because the state of the system must be inferred from imperfect monitoring systems. The former type of uncertainty has been addressed in ecology using Adaptive Management (AM) and the latter using the Partially Observable Markov Decision Processes (POMDP) framework. Here we present a unifying framework that extends standard POMDPs and encompasses both standard POMDPs and AM. The approach allows any system variable to be observed or not observed and uses any relevant observed variable to update beliefs about unknown variables and parameters. This extends standard AM, which only uses realizations of the state variable to update beliefs and extends standard POMDP by allowing more general stochastic dependence among the observable variables and the state variables. This framework enables both structural and observational uncertainty to be simultaneously modeled. We illustrate the features of the extended POMDP framework with an example.

  19. Scientific uncertainty and its relevance to science education

    NASA Astrophysics Data System (ADS)

    Ruggeri, Nancy Lee

    Uncertainty is inherent to scientific methods and practices, yet is it rarely explicitly discussed in science classrooms. Ironically, science is often equated with certainty in these contexts. Uncertainties that arise in science deserve special attention, as they are increasingly a part of public discussions and are susceptible to manipulation. Clarifying what is meant by scientific uncertainty would include identifying sources of uncertainty in scientific practice, and would help provide an instructional framework for understanding how scientists use methods, data, and models to justify claims about the natural world. This research introduces both a general typology of scientific uncertainty informed by a review of literature from a variety of perspectives, and two additional typologies that emerged from qualitative studies examining student essays about scientific uncertainty in two disciplinary contexts: biological evolution and global climate change. These typologies aim to provide leverage for curricular discussions about scientific knowledge and practices, and to help instructors interested in integrating scientific uncertainty into teaching these subjects. In particular, a focus on uncertainties in data and models can illustrate their integral relationship and can spark critical discussions about methods used to collect empirical data and the models used to explain them and make predictions. This research builds a case for integrating scientific uncertainty into science teaching and emphasizing its importance for understanding the practice of science within particular disciplinary contexts.

  20. Adaptively Addressing Uncertainty in Estuarine and Near Coastal Restoration Projects

    SciTech Connect

    Thom, Ronald M.; Williams, Greg D.; Borde, Amy B.; Southard, John A.; Sargeant, Susan L.; Woodruff, Dana L.; Laufle, Jeffrey C.; Glasoe, Stuart

    2005-03-01

    Restoration projects have an uncertain outcome because of a lack of information about current site conditions, historical disturbance levels, effects of landscape alterations on site development, unpredictable trajectories or patterns of ecosystem structural development, and many other factors. A poor understanding of the factors that control the development and dynamics of a system, such as hydrology, salinity, wave energies, can also lead to an unintended outcome. Finally, lack of experience in restoring certain types of systems (e.g., rare or very fragile habitats) or systems in highly modified situations (e.g., highly urbanized estuaries) makes project outcomes uncertain. Because of these uncertainties, project costs can rise dramatically in an attempt to come closer to project goals. All of the potential sources of error can be addressed to a certain degree through adaptive management. The first step is admitting that these uncertainties can exist, and addressing as many of the uncertainties with planning and directed research prior to implementing the project. The second step is to evaluate uncertainties through hypothesis-driven experiments during project implementation. The third step is to use the monitoring program to evaluate and adjust the project as needed to improve the probability of the project to reach is goal. The fourth and final step is to use the information gained in the project to improve future projects. A framework that includes a clear goal statement, a conceptual model, and an evaluation framework can help in this adaptive restoration process. Projects and programs vary in their application of adaptive management in restoration, and it is very difficult to be highly prescriptive in applying adaptive management to projects that necessarily vary widely in scope, goal, ecosystem characteristics, and uncertainties. Very large ecosystem restoration programs in the Mississippi River delta (Coastal Wetlands Planning, Protection, and Restoration

  1. Scientific Uncertainty and Its Relevance to Science Education

    ERIC Educational Resources Information Center

    Ruggeri, Nancy Lee

    2011-01-01

    Uncertainty is inherent to scientific methods and practices, yet is it rarely explicitly discussed in science classrooms. Ironically, science is often equated with "certainty" in these contexts. Uncertainties that arise in science deserve special attention, as they are increasingly a part of public discussions and are susceptible to manipulation.…

  2. Communication about scientific uncertainty in environmental nanoparticle research - a comparison of scientific literature and mass media

    NASA Astrophysics Data System (ADS)

    Heidmann, Ilona; Milde, Jutta

    2014-05-01

    The research about the fate and behavior of engineered nanoparticles in the environment is despite its wide applications still in the early stages. 'There is a high level of scientific uncertainty in nanoparticle research' is often stated in the scientific community. Knowledge about these uncertainties might be of interest to other scientists, experts and laymen. But how could these uncertainties be characterized and are they communicated within the scientific literature and the mass media? To answer these questions, the current state of scientific knowledge about scientific uncertainty through the example of environmental nanoparticle research was characterized and the communication of these uncertainties within the scientific literature is compared with its media coverage in the field of nanotechnologies. The scientific uncertainty within the field of environmental fate of nanoparticles is by method uncertainties and a general lack of data concerning the fate and effects of nanoparticles and their mechanisms in the environment, and by the uncertain transferability of results to the environmental system. In the scientific literature, scientific uncertainties, their sources, and consequences are mentioned with different foci and to a different extent. As expected, the authors in research papers focus on the certainty of specific results within their specific research question, whereas in review papers, the uncertainties due to a general lack of data are emphasized and the sources and consequences are discussed in a broader environmental context. In the mass media, nanotechnology is often framed as rather certain and positive aspects and benefits are emphasized. Although reporting about a new technology, only in one-third of the reports scientific uncertainties are mentioned. Scientific uncertainties are most often mentioned together with risk and they arise primarily from unknown harmful effects to human health. Environmental issues itself are seldom mentioned

  3. Addressing Unconscious Bias: Steps toward an Inclusive Scientific Culture

    NASA Astrophysics Data System (ADS)

    Stewart, Abigail

    2011-01-01

    In this talk I will outline the nature of unconscious bias, as it operates to exclude or marginalize some participants in the scientific community. I will show how bias results from non-conscious expectations about certain groups of people, including scientists and astronomers. I will outline scientific research in psychology, sociology and economics that has identified the impact these expectations have on interpersonal judgments that are at the heart of assessment of individuals' qualifications. This research helps us understand not only how bias operates within a single instance of evaluation, but how evaluation bias can accumulate over a career if not checked, creating an appearance of confirmation of biased expectations. Some research has focused on how best to interrupt and mitigate unconscious bias, and many institutions--including the University of Michigan--have identified strategic interventions at key points of institutional decision-making (particularly hiring, annual review, and promotion) that can make a difference. The NSF ADVANCE Institutional Transformation program encouraged institutions to draw on the social science literature to create experimental approaches to addressing unconscious bias. I will outline four approaches to intervention that have arisen through the ADVANCE program: (1) systematic education that increases awareness among decisionmakers of how evaluation bias operates; (2) development of practices that mitigate the operation of bias even when it is out of conscious awareness; (3) creation of institutional policies that routinize and sanction these practices; and (4) holding leaders accountable for these implementation of these new practices and policies. Although I will focus on ways to address unconscious bias within scientific institutions (colleges and universities, laboratories and research centers, etc.), I will close by considering how scientific organizations can address unconscious bias and contribute to creating an

  4. 42 CFR 82.19 - How will NIOSH address uncertainty about dose levels?

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 1 2011-10-01 2011-10-01 false How will NIOSH address uncertainty about dose... § 82.19 How will NIOSH address uncertainty about dose levels? The estimate of each annual dose will be characterized with a probability distribution that accounts for the uncertainty of the estimate....

  5. 42 CFR 82.19 - How will NIOSH address uncertainty about dose levels?

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 1 2013-10-01 2013-10-01 false How will NIOSH address uncertainty about dose... § 82.19 How will NIOSH address uncertainty about dose levels? The estimate of each annual dose will be characterized with a probability distribution that accounts for the uncertainty of the estimate....

  6. 42 CFR 82.19 - How will NIOSH address uncertainty about dose levels?

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 1 2014-10-01 2014-10-01 false How will NIOSH address uncertainty about dose... § 82.19 How will NIOSH address uncertainty about dose levels? The estimate of each annual dose will be characterized with a probability distribution that accounts for the uncertainty of the estimate....

  7. 42 CFR 82.19 - How will NIOSH address uncertainty about dose levels?

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 1 2012-10-01 2012-10-01 false How will NIOSH address uncertainty about dose... § 82.19 How will NIOSH address uncertainty about dose levels? The estimate of each annual dose will be characterized with a probability distribution that accounts for the uncertainty of the estimate....

  8. Risk newsboy: approach for addressing uncertainty in developing action levels and cleanup limits

    SciTech Connect

    Cooke, Roger; MacDonell, Margaret

    2007-07-01

    Site cleanup decisions involve developing action levels and residual limits for key contaminants, to assure health protection during the cleanup period and into the long term. Uncertainty is inherent in the toxicity information used to define these levels, based on incomplete scientific knowledge regarding dose-response relationships across various hazards and exposures at environmentally relevant levels. This problem can be addressed by applying principles used to manage uncertainty in operations research, as illustrated by the newsboy dilemma. Each day a newsboy must balance the risk of buying more papers than he can sell against the risk of not buying enough. Setting action levels and cleanup limits involves a similar concept of balancing and distributing risks and benefits in the face of uncertainty. The newsboy approach can be applied to develop health-based target concentrations for both radiological and chemical contaminants, with stakeholder input being crucial to assessing 'regret' levels. Associated tools include structured expert judgment elicitation to quantify uncertainty in the dose-response relationship, and mathematical techniques such as probabilistic inversion and iterative proportional fitting. (authors)

  9. Addressing Conceptual Model Uncertainty in the Evaluation of Model Prediction Errors

    NASA Astrophysics Data System (ADS)

    Carrera, J.; Pool, M.

    2014-12-01

    Model predictions are uncertain because of errors in model parameters, future forcing terms, and model concepts. The latter remain the largest and most difficult to assess source of uncertainty in long term model predictions. We first review existing methods to evaluate conceptual model uncertainty. We argue that they are highly sensitive to the ingenuity of the modeler, in the sense that they rely on the modeler's ability to propose alternative model concepts. Worse, we find that the standard practice of stochastic methods leads to poor, potentially biased and often too optimistic, estimation of actual model errors. This is bad news because stochastic methods are purported to properly represent uncertainty. We contend that the problem does not lie on the stochastic approach itself, but on the way it is applied. Specifically, stochastic inversion methodologies, which demand quantitative information, tend to ignore geological understanding, which is conceptually rich. We illustrate some of these problems with the application to Mar del Plata aquifer, where extensive data are available for nearly a century. Geologically based models, where spatial variability is handled through zonation, yield calibration fits similar to geostatiscally based models, but much better predictions. In fact, the appearance of the stochastic T fields is similar to the geologically based models only in areas with high density of data. We take this finding to illustrate the ability of stochastic models to accommodate many data, but also, ironically, their inability to address conceptual model uncertainty. In fact, stochastic model realizations tend to be too close to the "most likely" one (i.e., they do not really realize the full conceptualuncertainty). The second part of the presentation is devoted to argue that acknowledging model uncertainty may lead to qualitatively different decisions than just working with "most likely" model predictions. Therefore, efforts should concentrate on

  10. Addressing Uncertainty in Signal Propagation and Sensor Performance Predictions

    DTIC Science & Technology

    2008-11-01

    L. Pettit , Sean Mackay, Matthew S. Lewis, and Peter M. Seman November 2008 C ol d R eg io n s R es ea rc h an d E n gi n ee ri n g La b...U.S. Army Engineer Research and Development Center 72 Lyme Road Hanover, NH 03755-1290 Chris L. Pettit U.S. Naval Academy Aerospace Engineering...outcome. Uncertainty by itself is not a concern unless there is as- sociated, significant risk. Although uncertainty is emphasized in this re- port , we

  11. Scientific evidence and mass media: Investigating the journalistic intention to represent scientific uncertainty.

    PubMed

    Guenther, Lars; Ruhrmann, Georg

    2016-11-01

    Science journalists are responsible for the mass media's representation of life sciences (e.g. biotechnology, genetics, and nanotechnology) and for the depiction of research findings in these areas as more scientifically (un)certain. Although researchers have determined that the representational styles of scientific evidence vary among science journalists, the reasons for these differences have not yet been fully investigated. Against this background, for the first time, the present study applies a reasoned action approach and investigates the predictors of the journalistic intention to represent scientific uncertainty, using computer-assisted telephone interviews with a representative sample of German science journalists (n = 202). The results indicate that beliefs about the coverage of other media, perceptions regarding scientific uncertainty of the main field of coverage, perceived expectations of the audience, past behavior, and gender were the predictors that most strongly affected the journalists' intention to represent life sciences as more scientifically uncertain.

  12. Risks, scientific uncertainty and the approach of applying precautionary principle.

    PubMed

    Lo, Chang-fa

    2009-03-01

    The paper intends to clarify the nature and aspects of risks and scientific uncertainty and also to elaborate the approach of application of precautionary principle for the purpose of handling the risk arising from scientific uncertainty. It explains the relations between risks and the application of precautionary principle at international and domestic levels. In the situations where an international treaty has admitted the precautionary principle and in the situation where there is no international treaty admitting the precautionary principle or enumerating the conditions to take measures, the precautionary principle has a role to play. The paper proposes a decision making tool, containing questions to be asked, to help policymakers to apply the principle. It also proposes a "weighing and balancing" procedure to help them decide the contents of the measure to cope with the potential risk and to avoid excessive measures.

  13. Addressing uncertainty in fecal indicator bacteria dark inactivation rates.

    PubMed

    Gronewold, Andrew D; Myers, Luke; Swall, Jenise L; Noble, Rachel T

    2011-01-01

    Assessing the potential threat of fecal contamination in surface water often depends on model forecasts which assume that fecal indicator bacteria (FIB, a proxy for the concentration of pathogens found in fecal contamination from warm-blooded animals) are lost or removed from the water column at a certain rate (often referred to as an "inactivation" rate). In efforts to reduce human health risks in these water bodies, regulators enforce limits on easily-measured FIB concentrations, commonly reported as most probable number (MPN) and colony forming unit (CFU) values. Accurate assessment of the potential threat of fecal contamination, therefore, depends on propagating uncertainty surrounding "true" FIB concentrations into MPN and CFU values, inactivation rates, model forecasts, and management decisions. Here, we explore how empirical relationships between FIB inactivation rates and extrinsic factors might vary depending on how uncertainty in MPN values is expressed. Using water samples collected from the Neuse River Estuary (NRE) in eastern North Carolina, we compare Escherichia coli (EC) and Enterococcus (ENT) dark inactivation rates derived from two statistical models of first-order loss; a conventional model employing ordinary least-squares (OLS) regression with MPN values, and a novel Bayesian model utilizing the pattern of positive wells in an IDEXX Quanti-Tray®/2000 test. While our results suggest that EC dark inactivation rates tend to decrease as initial EC concentrations decrease and that ENT dark inactivation rates are relatively consistent across different ENT concentrations, we find these relationships depend upon model selection and model calibration procedures. We also find that our proposed Bayesian model provides a more defensible approach to quantifying uncertainty in microbiological assessments of water quality than the conventional MPN-based model, and that our proposed model represents a new strategy for developing robust relationships between

  14. Addressing Uncertainty in Fecal Indicator Bacteria Dark Inactivation Rates

    EPA Science Inventory

    Fecal contamination is a leading cause of surface water quality degradation. Roughly 20% of all total maximum daily load assessments approved by the United States Environmental Protection Agency since 1995, for example, address water bodies with unacceptably high fecal indicator...

  15. Designing Technology to Address Parent Uncertainty in Childhood Cancer.

    PubMed

    Morrison, Caroline F; Szulczewski, Lauren; Strahlendorf, Laura F; Lane, J Blake; Mullins, Larry L; Pai, Ahna L H

    2016-01-01

    The stress and uncertainty created by a child's cancer diagnosis and treatment can affect parent and child functioning. Health technology provides a potential avenue for intervention delivery. Interviews were conducted with parents of children diagnosed with cancer to discover their needs following diagnosis and design a relevant mobile application. Treatment experience was the overarching theme. Subthemes included the emotional response, use of information, and environmental factors. Technology was used primarily to seek out information and communicate with others. Health technologies are gaining popularity and have the potential to be beneficial for patients and families throughout the treatment experience.

  16. Addressing sources of uncertainty in a global terrestrial carbon model

    NASA Astrophysics Data System (ADS)

    Exbrayat, J.; Pitman, A. J.; Zhang, Q.; Abramowitz, G.; Wang, Y.

    2013-12-01

    Several sources of uncertainty exist in the parameterization of the land carbon cycle in current Earth System Models (ESMs). For example, recently implemented interactions between the carbon (C), nitrogen (N) and phosphorus (P) cycles lead to diverse changes in land-atmosphere C fluxes simulated by different models. Further, although soil organic matter decomposition is commonly parameterized as a first-order decay process, the formulation of the microbial response to changes in soil moisture and soil temperature varies tremendously between models. Here, we examine the sensitivity of historical land-atmosphere C fluxes simulated by an ESM to these two major sources of uncertainty. We implement three soil moisture (SMRF) and three soil temperature (STRF) respiration functions in the CABLE-CASA-CNP land biogeochemical component of the coarse resolution CSIRO Mk3L climate model. Simulations are undertaken using three degrees of biogeochemical nutrient limitation: C-only, C and N, and C and N and P. We first bring all 27 possible combinations of a SMRF with a STRF and a biogeochemical mode to a steady-state in their biogeochemical pools. Then, transient historical (1850-2005) simulations are driven by prescribed atmospheric CO2 concentrations used in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Similarly to some previously published results, representing N and P limitation on primary production reduces the global land carbon sink while some regions become net C sources over the historical period (1850-2005). However, the uncertainty due to the SMRFs and STRFs does not decrease relative to the inter-annual variability in net uptake when N and P limitations are added. Differences in the SMRFs and STRFs and their effect on the soil C balance can also change the sign of some regional sinks. We show that this response is mostly driven by the pool size achieved at the end of the spin-up procedure. Further, there exists a six-fold range in the level

  17. Assessing and Addressing Students' Scientific Literacy Needs in Physical Geology

    NASA Astrophysics Data System (ADS)

    Campbell-Stone, E. A.; Myers, J. D.

    2005-12-01

    Exacting excellence equally from university students around the globe can be accomplished by providing all students with necessary background tools to achieve mastery of their courses, even if those tools are not part of normal content. As instructors we hope to see our students grasp the substance of our courses, make mental connections between course material and practical applications, and use this knowledge to make informed decisions as citizens. Yet many educators have found that students enter university-level introductory courses in mathematics, science and engineering without adequate academic preparation. As part of a FIPSE-funded project at the University of Wyoming, the instructors of the Physical Geology course have taken a new approach to tackling the problem of lack of scientific/mathematic skills in incoming students. Instead of assuming that students should already know or will learn these skills on their own, they assess students' needs and provide them the opportunity to master scientific literacies as they learn geologic content. In the introductory geology course, instructors identified two categories of literacies, or basic skills that are necessary for academic success and citizen participation. Fundamental literacies include performing simple quantitative calculations, making qualitative assessments, and reading and analyzing tables and graphs. Technical literacies are those specific to understanding geology, and comprise the ability to read maps, visualize changes through time, and conceptualize in three dimensions. Because these skills are most easily taught in lab, the in-house lab manual was rewritten to be both literacy- and content-based. Early labs include simple exercises addressing literacies in the context of geological science, and each subsequent lab repeats exposure to literacies, but at increasing levels of difficulty. Resources available to assist students with literacy mastery include individual instruction, a detailed

  18. Addressing scientific literacy through content area reading and processes of scientific inquiry: What teachers report

    NASA Astrophysics Data System (ADS)

    Cooper, Susan J.

    The purpose of this study was to interpret the experiences of secondary science teachers in Florida as they address the scientific literacy of their students through teaching content reading strategies and student inquiry skills. Knowledge of the successful integration of content reading and inquiry skills by experienced classroom teachers would be useful to many educators as they plan instruction to achieve challenging state and national standards for reading as well as science. The problem was investigated using grounded theory methodology. Open-ended questions were asked in three focus groups and six individual interviews that included teachers from various Florida school districts. The constant comparative approach was used to analyze the data. Initial codes were collapsed into categories to determine the conceptual relationships among the data. From this, the five core categories were determined to be Influencers, Issues, Perceptions, Class Routines, and Future Needs. These relate to the central phenomenon, Instructional Modifications, because teachers often described pragmatic and philosophical changes in their teaching as they deliberated to meet state standards in both reading and science. Although Florida's secondary science teachers have been asked to incorporate content reading strategies into their science instruction for the past several years, there was limited evidence of using these strategies to further student understanding of scientific processes. Most teachers saw little connection between reading and inquiry, other than the fact that students must know how to read to follow directions in the lab. Scientific literacy, when it was addressed by teachers, was approached mainly through class discussions, not reading. Teachers realized that students cannot learn secondary science content unless they read science text with comprehension; therefore the focus of reading instruction was on learning science content, not scientific literacy or student

  19. Addressing STEM Retention through a Scientific Thought and Methods Course

    ERIC Educational Resources Information Center

    Koenig, Kathleen; Schen, Melissa; Edwards, Michael; Bao, Lei

    2012-01-01

    Retention of majors in science, technology, engineering, and mathematics (STEM) is a national problem that continues to be the focus of bridging and first-year experience programs. This article presents an innovative course, Scientific Thought and Methods, that targets students with low math placement scores. These students are not eligible for…

  20. Research approaches to address uncertainties in the risk assessment of arsenic in drinking water

    SciTech Connect

    Hughes, Michael F. Kenyon, Elaina M.; Kitchin, Kirk T.

    2007-08-01

    Inorganic arsenic (iAs), an environmental drinking water contaminant, is a human toxicant and carcinogen. The public health community has developed recommendations and regulations that limit human exposure to iAs in drinking water. Although there is a vast amount of information available to regulators on the exposure, disposition and the health-related effects of iAs, there is still critical information about the toxicology of this metalloid that is needed. This necessary information includes identification of the chemical species of arsenic that is (are) the active toxicant(s), the mode(s) of action for its various toxicities and information on potentially susceptible populations. Because of these unknown factors, the risk assessment of iAs still incorporates default assumptions, leading to uncertainties in the overall assessment. The characteristics of a scientifically defensible risk assessment for iAs are that it must: (1) quantitatively link exposure and target tissue dose of active metabolites to key events in the mode of action for major health effects and (2) identify sources of variation in susceptibility to arsenic-induced health effects and quantitatively evaluate their impact wherever possible. Integration of research to address these goals will better protect the health of iAs-exposed populations.

  1. 42 CFR 82.19 - How will NIOSH address uncertainty about dose levels?

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false How will NIOSH address uncertainty about dose levels? 82.19 Section 82.19 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES METHODS FOR CONDUCTING DOSE RECONSTRUCTION...

  2. 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.

  3. Teaching Scientific Measurement and Uncertainty in Elementary School

    ERIC Educational Resources Information Center

    Munier, Valérie; Merle, Hélène; Brehelin, Danie

    2013-01-01

    The concept of measurement is fundamental in science. In order to be meaningful, the value of a measurement must be given with a certain level of uncertainty. In this paper we try to identify and develop the reasoning of young French pupils about measurement variability. In France, official instructions for elementary school thus argue for having…

  4. Addressing rainfall data selection uncertainty using connections between rainfall and streamflow.

    PubMed

    Levy, Morgan C; Cohn, Avery; Lopes, Alan Vaz; Thompson, Sally E

    2017-03-16

    Studies of the hydroclimate at regional scales rely on spatial rainfall data products, derived from remotely-sensed (RS) and in-situ (IS, rain gauge) observations. Because regional rainfall cannot be directly measured, spatial data products are biased. These biases pose a source of uncertainty in environmental analyses, attributable to the choices made by data-users in selecting a representation of rainfall. We use the rainforest-savanna transition region in Brazil to show differences in the statistics describing rainfall across nine RS and interpolated-IS daily rainfall datasets covering the period of 1998-2013. These differences propagate into estimates of temporal trends in monthly rainfall and descriptive hydroclimate indices. Rainfall trends from different datasets are inconsistent at river basin scales, and the magnitude of index differences is comparable to the estimated bias in global climate model projections. To address this uncertainty, we evaluate the correspondence of different rainfall datasets with streamflow from 89 river basins. We demonstrate that direct empirical comparisons between rainfall and streamflow provide a method for evaluating rainfall dataset performance across multiple areal (basin) units. These results highlight the need for users of rainfall datasets to quantify this "data selection uncertainty" problem, and either justify data use choices, or report the uncertainty in derived results.

  5. A review of contemporary methods for the presentation of scientific uncertainty.

    PubMed

    Makinson, K A; Hamby, D M; Edwards, J A

    2012-12-01

    Graphic methods for displaying uncertainty are often the most concise and informative way to communicate abstract concepts. Presentation methods currently in use for the display and interpretation of scientific uncertainty are reviewed. Numerous subjective and objective uncertainty display methods are presented, including qualitative assessments, node and arrow diagrams, standard statistical methods, box-and-whisker plots,robustness and opportunity functions, contribution indexes, probability density functions, cumulative distribution functions, and graphical likelihood functions.

  6. Teaching Scientific Measurement and Uncertainty in Elementary School

    NASA Astrophysics Data System (ADS)

    Munier, Valérie; Merle, Hélène; Brehelin, Danie

    2013-11-01

    The concept of measurement is fundamental in science. In order to be meaningful, the value of a measurement must be given with a certain level of uncertainty. In this paper we try to identify and develop the reasoning of young French pupils about measurement variability. In France, official instructions for elementary school thus argue for having students do activities of measurement, followed by treatments and analysis of the data. The notion of measurement 'uncertainty' appears in fourth and fifth grades. A similar approach is proposed in the USA. We present a teaching sequence divided into two parts: the first part in grade 4, the second one in grade 5, the following year, with the same students. The main sources of data were field notes, videotapes, as well as the intermediate written traces produced, individual written tests given each year and clinical interview. We showed that the pupils were capable of entertaining all three possible causes of uncertainty (the quantity being measured, the measuring instrument, and the measurer). Concerning data organization and handling, we found that after teaching, most of them were able to construct a frequency table and a bar chart from a list of N measures of the same quantity. When interpreting this type of chart, some of them were able to argue in terms of a confidence interval. We have also shown that the proposed instructional units allowed pupils to become aware of the need to repeat measurements.

  7. Painting the world REDD: addressing scientific barriers to monitoring emissions from tropical forests

    NASA Astrophysics Data System (ADS)

    Asner, Gregory P.

    2011-06-01

    project scale to program readiness is a big step for all involved, and many are finding that it is not easy. Current barriers to national monitoring of forest carbon stocks and emissions range from technical to scientific, and from institutional to operational. In fact, a recent analysis suggested that about 3% of tropical countries currently have the capacity to monitor and report on changes in forest cover and carbon stocks (Herold 2009). But until now, the scientific and policy-development communities have had little quantitative information on exactly which aspects of national-scale monitoring are most uncertain, and how that uncertainty will affect REDD+ performance reporting. A new and remarkable study by Pelletier, Ramankutty and Potvin (2011) uses an integrated, spatially-explicit modeling technique to explore and quantify sources of uncertainty in carbon emissions mapping throughout the Republic of Panama. Their findings are sobering: deforestation rates would need to be reduced by a full 50% in Panama in order to be detectable above the statistical uncertainty caused by several current major monitoring problems. The number one uncertainty, accounting for a sum total of about 77% of the error, rests in the spatial variation of aboveground carbon stocks in primary forests, secondary forests and on fallow land. The poor quality of and insufficient time interval between land-cover maps account for the remainder of the overall uncertainty. These findings are a show-stopper for REDD+ under prevailing science and technology conditions. The Pelletier et al study highlights the pressing need to improve the accuracy of forest carbon and land cover mapping assessments in order for REDD+ to become viable, but how can the uncertainties be overcome? First, with REDD+ nations required to report their emissions, and with verification organizations wanting to check on the reported numbers, there is a clear need for shared measurement and monitoring approaches. One of the major

  8. Articulating uncertainty as part of scientific argumentation during model-based exoplanet detection tasks

    NASA Astrophysics Data System (ADS)

    Lee, Hee-Sun; Pallant, Amy; Pryputniewicz, Sarah

    2015-08-01

    Teaching scientific argumentation has emerged as an important goal for K-12 science education. In scientific argumentation, students are actively involved in coordinating evidence with theory based on their understanding of the scientific content and thinking critically about the strengths and weaknesses of the cited evidence in the context of the investigation. We developed a one-week-long online curriculum module called "Is there life in space?" where students conduct a series of four model-based tasks to learn how scientists detect extrasolar planets through the “wobble” and transit methods. The simulation model allows students to manipulate various parameters of an imaginary star and planet system such as planet size, orbit size, planet-orbiting-plane angle, and sensitivity of telescope equipment, and to adjust the display settings for graphs illustrating the relative velocity and light intensity of the star. Students can use model-based evidence to formulate an argument on whether particular signals in the graphs guarantee the presence of a planet. Students' argumentation is facilitated by the four-part prompts consisting of multiple-choice claim, open-ended explanation, Likert-scale uncertainty rating, and open-ended uncertainty rationale. We analyzed 1,013 scientific arguments formulated by 302 high school student groups taught by 7 teachers. We coded these arguments in terms of the accuracy of their claim, the sophistication of explanation connecting evidence to the established knowledge base, the uncertainty rating, and the scientific validity of uncertainty. We found that (1) only 18% of the students' uncertainty rationale involved critical reflection on limitations inherent in data and concepts, (2) 35% of students' uncertainty rationale reflected their assessment of personal ability and knowledge, rather than scientific sources of uncertainty related to the evidence, and (3) the nature of task such as the use of noisy data or the framing of

  9. Scientific Uncertainty in News Coverage of Cancer Research: Effects of Hedging on Scientists' and Journalists' Credibility

    ERIC Educational Resources Information Center

    Jensen, Jakob D.

    2008-01-01

    News reports of scientific research are rarely hedged; in other words, the reports do not contain caveats, limitations, or other indicators of scientific uncertainty. Some have suggested that hedging may influence news consumers' perceptions of scientists' and journalists' credibility (perceptions that may be related to support for scientific…

  10. Measuring the perceived uncertainty of scientific evidence and its relationship to engagement with science.

    PubMed

    Retzbach, Joachim; Otto, Lukas; Maier, Michaela

    2016-08-01

    Many scholars have argued for the need to communicate openly not only scientific successes to the public but also limitations, such as the tentativeness of research findings, in order to enhance public trust and engagement. Yet, it has not been quantitatively assessed how the perception of scientific uncertainties relates to engagement with science on an individual level. In this article, we report the development and testing of a new questionnaire in English and German measuring the perceived uncertainty of scientific evidence. Results indicate that the scale is reliable and valid in both language versions and that its two subscales are differentially related to measures of engagement: Science-friendly attitudes were positively related only to 'subjectively' perceived uncertainty, whereas interest in science as well as behavioural engagement actions and intentions were largely uncorrelated. We conclude that perceiving scientific knowledge to be uncertain is only weakly, but positively related to engagement with science.

  11. Towards a common oil spill risk assessment framework – Adapting ISO 31000 and addressing uncertainties.

    PubMed

    Sepp Neves, Antonio Augusto; Pinardi, Nadia; Martins, Flavio; Janeiro, Joao; Samaras, Achilleas; Zodiatis, George; De Dominicis, Michela

    2015-08-15

    Oil spills are a transnational problem, and establishing a common standard methodology for Oil Spill Risk Assessments (OSRAs) is thus paramount in order to protect marine environments and coastal communities. In this study we firstly identified the strengths and weaknesses of the OSRAs carried out in various parts of the globe. We then searched for a generic and recognized standard, i.e. ISO 31000, in order to design a method to perform OSRAs in a scientific and standard way. The new framework was tested for the Lebanon oil spill that occurred in 2006 employing ensemble oil spill modeling to quantify the risks and uncertainties due to unknown spill characteristics. The application of the framework generated valuable visual instruments for the transparent communication of the risks, replacing the use of risk tolerance levels, and thus highlighting the priority areas to protect in case of an oil spill.

  12. Risk, Scientific Uncertainty, and Policy Implications of Global Climate Change Models

    NASA Astrophysics Data System (ADS)

    Briggs, C.; Sahagian, D.

    2006-12-01

    The risks of global climate change to human populations and natural environments have received increasing attention in recent years. With high-profile events such as hurricane Katrina in the United States, rapid melting of the Greenland ice sheet, shifting precipitation patterns in Europe and elsewhere, more political attention has been given to the risks posed by anthropogenic changes in the earth's atmosphere. Yet despite increasing scientific evidence of such environmental risks, reactions from political sources have been far from consistent. While some states have adopted emissions regulations on greenhouse gases, other states or national governments have downplayed the existence of any significant risk. Explanations for why political actors or the public may appear unaware of scientific data relate to the nature of uncertainty in environmental risk models and decisions. Professional scientific methodologies must approach uncertainty in a far different manner than government agencies or members of the public, and these varying types of uncertainty create spaces for translation of scientific data into incompatible conclusions. Such conclusions depend not only upon the translation of scientific data, but also perception of the risks involved, differential local impacts of climate change, and available policy alternatives and resources. Scientists involved in climate research bear a particular responsibility for how their data are interpreted politically, but this requires awareness of the manners in which uncertainty is employed, the ethics of applying research to policy questions, and realization that risks will be perceived differently according to political cultures and geographic regions.

  13. Science Teachers' Use of Mass Media to Address Socio-Scientific and Sustainability Issues

    NASA Astrophysics Data System (ADS)

    Klosterman, Michelle L.; Sadler, Troy D.; Brown, Julie

    2012-01-01

    The currency, relevancy and changing nature of science makes it a natural topic of focus for mass media outlets. Science teachers and students can capitalize on this wealth of scientific information to explore socio-scientific and sustainability issues; however, without a lens on how those media are created and how representations of science are constructed through media, the use of mass media in the science classroom may be risky. Limited research has explored how science teachers naturally use mass media to explore scientific issues in the classroom or how mass media is used to address potential overlaps between socio-scientific-issue based instruction and education for sustainability. This naturalistic study investigated the reported and actual classroom uses of mass media by secondary science teachers' to explore socio-scientific and sustainability issues as well as the extent to which their instructional approaches did or did not overlap with frameworks for SSI-based instruction, education for sustainability, and media literacy education. The results of this study suggest that secondary science teachers use mass media to explore socio-scientific and sustainability issues, but their use of frameworks aligned with SSI-based, education for sustainability, and media literacy education was limited. This paper provides suggestions for how we, as science educators and researchers, can advance a teaching and learning agenda for encouraging instruction that more fully utilizes the potential of mass media to explore socio-scientific issues in line with perspectives from education for sustainability.

  14. 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

  15. Scientifically defensible fish conservation and recovery plans: Addressing diffuse threats and developing rigorous adaptive management plans

    USGS Publications Warehouse

    Maas-Hebner, Kathleen G.; Schreck, Carl B.; Hughes, Robert M.; Yeakley, Alan; Molina, Nancy

    2016-01-01

    We discuss the importance of addressing diffuse threats to long-term species and habitat viability in fish conservation and recovery planning. In the Pacific Northwest, USA, salmonid management plans have typically focused on degraded freshwater habitat, dams, fish passage, harvest rates, and hatchery releases. However, such plans inadequately address threats related to human population and economic growth, intra- and interspecific competition, and changes in climate, ocean, and estuarine conditions. Based on reviews conducted on eight conservation and/or recovery plans, we found that though threats resulting from such changes are difficult to model and/or predict, they are especially important for wide-ranging diadromous species. Adaptive management is also a critical but often inadequately constructed component of those plans. Adaptive management should be designed to respond to evolving knowledge about the fish and their supporting ecosystems; if done properly, it should help improve conservation efforts by decreasing uncertainty regarding known and diffuse threats. We conclude with a general call for environmental managers and planners to reinvigorate the adaptive management process in future management plans, including more explicitly identifying critical uncertainties, implementing monitoring programs to reduce those uncertainties, and explicitly stating what management actions will occur when pre-identified trigger points are reached.

  16. SCIENTIFIC UNCERTAINTIES IN ATMOSPHERIC MERCURY MODELS II: SENSITIVITY ANALYSIS IN THE CONUS DOMAIN

    EPA Science Inventory

    In this study, we present the response of model results to different scientific treatments in an effort to quantify the uncertainties caused by the incomplete understanding of mercury science and by model assumptions in atmospheric mercury models. Two sets of sensitivity simulati...

  17. Children's Understanding of Scientific Inquiry: Their Conceptualization of Uncertainty in Investigations of Their Own Design

    ERIC Educational Resources Information Center

    Metz, Kathleen E.

    2004-01-01

    The study examined children's understanding of scientific inquiry, through the lens of their conceptualization of uncertainty in investigations they had designed and implemented with a partner. These largely student-regulated investigations followed a unit about animal behavior that emphasized the scaffolding of independent inquiry. Participants…

  18. Educated Guesses and Other Ways to Address the Pharmacological Uncertainty of Designer Drugs

    PubMed Central

    Berning, Moritz

    2016-01-01

    This study examines how experimentation with designer drugs is mediated by the Internet. We selected a popular drug forum that presents reports on self-experimentation with little or even completely unexplored designer drugs to examine: (1) how participants report their “trying out” of new compounds and (2) how participants reduce the pharmacological uncertainty associated with using these substances. Our methods included passive observation online, engaging more actively with the online community using an avatar, and off-line interviews with key interlocutors to validate our online findings. This article reflects on how forum participants experiment with designer drugs, their trust in suppliers and the testimonials of others, the use of ethno-scientific techniques that involve numerical weighing, “allergy dosing,” and the use of standardized trip reports. We suggest that these techniques contribute to a sense of control in the face of the possible toxicity of unknown or little-known designer drugs. The online reporting of effects allows users to experience not only the thrill of a new kind of high but also connection with others in the self-experimenting drug community. PMID:27721526

  19. The Scientific Basis of Uncertainty Factors Used in Setting Occupational Exposure Limits

    PubMed Central

    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

  20. Simulating microbial systems: addressing model uncertainty/incompleteness via multiscale and entropy methods.

    PubMed

    Singharoy, A; Joshi, H; Cheluvaraja, S; Miao, Y; Brown, D; Ortoleva, P

    2012-01-01

    Most systems of interest in the natural and engineering sciences are multiscale in character. Typically available models are incomplete or uncertain. Thus, a probabilistic approach is required. We present a deductive multiscale approach to address such problems, focusing on virus and cell systems to demonstrate the ideas. There is usually an underlying physical model, all factors in which (e.g., particle masses, charges, and force constants) are known. For example, the underlying model can be cast in terms of a collection of N-atoms evolving via Newton's equations. When the number of atoms is 10(6) or more, these physical models cannot be simulated directly. However, one may only be interested in a coarse-grained description, e.g., in terms of molecular populations or overall system size, shape, position, and orientation. The premise of this chapter is that the coarse-grained equations should be derived from the underlying model so that a deductive calibration-free methodology is achieved. We consider a reduction in resolution from a description for the state of N-atoms to one in terms of coarse-grained variables. This implies a degree of uncertainty in the underlying microstates. We present a methodology for modeling microbial systems that integrates equations for coarse-grained variables with a probabilistic description of the underlying fine-scale ones. The implementation of our strategy as a general computational platform (SimEntropics™) for microbial modeling and prospects for developments and applications are discussed.

  1. It’s about time: How do sky surveys manage uncertainty about scientific needs many years into the future

    NASA Astrophysics Data System (ADS)

    Darch, Peter T.; Sands, Ashley E.

    2016-06-01

    Sky surveys, such as the Sloan Digital Sky Survey (SDSS) and the Large Synoptic Survey Telescope (LSST), generate data on an unprecedented scale. While many scientific projects span a few years from conception to completion, sky surveys are typically on the scale of decades. This paper focuses on critical challenges arising from long timescales, and how sky surveys address these challenges.We present findings from a study of LSST, comprising interviews (n=58) and observation. Conceived in the 1990s, the LSST Corporation was formed in 2003, and construction began in 2014. LSST will commence data collection operations in 2022 for ten years.One challenge arising from this long timescale is uncertainty about future needs of the astronomers who will use these data many years hence. Sources of uncertainty include scientific questions to be posed, astronomical phenomena to be studied, and tools and practices these astronomers will have at their disposal. These uncertainties are magnified by the rapid technological and scientific developments anticipated between now and the start of LSST operations.LSST is implementing a range of strategies to address these challenges. Some strategies involve delaying resolution of uncertainty, placing this resolution in the hands of future data users. Other strategies aim to reduce uncertainty by shaping astronomers’ data analysis practices so that these practices will integrate well with LSST once operations begin.One approach that exemplifies both types of strategy is the decision to make LSST data management software open source, even now as it is being developed. This policy will enable future data users to adapt this software to evolving needs. In addition, LSST intends for astronomers to start using this software well in advance of 2022, thereby embedding LSST software and data analysis approaches in the practices of astronomers.These findings strengthen arguments for making the software supporting sky surveys available as open

  2. Application of fuzzy system theory in addressing the presence of uncertainties

    SciTech Connect

    Yusmye, A. Y. N.; Goh, B. Y.; Adnan, N. F.; Ariffin, A. K.

    2015-02-03

    In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method.

  3. An integrated approach for addressing uncertainty in the delineation of groundwater management areas

    NASA Astrophysics Data System (ADS)

    Sousa, Marcelo R.; Frind, Emil O.; Rudolph, David L.

    2013-05-01

    Uncertainty is a pervasive but often poorly understood factor in the delineation of wellhead protection areas (WHPAs), which can discourage water managers and practitioners from relying on model results. To make uncertainty more understandable and thereby remove a barrier to the acceptance of models in the WHPA context, we present a simple approach for dealing with uncertainty. The approach considers two spatial scales for representing uncertainty: local and global. At the local scale, uncertainties are assumed to be due to heterogeneities, and a capture zone is expressed in terms of a capture probability plume. At the global scale, uncertainties are expressed through scenario analysis, using a limited number of physically realistic scenarios. The two scales are integrated by using the precautionary principle to merge the individual capture probability plumes corresponding to the different scenarios. The approach applies to both wellhead protection and the mitigation of contaminated aquifers, or in general, to groundwater management areas. An example relates to the WHPA for a supply well located in a complex glacial aquifer system in southwestern Ontario, where we focus on uncertainty due to the spatial distributions of recharge. While different recharge scenarios calibrate equally well to the same data, they result in different capture probability plumes. Using the precautionary approach, the different plumes are merged into two types of maps delineating groundwater management areas for either wellhead protection or aquifer mitigation. The study shows that calibrations may be non-unique, and that finding a "best" model on the basis of the calibration fit may not be possible.

  4. An integrated approach for addressing uncertainty in the delineation of groundwater management areas.

    PubMed

    Sousa, Marcelo R; Frind, Emil O; Rudolph, David L

    2013-05-01

    Uncertainty is a pervasive but often poorly understood factor in the delineation of wellhead protection areas (WHPAs), which can discourage water managers and practitioners from relying on model results. To make uncertainty more understandable and thereby remove a barrier to the acceptance of models in the WHPA context, we present a simple approach for dealing with uncertainty. The approach considers two spatial scales for representing uncertainty: local and global. At the local scale, uncertainties are assumed to be due to heterogeneities, and a capture zone is expressed in terms of a capture probability plume. At the global scale, uncertainties are expressed through scenario analysis, using a limited number of physically realistic scenarios. The two scales are integrated by using the precautionary principle to merge the individual capture probability plumes corresponding to the different scenarios. The approach applies to both wellhead protection and the mitigation of contaminated aquifers, or in general, to groundwater management areas. An example relates to the WHPA for a supply well located in a complex glacial aquifer system in southwestern Ontario, where we focus on uncertainty due to the spatial distributions of recharge. While different recharge scenarios calibrate equally well to the same data, they result in different capture probability plumes. Using the precautionary approach, the different plumes are merged into two types of maps delineating groundwater management areas for either wellhead protection or aquifer mitigation. The study shows that calibrations may be non-unique, and that finding a "best" model on the basis of the calibration fit may not be possible.

  5. Individual Uncertainty and the Uncertainty of Science: The Impact of Perceived Conflict and General Self-Efficacy on the Perception of Tentativeness and Credibility of Scientific Information.

    PubMed

    Flemming, Danny; Feinkohl, Insa; Cress, Ulrike; Kimmerle, Joachim

    2015-01-01

    We examined in two empirical studies how situational and personal aspects of uncertainty influence laypeople's understanding of the uncertainty of scientific information, with focus on the detection of tentativeness and perception of scientific credibility. In the first study (N = 48), we investigated the impact of a perceived conflict due to contradicting information as a situational, text-inherent aspect of uncertainty. The aim of the second study (N = 61) was to explore the role of general self-efficacy as an intra-personal uncertainty factor. In Study 1, participants read one of two versions of an introductory text in a between-group design. This text provided them with an overview about the neurosurgical procedure of deep brain stimulation (DBS). The text expressed a positive attitude toward DBS in one experimental condition or focused on the negative aspects of this method in the other condition. Then participants in both conditions read the same text that dealt with a study about DBS as experimental treatment in a small sample of patients with major depression. Perceived conflict between the two texts was found to increase the perception of tentativeness and to decrease the perception of scientific credibility, implicating that text-inherent aspects have significant effects on critical appraisal. The results of Study 2 demonstrated that participants with higher general self-efficacy detected the tentativeness to a lesser degree and assumed a higher level of scientific credibility, indicating a more naïve understanding of scientific information. This appears to be contradictory to large parts of previous findings that showed positive effects of high self-efficacy on learning. Both studies showed that perceived tentativeness and perceived scientific credibility of medical information contradicted each other. We conclude that there is a need for supporting laypeople in understanding the uncertainty of scientific information and that scientific writers should

  6. Addressing Uncertainty in Contaminant Transport in Groundwater Using the Ensemble Kalman Filter

    NASA Astrophysics Data System (ADS)

    Dwivedi, D.; Mohanty, B. P.

    2011-12-01

    Nitrate in groundwater shows significant uncertainty which arises from sparse data and interaction among multiple geophysical factors such as source availability (land use), thickness and composition of the vadose zone, types of aquifers (confined or unconfined), aquifer heterogeneity (geological and alluvial), precipitation characteristics, etc. This work presents the fusion of the ensemble Kalman filter (EnKF) with the numerical groundwater flow model MODFLOW and the solute transport model MT3DMS. The EnKF is a sequential data assimilation approach, which is applied to quantify and reduce the uncertainty of groundwater flow and solute transport models. We conducted numerical simulation experiments for the period January 1990 to December 2005 with MODFLOW and MT3DMS models for variably saturated groundwater flow in various aquifers across Texas. The EnKF was used to update the model parameters, hydraulic conductivity, hydraulic head and solute concentration. Results indicate that the EnKF method notably improves the estimation of the hydraulic conductivity distribution and solute transport prediction by assimilating piezometric head measurements with a known nitrate initial condition. A better estimation of hydraulic conductivity and assimilation of continuous measurements of solute concentrations resulted in reduced uncertainty in MODFLOW and MT3DMS models. It was found that the observation locations and locations in spatial proximity were appropriately corrected by the EnKF. The knowledge of nitrate plume evolution provided an insight into model structure, parameters, and sources of uncertainty.

  7. Life-cycle greenhouse gas assessment of Nigerian liquefied natural gas addressing uncertainty.

    PubMed

    Safaei, Amir; Freire, Fausto; Henggeler Antunes, Carlos

    2015-03-17

    Natural gas (NG) has been regarded as a bridge fuel toward renewable sources and is expected to play a greater role in future global energy mix; however, a high degree of uncertainty exists concerning upstream (well-to-tank, WtT) greenhouse gas (GHG) emissions of NG. In this study, a life-cycle (LC) model is built to assess uncertainty in WtT GHG emissions of liquefied NG (LNG) supplied to Europe by Nigeria. The 90% prediction interval of GHG intensity of Nigerian LNG was found to range between 14.9 and 19.3 g CO2 eq/MJ, with a mean value of 16.8 g CO2 eq/MJ. This intensity was estimated considering no venting practice in Nigerian fields. The mean estimation can shift up to 25 g CO2 eq when considering a scenario with a higher rate of venting emissions. A sensitivity analysis of the time horizon to calculate GHG intensity was also performed showing that higher GHG intensity and uncertainty are obtained for shorter time horizons, due to the higher impact factor of methane. The uncertainty calculated for Nigerian LNG, specifically regarding the gap of data for methane emissions, recommends initiatives to measure and report emissions and further LC studies to identify hotspots to reduce the GHG intensity of LNG chains.

  8. Cost effectiveness of antimicrobial catheters in the intensive care unit: addressing uncertainty in the decision

    PubMed Central

    Halton, Kate A; Cook, David A; Whitby, Michael; Paterson, David L; Graves, Nicholas

    2009-01-01

    Introduction Some types of antimicrobial-coated central venous catheters (A-CVC) have been shown to be cost effective in preventing catheter-related bloodstream infection (CR-BSI). However, not all types have been evaluated, and there are concerns over the quality and usefulness of these earlier studies. There is uncertainty amongst clinicians over which, if any, A-CVCs to use. We re-evaluated the cost effectiveness of all commercially available A-CVCs for prevention of CR-BSI in adult intensive care unit (ICU) patients. Methods We used a Markov decision model to compare the cost effectiveness of A-CVCs relative to uncoated catheters. Four catheter types were evaluated: minocycline and rifampicin (MR)-coated catheters, silver, platinum and carbon (SPC)-impregnated catheters, and two chlorhexidine and silver sulfadiazine-coated catheters; one coated on the external surface (CH/SSD (ext)) and the other coated on both surfaces (CH/SSD (int/ext)). The incremental cost per quality-adjusted life year gained and the expected net monetary benefits were estimated for each. Uncertainty arising from data estimates, data quality and heterogeneity was explored in sensitivity analyses. Results The baseline analysis, with no consideration of uncertainty, indicated all four types of A-CVC were cost-saving relative to uncoated catheters. MR-coated catheters prevented 15 infections per 1,000 catheters and generated the greatest health benefits, 1.6 quality-adjusted life years, and cost savings (AUD $130,289). After considering uncertainty in the current evidence, the MR-coated catheters returned the highest incremental monetary net benefits of AUD $948 per catheter; however there was a 62% probability of error in this conclusion. Although the MR-coated catheters had the highest monetary net benefits across multiple scenarios, the decision was always associated with high uncertainty. Conclusions Current evidence suggests that the cost effectiveness of using A-CVCs within the ICU is

  9. The future of human embryonic stem cell research: addressing ethical conflict with responsible scientific research.

    PubMed

    Gilbert, David M

    2004-05-01

    Embryonic stem (ES) cells have almost unlimited regenerative capacity and can potentially generate any body tissue. Hence they hold great promise for the cure of degenerative human diseases. But their derivation and the potential for misuse have raised a number of ethical issues. These ethical issues threaten to paralyze pubic funding for ES cell research, leaving experimentation in the hands of the private sector and precluding the public's ability to monitor practices, research alternatives, and effectively address the very ethical issues that are cause for concern in the first place. With new technology being inevitable, and the potential for abuse high, government must stay involved if the public is to play a role in shaping the direction of research. In this essay, I will define levels of ethical conflict that can be delineated by the anticipated advances in technology. From the urgent need to derive new ES cell lines with existing technology, to the most far-reaching goal of deriving genetically identical tissues from an adult patients cells, technology-specific ethical dilemmas can be defined and addressed. This staged approach provides a solid ethical framework for moving forward with ES cell research. Moreover, by anticipating the moral conflicts to come, one can predict the types of scientific advances that could overcome these conflicts, and appropriately direct federal funding toward these goals to offset potentially less responsible research directives that will inevitably go forward via private or foreign funding.

  10. Frames of scientific evidence: How journalists represent the (un)certainty of molecular medicine in science television programs.

    PubMed

    Ruhrmann, Georg; Guenther, Lars; Kessler, Sabrina Heike; Milde, Jutta

    2015-08-01

    For laypeople, media coverage of science on television is a gateway to scientific issues. Defining scientific evidence is central to the field of science, but there are still questions if news coverage of science represents scientific research findings as certain or uncertain. The framing approach is a suitable framework to classify different media representations; it is applied here to investigate the frames of scientific evidence in film clips (n=207) taken from science television programs. Molecular medicine is the domain of interest for this analysis, due to its high proportion of uncertain and conflicting research findings and risks. The results indicate that television clips vary in their coverage of scientific evidence of molecular medicine. Four frames were found: Scientific Uncertainty and Controversy, Scientifically Certain Data, Everyday Medical Risks, and Conflicting Scientific Evidence. They differ in their way of framing scientific evidence and risks of molecular medicine.

  11. LCA of emerging technologies: addressing high uncertainty on inputs' variability when performing global sensitivity analysis.

    PubMed

    Lacirignola, Martino; Blanc, Philippe; Girard, Robin; Pérez-López, Paula; Blanc, Isabelle

    2017-02-01

    In the life cycle assessment (LCA) context, global sensitivity analysis (GSA) has been identified by several authors as a relevant practice to enhance the understanding of the model's structure and ensure reliability and credibility of the LCA results. GSA allows establishing a ranking among the input parameters, according to their influence on the variability of the output. Such feature is of high interest in particular when aiming at defining parameterized LCA models. When performing a GSA, the description of the variability of each input parameter may affect the results. This aspect is critical when studying new products or emerging technologies, where data regarding the model inputs are very uncertain and may cause misleading GSA outcomes, such as inappropriate input rankings. A systematic assessment of this sensitivity issue is now proposed. We develop a methodology to analyze the sensitivity of the GSA results (i.e. the stability of the ranking of the inputs) with respect to the description of such inputs of the model (i.e. the definition of their inherent variability). With this research, we aim at enriching the debate on the application of GSA to LCAs affected by high uncertainties. We illustrate its application with a case study, aiming at the elaboration of a simple model expressing the life cycle greenhouse gas emissions of enhanced geothermal systems (EGS) as a function of few key parameters. Our methodology allows identifying the key inputs of the LCA model, taking into account the uncertainty related to their description.

  12. Adapting to climate change despite scientific uncertainty: A case study of coastal protection from sea-level rise in Kiribati

    NASA Astrophysics Data System (ADS)

    Donner, S. D.

    2013-12-01

    Climate change adaptation is an increasing focus of international aid. At recent meetings of the parties to the United Nations Framework Convention on Climate Change (UNFCCC), the developed world agreed to rapidly increase international assistance to help developing countries, like the low-lying island nation of Kiribati, respond to the impacts of climate change. These emerging adaptation efforts must proceed despite the large and partially irreducible scientific uncertainty about the magnitude of those future climate impacts. In this study, we use the example of efforts to adapt to sea-level rise in Kiribati to document the challenges facing such internationally-funded climate change adaptation projects given the scientific uncertainty about climate impacts. Drawing on field and document research, we describe the scientific uncertainty about projected sea-level rise in Tarawa, the capital of Kiribati, how that uncertainty can create trade-offs between adaptation measures, and the social, political and economic context in which adaptation decisions must be made. The analysis shows there is no 'silver bullet' adaptation strategy in countries like Kiribati, given the long-term scientific uncertainty about sea-level rise and the environment of climate change aid. The existence of irreducible scientific uncertainty does not preclude effective climate change adaptation, but instead requires adaptation programs that embrace multiple strategies and planning horizons, and continually build on and re-adjust previous investments. This work highlights the importance of sustained international climate change financing, as proposed in UNFCCC negotiations.

  13. Mars 2001 Mission: Addressing Scientific Questions Regarding the Characteristics and Origin of Local Bedrock and Soil

    NASA Technical Reports Server (NTRS)

    Saunders, R. S.; Arvidson, R. E.; Weitz, C. M.; Marshall, J.; Squyres, S. W.; Christensen, P. R.; Meloy, T.; Smith, P.

    1999-01-01

    The Mars Surveyor Program 2001 Mission will carry instruments on the orbiter, lander and rover that will support synergistic observations and experiments to address important scientific questions regarding the local bedrock and soils. The martian surface is covered in varying degrees by fine materials less than a few mms in size. Viking and Pathfinder images of the surface indicate that soils at those sites are composed of fine particles. Wheel tracks from the Sojourner rover suggest that soil deposits are composed of particles <40 mm. Viking images show that dunes are common in many areas on Mars and new MOC images indicate that dunes occur nearly everywhere. Dunes on Mars are thought to be composed of 250-500 microns particles based upon Viking IRTM data and Mars wind tunnel experiments. If martian dunes are composed of sand particles > 100 microns and soils are dominated by <10 micron particles, then where are the intermediate grain sizes? Have they been wom away through prolonged transport over the eons? Were they never generated to begin with? Or are they simply less easy to identify because do they not form distinctive geomorphic features such as dunes or uniform mantles that tend to assume superposition in the soil structure?

  14. Uncertainty

    USGS Publications Warehouse

    Hunt, Randall J.

    2012-01-01

    Management decisions will often be directly informed by model predictions. However, we now know there can be no expectation of a single ‘true’ model; thus, model results are uncertain. Understandable reporting of underlying uncertainty provides necessary context to decision-makers, as model results are used for management decisions. This, in turn, forms a mechanism by which groundwater models inform a risk-management framework because uncertainty around a prediction provides the basis for estimating the probability or likelihood of some event occurring. Given that the consequences of management decisions vary, it follows that the extent of and resources devoted to an uncertainty analysis may depend on the consequences. For events with low impact, a qualitative, limited uncertainty analysis may be sufficient for informing a decision. For events with a high impact, on the other hand, the risks might be better assessed and associated decisions made using a more robust and comprehensive uncertainty analysis. The purpose of this chapter is to provide guidance on uncertainty analysis through discussion of concepts and approaches, which can vary from heuristic (i.e. the modeller’s assessment of prediction uncertainty based on trial and error and experience) to a comprehensive, sophisticated, statistics-based uncertainty analysis. Most of the material presented here is taken from Doherty et al. (2010) if not otherwise cited. Although the treatment here is necessarily brief, the reader can find citations for the source material and additional references within this chapter.

  15. Addressing the Dynamics of Science in Curricular Reform for Scientific Literacy: The Case of Genomics

    ERIC Educational Resources Information Center

    van Eijck, Michiel

    2010-01-01

    Science education reform must anticipate the scientific literacy required by the next generation of citizens. Particularly, this counts for rapidly emerging and evolving scientific disciplines such as genomics. Taking this discipline as a case, such anticipation is becoming increasingly problematic in today's knowledge societies in which the…

  16. Science Teachers' Use of Mass Media to Address Socio-Scientific and Sustainability Issues

    ERIC Educational Resources Information Center

    Klosterman, Michelle L.; Sadler, Troy D.; Brown, Julie

    2012-01-01

    The currency, relevancy and changing nature of science makes it a natural topic of focus for mass media outlets. Science teachers and students can capitalize on this wealth of scientific information to explore socio-scientific and sustainability issues; however, without a lens on how those media are created and how representations of science are…

  17. Novel developments in benthic modelling to address scientific and policy challenges

    NASA Astrophysics Data System (ADS)

    Lessin, Gennadi; Artioli, Yuri; Bruggeman, Jorn; Aldridge, John; Blackford, Jerry

    2016-04-01

    Understanding the role of benthic systems in supporting, regulating and providing marine ecosystem services requires better understanding of their functioning and their response and resilience to stressors. Novel observational methods for the investigation of dynamics of benthic-pelagic coupling in shelf seas are being developed and new data is being collected. Therefore there is an increasing demand for robust representation of benthic processes in marine biogeochemical and ecosystem models, which would improve our understanding of whole systems and benthic-pelagic coupling, rather than act as mere closure terms for pelagic models. However, for several decades development of benthic models has lagged behind their pelagic counterparts. To address contemporary scientific, policy and societal challenges, the biogeochemical and ecological model ERSEM (European Regional Seas Ecosystem Model), including its benthic sub-model, was recently recoded in a scalable and modular format adopting the approach of FABM (Framework for Aquatic Biogeochemical Models). Within the Shelf Sea Biogeochemistry research programme, a series of additional processes have been included, such as a sedimentary carbonate system, a resuspendable fluff layer, and the simulation of advective sediments. It was shown that the inclusion of these processes changes the dynamics of benthic-pelagic fluxes as well as modifying the benthic food web. Comparison of model results with in-situ data demonstrated a general improvement of model performance and highlighted the importance of the benthic system in overall ecosystem dynamics. As an example, our simulations have shown that inclusion of a resuspendable fluff layer facilitates regeneration of inorganic nutrients in the water column due to degradation of resuspended organic material by pelagic bacteria. Moreover, the composition of fluff was found to be important for trophic interactions, and therefore indirectly affects benthic community composition. Where

  18. Advanced Test Reactor National Scientific User Facility: Addressing advanced nuclear materials research

    SciTech Connect

    John Jackson; Todd Allen; Frances Marshall; Jim Cole

    2013-03-01

    The Advanced Test Reactor National Scientific User Facility (ATR NSUF), based at the Idaho National Laboratory in the United States, is supporting Department of Energy and industry research efforts to ensure the properties of materials in light water reactors are well understood. The ATR NSUF is providing this support through three main efforts: establishing unique infrastructure necessary to conduct research on highly radioactive materials, conducting research in conjunction with industry partners on life extension relevant topics, and providing training courses to encourage more U.S. researchers to understand and address LWR materials issues. In 2010 and 2011, several advanced instruments with capability focused on resolving nuclear material performance issues through analysis on the micro (10-6 m) to atomic (10-10 m) scales were installed primarily at the Center for Advanced Energy Studies (CAES) in Idaho Falls, Idaho. These instruments included a local electrode atom probe (LEAP), a field-emission gun scanning transmission electron microscope (FEG-STEM), a focused ion beam (FIB) system, a Raman spectrometer, and an nanoindentor/atomic force microscope. Ongoing capability enhancements intended to support industry efforts include completion of two shielded, irradiation assisted stress corrosion cracking (IASCC) test loops, the first of which will come online in early calendar year 2013, a pressurized and controlled chemistry water loop for the ATR center flux trap, and a dedicated facility intended to house post irradiation examination equipment. In addition to capability enhancements at the main site in Idaho, the ATR NSUF also welcomed two new partner facilities in 2011 and two new partner facilities in 2012; the Oak Ridge National Laboratory, High Flux Isotope Reactor (HFIR) and associated hot cells and the University California Berkeley capabilities in irradiated materials analysis were added in 2011. In 2012, Purdue University’s Interaction of Materials

  19. A Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community System.

    ERIC Educational Resources Information Center

    Chen, Hsinchun; Ng, Tobun D.; Martinez, Joanne; Schatz, Bruce R.

    1997-01-01

    Presents an algorithmic approach to addressing the vocabulary problem in scientific information retrieval and information sharing, using the molecular biology domain as an example. A cognitive study and a follow-up document retrieval study were conducted using first a conjoined fly-worm thesaurus and then an actual worm database and the conjoined…

  20. Dealing with uncertainty: integrating local and scientific knowledge of the climate and weather.

    PubMed

    Kniveton, Dominic; Visman, Emma; Tall, Arame; Diop, Mariane; Ewbank, Richard; Njoroge, Ezekiel; Pearson, Lucy

    2015-01-01

    While climate science has made great progress in the projection of weather and climate information, its uptake by local communities remains largely elusive. This paper describes two innovative approaches that strengthen understanding between the providers and users of weather and climate information and support-appropriate application: (1) knowledge timelines, which compare different sources and levels of certainty in community and scientific weather and climate information; and (2) participatory downscaling, which supports users to translate national and regional information into a range of outcomes at the local level. Results from piloting these approaches among flood-prone communities in Senegal and drought-prone farmers in Kenya highlight the importance of co-producing 'user-useful' climate information. Recognising that disaster risk management actions draw on a wide range of knowledge sources, climate information that can effectively support community-based decision-making needs to be integrated with local knowledge systems and based on an appreciation of the inherent uncertainty of weather and climate information.

  1. Progression in Ethical Reasoning When Addressing Socio-Scientific Issues in Biotechnology

    ERIC Educational Resources Information Center

    Berne, Birgitta

    2014-01-01

    This article reports on the outcomes of an intervention in a Swedish school in which the author, a teacher-researcher, sought to develop students' (14-15 years old) ethical reasoning in science through the use of peer discussions about socio-scientific issues. Prior to the student discussions various prompts were used to highlight different…

  2. Encouraging Uncertainty in the "Scientific Method": Promoting Understanding in the Processes of Science with Preservice Teachers

    ERIC Educational Resources Information Center

    Melville, Wayne; Bartley, Anthony; Fazio, Xavier

    2012-01-01

    Teachers' feelings of uncertainty are an overlooked, though crucial, condition necessary for the promotion of educational change. This article investigates the feelings of uncertainty that preservice teachers have toward the conduct of science as inquiry and the extent to which methods courses can confront and embrace those uncertainties. Our work…

  3. Uncertainty as knowledge

    PubMed Central

    Lewandowsky, Stephan; Ballard, Timothy; Pancost, Richard D.

    2015-01-01

    This issue of Philosophical Transactions examines the relationship between scientific uncertainty about climate change and knowledge. Uncertainty is an inherent feature of the climate system. Considerable effort has therefore been devoted to understanding how to effectively respond to a changing, yet uncertain climate. Politicians and the public often appeal to uncertainty as an argument to delay mitigative action. We argue that the appropriate response to uncertainty is exactly the opposite: uncertainty provides an impetus to be concerned about climate change, because greater uncertainty increases the risks associated with climate change. We therefore suggest that uncertainty can be a source of actionable knowledge. We survey the papers in this issue, which address the relationship between uncertainty and knowledge from physical, economic and social perspectives. We also summarize the pervasive psychological effects of uncertainty, some of which may militate against a meaningful response to climate change, and we provide pointers to how those difficulties may be ameliorated. PMID:26460108

  4. Addressing Stability Robustness, Period Uncertainties, and Startup of Multiple-Period Repetitive Control for Spacecraft Jitter Mitigation

    NASA Astrophysics Data System (ADS)

    Ahn, Edwin S.

    Repetitive Control (RC) is a relatively new form of control that seeks to converge to zero tracking error when executing a periodic command, or when executing a constant command in the presence of a periodic disturbance. The design makes use of knowledge of the period of the disturbance or command, and makes use of the error observed in the previous period to update the command in the present period. The usual RC approaches address one period, and this means that potentially they can simultaneously address DC or constant error, the fundamental frequency for that period, and all harmonics up to Nyquist frequency. Spacecraft often have multiple sources of periodic excitation. Slight imbalance in reaction wheels used for attitude control creates three disturbance periods. A special RC structure was developed to allow one to address multiple unrelated periods which is referred to as Multiple-Period Repetitive Control (MPRC). MPRC in practice faces three main challenges for hardware implementation. One is instability due to model errors or parasitic high frequency modes, the second is degradation of the final error level due to period uncertainties or fluctuations, and the third is bad transients due to issues in startup. Regarding these three challenges, the thesis develops a series of methods to enhance the performance of MPRC or to assist in analyzing its performance for mitigating optical jitter induced by mechanical vibration within the structure of a spacecraft testbed. Experimental analysis of MPRC shows contrasting advantages over existing adaptive control algorithms, such as Filtered-X LMS, Adaptive Model Predictive Control, and Adaptive Basis Method, for mitigating jitter within the transmitting beam of Laser Communication (LaserCom) satellites.

  5. The optimisation approach of ALARA in nuclear practice: an early application of the precautionary principle. Scientific uncertainty versus legal uncertainty.

    PubMed

    Lierman, S; Veuchelen, L

    2005-01-01

    The late health effects of exposure to low doses of ionising radiation are subject to scientific controversy: one view finds threats of high cancer incidence exaggerated, while the other view thinks the effects are underestimated. Both views have good scientific arguments in favour of them. Since the nuclear field, both industry and medicine have had to deal with this controversy for many decades. One can argue that the optimisation approach to keep the effective doses as low as reasonably achievable, taking economic and social factors into account (ALARA), is a precautionary approach. However, because of these stochastic effects, no scientific proof can be provided. This paper explores how ALARA and the Precautionary Principle are influential in the legal field and in particular in tort law, because liability should be a strong incentive for safer behaviour. This so-called "deterrence effect" of liability seems to evaporate in today's technical and highly complex society, in particular when dealing with the late health effects of low doses of ionising radiation. Two main issues will be dealt with in the paper: 1. How are the health risks attributable to "low doses" of radiation regulated in nuclear law and what lessons can be learned from the field of radiation protection? 2. What does ALARA have to inform the discussion of the Precautionary Principle and vice-versa, in particular, as far as legal sanctions and liability are concerned? It will be shown that the Precautionary Principle has not yet been sufficiently implemented into nuclear law.

  6. Scientific problems addressed by the Spektr-UV space project (world space Observatory—Ultraviolet)

    NASA Astrophysics Data System (ADS)

    Boyarchuk, A. A.; Shustov, B. M.; Savanov, I. S.; Sachkov, M. E.; Bisikalo, D. V.; Mashonkina, L. I.; Wiebe, D. Z.; Shematovich, V. I.; Shchekinov, Yu. A.; Ryabchikova, T. A.; Chugai, N. N.; Ivanov, P. B.; Voshchinnikov, N. V.; Gomez de Castro, A. I.; Lamzin, S. A.; Piskunov, N.; Ayres, T.; Strassmeier, K. G.; Jeffrey, S.; Zwintz, S. K.; Shulyak, D.; Gérard, J.-C.; Hubert, B.; Fossati, L.; Lammer, H.; Werner, K.; Zhilkin, A. G.; Kaigorodov, P. V.; Sichevskii, S. G.; Ustamuich, S.; Kanev, E. N.; Kil'pio, E. Yu.

    2016-01-01

    The article presents a review of scientific problems and methods of ultraviolet astronomy, focusing on perspective scientific problems (directions) whose solution requires UV space observatories. These include reionization and the history of star formation in the Universe, searches for dark baryonic matter, physical and chemical processes in the interstellar medium and protoplanetary disks, the physics of accretion and outflows in astrophysical objects, from Active Galactic Nuclei to close binary stars, stellar activity (for both low-mass and high-mass stars), and processes occurring in the atmospheres of both planets in the solar system and exoplanets. Technological progress in UV astronomy achieved in recent years is also considered. The well advanced, international, Russian-led Spektr-UV (World Space Observatory—Ultraviolet) project is described in more detail. This project is directed at creating a major space observatory operational in the ultraviolet (115-310 nm). This observatory will provide an effective, and possibly the only, powerful means of observing in this spectral range over the next ten years, and will be an powerful tool for resolving many topical scientific problems.

  7. Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors: Final Scientific/Technical Report

    SciTech Connect

    Vierow, Karen; Aldemir, Tunc

    2009-09-10

    The project entitled, “Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors”, was conducted as a DOE NERI project collaboration between Texas A&M University and The Ohio State University between March 2006 and June 2009. The overall goal of the proposed project was to develop practical approaches and tools by which dynamic reliability and risk assessment techniques can be used to augment the uncertainty quantification process in probabilistic risk assessment (PRA) methods and PRA applications for Generation IV reactors. This report is the Final Scientific/Technical Report summarizing the project.

  8. Progression in Ethical Reasoning When Addressing Socio-scientific Issues in Biotechnology

    NASA Astrophysics Data System (ADS)

    Berne, Birgitta

    2014-11-01

    This article reports on the outcomes of an intervention in a Swedish school in which the author, a teacher-researcher, sought to develop students' (14-15 years old) ethical reasoning in science through the use of peer discussions about socio-scientific issues. Prior to the student discussions various prompts were used to highlight different aspects of the issues. In addition, students were given time to search for further information themselves. Analysis of students' written arguments, from the beginning of the intervention and afterwards, suggests that many students seem to be moving away from their use of everyday language towards using scientific concepts in their arguments. In addition, they moved from considering cloning and 'designer babies' solely in terms of the present to considering them in terms of the future. Furthermore, the students started to approach the issues in additional ways using not only consequentialism but also the approaches of virtue ethics, and rights and duties. Students' progression in ethical reasoning could be related to the characteristics of the interactions in peer discussions as students who critically and constructively argued with each other's ideas, and challenged each other's claims, made progress in more aspects of ethical reasoning than students merely using cumulative talk. As such, the work provides valuable indications for the importance of introducing peer discussions and debates about SSIs in connection to biotechnology into the teaching of science in schools.

  9. An Analysis Framework Addressing the Scale and Legibility of Large Scientific Data Sets

    SciTech Connect

    Childs, Hank R.

    2006-01-01

    Much of the previous work in the large data visualization area has solely focused on handling the scale of the data. This task is clearly a great challenge and necessary, but it is not sufficient. Applying standard visualization techniques to large scale data sets often creates complicated pictures where meaningful trends are lost. A second challenge, then, is to also provide algorithms that simplify what an analyst must understand, using either visual or quantitative means. This challenge can be summarized as improving the legibility or reducing the complexity of massive data sets. Fully meeting both of these challenges is the work of many, many PhD dissertations. In this dissertation, we describe some new techniques to address both the scale and legibility challenges, in hope of contributing to the larger solution. In addition to our assumption of simultaneously addressing both scale and legibility, we add an additional requirement that the solutions considered fit well within an interoperable framework for diverse algorithms, because a large suite of algorithms is often necessary to fully understand complex data sets. For scale, we present a general architecture for handling large data, as well as details of a contract-based system for integrating advanced optimizations into a data flow network design. We also describe techniques for volume rendering and performing comparisons at the extreme scale. For legibility, we present several techniques. Most noteworthy are equivalence class functions, a technique to drive visualizations using statistical methods, and line-scan based techniques for characterizing shape.

  10. Addressing Emerging Risks: Scientific and Regulatory Challenges Associated with Environmentally Persistent Free Radicals

    PubMed Central

    Dugas, Tammy R.; Lomnicki, Slawomir; Cormier, Stephania A.; Dellinger, Barry; Reams, Margaret

    2016-01-01

    Airborne fine and ultrafine particulate matter (PM) are often generated through widely-used thermal processes such as the combustion of fuels or the thermal decomposition of waste. Residents near Superfund sites are exposed to PM through the inhalation of windblown dust, ingestion of soil and sediments, and inhalation of emissions from the on-site thermal treatment of contaminated soils. Epidemiological evidence supports a link between exposure to airborne PM and an increased risk of cardiovascular and pulmonary diseases. It is well-known that during combustion processes, incomplete combustion can lead to the production of organic pollutants that can adsorb to the surface of PM. Recent studies have demonstrated that their interaction with metal centers can lead to the generation of a surface stabilized metal-radical complex capable of redox cycling to produce ROS. Moreover, these free radicals can persist in the environment, hence their designation as Environmentally Persistent Free Radicals (EPFR). EPFR has been demonstrated in both ambient air PM2.5 (diameter < 2.5 µm) and in PM from a variety of combustion sources. Thus, low-temperature, thermal treatment of soils can potentially increase the concentration of EPFR in areas in and around Superfund sites. In this review, we will outline the evidence to date supporting EPFR formation and its environmental significance. Furthermore, we will address the lack of methodologies for specifically addressing its risk assessment and challenges associated with regulating this new, emerging contaminant. PMID:27338429

  11. Addressing Emerging Risks: Scientific and Regulatory Challenges Associated with Environmentally Persistent Free Radicals.

    PubMed

    Dugas, Tammy R; Lomnicki, Slawomir; Cormier, Stephania A; Dellinger, Barry; Reams, Margaret

    2016-06-08

    Airborne fine and ultrafine particulate matter (PM) are often generated through widely-used thermal processes such as the combustion of fuels or the thermal decomposition of waste. Residents near Superfund sites are exposed to PM through the inhalation of windblown dust, ingestion of soil and sediments, and inhalation of emissions from the on-site thermal treatment of contaminated soils. Epidemiological evidence supports a link between exposure to airborne PM and an increased risk of cardiovascular and pulmonary diseases. It is well-known that during combustion processes, incomplete combustion can lead to the production of organic pollutants that can adsorb to the surface of PM. Recent studies have demonstrated that their interaction with metal centers can lead to the generation of a surface stabilized metal-radical complex capable of redox cycling to produce ROS. Moreover, these free radicals can persist in the environment, hence their designation as Environmentally Persistent Free Radicals (EPFR). EPFR has been demonstrated in both ambient air PM2.5 (diameter < 2.5 µm) and in PM from a variety of combustion sources. Thus, low-temperature, thermal treatment of soils can potentially increase the concentration of EPFR in areas in and around Superfund sites. In this review, we will outline the evidence to date supporting EPFR formation and its environmental significance. Furthermore, we will address the lack of methodologies for specifically addressing its risk assessment and challenges associated with regulating this new, emerging contaminant.

  12. Using Next Generation Science Standards (NGSS) Practices to Address Scientific Misunderstandings Around Complex Environmental Issues

    NASA Astrophysics Data System (ADS)

    Turrin, M.; Kenna, T. C.

    2014-12-01

    The new NGSS provide an important opportunity for scientists to develop curriculum that links the practice of science to research-based data in order to improve understanding in areas of science that are both complex and confusing. Our curriculum focuses in particular on the fate and transport of anthropogenic radionuclides. Radioactivity, both naturally occurring and anthropogenic, is highly debated and largely misunderstood, and for large sections of the population is a source of scientific misunderstanding. Developed as part of the international GEOTRACES project which focuses on identifying ocean processes and quantifying fluxes that control the distributions of selected trace elements and isotopes in the ocean, and on establishing the sensitivity of these distributions to changing environmental conditions, the curriculum topic fits nicely into the applied focus of NGSS with both environmental and topical relevance. Our curriculum design focuses on small group discussion driven by questions, yet unlike more traditional curriculum pieces these are not questions posed to the students, rather they are questions posed by the students to facilitate their deeper understanding. Our curriculum design challenges the traditional question/answer memorization approach to instruction as we strive to develop an educational approach that supports the practice of science as well as the NGSS Cross Cutting Concepts and the Science & Engineering Practices. Our goal is for students to develop a methodology they can employ when faced with a complex scientific issue. Through background readings and team discussions they identify what type of information is important for them to know and where to find a reliable source for that information. Framing their discovery around key questions such as "What type of radioactive decay are we dealing with?", "What is the potential half-life of the isotope?", and "What are the pathways of transport of radioactivity?" allows students to evaluate a

  13. Implementation of Scientific Community Laboratories and Their Effect on Student Conceptual Learning, Attitudes, and Understanding of Uncertainty

    NASA Astrophysics Data System (ADS)

    Lark, Adam

    Scientific Community Laboratories, developed by The University of Maryland, have shown initial promise as laboratories meant to emulate the practice of doing physics. These laboratories have been re-created by incorporating their design elements with the University of Toledo course structure and resources. The laboratories have been titled the Scientific Learning Community (SLC) Laboratories. A comparative study between these SLC laboratories and the University of Toledo physics department's traditional laboratories was executed during the fall 2012 semester on first semester calculus-based physics students. Three tests were executed as pre-test and post-tests to capture the change in students' concept knowledge, attitudes, and understanding of uncertainty. The Force Concept Inventory (FCI) was used to evaluate students' conceptual changes through the semester and average normalized gains were compared between both traditional and SLC laboratories. The Colorado Learning Attitudes about Science Survey for Experimental Physics (E-CLASS) was conducted to elucidate students' change in attitudes through the course of each laboratory. Finally, interviews regarding data analysis and uncertainty were transcribed and coded to track changes in the way students understand uncertainty and data analysis in experimental physics after their participation in both laboratory type. Students in the SLC laboratories showed a notable an increase conceptual knowledge and attitudes when compared to traditional laboratories. SLC students' understanding of uncertainty showed most improvement, diverging completely from students in the traditional laboratories, who declined throughout the semester.

  14. Building non-traditional collaborations to innovatively address climate-related scientific and management needs

    NASA Astrophysics Data System (ADS)

    Bamzai, A.; Mcpherson, R. A.

    2014-12-01

    The South Central Climate Science Center (SC-CSC) is one of eight regional centers formed by the U.S. Department of the Interior in order to provide decision makers with the science, tools, and information they need to address the impacts of climate variability and change on their areas of responsibility. The SC-CSC is operated through the U.S. Geological Survey, in partnership with a consortium led by the University of Oklahoma that also includes Texas Tech University, Oklahoma State University, Louisiana State University, the Chickasaw Nation, the Choctaw Nation of Oklahoma, and NOAA's Geophysical Fluid Dynamics Lab (GFDL). The SC-CSC is distinct from all other CSCs in that we have strategically included non-traditional collaborators directly within our governing consortium. The SC-CSC is the only CSC to include any Tribal nations amongst our consortium (the Chickasaw Nation and the Choctaw Nation of Oklahoma) and to employ a full-time tribal liaison. As a result and in partnership with Tribes, we are able to identify the unique challenges that the almost 70 federally recognized Tribes within our region face. We also can develop culturally sensitive research projects or outreach efforts that bridge western science and traditional knowledge to address their needs. In addition, the SC-CSC is the only CSC to include another federal institution (GFDL) amongst our consortium membership. GFDL is a world-leader in climate modeling and model interpretation. Partnering GFDL's expertise in the evaluation of climate models and downscaling methods with the SC-CSC's stakeholder-driven approach allows for the generation and dissemination of guidance documents and training to accompany the high quality datasets already in development. This presentation will highlight the success stories and co-benefits of the SC-CSC's collaborations with Tribal nations and with GFDL, as well as include information on how other partners can connect to our ongoing efforts.

  15. Eliciting climate experts' knowledge to address model uncertainties in regional climate projections: a case study of Guanacaste, Northwest Costa Rica

    NASA Astrophysics Data System (ADS)

    Grossmann, I.; Steyn, D. G.

    2014-12-01

    Global general circulation models typically cannot provide the detailed and accurate regional climate information required by stakeholders for climate adaptation efforts, given their limited capacity to resolve the regional topography and changes in local sea surface temperature, wind and circulation patterns. The study region in Northwest Costa Rica has a tropical wet-dry climate with a double-peak wet season. During the dry season the central Costa Rican mountains prevent tropical Atlantic moisture from reaching the region. Most of the annual precipitation is received following the northward migration of the ITCZ in May that allows the region to benefit from moist southwesterly flow from the tropical Pacific. The wet season begins with a short period of "early rains" and is interrupted by the mid-summer drought associated with the intensification and westward expansion of the North Atlantic subtropical high in late June. Model projections for the 21st century indicate a lengthening and intensification of the mid-summer drought and a weakening of the early rains on which current crop cultivation practices rely. We developed an expert elicitation to systematically address uncertainties in the available model projections of changes in the seasonal precipitation pattern. Our approach extends an elicitation approach developed previously at Carnegie Mellon University. Experts in the climate of the study region or Central American climate were asked to assess the mechanisms driving precipitation during each part of the season, uncertainties regarding these mechanisms, expected changes in each mechanism in a warming climate, and the capacity of current models to reproduce these processes. To avoid overconfidence bias, a step-by-step procedure was followed to estimate changes in the timing and intensity of precipitation during each part of the season. The questions drew upon interviews conducted with the regions stakeholders to assess their climate information needs. This

  16. How can present and future satellite missions support scientific studies that address ocean acidification?

    USGS Publications Warehouse

    Salisbury, Joseph; Vandemark, Douglas; Jonsson, Bror; Balch, William; Chakraborty, Sumit; Lohrenz, Steven; Chapron, Bertrand; Hales, Burke; Mannino, Antonio; Mathis, Jeremy T.; Reul, Nicolas; Signorini, Sergio; Wanninkhof, Rik; Yates, Kimberly K.

    2016-01-01

    Space-based observations offer unique capabilities for studying spatial and temporal dynamics of the upper ocean inorganic carbon cycle and, in turn, supporting research tied to ocean acidification (OA). Satellite sensors measuring sea surface temperature, color, salinity, wind, waves, currents, and sea level enable a fuller understanding of a range of physical, chemical, and biological phenomena that drive regional OA dynamics as well as the potentially varied impacts of carbon cycle change on a broad range of ecosystems. Here, we update and expand on previous work that addresses the benefits of space-based assets for OA and carbonate system studies. Carbonate chemistry and the key processes controlling surface ocean OA variability are reviewed. Synthesis of present satellite data streams and their utility in this arena are discussed, as are opportunities on the horizon for using new satellite sensors with increased spectral, temporal, and/or spatial resolution. We outline applications that include the ability to track the biochemically dynamic nature of water masses, to map coral reefs at higher resolution, to discern functional phytoplankton groups and their relationships to acid perturbations, and to track processes that contribute to acid variation near the land-ocean interface.

  17. Trends in scientific activity addressing transmissible spongiform encephalopathies: a bibliometric study covering the period 1973–2002

    PubMed Central

    Sanz-Casado, Elías; Ramírez-de Santa Pau, Margarita; Suárez-Balseiro, Carlos A; Iribarren-Maestro, Isabel; de Pedro-Cuesta, Jesús

    2006-01-01

    Background The purpose of this study is to analyse the trends in scientific research on transmissible spongiform encephalopathies by applying bibliometric tools to the scientific literature published between 1973 and 2002. Methods The data for the study were obtained from Medline database, in order to determine the volume of scientific output in the above period, the countries involved, the type of document and the trends in the subject matters addressed. The period 1973–2002 was divided in three sub-periods. Results We observed a significant growth in scientific production. The percentage of increase is 871.7 from 1973 to 2002. This is more evident since 1991 and particularly in the 1996–2001 period. The countries found to have the highest output were the United States, the United Kingdom, Japan, France and Germany. The evolution in the subject matters was almost constant in the three sub-periods in which the study was divided. In the first and second sub-periods, the subject matters of greatest interest were more general, i.e Nervous system or Nervous system diseases, Creutzfeldt-Jakob disease, Scrapie, and Chemicals and Drugs, but in the last sub-period, some changes were observed because the Prion-related matters had the greatest presence. Collaboration among authors is small from 1973 to 1992, but increases notably in the third sub-period, and also the number of authors and clusters formed. Some of the authors, like Gajdusek or Prusiner, appear in the whole period. Conclusion The study reveals a very high increase in scientific production. It is related also with the beginnings of research on bovine spongiform encephalopathy and variant Creutzfeldt-Jakob disease, with the establishment of progressive collaboration relationships and a reflection of public health concerns about this problem. PMID:17026743

  18. Crossing Science-Policy-Societal Boundaries to Reduce Scientific and Institutional Uncertainty in Small-Scale Fisheries.

    PubMed

    Sutton, Abigail M; Rudd, Murray A

    2016-10-01

    The governance of small-scale fisheries (SSF) is challenging due to the uncertainty, complexity, and interconnectedness of social, political, ecological, and economical processes. Conventional SSF management has focused on a centralized and top-down approach. A major criticism of conventional management is the over-reliance on 'expert science' to guide decision-making and poor consideration of fishers' contextually rich knowledge. That is thought to exacerbate the already low governance potential of SSF. Integrating scientific knowledge with fishers' knowledge is increasingly popular and is often assumed to help reduce levels of biophysical and institutional uncertainties. Many projects aimed at encouraging knowledge integration have, however, been unsuccessful. Our objective in this research was to assess factors that influence knowledge integration and the uptake of integrated knowledge into policy-making. We report results from 54 semi-structured interviews with SSF researchers and practitioners from around the globe. Our analysis is framed in terms of scientific credibility, societal legitimacy, and policy saliency, and we discuss cases that have been partially or fully successful in reducing uncertainty via push-and-pull-oriented boundary crossing initiatives. Our findings suggest that two important factors affect the science-policy-societal boundary: a lack of consensus among stakeholders about what constitutes credible knowledge and institutional uncertainty resulting from shifting policies and leadership change. A lack of training for scientific leaders and an apparent 'shelf-life' for community organizations highlight the importance of ongoing institutional support for knowledge integration projects. Institutional support may be enhanced through such investments, such as capacity building and specialized platforms for knowledge integration.

  19. Crossing Science-Policy-Societal Boundaries to Reduce Scientific and Institutional Uncertainty in Small-Scale Fisheries

    NASA Astrophysics Data System (ADS)

    Sutton, Abigail M.; Rudd, Murray A.

    2016-10-01

    The governance of small-scale fisheries (SSF) is challenging due to the uncertainty, complexity, and interconnectedness of social, political, ecological, and economical processes. Conventional SSF management has focused on a centralized and top-down approach. A major criticism of conventional management is the over-reliance on `expert science' to guide decision-making and poor consideration of fishers' contextually rich knowledge. That is thought to exacerbate the already low governance potential of SSF. Integrating scientific knowledge with fishers' knowledge is increasingly popular and is often assumed to help reduce levels of biophysical and institutional uncertainties. Many projects aimed at encouraging knowledge integration have, however, been unsuccessful. Our objective in this research was to assess factors that influence knowledge integration and the uptake of integrated knowledge into policy-making. We report results from 54 semi-structured interviews with SSF researchers and practitioners from around the globe. Our analysis is framed in terms of scientific credibility, societal legitimacy, and policy saliency, and we discuss cases that have been partially or fully successful in reducing uncertainty via push-and-pull-oriented boundary crossing initiatives. Our findings suggest that two important factors affect the science-policy-societal boundary: a lack of consensus among stakeholders about what constitutes credible knowledge and institutional uncertainty resulting from shifting policies and leadership change. A lack of training for scientific leaders and an apparent `shelf-life' for community organizations highlight the importance of ongoing institutional support for knowledge integration projects. Institutional support may be enhanced through such investments, such as capacity building and specialized platforms for knowledge integration.

  20. Beyond Sound Bites and News Quotes: NSIDC's Arctic Sea Ice and News Analysis Web blog and Scientific Uncertainty

    NASA Astrophysics Data System (ADS)

    Beitler, J.; Vizcarra, N.; Scambos, T. A.; Meier, W.

    2013-12-01

    The public, the media, and policymakers often turn to scientists for definite answers about Earth's changing climate. Researchers, in turn, offer observations with the caveat that there is always an amount of uncertainty in the data and the analysis. More or better data could modify trends. Random processes in Earth's most complex systems, like clouds, could contradict current theories about how they evolve and develop into weather systems that could put lives in danger. Often, these careful answers are reduced to a soundbite in TV or a quote in a newspaper report, and the public gets an answer, but the message of scientific uncertainty is almost always omitted. Arctic sea ice has long been recognized as a sensitive climate indicator, and has undergone a dramatic decline over the past thirty years. The National Snow and Ice Data Center has evolved into a top source for sea ice data and analysis. How does NSIDC respond to increasing questions about Arctic sea ice and climate and how does it communicate scientific uncertainty? This poster examines the ways that NSIDC's Arctic Sea Ice News and Analysis (ASINA) Web blog offers the public a transparent view of sea ice analysis, with discussions in scientific uncertainty that are lost in news reportage. It highlights the Web blog's interactive sea ice graph called ChArctic, which the pubic can use to explore sea ice data by year and make their own observations. It also discusses issues around the replacement of NSIDC's 20-year baseline with a new 30-year baseline for analyzing sea ice.

  1. Human health and endocrine disruption: a simple multicriteria framework for the qualitative assessment of end point specific risks in a context of scientific uncertainty.

    PubMed

    Martin, Olwenn V; Lester, John N; Voulvoulis, Nikolaos; Boobis, Alan R

    2007-08-01

    Endocrine disruption remains one of the most controversial contemporary environmental issues. While the desired level of protection is ultimately a societal choice, endocrine toxicity could result in a wide spectrum of adverse health effects. Although the application of the causal framework of weight-of-evidence approaches to complex toxicological issues has incited much interest, no international criteria or guidance have yet been developed. In this context, the evidence on end point-specific risks to human health contained in the International Program on Chemical Safety Global assessment of the State-of-Science on Endocrine Disruptors report was updated and assessed qualitatively using three simple criteria relevant to the practical application of the precautionary principle (PP): incidence trends, association, and consequence. The current degree of knowledge was then ranked according to ignorance, uncertainty, and risk. The main sources of scientific uncertainty in relation to incidence trends were associated with the evolution of diagnostic criteria or diagnostic tests, while genetic susceptibility is often proposed as an explanation for the wide geographic variations in the incidence of some diseases. Such genetic polymorphisms are also offered as a potential explanation for some of the inconsistent findings or lack of clear dose-response gradients described under the association criterion. The methodology yielded a relative paucity of data addressing directly the impact for adverse human health effect from both individual and public health perspectives. Results are discussed within the context of the application of the PP. Within a participatory context, this simple framework could provide a useful decision-making tool to both communicate scientific uncertainty to the wider public and manage uncertain risks.

  2. Trapped Between Two Tails: Trading Off Scientific Uncertainties via Climate Targets

    SciTech Connect

    Lemoine, Derek M.; McJeon, Haewon C.

    2013-08-20

    Climate change policies must trade off uncertainties about future warming, about the social and ecological impacts of warming, and about the cost of reducing greenhouse gas emissions. We show that laxer carbon targets produce broader distributions for climate damages, skewed towards severe outcomes. However, if potential low-carbon technologies fill overlapping niches, then more stringent carbon targets produce broader distributions for the cost of reducing emissions, skewed towards high-cost outcomes. We use the technology- rich GCAM integrated assessment model to assess the robustness of 450 ppm and 500 ppm carbon targets to each uncertain factor. The 500 ppm target provides net benefits across a broad range of futures. The 450 ppm target provides net benefits only when impacts are greater than conventionally assumed, when multiple technological breakthroughs lower the cost of abatement, or when evaluated with a low discount rate. Policy evaluations are more sensitive to uncertainty about abatement technology and impacts than to uncertainty about warming.

  3. Binary variable multiple-model multiple imputation to address missing data mechanism uncertainty: application to a smoking cessation trial.

    PubMed

    Siddique, Juned; Harel, Ofer; Crespi, Catherine M; Hedeker, Donald

    2014-07-30

    The true missing data mechanism is never known in practice. We present a method for generating multiple imputations for binary variables, which formally incorporates missing data mechanism uncertainty. Imputations are generated from a distribution of imputation models rather than a single model, with the distribution reflecting subjective notions of missing data mechanism uncertainty. Parameter estimates and standard errors are obtained using rules for nested multiple imputation. Using simulation, we investigate the impact of missing data mechanism uncertainty on post-imputation inferences and show that incorporating this uncertainty can increase the coverage of parameter estimates. We apply our method to a longitudinal smoking cessation trial where nonignorably missing data were a concern. Our method provides a simple approach for formalizing subjective notions regarding nonresponse and can be implemented using existing imputation software.

  4. Addressing Missing Data Mechanism Uncertainty using Multiple-Model Multiple Imputation: Application to a Longitudinal Clinical Trial.

    PubMed

    Siddique, Juned; Harel, Ofer; Crespi, Catherine M

    2012-12-01

    We present a framework for generating multiple imputations for continuous data when the missing data mechanism is unknown. Imputations are generated from more than one imputation model in order to incorporate uncertainty regarding the missing data mechanism. Parameter estimates based on the different imputation models are combined using rules for nested multiple imputation. Through the use of simulation, we investigate the impact of missing data mechanism uncertainty on post-imputation inferences and show that incorporating this uncertainty can increase the coverage of parameter estimates. We apply our method to a longitudinal clinical trial of low-income women with depression where nonignorably missing data were a concern. We show that different assumptions regarding the missing data mechanism can have a substantial impact on inferences. Our method provides a simple approach for formalizing subjective notions regarding nonresponse so that they can be easily stated, communicated, and compared.

  5. Science, law, and politics in FDA's genetically engineered foods policy: scientific concerns and uncertainties.

    PubMed

    Pelletier, David L

    2005-06-01

    The Food and Drug Administration's (FDA's) 1992 policy statement granted genetically engineered foods presumptive GRAS (generally recognized as safe) status. Since then, divergent views have been expressed concerning the scientific support for this policy. This paper examines four sources to better understand the basis for these claims: 1) internal FDA correspondence; 2) reports from the National Academy of Sciences; 3) research funded by US Department of Agriculture from 1981 to 2002; and 4) FDA's proposed rules issued in 2001. These sources reveal that little research has been conducted on unintended compositional changes from genetic engineering. Profiling techniques now make this feasible, but the new debate centers on the functional meaning of compositional changes.

  6. MODEL EVALUATION SCIENCE TO MEET TODAY'S QUALITY ASSURANCE REQUIREMENTS FOR REGULATORY USE: ADDRESSING UNCERTAINTY, SENSITIVITY, AND PARAMETERIZATION

    EPA Science Inventory

    The EPA/ORD National Exposure Research Lab's (NERL) UA/SA/PE research program addresses both tactical and strategic needs in direct support of ORD's client base. The design represents an integrated approach in achieving the highest levels of quality assurance in environmental de...

  7. MEETING IN TUCSON: MODEL EVALUATION SCIENCE TO MEET TODAY'S QUALITY ASSURANCE REQUIREMENTS FOR REGULATORY USE: ADDRESSING UNCERTAINTY, SENSITIVITY, AND PARAMETERIZATION

    EPA Science Inventory

    The EPA/ORD National Exposure Research Lab's (NERL) UA/SA/PE research program addresses both tactical and strategic needs in direct support of ORD's client base. The design represents an integrated approach in achieving the highest levels of quality assurance in environmental dec...

  8. The Role of Health Education in Addressing Uncertainty about Health and Cell Phone Use--A Commentary

    ERIC Educational Resources Information Center

    Ratnapradipa, Dhitinut; Dundulis, William P., Jr.; Ritzel, Dale O.; Haseeb, Abdul

    2012-01-01

    Although the fundamental principles of health education remain unchanged, the practice of health education continues to evolve in response to the rapidly changing lifestyles and technological advances. Emerging health risks are often associated with these lifestyle changes. The purpose of this article is to address the role of health educators…

  9. Effectiveness and Tradeoffs between Portfolios of Adaptation Strategies Addressing Future Climate and Socioeconomic Uncertainties in California's Central Valley

    NASA Astrophysics Data System (ADS)

    Tansey, M. K.; Van Lienden, B.; Das, T.; Munevar, A.; Young, C. A.; Flores-Lopez, F.; Huntington, J. L.

    2013-12-01

    The Central Valley of California is one of the major agricultural areas in the United States. The Central Valley Project (CVP) is operated by the Bureau of Reclamation to serve multiple purposes including generating approximately 4.3 million gigawatt hours of hydropower and providing, on average, 5 million acre-feet of water per year to irrigate approximately 3 million acres of land in the Sacramento, San Joaquin, and Tulare Lake basins, 600,000 acre-feet per year of water for urban users, and 800,000 acre-feet of annual supplies for environmental purposes. The development of effective adaptation and mitigation strategies requires assessing multiple risks including potential climate changes as well as uncertainties in future socioeconomic conditions. In this study, a scenario-based analytical approach was employed by combining three potential 21st century socioeconomic futures with six representative climate and sea level change projections developed using a transient hybrid delta ensemble method from an archive of 112 bias corrected spatially downscaled CMIP3 global climate model simulations to form 18 future socioeconomic-climate scenarios. To better simulate the effects of climate changes on agricultural water demands, analyses of historical agricultural meteorological station records were employed to develop estimates of future changes in solar radiation and atmospheric humidity from the GCM simulated temperature and precipitation. Projected changes in atmospheric carbon dioxide were computed directly by weighting SRES emissions scenarios included in each representative climate projection. These results were used as inputs to a calibrated crop water use, growth and yield model to simulate the effects of climate changes on the evapotranspiration and yields of major crops grown in the Central Valley. Existing hydrologic, reservoir operations, water quality, hydropower, greenhouse gas (GHG) emissions and both urban and agricultural economic models were integrated

  10. Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

    PubMed Central

    Curtis, Janelle M.R.

    2016-01-01

    Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along

  11. Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes.

    PubMed

    Naujokaitis-Lewis, Ilona; Curtis, Janelle M R

    2016-01-01

    Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along

  12. Toward Scientific Numerical Modeling

    NASA Technical Reports Server (NTRS)

    Kleb, Bil

    2007-01-01

    Ultimately, scientific numerical models need quantified output uncertainties so that modeling can evolve to better match reality. Documenting model input uncertainties and verifying that numerical models are translated into code correctly, however, are necessary first steps toward that goal. Without known input parameter uncertainties, model sensitivities are all one can determine, and without code verification, output uncertainties are simply not reliable. To address these two shortcomings, two proposals are offered: (1) an unobtrusive mechanism to document input parameter uncertainties in situ and (2) an adaptation of the Scientific Method to numerical model development and deployment. Because these two steps require changes in the computational simulation community to bear fruit, they are presented in terms of the Beckhard-Harris-Gleicher change model.

  13. Addressing solar modulation and long-term uncertainties in scaling secondary cosmic rays for in situ cosmogenic nuclide applications [rapid communication

    NASA Astrophysics Data System (ADS)

    Lifton, Nathaniel A.; Bieber, John W.; Clem, John M.; Duldig, Marc L.; Evenson, Paul; Humble, John E.; Pyle, Roger

    2005-10-01

    Solar modulation affects the secondary cosmic rays responsible for in situ cosmogenic nuclide (CN) production the most at the high geomagnetic latitudes to which CN production rates are traditionally referenced. While this has long been recognized (e.g., D. Lal, B. Peters, Cosmic ray produced radioactivity on the Earth, in: K. Sitte (Ed.), Handbuch Der Physik XLVI/2, Springer-Verlag, Berlin, 1967, pp. 551-612 and D. Lal, Theoretically expected variations in the terrestrial cosmic ray production rates of isotopes, in: G.C. Castagnoli (Ed.), Proceedings of the Enrico Fermi International School of Physics 95, Italian Physical Society, Varenna 1988, pp. 216-233), these variations can lead to potentially significant scaling model uncertainties that have not been addressed in detail. These uncertainties include the long-term (millennial-scale) average solar modulation level to which secondary cosmic rays should be referenced, and short-term fluctuations in cosmic ray intensity measurements used to derive published secondary cosmic ray scaling models. We have developed new scaling models for spallogenic nucleons, slow-muon capture and fast-muon interactions that specifically address these uncertainties. Our spallogenic nucleon scaling model, which includes data from portions of 5 solar cycles, explicitly incorporates a measure of solar modulation ( S), and our fast- and slow-muon scaling models (based on more limited data) account for solar modulation effects through increased uncertainties. These models improve on previously published models by better sampling the observed variability in measured cosmic ray intensities as a function of geomagnetic latitude, altitude, and solar activity. Furthermore, placing the spallogenic nucleon data in a consistent time-space framework allows for a more realistic assessment of uncertainties in our model than in earlier ones. We demonstrate here that our models reasonably account for the effects of solar modulation on measured

  14. Procedures for addressing uncertainty and variability in exposure to characterize potential health risk from trichloroethylene contaminated groundwater at Beale Air Force Base in California

    SciTech Connect

    Bogen, K T; Daniels, J I; Hall, L C

    1999-09-01

    This study was designed to accomplish two objectives. The first was to provide to the US Air Force and the regulatory community quantitative procedures that they might want to consider using for addressing uncertainty and variability in exposure to better characterize potential health risk. Such methods could be used at sites where populations may now or in the future be faced with using groundwater contaminated with low concentrations of the chemical trichloroethylene (TCE). The second was to illustrate and explain the application of these procedures with respect to available data for TCE in ground water beneath an inactive landfill site that is undergoing remediation at Beale Air Force Base in California. The results from this illustration provide more detail than the more traditional conservative deterministic, screening-level calculations of risk, also computed for purposes of comparison. Application of the procedures described in this report can lead to more reasonable and equitable risk-acceptability criteria for potentially exposed populations at specific sites.

  15. Procedures for addressing uncertainty and variability in exposure to characterize potential health risk from trichloroethylene contaminated ground water at Beale Air Force Base in California

    SciTech Connect

    Daniels, J I; Bogen, K T; Hall, L C

    1999-10-05

    Conservative deterministic, screening-level calculations of exposure and risk commonly are used in quantitative assessments of potential human-health consequences from contaminants in environmental media. However, these calculations generally are based on multiple upper-bound point estimates of input parameters, particularly for exposure attributes, and can therefore produce results for decision makers that actually overstate the need for costly remediation. Alternatively, a more informative and quantitative characterization of health risk can be obtained by quantifying uncertainty and variability in exposure. This process is illustrated in this report for a hypothetical population at a specific site at Beale Air Force Base in California, where there is trichloroethylene (TCE) contaminated ground water and a potential for future residential use. When uncertainty and variability in exposure were addressed jointly for this case, the 95th-percentile upper-bound value of individual excess lifetime cancer risk was a factor approaching 10 lower than the most conservative deterministic estimate. Additionally, the probability of more than zero additional cases of cancer can be estimated, and in this case it is less than 0.5 for a hypothetical future residential population of up to 26,900 individuals present for any 7.6-y interval of a 70-y time period. Clearly, the results from application of this probabilistic approach can provide reasonable and equitable risk-acceptability criteria for a contaminated site.

  16. Methods for Addressing Uncertainty and Variability to Characterize Potential Health Risk from Trichloroethylene-Contaminated Ground Water at Beale Air Force Base in California:Integration of Uncertainty and Variability in Pharmacokinetics and Dose-Response

    SciTech Connect

    Bogen, K T

    2001-05-24

    Traditional estimates of health risk are typically inflated, particularly if cancer is the dominant endpoint and there is fundamental uncertainty as to mechanism(s) of action. Risk is more realistically characterized if it accounts for joint uncertainty and interindividual variability within a systematic probabilistic framework to integrate the joint effects on risk of distributed parameters of all (linear as well as nonlinear) risk-extrapolation models involved. Such a framework was used to characterize risks to potential future residents posed by trichloroethylene (TCE) in ground water at an inactive landfill site on Beale Air Force Base in California. Variability and uncertainty were addressed in exposure-route-specific estimates of applied dose, in pharmacokinetically based estimates of route-specific metabolized fractions of absorbed TCE, and in corresponding biologically effective doses estimated under a genotoxic/linear (MA{sub G}) vs. a cytotoxic/nonlinear (MA{sub c}) mechanistic assumption for TCE-induced cancer. Increased risk conditional on effective dose was estimated under MA{sub G} based on seven rodent-bioassay data sets, and under MA{sub c} based on mouse hepatotoxicity data. Mean and upper-bound estimates of combined risk calculated by the unified approach were <10{sup -6} and 10{sup -4}, respectively, while corresponding estimates based on traditional deterministic methods were >10{sup -5} and 10{sup -4}, respectively. It was estimated that no TCE-related harm is likely to occur due to any plausible residential exposure scenario involving the site. The systematic probabilistic framework illustrated is particularly suited to characterizing risks that involve uncertain and/or diverse mechanisms of action.

  17. Methods for Addressing Uncertainty and Variability to Characterize Potential Health Risk From Trichloroethylene-Contaminated Ground Water Beale Air Force Base in California: Integration of Uncertainty and Variability in Pharmacokinetics and Dose-Response

    SciTech Connect

    Bogen, K.T.

    1999-09-29

    Traditional estimates of health risk are typically inflated, particularly if cancer is the dominant endpoint and there is fundamental uncertainty as to mechanism(s) of action. Risk is more realistically characterized if it accounts for joint uncertainty and interindividual variability after applying a unified probabilistic approach to the distributed parameters of all (linear as well as nonlinear) risk-extrapolation models involved. Such an approach was applied to characterize risks to potential future residents posed by trichloroethylene (TCE) in ground water at an inactive landfill site on Beale Air Force Base in California. Variability and uncertainty were addressed in exposure-route-specific estimates of applied dose, in pharmacokinetically based estimates of route-specific metabolized fractions of absorbed TCE, and in corresponding biologically effective doses estimated under a genotoxic/linear (MA{sub g}) vs. a cytotoxic/nonlinear (MA{sub c}) mechanistic assumption for TCE-induced cancer. Increased risk conditional on effective dose was estimated under MA{sub G} based on seven rodent-bioassay data sets, and under MA, based on mouse hepatotoxicity data. Mean and upper-bound estimates of combined risk calculated by the unified approach were <10{sup -6} and <10{sup -4}, respectively, while corresponding estimates based on traditional deterministic methods were >10{sup -5} and >10{sup -4}, respectively. It was estimated that no TCE-related harm is likely occur due any plausible residential exposure scenario involving the site. The unified approach illustrated is particularly suited to characterizing risks that involve uncertain and/or diverse mechanisms of action.

  18. Addressing the impact of environmental uncertainty in plankton model calibration with a dedicated software system: the Marine Model Optimization Testbed (MarMOT)

    NASA Astrophysics Data System (ADS)

    Hemmings, J. C. P.; Challenor, P. G.

    2011-08-01

    A wide variety of different marine plankton system models have been coupled with ocean circulation models, with the aim of understanding and predicting aspects of environmental change. However, an ability to make reliable inferences about real-world processes from the model behaviour demands a quantitative understanding of model error that remains elusive. Assessment of coupled model output is inhibited by relatively limited observing system coverage of biogeochemical components. Any direct assessment of the plankton model is further inhibited by uncertainty in the physical state. Furthermore, comparative evaluation of plankton models on the basis of their design is inhibited by the sensitivity of their dynamics to many adjustable parameters. The Marine Model Optimization Testbed is a new software tool designed for rigorous analysis of plankton models in a multi-site 1-D framework, in particular to address uncertainty issues in model assessment. A flexible user interface ensures its suitability to more general inter-comparison, sensitivity and uncertainty analyses, including model comparison at the level of individual processes, and to state estimation for specific locations. The principal features of MarMOT are described and its application to model calibration is demonstrated by way of a set of twin experiments, in which synthetic observations are assimilated in an attempt to recover the true parameter values of a known system. The experimental aim is to investigate the effect of different misfit weighting schemes on parameter recovery in the presence of error in the plankton model's environmental input data. Simulated errors are derived from statistical characterizations of the mixed layer depth, the horizontal flux divergences of the biogeochemical tracers and the initial state. Plausible patterns of uncertainty in these data are shown to produce strong temporal and spatial variability in the expected simulation error over an annual cycle, indicating

  19. Addressing the impact of environmental uncertainty in plankton model calibration with a dedicated software system: the Marine Model Optimization Testbed (MarMOT 1.1 alpha)

    NASA Astrophysics Data System (ADS)

    Hemmings, J. C. P.; Challenor, P. G.

    2012-04-01

    A wide variety of different plankton system models have been coupled with ocean circulation models, with the aim of understanding and predicting aspects of environmental change. However, an ability to make reliable inferences about real-world processes from the model behaviour demands a quantitative understanding of model error that remains elusive. Assessment of coupled model output is inhibited by relatively limited observing system coverage of biogeochemical components. Any direct assessment of the plankton model is further inhibited by uncertainty in the physical state. Furthermore, comparative evaluation of plankton models on the basis of their design is inhibited by the sensitivity of their dynamics to many adjustable parameters. Parameter uncertainty has been widely addressed by calibrating models at data-rich ocean sites. However, relatively little attention has been given to quantifying uncertainty in the physical fields required by the plankton models at these sites, and tendencies in the biogeochemical properties due to the effects of horizontal processes are often neglected. Here we use model twin experiments, in which synthetic data are assimilated to estimate a system's known "true" parameters, to investigate the impact of error in a plankton model's environmental input data. The experiments are supported by a new software tool, the Marine Model Optimization Testbed, designed for rigorous analysis of plankton models in a multi-site 1-D framework. Simulated errors are derived from statistical characterizations of the mixed layer depth, the horizontal flux divergence tendencies of the biogeochemical tracers and the initial state. Plausible patterns of uncertainty in these data are shown to produce strong temporal and spatial variability in the expected simulation error variance over an annual cycle, indicating variation in the significance attributable to individual model-data differences. An inverse scheme using ensemble-based estimates of the

  20. The Role of Uncertainty in Climate Science

    NASA Astrophysics Data System (ADS)

    Oreskes, N.

    2012-12-01

    Scientific discussions of climate change place considerable weight on uncertainty. The research frontier, by definition, rests at the interface between the known and the unknown and our scientific investigations necessarily track this interface. Yet, other areas of active scientific research are not necessarily characterized by a similar focus on uncertainty; previous assessments of science for policy, for example, do not reveal such extensive efforts at uncertainty quantification. Why has uncertainty loomed so large in climate science? This paper argues that the extensive discussions of uncertainty surrounding climate change are at least in part a response to the social and political context of climate change. Skeptics and contrarians focus on uncertainty as a political strategy, emphasizing or exaggerating uncertainties as a means to undermine public concern about climate change and delay policy action. The strategy works in part because it appeals to a certain logic: if our knowledge is uncertain, then it makes sense to do more research. Change, as the tobacco industry famously realized, requires justification; doubt favors the status quo. However, the strategy also works by pulling scientists into an "uncertainty framework," inspiring them to respond to the challenge by addressing and quantifying the uncertainties. The problem is that all science is uncertain—nothing in science is ever proven absolutely, positively—so as soon as one uncertainty is addressed, another can be raised, which is precisely what contrarians have done over the past twenty years.

  1. Science and Theatre Education: A Cross-disciplinary Approach of Scientific Ideas Addressed to Student Teachers of Early Childhood Education

    NASA Astrophysics Data System (ADS)

    Tselfes, Vasilis; Paroussi, Antigoni

    2009-09-01

    There is, in Greece, an ongoing attempt to breach the boundaries established between the different teaching-learning subjects of compulsory education. In this context, we are interested in exploring to what degree the teaching and learning of ideas from the sciences’ “internal life” (Hacking, in: Pickering (ed) Science as practice and culture, 1992) benefits from creatively coming into contact with theatrical education as part of the corresponding curriculum subject. To this end, 57 students of the Early Childhood Education Department of the University of Athens were called to study extracts from Galileo’s Dialogue Concerning the Two Chief World Systems, Ptolemaic and Copernican, to focus on a subject that the Dialogue’s “interlocutors” forcefully disagree about and to theatrically represent (using shadow theatre techniques) what they considered as being the central idea of this clash of opinions. The results indicate that this attempt leads to a satisfactory understanding of ideas relating to the content and methodology of the natural sciences. At the same time, theatrical education avails itself of the representation of scientific ideas and avoids the clichés and hackneyed techniques that the (often) simplistic choices available in the educational context of early childhood education tend towards. The basic reasons for both facets of this success are: (a) Genuine scientific texts force the students to approach them with seriousness, and all the more so if these recount the manner in which scientific ideas are produced and are embedded in the historical and social context of the age that created them; (b) The theatrical framework, which essentially guides the students’ activities, allows (if not obliges) them to approach scientific issues creatively; in other words, it allows them to create something related to science and recognize it as theirs; and, (c) Both the narrative texts describing processes of “science making” (Bruner, J Sci Educ

  2. Toward eliminating health disparities in HIV/AIDS: the importance of the minority investigator in addressing scientific gaps in Black and Latino communities.

    PubMed Central

    Fitzpatrick, Lisa K.; Sutton, Madeline; Greenberg, Alan E.

    2006-01-01

    Dialogue in the medical and public health communities has increasingly focused attention in the area of health disparities. We believe that the elimination of health disparities in the United States will require a multipronged approach that includes, at the very least, new approaches in both biomedical and prevention interventions. We also believe that since health disparities primarily affect communities of color, a model which fosters the development of junior scientists, clinicians and researchers of color who serve these communities will yield important progress in this field. The Minority HIV/AIDS Research Initiative at the Centers for Disease Control and Prevention (CDC) is a program that, through targeted research, aims to address health disparities in HIV/AIDS. Although the program is disease specific, there are a variety of lessons learned from its inception and implementation that can be useful throughout the scientific, medical and public health communities. PMID:17225832

  3. Balancing consumer protection and scientific integrity in the face of uncertainty: the example of gluten-free foods.

    PubMed

    McCabe, Margaret Sova

    2010-01-01

    In 2009, gluten-free foods were not only "hot" in the marketplace, several countries, including the United States, continued efforts to define gluten-free and appropriate labeling parameters. The regulatory process illuminates how difficult regulations based on safe scientific thresholds can be for regulators, manufacturers and consumers. This article analyzes the gluten-free regulatory landscape, challenges to defining a safe gluten threshold, and how consumers might need more label information beyond the term "gluten-free." The article includes an overview of international gluten-free regulations, the Food and Drug Administration (FDA) rulemaking process, and issues for consumers.

  4. Identification and evaluation of scientific uncertainties related to fish and aquatic resources in the Colorado River, Grand Canyon - summary and interpretation of an expert-elicitation questionnaire

    USGS Publications Warehouse

    Kennedy, Theodore A.

    2013-01-01

    Identifying areas of scientific uncertainty is a critical step in the adaptive management process (Walters, 1986; Runge, Converse, and Lyons, 2011). To identify key areas of scientific uncertainty regarding biologic resources of importance to the Glen Canyon Dam Adaptive Management Program, the Grand Canyon Monitoring and Research Center (GCMRC) convened Knowledge Assessment Workshops in May and July 2005. One of the products of these workshops was a set of strategic science questions that highlighted key areas of scientific uncertainty. These questions were intended to frame and guide the research and monitoring activities conducted by the GCMRC in subsequent years. Questions were developed collaboratively by scientists and managers. The questions were not all of equal importance or merit—some questions were large scale and others were small scale. Nevertheless, these questions were adopted and have guided the research and monitoring efforts conducted by the GCMRC since 2005. A new round of Knowledge Assessment Workshops was convened by the GCMRC in June and October 2011 and January 2012 to determine whether the research and monitoring activities conducted since 2005 had successfully answered some of the strategic science questions. Oral presentations by scientists highlighting research findings were a centerpiece of all three of the 2011–12 workshops. Each presenter was also asked to provide an answer to the strategic science questions that were specific to the presenter’s research area. One limitation of this approach is that these answers represented the views of the handful of scientists who developed the presentations, and, as such, they did not incorporate other perspectives. Thus, the answers provided by presenters at the Knowledge Assessment Workshops may not have accurately captured the sentiments of the broader group of scientists involved in research and monitoring of the Colorado River in Glen and Grand Canyons. Yet a fundamental ingredient of

  5. Statistics of Scientific Procedures on Living Animals 2013: Experimentation continues to rise--the reliance on genetically-altered animals must be addressed.

    PubMed

    Hudson-Shore, Michelle

    2014-09-01

    The 2013 Statistics of Scientific Procedures on Living Animals reveal that the level of animal experimentation in Great Britain continues to rise, with 4.12 million procedures being conducted. The figures indicate that this is almost exclusively a result of the breeding and use of genetically-altered (GA) animals (i.e. genetically-modified animals, plus those with harmful genetic defects). The breeding of GA animals increased to over half (51%) of all the procedures, and GA animals were involved in 61% of all the procedures. Indeed, if these animals were removed from the statistics, the number of procedures would actually have declined by 4%. It is argued that the Coalition Government has failed to address this issue, and, as a consequence, will not be able to deliver its pledge to reduce animal use in science. Recent publications supporting the need to reassess the dominance of genetic alteration are also discussed, as well as the need to move away from the use of dogs as the default second species in safety testing. The general trends in the species used, and the numbers and types of procedures, are also reviewed. Finally, forthcoming changes to the statistics are discussed.

  6. Uncertainty Assessment: What Good Does it Do? (Invited)

    NASA Astrophysics Data System (ADS)

    Oreskes, N.; Lewandowsky, S.

    2013-12-01

    The scientific community has devoted considerable time and energy to understanding, quantifying and articulating the uncertainties related to anthropogenic climate change. However, informed decision-making and good public policy arguably rely far more on a central core of understanding of matters that are scientifically well established than on detailed understanding and articulation of all relevant uncertainties. Advocates of vaccination, for example, stress its overall efficacy in preventing morbidity and mortality--not the uncertainties over how long the protective effects last. Advocates for colonoscopy for cancer screening stress its capacity to detect polyps before they become cancerous, with relatively little attention paid to the fact that many, if not most, polyps, would not become cancerous even if left unremoved. So why has the climate science community spent so much time focused on uncertainty? One reason, of course, is that articulation of uncertainty is a normal and appropriate part of scientific work. However, we argue that there is another reason that involves the pressure that the scientific community has experienced from individuals and groups promoting doubt about anthropogenic climate change. Specifically, doubt-mongering groups focus public attention on scientific uncertainty as a means to undermine scientific claims, equating uncertainty with untruth. Scientists inadvertently validate these arguments by agreeing that much of the science is uncertain, and thus seemingly implying that our knowledge is insecure. The problem goes further, as the scientific community attempts to articulate more clearly, and reduce, those uncertainties, thus, seemingly further agreeing that the knowledge base is insufficient to warrant public and governmental action. We refer to this effect as 'seepage,' as the effects of doubt-mongering seep into the scientific community and the scientific agenda, despite the fact that addressing these concerns does little to alter

  7. Livestock grazing and habitat for a threatened species: Land-use decisions under scientific uncertainty in the White Mountains, California, USA

    NASA Astrophysics Data System (ADS)

    Kondolf, G. Mathias

    1994-07-01

    The North Fork of Cottonwood Creek, in the White Mountains, Inyo National Forest, California, is a critically important refuge for the Paiute cutthroat trout ( Oncorhynchus clarki seleniris), a federally listed threatened species. Habitat for these fish appears to be limited by excessive levels of fine sediment in the channel, and livestock grazing of riparian meadows has been implicated in delivery of sediment to the channel. However, the relationships between land use and sediment yield have not been conclusively determined, in large part because there are no historically ungrazed sites to serve as long-term controls. Accordingly, land-use decisions must be made under scientific uncertainty. To reduce erosion and sedimentation in the stream, the Forest Service spent approximately US260,000 from 1981 to 1991 to repair watershed damage from livestock grazing, prevent livestock from traversing steep banks, and limit livestock access to the channel. Throughout this period, livestock grazing has continued on these lands, yielding less than 12,000 in grazing fees. In revising its Allotment Management Plan for the basin, the Forest Service rejected the “no-grazing” alternative because it was inconsistent with its Land and Resource Management Plan, which specifies there is to be no net reduction of grazing.

  8. Uncertainty and global climate change research

    SciTech Connect

    Tonn, B.E.; Weiher, R.

    1994-06-01

    The Workshop on Uncertainty and Global Climate Change Research March 22--23, 1994, in Knoxville, Tennessee. This report summarizes the results and recommendations of the workshop. The purpose of the workshop was to examine in-depth the concept of uncertainty. From an analytical point of view, uncertainty is a central feature of global climate science, economics and decision making. The magnitude and complexity of uncertainty surrounding global climate change has made it quite difficult to answer even the most simple and important of questions-whether potentially costly action is required now to ameliorate adverse consequences of global climate change or whether delay is warranted to gain better information to reduce uncertainties. A major conclusion of the workshop is that multidisciplinary integrated assessments using decision analytic techniques as a foundation is key to addressing global change policy concerns. First, uncertainty must be dealt with explicitly and rigorously since it is and will continue to be a key feature of analysis and recommendations on policy questions for years to come. Second, key policy questions and variables need to be explicitly identified, prioritized, and their uncertainty characterized to guide the entire scientific, modeling, and policy analysis process. Multidisciplinary integrated assessment techniques and value of information methodologies are best suited for this task. In terms of timeliness and relevance of developing and applying decision analytic techniques, the global change research and policy communities are moving rapidly toward integrated approaches to research design and policy analysis.

  9. Opening address

    NASA Astrophysics Data System (ADS)

    Castagnoli, C.

    1994-01-01

    Ladies and Gentlemen My cordial thanks to you for participating in our workshop and to all those who have sponsored it. When in 1957 I attended the International Congress on Fundamental Constants held in Turin on the occasion of the first centenary of the death of Amedeo Avogadro, I did not expect that about thirty-five years later a small but representative number of distinguished scientists would meet here again, to discuss how to go beyond the sixth decimal figure of the Avogadro constant. At that time, the uncertainty of the value of this constant was linked to the fourth decimal figure, as reported in the book by DuMond and Cohen. The progress made in the meantime is universally acknowledged to be due to the discovery of x-ray interferometry. We are honoured that one of the two founding fathers, Prof. Ulrich Bonse, is here with us, but we regret that the other, Prof. Michael Hart, is not present. After Bonse and Hart's discovery, the x-ray crystal density method triggered, as in a chain reaction, the investigation of two other quantities related to the Avogadro constant—density and molar mass. Scientists became, so to speak, resonant and since then have directed their efforts, just to mention a few examples, to producing near-perfect silicon spheres and determining their density, to calibrating, with increasing accuracy, mass spectrometers, and to studying the degree of homogeneity of silicon specimens. Obviously, I do not need to explain to you why the Avogadro constant is important. I wish, however, to underline that it is not only because of its position among fundamental constants, as we all know very well its direct links with the fine structure constant, the Boltzmann and Faraday constants, the h/e ratio, but also because when a new value of NA is obtained, the whole structure of the fundamental constants is shaken to a lesser or greater extent. Let me also remind you that the second part of the title of this workshop concerns the silicon

  10. Opening Address

    NASA Astrophysics Data System (ADS)

    Yamada, T.

    2014-12-01

    related fields such as nuclear astrophysics, hypernuclear physics, hadron physics, and condensate matter physics so on. In fact, in this workshop, we also discuss the clustering aspects in the related fields. Thus, I expect in this workshop we can grasp the present status of the nuclear cluster physics and demonstrate its perspective in near future. This workshop is sponsored by several institutes and organizations. In particular, I would express our thanks for financial supports to Research Center for Nuclear Physics (RCNP), Osaka University, Center for Nuclear Study (CNS), University of Tokyo, Joint Institute for Computational Fundamental Science (JICFuS), and RIKEN Nishina Center for Accelerator- Based Science. They are cohosting this workshop. I would like also to appreciate my University, Kanto Gakuin University, who offers this nice place for one week and helps us to hold this workshop smoothly and conveniently. Today, the president of my University, Prof. Kuku, is here to present a welcome address. Thank you very much. Finally, with many of the participants leading this field both in theory and in experiment, we wish this workshop offers an opportunity to simulate communications not only during the workshop but also in the future. In addition, we hope you enjoy exploring city of Yokohama and the area around, as well as scientific discussions. Thank you very much for your attention.

  11. Uncertainty and Surprise: An Introduction

    NASA Astrophysics Data System (ADS)

    McDaniel, Reuben R.; Driebe, Dean J.

    Much of the traditional scientific and applied scientific work in the social and natural sciences has been built on the supposition that the unknowability of situations is the result of a lack of information. This has led to an emphasis on uncertainty reduction through ever-increasing information seeking and processing, including better measurement and observational instrumentation. Pending uncertainty reduction through better information, efforts are devoted to uncertainty management and hierarchies of controls. A central goal has been the avoidance of surprise.

  12. Scientific Issues Addressed by the Kepler Mission

    NASA Technical Reports Server (NTRS)

    Bourcki, W. J.; Koch, D. G.; Lissauer, J. J.; Jenkins, J. M.; DeVincenzi, Donald L. (Technical Monitor)

    1998-01-01

    The Kepler Mission uses a wide field-of-view telescope to photometrically monitor 100,000 main-sequence stars for evidence of planetary transits. Because of the large number of stars monitored and because the mission is designed with a precision (0.002%) sufficient to readily recognize Earth-size planets transiting solar-like stars, several hundred Earth-size planets should be found. Based on the the Dopper velocity observations that find 2% of the main-sequence stars have Jupiter-size planets in short-period orbits, the Kepler mission is also expected to detect about 2000 giant planets. Several questions about the association of planet types and stellar characteristics can be investigated. For example; Are small planets found when Jupiter-mass planets are also present in inner orbits? What is the frequency of small planets compared to Jupiter-mass planets? What is the frequency and distribution of planets intermediate in size and mass to that of Earth and Jupiter? What correlations exist between planet size, distribution, and frequency with the characteristics of the stars they orbit? A comparison between model predictions and observation should be a useful step in evolving better models of planetary system formation and help put the formation of our Solar System in perspective.

  13. Climate change risk perception and communication: addressing a critical moment?

    PubMed

    Pidgeon, Nick

    2012-06-01

    Climate change is an increasingly salient issue for societies and policy-makers worldwide. It now raises fundamental interdisciplinary issues of risk and uncertainty analysis and communication. The growing scientific consensus over the anthropogenic causes of climate change appears to sit at odds with the increasing use of risk discourses in policy: for example, to aid in climate adaptation decision making. All of this points to a need for a fundamental revision of our conceptualization of what it is to do climate risk communication. This Special Collection comprises seven papers stimulated by a workshop on "Climate Risk Perceptions and Communication" held at Cumberland Lodge Windsor in 2010. Topics addressed include climate uncertainties, images and the media, communication and public engagement, uncertainty transfer in climate communication, the role of emotions, localization of hazard impacts, and longitudinal analyses of climate perceptions. Climate change risk perceptions and communication work is critical for future climate policy and decisions.

  14. Addressing healthcare.

    PubMed

    Daly, Rich

    2013-02-11

    Though President Barack Obama has rarely made healthcare references in his State of the Union addresses, health policy experts are hoping he changes that strategy this year. "The question is: Will he say anything? You would hope that he would, given that that was the major issue he started his presidency with," says Dr. James Weinstein, left, of the Dartmouth-Hitchcock health system.

  15. Uncertainty in Measured Data and Model Predictions: Essential Components for Mobilizing Environmental Data and Modeling

    NASA Astrophysics Data System (ADS)

    Harmel, D.

    2014-12-01

    In spite of pleas for uncertainty analysis - such as Beven's (2006) "Should it not be required that every paper in both field and modeling studies attempt to evaluate the uncertainty in the results?" - the uncertainty associated with hydrology and water quality data is rarely quantified and rarely considered in model evaluation. This oversight, justified in the past by mainly tenuous philosophical concerns, diminishes the value of measured data and ignores the environmental and socio-economic benefits of improved decisions and policies based on data with estimated uncertainty. This oversight extends to researchers, who typically fail to estimate uncertainty in measured discharge and water quality data because of additional effort required, lack of adequate scientific understanding on the subject, and fear of negative perception if data with "high" uncertainty are reported; however, the benefits are certain. Furthermore, researchers have a responsibility for scientific integrity in reporting what is known and what is unknown, including the quality of measured data. In response we produced an uncertainty estimation framework and the first cumulative uncertainty estimates for measured water quality data (Harmel et al., 2006). From that framework, DUET-H/WQ was developed (Harmel et al., 2009). Application to several real-world data sets indicated that substantial uncertainty can be contributed by each data collection procedural category and that uncertainties typically occur in order discharge < sediment < dissolved N and P < total N and P. Similarly, modelers address certain aspects of model uncertainty but ignore others, such as the impact of uncertainty in discharge and water quality data. Thus, we developed methods to incorporate prediction uncertainty as well as calibration/validation data uncertainty into model goodness-of-fit evaluation (Harmel and Smith, 2007; Harmel et al., 2010). These enhance model evaluation by: appropriately sharing burden with "data

  16. État des connaissances et incertitudes sur le changement climatique induit par les activités humainesScientific basis and uncertainties of human induced climate change

    NASA Astrophysics Data System (ADS)

    Duplessy, Jean-Claude

    2001-12-01

    During the 20th century, the mean temperature of the air at the ground level has increased by 0.6±0.2 °C and the warmest air temperatures occurred after 1980. These were significantly warmer than those of the last millennium. Simultaneously, rain and drought, cold and heat wave frequencies have changed, mountain glaciers retreated and the sea-level increased by ˜10 cm. This warming was at least in part induced by human activities and will continue during the next decades. Its amplitude will depend on the rate of greenhouse gas and sulphate aerosols emissions, i.e. on energetic scenarios. Pending scientific uncertainties include cloud variations and interactions between the physical parts of the climate system and the biogeochemical cycles and the biosphere.

  17. Linear Programming Problems for Generalized Uncertainty

    ERIC Educational Resources Information Center

    Thipwiwatpotjana, Phantipa

    2010-01-01

    Uncertainty occurs when there is more than one realization that can represent an information. This dissertation concerns merely discrete realizations of an uncertainty. Different interpretations of an uncertainty and their relationships are addressed when the uncertainty is not a probability of each realization. A well known model that can handle…

  18. Are models, uncertainty, and dispute resolution compatible?

    NASA Astrophysics Data System (ADS)

    Anderson, J. D.; Wilson, J. L.

    2013-12-01

    Models and their uncertainty often move from an objective use in planning and decision making into the regulatory environment, then sometimes on to dispute resolution through litigation or other legal forums. Through this last transition whatever objectivity the models and uncertainty assessment may have once possessed becomes biased (or more biased) as each party chooses to exaggerate either the goodness of a model, or its worthlessness, depending on which view is in its best interest. If worthlessness is desired, then what was uncertain becomes unknown, or even unknowable. If goodness is desired, then precision and accuracy are often exaggerated and uncertainty, if it is explicitly recognized, encompasses only some parameters or conceptual issues, ignores others, and may minimize the uncertainty that it accounts for. In dispute resolution, how well is the adversarial process able to deal with these biases? The challenge is that they are often cloaked in computer graphics and animations that appear to lend realism to what could be mostly fancy, or even a manufactured outcome. While junk science can be challenged through appropriate motions in federal court, and in most state courts, it not unusual for biased or even incorrect modeling results, or conclusions based on incorrect results, to be permitted to be presented at trial. Courts allow opinions that are based on a "reasonable degree of scientific certainty," but when that 'certainty' is grossly exaggerated by an expert, one way or the other, how well do the courts determine that someone has stepped over the line? Trials are based on the adversary system of justice, so opposing and often irreconcilable views are commonly allowed, leaving it to the judge or jury to sort out the truth. Can advances in scientific theory and engineering practice, related to both modeling and uncertainty, help address this situation and better ensure that juries and judges see more objective modeling results, or at least see

  19. Inaugural address

    NASA Astrophysics Data System (ADS)

    Joshi, P. S.

    2014-03-01

    From jets to cosmos to cosmic censorship P S Joshi Tata Institute of Fundamental Research, Homi Bhabha Road, Colaba, Mumbai 400005, India E-mail: psj@tifr.res.in 1. Introduction At the outset, I should like to acknowledge that part of the title above, which tries to capture the main flavour of this meeting, and has been borrowed from one of the plenary talks at the conference. When we set out to make the programme for the conference, we thought of beginning with observations on the Universe, but then we certainly wanted to go further and address deeper questions, which were at the very foundations of our inquiry, and understanding on the nature and structure of the Universe. I believe, we succeeded to a good extent, and it is all here for you in the form of these Conference Proceedings, which have been aptly titled as 'Vishwa Mimansa', which could be possibly translated as 'Analysis of the Universe'! It is my great pleasure and privilege to welcome you all to the ICGC-2011 meeting at Goa. The International Conference on Gravitation and Cosmology (ICGC) series of meetings are being organized by the Indian Association for General Relativity and Gravitation (IAGRG), and the first such meeting was planned and conducted in Goa in 1987, with subsequent meetings taking place at a duration of about four years at various locations in India. So, it was thought appropriate to return to Goa to celebrate the 25 years of the ICGC meetings. The recollections from that first meeting have been recorded elsewhere here in these Proceedings. The research and teaching on gravitation and cosmology was initiated quite early in India, by V V Narlikar at the Banares Hindu University, and by N R Sen in Kolkata in the 1930s. In course of time, this activity grew and gained momentum, and in early 1969, at the felicitation held for the 60 years of V V Narlikar at a conference in Ahmedabad, P C Vaidya proposed the formation of the IAGRG society, with V V Narlikar being the first President. This

  20. Convocation address.

    PubMed

    Kakodkar, A

    1999-07-01

    This convocation addressed by Dr. Anil Kakodkar focuses on the challenges faced by graduating students. In his speech, he emphasized the high level of excellence achieved by the industrial sector; however, he noted that there has been a loss of initiative in maximizing value addition, which was worsened by an increasing population pressure. In facing a stiff competition in the external and domestic markets, it is imperative to maximize value addition within the country in a competitive manner and capture the highest possible market share. To achieve this, high-quality human resources are central. Likewise, family planning programs should become more effective and direct available resources toward national advantage. To boost the domestic market, he suggests the need to search for strengths to achieve leadership position in those areas. First, an insight into the relationship between the lifestyles and the needs of our people and the natural resource endowment must be gained. Second, remodeling of the education system must be undertaken to prepare the people for adding the necessary innovative content in our value addition activities. Lastly, Dr. Kakodkar emphasizes the significance of developing a strong bond between parents and children to provide a sound foundation and allow the education system to grow upon it.

  1. Measurement Uncertainty

    NASA Astrophysics Data System (ADS)

    Koch, Michael

    Measurement uncertainty is one of the key issues in quality assurance. It became increasingly important for analytical chemistry laboratories with the accreditation to ISO/IEC 17025. The uncertainty of a measurement is the most important criterion for the decision whether a measurement result is fit for purpose. It also delivers help for the decision whether a specification limit is exceeded or not. Estimation of measurement uncertainty often is not trivial. Several strategies have been developed for this purpose that will shortly be described in this chapter. In addition the different possibilities to take into account the uncertainty in compliance assessment are explained.

  2. Assessing Uncertainty in Subsurface Transport Predictions Using the ASCEM Toolset

    NASA Astrophysics Data System (ADS)

    Freedman, V.; Chen, X.; Keating, E. H.; Higdon, D. M.; Rockhold, M. L.; Schuchardt, K. L.; Finsterle, S.; Gorton, I.; Freshley, M.

    2011-12-01

    Transport simulation of nonreactive solutes can be used to identify potential pathways of contaminants in the vadose zone and the effectiveness of site remediation technologies. At the BC Cribs site at Hanford in southeastern Washington State, innovative remedial technologies are being explored to address recalcitrant contamination in the deep (~100 m) vadose zone. To identify the effectiveness of the technologies, the impacts of a "no-action" alternative must also be explored. Because only sparse information is available for the geologic conceptual model and the physical and chemical properties of the sediments, there is considerable uncertainty in subsurface transport predictions. In this contribution, the uncertainty of the technetium-99 mass flux to the water table due to parameter uncertainty and variations in the conceptual model are investigated using a newly developed toolset for performing an uncertainty quantification (UQ) analysis. This toolset is part of ASCEM (Advanced Simulation Capability for Environmental Management), a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. Using the Akuna user environment currently under development, the uncertainty in technetium-99 transport through a two-dimensional, heterogeneous vadose-zone system is quantified with Monte Carlo simulation. Results show that uncertainty in simulated mass fluxes in hydraulic properties can be significant within a single conceptual model, and that significant additional uncertainty can be introduced by conceptual model variation.

  3. Presidential address.

    PubMed

    Vohra, U

    1993-07-01

    The Secretary of India's Ministry of Health and Family Welfare serves as Chair of the Executive Council of the International Institute for Population Sciences in Bombay. She addressed its 35th convocation in 1993. Global population stands at 5.43 billion and increases by about 90 million people each year. 84 million of these new people are born in developing countries. India contributes 17 million new people annually. The annual population growth rate in India is about 2%. Its population size will probably surpass 1 billion by the 2000. High population growth rates are a leading obstacle to socioeconomic development in developing countries. Governments of many developing countries recognize this problem and have expanded their family planning programs to stabilize population growth. Asian countries that have done so and have completed the fertility transition include China, Japan, Singapore, South Korea, and Thailand. Burma, Malaysia, North Korea, Sri Lanka, and Vietnam have not yet completed the transition. Afghanistan, Bangladesh, Iran, Nepal, and Pakistan are half-way through the transition. High population growth rates put pressure on land by fragmenting finite land resources, increasing the number of landless laborers and unemployment, and by causing considerable rural-urban migration. All these factors bring about social stress and burden civic services. India has reduced its total fertility rate from 5.2 to 3.9 between 1971 and 1991. Some Indian states have already achieved replacement fertility. Considerable disparity in socioeconomic development exists among states and districts. For example, the states of Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh have female literacy rates lower than 27%, while that for Kerala is 87%. Overall, infant mortality has fallen from 110 to 80 between 1981 and 1990. In Uttar Pradesh, it has fallen from 150 to 98, while it is at 17 in Kerala. India needs innovative approaches to increase contraceptive prevalence rates

  4. Opening Address

    NASA Astrophysics Data System (ADS)

    Crovini, L.

    1994-01-01

    Ladies and Gentlemen To quote Mr Jean Terrien: "Physics must be one step ahead of metrology". A long-serving Director of the BIPM, he said these words when visiting the IMGC in 1970 as a member of the scientific board of our Institute. At that time it was still an open question whether the IMGC should start research work on the absolute measurement of silicon lattice spacing. Mr Terrien underlined the revolutionary character of x-ray interferometry and, eventually, he caused the balance needle to lean towards the ... right direction. Mr Terrien correctly foresaw that, like Michelson's interferometer of 1880, x-ray interferometry could have a prominent place in today's science and technology. And while, in the first case, after more than a century we can see instruments based on electromagnetic wave interaction within every one's reach in laboratories and, sometimes, in workshops, in the second case, twenty-five years since the first development of an x-ray interferometer we can witness its role in nanometrology. Today and tomorrow we meet to discuss how to go beyond the sixth decimal place in the value of the Avogadro constant. We are aware that the quest for this achievement requires the cooperation of scientists with complementary capabilities. I am sure that the present workshop is a very good opportunity to present and discuss results and to improve and extend existing cooperation. The new adjustment of fundamental constants envisaged by the CODATA Task Group is redoubling scientists' efforts to produce competitive values of NA. The results of the measurements of the silicon lattice spacing in terms of an optical wavelength, which were available for the 1986 adjustment, combined with the determination of silicon molar volume, demonstrate how such an NA determination produces a consistent set of other constants and opens the way to a possible redefinition of the kilogram. We shall see in these two days how far we have progressed along this road. For us at the

  5. Welcome Address

    NASA Astrophysics Data System (ADS)

    Kiku, H.

    2014-12-01

    Ladies and Gentlemen, It is an honor for me to present my welcome address in the 3rd International Workshop on "State of the Art in Nuclear Cluster Physics"(SOTANCP3), as the president of Kanto Gakuin University. Particularly to those from abroad more than 17 countries, I am very grateful for your participation after long long trips from your home to Yokohama. On the behalf of the Kanto Gakuin University, we certainly welcome your visit to our university and stay in Yokohama. First I would like to introduce Kanto Gakuin University briefly. Kanto Gakuin University, which is called KGU, traces its roots back to the Yokohama Baptist Seminary founded in 1884 in Yamate, Yokohama. The seminary's founder was Albert Arnold Bennett, alumnus of Brown University, who came to Japan from the United States to establish a theological seminary for cultivating and training Japanese missionaries. Now KGU is a major member of the Kanto Gakuin School Corporation, which is composed of two kindergartens, two primary schools, two junior high schools, two senior high schools as well as KGU. In this university, we have eight faculties with graduate school including Humanities, Economics, Law, Sciences and Engineering, Architecture and Environmental Design, Human and Environmental Studies, Nursing, and Law School. Over eleven thousands students are currently learning in our university. By the way, my major is the geotechnical engineering, and I belong to the faculty of Sciences and Engineering in my university. Prof. T. Yamada, here, is my colleague in the same faculty. I know that the nuclear physics is one of the most active academic fields in the world. In fact, about half of the participants, namely, more than 50 scientists, come from abroad in this conference. Moreover, I know that the nuclear physics is related to not only the other fundamental physics such as the elementary particle physics and astrophysics but also chemistry, medical sciences, medical cares, and radiation metrology

  6. Uncertainty and equipoise: at interplay between epistemology, decision making and ethics.

    PubMed

    Djulbegovic, Benjamin

    2011-10-01

    In recent years, various authors have proposed that the concept of equipoise be abandoned because it conflates the practice of clinical care with clinical research. At the same time, the equipoise opponents acknowledge the necessity of clinical research if there are unresolved uncertainties about the effects of proposed healthcare interventions. As equipoise represents just 1 measure of uncertainty, proposals to abandon equipoise while maintaining a requirement for addressing uncertainties are contradictory and ultimately not valid. As acknowledgment and articulation of uncertainties represent key scientific and moral requirements for human experimentation, the concept of equipoise remains the most useful framework to link the theory of human experimentation with the theory of rational choice. In this article, I show how uncertainty (equipoise) is at the intersection between epistemology, decision making and ethics of clinical research. In particular, I show how our formulation of responses to uncertainties of hoped-for benefits and unknown harms of testing is a function of the way humans cognitively process information. This approach is based on the view that considerations of ethics and rationality cannot be separated. I analyze the response to uncertainties as it relates to the dual-processing theory, which postulates that rational approach to (clinical research) decision making depends both on analytical, deliberative processes embodied in scientific method (system II), and good human intuition (system I). Ultimately, our choices can only become wiser if we understand a close and intertwined relationship between irreducible uncertainty, inevitable errors and unavoidable injustice.

  7. History Forum Addresses Creation/Evolution Controversy.

    ERIC Educational Resources Information Center

    Schweinsberg, John

    1997-01-01

    A series of programs entitled Creationism and Evolution: The History of a Controversy was presented at the University of Alabama in Huntsville. The controversy was addressed from an historical and sociological, rather than a scientific perspective. Speakers addressed the evolution of scientific creationism, ancient texts versus sedimentary rocks…

  8. Uncertainty in environmental risk assessment: implications for risk-based management of river basins.

    PubMed

    Ragas, Ad M J; Huijbregts, Mark A J; Henning-de Jong, Irmgard; Leuven, Rob S E W

    2009-01-01

    Environmental risk assessment is typically uncertain due to different perceptions of the risk problem and limited knowledge about the physical, chemical, and biological processes underlying the risk. The present paper provides a systematic overview of the implications of different types of uncertainty for risk management, with a focus on risk-based management of river basins. Three different types of uncertainty are distinguished: 1) problem definition uncertainty, 2) true uncertainty, and 3) variability. Methods to quantify and describe these types of uncertainty are discussed and illustrated in 4 case studies. The case studies demonstrate that explicit regulation of uncertainty can improve risk management (e.g., by identification of the most effective risk reduction measures, optimization of the use of resources, and improvement of the decision-making process). It is concluded that the involvement of nongovernmental actors as prescribed by the European Union Water Framework Directive (WFD) provides challenging opportunities to address problem definition uncertainty and those forms of true uncertainty that are difficult to quantify. However, the WFD guidelines for derivation and application of environmental quality standards could be improved by the introduction of a probabilistic approach to deal with true uncertainty and a better scientific basis for regulation of variability.

  9. Teaching Uncertainties

    ERIC Educational Resources Information Center

    Duerdoth, Ian

    2009-01-01

    The subject of uncertainties (sometimes called errors) is traditionally taught (to first-year science undergraduates) towards the end of a course on statistics that defines probability as the limit of many trials, and discusses probability distribution functions and the Gaussian distribution. We show how to introduce students to the concepts of…

  10. Measuring, Estimating, and Deciding under Uncertainty.

    PubMed

    Michel, Rolf

    2016-03-01

    The problem of uncertainty as a general consequence of incomplete information and the approach to quantify uncertainty in metrology is addressed. Then, this paper discusses some of the controversial aspects of the statistical foundation of the concepts of uncertainty in measurements. The basics of the ISO Guide to the Expression of Uncertainty in Measurement as well as of characteristic limits according to ISO 11929 are described and the needs for a revision of the latter standard are explained.

  11. Uncertainty quantification in molecular dynamics

    NASA Astrophysics Data System (ADS)

    Rizzi, Francesco

    This dissertation focuses on uncertainty quantification (UQ) in molecular dynamics (MD) simulations. The application of UQ to molecular dynamics is motivated by the broad uncertainty characterizing MD potential functions and by the complexity of the MD setting, where even small uncertainties can be amplified to yield large uncertainties in the model predictions. Two fundamental, distinct sources of uncertainty are investigated in this work, namely parametric uncertainty and intrinsic noise. Intrinsic noise is inherently present in the MD setting, due to fluctuations originating from thermal effects. Averaging methods can be exploited to reduce the fluctuations, but due to finite sampling, this effect cannot be completely filtered, thus yielding a residual uncertainty in the MD predictions. Parametric uncertainty, on the contrary, is introduced in the form of uncertain potential parameters, geometry, and/or boundary conditions. We address the UQ problem in both its main components, namely the forward propagation, which aims at characterizing how uncertainty in model parameters affects selected observables, and the inverse problem, which involves the estimation of target model parameters based on a set of observations. The dissertation highlights the challenges arising when parametric uncertainty and intrinsic noise combine to yield non-deterministic, noisy MD predictions of target macroscale observables. Two key probabilistic UQ methods, namely Polynomial Chaos (PC) expansions and Bayesian inference, are exploited to develop a framework that enables one to isolate the impact of parametric uncertainty on the MD predictions and, at the same time, properly quantify the effect of the intrinsic noise. Systematic applications to a suite of problems of increasing complexity lead to the observation that an uncertain PC representation built via Bayesian regression is the most suitable model for the representation of uncertain MD predictions of target observables in the

  12. 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

  13. Uncertainty analysis

    SciTech Connect

    Thomas, R.E.

    1982-03-01

    An evaluation is made of the suitability of analytical and statistical sampling methods for making uncertainty analyses. The adjoint method is found to be well-suited for obtaining sensitivity coefficients for computer programs involving large numbers of equations and input parameters. For this purpose the Latin Hypercube Sampling method is found to be inferior to conventional experimental designs. The Latin hypercube method can be used to estimate output probability density functions, but requires supplementary rank transformations followed by stepwise regression to obtain uncertainty information on individual input parameters. A simple Cork and Bottle problem is used to illustrate the efficiency of the adjoint method relative to certain statistical sampling methods. For linear models of the form Ax=b it is shown that a complete adjoint sensitivity analysis can be made without formulating and solving the adjoint problem. This can be done either by using a special type of statistical sampling or by reformulating the primal problem and using suitable linear programming software.

  14. Uncertainty as Impetus for Climate Mitigation

    NASA Astrophysics Data System (ADS)

    Lewandowsky, S.; Oreskes, N.; Risbey, J.

    2015-12-01

    For decades, the scientific community has called for actions to be taken to mitigate the adverse consequences of climate change. To date, those calls have found little substantial traction, and politicians and the general public are instead engaged in a debate about the causes and effects of climate change that bears little resemblance to the state of scientific knowledge. Uncertainty plays a pivotal role in that public debate, and arguments against mitigation are frequently couched in terms of uncertainty. We show that the rhetorical uses of scientific uncertainty in public debate by some actors (often with vested interests or political agendas) contrast with the mathematical result that greater uncertainty about the extent of warming is virtually always associated with an increased risk: The expected damage costs increase as a function of uncertainty about future warming. We suggest ways in which the actual implications of scientific uncertainty can be better communicated and how scientific uncertainty should be understood as an impetus, rather than a barrier, for climate mitigation.

  15. Uncertainty quantification in reacting flow modeling.

    SciTech Connect

    Le MaÒitre, Olivier P.; Reagan, Matthew T.; Knio, Omar M.; Ghanem, Roger Georges; Najm, Habib N.

    2003-10-01

    Uncertainty quantification (UQ) in the computational modeling of physical systems is important for scientific investigation, engineering design, and model validation. In this work we develop techniques for UQ based on spectral and pseudo-spectral polynomial chaos (PC) expansions, and we apply these constructions in computations of reacting flow. We develop and compare both intrusive and non-intrusive spectral PC techniques. In the intrusive construction, the deterministic model equations are reformulated using Galerkin projection into a set of equations for the time evolution of the field variable PC expansion mode strengths. The mode strengths relate specific parametric uncertainties to their effects on model outputs. The non-intrusive construction uses sampling of many realizations of the original deterministic model, and projects the resulting statistics onto the PC modes, arriving at the PC expansions of the model outputs. We investigate and discuss the strengths and weaknesses of each approach, and identify their utility under different conditions. We also outline areas where ongoing and future research are needed to address challenges with both approaches.

  16. The ends of uncertainty: Air quality science and planning in Central California

    SciTech Connect

    Fine, James

    2003-09-01

    Air quality planning in Central California is complicated and controversial despite millions of dollars invested to improve scientific understanding. This research describes and critiques the use of photochemical air quality simulation modeling studies in planning to attain standards for ground-level ozone in the San Francisco Bay Area and the San Joaquin Valley during the 1990's. Data are gathered through documents and interviews with planners, modelers, and policy-makers at public agencies and with representatives from the regulated and environmental communities. Interactions amongst organizations are diagramed to identify significant nodes of interaction. Dominant policy coalitions are described through narratives distinguished by their uses of and responses to uncertainty, their exposures to risks, and their responses to the principles of conservatism, civil duty, and caution. Policy narratives are delineated using aggregated respondent statements to describe and understand advocacy coalitions. I found that models impacted the planning process significantly, but were used not purely for their scientific capabilities. Modeling results provided justification for decisions based on other constraints and political considerations. Uncertainties were utilized opportunistically by stakeholders instead of managed explicitly. Ultimately, the process supported the partisan views of those in control of the modeling. Based on these findings, as well as a review of model uncertainty analysis capabilities, I recommend modifying the planning process to allow for the development and incorporation of uncertainty information, while addressing the need for inclusive and meaningful public participation. By documenting an actual air quality planning process these findings provide insights about the potential for using new scientific information and understanding to achieve environmental goals, most notably the analysis of uncertainties in modeling applications. Concurrently, needed

  17. Information Theory and the Analysis of Uncertainties in a Spatial Geological Context

    NASA Astrophysics Data System (ADS)

    Wellmann, Florian; Jessell, Mark

    2014-05-01

    The interpretation of uncertainties in a spatial context is of fundamental importance for the generation of structural geological models; this applies to models for mineral exploration, to scientific structural geological studies and fundamental geological evaluations. With our work, we are addressing uncertainties in this spatial geological context. Encouraged by the interdisciplinary and interactive aspect of the session, we would like to present our method to other branches of geosciences. Structural geological models, here understood as structural representations of the dominant geological units in the subsurface, always contain uncertainties. The analysis of these uncertainties is intricate as these models are usually constructed on the basis of greatly varying data quality and spatial distribution. An additional complication is that, in most cases, the general distribution of uncertainties in space is of interest, and not a single outcome as, for example, the flow at a well. In the context of structural geological uncertainties, we therefore face two problems: (i) how can we estimate uncertainties in a complex 3-D geological model, and (ii) what is a meaningful measure to visualise and analyse these uncertainties quantitatively? In recent years, several approaches have been developed to solve the first problem. We show here an approach based on implicit stochastic geological modelling techniques, capable of handling complex geological settings. To address the second problem, we apply measures from information theory. We consider each subspace in a discretised model domain as a random variable. Based on the probability functions estimated from a suite of generated models, we evaluate the information entropy at each location in the subsurface as a measure of uncertainty. We subsequently estimate multivariate conditional entropy and mutual information between a set of locations and other regions in space, to determine spatial uncertainty correlations, and the

  18. Is Current Hydrogeologic Research Addressing Long-TermPredictions?

    SciTech Connect

    Tsang, Chin-Fu

    2004-09-10

    Hydrogeology is a field closely related to the needs of society. Many problems of current national and local interest require predictions of hydrogeological system behavior, and, in a number of important cases, the period of prediction is tens to hundreds of thousands of years. It is argued that the demand for such long-term hydrogeological predictions casts a new light on the future needs of hydrogeological research. Key scientific issues are no longer concerned only with simple processes or narrowly focused modeling or testing methods, but also with assessment of prediction uncertainties and confidence, couplings among multiple physico-chemical processes occurring simultaneously at a site, and the interplay between site characterization and predictive modeling. These considerations also have significant implications for hydrogeological education. With this view, it is asserted that hydrogeological directions and education need to be reexamined and possibly refocused to address specific needs for long-term predictions.

  19. Uncertainty Can Increase Explanatory Credibility

    DTIC Science & Technology

    2013-08-01

    metacognitive cue to infer their conversational partner’s depth of processing . Keywords: explanations, confidence, uncertainty, collaborative reasoning...scope, i.e., those that account for only observed phenomena (Khemlani, Sussman, & Oppenheimer , 2011). These preferences show that properties intrinsic...Fischhoff, & Phillips , 1982; Lindley, 1982; McClelland & Bolger, 1994). Much of the research on subjective confidence addresses how individuals

  20. Capturing the uncertainty in adversary attack simulations.

    SciTech Connect

    Darby, John L.; Brooks, Traci N.; Berry, Robert Bruce

    2008-09-01

    This work provides a comprehensive uncertainty technique to evaluate uncertainty, resulting in a more realistic evaluation of PI, thereby requiring fewer resources to address scenarios and allowing resources to be used across more scenarios. For a given set of dversary resources, two types of uncertainty are associated with PI for a scenario: (1) aleatory (random) uncertainty for detection probabilities and time delays and (2) epistemic (state of knowledge) uncertainty for the adversary resources applied during an attack. Adversary esources consist of attributes (such as equipment and training) and knowledge about the security system; to date, most evaluations have assumed an adversary with very high resources, adding to the conservatism in the evaluation of PI. The aleatory uncertainty in PI is ddressed by assigning probability distributions to detection probabilities and time delays. A numerical sampling technique is used to evaluate PI, addressing the repeated variable dependence in the equation for PI.

  1. Clarifying types of uncertainty: when are models accurate, and uncertainties small?

    PubMed

    Cox, Louis Anthony Tony

    2011-10-01

    Professor Aven has recently noted the importance of clarifying the meaning of terms such as "scientific uncertainty" for use in risk management and policy decisions, such as when to trigger application of the precautionary principle. This comment examines some fundamental conceptual challenges for efforts to define "accurate" models and "small" input uncertainties by showing that increasing uncertainty in model inputs may reduce uncertainty in model outputs; that even correct models with "small" input uncertainties need not yield accurate or useful predictions for quantities of interest in risk management (such as the duration of an epidemic); and that accurate predictive models need not be accurate causal models.

  2. Overcoming the Uncertainty Barrier to Adaptation

    EPA Pesticide Factsheets

    The second in a three-part webinar series about climate change adaptation for state and local governments, this webinar addressed the challenge of planning for climate change in the face of uncertainty.

  3. Intolerance of uncertainty in emotional disorders: What uncertainties remain?

    PubMed

    Shihata, Sarah; McEvoy, Peter M; Mullan, Barbara Ann; Carleton, R Nicholas

    2016-06-01

    The current paper presents a future research agenda for intolerance of uncertainty (IU), which is a transdiagnostic risk and maintaining factor for emotional disorders. In light of the accumulating interest and promising research on IU, it is timely to emphasize the theoretical and therapeutic significance of IU, as well as to highlight what remains unknown about IU across areas such as development, assessment, behavior, threat and risk, and relationships to cognitive vulnerability factors and emotional disorders. The present paper was designed to provide a synthesis of what is known and unknown about IU, and, in doing so, proposes broad and novel directions for future research to address the remaining uncertainties in the literature.

  4. Meeting Materials for the December 4-6, 2013 Scientific Advisory Panel

    EPA Pesticide Factsheets

    Meeting Materials for the December 4-6, 2013 Scientific Advisory Panel on Scientific Uncertainties Associated with Corn Rootworm Resistance Monitoring for Bt Corn Plant Incorporated Protectants (PIPs)

  5. The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems

    NASA Astrophysics Data System (ADS)

    Rossa, Andrea; Liechti, Katharina; Zappa, Massimiliano; Bruen, Michael; Germann, Urs; Haase, Günther; Keil, Christian; Krahe, Peter

    2011-05-01

    Quantifying uncertainty in flood forecasting is a difficult task, given the multiple and strongly non-linear model components involved in such a system. Much effort has been and is being invested in the quest of dealing with uncertain precipitation observations and forecasts and the propagation of such uncertainties through hydrological and hydraulic models predicting river discharges and risk for inundation. The COST 731 Action is one of these and constitutes a European initiative which deals with the quantification of forecast uncertainty in hydro-meteorological forecast systems. COST 731 addresses three major lines of development: (1) combining meteorological and hydrological models to form a forecast chain, (2) propagating uncertainty information through this chain and make it available to end users in a suitable form, (3) advancing high-resolution numerical weather prediction precipitation forecasts by using non-conventional observations from, for instance, radar to determine details in the initial conditions on scales smaller than what can be resolved by conventional observing systems. Recognizing the interdisciplinarity of the challenge COST 731 has organized its work forming Working Groups at the interfaces between the different scientific disciplines involved, i.e. between observation and atmospheric (and hydrological) modelling (WG-1), between atmospheric and hydrologic modelling (WG-2) and between hydrologic modelling and end-users (WG-3). This paper summarizes the COST 731 activities and its context, provides a review of the recent progress made in dealing with uncertainties in flood forecasting, and sets the scene for the papers of this Thematic Issue. In particular, a bibliometric analysis highlights the strong recent increase in addressing the uncertainty analysis in flood forecasting from an integrated perspective. Such a perspective necessarily involves the area of meteorology, hydrology, and decision making in order to take operational advantage

  6. Characterizing Uncertainty for Regional Climate Change Mitigation and Adaptation Decisions

    SciTech Connect

    Unwin, Stephen D.; Moss, Richard H.; Rice, Jennie S.; Scott, Michael J.

    2011-09-30

    This white paper describes the results of new research to develop an uncertainty characterization process to help address the challenges of regional climate change mitigation and adaptation decisions.

  7. Wildfire Decision Making Under Uncertainty

    NASA Astrophysics Data System (ADS)

    Thompson, M.

    2013-12-01

    Decisions relating to wildfire management are subject to multiple sources of uncertainty, and are made by a broad range of individuals, across a multitude of environmental and socioeconomic contexts. In this presentation I will review progress towards identification and characterization of uncertainties and how this information can support wildfire decision-making. First, I will review a typology of uncertainties common to wildfire management, highlighting some of the more salient sources of uncertainty and how they present challenges to assessing wildfire risk. This discussion will cover the expanding role of burn probability modeling, approaches for characterizing fire effects, and the role of multi-criteria decision analysis, and will provide illustrative examples of integrated wildfire risk assessment across a variety of planning scales. Second, I will describe a related uncertainty typology that focuses on the human dimensions of wildfire management, specifically addressing how social, psychological, and institutional factors may impair cost-effective risk mitigation. This discussion will encompass decision processes before, during, and after fire events, with a specific focus on active management of complex wildfire incidents. An improved ability to characterize uncertainties faced in wildfire management could lead to improved delivery of decision support, targeted communication strategies, and ultimately to improved wildfire management outcomes.

  8. Scientific Misconduct.

    PubMed

    Gross, Charles

    2016-01-01

    Scientific misconduct has been defined as fabrication, falsification, and plagiarism. Scientific misconduct has occurred throughout the history of science. The US government began to take systematic interest in such misconduct in the 1980s. Since then, a number of studies have examined how frequently individual scientists have observed scientific misconduct or were involved in it. Although the studies vary considerably in their methodology and in the nature and size of their samples, in most studies at least 10% of the scientists sampled reported having observed scientific misconduct. In addition to studies of the incidence of scientific misconduct, this review considers the recent increase in paper retractions, the role of social media in scientific ethics, several instructional examples of egregious scientific misconduct, and potential methods to reduce research misconduct.

  9. A Probabilistic Approach for Analysis of Modeling Uncertainties in Quantification of Trading Ratios in Nonpoint to Point Source Nutrient Trading Programs

    NASA Astrophysics Data System (ADS)

    Tasdighi, A.; Arabi, M.

    2015-12-01

    Quantifying the nonpoint source pollutant loads and assessing the water quality benefits of conservation practices (BMPs) are prone to different types of uncertainties which have to be taken into account when developing nutrient trading programs. Although various types of modeling uncertainties (parameter, input and structure) have been examined in the literature more or less, the impact of modeling uncertainties on evaluation of BMPs has not been addressed sufficiently. Currently, "trading ratios" are used within nutrient trading programs to account for variability of nonpoint source loads. However, we were not able to find any case of some rigorous scientific approach to account for any type of uncertainties in trading ratios. In this study, Bayesian inferences were applied to incorporate input, parameter and structural uncertainties using a statistically valid likelihood function. IPEAT (Integrated Parameter Estimation and Uncertainty Analysis Tool), a framework developed for simultaneous evaluation of parameterization, input data, model structure, and observation data uncertainty and their contribution to predictive uncertainty was used to quantify the uncertainties in effectiveness of agricultural BMPs while propagating different sources of uncertainty. SWAT was used as the simulation model. SWAT parameterization was done for three different model structures (SCS CN I, SCS CN II and G&A methods) using a Bayesian based Markov Chain Monte Carlo (MCMC) method named Differential Evolution Adaptive Metropolis (DREAM). For each model structure, the Integrated Bayesian Uncertainty Estimator (IBUNE) was employed to generate latent variables from input data. Bayesian Model Averaging (BMA) was then used to combine the models and Expectation-Maximization (EM) optimization technique was used to estimate the BMA weights. Using this framework, the impact of different sources of uncertainty on nutrient loads from nonpoint sources and subsequently effectiveness of BMPs in

  10. Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling.

    PubMed

    Cressie, Noel; Calder, Catherine A; Clark, James S; Ver Hoef, Jay M; Wikle, Christopher K

    2009-04-01

    Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

  11. Estimating uncertainties in complex joint inverse problems

    NASA Astrophysics Data System (ADS)

    Afonso, Juan Carlos

    2016-04-01

    Sources of uncertainty affecting geophysical inversions can be classified either as reflective (i.e. the practitioner is aware of her/his ignorance) or non-reflective (i.e. the practitioner does not know that she/he does not know!). Although we should be always conscious of the latter, the former are the ones that, in principle, can be estimated either empirically (by making measurements or collecting data) or subjectively (based on the experience of the researchers). For complex parameter estimation problems in geophysics, subjective estimation of uncertainty is the most common type. In this context, probabilistic (aka Bayesian) methods are commonly claimed to offer a natural and realistic platform from which to estimate model uncertainties. This is because in the Bayesian approach, errors (whatever their nature) can be naturally included as part of the global statistical model, the solution of which represents the actual solution to the inverse problem. However, although we agree that probabilistic inversion methods are the most powerful tool for uncertainty estimation, the common claim that they produce "realistic" or "representative" uncertainties is not always justified. Typically, ALL UNCERTAINTY ESTIMATES ARE MODEL DEPENDENT, and therefore, besides a thorough characterization of experimental uncertainties, particular care must be paid to the uncertainty arising from model errors and input uncertainties. We recall here two quotes by G. Box and M. Gunzburger, respectively, of special significance for inversion practitioners and for this session: "…all models are wrong, but some are useful" and "computational results are believed by no one, except the person who wrote the code". In this presentation I will discuss and present examples of some problems associated with the estimation and quantification of uncertainties in complex multi-observable probabilistic inversions, and how to address them. Although the emphasis will be on sources of uncertainty related

  12. Picturing Data With Uncertainty

    NASA Technical Reports Server (NTRS)

    Kao, David; Love, Alison; Dungan, Jennifer L.; Pang, Alex

    2004-01-01

    NASA is in the business of creating maps for scientific purposes to represent important biophysical or geophysical quantities over space and time. For example, maps of surface temperature over the globe tell scientists where and when the Earth is heating up; regional maps of the greenness of vegetation tell scientists where and when plants are photosynthesizing. There is always uncertainty associated with each value in any such map due to various factors. When uncertainty is fully modeled, instead of a single value at each map location, there is a distribution expressing a set of possible outcomes at each location. We consider such distribution data as multi-valued data since it consists of a collection of values about a single variable. Thus, a multi-valued data represents both the map and its uncertainty. We have been working on ways to visualize spatial multi-valued data sets effectively for fields with regularly spaced units or grid cells such as those in NASA's Earth science applications. A new way to display distributions at multiple grid locations is to project the distributions from an individual row, column or other user-selectable straight transect from the 2D domain. First at each grid cell in a given slice (row, column or transect), we compute a smooth density estimate from the underlying data. Such a density estimate for the probability density function (PDF) is generally more useful than a histogram, which is a classic density estimate. Then, the collection of PDFs along a given slice are presented vertically above the slice and form a wall. To minimize occlusion of intersecting slices, the corresponding walls are positioned at the far edges of the boundary. The PDF wall depicts the shapes of the distributions very dearly since peaks represent the modes (or bumps) in the PDFs. We've defined roughness as the number of peaks in the distribution. Roughness is another useful summary information for multimodal distributions. The uncertainty of the multi

  13. 78 FR 64211 - FIFRA Scientific Advisory Panel; Notice of Cancellation

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-28

    ... review scientific uncertainties associated with corn rootworm resistance monitoring for Bt corn Plant... future and announced in the Federal Register. List of Subjects Environmental protection, Pesticides...

  14. A Defence of the AR4’s Bayesian Approach to Quantifying Uncertainty

    NASA Astrophysics Data System (ADS)

    Vezer, M. A.

    2009-12-01

    The field of climate change research is a kimberlite pipe filled with philosophic diamonds waiting to be mined and analyzed by philosophers. Within the scientific literature on climate change, there is much philosophical dialogue regarding the methods and implications of climate studies. To this date, however, discourse regarding the philosophy of climate science has been confined predominately to scientific - rather than philosophical - investigations. In this paper, I hope to bring one such issue to the surface for explicit philosophical analysis: The purpose of this paper is to address a philosophical debate pertaining to the expressions of uncertainty in the International Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), which, as will be noted, has received significant attention in scientific journals and books, as well as sporadic glances from the popular press. My thesis is that the AR4’s Bayesian method of uncertainty analysis and uncertainty expression is justifiable on pragmatic grounds: it overcomes problems associated with vagueness, thereby facilitating communication between scientists and policy makers such that the latter can formulate decision analyses in response to the views of the former. Further, I argue that the most pronounced criticisms against the AR4’s Bayesian approach, which are outlined below, are misguided. §1 Introduction Central to AR4 is a list of terms related to uncertainty that in colloquial conversations would be considered vague. The IPCC attempts to reduce the vagueness of its expressions of uncertainty by calibrating uncertainty terms with numerical probability values derived from a subjective Bayesian methodology. This style of analysis and expression has stimulated some controversy, as critics reject as inappropriate and even misleading the association of uncertainty terms with Bayesian probabilities. [...] The format of the paper is as follows. The investigation begins (§2) with an explanation of

  15. Uncertainty and instream flow standards

    USGS Publications Warehouse

    Castleberry, D.; Cech, J.; Erman, D.; Hankin, D.; Healey, M.; Kondolf, M.; Mengel, M.; Mohr, M.; Moyle, P.; Nielsen, Jennifer; Speed, T.; Williams, J.

    1996-01-01

    Several years ago, Science published an important essay (Ludwig et al. 1993) on the need to confront the scientific uncertainty associated with managing natural resources. The essay did not discuss instream flow standards explicitly, but its arguments apply. At an April 1995 workshop in Davis, California, all 12 participants agreed that currently no scientifically defensible method exists for defining the instream flows needed to protect particular species of fish or aquatic ecosystems (Williams, in press). We also agreed that acknowledging this fact is an essential step in dealing rationally and effectively with the problem.Practical necessity and the protection of fishery resources require that new instream flow standards be established and that existing standards be revised. However, if standards cannot be defined scientifically, how can this be done? We join others in recommending the approach of adaptive management. Applied to instream flow standards, this approach involves at least three elements.

  16. A Critical Appraisal of Uncertainty Challenges in Climate Change (Invited)

    NASA Astrophysics Data System (ADS)

    Ghanem, R.

    2010-12-01

    Climate characterization, let alone prediction if fraught with technological and scientific challenges. While some of the are procedural, others are fundamental. The net effect of these challenges is the introduction of uncertainty at many juncture throughout the process of climate prediction. A quantification of this uncertainty is paramount for the confident design of effective mitigation actions, specially as these pertain to the dynamics of socio-economic systems intricately coupled to the future climate. Uncertainties are compounded as the chain of custody on evidence is transferred from a sparsely observed reality through a series of actions where assumptions are indiscriminately applied. These actions include 1) modeling of both instruments and 2) physical reality (which includes both choice of reality to model and mathematics by which to model it), 3) assimilation of data through those models in accordance to specific criteria, 4) choice of probabilistic models by which to parametrize the weight of evidence, and 5) statistical assumptions associated with the deterministic propagation of this parametrization, 6) the synthesis of reduced models that are adapted to such constraints as computational resources and paucity of data. In climate modeling, this list is further complicated by the necessity or practice of having recourse to an ensemble of models. This talk will interpret current concepts, methods, tools and practice used in uncertainty quantification (UQ) for climate prediction in light of recent UQ developments in other domains of science and engineering. Issues of uncertainty identification, characterization, propagation, and management are addressed. The talk will highlight the requirements that must be met in order to certify and validate various statements associated with climate change science. These requirements can be viewed as drivers for innovation in science and technology. These required innovations will be also described.

  17. The uncertainties in estimating measurement uncertainties

    SciTech Connect

    Clark, J.P.; Shull, A.H.

    1994-07-01

    All measurements include some error. Whether measurements are used for accountability, environmental programs or process support, they are of little value unless accompanied by an estimate of the measurements uncertainty. This fact is often overlooked by the individuals who need measurements to make decisions. This paper will discuss the concepts of measurement, measurements errors (accuracy or bias and precision or random error), physical and error models, measurement control programs, examples of measurement uncertainty, and uncertainty as related to measurement quality. Measurements are comparisons of unknowns to knowns, estimates of some true value plus uncertainty; and are no better than the standards to which they are compared. Direct comparisons of unknowns that match the composition of known standards will normally have small uncertainties. In the real world, measurements usually involve indirect comparisons of significantly different materials (e.g., measuring a physical property of a chemical element in a sample having a matrix that is significantly different from calibration standards matrix). Consequently, there are many sources of error involved in measurement processes that can affect the quality of a measurement and its associated uncertainty. How the uncertainty estimates are determined and what they mean is as important as the measurement. The process of calculating the uncertainty of a measurement itself has uncertainties that must be handled correctly. Examples of chemistry laboratory measurement will be reviewed in this report and recommendations made for improving measurement uncertainties.

  18. Assessment of SFR Wire Wrap Simulation Uncertainties

    SciTech Connect

    Delchini, Marc-Olivier G.; Popov, Emilian L.; Pointer, William David; Swiler, Laura P.

    2016-09-30

    Predictive modeling and simulation of nuclear reactor performance and fuel are challenging due to the large number of coupled physical phenomena that must be addressed. Models that will be used for design or operational decisions must be analyzed for uncertainty to ascertain impacts to safety or performance. Rigorous, structured uncertainty analyses are performed by characterizing the model’s input uncertainties and then propagating the uncertainties through the model to estimate output uncertainty. This project is part of the ongoing effort to assess modeling uncertainty in Nek5000 simulations of flow configurations relevant to the advanced reactor applications of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Three geometries are under investigation in these preliminary assessments: a 3-D pipe, a 3-D 7-pin bundle, and a single pin from the Thermal-Hydraulic Out-of-Reactor Safety (THORS) facility.

  19. Quantifying Mixed Uncertainties in Cyber Attacker Payoffs

    SciTech Connect

    Chatterjee, Samrat; Halappanavar, Mahantesh; Tipireddy, Ramakrishna; Oster, Matthew R.; Saha, Sudip

    2015-04-15

    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 about 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.

  20. Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals

    NASA Astrophysics Data System (ADS)

    Lorente, Alba; Folkert Boersma, K.; Yu, Huan; Dörner, Steffen; Hilboll, Andreas; Richter, Andreas; Liu, Mengyao; Lamsal, Lok N.; Barkley, Michael; De Smedt, Isabelle; Van Roozendael, Michel; Wang, Yang; Wagner, Thomas; Beirle, Steffen; Lin, Jin-Tai; Krotkov, Nickolay; Stammes, Piet; Wang, Ping; Eskes, Henk J.; Krol, Maarten

    2017-03-01

    Air mass factor (AMF) calculation is the largest source of uncertainty in NO2 and HCHO satellite retrievals in situations with enhanced trace gas concentrations in the lower troposphere. Structural uncertainty arises when different retrieval methodologies are applied within the scientific community to the same satellite observations. Here, we address the issue of AMF structural uncertainty via a detailed comparison of AMF calculation methods that are structurally different between seven retrieval groups for measurements from the Ozone Monitoring Instrument (OMI). We estimate the escalation of structural uncertainty in every sub-step of the AMF calculation process. This goes beyond the algorithm uncertainty estimates provided in state-of-the-art retrievals, which address the theoretical propagation of uncertainties for one particular retrieval algorithm only. We find that top-of-atmosphere reflectances simulated by four radiative transfer models (RTMs) (DAK, McArtim, SCIATRAN and VLIDORT) agree within 1.5 %. We find that different retrieval groups agree well in the calculations of altitude resolved AMFs from different RTMs (to within 3 %), and in the tropospheric AMFs (to within 6 %) as long as identical ancillary data (surface albedo, terrain height, cloud parameters and trace gas profile) and cloud and aerosol correction procedures are being used. Structural uncertainty increases sharply when retrieval groups use their preference for ancillary data, cloud and aerosol correction. On average, we estimate the AMF structural uncertainty to be 42 % over polluted regions and 31 % over unpolluted regions, mostly driven by substantial differences in the a priori trace gas profiles, surface albedo and cloud parameters. Sensitivity studies for one particular algorithm indicate that different cloud correction approaches result in substantial AMF differences in polluted conditions (5 to 40 % depending on cloud fraction and cloud pressure, and 11 % on average) even for low

  1. 32 CFR 806.26 - Addressing FOIA requests.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... determining the correct Air Force element to address their requests. If there is uncertainty as to the... Reserve Command (AFRC): HQ AFRC/SCSM, 155 2nd Street, Robins AFB, GA 31098-1635. (5) Air Force...

  2. 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.

  3. Uncertainty Analysis in the Decadal Survey Era: A Hydrologic Application using the Land Information System (LIS)

    NASA Astrophysics Data System (ADS)

    Harrison, K.; Kumar, S.; Peters-Lidard, C. D.; Santanello, J. A.

    2010-12-01

    Computing and algorithmic advancements are making possible a more complete accounting of errors and uncertainties in earth science modeling. Knowledge of uncertainty can be critical in many application areas and can help to guide scientific research efforts. Here, we describe a plan and progress to date for a fuller accounting of hydrologic modeling uncertainties that addresses the challenges posed by decadal survey missions. These challenges include the need to account for a wide range of error sources (e.g., model error, stochastically varying inputs, observational error, downscaling) and uncertainties (model parameters, error parameters, model selection). In addition, there is a need to incorporate into an assessment all available data, which for decadal survey missions includes the wealth of data from ground, air and satellite observing systems. Our core tool is NASA’s Land Information System (LIS), a high-resolution, high-performance, land surface modeling and data assimilation system that supports a wide range of land surface research and applications. Support for parameter and uncertainty estimation was recently incorporated into the software architecture, and to date three optimization algorithms (Levenberg-Marquardt, Genetic Algorithm, and SCE-UA) and two Markov chain Monte Carlo algorithms for Bayesian analysis (random walk, Differential Evolution-Monte Carlo) have been added. Results and discussion center on a case study that was the focus of Santanello et al. (2007) who demonstrated the use of remotely sensed soil moisture for hydrologic parameter estimation in the Walnut Gulch Experimental Watershed. We contrast results from uncertainty estimation to those from parameter estimation alone. We demonstrate considerable but not complete uncertainty reduction. From this analysis, we identify remaining challenges to a more complete accounting of uncertainties.

  4. The face of uncertainty eats.

    PubMed

    Corwin, Rebecca L W

    2011-09-01

    The idea that foods rich in fat and sugar may be addictive has generated much interest, as well as controversy, among both scientific and lay communities. Recent research indicates that fatty and sugary food in-and-of itself is not addictive. Rather, the food and the context in which it is consumed interact to produce an addiction-like state. One of the contexts that appears to be important is the intermittent opportunity to consume foods rich in fat and sugar in environments where food is plentiful. Animal research indicates that, under these conditions, intake of the fatty sugary food escalates across time and binge-type behavior develops. However, the mechanisms that account for the powerful effect of intermittency on ingestive behavior have only begun to be elucidated. In this review, it is proposed that intermittency stimulates appetitive behavior that is associated with uncertainty regarding what, when, and how much of the highly palatable food to consume. Uncertainty may stimulate consumption of optional fatty and sugary treats due to differential firing of midbrain dopamine neurons, activation of the stress axis, and involvement of orexin signaling. In short, uncertainty may produce an aversive state that bingeing on palatable food can alleviate, however temporarily. "Food addiction" may not be "addiction" to food at all; it may be a response to uncertainty within environments of food abundance.

  5. MODEL VALIDATION AND UNCERTAINTY QUANTIFICATION.

    SciTech Connect

    Hemez, F.M.; Doebling, S.W.

    2000-10-01

    This session offers an open forum to discuss issues and directions of research in the areas of model updating, predictive quality of computer simulations, model validation and uncertainty quantification. Technical presentations review the state-of-the-art in nonlinear dynamics and model validation for structural dynamics. A panel discussion introduces the discussion on technology needs, future trends and challenges ahead with an emphasis placed on soliciting participation of the audience, One of the goals is to show, through invited contributions, how other scientific communities are approaching and solving difficulties similar to those encountered in structural dynamics. The session also serves the purpose of presenting the on-going organization of technical meetings sponsored by the U.S. Department of Energy and dedicated to health monitoring, damage prognosis, model validation and uncertainty quantification in engineering applications. The session is part of the SD-2000 Forum, a forum to identify research trends, funding opportunities and to discuss the future of structural dynamics.

  6. Pandemic influenza: certain uncertainties

    PubMed Central

    Morens, David M.; Taubenberger, Jeffery K.

    2011-01-01

    SUMMARY For at least five centuries, major epidemics and pandemics of influenza have occurred unexpectedly and at irregular intervals. Despite the modern notion that pandemic influenza is a distinct phenomenon obeying such constant (if incompletely understood) rules such as dramatic genetic change, cyclicity, “wave” patterning, virus replacement, and predictable epidemic behavior, much evidence suggests the opposite. Although there is much that we know about pandemic influenza, there appears to be much more that we do not know. Pandemics arise as a result of various genetic mechanisms, have no predictable patterns of mortality among different age groups, and vary greatly in how and when they arise and recur. Some are followed by new pandemics, whereas others fade gradually or abruptly into long-term endemicity. Human influenza pandemics have been caused by viruses that evolved singly or in co-circulation with other pandemic virus descendants and often have involved significant transmission between, or establishment of, viral reservoirs within other animal hosts. In recent decades, pandemic influenza has continued to produce numerous unanticipated events that expose fundamental gaps in scientific knowledge. Influenza pandemics appear to be not a single phenomenon but a heterogeneous collection of viral evolutionary events whose similarities are overshadowed by important differences, the determinants of which remain poorly understood. These uncertainties make it difficult to predict influenza pandemics and, therefore, to adequately plan to prevent them. PMID:21706672

  7. MOMENTS OF UNCERTAINTY: ETHICAL CONSIDERATIONS AND EMERGING CONTAMINANTS

    PubMed Central

    Cordner, Alissa; Brown, Phil

    2013-01-01

    Science on emerging environmental health threats involves numerous ethical concerns related to scientific uncertainty about conducting, interpreting, communicating, and acting upon research findings, but the connections between ethical decision making and scientific uncertainty are under-studied in sociology. Under conditions of scientific uncertainty, researcher conduct is not fully prescribed by formal ethical codes of conduct, increasing the importance of ethical reflection by researchers, conflicts over research conduct, and reliance on informal ethical standards. This paper draws on in-depth interviews with scientists, regulators, activists, industry representatives, and fire safety experts to explore ethical considerations of moments of uncertainty using a case study of flame retardants, chemicals widely used in consumer products with potential negative health and environmental impacts. We focus on the uncertainty that arises in measuring people’s exposure to these chemicals through testing of their personal environments or bodies. We identify four sources of ethical concerns relevant to scientific uncertainty: 1) choosing research questions or methods, 2) interpreting scientific results, 3) communicating results to multiple publics, and 4) applying results for policy-making. This research offers lessons about professional conduct under conditions of uncertainty, ethical research practice, democratization of scientific knowledge, and science’s impact on policy. PMID:24249964

  8. MOMENTS OF UNCERTAINTY: ETHICAL CONSIDERATIONS AND EMERGING CONTAMINANTS.

    PubMed

    Cordner, Alissa; Brown, Phil

    2013-09-01

    Science on emerging environmental health threats involves numerous ethical concerns related to scientific uncertainty about conducting, interpreting, communicating, and acting upon research findings, but the connections between ethical decision making and scientific uncertainty are under-studied in sociology. Under conditions of scientific uncertainty, researcher conduct is not fully prescribed by formal ethical codes of conduct, increasing the importance of ethical reflection by researchers, conflicts over research conduct, and reliance on informal ethical standards. This paper draws on in-depth interviews with scientists, regulators, activists, industry representatives, and fire safety experts to explore ethical considerations of moments of uncertainty using a case study of flame retardants, chemicals widely used in consumer products with potential negative health and environmental impacts. We focus on the uncertainty that arises in measuring people's exposure to these chemicals through testing of their personal environments or bodies. We identify four sources of ethical concerns relevant to scientific uncertainty: 1) choosing research questions or methods, 2) interpreting scientific results, 3) communicating results to multiple publics, and 4) applying results for policy-making. This research offers lessons about professional conduct under conditions of uncertainty, ethical research practice, democratization of scientific knowledge, and science's impact on policy.

  9. Earthquake Loss Estimation Uncertainties

    NASA Astrophysics Data System (ADS)

    Frolova, Nina; Bonnin, Jean; Larionov, Valery; Ugarov, Aleksander

    2013-04-01

    The paper addresses the reliability issues of strong earthquakes loss assessment following strong earthquakes with worldwide Systems' application in emergency mode. Timely and correct action just after an event can result in significant benefits in saving lives. In this case the information about possible damage and expected number of casualties is very critical for taking decision about search, rescue operations and offering humanitarian assistance. Such rough information may be provided by, first of all, global systems, in emergency mode. The experience of earthquakes disasters in different earthquake-prone countries shows that the officials who are in charge of emergency response at national and international levels are often lacking prompt and reliable information on the disaster scope. Uncertainties on the parameters used in the estimation process are numerous and large: knowledge about physical phenomena and uncertainties on the parameters used to describe them; global adequacy of modeling techniques to the actual physical phenomena; actual distribution of population at risk at the very time of the shaking (with respect to immediate threat: buildings or the like); knowledge about the source of shaking, etc. Needless to be a sharp specialist to understand, for example, that the way a given building responds to a given shaking obeys mechanical laws which are poorly known (if not out of the reach of engineers for a large portion of the building stock); if a carefully engineered modern building is approximately predictable, this is far not the case for older buildings which make up the bulk of inhabited buildings. The way population, inside the buildings at the time of shaking, is affected by the physical damage caused to the buildings is not precisely known, by far. The paper analyzes the influence of uncertainties in strong event parameters determination by Alert Seismological Surveys, of simulation models used at all stages from, estimating shaking intensity

  10. Climate change adaptation under uncertainty in the developing world: A case study of sea level rise in Kiribati

    NASA Astrophysics Data System (ADS)

    Donner, S. D.; Webber, S.

    2011-12-01

    Climate change is expected to have the greatest impact in parts of the developing world. At the 2010 meeting of U.N. Framework Convention on Climate Change in Cancun, industrialized countries agreed in principle to provide US$100 billion per year by 2020 to assist the developing world respond to climate change. This "Green Climate Fund" is a critical step towards addressing the challenge of climate change. However, the policy and discourse on supporting adaptation in the developing world remains highly idealized. For example, the efficacy of "no regrets" adaptation efforts or "mainstreaming" adaptation into decision-making are rarely evaluated in the real world. In this presentation, I will discuss the gap between adaptation theory and practice using a multi-year case study of the cultural, social and scientific obstacles to adapting to sea level rise in the Pacific atoll nation of Kiribati. Our field research reveals how scientific and institutional uncertainty can limit international efforts to fund adaptation and lead to spiraling costs. Scientific uncertainty about hyper-local impacts of sea level rise, though irreducible, can at times limit decision-making about adaptation measures, contrary to the notion that "good" decision-making practices can incorporate scientific uncertainty. Efforts to improve institutional capacity must be done carefully, or they risk inadvertently slowing the implementation of adaptation measures and increasing the likelihood of "mal"-adaptation.

  11. The Scientific Competitiveness of Nations

    PubMed Central

    Cimini, Giulio; Gabrielli, Andrea; Sylos Labini, Francesco

    2014-01-01

    We use citation data of scientific articles produced by individual nations in different scientific domains to determine the structure and efficiency of national research systems. We characterize the scientific fitness of each nation—that is, the competitiveness of its research system—and the complexity of each scientific domain by means of a non-linear iterative algorithm able to assess quantitatively the advantage of scientific diversification. We find that technological leading nations, beyond having the largest production of scientific papers and the largest number of citations, do not specialize in a few scientific domains. Rather, they diversify as much as possible their research system. On the other side, less developed nations are competitive only in scientific domains where also many other nations are present. Diversification thus represents the key element that correlates with scientific and technological competitiveness. A remarkable implication of this structure of the scientific competition is that the scientific domains playing the role of “markers” of national scientific competitiveness are those not necessarily of high technological requirements, but rather addressing the most “sophisticated” needs of the society. PMID:25493626

  12. Addressing Ozone Layer Depletion

    EPA Pesticide Factsheets

    Access information on EPA's efforts to address ozone layer depletion through regulations, collaborations with stakeholders, international treaties, partnerships with the private sector, and enforcement actions under Title VI of the Clean Air Act.

  13. Do uncertainty analyses reveal uncertainties? Using the introduction of DNA vaccines to aquaculture as a case.

    PubMed

    Gillund, Frøydis; Kjølberg, Kamilla A; von Krauss, Martin Krayer; Myhr, Anne I

    2008-12-15

    The Walker and Harremoës (W&H) uncertainty framework is a tool to systematically identify scientific uncertainty. We applied the W&H uncertainty framework to elicit scientists' judgements of potential sources of uncertainty associated with the use of DNA vaccination in aquaculture. DNA vaccination is considered a promising solution to combat pathological fish diseases. There is, however, lack of knowledge regarding its ecological and social implications. Our findings indicate that scientists are open and aware of a number of uncertainties associated with DNA vaccination e.g. with regard to immune response, degradation and distribution of the DNA plasmid after injection and environmental release, and consider most of these uncertainties to be adequately reduced through more research. We proceed to discuss our experience of using the W&H uncertainty framework. Some challenges related to the application of the framework were recognised. This was especially related to the respondents' unfamiliarity with the concepts used and their lack of experience in discussing qualitative aspects of uncertainties. As we see it, the W&H framework should be considered as a useful tool to stimulate reflection on uncertainty and an important first step in a more extensive process of including and properly dealing with uncertainties in science and policymaking.

  14. An Ontology for Uncertainty in Climate Change Projections

    NASA Astrophysics Data System (ADS)

    King, A. W.

    2011-12-01

    Paraphrasing Albert Einstein's aphorism about scientific quantification: not all uncertainty that counts can be counted, and not all uncertainty that can be counted counts. The meaning of the term "uncertainty" in climate change science and assessment is itself uncertain. Different disciplines and perspectives bring different nuances if not meanings of the term to the conversation. For many scientists, uncertainty is somehow associated with statistical dispersion and standard error. For many users of climate change information, uncertainty is more related to their confidence, or lack thereof, in climate models. These "uncertainties" may be related, but they are not identical, and there is considerable room for confusion and misunderstanding. A knowledge framework, a system of concepts and vocabulary, for communicating uncertainty can add structure to the characterization and quantification of uncertainty and aid communication among scientists and users. I have developed an ontology for uncertainty in climate change projections derived largely from the report of the W3C Uncertainty Reasoning for the World Wide Web Incubator Group (URW3-XG) dealing with the problem of uncertainty representation and reasoning on the World Wide Web. I have adapted this ontology for uncertainty about information to uncertainty about climate change. Elements of the ontology apply with little or no translation to the information of climate change projections, with climate change almost a use case. Other elements can be translated into language used in climate-change discussions; translating aleatory uncertainty in the UncertaintyNature class as irreducible uncertainty is an example. I have added classes for source of uncertainty (UncertaintySource) (different model physics, for example) and metrics of uncertainty (UncertaintyMetric), at least, in the case of the latter, for those instances of uncertainty that can be quantified (i.e., counted). The statistical standard deviation isa member

  15. Structural Damage Assessment under Uncertainty

    NASA Astrophysics Data System (ADS)

    Lopez Martinez, Israel

    Structural damage assessment has applications in the majority of engineering structures and mechanical systems ranging from aerospace vehicles to manufacturing equipment. The primary goals of any structural damage assessment and health monitoring systems are to ascertain the condition of a structure and to provide an evaluation of changes as a function of time as well as providing an early-warning of an unsafe condition. There are many structural heath monitoring and assessment techniques developed for research using numerical simulations and scaled structural experiments. However, the transition from research to real-world structures has been rather slow. One major reason for this slow-progress is the existence of uncertainty in every step of the damage assessment process. This dissertation research involved the experimental and numerical investigation of uncertainty in vibration-based structural health monitoring and development of robust detection and localization methods. The basic premise of vibration-based structural health monitoring is that changes in structural characteristics, such as stiffness, mass and damping, will affect the global vibration response of the structure. The diagnostic performance of vibration-based monitoring system is affected by uncertainty sources such as measurement errors, environmental disturbances and parametric modeling uncertainties. To address diagnostic errors due to irreducible uncertainty, a pattern recognition framework for damage detection has been developed to be used for continuous monitoring of structures. The robust damage detection approach developed is based on the ensemble of dimensional reduction algorithms for improved damage-sensitive feature extraction. For damage localization, the determination of an experimental structural model was performed based on output-only modal analysis. An experimental model correlation technique is developed in which the discrepancies between the undamaged and damaged modal data are

  16. Quantification of uncertainties for application in detonation simulation

    NASA Astrophysics Data System (ADS)

    Zheng, Miao; Ma, Zhibo

    2016-06-01

    Numerical simulation has become an important means in designing detonation systems, and the quantification of its uncertainty is also necessary to reliability certification. As to quantifying the uncertainty, it is the most important to analyze how the uncertainties occur and develop, and how the simulations develop from benchmark models to new models. Based on the practical needs of engineering and the technology of verification & validation, a framework of QU(quantification of uncertainty) is brought forward in the case that simulation is used on detonation system for scientific prediction. An example is offered to describe the general idea of quantification of simulation uncertainties.

  17. AMCA Presidential Address

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The American Mosquito Control Association and mosquito control will be discussed. The American Mosquito Control Association in a non-profit scientific organization dedicated to promoting the highest standard in professional mosquito control. It is comprised of more than 1500 members representing st...

  18. Direct Aerosol Forcing Uncertainty

    DOE Data Explorer

    Mccomiskey, Allison

    2008-01-15

    Understanding sources of uncertainty in aerosol direct radiative forcing (DRF), the difference in a given radiative flux component with and without aerosol, is essential to quantifying changes in Earth's radiation budget. We examine the uncertainty in DRF due to measurement uncertainty in the quantities on which it depends: aerosol optical depth, single scattering albedo, asymmetry parameter, solar geometry, and surface albedo. Direct radiative forcing at the top of the atmosphere and at the surface as well as sensitivities, the changes in DRF in response to unit changes in individual aerosol or surface properties, are calculated at three locations representing distinct aerosol types and radiative environments. The uncertainty in DRF associated with a given property is computed as the product of the sensitivity and typical measurement uncertainty in the respective aerosol or surface property. Sensitivity and uncertainty values permit estimation of total uncertainty in calculated DRF and identification of properties that most limit accuracy in estimating forcing. Total uncertainties in modeled local diurnally averaged forcing range from 0.2 to 1.3 W m-2 (42 to 20%) depending on location (from tropical to polar sites), solar zenith angle, surface reflectance, aerosol type, and aerosol optical depth. The largest contributor to total uncertainty in DRF is usually single scattering albedo; however decreasing measurement uncertainties for any property would increase accuracy in DRF. Comparison of two radiative transfer models suggests the contribution of modeling error is small compared to the total uncertainty although comparable to uncertainty arising from some individual properties.

  19. Experimental uncertainty estimation and statistics for data having interval uncertainty.

    SciTech Connect

    Kreinovich, Vladik (Applied Biomathematics, Setauket, New York); Oberkampf, William Louis (Applied Biomathematics, Setauket, New York); Ginzburg, Lev (Applied Biomathematics, Setauket, New York); Ferson, Scott (Applied Biomathematics, Setauket, New York); Hajagos, Janos (Applied Biomathematics, Setauket, New York)

    2007-05-01

    This report addresses the characterization of measurements that include epistemic uncertainties in the form of intervals. It reviews the application of basic descriptive statistics to data sets which contain intervals rather than exclusively point estimates. It describes algorithms to compute various means, the median and other percentiles, variance, interquartile range, moments, confidence limits, and other important statistics and summarizes the computability of these statistics as a function of sample size and characteristics of the intervals in the data (degree of overlap, size and regularity of widths, etc.). It also reviews the prospects for analyzing such data sets with the methods of inferential statistics such as outlier detection and regressions. The report explores the tradeoff between measurement precision and sample size in statistical results that are sensitive to both. It also argues that an approach based on interval statistics could be a reasonable alternative to current standard methods for evaluating, expressing and propagating measurement uncertainties.

  20. Spatial uncertainty and ecological models

    SciTech Connect

    Jager, Yetta; King, Anthony Wayne

    2004-07-01

    Applied ecological models that are used to understand and manage natural systems often rely on spatial data as input. Spatial uncertainty in these data can propagate into model predictions. Uncertainty analysis, sensitivity analysis, error analysis, error budget analysis, spatial decision analysis, and hypothesis testing using neutral models are all techniques designed to explore the relationship between variation in model inputs and variation in model predictions. Although similar methods can be used to answer them, these approaches address different questions. These approaches differ in (a) whether the focus is forward or backward (forward to evaluate the magnitude of variation in model predictions propagated or backward to rank input parameters by their influence); (b) whether the question involves model robustness to large variations in spatial pattern or to small deviations from a reference map; and (c) whether processes that generate input uncertainty (for example, cartographic error) are of interest. In this commentary, we propose a taxonomy of approaches, all of which clarify the relationship between spatial uncertainty and the predictions of ecological models. We describe existing techniques and indicate a few areas where research is needed.

  1. Uncertainty estimation and prediction for interdisciplinary ocean dynamics

    SciTech Connect

    Lermusiaux, Pierre F.J. . E-mail: pierrel@pacific.harvard.edu

    2006-09-01

    Scientific computations for the quantification, estimation and prediction of uncertainties for ocean dynamics are developed and exemplified. Primary characteristics of ocean data, models and uncertainties are reviewed and quantitative data assimilation concepts defined. Challenges involved in realistic data-driven simulations of uncertainties for four-dimensional interdisciplinary ocean processes are emphasized. Equations governing uncertainties in the Bayesian probabilistic sense are summarized. Stochastic forcing formulations are introduced and a new stochastic-deterministic ocean model is presented. The computational methodology and numerical system, Error Subspace Statistical Estimation, that is used for the efficient estimation and prediction of oceanic uncertainties based on these equations is then outlined. Capabilities of the ESSE system are illustrated in three data-assimilative applications: estimation of uncertainties for physical-biogeochemical fields, transfers of ocean physics uncertainties to acoustics, and real-time stochastic ensemble predictions with assimilation of a wide range of data types. Relationships with other modern uncertainty quantification schemes and promising research directions are discussed.

  2. Rethinking Uncertainty: What Does the Public Need to Know?

    NASA Astrophysics Data System (ADS)

    Oreskes, N.

    2012-12-01

    The late Steven Schneider is often quoted as addressing the double-bind of science communication: that to be a good scientist one has to be cautious and acknowledge uncertainty, but to reach the media and the public one has to be bold, incautious, and even a bit dramatic. Here, I focus on a related but different double-bind: the double bind of responding to doubt. In our recent book, Merchants of Doubt, Erik M. Conway and I showed how doubt-mongers exploited scientific uncertainty as a political strategy to confuse the public and delay action on a range of environmental issues from the harms of tobacco to the reality of anthropogenic climate change. This strategy is effective because it appeals to lay people, journalists,' and even fellow scientists' sense of fair play—that it is right to hear "both sides" of an issue. Scientists are then caught in a double-bind: refusing to respond seems smug and elitist, but responding scientifically seems to confirm that there is in fact a scientific debate. Doubt-mongering is also hard to counter because our knowledge is, in fact, uncertain, so when we communicate in conventional scientific ways, acknowledging the uncertainties and limits in our understanding, we may end up reinforcing the uncertainty framework. The difficulty is exacerbated by the natural tendency of scientists to focus on novel and original results, rather than matters that are well established, lest we be accused of lacking originality or of taking credit for other's work. The net result is the impression among lay people that our knowledge is very likely to change and therefore a weak basis for making public policy decision. History of science, however, suggests a different picture: we know that a good deal of scientific knowledge has proved temporally robust and has provided a firm basis for effective public policy. Action on earlier environmental issues such as DDT and acid rain, guided by scientific knowledge, has worked to limit environmental damage

  3. Uncertainty in environmental health impact assessment: quantitative methods and perspectives.

    PubMed

    Mesa-Frias, Marco; Chalabi, Zaid; Vanni, Tazio; Foss, Anna M

    2013-01-01

    Environmental health impact assessment models are subjected to great uncertainty due to the complex associations between environmental exposures and health. Quantifying the impact of uncertainty is important if the models are used to support health policy decisions. We conducted a systematic review to identify and appraise current methods used to quantify the uncertainty in environmental health impact assessment. In the 19 studies meeting the inclusion criteria, several methods were identified. These were grouped into random sampling methods, second-order probability methods, Bayesian methods, fuzzy sets, and deterministic sensitivity analysis methods. All 19 studies addressed the uncertainty in the parameter values but only 5 of the studies also addressed the uncertainty in the structure of the models. None of the articles reviewed considered conceptual sources of uncertainty associated with the framing assumptions or the conceptualisation of the model. Future research should attempt to broaden the way uncertainty is taken into account in environmental health impact assessments.

  4. Uncertainties in Arctic Precipitation

    NASA Astrophysics Data System (ADS)

    Majhi, I.; Alexeev, V. A.; Cherry, J. E.; Cohen, J. L.; Groisman, P. Y.

    2012-12-01

    Arctic precipitation is riddled with measurement biases; to address the problem is imperative. Our study focuses on comparison of various datasets and analyzing their biases for the region of Siberia and caution that is needed when using them. Five sources of data were used ranging from NOAA's product (RAW, Bogdanova's correction), Yang's correction technique and two reanalysis products (ERA-Interim and NCEP). The reanalysis dataset performed better for some months in comparison to Yang's product, which tends to overestimate precipitation, and the raw dataset, which tends to underestimate. The sources of bias vary from topography, to wind, to missing data .The final three products chosen show higher biases during the winter and spring season. Emphasis on equations which incorporate blizzards, blowing snow and higher wind speed is necessary for regions which are influenced by any or all of these factors; Bogdanova's correction technique is the most robust of all the datasets analyzed and gives the most reasonable results. One of our future goals is to analyze the impact of precipitation uncertainties on water budget analysis for the Siberian Rivers.

  5. Understanding Scientific Misconduct: What Do We Know?

    ERIC Educational Resources Information Center

    Knowledge: Creation, Diffusion, Utilization, 1992

    1992-01-01

    Ten articles in this special section address the incidence and nature of scientific misconduct in the research publication process. Discussed are definitions of the problem, its prevalence, policies which may be developed to address ethical issues, and the results of a survey of the scientific community. (EA)

  6. 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

  7. Scientific Satellites

    DTIC Science & Technology

    1967-01-01

    1919 paper (ref. 9), in which he suggested a Moon rocket. Rock- etry was on a par with extrasensory perception in those days. 38 SCIENTIFIC SA&TLLITES...this way, images of sky can be taken at different wavelengths. The perceptive reader will note that the two zodiacal-light ex- periments described

  8. Scientific Documentation.

    ERIC Educational Resources Information Center

    Pieper, Gail W.

    1980-01-01

    Describes how scientific documentation is taught in three 50-minute sessions in a technical writing course. Tells how session one distinguishes between in-text notes, footnotes, and reference entries; session two discusses the author-year system of citing references; and session three is concerned with the author-number system of reference…

  9. Addressing Social Issues.

    ERIC Educational Resources Information Center

    Schoebel, Susan

    1991-01-01

    Maintains that advertising can help people become more aware of social responsibilities. Describes a successful nationwide newspaper advertising competition for college students in which ads address social issues such as literacy, drugs, teen suicide, and teen pregnancy. Notes how the ads have helped grassroots programs throughout the United…

  10. Invitational Addresses, 1965.

    ERIC Educational Resources Information Center

    Gates, Arthur I.; And Others

    The full texts of invitational addresses given at the 1965 International Reading Association (IRA) Convention in Detroit, Michigan, by six recipients of IRA citation awards are presented. Gates suggests steps IRA should take to revive and redirect reading research. McCallister discusses the implications of the changing and expanding vocabulary of…

  11. States Address Achievement Gaps.

    ERIC Educational Resources Information Center

    Christie, Kathy

    2002-01-01

    Summarizes 2 state initiatives to address the achievement gap: North Carolina's report by the Advisory Commission on Raising Achievement and Closing Gaps, containing an 11-point strategy, and Kentucky's legislation putting in place 10 specific processes. The North Carolina report is available at www.dpi.state.nc.us.closingthegap; Kentucky's…

  12. Addressing Sexual Harassment

    ERIC Educational Resources Information Center

    Young, Ellie L.; Ashbaker, Betty Y.

    2008-01-01

    This article discusses ways on how to address the problem of sexual harassment in schools. Sexual harassment--simply defined as any unwanted and unwelcome sexual behavior--is a sensitive topic. Merely providing students, parents, and staff members with information about the school's sexual harassment policy is insufficient; schools must take…

  13. Chemical Principles Revisited: Perspectives on the Uncertainty Principle and Quantum Reality.

    ERIC Educational Resources Information Center

    Bartell, Lawrence S.

    1985-01-01

    Explicates an approach that not only makes the uncertainty seem more useful to introductory students but also helps convey the real meaning of the term "uncertainty." General topic areas addressed include probability amplitudes, rationale behind the uncertainty principle, applications of uncertainty relations, and quantum processes. (JN)

  14. Scientific Software Component Technology

    SciTech Connect

    Kohn, S.; Dykman, N.; Kumfert, G.; Smolinski, B.

    2000-02-16

    We are developing new software component technology for high-performance parallel scientific computing to address issues of complexity, re-use, and interoperability for laboratory software. Component technology enables cross-project code re-use, reduces software development costs, and provides additional simulation capabilities for massively parallel laboratory application codes. The success of our approach will be measured by its impact on DOE mathematical and scientific software efforts. Thus, we are collaborating closely with library developers and application scientists in the Common Component Architecture forum, the Equation Solver Interface forum, and other DOE mathematical software groups to gather requirements, write and adopt a variety of design specifications, and develop demonstration projects to validate our approach. Numerical simulation is essential to the science mission at the laboratory. However, it is becoming increasingly difficult to manage the complexity of modern simulation software. Computational scientists develop complex, three-dimensional, massively parallel, full-physics simulations that require the integration of diverse software packages written by outside development teams. Currently, the integration of a new software package, such as a new linear solver library, can require several months of effort. Current industry component technologies such as CORBA, JavaBeans, and COM have all been used successfully in the business domain to reduce software development costs and increase software quality. However, these existing industry component infrastructures will not scale to support massively parallel applications in science and engineering. In particular, they do not address issues related to high-performance parallel computing on ASCI-class machines, such as fast in-process connections between components, language interoperability for scientific languages such as Fortran, parallel data redistribution between components, and massively

  15. Scientific Claims versus Scientific Knowledge.

    ERIC Educational Resources Information Center

    Ramsey, John

    1991-01-01

    Provides activities that help students to understand the importance of the scientific method. The activities include the science of fusion and cold fusion; a group activity that analyzes and interprets the events surrounding cold fusion; and an application research project concerning a current science issue. (ZWH)

  16. Scientific Misconduct

    NASA Astrophysics Data System (ADS)

    Moore, John W.

    2002-12-01

    These cases provide a good basis for discussions of scientific ethics, particularly with respect to the responsibilities of colleagues in collaborative projects. With increasing numbers of students working in cooperative or collaborative groups, there may be opportunities for more than just discussion—similar issues of responsibility apply to the members of such groups. Further, this is an area where, “no clear, widely accepted standards of behavior exist” (1). Thus there is an opportunity to point out to students that scientific ethics, like science itself, is incomplete and needs constant attention to issues that result from new paradigms such as collaborative research. Finally, each of us can resolve to pay more attention to the contributions we and our colleagues make to collaborative projects, applying to our own work no less critical an eye than we would cast on the work of those we don’t know at all.

  17. Maintaining Realistic Uncertainty in Model and Forecast

    DTIC Science & Technology

    2000-09-30

    Maintaining Realistic Uncertainty in Model and Forecast Leonard Smith Pembroke College Oxford University St. Aldates Oxford OX1 1DW United Kingdom...5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Pembroke College, Oxford University ,,St...evaluation: l-shadowing, probabilistic prediction and weather forecasting. D.Phil Thesis, Oxford University . Lorenz, E. (1995) Predictability-a Partially

  18. Content Addressable Memory Project

    DTIC Science & Technology

    1990-11-01

    The Content Addressable M1-emory Project consists of the development of several experimental software systems on an AMT Distributed Array Processor...searching (database) compiler algorithms memory management other systems software) Linear C is an unlovely hybrid language which imports the CAM...memory from AMT’s operating system for the DAP; how- ever, other than this limitation, the memory management routines work exactly as their C counterparts

  19. Uncertainty in hydrological signatures

    NASA Astrophysics Data System (ADS)

    Westerberg, I. K.; McMillan, H. K.

    2015-09-01

    Information about rainfall-runoff processes is essential for hydrological analyses, modelling and water-management applications. A hydrological, or diagnostic, signature quantifies such information from observed data as an index value. Signatures are widely used, e.g. for catchment classification, model calibration and change detection. Uncertainties in the observed data - including measurement inaccuracy and representativeness as well as errors relating to data management - propagate to the signature values and reduce their information content. Subjective choices in the calculation method are a further source of uncertainty. We review the uncertainties relevant to different signatures based on rainfall and flow data. We propose a generally applicable method to calculate these uncertainties based on Monte Carlo sampling and demonstrate it in two catchments for common signatures including rainfall-runoff thresholds, recession analysis and basic descriptive signatures of flow distribution and dynamics. Our intention is to contribute to awareness and knowledge of signature uncertainty, including typical sources, magnitude and methods for its assessment. We found that the uncertainties were often large (i.e. typical intervals of ±10-40 % relative uncertainty) and highly variable between signatures. There was greater uncertainty in signatures that use high-frequency responses, small data subsets, or subsets prone to measurement errors. There was lower uncertainty in signatures that use spatial or temporal averages. Some signatures were sensitive to particular uncertainty types such as rating-curve form. We found that signatures can be designed to be robust to some uncertainty sources. Signature uncertainties of the magnitudes we found have the potential to change the conclusions of hydrological and ecohydrological analyses, such as cross-catchment comparisons or inferences about dominant processes.

  20. [Ethics, empiricism and uncertainty].

    PubMed

    Porz, R; Zimmermann, H; Exadaktylos, A K

    2011-01-01

    Accidents can lead to difficult boundary situations. Such situations often take place in the emergency units. The medical team thus often and inevitably faces professional uncertainty in their decision-making. It is essential to communicate these uncertainties within the medical team, instead of downplaying or overriding existential hurdles in decision-making. Acknowledging uncertainties might lead to alert and prudent decisions. Thus uncertainty can have ethical value in treatment or withdrawal of treatment. It does not need to be covered in evidence-based arguments, especially as some singular situations of individual tragedies cannot be grasped in terms of evidence-based medicine.

  1. Classification and moral evaluation of uncertainties in engineering modeling.

    PubMed

    Murphy, Colleen; Gardoni, Paolo; Harris, Charles E

    2011-09-01

    Engineers must deal with risks and uncertainties as a part of their professional work and, in particular, uncertainties are inherent to engineering models. Models play a central role in engineering. Models often represent an abstract and idealized version of the mathematical properties of a target. Using models, engineers can investigate and acquire understanding of how an object or phenomenon will perform under specified conditions. This paper defines the different stages of the modeling process in engineering, classifies the various sources of uncertainty that arise in each stage, and discusses the categories into which these uncertainties fall. The paper then considers the way uncertainty and modeling are approached in science and the criteria for evaluating scientific hypotheses, in order to highlight the very different criteria appropriate for the development of models and the treatment of the inherent uncertainties in engineering. Finally, the paper puts forward nine guidelines for the treatment of uncertainty in engineering modeling.

  2. Articulating and responding to uncertainties in clinical research.

    PubMed

    Djulbegovic, Benjamin

    2007-01-01

    This paper introduces taxonomy of clinical uncertaintes and argues that the choice of scientific method should match the underlying level of uncertainty. Clinical trial is one of these methods aiming to resolve clinical uncertainties. Whenever possible these uncertainties should be quantified. The paper further shows that the still ongoing debate about the usage of "equipoise" vs. "uncertainty principle" vs. "indifference" as an entry criterion to clinical trials actually refers to the question "whose uncertainty counts". This question is intimately linked to the control of research agenda, which is not quantifiable and hence is not solvable to equal acceptability to all interested parties. The author finally shows that there is a predictable relation between [acknowledgement of] uncertainty (the moral principle) on which trials are based and the ultimate outcomes of clinical trials. That is, [acknowledgement of] uncertainty determines a pattern of success in medicine and drives clinical discoveries.

  3. A review of uncertainty research in impact assessment

    SciTech Connect

    Leung, Wanda; Noble, Bram; Gunn, Jill; Jaeger, Jochen A.G.

    2015-01-15

    This paper examines uncertainty research in Impact Assessment (IA) and the focus of attention of the IA scholarly literature. We do so by first exploring ‘outside’ the IA literature, identifying three main themes of uncertainty research, and then apply these themes to examine the focus of scholarly research on uncertainty ‘inside’ IA. Based on a search of the database Scopus, we identified 134 journal papers published between 1970 and 2013 that address uncertainty in IA, 75% of which were published since 2005. We found that 90% of IA research addressing uncertainty focused on uncertainty in the practice of IA, including uncertainty in impact predictions, models and managing environmental impacts. Notwithstanding early guidance on uncertainty treatment in IA from the 1980s, we found no common, underlying conceptual framework that was guiding research on uncertainty in IA practice. Considerably less attention, only 9% of papers, focused on uncertainty communication, disclosure and decision-making under uncertain conditions, the majority of which focused on the need to disclose uncertainties as opposed to providing guidance on how to do so and effectively use that information to inform decisions. Finally, research focused on theory building for explaining human behavior with respect to uncertainty avoidance constituted only 1% of the IA published literature. We suggest the need for further conceptual framework development for researchers focused on identifying and addressing uncertainty in IA practice; the need for guidance on how best to communicate uncertainties in practice, versus criticizing practitioners for not doing so; research that explores how best to interpret and use disclosures about uncertainty when making decisions about project approvals, and the implications of doing so; and academic theory building and exploring the utility of existing theories to better understand and explain uncertainty avoidance behavior in IA. - Highlights: • We

  4. Because Doubt Is A Sure Thing: Incorporating Uncertainty Characterization Into Climate Change Decision-Making

    NASA Astrophysics Data System (ADS)

    Moss, R.; Rice, J.; Scott, M. J.; Unwin, S.; Whitney, P.

    2012-12-01

    This presentation describes the results of new research to develop a stakeholder-driven uncertainty characterization (UC) process to help address the challenges of regional climate change mitigation and adaptation decisions. Integrated regional Earth system models are a promising approach for modeling how climate change may affect natural resources, infrastructure, and socioeconomic conditions at regional scales, and how different adaptation and mitigation strategies may interact. However, the inherent complexity, long run-times, and large numbers of uncertainties in coupled regional human-environment systems render standard, model-driven approaches for uncertainty characterization infeasible. This new research focuses on characterizing stakeholder decision support needs as part of an overall process to identify the key uncertainties relevant for the application in question. The stakeholder-driven process reduces the dimensionality of the uncertainty modeling challenge while providing robust insights for science and decision-making. This research is being carried out as part of the integrated Regional Earth System Model (iRESM) initiative, a new scientific framework developed at Pacific Northwest National Laboratory to evaluate the interactions between human and environmental systems and mitigation and adaptation decisions at regional scales. The framework provides a flexible architecture for model couplings between a regional Earth system model, a regional integrated assessment model, and highly spatially resolved models of crop productivity, building energy demands, electricity infrastructure operation and expansion, and water supply and management. In an example of applying the stakeholder-driven UC process, the presentation first identifies stakeholder decision criteria for a particular regional mitigation or adaptation question. These criteria are used in conjunction with the flexible architecture to determine the relevant component models for coupling and the

  5. Tolerance and UQ4SIM: Nimble Uncertainty Documentation and Analysis Software

    NASA Technical Reports Server (NTRS)

    Kleb, Bil

    2008-01-01

    Ultimately, scientific numerical models need quantified output uncertainties so that modeling can evolve to better match reality. Documenting model input uncertainties and variabilities is a necessary first step toward that goal. Without known input parameter uncertainties, model sensitivities are all one can determine, and without code verification, output uncertainties are simply not reliable. The basic premise of uncertainty markup is to craft a tolerance and tagging mini-language that offers a natural, unobtrusive presentation and does not depend on parsing each type of input file format. Each file is marked up with tolerances and optionally, associated tags that serve to label the parameters and their uncertainties. The evolution of such a language, often called a Domain Specific Language or DSL, is given in [1], but in final form it parallels tolerances specified on an engineering drawing, e.g., 1 +/- 0.5, 5 +/- 10%, 2 +/- 10 where % signifies percent and o signifies order of magnitude. Tags, necessary for error propagation, can be added by placing a quotation-mark-delimited tag after the tolerance, e.g., 0.7 +/- 20% 'T_effective'. In addition, tolerances might have different underlying distributions, e.g., Uniform, Normal, or Triangular, or the tolerances may merely be intervals due to lack of knowledge (uncertainty). Finally, to address pragmatic considerations such as older models that require specific number-field formats, C-style format specifiers can be appended to the tolerance like so, 1.35 +/- 10U_3.2f. As an example of use, consider figure 1, where a chemical reaction input file is has been marked up to include tolerances and tags per table 1. Not only does the technique provide a natural method of specifying tolerances, but it also servers as in situ documentation of model uncertainties. This tolerance language comes with a utility to strip the tolerances (and tags), to provide a path to the nominal model parameter file. And, as shown in [1

  6. Demonstrating the value of medicines: evolution of value equation and stakeholder perception of uncertainties.

    PubMed

    Narayanan, Siva

    2016-01-01

    It is important to evaluate how the value of medicine is assessed, as it may have important implications for health technology and reimbursement assessments. The value equation could comprise 'incremental benefit/outcome' (relative results of care in terms of patient health, comparing the innovation to best available alternative(s)) in the numerator and 'cost' (relative costs involved in the full cycle of care (or a defined period) for the patient's medical condition, incorporating the relevant cost-offsets due to displacement of best available alternative(s)) in the denominator. This 'relative value' combined with the overall net budget impact (of including the drug in the formulary or reimbursed drug list) at the concerned population level in the given institution/region/country may better inform the usefulness of the new therapeutic option to the healthcare system. As product value messages are created, anticipating external stakeholder questions and information needs, including addressing three main categories of 'uncertainties', namely the scientific uncertainties, usage uncertainties, and financial uncertainties, could facilitate demonstration of optimal product value and help informed decision-making to benefit all stakeholders involved in the process.

  7. Bioreactors Addressing Diabetes Mellitus

    PubMed Central

    Minteer, Danielle M.; Gerlach, Jorg C.

    2014-01-01

    The concept of bioreactors in biochemical engineering is a well-established process; however, the idea of applying bioreactor technology to biomedical and tissue engineering issues is relatively novel and has been rapidly accepted as a culture model. Tissue engineers have developed and adapted various types of bioreactors in which to culture many different cell types and therapies addressing several diseases, including diabetes mellitus types 1 and 2. With a rising world of bioreactor development and an ever increasing diagnosis rate of diabetes, this review aims to highlight bioreactor history and emerging bioreactor technologies used for diabetes-related cell culture and therapies. PMID:25160666

  8. Bioreactors addressing diabetes mellitus.

    PubMed

    Minteer, Danielle M; Gerlach, Jorg C; Marra, Kacey G

    2014-11-01

    The concept of bioreactors in biochemical engineering is a well-established process; however, the idea of applying bioreactor technology to biomedical and tissue engineering issues is relatively novel and has been rapidly accepted as a culture model. Tissue engineers have developed and adapted various types of bioreactors in which to culture many different cell types and therapies addressing several diseases, including diabetes mellitus types 1 and 2. With a rising world of bioreactor development and an ever increasing diagnosis rate of diabetes, this review aims to highlight bioreactor history and emerging bioreactor technologies used for diabetes-related cell culture and therapies.

  9. Content addressable memory project

    NASA Technical Reports Server (NTRS)

    Hall, J. Storrs; Levy, Saul; Smith, Donald E.; Miyake, Keith M.

    1992-01-01

    A parameterized version of the tree processor was designed and tested (by simulation). The leaf processor design is 90 percent complete. We expect to complete and test a combination of tree and leaf cell designs in the next period. Work is proceeding on algorithms for the computer aided manufacturing (CAM), and once the design is complete we will begin simulating algorithms for large problems. The following topics are covered: (1) the practical implementation of content addressable memory; (2) design of a LEAF cell for the Rutgers CAM architecture; (3) a circuit design tool user's manual; and (4) design and analysis of efficient hierarchical interconnection networks.

  10. Aeroservoelastic Uncertainty Model Identification from Flight Data

    NASA Technical Reports Server (NTRS)

    Brenner, Martin J.

    2001-01-01

    Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

  11. Uncertainty quantification approaches for advanced reactor analyses.

    SciTech Connect

    Briggs, L. L.; Nuclear Engineering Division

    2009-03-24

    The original approach to nuclear reactor design or safety analyses was to make very conservative modeling assumptions so as to ensure meeting the required safety margins. Traditional regulation, as established by the U. S. Nuclear Regulatory Commission required conservatisms which have subsequently been shown to be excessive. The commission has therefore moved away from excessively conservative evaluations and has determined best-estimate calculations to be an acceptable alternative to conservative models, provided the best-estimate results are accompanied by an uncertainty evaluation which can demonstrate that, when a set of analysis cases which statistically account for uncertainties of all types are generated, there is a 95% probability that at least 95% of the cases meet the safety margins. To date, nearly all published work addressing uncertainty evaluations of nuclear power plant calculations has focused on light water reactors and on large-break loss-of-coolant accident (LBLOCA) analyses. However, there is nothing in the uncertainty evaluation methodologies that is limited to a specific type of reactor or to specific types of plant scenarios. These same methodologies can be equally well applied to analyses for high-temperature gas-cooled reactors and to liquid metal reactors, and they can be applied to steady-state calculations, operational transients, or severe accident scenarios. This report reviews and compares both statistical and deterministic uncertainty evaluation approaches. Recommendations are given for selection of an uncertainty methodology and for considerations to be factored into the process of evaluating uncertainties for advanced reactor best-estimate analyses.

  12. Climate change, uncertainty, and natural resource management

    USGS Publications Warehouse

    Nichols, J.D.; Koneff, M.D.; Heglund, P.J.; Knutson, M.G.; Seamans, M.E.; Lyons, J.E.; Morton, J.M.; Jones, M.T.; Boomer, G.S.; Williams, B.K.

    2011-01-01

    Climate change and its associated uncertainties are of concern to natural resource managers. Although aspects of climate change may be novel (e.g., system change and nonstationarity), natural resource managers have long dealt with uncertainties and have developed corresponding approaches to decision-making. Adaptive resource management is an application of structured decision-making for recurrent decision problems with uncertainty, focusing on management objectives, and the reduction of uncertainty over time. We identified 4 types of uncertainty that characterize problems in natural resource management. We examined ways in which climate change is expected to exacerbate these uncertainties, as well as potential approaches to dealing with them. As a case study, we examined North American waterfowl harvest management and considered problems anticipated to result from climate change and potential solutions. Despite challenges expected to accompany the use of adaptive resource management to address problems associated with climate change, we conclude that adaptive resource management approaches will be the methods of choice for managers trying to deal with the uncertainties of climate change. ?? 2010 The Wildlife Society.

  13. Scientific Component Technology Initiative

    SciTech Connect

    Kohn, S; Bosl, B; Dahlgren, T; Kumfert, G; Smith, S

    2003-02-07

    The laboratory has invested a significant amount of resources towards the development of high-performance scientific simulation software, including numerical libraries, visualization, steering, software frameworks, and physics packages. Unfortunately, because this software was not designed for interoperability and re-use, it is often difficult to share these sophisticated software packages among applications due to differences in implementation language, programming style, or calling interfaces. This LDRD Strategic Initiative investigated and developed software component technology for high-performance parallel scientific computing to address problems of complexity, re-use, and interoperability for laboratory software. Component technology is an extension of scripting and object-oriented software development techniques that specifically focuses on the needs of software interoperability. Component approaches based on CORBA, COM, and Java technologies are widely used in industry; however, they do not support massively parallel applications in science and engineering. Our research focused on the unique requirements of scientific computing on ASCI-class machines, such as fast in-process connections among components, language interoperability for scientific languages, and data distribution support for massively parallel SPMD components.

  14. Addressing Environmental Health Inequalities

    PubMed Central

    Gouveia, Nelson

    2016-01-01

    Environmental health inequalities refer to health hazards disproportionately or unfairly distributed among the most vulnerable social groups, which are generally the most discriminated, poor populations and minorities affected by environmental risks. Although it has been known for a long time that health and disease are socially determined, only recently has this idea been incorporated into the conceptual and practical framework for the formulation of policies and strategies regarding health. In this Special Issue of the International Journal of Environmental Research and Public Health (IJERPH), “Addressing Environmental Health Inequalities—Proceedings from the ISEE Conference 2015”, we incorporate nine papers that were presented at the 27th Conference of the International Society for Environmental Epidemiology (ISEE), held in Sao Paulo, Brazil, in 2015. This small collection of articles provides a brief overview of the different aspects of this topic. Addressing environmental health inequalities is important for the transformation of our reality and for changing the actual development model towards more just, democratic, and sustainable societies driven by another form of relationship between nature, economy, science, and politics. PMID:27618906

  15. Final Scientific EFNUDAT Workshop

    ScienceCinema

    None

    2016-07-12

    The Final Scientific EFNUDAT Workshop - organized by the CERN/EN-STI group on behalf of n_TOF Collaboration - will be held at CERN, Geneva (Switzerland) from 30 August to 2 September 2010 inclusive.EFNUDAT website: http://www.efnudat.euTopics of interest include: Data evaluationCross section measurementsExperimental techniquesUncertainties and covariancesFission propertiesCurrent and future facilities  International Advisory Committee: C. Barreau (CENBG, France)T. Belgya (IKI KFKI, Hungary)E. Gonzalez (CIEMAT, Spain)F. Gunsing (CEA, France)F.-J. Hambsch (IRMM, Belgium)A. Junghans (FZD, Germany)R. Nolte (PTB, Germany)S. Pomp (TSL UU, Sweden) Workshop Organizing Committee: Enrico Chiaveri (Chairman)Marco CalvianiSamuel AndriamonjeEric BerthoumieuxCarlos GuerreroRoberto LositoVasilis Vlachoudis Workshop Assistant: Géraldine Jean

  16. Electoral Knowledge and Uncertainty.

    ERIC Educational Resources Information Center

    Blood, R. Warwick; And Others

    Research indicates that the media play a role in shaping the information that voters have about election options. Knowledge of those options has been related to actual vote, but has not been shown to be strongly related to uncertainty. Uncertainty, however, does seem to motivate voters to engage in communication activities, some of which may…

  17. Intolerance of Uncertainty

    PubMed Central

    Beier, Meghan L.

    2015-01-01

    Multiple sclerosis (MS) is a chronic and progressive neurologic condition that, by its nature, carries uncertainty as a hallmark characteristic. Although all patients face uncertainty, there is variability in how individuals cope with its presence. In other populations, the concept of “intolerance of uncertainty” has been conceptualized to explain this variability such that individuals who have difficulty tolerating the possibility of future occurrences may engage in thoughts or behaviors by which they attempt to exert control over that possibility or lessen the uncertainty but may, as a result, experience worse outcomes, particularly in terms of psychological well-being. This topical review introduces MS-focused researchers, clinicians, and patients to intolerance of uncertainty, integrates the concept with what is already understood about coping with MS, and suggests future steps for conceptual, assessment, and treatment-focused research that may benefit from integrating intolerance of uncertainty as a central feature. PMID:26300700

  18. Economic uncertainty and econophysics

    NASA Astrophysics Data System (ADS)

    Schinckus, Christophe

    2009-10-01

    The objective of this paper is to provide a methodological link between econophysics and economics. I will study a key notion of both fields: uncertainty and the ways of thinking about it developed by the two disciplines. After having presented the main economic theories of uncertainty (provided by Knight, Keynes and Hayek), I show how this notion is paradoxically excluded from the economic field. In economics, uncertainty is totally reduced by an a priori Gaussian framework-in contrast to econophysics, which does not use a priori models because it works directly on data. Uncertainty is then not shaped by a specific model, and is partially and temporally reduced as models improve. This way of thinking about uncertainty has echoes in the economic literature. By presenting econophysics as a Knightian method, and a complementary approach to a Hayekian framework, this paper shows that econophysics can be methodologically justified from an economic point of view.

  19. Physical Uncertainty Bounds (PUB)

    SciTech Connect

    Vaughan, Diane Elizabeth; Preston, Dean L.

    2015-03-19

    This paper introduces and motivates the need for a new methodology for determining upper bounds on the uncertainties in simulations of engineered systems due to limited fidelity in the composite continuum-level physics models needed to simulate the systems. We show that traditional uncertainty quantification methods provide, at best, a lower bound on this uncertainty. We propose to obtain bounds on the simulation uncertainties by first determining bounds on the physical quantities or processes relevant to system performance. By bounding these physics processes, as opposed to carrying out statistical analyses of the parameter sets of specific physics models or simply switching out the available physics models, one can obtain upper bounds on the uncertainties in simulated quantities of interest.

  20. Quantifying uncertainty from material inhomogeneity.

    SciTech Connect

    Battaile, Corbett Chandler; Emery, John M.; Brewer, Luke N.; Boyce, Brad Lee

    2009-09-01

    Most engineering materials are inherently inhomogeneous in their processing, internal structure, properties, and performance. Their properties are therefore statistical rather than deterministic. These inhomogeneities manifest across multiple length and time scales, leading to variabilities, i.e. statistical distributions, that are necessary to accurately describe each stage in the process-structure-properties hierarchy, and are ultimately the primary source of uncertainty in performance of the material and component. When localized events are responsible for component failure, or when component dimensions are on the order of microstructural features, this uncertainty is particularly important. For ultra-high reliability applications, the uncertainty is compounded by a lack of data describing the extremely rare events. Hands-on testing alone cannot supply sufficient data for this purpose. To date, there is no robust or coherent method to quantify this uncertainty so that it can be used in a predictive manner at the component length scale. The research presented in this report begins to address this lack of capability through a systematic study of the effects of microstructure on the strain concentration at a hole. To achieve the strain concentration, small circular holes (approximately 100 {micro}m in diameter) were machined into brass tensile specimens using a femto-second laser. The brass was annealed at 450 C, 600 C, and 800 C to produce three hole-to-grain size ratios of approximately 7, 1, and 1/7. Electron backscatter diffraction experiments were used to guide the construction of digital microstructures for finite element simulations of uniaxial tension. Digital image correlation experiments were used to qualitatively validate the numerical simulations. The simulations were performed iteratively to generate statistics describing the distribution of plastic strain at the hole in varying microstructural environments. In both the experiments and simulations, the

  1. Content addressable memory project

    NASA Technical Reports Server (NTRS)

    Hall, Josh; Levy, Saul; Smith, D.; Wei, S.; Miyake, K.; Murdocca, M.

    1991-01-01

    The progress on the Rutgers CAM (Content Addressable Memory) Project is described. The overall design of the system is completed at the architectural level and described. The machine is composed of two kinds of cells: (1) the CAM cells which include both memory and processor, and support local processing within each cell; and (2) the tree cells, which have smaller instruction set, and provide global processing over the CAM cells. A parameterized design of the basic CAM cell is completed. Progress was made on the final specification of the CPS. The machine architecture was driven by the design of algorithms whose requirements are reflected in the resulted instruction set(s). A few of these algorithms are described.

  2. Estimating the magnitude of prediction uncertainties for the APLE model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, we conduct an uncertainty analysis for the Annual P ...

  3. Integrating uncertainties for climate change mitigation

    NASA Astrophysics Data System (ADS)

    Rogelj, Joeri; McCollum, David; Reisinger, Andy; Meinshausen, Malte; Riahi, Keywan

    2013-04-01

    The target of keeping global average temperature increase to below 2°C has emerged in the international climate debate more than a decade ago. In response, the scientific community has tried to estimate the costs of reaching such a target through modelling and scenario analysis. Producing such estimates remains a challenge, particularly because of relatively well-known, but ill-quantified uncertainties, and owing to limited integration of scientific knowledge across disciplines. The integrated assessment community, on one side, has extensively assessed the influence of technological and socio-economic uncertainties on low-carbon scenarios and associated costs. The climate modelling community, on the other side, has worked on achieving an increasingly better understanding of the geophysical response of the Earth system to emissions of greenhouse gases (GHG). This geophysical response remains a key uncertainty for the cost of mitigation scenarios but has only been integrated with assessments of other uncertainties in a rudimentary manner, i.e., for equilibrium conditions. To bridge this gap between the two research communities, we generate distributions of the costs associated with limiting transient global temperature increase to below specific temperature limits, taking into account uncertainties in multiple dimensions: geophysical, technological, social and political. In other words, uncertainties resulting from our incomplete knowledge about how the climate system precisely reacts to GHG emissions (geophysical uncertainties), about how society will develop (social uncertainties and choices), which technologies will be available (technological uncertainty and choices), when we choose to start acting globally on climate change (political choices), and how much money we are or are not willing to spend to achieve climate change mitigation. We find that political choices that delay mitigation have the largest effect on the cost-risk distribution, followed by

  4. Managing the Future: Public Policy, Scientific Uncertainty, and Global Warming.

    ERIC Educational Resources Information Center

    Jamieson, Dale

    Due to the injection of carbon dioxide and various other gasses into the atmosphere, the world of the 21st century may well have a climate that is beyond the parameters of human existence. Physical science produces information regarding the physical effects of increasing concentrations of "greenhouse" gasses. Once this information is…

  5. The challenges on uncertainty analysis for pebble bed HTGR

    SciTech Connect

    Hao, C.; Li, F.; Zhang, H.

    2012-07-01

    The uncertainty analysis is very popular and important, and many works have been done for Light Water Reactor (LWR), although the experience for the uncertainty analysis in High Temperature Gas cooled Reactor (HTGR) modeling is still in the primary stage. IAEA will launch a Coordination Research Project (CRP) on this topic soon. This paper addresses some challenges for the uncertainty analysis in HTGR modeling, based on the experience of OECD LWR Uncertainty Analysis in Modeling (UAM) activities, and taking into account the peculiarities of pebble bed HTGR designs. The main challenges for HTGR UAM are: the lack of experience, the totally different code packages, the coupling of power distribution, temperature distribution and burnup distribution through the temperature feedback and pebble flow. The most serious challenge is how to deal with the uncertainty in pebble flow, the uncertainty in pebble bed flow modeling, and their contribution to the uncertainty of maximum fuel temperature, which is the most interested parameter for the modular HTGR. (authors)

  6. Fragility, uncertainty, and healthcare.

    PubMed

    Rogers, Wendy A; Walker, Mary J

    2016-02-01

    Medicine seeks to overcome one of the most fundamental fragilities of being human, the fragility of good health. No matter how robust our current state of health, we are inevitably susceptible to future illness and disease, while current disease serves to remind us of various frailties inherent in the human condition. This article examines the relationship between fragility and uncertainty with regard to health, and argues that there are reasons to accept rather than deny at least some forms of uncertainty. In situations of current ill health, both patients and doctors seek to manage this fragility through diagnoses that explain suffering and provide some certainty about prognosis as well as treatment. However, both diagnosis and prognosis are inevitably uncertain to some degree, leading to questions about how much uncertainty health professionals should disclose, and how to manage when diagnosis is elusive, leaving patients in uncertainty. We argue that patients can benefit when they are able to acknowledge, and appropriately accept, some uncertainty. Healthy people may seek to protect the fragility of their good health by undertaking preventative measures including various tests and screenings. However, these attempts to secure oneself against the onset of biological fragility can cause harm by creating rather than eliminating uncertainty. Finally, we argue that there are good reasons for accepting the fragility of health, along with the associated uncertainties.

  7. Confronting Uncertainty in Wildlife Management: Performance of Grizzly Bear Management

    PubMed Central

    Artelle, Kyle A.; Anderson, Sean C.; Cooper, Andrew B.; Paquet, Paul C.; Reynolds, John D.; Darimont, Chris T.

    2013-01-01

    Scientific management of wildlife requires confronting the complexities of natural and social systems. Uncertainty poses a central problem. Whereas the importance of considering uncertainty has been widely discussed, studies of the effects of unaddressed uncertainty on real management systems have been rare. We examined the effects of outcome uncertainty and components of biological uncertainty on hunt management performance, illustrated with grizzly bears (Ursus arctos horribilis) in British Columbia, Canada. We found that both forms of uncertainty can have serious impacts on management performance. Outcome uncertainty alone – discrepancy between expected and realized mortality levels – led to excess mortality in 19% of cases (population-years) examined. Accounting for uncertainty around estimated biological parameters (i.e., biological uncertainty) revealed that excess mortality might have occurred in up to 70% of cases. We offer a general method for identifying targets for exploited species that incorporates uncertainty and maintains the probability of exceeding mortality limits below specified thresholds. Setting targets in our focal system using this method at thresholds of 25% and 5% probability of overmortality would require average target mortality reductions of 47% and 81%, respectively. Application of our transparent and generalizable framework to this or other systems could improve management performance in the presence of uncertainty. PMID:24223134

  8. Confronting uncertainty in wildlife management: performance of grizzly bear management.

    PubMed

    Artelle, Kyle A; Anderson, Sean C; Cooper, Andrew B; Paquet, Paul C; Reynolds, John D; Darimont, Chris T

    2013-01-01

    Scientific management of wildlife requires confronting the complexities of natural and social systems. Uncertainty poses a central problem. Whereas the importance of considering uncertainty has been widely discussed, studies of the effects of unaddressed uncertainty on real management systems have been rare. We examined the effects of outcome uncertainty and components of biological uncertainty on hunt management performance, illustrated with grizzly bears (Ursus arctos horribilis) in British Columbia, Canada. We found that both forms of uncertainty can have serious impacts on management performance. Outcome uncertainty alone--discrepancy between expected and realized mortality levels--led to excess mortality in 19% of cases (population-years) examined. Accounting for uncertainty around estimated biological parameters (i.e., biological uncertainty) revealed that excess mortality might have occurred in up to 70% of cases. We offer a general method for identifying targets for exploited species that incorporates uncertainty and maintains the probability of exceeding mortality limits below specified thresholds. Setting targets in our focal system using this method at thresholds of 25% and 5% probability of overmortality would require average target mortality reductions of 47% and 81%, respectively. Application of our transparent and generalizable framework to this or other systems could improve management performance in the presence of uncertainty.

  9. Uncertainty Quantification in Climate Modeling

    NASA Astrophysics Data System (ADS)

    Sargsyan, K.; Safta, C.; Berry, R.; Debusschere, B.; Najm, H.

    2011-12-01

    We address challenges that sensitivity analysis and uncertainty quantification methods face when dealing with complex computational models. In particular, climate models are computationally expensive and typically depend on a large number of input parameters. We consider the Community Land Model (CLM), which consists of a nested computational grid hierarchy designed to represent the spatial heterogeneity of the land surface. Each computational cell can be composed of multiple land types, and each land type can incorporate one or more sub-models describing the spatial and depth variability. Even for simulations at a regional scale, the computational cost of a single run is quite high and the number of parameters that control the model behavior is very large. Therefore, the parameter sensitivity analysis and uncertainty propagation face significant difficulties for climate models. This work employs several algorithmic avenues to address some of the challenges encountered by classical uncertainty quantification methodologies when dealing with expensive computational models, specifically focusing on the CLM as a primary application. First of all, since the available climate model predictions are extremely sparse due to the high computational cost of model runs, we adopt a Bayesian framework that effectively incorporates this lack-of-knowledge as a source of uncertainty, and produces robust predictions with quantified uncertainty even if the model runs are extremely sparse. In particular, we infer Polynomial Chaos spectral expansions that effectively encode the uncertain input-output relationship and allow efficient propagation of all sources of input uncertainties to outputs of interest. Secondly, the predictability analysis of climate models strongly suffers from the curse of dimensionality, i.e. the large number of input parameters. While single-parameter perturbation studies can be efficiently performed in a parallel fashion, the multivariate uncertainty analysis

  10. Assessing MODIS Macrophysical Cloud Property Uncertainties

    NASA Astrophysics Data System (ADS)

    Maddux, B. C.; Ackerman, S. A.; Frey, R.; Holz, R.

    2013-12-01

    Cloud, being multifarious and ephemeral, is difficult to observe and quantify in a systematic way. Even basic terminology used to describe cloud observations is fraught with ambiguity in the scientific literature. Any observational technique, method, or platform will contain inherent and unavoidable measurement uncertainties. Quantifying these uncertainties in cloud observations is a complex task that requires an understanding of all aspects of the measurement. We will use cloud observations obtained from the Moderate Resolution Imaging Spectroradiameter(MODIS) to obtain metrics of the uncertainty of its cloud observations. Our uncertainty analyses will contain two main components, 1) an attempt to create a bias or uncertainty with respect to active measurements from CALIPSO and 2) a relative uncertainty within the MODIS cloud climatologies themselves. Our method will link uncertainty to the physical observation and its environmental/scene characteristics. Our aim is to create statistical uncertainties that are based on the cloud observational values, satellite view geometry, surface type, etc, for cloud amount and cloud top pressure. The MODIS instruments on the NASA Terra and Aqua satellites provide observations over a broad spectral range (36 bands between 0.415 and 14.235 micron) and high spatial resolution (250 m for two bands, 500 m for five bands, 1000 m for 29 bands), which the MODIS cloud mask algorithm (MOD35) utilizes to provide clear/cloud determinations over a wide array of surface types, solar illuminations and view geometries. For this study we use the standard MODIS products, MOD03, MOD06 and MOD35, all of which were obtained from the NASA Level 1 and Atmosphere Archive and Distribution System.

  11. Assessing what to address in science communication

    PubMed Central

    Bruine de Bruin, Wändi; Bostrom, Ann

    2013-01-01

    As members of a democratic society, individuals face complex decisions about whether to support climate change mitigation, vaccinations, genetically modified food, nanotechnology, geoengineering, and so on. To inform people’s decisions and public debate, scientific experts at government agencies, nongovernmental organizations, and other organizations aim to provide understandable and scientifically accurate communication materials. Such communications aim to improve people’s understanding of the decision-relevant issues, and if needed, promote behavior change. Unfortunately, existing communications sometimes fail when scientific experts lack information about what people need to know to make more informed decisions or what wording people use to describe relevant concepts. We provide an introduction for scientific experts about how to use mental models research with intended audience members to inform their communication efforts. Specifically, we describe how to conduct interviews to characterize people’s decision-relevant beliefs or mental models of the topic under consideration, identify gaps and misconceptions in their knowledge, and reveal their preferred wording. We also describe methods for designing follow-up surveys with larger samples to examine the prevalence of beliefs as well as the relationships of beliefs with behaviors. Finally, we discuss how findings from these interviews and surveys can be used to design communications that effectively address gaps and misconceptions in people’s mental models in wording that they understand. We present applications to different scientific domains, showing that this approach leads to communications that improve recipients’ understanding and ability to make informed decisions. PMID:23942122

  12. Assessing what to address in science communication.

    PubMed

    Bruine de Bruin, Wändi; Bostrom, Ann

    2013-08-20

    As members of a democratic society, individuals face complex decisions about whether to support climate change mitigation, vaccinations, genetically modified food, nanotechnology, geoengineering, and so on. To inform people's decisions and public debate, scientific experts at government agencies, nongovernmental organizations, and other organizations aim to provide understandable and scientifically accurate communication materials. Such communications aim to improve people's understanding of the decision-relevant issues, and if needed, promote behavior change. Unfortunately, existing communications sometimes fail when scientific experts lack information about what people need to know to make more informed decisions or what wording people use to describe relevant concepts. We provide an introduction for scientific experts about how to use mental models research with intended audience members to inform their communication efforts. Specifically, we describe how to conduct interviews to characterize people's decision-relevant beliefs or mental models of the topic under consideration, identify gaps and misconceptions in their knowledge, and reveal their preferred wording. We also describe methods for designing follow-up surveys with larger samples to examine the prevalence of beliefs as well as the relationships of beliefs with behaviors. Finally, we discuss how findings from these interviews and surveys can be used to design communications that effectively address gaps and misconceptions in people's mental models in wording that they understand. We present applications to different scientific domains, showing that this approach leads to communications that improve recipients' understanding and ability to make informed decisions.

  13. Mutually Exclusive Uncertainty Relations

    NASA Astrophysics Data System (ADS)

    Xiao, Yunlong; Jing, Naihuan

    2016-11-01

    The uncertainty principle is one of the characteristic properties of quantum theory based on incompatibility. Apart from the incompatible relation of quantum states, mutually exclusiveness is another remarkable phenomenon in the information- theoretic foundation of quantum theory. We investigate the role of mutual exclusive physical states in the recent work of stronger uncertainty relations for all incompatible observables by Mccone and Pati and generalize the weighted uncertainty relation to the product form as well as their multi-observable analogues. The new bounds capture both incompatibility and mutually exclusiveness, and are tighter compared with the existing bounds.

  14. Mutually Exclusive Uncertainty Relations.

    PubMed

    Xiao, Yunlong; Jing, Naihuan

    2016-11-08

    The uncertainty principle is one of the characteristic properties of quantum theory based on incompatibility. Apart from the incompatible relation of quantum states, mutually exclusiveness is another remarkable phenomenon in the information- theoretic foundation of quantum theory. We investigate the role of mutual exclusive physical states in the recent work of stronger uncertainty relations for all incompatible observables by Mccone and Pati and generalize the weighted uncertainty relation to the product form as well as their multi-observable analogues. The new bounds capture both incompatibility and mutually exclusiveness, and are tighter compared with the existing bounds.

  15. Mutually Exclusive Uncertainty Relations

    PubMed Central

    Xiao, Yunlong; Jing, Naihuan

    2016-01-01

    The uncertainty principle is one of the characteristic properties of quantum theory based on incompatibility. Apart from the incompatible relation of quantum states, mutually exclusiveness is another remarkable phenomenon in the information- theoretic foundation of quantum theory. We investigate the role of mutual exclusive physical states in the recent work of stronger uncertainty relations for all incompatible observables by Mccone and Pati and generalize the weighted uncertainty relation to the product form as well as their multi-observable analogues. The new bounds capture both incompatibility and mutually exclusiveness, and are tighter compared with the existing bounds. PMID:27824161

  16. Optimal Universal Uncertainty Relations

    PubMed Central

    Li, Tao; Xiao, Yunlong; Ma, Teng; Fei, Shao-Ming; Jing, Naihuan; Li-Jost, Xianqing; Wang, Zhi-Xi

    2016-01-01

    We study universal uncertainty relations and present a method called joint probability distribution diagram to improve the majorization bounds constructed independently in [Phys. Rev. Lett. 111, 230401 (2013)] and [J. Phys. A. 46, 272002 (2013)]. The results give rise to state independent uncertainty relations satisfied by any nonnegative Schur-concave functions. On the other hand, a remarkable recent result of entropic uncertainty relation is the direct-sum majorization relation. In this paper, we illustrate our bounds by showing how they provide a complement to that in [Phys. Rev. A. 89, 052115 (2014)]. PMID:27775010

  17. [Keynote address: Climate change

    SciTech Connect

    Forrister, D.

    1994-12-31

    Broadly speaking, the climate issue is moving from talk to action both in the United States and internationally. While few nations have adopted strict controls or stiff new taxes, a number of them are developing action plans that are making clear their intention to ramp up activity between now and the year 2000... and beyond. There are sensible, economically efficient strategies to be undertaken in the near term that offer the possibility, in many countries, to avoid more draconian measures. These strategies are by-and-large the same measures that the National Academy of Sciences recommended in a 1991 report called, Policy Implications of Greenhouse Warming. The author thinks the Academy`s most important policy contribution was how it recommended the nations act in the face of uncertain science and high risks--that cost effective measures are adopted as cheap insurance... just as nations insure against other high risk, low certainty possibilities, like catastrophic health insurance, auto insurance, and fire insurance. This insurance theme is still right. First, the author addresses how the international climate change negotiations are beginning to produce insurance measures. Next, the author will discuss some of the key issues to watch in those negotiations that relate to longer-term insurance. And finally, the author will report on progress in the United States on the climate insurance plan--The President`s Climate Action Plan.

  18. Scientific Reporting: Raising the Standards

    ERIC Educational Resources Information Center

    McLeroy, Kenneth R.; Garney, Whitney; Mayo-Wilson, Evan; Grant, Sean

    2016-01-01

    This article is based on a presentation that was made at the 2014 annual meeting of the editorial board of "Health Education & Behavior." The article addresses critical issues related to standards of scientific reporting in journals, including concerns about external and internal validity and reporting bias. It reviews current…

  19. Uncertainty in chemistry.

    PubMed

    Menger, Fredric M

    2010-09-01

    It might come as a disappointment to some chemists, but just as there are uncertainties in physics and mathematics, there are some chemistry questions we may never know the answer to either, suggests Fredric M. Menger.

  20. 78 FR 68439 - FIFRA Scientific Advisory Panel; Notice of Rescheduled Public Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-11-14

    ...) to consider and review, Scientific Uncertainties Associated with Corn Rootworm Resistance Monitoring for Bt Corn Plant Incorporated Protectants (PIPs). The meeting was announced in the Federal...

  1. Conundrums with uncertainty factors.

    PubMed

    Cooke, Roger

    2010-03-01

    The practice of uncertainty factors as applied to noncancer endpoints in the IRIS database harkens back to traditional safety factors. In the era before risk quantification, these were used to build in a "margin of safety." As risk quantification takes hold, the safety factor methods yield to quantitative risk calculations to guarantee safety. Many authors believe that uncertainty factors can be given a probabilistic interpretation as ratios of response rates, and that the reference values computed according to the IRIS methodology can thus be converted to random variables whose distributions can be computed with Monte Carlo methods, based on the distributions of the uncertainty factors. Recent proposals from the National Research Council echo this view. Based on probabilistic arguments, several authors claim that the current practice of uncertainty factors is overprotective. When interpreted probabilistically, uncertainty factors entail very strong assumptions on the underlying response rates. For example, the factor for extrapolating from animal to human is the same whether the dosage is chronic or subchronic. Together with independence assumptions, these assumptions entail that the covariance matrix of the logged response rates is singular. In other words, the accumulated assumptions entail a log-linear dependence between the response rates. This in turn means that any uncertainty analysis based on these assumptions is ill-conditioned; it effectively computes uncertainty conditional on a set of zero probability. The practice of uncertainty factors is due for a thorough review. Two directions are briefly sketched, one based on standard regression models, and one based on nonparametric continuous Bayesian belief nets.

  2. Uncertainty Quantification in Climate Modeling and Projection

    SciTech Connect

    Qian, Yun; Jackson, Charles; Giorgi, Filippo; Booth, Ben; Duan, Qingyun; Forest, Chris; Higdon, Dave; Hou, Z. Jason; Huerta, Gabriel

    2016-05-01

    The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for

  3. Uncertainty in QSAR predictions.

    PubMed

    Sahlin, Ullrika

    2013-03-01

    It is relevant to consider uncertainty in individual predictions when quantitative structure-activity (or property) relationships (QSARs) are used to support decisions of high societal concern. Successful communication of uncertainty in the integration of QSARs in chemical safety assessment under the EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) system can be facilitated by a common understanding of how to define, characterise, assess and evaluate uncertainty in QSAR predictions. A QSAR prediction is, compared to experimental estimates, subject to added uncertainty that comes from the use of a model instead of empirically-based estimates. A framework is provided to aid the distinction between different types of uncertainty in a QSAR prediction: quantitative, i.e. for regressions related to the error in a prediction and characterised by a predictive distribution; and qualitative, by expressing our confidence in the model for predicting a particular compound based on a quantitative measure of predictive reliability. It is possible to assess a quantitative (i.e. probabilistic) predictive distribution, given the supervised learning algorithm, the underlying QSAR data, a probability model for uncertainty and a statistical principle for inference. The integration of QSARs into risk assessment may be facilitated by the inclusion of the assessment of predictive error and predictive reliability into the "unambiguous algorithm", as outlined in the second OECD principle.

  4. Science, Uncertainty, and Adaptive Management in Large River Restoration Programs: Trinity River example

    NASA Astrophysics Data System (ADS)

    McBain, S.

    2002-12-01

    Following construction of Trinity and Lewiston dams on the upper Trinity River in 1964, dam induced changes to streamflows and sediment regime had severely simplified channel morphology and aquatic habitat downstream of the dams. This habitat change, combined with blocked access to over 100 miles of salmon and steelhead habitat upstream of the dams, caused salmon and steelhead populations to quickly plummet. An instream flow study was initiated in 1984 to address the flow needs to restore the fishery, and this study relied on the Physical Habitat Simulation (PHABSIM) Model to quantify instream flow needs. In 1992, geomorphic and riparian studies were integrated into the instream flow study, with the overall study completed in 1999 (USFWS 1999). This 13-year process continued through three presidential administrations, several agency managers, and many turnovers of the agency technical staff responsible for conducting the study. This process culminated in 1996-1998 when a group of scientists were convened to integrate all the studies and data to produce the final instream flow study document. This 13-year, non-linear process, resulted in many uncertainties that could not be resolved in the short amount of time allowed for completing the instream flow study document. Shortly after completion of the instream flow study document, the Secretary of Interior issued a Record of Decision to implement the recommendations contained in the instream flow study document. The uncertainties encountered as the instream flow study report was prepared were highlighted in the report, and the Record of Decision initiated an Adaptive Environmental Assessment and Management program to address these existing uncertainties and improve future river management. There have been many lessons learned going through this process, and the presentation will summarize: 1)The progression of science used to develop the instream flow study report; 2)How the scientists preparing the report addressed

  5. I Am Sure There May Be a Planet There: Student articulation of uncertainty in argumentation tasks

    NASA Astrophysics Data System (ADS)

    Buck, Zoë E.; Lee, Hee-Sun; Flores, Joanna

    2014-09-01

    We investigated how students articulate uncertainty when they are engaged in structured scientific argumentation tasks where they generate, examine, and interpret data to determine the existence of exoplanets. In this study, 302 high school students completed 4 structured scientific arguments that followed a series of computer-model-based curriculum module activities simulating the radial velocity and/or the transit method. Structured scientific argumentation tasks involved claim, explanation, uncertainty rating, and uncertainty rationale. We explored (1) how students are articulating uncertainty within the various elements of the task and (2) the relationship between the way the task is presented and the way students are articulating uncertainty. We found that (1) while the majority of students did not express uncertainty in either explanation or uncertainty rationale, students who did express uncertainty in their explanations did so scientifically without being prompted explicitly, (2) students' uncertainty ratings and rationales revealed a mix of their personal confidence and uncertainty related to science, and (3) if a task presented noisy data, students were less likely to express uncertainty in their explanations.

  6. Uncertainty in quantum mechanics: faith or fantasy?

    PubMed

    Penrose, Roger

    2011-12-13

    The word 'uncertainty', in the context of quantum mechanics, usually evokes an impression of an essential unknowability of what might actually be going on at the quantum level of activity, as is made explicit in Heisenberg's uncertainty principle, and in the fact that the theory normally provides only probabilities for the results of quantum measurement. These issues limit our ultimate understanding of the behaviour of things, if we take quantum mechanics to represent an absolute truth. But they do not cause us to put that very 'truth' into question. This article addresses the issue of quantum 'uncertainty' from a different perspective, raising the question of whether this term might be applied to the theory itself, despite its unrefuted huge success over an enormously diverse range of observed phenomena. There are, indeed, seeming internal contradictions in the theory that lead us to infer that a total faith in it at all levels of scale leads us to almost fantastical implications.

  7. Model development and data uncertainty integration

    SciTech Connect

    Swinhoe, Martyn Thomas

    2015-12-02

    The effect of data uncertainties is discussed, with the epithermal neutron multiplicity counter as an illustrative example. Simulation using MCNP6, cross section perturbations and correlations are addressed, along with the effect of the 240Pu spontaneous fission neutron spectrum, the effect of P(ν) for 240Pu spontaneous fission, and the effect of spontaneous fission and (α,n) intensity. The effect of nuclear data is the product of the initial uncertainty and the sensitivity -- both need to be estimated. In conclusion, a multi-parameter variation method has been demonstrated, the most significant parameters are the basic emission rates of spontaneous fission and (α,n) processes, and uncertainties and important data depend on the analysis technique chosen.

  8. Interpreting uncertainty terms.

    PubMed

    Holtgraves, Thomas

    2014-08-01

    Uncertainty terms (e.g., some, possible, good, etc.) are words that do not have a fixed referent and hence are relatively ambiguous. A model is proposed that specifies how, from the hearer's perspective, recognition of facework as a potential motive for the use of an uncertainty term results in a calibration of the intended meaning of that term. Four experiments are reported that examine the impact of face threat, and the variables that affect it (e.g., power), on the manner in which a variety of uncertainty terms (probability terms, quantifiers, frequency terms, etc.) are interpreted. Overall, the results demonstrate that increased face threat in a situation will result in a more negative interpretation of an utterance containing an uncertainty term. That the interpretation of so many different types of uncertainty terms is affected in the same way suggests the operation of a fundamental principle of language use, one with important implications for the communication of risk, subjective experience, and so on.

  9. European Scientific Notes. Volume 36, Number 4,

    DTIC Science & Technology

    1982-04-30

    primarily for the information of L ’ S. Government scientific personnel and contractors. It i-, not coli- c sidered part of the scientific literature...Stjbtiti.) S YEO EOT&PRO OEE EUROPEAN SCIENTIFIC NOTES April_____________ S. PERFORMING ORG. REPORT NUMBER 7. AUTHOR(*) S. CONTRACT OR GRANT NUMBER(#) 9... PERFORMING ORGANI1ZATION NAME AND ADDRESS 10, PROGRAM ELEMENT PROJECT, TASK( AREA & WORK UNIT NUMBERS US OFFICE OF NAVAL RESEARCH BRANCH OFFICE

  10. [Transgenic products. A scientific-production evaluation of possible food (in)security].

    PubMed

    Camara, Maria Clara Coelho; Marinho, Carmem L C; Guilam, Maria Cristina Rodrigues; Nodari, Rubens Onofre

    2009-01-01

    Based on a bibliographic review, the article identifies and offers a critical analysis of scientific production by the public health field in Brazil on genetically modified organisms and food (in)security. Of the 716 articles found on the portals of the Scientific Electronic Library Online (SciELO) and the Coordinating Agency for the Development of Higher Education (Capes), only 8 address the food security of transgenic products, primarily in terms of risk exposure and the uncertainties about how these products impact health and the environment. The main conclusion involves the fact that the eight analyzed articles do not speak to the question of the security but rather the insecurity of genetically modified foods.

  11. A review of approaches for communicating uncertainty in radioactive waste disposal programmes

    NASA Astrophysics Data System (ADS)

    McEvoy, Fiona; West, Julie; Bloodworth, Andrew

    2014-05-01

    The technical safety case for a geological repository is based in part on assessments of long-term future behaviour. Technical specialists are required to provide evidence to the greatest extent possible that the predictions are sufficiently reliable for the purpose of making the safety case. This process involves comparison of modelling results with laboratory and field results and with observations on natural and man-made analogue systems. A collection of arguments and evidence are required to help establish the basis for the safety of the repository, as well as to help reduce uncertainty and develop confidence in the analyses themselves. The safety case prepared for a proposed repository must be understood by regulators responsible for scrutinising and judging its acceptability. For the general public, however, it is difficult to make all of the arguments sufficiently transparent and understandable to ensure they share the same level of confidence as the technical specialists. A large body of qualified knowledge resides in the worldwide radioactive waste technical community. This knowledge should provide a firm scientific basis on which the long-term performance and safety of a geological repository can be discussed with confidence so informed decisions can be made. Despite this many countries around the world continue to face difficulties with implementing programmes for the deep geological disposal of radioactive waste. Geology, and effective communication of geological knowledge and uncertainty, are essential parts of the 'tool kit' needed to allow meaningful communication and engagement with the public. These tools can be used to build and maintain public confidence at each step in the process. The search for a geological disposal site is complex, with many stages. At each stage, geological uncertainty will inevitable exist as we will never know everything about the sub-surface unless it is mined out at which point it is of no use as a repository! What level

  12. Uncertainty in ecological risk assessment: A statistician`s view

    SciTech Connect

    Smith, E.P.

    1995-12-31

    Uncertainty is a topic that has different meanings to researchers, modelers, managers and policy makers. The perspective of this presentation will be on the modeling view of uncertainty and its quantitative assessment. The goal is to provide some insight into how a statistician visualizes and addresses the issue of uncertainty in ecological risk assessment problems. In ecological risk assessment, uncertainty arises from many sources and is of different type depending on what is studies, where it is studied and how it is studied. Some major sources and their impact are described. A variety of quantitative approaches to modeling uncertainty are characterized and a general taxonomy given. Examples of risk assessments of lake acidification, power plant impact assessment and the setting of standards for chemicals will be used discuss approaches to quantitative assessment of uncertainty and some of the potential difficulties.

  13. Measurement uncertainty relations

    SciTech Connect

    Busch, Paul; Lahti, Pekka; Werner, Reinhard F.

    2014-04-15

    Measurement uncertainty relations are quantitative bounds on the errors in an approximate joint measurement of two observables. They can be seen as a generalization of the error/disturbance tradeoff first discussed heuristically by Heisenberg. Here we prove such relations for the case of two canonically conjugate observables like position and momentum, and establish a close connection with the more familiar preparation uncertainty relations constraining the sharpness of the distributions of the two observables in the same state. Both sets of relations are generalized to means of order α rather than the usual quadratic means, and we show that the optimal constants are the same for preparation and for measurement uncertainty. The constants are determined numerically and compared with some bounds in the literature. In both cases, the near-saturation of the inequalities entails that the state (resp. observable) is uniformly close to a minimizing one.

  14. SU(2) uncertainty limits

    NASA Astrophysics Data System (ADS)

    Shabbir, Saroosh; Björk, Gunnar

    2016-05-01

    Although progress has been made recently in defining nontrivial uncertainty limits for the SU(2) group, a description of the intermediate states bound by these limits remains lacking. In this paper we enumerate possible uncertainty relations for the SU(2) group that involve all three observables and that are, moreover, invariant under SU(2) transformations. We demonstrate that these relations however, even taken as a group, do not provide sharp, saturable bounds. To find sharp bounds, we systematically calculate the variance of the SU(2) operators for all pure states belonging to the N =2 and N =3 polarization excitation manifold (corresponding to spin 1 and spin 3/2). Lastly, and perhaps counter to expectation, we note that even pure states can reach the maximum uncertainty limit.

  15. The Reach Address Database (RAD)

    EPA Pesticide Factsheets

    The Reach Address Database (RAD) stores reach address information for each Water Program feature that has been linked to the underlying surface water features (streams, lakes, etc) in the National Hydrology Database (NHD) Plus dataset.

  16. Uncertainty and Dimensional Calibrations

    PubMed Central

    Doiron, Ted; Stoup, John

    1997-01-01

    The calculation of uncertainty for a measurement is an effort to set reasonable bounds for the measurement result according to standardized rules. Since every measurement produces only an estimate of the answer, the primary requisite of an uncertainty statement is to inform the reader of how sure the writer is that the answer is in a certain range. This report explains how we have implemented these rules for dimensional calibrations of nine different types of gages: gage blocks, gage wires, ring gages, gage balls, roundness standards, optical flats indexing tables, angle blocks, and sieves. PMID:27805114

  17. A Certain Uncertainty

    NASA Astrophysics Data System (ADS)

    Silverman, Mark P.

    2014-07-01

    1. Tools of the trade; 2. The 'fundamental problem' of a practical physicist; 3. Mother of all randomness I: the random disintegration of matter; 4. Mother of all randomness II: the random creation of light; 5. A certain uncertainty; 6. Doing the numbers: nuclear physics and the stock market; 7. On target: uncertainties of projectile flight; 8. The guesses of groups; 9. The random flow of energy I: power to the people; 10. The random flow of energy II: warning from the weather underground; Index.

  18. The legacy of uncertainty

    NASA Technical Reports Server (NTRS)

    Brown, Laurie M.

    1993-01-01

    An historical account is given of the circumstances whereby the uncertainty relations were introduced into physics by Heisenberg. The criticisms of QED on measurement-theoretical grounds by Landau and Peierls are then discussed, as well as the response to them by Bohr and Rosenfeld. Finally, some examples are given of how the new freedom to advance radical proposals, in part the result of the revolution brought about by 'uncertainty,' was implemented in dealing with the new phenomena encountered in elementary particle physics in the 1930's.

  19. Uncertainty and Dimensional Calibrations.

    PubMed

    Doiron, Ted; Stoup, John

    1997-01-01

    The calculation of uncertainty for a measurement is an effort to set reasonable bounds for the measurement result according to standardized rules. Since every measurement produces only an estimate of the answer, the primary requisite of an uncertainty statement is to inform the reader of how sure the writer is that the answer is in a certain range. This report explains how we have implemented these rules for dimensional calibrations of nine different types of gages: gage blocks, gage wires, ring gages, gage balls, roundness standards, optical flats indexing tables, angle blocks, and sieves.

  20. Orbital State Uncertainty Realism

    NASA Astrophysics Data System (ADS)

    Horwood, J.; Poore, A. B.

    2012-09-01

    Fundamental to the success of the space situational awareness (SSA) mission is the rigorous inclusion of uncertainty in the space surveillance network. The *proper characterization of uncertainty* in the orbital state of a space object is a common requirement to many SSA functions including tracking and data association, resolution of uncorrelated tracks (UCTs), conjunction analysis and probability of collision, sensor resource management, and anomaly detection. While tracking environments, such as air and missile defense, make extensive use of Gaussian and local linearity assumptions within algorithms for uncertainty management, space surveillance is inherently different due to long time gaps between updates, high misdetection rates, nonlinear and non-conservative dynamics, and non-Gaussian phenomena. The latter implies that "covariance realism" is not always sufficient. SSA also requires "uncertainty realism"; the proper characterization of both the state and covariance and all non-zero higher-order cumulants. In other words, a proper characterization of a space object's full state *probability density function (PDF)* is required. In order to provide a more statistically rigorous treatment of uncertainty in the space surveillance tracking environment and to better support the aforementioned SSA functions, a new class of multivariate PDFs are formulated which more accurately characterize the uncertainty of a space object's state or orbit. The new distribution contains a parameter set controlling the higher-order cumulants which gives the level sets a distinctive "banana" or "boomerang" shape and degenerates to a Gaussian in a suitable limit. Using the new class of PDFs within the general Bayesian nonlinear filter, the resulting filter prediction step (i.e., uncertainty propagation) is shown to have the *same computational cost as the traditional unscented Kalman filter* with the former able to maintain a proper characterization of the uncertainty for up to *ten

  1. Weighted Uncertainty Relations

    PubMed Central

    Xiao, Yunlong; Jing, Naihuan; Li-Jost, Xianqing; Fei, Shao-Ming

    2016-01-01

    Recently, Maccone and Pati have given two stronger uncertainty relations based on the sum of variances and one of them is nontrivial when the quantum state is not an eigenstate of the sum of the observables. We derive a family of weighted uncertainty relations to provide an optimal lower bound for all situations and remove the restriction on the quantum state. Generalization to multi-observable cases is also given and an optimal lower bound for the weighted sum of the variances is obtained in general quantum situation. PMID:26984295

  2. Demonstrating the value of medicines: evolution of value equation and stakeholder perception of uncertainties

    PubMed Central

    Narayanan, Siva

    2016-01-01

    It is important to evaluate how the value of medicine is assessed, as it may have important implications for health technology and reimbursement assessments. The value equation could comprise ‘incremental benefit/outcome’ (relative results of care in terms of patient health, comparing the innovation to best available alternative(s)) in the numerator and ‘cost’ (relative costs involved in the full cycle of care (or a defined period) for the patient's medical condition, incorporating the relevant cost-offsets due to displacement of best available alternative(s)) in the denominator. This ‘relative value’ combined with the overall net budget impact (of including the drug in the formulary or reimbursed drug list) at the concerned population level in the given institution/region/country may better inform the usefulness of the new therapeutic option to the healthcare system. As product value messages are created, anticipating external stakeholder questions and information needs, including addressing three main categories of ‘uncertainties’, namely the scientific uncertainties, usage uncertainties, and financial uncertainties, could facilitate demonstration of optimal product value and help informed decision-making to benefit all stakeholders involved in the process. PMID:27489585

  3. ENHANCED UNCERTAINTY ANALYSIS FOR SRS COMPOSITE ANALYSIS

    SciTech Connect

    Smith, F.; Phifer, M.

    2011-06-30

    sand and clay), (b) Dose Parameters (34 parameters), (c) Material Properties (20 parameters), (d) Surface Water Flows (6 parameters), and (e) Vadose and Aquifer Flow (4 parameters). Results provided an assessment of which group of parameters is most significant in the dose uncertainty. It was found that K{sub d} and the vadose/aquifer flow parameters, both of which impact transport timing, had the greatest impact on dose uncertainty. Dose parameters had an intermediate level of impact while material properties and surface water flows had little impact on dose uncertainty. Results of the importance analysis are discussed further in Section 7 of this report. The objectives of this work were to address comments received during the CA review on the uncertainty analysis and to demonstrate an improved methodology for CA uncertainty calculations as part of CA maintenance. This report partially addresses the LFRG Review Team issue of producing an enhanced CA sensitivity and uncertainty analysis. This is described in Table 1-1 which provides specific responses to pertinent CA maintenance items extracted from Section 11 of the SRS CA (2009). As noted above, the original uncertainty analysis looked at each POA separately and only included the effects from at most five sources giving the highest peak doses at each POA. Only 17 of the 152 CA sources were used in the original uncertainty analysis and the simulation time was reduced from 10,000 to 2,000 years. A major constraint on the original uncertainty analysis was the limitation of only being able to use at most four distributed processes. This work expanded the analysis to 10,000 years using 39 of the CA sources, included cumulative dose effects at downstream POAs, with more realizations (1,000) and finer time steps. This was accomplished by using the GoldSim DP-Plus module and the 36 processors available on a new windows cluster. The last part of the work looked at the contribution to overall uncertainty from the main

  4. Uncertainties in the North Korean Nuclear Threat

    DTIC Science & Technology

    2010-01-01

    providing objective analysis and effective solutions that address the challenges facing the public and private sectors around the world . RAND’s...stigmatize Korean goods, further complicating problems for the Korean economy. And economic disruption can ripple through an economy in devastating ways...the outside world . 1 “N. Korean Poster Seems to Confi rm Succession,” 2009. 4 Uncertainties in the North Korean Nuclear Threat NK Nuclear

  5. Optimal test selection for prediction uncertainty reduction

    DOE PAGES

    Mullins, Joshua; Mahadevan, Sankaran; Urbina, Angel

    2016-12-02

    Economic factors and experimental limitations often lead to sparse and/or imprecise data used for the calibration and validation of computational models. This paper addresses resource allocation for calibration and validation experiments, in order to maximize their effectiveness within given resource constraints. When observation data are used for model calibration, the quality of the inferred parameter descriptions is directly affected by the quality and quantity of the data. This paper characterizes parameter uncertainty within a probabilistic framework, which enables the uncertainty to be systematically reduced with additional data. The validation assessment is also uncertain in the presence of sparse and imprecisemore » data; therefore, this paper proposes an approach for quantifying the resulting validation uncertainty. Since calibration and validation uncertainty affect the prediction of interest, the proposed framework explores the decision of cost versus importance of data in terms of the impact on the prediction uncertainty. Often, calibration and validation tests may be performed for different input scenarios, and this paper shows how the calibration and validation results from different conditions may be integrated into the prediction. Then, a constrained discrete optimization formulation that selects the number of tests of each type (calibration or validation at given input conditions) is proposed. Furthermore, the proposed test selection methodology is demonstrated on a microelectromechanical system (MEMS) example.« less

  6. Optimal test selection for prediction uncertainty reduction

    SciTech Connect

    Mullins, Joshua; Mahadevan, Sankaran; Urbina, Angel

    2016-12-02

    Economic factors and experimental limitations often lead to sparse and/or imprecise data used for the calibration and validation of computational models. This paper addresses resource allocation for calibration and validation experiments, in order to maximize their effectiveness within given resource constraints. When observation data are used for model calibration, the quality of the inferred parameter descriptions is directly affected by the quality and quantity of the data. This paper characterizes parameter uncertainty within a probabilistic framework, which enables the uncertainty to be systematically reduced with additional data. The validation assessment is also uncertain in the presence of sparse and imprecise data; therefore, this paper proposes an approach for quantifying the resulting validation uncertainty. Since calibration and validation uncertainty affect the prediction of interest, the proposed framework explores the decision of cost versus importance of data in terms of the impact on the prediction uncertainty. Often, calibration and validation tests may be performed for different input scenarios, and this paper shows how the calibration and validation results from different conditions may be integrated into the prediction. Then, a constrained discrete optimization formulation that selects the number of tests of each type (calibration or validation at given input conditions) is proposed. Furthermore, the proposed test selection methodology is demonstrated on a microelectromechanical system (MEMS) example.

  7. Uncertainty in NIST Force Measurements.

    PubMed

    Bartel, Tom

    2005-01-01

    This paper focuses upon the uncertainty of force calibration measurements at the National Institute of Standards and Technology (NIST). The uncertainty of the realization of force for the national deadweight force standards at NIST is discussed, as well as the uncertainties associated with NIST's voltage-ratio measuring instruments and with the characteristics of transducers being calibrated. The combined uncertainty is related to the uncertainty of dissemination for force transfer standards sent to NIST for calibration.

  8. An uncertainty inventory demonstration - a primary step in uncertainty quantification

    SciTech Connect

    Langenbrunner, James R.; Booker, Jane M; Hemez, Francois M; Salazar, Issac F; Ross, Timothy J

    2009-01-01

    Tools, methods, and theories for assessing and quantifying uncertainties vary by application. Uncertainty quantification tasks have unique desiderata and circumstances. To realistically assess uncertainty requires the engineer/scientist to specify mathematical models, the physical phenomena of interest, and the theory or framework for assessments. For example, Probabilistic Risk Assessment (PRA) specifically identifies uncertainties using probability theory, and therefore, PRA's lack formal procedures for quantifying uncertainties that are not probabilistic. The Phenomena Identification and Ranking Technique (PIRT) proceeds by ranking phenomena using scoring criteria that results in linguistic descriptors, such as importance ranked with words, 'High/Medium/Low.' The use of words allows PIRT to be flexible, but the analysis may then be difficult to combine with other uncertainty theories. We propose that a necessary step for the development of a procedure or protocol for uncertainty quantification (UQ) is the application of an Uncertainty Inventory. An Uncertainty Inventory should be considered and performed in the earliest stages of UQ.

  9. Uncertainties in successive measurements

    NASA Astrophysics Data System (ADS)

    Distler, Jacques; Paban, Sonia

    2013-06-01

    When you measure an observable, A, in quantum mechanics, the state of the system changes. This, in turn, affects the quantum-mechanical uncertainty in some noncommuting observable, B. The standard uncertainty relation puts a lower bound on the uncertainty of B in the initial state. What is relevant for a subsequent measurement of B, however, is the uncertainty of B in the postmeasurement state. We re-examine this problem, both in the case where A has a pure point spectrum and in the case where A has a continuous spectrum. In the latter case, the need to include a finite detector resolution, as part of what it means to measure such an observable, has dramatic implications for the result of successive measurements. Ozawa, [Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.67.042105 67, 042105 (2003)] proposed an inequality satisfied in the case of successive measurements. Among our results, we show that his inequality is ineffective (can never come close to being saturated). For the cases of interest, we compute a sharper lower bound.

  10. Uncertainties in repository modeling

    SciTech Connect

    Wilson, J.R.

    1996-12-31

    The distant future is ver difficult to predict. Unfortunately, our regulators are being enchouraged to extend ther regulatory period form the standard 10,000 years to 1 million years. Such overconfidence is not justified due to uncertainties in dating, calibration, and modeling.

  11. Uncertainty in Computational Aerodynamics

    NASA Technical Reports Server (NTRS)

    Luckring, J. M.; Hemsch, M. J.; Morrison, J. H.

    2003-01-01

    An approach is presented to treat computational aerodynamics as a process, subject to the fundamental quality assurance principles of process control and process improvement. We consider several aspects affecting uncertainty for the computational aerodynamic process and present a set of stages to determine the level of management required to meet risk assumptions desired by the customer of the predictions.

  12. Uncertainties in risk assessment at USDOE facilities

    SciTech Connect

    Hamilton, L.D.; Holtzman, S.; Meinhold, A.F.; Morris, S.C.; Rowe, M.D.

    1994-01-01

    The United States Department of Energy (USDOE) has embarked on an ambitious program to remediate environmental contamination at its facilities. Decisions concerning cleanup goals, choices among cleanup technologies, and funding prioritization should be largely risk-based. Risk assessments will be used more extensively by the USDOE in the future. USDOE needs to develop and refine risk assessment methods and fund research to reduce major sources of uncertainty in risk assessments at USDOE facilities. The terms{open_quote} risk assessment{close_quote} and{open_quote} risk management{close_quote} are frequently confused. The National Research Council (1983) and the United States Environmental Protection Agency (USEPA, 1991a) described risk assessment as a scientific process that contributes to risk management. Risk assessment is the process of collecting, analyzing and integrating data and information to identify hazards, assess exposures and dose responses, and characterize risks. Risk characterization must include a clear presentation of {open_quotes}... the most significant data and uncertainties...{close_quotes} in an assessment. Significant data and uncertainties are {open_quotes}...those that define and explain the main risk conclusions{close_quotes}. Risk management integrates risk assessment information with other considerations, such as risk perceptions, socioeconomic and political factors, and statutes, to make and justify decisions. Risk assessments, as scientific processes, should be made independently of the other aspects of risk management (USEPA, 1991a), but current methods for assessing health risks are based on conservative regulatory principles, causing unnecessary public concern and misallocation of funds for remediation.

  13. Cloud Feedbacks on Climate: A Challenging Scientific Problem

    SciTech Connect

    Norris, Joel

    2010-05-10

    One reason it has been difficult to develop suitable social and economic policies to address global climate change is that projected global warming during the coming century has a large uncertainty range. The primary physical cause of this large uncertainty range is lack of understanding of the magnitude and even sign of cloud feedbacks on the climate system. If Earth's cloudiness responded to global warming by reflecting more solar radiation back to space or allowing more terrestrial radiation to be emitted to space, this would mitigate the warming produced by increased anthropogenic greenhouse gases. Contrastingly, a cloud response that reduced solar reflection or terrestrial emission would exacerbate anthropogenic greenhouse warming. It is likely that a mixture of responses will occur depending on cloud type and meteorological regime, and at present, we do not know what the net effect will be. This presentation will explain why cloud feedbacks have been a challenging scientific problem from the perspective of theory, modeling, and observations. Recent research results on observed multidecadal cloud-atmosphere-ocean variability over the Pacific Ocean will also be shown, along with suggestions for future research.

  14. Cloud Feedbacks on Climate: A Challenging Scientific Problem

    ScienceCinema

    Norris, Joe [Scripps Institution of Oceanography, University of California, San Diego, California, USA

    2016-07-12

    One reason it has been difficult to develop suitable social and economic policies to address global climate change is that projected global warming during the coming century has a large uncertainty range. The primary physical cause of this large uncertainty range is lack of understanding of the magnitude and even sign of cloud feedbacks on the climate system. If Earth's cloudiness responded to global warming by reflecting more solar radiation back to space or allowing more terrestrial radiation to be emitted to space, this would mitigate the warming produced by increased anthropogenic greenhouse gases. Contrastingly, a cloud response that reduced solar reflection or terrestrial emission would exacerbate anthropogenic greenhouse warming. It is likely that a mixture of responses will occur depending on cloud type and meteorological regime, and at present, we do not know what the net effect will be. This presentation will explain why cloud feedbacks have been a challenging scientific problem from the perspective of theory, modeling, and observations. Recent research results on observed multidecadal cloud-atmosphere-ocean variability over the Pacific Ocean will also be shown, along with suggestions for future research.

  15. Presentation of uncertainties on web platforms for climate change information

    NASA Astrophysics Data System (ADS)

    Nocke, Thomas; Wrobel, Markus; Reusser, Dominik

    2014-05-01

    Climate research has a long tradition, however there is still uncertainty about the specific effects of climate change. One of the key tasks is - beyond discussing climate change and its impacts in specialist groups - to present these to a wider audience. In that respect, decision-makers in the public sector as well as directly affected professional groups require to obtain easy-to-understand information. These groups are not made up of specialist scientists. This gives rise to the challenge that the scientific information must be presented such that it is commonly understood, however, the complexity of the science behind needs to be incorporated. In particular, this requires the explicit representation of spatial and temporal uncertainty information to lay people. Within this talk/poster we survey how climate change and climate impact uncertainty information is presented on various climate service web-based platforms. We outline how the specifics of this medium make it challenging to find adequate and readable representations of uncertainties. First, we introduce a multi-step approach in communicating the uncertainty basing on a typology of uncertainty distinguishing between epistemic, natural stochastic, and human reflexive uncertainty. Then, we compare existing concepts and representations for uncertainty communication with current practices on web-based platforms, including own solutions within our web platforms ClimateImpactsOnline and ci:grasp. Finally, we review surveys on how spatial uncertainty visualization techniques are conceived by untrainded users.

  16. Strategy under uncertainty.

    PubMed

    Courtney, H; Kirkland, J; Viguerie, P

    1997-01-01

    At the heart of the traditional approach to strategy lies the assumption that by applying a set of powerful analytic tools, executives can predict the future of any business accurately enough to allow them to choose a clear strategic direction. But what happens when the environment is so uncertain that no amount of analysis will allow us to predict the future? What makes for a good strategy in highly uncertain business environments? The authors, consultants at McKinsey & Company, argue that uncertainty requires a new way of thinking about strategy. All too often, they say, executives take a binary view: either they underestimate uncertainty to come up with the forecasts required by their companies' planning or capital-budging processes, or they overestimate it, abandon all analysis, and go with their gut instinct. The authors outline a new approach that begins by making a crucial distinction among four discrete levels of uncertainty that any company might face. They then explain how a set of generic strategies--shaping the market, adapting to it, or reserving the right to play at a later time--can be used in each of the four levels. And they illustrate how these strategies can be implemented through a combination of three basic types of actions: big bets, options, and no-regrets moves. The framework can help managers determine which analytic tools can inform decision making under uncertainty--and which cannot. At a broader level, it offers executives a discipline for thinking rigorously and systematically about uncertainty and its implications for strategy.

  17. Uncertainty law in ambient modal identification-Part I: Theory

    NASA Astrophysics Data System (ADS)

    Au, Siu-Kui

    2014-10-01

    Ambient vibration test has gained increasing popularity in practice as it provides an economical means for modal identification without artificial loading. Since the signal-to-noise ratio cannot be directly controlled, the uncertainty associated with the identified modal parameters is a primary concern. From a scientific point of view, it is of interest to know on what factors the uncertainty depends and what the relationship is. For planning or specification purposes, it is desirable to have an assessment of the test configuration required to achieve a specified accuracy in the modal parameters. For example, what is the minimum data duration to achieve a 30% coefficient of variation (c.o.v.) in the damping ratio? To address these questions, this work investigates the leading order behavior of the ‘posterior uncertainties’ (i.e., given data) of the modal parameters in a Bayesian identification framework. In the context of well-separated modes, small damping and sufficient data, it is shown rigorously that, among other results, the posterior c.o.v. of the natural frequency and damping ratio are asymptotically equal to ( and 1/(2, respectively; where ζ is the damping ratio; Nc is the data length as a multiple of the natural period; Bf and Bζ are data length factors that depend only on the bandwidth utilized for identification, for which explicit expressions have been derived. As the Bayesian approach allows full use of information contained in the data, the results are fundamental characteristics of the ambient modal identification problem. This paper develops the main theory. The companion paper investigates the implication of the results and verification with field test data.

  18. An Integrated Bayesian Uncertainty Estimator: fusion of Input, Parameter and Model Structural Uncertainty Estimation in Hydrologic Prediction System

    NASA Astrophysics Data System (ADS)

    Ajami, N. K.; Duan, Q.; Sorooshian, S.

    2005-12-01

    To-date single conceptual hydrologic models often applied to interpret physical processes within a watershed. Nevertheless hydrologic models regardless of their sophistication and complexity are simplified representation of the complex, spatially distributed and highly nonlinear real world system. Consequently their hydrologic predictions contain considerable uncertainty from different sources including: hydrometeorological forcing inputs, boundary/initial conditions, model structure, model parameters which need to be accounted for. Thus far the effort has gone to address these sources of uncertainty explicitly, making an implicit assumption that uncertainties from different sources are additive. Nevertheless because of the nonlinear nature of the hydrologic systems, it is not feasible to account for these uncertainties independently. Here we present the Integrated Bayesian Uncertainty Estimator (IBUNE) which accounts for total uncertainties from all major sources: inputs forcing, model structure, model parameters. This algorithm explores multi-model framework to tackle model structural uncertainty while using the Bayesian rules to estimate parameter and input uncertainty within individual models. Three hydrologic models including SACramento Soil Moisture Accounting (SAC-SMA) model, Hydrologic model (HYMOD) and Simple Water Balance (SWB) model were considered within IBUNE framework for this study. The results which are presented for the Leaf River Basin, MS, indicates that IBUNE gives a better quantification of uncertainty through hydrological modeling processes, therefore provide more reliable and less bias prediction with realistic uncertainty boundaries.

  19. Nature of Science, Scientific Inquiry, and Socio-Scientific Issues Arising from Genetics: A Pathway to Developing a Scientifically Literate Citizenry

    ERIC Educational Resources Information Center

    Lederman, Norman G.; Antink, Allison; Bartos, Stephen

    2014-01-01

    The primary focus of this article is to illustrate how teachers can use contemporary socio-scientific issues to teach students about nature of scientific knowledge as well as address the science subject matter embedded in the issues. The article provides an initial discussion about the various aspects of nature of scientific knowledge that are…

  20. Uncertainty As a Trigger for a Paradigm Change in Science Communication

    NASA Astrophysics Data System (ADS)

    Schneider, S.

    2014-12-01

    Over the last decade, the need to communicate uncertainty increased. Climate sciences and environmental sciences have faced massive propaganda campaigns by global industry and astroturf organizations. These organizations use the deep societal mistrust in uncertainty to point out alleged unethical and intentional delusion of decision makers and the public by scientists and their consultatory function. Scientists, who openly communicate uncertainty of climate model calculations, earthquake occurrence frequencies, or possible side effects of genetic manipulated semen have to face massive campaigns against their research, and sometimes against their person and live as well. Hence, new strategies to communicate uncertainty have to face the societal roots of the misunderstanding of the concept of uncertainty itself. Evolutionary biology has shown, that human mind is well suited for practical decision making by its sensory structures. Therefore, many of the irrational concepts about uncertainty are mitigated if data is presented in formats the brain is adapted to understand. At the end, the impact of uncertainty to the decision-making process is finally dominantly driven by preconceptions about terms such as uncertainty, vagueness or probabilities. Parallel to the increasing role of scientific uncertainty in strategic communication, science communicators for example at the Research and Development Program GEOTECHNOLOGIEN developed a number of techniques to master the challenge of putting uncertainty in the focus. By raising the awareness of scientific uncertainty as a driving force for scientific development and evolution, the public perspective on uncertainty is changing. While first steps to implement this process are under way, the value of uncertainty still is underestimated in the public and in politics. Therefore, science communicators are in need for new and innovative ways to talk about scientific uncertainty.

  1. Probabilistic numerics and uncertainty in computations

    PubMed Central

    Hennig, Philipp; Osborne, Michael A.; Girolami, Mark

    2015-01-01

    We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations. PMID:26346321

  2. Probabilistic numerics and uncertainty in computations.

    PubMed

    Hennig, Philipp; Osborne, Michael A; Girolami, Mark

    2015-07-08

    We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.

  3. On the Directional Dependence and Null Space Freedom in Uncertainty Bound Identification

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

    In previous work, the determination of uncertainty models via minimum norm model validation is based on a single set of input and output measurement data. Since uncertainty bounds at each frequency is directionally dependent for multivariable systems, this will lead to optimistic uncertainty levels. In addition, the design freedom in the uncertainty model has not been utilized to further reduce uncertainty levels. The above issues are addressed by formulating a min- max problem. An analytical solution to the min-max problem is given to within a generalized eigenvalue problem, thus avoiding a direct numerical approach. This result will lead to less conservative and more realistic uncertainty models for use in robust control.

  4. Arctic health policy: contribution of scientific data.

    PubMed

    Berner, James E; Gilman, Andrew

    2003-08-01

    In Western Hemisphere arctic regions, scientific findings in humans, wildlife, and the environment have resulted in major governmental policy formulations. Government policy resulted in establishment of an effective international organization to address scientifically identified problems, including health disparities in arctic indigenous populations. Western scientific data and indigenous knowledge from initial international programs led to international agreements restricting certain persistent organic pollutants. In recent years, scientific data, and indigenous traditional knowledge, have resulted in governmental policy in the United States, Canada, and Nordic countries that includes the full participation of indigenous residents in defining research agendas, interpreting data, communicating information, and local community policy formulation.

  5. CONTENT-ADDRESSABLE MEMORY SYSTEMS,

    DTIC Science & Technology

    The utility of content -addressable memories (CAM’s) within a general purpose computing system is investigated. Word cells within CAM may be...addressed by the character of all or a part of cell contents . Multimembered sets of word cells may be addressed simultaneously. The distributed logical...package is developed which allows simulation of CAM commands within job programs run on the IBM 7090 and derives tallies of execution times corresponding to a particular realization of a CAM system . (Author)

  6. Radar stage uncertainty

    USGS Publications Warehouse

    Fulford, J.M.; Davies, W.J.

    2005-01-01

    The U.S. Geological Survey is investigating the performance of radars used for stage (or water-level) measurement. This paper presents a comparison of estimated uncertainties and data for radar water-level measurements with float, bubbler, and wire weight water-level measurements. The radar sensor was also temperature-tested in a laboratory. The uncertainty estimates indicate that radar measurements are more accurate than uncorrected pressure sensors at higher water stages, but are less accurate than pressure sensors at low stages. Field data at two sites indicate that radar sensors may have a small negative bias. Comparison of field radar measurements with wire weight measurements found that the radar tends to measure slightly lower values as stage increases. Copyright ASCE 2005.

  7. How Uncertain is Uncertainty?

    NASA Astrophysics Data System (ADS)

    Vámos, Tibor

    The gist of the paper is the fundamental uncertain nature of all kinds of uncertainties and consequently a critical epistemic review of historical and recent approaches, computational methods, algorithms. The review follows the development of the notion from the beginnings of thinking, via the Aristotelian and Skeptic view, the medieval nominalism and the influential pioneering metaphors of ancient India and Persia to the birth of modern mathematical disciplinary reasoning. Discussing the models of uncertainty, e.g. the statistical, other physical and psychological background we reach a pragmatic model related estimation perspective, a balanced application orientation for different problem areas. Data mining, game theories and recent advances in approximation algorithms are discussed in this spirit of modest reasoning.

  8. Uncertainties in transpiration estimates.

    PubMed

    Coenders-Gerrits, A M J; van der Ent, R J; Bogaard, T A; Wang-Erlandsson, L; Hrachowitz, M; Savenije, H H G

    2014-02-13

    arising from S. Jasechko et al. Nature 496, 347-350 (2013)10.1038/nature11983How best to assess the respective importance of plant transpiration over evaporation from open waters, soils and short-term storage such as tree canopies and understories (interception) has long been debated. On the basis of data from lake catchments, Jasechko et al. conclude that transpiration accounts for 80-90% of total land evaporation globally (Fig. 1a). However, another choice of input data, together with more conservative accounting of the related uncertainties, reduces and widens the transpiration ratio estimation to 35-80%. Hence, climate models do not necessarily conflict with observations, but more measurements on the catchment scale are needed to reduce the uncertainty range. There is a Reply to this Brief Communications Arising by Jasechko, S. et al. Nature 506, http://dx.doi.org/10.1038/nature12926 (2014).

  9. Uncertainty in mapping urban air quality using crowdsourcing techniques

    NASA Astrophysics Data System (ADS)

    Schneider, Philipp; Castell, Nuria; Lahoz, William; Bartonova, Alena

    2016-04-01

    Small and low-cost sensors measuring various air pollutants have become available in recent years owing to advances in sensor technology. Such sensors have significant potential for improving high-resolution mapping of air quality in the urban environment as they can be deployed in comparatively large numbers and therefore are able to provide information at unprecedented spatial detail. However, such sensor devices are subject to significant and currently little understood uncertainties that affect their usability. Not only do these devices exhibit random errors and biases of occasionally substantial magnitudes, but these errors may also shift over time. In addition, there often tends to be significant inter-sensor variability even when supposedly identical sensors from the same manufacturer are used. We need to quantify accurately these uncertainties to make proper use of the information they provide. Furthermore, when making use of the data and producing derived products such as maps, the measurement uncertainties that propagate throughout the analysis need to be clearly communicated to the scientific and non-scientific users of the map products. Based on recent experiences within the EU-funded projects CITI-SENSE and hackAIR we discuss the uncertainties along the entire processing chain when using crowdsourcing techniques for mapping urban air quality. Starting with the uncertainties exhibited by the sensors themselves, we present ways of quantifying the error characteristics of a network of low-cost microsensors and show suitable statistical metrics for summarizing them. Subsequently, we briefly present a data-fusion-based method for mapping air quality in the urban environment and illustrate how we propagate the uncertainties of the individual sensors throughout the mapping system, resulting in detailed maps that document the pixel-level uncertainty for each concentration field. Finally, we present methods for communicating the resulting spatial uncertainty

  10. Aggregating and Communicating Uncertainty.

    DTIC Science & Technology

    1980-04-01

    means for identifying and communicating uncertainty. i 12- APPENDIX A BIBLIOGRAPHY j| 1. Ajzen , Icek ; "Intuitive Theories of Events and the Effects...disregarding valid but noncausal information." (Icak Ajzen , "Intuitive Theo- ries of Events and the Effects of Base-Rate Information on Prediction...9 4i,* ,4.. -. .- S % to the criterion while disregarding valid but noncausal information." (Icak Ajzen , "Intuitive Theories of Events and the Effects

  11. Uncertainties in climate stabilization

    SciTech Connect

    Wigley, T. M.; Clarke, Leon E.; Edmonds, James A.; Jacoby, H. D.; Paltsev, S.; Pitcher, Hugh M.; Reilly, J. M.; Richels, Richard G.; Sarofim, M. C.; Smith, Steven J.

    2009-11-01

    We explore the atmospheric composition, temperature and sea level implications of new reference and cost-optimized stabilization emissions scenarios produced using three different Integrated Assessment (IA) models for U.S. Climate Change Science Program (CCSP) Synthesis and Assessment Product 2.1a. We also consider an extension of one of these sets of scenarios out to 2300. Stabilization is defined in terms of radiative forcing targets for the sum of gases potentially controlled under the Kyoto Protocol. For the most stringent stabilization case (“Level 1” with CO2 concentration stabilizing at about 450 ppm), peak CO2 emissions occur close to today, implying a need for immediate CO2 emissions abatement if we wish to stabilize at this level. In the extended reference case, CO2 stabilizes at 1000 ppm in 2200 – but even to achieve this target requires large and rapid CO2 emissions reductions over the 22nd century. Future temperature changes for the Level 1 stabilization case show considerable uncertainty even when a common set of climate model parameters is used (a result of different assumptions for non-Kyoto gases). Uncertainties are about a factor of three when climate sensitivity uncertainties are accounted for. We estimate the probability that warming from pre-industrial times will be less than 2oC to be about 50%. For one of the IA models, warming in the Level 1 case is greater out to 2050 than in the reference case, due to the effect of decreasing SO2 emissions that occur as a side effect of the policy-driven reduction in CO2 emissions. Sea level rise uncertainties for the Level 1 case are very large, with increases ranging from 12 to 100 cm over 2000 to 2300.

  12. Variants of Uncertainty

    DTIC Science & Technology

    1981-05-15

    Variants of Uncertainty Daniel Kahneman University of British Columbia Amos Tversky Stanford University DTI-C &%E-IECTE ~JUNO 1i 19 8 1j May 15, 1981... Dennett , 1979) in which different parts have ac- cess to different data, assign then different weights and hold different views of the situation...2robable and t..h1 provable. Oxford- Claredor Press, 1977. Dennett , D.C. Brainstorms. Hassocks: Harvester, 1979. Donchin, E., Ritter, W. & McCallum, W.C

  13. Integrating Scientific Inquiry into an Undergraduate Applied Remote Sensing Course

    NASA Astrophysics Data System (ADS)

    Sivanpillai, R.

    2015-12-01

    Inquiry-based learning (IBL) methods require students to engage in learning activities instead of focusing on learning concepts and facts. Working with the instructor, students have to formulate their research questions, collect and analyze data, and arrive at conclusions. In other words, the focus is shifted from preparing for exams to learning to apply the concepts introduced in the classroom. This experience could result in better understanding of the scientific concepts but instructors have to devote more time for designing and implementing IBL methods in their classroom. At the University of Wyoming, an applied remote sensing course has been taught since 2008. Students enrolled in this course are required to complete a project that is designed around IBL methods. Students do not receive detailed instructions for completing their project, but are trained to develop their own research questions, design an experiment, review literature, and collect, analyze and interpret their data. Additionally they learn about uncertainties and strategies for addressing them at various stages of their project. This presentation will describe the work involved in designing, implementing and mentoring students to successfully complete the course requirements and learn scientific research methods. Lessons learned from this course could provide insights to other instructors interested in implementing IBL or other active learning methods in their classroom.

  14. The Species Delimitation Uncertainty Principle

    PubMed Central

    Adams, Byron J.

    2001-01-01

    If, as Einstein said, "it is the theory which decides what we can observe," then "the species problem" could be solved by simply improving our theoretical definition of what a species is. However, because delimiting species entails predicting the historical fate of evolutionary lineages, species appear to behave according to the Heisenberg Uncertainty Principle, which states that the most philosophically satisfying definitions of species are the least operational, and as species concepts are modified to become more operational they tend to lose their philosophical integrity. Can species be delimited operationally without losing their philosophical rigor? To mitigate the contingent properties of species that tend to make them difficult for us to delimit, I advocate a set of operations that takes into account the prospective nature of delimiting species. Given the fundamental role of species in studies of evolution and biodiversity, I also suggest that species delimitation proceed within the context of explicit hypothesis testing, like other scientific endeavors. The real challenge is not so much the inherent fallibility of predicting the future but rather adequately sampling and interpreting the evidence available to us in the present. PMID:19265874

  15. Calibration Under Uncertainty.

    SciTech Connect

    Swiler, Laura Painton; Trucano, Timothy Guy

    2005-03-01

    This report is a white paper summarizing the literature and different approaches to the problem of calibrating computer model parameters in the face of model uncertainty. Model calibration is often formulated as finding the parameters that minimize the squared difference between the model-computed data (the predicted data) and the actual experimental data. This approach does not allow for explicit treatment of uncertainty or error in the model itself: the model is considered the %22true%22 deterministic representation of reality. While this approach does have utility, it is far from an accurate mathematical treatment of the true model calibration problem in which both the computed data and experimental data have error bars. This year, we examined methods to perform calibration accounting for the error in both the computer model and the data, as well as improving our understanding of its meaning for model predictability. We call this approach Calibration under Uncertainty (CUU). This talk presents our current thinking on CUU. We outline some current approaches in the literature, and discuss the Bayesian approach to CUU in detail.

  16. Uncertainty Quantification in Aeroelasticity

    NASA Astrophysics Data System (ADS)

    Beran, Philip; Stanford, Bret; Schrock, Christopher

    2017-01-01

    Physical interactions between a fluid and structure, potentially manifested as self-sustained or divergent oscillations, can be sensitive to many parameters whose values are uncertain. Of interest here are aircraft aeroelastic interactions, which must be accounted for in aircraft certification and design. Deterministic prediction of these aeroelastic behaviors can be difficult owing to physical and computational complexity. New challenges are introduced when physical parameters and elements of the modeling process are uncertain. By viewing aeroelasticity through a nondeterministic prism, where key quantities are assumed stochastic, one may gain insights into how to reduce system uncertainty, increase system robustness, and maintain aeroelastic safety. This article reviews uncertainty quantification in aeroelasticity using traditional analytical techniques not reliant on computational fluid dynamics; compares and contrasts this work with emerging methods based on computational fluid dynamics, which target richer physics; and reviews the state of the art in aeroelastic optimization under uncertainty. Barriers to continued progress, for example, the so-called curse of dimensionality, are discussed.

  17. Facing uncertainty in ecosystem services-based resource management.

    PubMed

    Grêt-Regamey, Adrienne; Brunner, Sibyl H; Altwegg, Jürg; Bebi, Peter

    2013-09-01

    The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes.

  18. Multi-scenario modelling of uncertainty in stochastic chemical systems

    SciTech Connect

    Evans, R. David; Ricardez-Sandoval, Luis A.

    2014-09-15

    Uncertainty analysis has not been well studied at the molecular scale, despite extensive knowledge of uncertainty in macroscale systems. The ability to predict the effect of uncertainty allows for robust control of small scale systems such as nanoreactors, surface reactions, and gene toggle switches. However, it is difficult to model uncertainty in such chemical systems as they are stochastic in nature, and require a large computational cost. To address this issue, a new model of uncertainty propagation in stochastic chemical systems, based on the Chemical Master Equation, is proposed in the present study. The uncertain solution is approximated by a composite state comprised of the averaged effect of samples from the uncertain parameter distributions. This model is then used to study the effect of uncertainty on an isomerization system and a two gene regulation network called a repressilator. The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation. -- Highlights: •A method to model uncertainty on stochastic systems was developed. •The method is based on the Chemical Master Equation. •Uncertainty in an isomerization reaction and a gene regulation network was modelled. •Effects were significant and dependent on the uncertain input and reaction system. •The model was computationally more efficient than Kinetic Monte Carlo.

  19. 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.

  20. Uncertainty and error in computational simulations

    SciTech Connect

    Oberkampf, W.L.; Diegert, K.V.; Alvin, K.F.; Rutherford, B.M.

    1997-10-01

    The present paper addresses the question: ``What are the general classes of uncertainty and error sources in complex, computational simulations?`` This is the first step of a two step process to develop a general methodology for quantitatively estimating the global modeling and simulation uncertainty in computational modeling and simulation. The second step is to develop a general mathematical procedure for representing, combining and propagating all of the individual sources through the simulation. The authors develop a comprehensive view of the general phases of modeling and simulation. The phases proposed are: conceptual modeling of the physical system, mathematical modeling of the system, discretization of the mathematical model, computer programming of the discrete model, numerical solution of the model, and interpretation of the results. This new view is built upon combining phases recognized in the disciplines of operations research and numerical solution methods for partial differential equations. The characteristics and activities of each of these phases is discussed in general, but examples are given for the fields of computational fluid dynamics and heat transfer. They argue that a clear distinction should be made between uncertainty and error that can arise in each of these phases. The present definitions for uncertainty and error are inadequate and. therefore, they propose comprehensive definitions for these terms. Specific classes of uncertainty and error sources are then defined that can occur in each phase of modeling and simulation. The numerical sources of error considered apply regardless of whether the discretization procedure is based on finite elements, finite volumes, or finite differences. To better explain the broad types of sources of uncertainty and error, and the utility of their categorization, they discuss a coupled-physics example simulation.

  1. Professionalism, scientific freedom and dissent: individual and institutional roles and responsibilities in geoethics

    NASA Astrophysics Data System (ADS)

    Bilham, Nic

    2015-04-01

    Debate and dissent are at the heart of scientific endeavour. A diversity of perspectives, alternative interpretations of evidence and the robust defence of competing theories and models drive the advancement of scientific knowledge. Just as importantly, legitimate dissent and diversity of views should not be covered up when offering scientific advice to policy-makers and providing evidence to inform public debate - indeed, they should be valued. We should offer what Andy Stirling has termed 'plural and conditional' scientific advice, not just for the sake of democratic legitimacy, but because it supports better informed and more effective policy-making. 'Monocultures' of scientific advice may have a superficial appeal to policy-makers, but they devalue the contribution of scientists, undermine the resilience of regulatory structures, are often misleading, and can lead to catastrophic policy failure. Furthermore, many of the great societal challenges now facing us require interdisciplinary approaches, across the natural sciences and more widely still, which bring to the fore the need for humility, recognition that we do not have all the answers, and mutual respect for the views of others. In contentious areas such as climate change, extraction of shale gas and radioactive waste disposal, however, such open dialogue may make researchers and practitioners vulnerable to advocates and campaigners who cherry-pick the evidence, misinterpret it, or seek to present scientific uncertainty and debate as mere ignorance. Nor are scientists themselves always above such unethical tactics. The apparent authority conferred on unscrupulous 'campaigning scientists' by their academic and professional credentials may make it all but impossible to distinguish them from those who legitimately make the case for a minority scientific view (and may be marginalised by the mainstream of their discipline in doing so). There is a risk that real scientific debate may be thwarted. Individual

  2. Tutorial examples for uncertainty quantification methods.

    SciTech Connect

    De Bord, Sarah

    2015-08-01

    This report details the work accomplished during my 2015 SULI summer internship at Sandia National Laboratories in Livermore, CA. During this internship, I worked on multiple tasks with the common goal of making uncertainty quantification (UQ) methods more accessible to the general scientific community. As part of my work, I created a comprehensive numerical integration example to incorporate into the user manual of a UQ software package. Further, I developed examples involving heat transfer through a window to incorporate into tutorial lectures that serve as an introduction to UQ methods.

  3. PREDON Scientific Data Preservation 2014

    NASA Astrophysics Data System (ADS)

    Diaconu, C.; Kraml, S.; Surace, C.; Chateigner, D.; Libourel, T.; Laurent, A.; Lin, Y.; Schaming, M.; Benbernou, S.; Lebbah, M.; Boucon, D.; Cérin, C.; Azzag, H.; Mouron, P.; Nief, J.-Y.; Coutin, S.; Beckmann, V.

    Scientific data collected with modern sensors or dedicated detectors exceed very often the perimeter of the initial scientific design. These data are obtained more and more frequently with large material and human efforts. A large class of scientific experiments are in fact unique because of their large scale, with very small chances to be repeated and to superseded by new experiments in the same domain: for instance high energy physics and astrophysics experiments involve multi-annual developments and a simple duplication of efforts in order to reproduce old data is simply not affordable. Other scientific experiments are in fact unique by nature: earth science, medical sciences etc. since the collected data is "time-stamped" and thereby non-reproducible by new experiments or observations. In addition, scientific data collection increased dramatically in the recent years, participating to the so-called "data deluge" and inviting for common reflection in the context of "big data" investigations. The new knowledge obtained using these data should be preserved long term such that the access and the re-use are made possible and lead to an enhancement of the initial investment. Data observatories, based on open access policies and coupled with multi-disciplinary techniques for indexing and mining may lead to truly new paradigms in science. It is therefore of outmost importance to pursue a coherent and vigorous approach to preserve the scientific data at long term. The preservation remains nevertheless a challenge due to the complexity of the data structure, the fragility of the custom-made software environments as well as the lack of rigorous approaches in workflows and algorithms. To address this challenge, the PREDON project has been initiated in France in 2012 within the MASTODONS program: a Big Data scientific challenge, initiated and supported by the Interdisciplinary Mission of the National Centre for Scientific Research (CNRS). PREDON is a study group formed by

  4. The Crossroads between Biology and Mathematics: The Scientific Method as the Basics of Scientific Literacy

    ERIC Educational Resources Information Center

    Karsai, Istvan; Kampis, George

    2010-01-01

    Biology is changing and becoming more quantitative. Research is creating new challenges that need to be addressed in education as well. New educational initiatives focus on combining laboratory procedures with mathematical skills, yet it seems that most curricula center on a single relationship between scientific knowledge and scientific method:…

  5. "So a Frackademic and an Environmentalist Walk into an Error Bar...": Communicating Uncertainty Amidst Controversy

    NASA Astrophysics Data System (ADS)

    Kroepsch, A.

    2013-12-01

    above. In striving to separate 'signal' from 'noise' in the public discourse, we have experimented with literary devices (metaphor and narrative), pedagogical tools (the 'what we know, what we don't know, and what we hope to learn' format), journalistic practices (the humanizing profile), and, perhaps most importantly, disarming delivery techniques (humor). In describing these methods, and their effectiveness at addressing scientific uncertainty, the author will be sure to acknowledge the uncertainties inherent therein.

  6. Pauli effects in uncertainty relations

    NASA Astrophysics Data System (ADS)

    Toranzo, I. V.; Sánchez-Moreno, P.; Esquivel, R. O.; Dehesa, J. S.

    2014-10-01

    In this Letter we analyze the effect of the spin dimensionality of a physical system in two mathematical formulations of the uncertainty principle: a generalized Heisenberg uncertainty relation valid for all antisymmetric N-fermion wavefunctions, and the Fisher-information-based uncertainty relation valid for all antisymmetric N-fermion wavefunctions of central potentials. The accuracy of these spin-modified uncertainty relations is examined for all atoms from Hydrogen to Lawrencium in a self-consistent framework.

  7. Innovative Legal Approaches to Address Obesity

    PubMed Central

    Pomeranz, Jennifer L; Teret, Stephen P; Sugarman, Stephen D; Rutkow, Lainie; Brownell, Kelly D

    2009-01-01

    Context: The law is a powerful public health tool with considerable potential to address the obesity issue. Scientific advances, gaps in the current regulatory environment, and new ways of conceptualizing rights and responsibilities offer a foundation for legal innovation. Methods: This article connects developments in public health and nutrition with legal advances to define promising avenues for preventing obesity through the application of the law. Findings: Two sets of approaches are defined: (1) direct application of the law to factors known to contribute to obesity and (2) original and innovative legal solutions that address the weak regulatory stance of government and the ineffectiveness of existing policies used to control obesity. Specific legal strategies are discussed for limiting children's food marketing, confronting the potential addictive properties of food, compelling industry speech, increasing government speech, regulating conduct, using tort litigation, applying nuisance law as a litigation strategy, and considering performance-based regulation as an alternative to typical regulatory actions. Finally, preemption is an overriding issue and can play both a facilitative and a hindering role in obesity policy. Conclusions: Legal solutions are immediately available to the government to address obesity and should be considered at the federal, state, and local levels. New and innovative legal solutions represent opportunities to take the law in creative directions and to link legal, nutrition, and public health communities in constructive ways. PMID:19298420

  8. Asymmetric Uncertainty Expression for High Gradient Aerodynamics

    NASA Technical Reports Server (NTRS)

    Pinier, Jeremy T

    2012-01-01

    When the physics of the flow around an aircraft changes very abruptly either in time or space (e.g., flow separation/reattachment, boundary layer transition, unsteadiness, shocks, etc), the measurements that are performed in a simulated environment like a wind tunnel test or a computational simulation will most likely incorrectly predict the exact location of where (or when) the change in physics happens. There are many reasons for this, includ- ing the error introduced by simulating a real system at a smaller scale and at non-ideal conditions, or the error due to turbulence models in a computational simulation. The un- certainty analysis principles that have been developed and are being implemented today do not fully account for uncertainty in the knowledge of the location of abrupt physics changes or sharp gradients, leading to a potentially underestimated uncertainty in those areas. To address this problem, a new asymmetric aerodynamic uncertainty expression containing an extra term to account for a phase-uncertainty, the magnitude of which is emphasized in the high-gradient aerodynamic regions is proposed in this paper. Additionally, based on previous work, a method for dispersing aerodynamic data within asymmetric uncer- tainty bounds in a more realistic way has been developed for use within Monte Carlo-type analyses.

  9. 48 CFR 435.010 - Scientific and technical reports.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... CATEGORIES OF CONTRACTING RESEARCH AND DEVELOPMENT CONTRACTING 435.010 Scientific and technical reports... all scientific and technical reports to the National Technical Information Service at the address... 48 Federal Acquisition Regulations System 4 2014-10-01 2014-10-01 false Scientific and...

  10. 48 CFR 435.010 - Scientific and technical reports.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... CATEGORIES OF CONTRACTING RESEARCH AND DEVELOPMENT CONTRACTING 435.010 Scientific and technical reports... all scientific and technical reports to the National Technical Information Service at the address... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Scientific and...

  11. 48 CFR 435.010 - Scientific and technical reports.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... CATEGORIES OF CONTRACTING RESEARCH AND DEVELOPMENT CONTRACTING 435.010 Scientific and technical reports... all scientific and technical reports to the National Technical Information Service at the address... 48 Federal Acquisition Regulations System 4 2012-10-01 2012-10-01 false Scientific and...

  12. 48 CFR 435.010 - Scientific and technical reports.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... CATEGORIES OF CONTRACTING RESEARCH AND DEVELOPMENT CONTRACTING 435.010 Scientific and technical reports... all scientific and technical reports to the National Technical Information Service at the address... 48 Federal Acquisition Regulations System 4 2011-10-01 2011-10-01 false Scientific and...

  13. 48 CFR 435.010 - Scientific and technical reports.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... CATEGORIES OF CONTRACTING RESEARCH AND DEVELOPMENT CONTRACTING 435.010 Scientific and technical reports... all scientific and technical reports to the National Technical Information Service at the address... 48 Federal Acquisition Regulations System 4 2013-10-01 2013-10-01 false Scientific and...

  14. On different types of uncertainties in the context of the precautionary principle.

    PubMed

    Aven, Terje

    2011-10-01

    Few policies for risk management have created more controversy than the precautionary principle. A main problem is the extreme number of different definitions and interpretations. Almost all definitions of the precautionary principle identify "scientific uncertainties" as the trigger or criterion for its invocation; however, the meaning of this concept is not clear. For applying the precautionary principle it is not sufficient that the threats or hazards are uncertain. A stronger requirement is needed. This article provides an in-depth analysis of this issue. We question how the scientific uncertainties are linked to the interpretation of the probability concept, expected values, the results from probabilistic risk assessments, the common distinction between aleatory uncertainties and epistemic uncertainties, and the problem of establishing an accurate prediction model (cause-effect relationship). A new classification structure is suggested to define what scientific uncertainties mean.

  15. Nuclear Data Uncertainty Propagation in Depletion Calculations Using Cross Section Uncertainties in One-group or Multi-group

    NASA Astrophysics Data System (ADS)

    Díez, C. J.; Cabellos, O.; Martínez, J. S.

    2015-01-01

    Several approaches have been developed in last decades to tackle nuclear data uncertainty propagation problems of burn-up calculations. One approach proposed was the Hybrid Method, where uncertainties in nuclear data are propagated only on the depletion part of a burn-up problem. Because only depletion is addressed, only one-group cross sections are necessary, and hence, their collapsed one-group uncertainties. This approach has been applied successfully in several advanced reactor systems like EFIT (ADS-like reactor) or ESFR (Sodium fast reactor) to assess uncertainties on the isotopic composition. However, a comparison with using multi-group energy structures was not carried out, and has to be performed in order to analyse the limitations of using one-group uncertainties.

  16. Nuclear Data Uncertainty Propagation in Depletion Calculations Using Cross Section Uncertainties in One-group or Multi-group

    SciTech Connect

    Díez, C.J.; Cabellos, O.; Martínez, J.S.

    2015-01-15

    Several approaches have been developed in last decades to tackle nuclear data uncertainty propagation problems of burn-up calculations. One approach proposed was the Hybrid Method, where uncertainties in nuclear data are propagated only on the depletion part of a burn-up problem. Because only depletion is addressed, only one-group cross sections are necessary, and hence, their collapsed one-group uncertainties. This approach has been applied successfully in several advanced reactor systems like EFIT (ADS-like reactor) or ESFR (Sodium fast reactor) to assess uncertainties on the isotopic composition. However, a comparison with using multi-group energy structures was not carried out, and has to be performed in order to analyse the limitations of using one-group uncertainties.

  17. 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

  18. Satellite altitude determination uncertainties

    NASA Technical Reports Server (NTRS)

    Siry, J. W.

    1972-01-01

    Satellite altitude determination uncertainties will be discussed from the standpoint of the GEOS-C satellite, from the longer range viewpoint afforded by the Geopause concept. Data are focused on methods for short-arc tracking which are essentially geometric in nature. One uses combinations of lasers and collocated cameras. The other method relies only on lasers, using three or more to obtain the position fix. Two typical locales are looked at, the Caribbean area, and a region associated with tracking sites at Goddard, Bermuda and Canada which encompasses a portion of the Gulf Stream in which meanders develop.

  19. Uncertainty bounds using sector theory

    NASA Technical Reports Server (NTRS)

    Waszak, Martin R.; Schmidt, David K.

    1989-01-01

    An approach based on sector-stability theory can furnish a description of the uncertainty associated with the frequency response of a model, given sector-bounds on the individual parameters of the model. The application of the sector-based approach to the formulation of useful uncertainty descriptions for linear, time-invariant multivariable systems is presently explored, and the approach is applied to two generic forms of parameter uncertainty in order to investigate its advantages and limitations. The results obtained show that sector-uncertainty bounds can be used to evaluate the impact of parameter uncertainties on the frequency response of the design model.

  20. A review of the generalized uncertainty principle.

    PubMed

    Tawfik, Abdel Nasser; Diab, Abdel Magied

    2015-12-01

    Based on string theory, black hole physics, doubly special relativity and some 'thought' experiments, minimal distance and/or maximum momentum are proposed. As alternatives to the generalized uncertainty principle (GUP), the modified dispersion relation, the space noncommutativity, the Lorentz invariance violation, and the quantum-gravity-induced birefringence effects are summarized. The origin of minimal measurable quantities and the different GUP approaches are reviewed and the corresponding observations are analysed. Bounds on the GUP parameter are discussed and implemented in the understanding of recent PLANCK observations of cosmic inflation. The higher-order GUP approaches predict minimal length uncertainty with and without maximum momenta. Possible arguments against the GUP are discussed; for instance, the concern about its compatibility with the equivalence principles, the universality of gravitational redshift and the free fall and law of reciprocal action are addressed.

  1. Address tracing for parallel machines

    NASA Technical Reports Server (NTRS)

    Stunkel, Craig B.; Janssens, Bob; Fuchs, W. Kent

    1991-01-01

    Recently implemented parallel system address-tracing methods based on several metrics are surveyed. The issues specific to collection of traces for both shared and distributed memory parallel computers are highlighted. Five general categories of address-trace collection methods are examined: hardware-captured, interrupt-based, simulation-based, altered microcode-based, and instrumented program-based traces. The problems unique to shared memory and distributed memory multiprocessors are examined separately.

  2. Teaching Quantum Uncertainty1

    NASA Astrophysics Data System (ADS)

    Hobson, Art

    2011-10-01

    An earlier paper2 introduces quantum physics by means of four experiments: Youngs double-slit interference experiment using (1) a light beam, (2) a low-intensity light beam with time-lapse photography, (3) an electron beam, and (4) a low-intensity electron beam with time-lapse photography. It's ironic that, although these experiments demonstrate most of the quantum fundamentals, conventional pedagogy stresses their difficult and paradoxical nature. These paradoxes (i.e., logical contradictions) vanish, and understanding becomes simpler, if one takes seriously the fact that quantum mechanics is the nonrelativistic limit of our most accurate physical theory, namely quantum field theory, and treats the Schroedinger wave function, as well as the electromagnetic field, as quantized fields.2 Both the Schroedinger field, or "matter field," and the EM field are made of "quanta"—spatially extended but energetically discrete chunks or bundles of energy. Each quantum comes nonlocally from the entire space-filling field and interacts with macroscopic systems such as the viewing screen by collapsing into an atom instantaneously and randomly in accordance with the probability amplitude specified by the field. Thus, uncertainty and nonlocality are inherent in quantum physics. This paper is about quantum uncertainty. A planned later paper will take up quantum nonlocality.

  3. Antarctic Photochemistry: Uncertainty Analysis

    NASA Technical Reports Server (NTRS)

    Stewart, Richard W.; McConnell, Joseph R.

    1999-01-01

    Understanding the photochemistry of the Antarctic region is important for several reasons. Analysis of ice cores provides historical information on several species such as hydrogen peroxide and sulfur-bearing compounds. The former can potentially provide information on the history of oxidants in the troposphere and the latter may shed light on DMS-climate relationships. Extracting such information requires that we be able to model the photochemistry of the Antarctic troposphere and relate atmospheric concentrations to deposition rates and sequestration in the polar ice. This paper deals with one aspect of the uncertainty inherent in photochemical models of the high latitude troposphere: that arising from imprecision in the kinetic data used in the calculations. Such uncertainties in Antarctic models tend to be larger than those in models of mid to low latitude clean air. One reason is the lower temperatures which result in increased imprecision in kinetic data, assumed to be best characterized at 298K. Another is the inclusion of a DMS oxidation scheme in the present model. Many of the rates in this scheme are less precisely known than are rates in the standard chemistry used in many stratospheric and tropospheric models.

  4. Probabilistic Mass Growth Uncertainties

    NASA Technical Reports Server (NTRS)

    Plumer, Eric; Elliott, Darren

    2013-01-01

    Mass has been widely used as a variable input parameter for Cost Estimating Relationships (CER) for space systems. As these space systems progress from early concept studies and drawing boards to the launch pad, their masses tend to grow substantially, hence adversely affecting a primary input to most modeling CERs. Modeling and predicting mass uncertainty, based on historical and analogous data, is therefore critical and is an integral part of modeling cost risk. This paper presents the results of a NASA on-going effort to publish mass growth datasheet for adjusting single-point Technical Baseline Estimates (TBE) of masses of space instruments as well as spacecraft, for both earth orbiting and deep space missions at various stages of a project's lifecycle. This paper will also discusses the long term strategy of NASA Headquarters in publishing similar results, using a variety of cost driving metrics, on an annual basis. This paper provides quantitative results that show decreasing mass growth uncertainties as mass estimate maturity increases. This paper's analysis is based on historical data obtained from the NASA Cost Analysis Data Requirements (CADRe) database.

  5. Uncertainty in adaptive capacity

    NASA Astrophysics Data System (ADS)

    Adger, W. Neil; Vincent, Katharine

    2005-03-01

    The capacity to adapt is a critical element of the process of adaptation: it is the vector of resources that represent the asset base from which adaptation actions can be made. Adaptive capacity can in theory be identified and measured at various scales, from the individual to the nation. The assessment of uncertainty within such measures comes from the contested knowledge domain and theories surrounding the nature of the determinants of adaptive capacity and the human action of adaptation. While generic adaptive capacity at the national level, for example, is often postulated as being dependent on health, governance and political rights, and literacy, and economic well-being, the determinants of these variables at national levels are not widely understood. We outline the nature of this uncertainty for the major elements of adaptive capacity and illustrate these issues with the example of a social vulnerability index for countries in Africa. To cite this article: W.N. Adger, K. Vincent, C. R. Geoscience 337 (2005).

  6. Communicating uncertainties in assessments of future sea level rise

    NASA Astrophysics Data System (ADS)

    Wikman-Svahn, P.

    2013-12-01

    How uncertainty should be managed and communicated in policy-relevant scientific assessments is directly connected to the role of science and the responsibility of scientists. These fundamentally philosophical issues influence how scientific assessments are made and how scientific findings are communicated to policymakers. It is therefore of high importance to discuss implicit assumptions and value judgments that are made in policy-relevant scientific assessments. The present paper examines these issues for the case of scientific assessments of future sea level rise. The magnitude of future sea level rise is very uncertain, mainly due to poor scientific understanding of all physical mechanisms affecting the great ice sheets of Greenland and Antarctica, which together hold enough land-based ice to raise sea levels more than 60 meters if completely melted. There has been much confusion from policymakers on how different assessments of future sea levels should be interpreted. Much of this confusion is probably due to how uncertainties are characterized and communicated in these assessments. The present paper draws on the recent philosophical debate on the so-called "value-free ideal of science" - the view that science should not be based on social and ethical values. Issues related to how uncertainty is handled in scientific assessments are central to this debate. This literature has much focused on how uncertainty in data, parameters or models implies that choices have to be made, which can have social consequences. However, less emphasis has been on how uncertainty is characterized when communicating the findings of a study, which is the focus of the present paper. The paper argues that there is a tension between on the one hand the value-free ideal of science and on the other hand usefulness for practical applications in society. This means that even if the value-free ideal could be upheld in theory, by carefully constructing and hedging statements characterizing

  7. Fast control latency uncertainty elimination for the BESIII ETOF upgrade

    NASA Astrophysics Data System (ADS)

    Wang, Yun; Cao, Ping; Liu, Shu-bin; An, Qi

    2016-09-01

    A new fanning topology is proposed to precisely fan out fast control signals in the Beijing Spectrometer (BESIII) end-cap time-of-flight (ETOF) electronics. However, uncertainty in transfer latency is introduced by the new fanning channel, which will degrade the precision of fast control. In this paper, latency uncertainty elimination for the BESIII ETOF upgrade is introduced. The latency uncertainty is determined by a Time-Digital-Converter (TDC) embedded in a Field-Programmable Gate Array (FPGA) and is eliminated by re-capturing at synchronous and determinate time. Compared with the existing method of Barrel-cap TOF (BTOF), it has advantages of flexible structure, easy calibration and good adaptability. Field tests on the BESIII ETOF system show that this method effectively eliminates transfer latency uncertainty. Supported by CAS Maintenance Project for Major Scientific and Technological Infrastructure (IHEP-SW-953/2013)

  8. SALTON SEA SCIENTIFIC DRILLING PROJECT: SCIENTIFIC PROGRAM.

    USGS Publications Warehouse

    Sass, J.H.; Elders, W.A.

    1986-01-01

    The Salton Sea Scientific Drilling Project, was spudded on 24 October 1985, and reached a total depth of 10,564 ft. (3. 2 km) on 17 March 1986. There followed a period of logging, a flow test, and downhole scientific measurements. The scientific goals were integrated smoothly with the engineering and economic objectives of the program and the ideal of 'science driving the drill' in continental scientific drilling projects was achieved in large measure. The principal scientific goals of the project were to study the physical and chemical processes involved in an active, magmatically driven hydrothermal system. To facilitate these studies, high priority was attached to four areas of sample and data collection, namely: (1) core and cuttings, (2) formation fluids, (3) geophysical logging, and (4) downhole physical measurements, particularly temperatures and pressures.

  9. Nature of Science, Scientific Inquiry, and Socio-Scientific Issues Arising from Genetics: A Pathway to Developing a Scientifically Literate Citizenry

    NASA Astrophysics Data System (ADS)

    Lederman, Norman G.; Antink, Allison; Bartos, Stephen

    2012-06-01

    The primary focus of this article is to illustrate how teachers can use contemporary socio-scientific issues to teach students about nature of scientific knowledge as well as address the science subject matter embedded in the issues. The article provides an initial discussion about the various aspects of nature of scientific knowledge that are addressed. It is important to remember that the aspects of nature of scientific knowledge are not considered to be a comprehensive list, but rather a set of important ideas for adolescent students to learn about scientific knowledge. These ideas have been advocated as important for secondary students by numerous reform documents internationally. Then, several examples are used to illustrate how genetically based socio-scientific issues can be used by teachers to improve students' understandings of the discussed aspects of nature of scientific knowledge.

  10. Exploration of Uncertainty in Glacier Modelling

    NASA Technical Reports Server (NTRS)

    Thompson, David E.

    1999-01-01

    There are procedures and methods for verification of coding algebra and for validations of models and calculations that are in use in the aerospace computational fluid dynamics (CFD) community. These methods would be efficacious if used by the glacier dynamics modelling community. This paper is a presentation of some of those methods, and how they might be applied to uncertainty management supporting code verification and model validation for glacier dynamics. The similarities and differences between their use in CFD analysis and the proposed application of these methods to glacier modelling are discussed. After establishing sources of uncertainty and methods for code verification, the paper looks at a representative sampling of verification and validation efforts that are underway in the glacier modelling community, and establishes a context for these within overall solution quality assessment. Finally, an information architecture and interactive interface is introduced and advocated. This Integrated Cryospheric Exploration (ICE) Environment is proposed for exploring and managing sources of uncertainty in glacier modelling codes and methods, and for supporting scientific numerical exploration and verification. The details and functionality of this Environment are described based on modifications of a system already developed for CFD modelling and analysis.

  11. Opportunities and challenges of using technology to address health disparities.

    PubMed

    Rivers, Brian M; Bernhardt, Jay M; Fleisher, Linda; Green, Bernard Lee

    2014-03-01

    During a panel presentation at the American Association for Cancer Research Cancer Health Disparities Conference titled 'Opportunities and challenges of using technology to address health disparities', the latest scientific advances in the application and utilization of mobile technology and/or mobile-health (mHealth) interventions to address cancer health disparities were discussed. The session included: an examination of overall population trends in the uptake of technology and the potential of addressing health disparities through such media; an exploration of the conceptual issues and challenges in the construction of mHealth interventions to address disparate and underserved populations; and a presentation of pilot study findings on the acceptability and feasibility of using mHealth interventions to address prostate cancer disparities among African-American men.

  12. Uncertainty relation in Schwarzschild spacetime

    NASA Astrophysics Data System (ADS)

    Feng, Jun; Zhang, Yao-Zhong; Gould, Mark D.; Fan, Heng

    2015-04-01

    We explore the entropic uncertainty relation in the curved background outside a Schwarzschild black hole, and find that Hawking radiation introduces a nontrivial modification on the uncertainty bound for particular observer, therefore it could be witnessed by proper uncertainty game experimentally. We first investigate an uncertainty game between a free falling observer and his static partner holding a quantum memory initially entangled with the quantum system to be measured. Due to the information loss from Hawking decoherence, we find an inevitable increase of the uncertainty on the outcome of measurements in the view of static observer, which is dependent on the mass of the black hole, the distance of observer from event horizon, and the mode frequency of quantum memory. To illustrate the generality of this paradigm, we relate the entropic uncertainty bound with other uncertainty probe, e.g., time-energy uncertainty. In an alternative game between two static players, we show that quantum information of qubit can be transferred to quantum memory through a bath of fluctuating quantum fields outside the black hole. For a particular choice of initial state, we show that the Hawking decoherence cannot counteract entanglement generation after the dynamical evolution of system, which triggers an effectively reduced uncertainty bound that violates the intrinsic limit -log2 ⁡ c. Numerically estimation for a proper choice of initial state shows that our result is comparable with possible real experiments. Finally, a discussion on the black hole firewall paradox in the context of entropic uncertainty relation is given.

  13. Scientific integrity in Brazil.

    PubMed

    Lins, Liliane; Carvalho, Fernando Martins

    2014-09-01

    This article focuses on scientific integrity and the identification of predisposing factors to scientific misconduct in Brazil. Brazilian scientific production has increased in the last ten years, but the quality of the articles has decreased. Pressure on researchers and students for increasing scientific production may contribute to scientific misconduct. Cases of misconduct in science have been recently denounced in the country. Brazil has important institutions for controlling ethical and safety aspects of human research, but there is a lack of specific offices to investigate suspected cases of misconduct and policies to deal with scientific dishonesty.

  14. USGS Science: Addressing Our Nation's Challenges

    USGS Publications Warehouse

    Larson, Tania M.

    2009-01-01

    With 6.6 billion people already living on Earth, and that number increasing every day, human influence on our planet is ever more apparent. Changes to the natural world combined with increasing human demands threaten our health and safety, our national security, our economy, and our quality of life. As a planet and a Nation, we face unprecedented challenges: loss of critical and unique ecosystems, the effects of climate change, increasing demand for limited energy and mineral resources, increasing vulnerability to natural hazards, the effects of emerging diseases on wildlife and human health, and growing needs for clean water. The time to respond to these challenges is now, but policymakers and decisionmakers face difficult choices. With competing priorities to balance, and potentially serious - perhaps irreversible - consequences at stake, our leaders need reliable scientific information to guide their decisions. As the Nation's earth and natural science agency, the USGS monitors and conducts scientific research on natural hazards and resources and how these elements and human activities influence our environment. Because the challenges we face are complex, the science needed to better understand and deal with these challenges must reflect the complex interplay among natural and human systems. With world-class expertise in biology, geology, geography, hydrology, geospatial information, and remote sensing, the USGS is uniquely capable of conducting the comprehensive scientific research needed to better understand the interdependent interactions of Earth's systems. Every day, the USGS helps decisionmakers to minimize loss of life and property, manage our natural resources, and protect and enhance our quality of life. This brochure provides examples of the challenges we face and how USGS science helps decisionmakers to address these challenges.

  15. Load Balancing Scientific Applications

    SciTech Connect

    Pearce, Olga Tkachyshyn

    2014-12-01

    The largest supercomputers have millions of independent processors, and concurrency levels are rapidly increasing. For ideal efficiency, developers of the simulations that run on these machines must ensure that computational work is evenly balanced among processors. Assigning work evenly is challenging because many large modern parallel codes simulate behavior of physical systems that evolve over time, and their workloads change over time. Furthermore, the cost of imbalanced load increases with scale because most large-scale scientific simulations today use a Single Program Multiple Data (SPMD) parallel programming model, and an increasing number of processors will wait for the slowest one at the synchronization points. To address load imbalance, many large-scale parallel applications use dynamic load balance algorithms to redistribute work evenly. The research objective of this dissertation is to develop methods to decide when and how to load balance the application, and to balance it effectively and affordably. We measure and evaluate the computational load of the application, and develop strategies to decide when and how to correct the imbalance. Depending on the simulation, a fast, local load balance algorithm may be suitable, or a more sophisticated and expensive algorithm may be required. We developed a model for comparison of load balance algorithms for a specific state of the simulation that enables the selection of a balancing algorithm that will minimize overall runtime.

  16. Risk communication: Uncertainties and the numbers game

    SciTech Connect

    Ortigara, M.

    1995-08-30

    The science of risk assessment seeks to characterize the potential risk in situations that may pose hazards to human health or the environment. However, the conclusions reached by the scientists and engineers are not an end in themselves - they are passed on to the involved companies, government agencies, legislators, and the public. All interested parties must then decide what to do with the information. Risk communication is a type of technical communication that involves some unique challenges. This paper first defines the relationships between risk assessment, risk management, and risk communication and then explores two issues in risk communication: addressing uncertainty and putting risk number into perspective.

  17. Uncertainties in container failure time predictions

    SciTech Connect

    Williford, R.E.

    1990-01-01

    Stochastic variations in the local chemical environment of a geologic waste repository can cause corresponding variations in container corrosion rates and failure times, and thus in radionuclide release rates. This paper addresses how well the future variations in repository chemistries must be known in order to predict container failure times that are bounded by a finite time period within the repository lifetime. Preliminary results indicate that a 5000 year scatter in predicted container failure times requires that repository chemistries be known to within {plus minus}10% over the repository lifetime. These are small uncertainties compared to current estimates. 9 refs., 3 figs.

  18. DOD ELAP Lab Uncertainties

    DTIC Science & Technology

    2012-03-01

    IPV6, NLLAP, NEFAP  TRAINING Programs  Certification Bodies – ISO /IEC 17021  Accreditation for  Management  System  Certification Bodies that...certify to :  ISO   9001  (QMS),  ISO  14001 (EMS),   TS 16949 (US Automotive)  etc. 2 3 DoD QSM 4.2 standard   ISO /IEC 17025:2005  Each has uncertainty...NOTES Presented at the 9th Annual DoD Environmental Monitoring and Data Quality (EDMQ) Workshop Held 26-29 March 2012 in La Jolla, CA. U.S

  19. Generalized uncertainty relations

    NASA Astrophysics Data System (ADS)

    Herdegen, Andrzej; Ziobro, Piotr

    2017-04-01

    The standard uncertainty relations (UR) in quantum mechanics are typically used for unbounded operators (like the canonical pair). This implies the need for the control of the domain problems. On the other hand, the use of (possibly bounded) functions of basic observables usually leads to more complex and less readily interpretable relations. In addition, UR may turn trivial for certain states if the commutator of observables is not proportional to a positive operator. In this letter we consider a generalization of standard UR resulting from the use of two, instead of one, vector states. The possibility to link these states to each other in various ways adds additional flexibility to UR, which may compensate some of the above-mentioned drawbacks. We discuss applications of the general scheme, leading not only to technical improvements, but also to interesting new insight.

  20. Uncertainty as Certaint

    NASA Astrophysics Data System (ADS)

    Petzinger, Tom

    I am trying to make money in the biotech industry from complexity science. And I am doing it with inspiration that I picked up on the edge of Appalachia spending time with June Holley and ACEnet when I was a Wall Street Journal reporter. I took some of those ideas to Pittsburgh, in biotechnology, in a completely private setting with an economic development focus, but also with a mission t o return profit to private capital. And we are doing that. I submit as a hypothesis, something we are figuring out in the post- industrial era, that business evolves. It is not the definition of business, but business critically involves the design of systems in which uncertainty is treated as a certainty. That is what I have seen and what I have tried to put into practice.

  1. Medical decisions under uncertainty.

    PubMed

    Carmi, A

    1993-01-01

    The court applies the criteria of the reasonable doctor and common practice in order to consider the behaviour of a defendant physician. The meaning of our demand that the doctor expects that his or her acts or omissions will bring about certain implications is that, according to the present circumstances and subject to the limited knowledge of the common practice, the course of certain events or situations in the future may be assumed in spite of the fog of uncertainty which surrounds us. The miracles and wonders of creation are concealed from us, and we are not aware of the way and the nature of our bodily functioning. Therefore, there seems to be no way to avoid mistakes, because in several cases the correct diagnosis cannot be determined even with the most advanced application of all information available. Doctors find it difficult to admit that they grope in the dark. They wish to form clear and accurate diagnoses for their patients. The fact that their profession is faced with innumerable and unavoidable risks and mistakes is hard to swallow, and many of them claim that in their everyday work this does not happen. They should not content themselves by changing their style. A radical metamorphosis is needed. They should not be tempted to formulate their diagnoses in 'neutral' statements in order to be on the safe side. Uncertainty should be accepted and acknowledged by the profession and by the public at large as a human phenomenon, as an integral part of any human decision, and as a clear characteristic of any legal or medical diagnosis.(ABSTRACT TRUNCATED AT 250 WORDS)

  2. Going public: good scientific conduct.

    PubMed

    Meyer, Gitte; Sandøe, Peter

    2012-06-01

    The paper addresses issues of scientific conduct regarding relations between science and the media, relations between scientists and journalists, and attitudes towards the public at large. In the large and increasing body of literature on scientific conduct and misconduct, these issues seem underexposed as ethical challenges. Consequently, individual scientists here tend to be left alone with problems and dilemmas, with no guidance for good conduct. Ideas are presented about how to make up for this omission. Using a practical, ethical approach, the paper attempts to identify ways scientists might deal with ethical public relations issues, guided by a norm or maxim of openness. Drawing on and rethinking the CUDOS codification of the scientific ethos, as it was worked out by Robert K. Merton in 1942, we propose that this, which is echoed in current codifications of norms for good scientific conduct, contains a tacit maxim of openness which may naturally be extended to cover the public relations of science. Discussing openness as access, accountability, transparency and receptiveness, the argumentation concentrates on the possible prevention of misconduct with respect to, on the one hand, sins of omission-withholding important information from the public-and, on the other hand, abuses of the authority of science in order to gain publicity. Statements from interviews with scientists are used to illustrate how scientists might view the relevance of the issues raised.

  3. Back to the future: The Grassroots of Hydrological Uncertainty

    NASA Astrophysics Data System (ADS)

    Smith, K. A.

    2013-12-01

    Uncertainties are widespread within hydrological science, and as society is looking to models to provide answers as to how climate change may affect our future water resources, the performance of hydrological models should be evaluated. With uncertainties being introduced from input data, parameterisation, model structure, validation data, and ';unknown unknowns' it is easy to be pessimistic about model outputs. But uncertainties are an opportunity for scientific endeavour, not a threat. Investigation and suitable presentation of uncertainties, which results in a range of potential outcomes, provides more insight into model projections than just one answer. This paper aims to demonstrate the feasibility of conducting computationally demanding parameter uncertainty estimation experiments on global hydrological models (GHMs). Presently, individual GHMs tend to present their one, best projection, but this leads to spurious precision - a false impression of certainty - which can be misleading to decision makers. Whilst uncertainty estimation is firmly established in catchment hydrology, GHM uncertainty, and parameter uncertainty in particular, has remained largely overlooked. Model inter-comparison studies that investigate model structure uncertainty have been undertaken (e.g. ISI-MIP, EU-WATCH etc.), but these studies seem premature when the uncertainties within each individual model itself have not yet been considered. This study takes a few steps back, going down to one of the first introductions of assumptions in model development, the assignment of model parameter values. Making use of the University of Nottingham's High Performance Computer Cluster (HPC), the Mac-PDM.09 GHM has been subjected to rigorous uncertainty experiments. The Generalised Likelihood Uncertainty Estimation method (GLUE) with Latin Hypercube Sampling has been applied to a GHM for the first time, to produce 100,000 simultaneous parameter perturbations. The results of this ensemble of 100

  4. Incorporating Model Parameter Uncertainty into Prostate IMRT Treatment Planning

    DTIC Science & Technology

    2005-04-01

    Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author( s ) and should not be construed as an...Incorporating Model Parameter Uncertainty into Prostate DAMD17-03-1-0019 IMRT Treatment Planning 6. AUTHOR( S ) David Y. Yang, Ph.D. 7. PERFORMING ORGANIZA TION...NAME( S ) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION Stanford University REPORT NUMBER Stanford, California 94305-5401 E-Mail: yong@reyes .stanford

  5. Coalition Formation under Uncertainty

    DTIC Science & Technology

    2010-03-01

    Management Air Force Institute of Technology Air University Air Education and Training Command In Partial Fulfillment of the Requirements for the Degree of...Accepted: M.U. Thomas, PhD Date Dean, Graduate School of Engineering and Management AFIT/DEE/ENG/10-05 Abstract Many multiagent systems require allocation...andartificial intelligence. The first direct address of cooperative game theory is in von Neumann and Morgenstern’s book, Theory of Games and Economic Behavior

  6. Museology and Scientific Culture.

    ERIC Educational Resources Information Center

    Saunier, Diane

    1988-01-01

    Discusses the period of transition and self examination of the museology of science. Defines the main issues and limits of the museum as a means of transmitting a scientific culture and scientific ways. (Author/RT)

  7. FIFRA Scientific Advisory Panel

    EPA Pesticide Factsheets

    Experts on the Federal Insecticide, Fungicide, and Rodenticide Act Scientific Advisory Panel provide independent scientific advice to the EPA on a wide range of health and safety issues related to pesticides.

  8. Impact of discharge data uncertainty on nutrient load uncertainty

    NASA Astrophysics Data System (ADS)

    Westerberg, Ida; Gustavsson, Hanna; Sonesten, Lars

    2016-04-01

    Uncertainty in the rating-curve model of the stage-discharge relationship leads to uncertainty in discharge time series. These uncertainties in turn affect many other analyses based on discharge data, such as nutrient load estimations. It is important to understand how large the impact of discharge data uncertainty is on such analyses, since they are often used as the basis to take important environmental management decisions. In the Baltic Sea basin, nutrient load estimates from river mouths are a central information basis for managing and reducing eutrophication in the Baltic Sea. In this study we investigated rating curve uncertainty and its propagation to discharge data uncertainty and thereafter to uncertainty in the load of phosphorous and nitrogen for twelve Swedish river mouths. We estimated rating curve uncertainty using the Voting Point method, which accounts for random and epistemic errors in the stage-discharge relation and allows drawing multiple rating-curve realisations consistent with the total uncertainty. We sampled 40,000 rating curves, and for each sampled curve we calculated a discharge time series from 15-minute water level data for the period 2005-2014. Each discharge time series was then aggregated to daily scale and used to calculate the load of phosphorous and nitrogen from linearly interpolated monthly water samples, following the currently used methodology for load estimation. Finally the yearly load estimates were calculated and we thus obtained distributions with 40,000 load realisations per year - one for each rating curve. We analysed how the rating curve uncertainty propagated to the discharge time series at different temporal resolutions, and its impact on the yearly load estimates. Two shorter periods of daily water quality sampling around the spring flood peak allowed a comparison of load uncertainty magnitudes resulting from discharge data with those resulting from the monthly water quality sampling.

  9. Extensional scientific realism vs. intensional scientific realism.

    PubMed

    Park, Seungbae

    2016-10-01

    Extensional scientific realism is the view that each believable scientific theory is supported by the unique first-order evidence for it and that if we want to believe that it is true, we should rely on its unique first-order evidence. In contrast, intensional scientific realism is the view that all believable scientific theories have a common feature and that we should rely on it to determine whether a theory is believable or not. Fitzpatrick argues that extensional realism is immune, while intensional realism is not, to the pessimistic induction. I reply that if extensional realism overcomes the pessimistic induction at all, that is because it implicitly relies on the theoretical resource of intensional realism. I also argue that extensional realism, by nature, cannot embed a criterion for distinguishing between believable and unbelievable theories.

  10. New approaches to uncertainty analysis for use in aggregate and cumulative risk assessment of pesticides.

    PubMed

    Kennedy, Marc C; van der Voet, Hilko; Roelofs, Victoria J; Roelofs, Willem; Glass, C Richard; de Boer, Waldo J; Kruisselbrink, Johannes W; Hart, Andy D M

    2015-05-01

    Risk assessments for human exposures to plant protection products (PPPs) have traditionally focussed on single routes of exposure and single compounds. Extensions to estimate aggregate (multi-source) and cumulative (multi-compound) exposure from PPPs present many new challenges and additional uncertainties that should be addressed as part of risk analysis and decision-making. A general approach is outlined for identifying and classifying the relevant uncertainties and variabilities. The implementation of uncertainty analysis within the MCRA software, developed as part of the EU-funded ACROPOLIS project to address some of these uncertainties, is demonstrated. An example is presented for dietary and non-dietary exposures to the triazole class of compounds. This demonstrates the chaining of models, linking variability and uncertainty generated from an external model for bystander exposure with variability and uncertainty in MCRA dietary exposure assessments. A new method is also presented for combining pesticide usage survey information with limited residue monitoring data, to address non-detect uncertainty. The results show that incorporating usage information reduces uncertainty in parameters of the residue distribution but that in this case quantifying uncertainty is not a priority, at least for UK grown crops. A general discussion of alternative approaches to treat uncertainty, either quantitatively or qualitatively, is included.

  11. Higher-order uncertainty relations

    NASA Astrophysics Data System (ADS)

    Wünsche, A.

    2006-07-01

    Using the non-negativity of Gram determinants of arbitrary order, we derive higher-order uncertainty relations for the symmetric uncertainty matrices of corresponding order n?>?2 to n Hermitean operators (n?=?2 is the usual case). The special cases of third-order and fourth-order uncertainty relations are considered in detail. The obtained third-order uncertainty relations are applied to the Lie groups SU(1,1) with three Hermitean basis operators (K1,K2,K0) and SU(2) with three Hermitean basis operators (J1,J2,J3) where, in particular, the group-coherent states of Perelomov type and of Barut Girardello type for SU(1,1) and the spin or atomic coherent states for SU(2) are investigated. The uncertainty relations for the determinant of the third-order uncertainty matrix are satisfied with the equality sign for coherent states and this determinant becomes vanishing for the Perelomov type of coherent states for SU(1,1) and SU(2). As an example of the application of fourth-order uncertainty relations, we consider the canonical operators (Q1,P1,Q2,P2) of two boson modes and the corresponding uncertainty matrix formed by the operators of the corresponding mean deviations, taking into account the correlations between the two modes. In two mathematical appendices, we prove the non-negativity of the determinant of correlation matrices of arbitrary order and clarify the principal structure of higher-order uncertainty relations.

  12. Simplified propagation of standard uncertainties

    SciTech Connect

    Shull, A.H.

    1997-06-09

    An essential part of any measurement control program is adequate knowledge of the uncertainties of the measurement system standards. Only with an estimate of the standards` uncertainties can one determine if the standard is adequate for its intended use or can one calculate the total uncertainty of the measurement process. Purchased standards usually have estimates of uncertainty on their certificates. However, when standards are prepared and characterized by a laboratory, variance propagation is required to estimate the uncertainty of the standard. Traditional variance propagation typically involves tedious use of partial derivatives, unfriendly software and the availability of statistical expertise. As a result, the uncertainty of prepared standards is often not determined or determined incorrectly. For situations meeting stated assumptions, easier shortcut methods of estimation are now available which eliminate the need for partial derivatives and require only a spreadsheet or calculator. A system of simplifying the calculations by dividing into subgroups of absolute and relative uncertainties is utilized. These methods also incorporate the International Standards Organization (ISO) concepts for combining systematic and random uncertainties as published in their Guide to the Expression of Measurement Uncertainty. Details of the simplified methods and examples of their use are included in the paper.

  13. Every Other Day. Keynote Address.

    ERIC Educational Resources Information Center

    Tiller, Tom

    Schools need to be reoriented and restructured so that what is taught and learned, and the way in which it is taught and learned, are better integrated with young people's real-world experiences. Many indicators suggest that the meaningful aspects of school have been lost in the encounter with modern times. The title of this address--"Every…

  14. Agenda to address climate change

    SciTech Connect

    1998-10-01

    This document looks at addressing climate change in the 21st century. Topics covered are: Responding to climate change; exploring new avenues in energy efficiency; energy efficiency and alternative energy; residential sector; commercial sector; industrial sector; transportation sector; communities; renewable energy; understanding forests to mitigate and adapt to climate change; the Forest Carbon budget; mitigation and adaptation.

  15. Addressing Phonological Questions with Ultrasound

    ERIC Educational Resources Information Center

    Davidson, Lisa

    2005-01-01

    Ultrasound can be used to address unresolved questions in phonological theory. To date, some studies have shown that results from ultrasound imaging can shed light on how differences in phonological elements are implemented. Phenomena that have been investigated include transitional schwa, vowel coalescence, and transparent vowels. A study of…

  16. Keynote Address: Rev. Mark Massa

    ERIC Educational Resources Information Center

    Massa, Mark S.

    2011-01-01

    Rev. Mark S. Massa, S.J., is the dean and professor of Church history at the School of Theology and Ministry at Boston College. He was invited to give a keynote to begin the third Catholic Higher Education Collaborative Conference (CHEC), cosponsored by Boston College and Fordham University. Fr. Massa's address posed critical questions about…

  17. State of the Lab Address

    ScienceCinema

    King, Alex

    2016-07-12

    In his third-annual State of the Lab address, Ames Laboratory Director Alex King called the past year one of "quiet but strong progress" and called for Ames Laboratory to continue to build on its strengths while responding to changing expectations for energy research.

  18. WWW: The Scientific Method

    ERIC Educational Resources Information Center

    Blystone, Robert V.; Blodgett, Kevin

    2006-01-01

    The scientific method is the principal methodology by which biological knowledge is gained and disseminated. As fundamental as the scientific method may be, its historical development is poorly understood, its definition is variable, and its deployment is uneven. Scientific progress may occur without the strictures imposed by the formal…

  19. Addressing Risks to Advance Mental Health Research

    PubMed Central

    Iltis, Ana S.; Misra, Sahana; Dunn, Laura B.; Brown, Gregory K.; Campbell, Amy; Earll, Sarah A.; Glowinski, Anne; Hadley, Whitney B.; Pies, Ronald; DuBois, James M.

    2015-01-01

    Objective Risk communication and management are essential to the ethical conduct of research, yet addressing risks may be time consuming for investigators and institutional review boards (IRBs) may reject study designs that appear too risky. This can discourage needed research, particularly in higher risk protocols or those enrolling potentially vulnerable individuals, such as those with some level of suicidality. Improved mechanisms for addressing research risks may facilitate much needed psychiatric research. This article provides mental health researchers with practical approaches to: 1) identify and define various intrinsic research risks; 2) communicate these risks to others (e.g., potential participants, regulatory bodies, society); 3) manage these risks during the course of a study; and 4) justify the risks. Methods As part of a National Institute of Mental Health (NIMH)-funded scientific meeting series, a public conference and a closed-session expert panel meeting were held on managing and disclosing risks in mental health clinical trials. The expert panel reviewed the literature with a focus on empirical studies and developed recommendations for best practices and further research on managing and disclosing risks in mental health clinical trials. IRB review was not required because there were no human subjects. The NIMH played no role in developing or reviewing the manuscript. Results Challenges, current data, practical strategies, and topics for future research are addressed for each of four key areas pertaining to management and disclosure of risks in clinical trials: identifying and defining risks, communicating risks, managing risks during studies, and justifying research risks. Conclusions Empirical data on risk communication, managing risks, and the benefits of research can support the ethical conduct of mental health research and may help investigators better conceptualize and confront risks and to gain IRB approval. PMID:24173618

  20. Climate change risk analysis framework (CCRAF) a probabilistic tool for analyzing climate change uncertainties

    NASA Astrophysics Data System (ADS)

    Legget, J.; Pepper, W.; Sankovski, A.; Smith, J.; Tol, R.; Wigley, T.

    2003-04-01

    Potential risks of human-induced climate change are subject to a three-fold uncertainty associated with: the extent of future anthropogenic and natural GHG emissions; global and regional climatic responses to emissions; and impacts of climatic changes on economies and the biosphere. Long-term analyses are also subject to uncertainty regarding how humans will respond to actual or perceived changes, through adaptation or mitigation efforts. Explicitly addressing these uncertainties is a high priority in the scientific and policy communities Probabilistic modeling is gaining momentum as a technique to quantify uncertainties explicitly and use decision analysis techniques that take advantage of improved risk information. The Climate Change Risk Assessment Framework (CCRAF) presented here a new integrative tool that combines the probabilistic approaches developed in population, energy and economic sciences with empirical data and probabilistic results of climate and impact models. The main CCRAF objective is to assess global climate change as a risk management challenge and to provide insights regarding robust policies that address the risks, by mitigating greenhouse gas emissions and by adapting to climate change consequences. The CCRAF endogenously simulates to 2100 or beyond annual region-specific changes in population; GDP; primary (by fuel) and final energy (by type) use; a wide set of associated GHG emissions; GHG concentrations; global temperature change and sea level rise; economic, health, and biospheric impacts; costs of mitigation and adaptation measures and residual costs or benefits of climate change. Atmospheric and climate components of CCRAF are formulated based on the latest version of Wigley's and Raper's MAGICC model and impacts are simulated based on a modified version of Tol's FUND model. The CCRAF is based on series of log-linear equations with deterministic and random components and is implemented using a Monte-Carlo method with up to 5000

  1. Scientific Reporting: Raising the Standards.

    PubMed

    McLeroy, Kenneth R; Garney, Whitney; Mayo-Wilson, Evan; Grant, Sean

    2016-10-01

    This article is based on a presentation that was made at the 2014 annual meeting of the editorial board of Health Education & Behavior. The article addresses critical issues related to standards of scientific reporting in journals, including concerns about external and internal validity and reporting bias. It reviews current reporting guidelines, effects of adopting guidelines, and offers suggestions for improving reporting. The evidence about the effects of guideline adoption and implementation is briefly reviewed. Recommendations for adoption and implementation of appropriate guidelines, including considerations for journals, are provided.

  2. I Am Sure There May Be a Planet There: Student Articulation of Uncertainty in Argumentation Tasks

    ERIC Educational Resources Information Center

    Buck, Zoë E.; Lee, Hee-Sun; Flores, Joanna

    2014-01-01

    We investigated how students articulate uncertainty when they are engaged in structured scientific argumentation tasks where they generate, examine, and interpret data to determine the existence of exoplanets. In this study, 302 high school students completed 4 structured scientific arguments that followed a series of computer-model-based…

  3. Generalized uncertainty principle: Approaches and applications

    NASA Astrophysics Data System (ADS)

    Tawfik, A.; Diab, A.

    2014-11-01

    In this paper, we review some highlights from the String theory, the black hole physics and the doubly special relativity and some thought experiments which were suggested to probe the shortest distances and/or maximum momentum at the Planck scale. Furthermore, all models developed in order to implement the minimal length scale and/or the maximum momentum in different physical systems are analyzed and compared. They entered the literature as the generalized uncertainty principle (GUP) assuming modified dispersion relation, and therefore are allowed for a wide range of applications in estimating, for example, the inflationary parameters, Lorentz invariance violation, black hole thermodynamics, Saleker-Wigner inequalities, entropic nature of gravitational laws, Friedmann equations, minimal time measurement and thermodynamics of the high-energy collisions. One of the higher-order GUP approaches gives predictions for the minimal length uncertainty. A second one predicts a maximum momentum and a minimal length uncertainty, simultaneously. An extensive comparison between the different GUP approaches is summarized. We also discuss the GUP impacts on the equivalence principles including the universality of the gravitational redshift and the free fall and law of reciprocal action and on the kinetic energy of composite system. The existence of a minimal length and a maximum momentum accuracy is preferred by various physical observations. The concern about the compatibility with the equivalence principles, the universality of gravitational redshift and the free fall and law of reciprocal action should be addressed. We conclude that the value of the GUP parameters remain a puzzle to be verified.

  4. Uncertainty analysis for a field-scale P loss model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study we assessed the effect of model input error on predic...

  5. Methods for exploring uncertainty in groundwater management predictions

    USGS Publications Warehouse

    Guillaume, Joseph H. A.; Hunt, Randall J.; Comunian, Alessandro; Fu, Baihua; Blakers, Rachel S; Jakeman, Anthony J; Barreteau, Olivier; Hunt, Randall J.; Rinaudo, Jean-Daniel; Ross, Andrew

    2016-01-01

    Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.

  6. Probabilistic Accident Consequence Uncertainty - A Joint CEC/USNRC Study

    SciTech Connect

    Gregory, Julie J.; Harper, Frederick T.

    1999-07-28

    The joint USNRC/CEC consequence uncertainty study was chartered after the development of two new probabilistic accident consequence codes, MACCS in the U.S. and COSYMA in Europe. Both the USNRC and CEC had a vested interest in expanding the knowledge base of the uncertainty associated with consequence modeling, and teamed up to co-sponsor a consequence uncertainty study. The information acquired from the study was expected to provide understanding of the strengths and weaknesses of current models as well as a basis for direction of future research. This paper looks at the elicitation process implemented in the joint study and discusses some of the uncertainty distributions provided by eight panels of experts from the U.S. and Europe that were convened to provide responses to the elicitation. The phenomenological areas addressed by the expert panels include atmospheric dispersion and deposition, deposited material and external doses, food chain, early health effects, late health effects and internal dosimetry.

  7. Qualitative Representation and Reasoning with Uncertainty in Space and Time

    NASA Astrophysics Data System (ADS)

    El-Geresy, Baher A.; Abdelmoty, Alia I.

    Imprecision, indeterminacy and vagueness are all terms which have been studied recently in studies of representations of entities in space and time. The interest has arisen from the fact that in many cases, precise information about objects in space are not available. In this paper a study of spatial uncertainty is presented and extended to temporal uncertainty. Different types and modes of uncertainty are identified. A unified framework is presented for the representation and reasoning over uncertain qualitative domains. The method addresses some of the main limitations of the current approaches. It is shown to apply to different types of entities with arbitrary complexity with total or partial uncertainty. The approach is part of a comprehensive research program aimed at developing a unified complete theory for qualitative spatial and temporal domains.

  8. Analysis and Reduction of Complex Networks Under Uncertainty

    SciTech Connect

    Knio, Omar M

    2014-04-09

    This is a collaborative proposal that aims at developing new methods for the analysis and reduction of complex multiscale networks under uncertainty. The approach is based on combining methods of computational singular perturbation (CSP) and probabilistic uncertainty quantification. In deterministic settings, CSP yields asymptotic approximations of reduced-dimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty raises fundamentally new issues, particularly concerning its impact on the topology of slow manifolds, and means to represent and quantify associated variability. To address these challenges, this project uses polynomial chaos (PC) methods to reformulate uncertain network models, and to analyze them using CSP in probabilistic terms. Specific objectives include (1) developing effective algorithms that can be used to illuminate fundamental and unexplored connections among model reduction, multiscale behavior, and uncertainty, and (2) demonstrating the performance of these algorithms through applications to model problems.

  9. Approaches for describing and communicating overall uncertainty in toxicity characterizations: U.S. Environmental Protection Agency's Integrated Risk Information System (IRIS) as a case study.

    PubMed

    Beck, Nancy B; Becker, Richard A; Erraguntla, Neeraja; Farland, William H; Grant, Roberta L; Gray, George; Kirman, Christopher; LaKind, Judy S; Jeffrey Lewis, R; Nance, Patricia; Pottenger, Lynn H; Santos, Susan L; Shirley, Stephanie; Simon, Ted; Dourson, Michael L

    2016-01-01

    Single point estimates of human health hazard/toxicity values such as a reference dose (RfD) are generally used in chemical hazard and risk assessment programs for assessing potential risks associated with site- or use-specific exposures. The resulting point estimates are often used by risk managers for regulatory decision-making, including standard setting, determination of emission controls, and mitigation of exposures to chemical substances. Risk managers, as well as stakeholders (interested and affected parties), often have limited information regarding assumptions and uncertainty factors in numerical estimates of both hazards and risks. Further, the use of different approaches for addressing uncertainty, which vary in transparency, can lead to a lack of confidence in the scientific underpinning of regulatory decision-making. The overarching goal of this paper, which was developed from an invited participant workshop, is to offer five approaches for presenting toxicity values in a transparent manner in order to improve the understanding, consideration, and informed use of uncertainty by risk assessors, risk managers, and stakeholders. The five approaches for improving the presentation and communication of uncertainty are described using U.S. Environmental Protection Agency's (EPA's) Integrated Risk Information System (IRIS) as a case study. These approaches will ensure transparency in the documentation, development, and use of toxicity values at EPA, the Agency for Toxic Substances and Disease Registry (ATSDR), and other similar assessment programs in the public and private sector. Further empirical testing will help to inform the approaches that will work best for specific audiences and situations.

  10. TRITIUM UNCERTAINTY ANALYSIS FOR SURFACE WATER SAMPLES AT THE SAVANNAH RIVER SITE

    SciTech Connect

    Atkinson, R.

    2012-07-31

    Radiochemical analyses of surface water samples, in the framework of Environmental Monitoring, have associated uncertainties for the radioisotopic results reported. These uncertainty analyses pertain to the tritium results from surface water samples collected at five locations on the Savannah River near the U.S. Department of Energy's Savannah River Site (SRS). Uncertainties can result from the field-sampling routine, can be incurred during transport due to the physical properties of the sample, from equipment limitations, and from the measurement instrumentation used. The uncertainty reported by the SRS in their Annual Site Environmental Report currently considers only the counting uncertainty in the measurements, which is the standard reporting protocol for radioanalytical chemistry results. The focus of this work is to provide an overview of all uncertainty components associated with SRS tritium measurements, estimate the total uncertainty according to ISO 17025, and to propose additional experiments to verify some of the estimated uncertainties. The main uncertainty components discovered and investigated in this paper are tritium absorption or desorption in the sample container, HTO/H{sub 2}O isotopic effect during distillation, pipette volume, and tritium standard uncertainty. The goal is to quantify these uncertainties and to establish a combined uncertainty in order to increase the scientific depth of the SRS Annual Site Environmental Report.

  11. A review of uncertainty visualization within the IPCC reports

    NASA Astrophysics Data System (ADS)

    Nocke, Thomas; Reusser, Dominik; Wrobel, Markus

    2015-04-01

    Results derived from climate model simulations confront non-expert users with a variety of uncertainties. This gives rise to the challenge that the scientific information must be communicated such that it can be easily understood, however, the complexity of the science behind is still incorporated. With respect to the assessment reports of the IPCC, the situation is even more complicated, because heterogeneous sources and multiple types of uncertainties need to be compiled together. Within this work, we systematically (1) analyzed the visual representation of uncertainties in the IPCC AR4 and AR5 reports, and (2) executed a questionnaire to evaluate how different user groups such as decision-makers and teachers understand these uncertainty visualizations. Within the first step, we classified visual uncertainty metaphors for spatial, temporal and abstract representations. As a result, we clearly identified a high complexity of the IPCC visualizations compared to standard presentation graphics, sometimes even integrating two or more uncertainty classes / measures together with the "certain" (mean) information. Further we identified complex written uncertainty explanations within image captions even within the "summary reports for policy makers". In the second step, based on these observations, we designed a questionnaire to investigate how non-climate experts understand these visual representations of uncertainties, how visual uncertainty coding might hinder the perception of the "non-uncertain" data, and if alternatives for certain IPCC visualizations exist. Within the talk/poster, we will present first results from this questionnaire. Summarizing, we identified a clear trend towards complex images within the latest IPCC reports, with a tendency to incorporate as much as possible information into the visual representations, resulting in proprietary, non-standard graphic representations that are not necessarily easy to comprehend on one glimpse. We conclude that

  12. Nanomedicine: Governing uncertainties

    NASA Astrophysics Data System (ADS)

    Trisolino, Antonella

    Nanomedicine is a promising and revolutionary field to improve medical diagnoses and therapies leading to a higher quality of life for everybody. Huge benefits are expected from nanomedicine applications such as in diagnostic and therapeutic field. However, nanomedicine poses several issues on risks to the human health. This thesis aims to defense a perspective of risk governance that sustains scientific knowledge process by developing guidelines and providing the minimum safety standards acceptable to protect the human health. Although nanomedicine is in an early stage of its discovery, some cautious measures are required to provide regulatory mechanisms able to response to the unique set of challenges associated to nanomedicine. Nanotechnology offers an unique opportunity to intensify a major interplay between different disciplines such as science and law. This multidisciplinary approach can positively contributes to find reliable regulatory choices and responsive normative tools in dealing with challenges of novel technologies.

  13. Soliciting scientific information and beliefs in predictive modeling and adaptive management

    NASA Astrophysics Data System (ADS)

    Glynn, P. D.; Voinov, A. A.; Shapiro, C. D.

    2015-12-01

    Post-normal science requires public engagement and adaptive corrections in addressing issues with high complexity and uncertainty. An adaptive management framework is presented for the improved management of natural resources and environments through a public participation process. The framework solicits the gathering and transformation and/or modeling of scientific information but also explicitly solicits the expression of participant beliefs. Beliefs and information are compared, explicitly discussed for alignments or misalignments, and ultimately melded back together as a "knowledge" basis for making decisions. An effort is made to recognize the human or participant biases that may affect the information base and the potential decisions. In a separate step, an attempt is made to recognize and predict the potential "winners" and "losers" (perceived or real) of any decision or action. These "winners" and "losers" include present human communities with different spatial, demographic or socio-economic characteristics as well as more dispersed or more diffusely characterized regional or global communities. "Winners" and "losers" may also include future human communities as well as communities of other biotic species. As in any adaptive management framework, assessment of predictions, iterative follow-through and adaptation of policies or actions is essential, and commonly very difficult or impossible to achieve. Recognizing beforehand the limits of adaptive management is essential. More generally, knowledge of the behavioral and economic sciences and of ethics and sociology will be key to a successful implementation of this adaptive management framework. Knowledge of biogeophysical processes will also be essential, but by definition of the issues being addressed, will always be incomplete and highly uncertain. The human dimensions of the issues addressed and the participatory processes used carry their own complexities and uncertainties. Some ideas and principles are

  14. Keynote Address: Science Since the Medicean Stars and the Beagle

    NASA Astrophysics Data System (ADS)

    Partridge, B.; Hillenbrand, L. A.; Grinspoon, D.

    2010-08-01

    In 2009, the world celebrates both the International Year of Astronomy (IYA), commemorating the 400th anniversary of Galileo's first observations of the heavens with his telescope, and the 200th anniversary of the birth of Charles Darwin and the 150th anniversary of the publication of his Origin of Species, a key impetus for the 2009 Year of Science. In this keynote address, the three presenters (distinguished scientists themselves) will reflect on how these recent centuries of astronomical and scientific discovery have changed our perspectives about the universe, the natural world, and ourselves—and underpin our education and public outreach efforts to help ensure continued scientific advance in the future.

  15. Quantification of Emission Factor Uncertainty

    EPA Science Inventory

    Emissions factors are important for estimating and characterizing emissions from sources of air pollution. There is no quantitative indication of uncertainty for these emission factors, most factors do not have an adequate data set to compute uncertainty, and it is very difficult...

  16. Uncertainties in nuclear fission data

    NASA Astrophysics Data System (ADS)

    Talou, Patrick; Kawano, Toshihiko; Chadwick, Mark B.; Neudecker, Denise; Rising, Michael E.

    2015-03-01

    We review the current status of our knowledge of nuclear fission data, and quantify uncertainties related to each fission observable whenever possible. We also discuss the roles that theory and experiment play in reducing those uncertainties, contributing to the improvement of our fundamental understanding of the nuclear fission process as well as of evaluated nuclear data libraries used in nuclear applications.

  17. Mama Software Features: Uncertainty Testing

    SciTech Connect

    Ruggiero, Christy E.; Porter, Reid B.

    2014-05-30

    This document reviews how the uncertainty in the calculations is being determined with test image data. The results of this testing give an ‘initial uncertainty’ number than can be used to estimate the ‘back end’ uncertainty in digital image quantification in images. Statisticians are refining these numbers as part of a UQ effort.

  18. A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning

    USGS Publications Warehouse

    Matchett, Elliott L.; Fleskes, Joseph P.; Young, Charles A.; Purkey, David R.

    2015-01-01

    The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats are expected to decrease throughout the world in areas that are intensively managed for urban and agricultural uses. Changes in climate and management of increasingly limited water supplies may further impact water resources essential for sustaining habitats. In this report, we document adapting a Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We demonstrate using this adapted model (WEAP-CVwh) to evaluate impacts produced from plausible future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed output from WEAP-CVwh indicated varying levels of impact caused by projected climate, urbanization, and water supply management in scenarios used to exemplify this approach. Among scenarios, the NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow requirements on important water supply sources produced large impacts on annual availability of waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all months of the wintering period relative to other scenarios. This approach provides a new and useful tool for habitat conservation planning in the Central Valley and a model to guide similar research investigations aiming to inform conservation, management, and restoration of important wildlife habitats.

  19. Evaluating Health Risks from Inhaled Polychlorinated Biphenyls: Research Needs for Addressing Uncertainty

    EPA Science Inventory

    Indoor air polychlorinated biphenyl (PCB) concentrations in some U.S. schools are one or more orders of magnitude higher than background levels. In response to this, efforts have been made to assess the potential health risk posed by inhaled PCBs. These efforts are hindered by un...

  20. Towards Algorithmic Advances for Solving Stackelberg Games: Addressing Model Uncertainties and Massive Game Scale-up

    DTIC Science & Technology

    2015-02-04

    SECURITY CLASSIFICATION OF: This project opens up a brand new area of research that fuses two separate subareas of game theory: algorithmic game theory...and behavioral game theory. More specifically, game -theoretic algorithms have been deployed by several security agencies, allowing them to generate...optimal randomized schedules against adversaries who may exploit predictability. However, one key challenge in applying game theory to solving real

  1. From stratospheric ozone to climate change: historical perspective on precaution and scientific responsibility.

    PubMed

    Mégie, Gérard

    2006-10-01

    The issue of the impact of human activities on the stratospheric ozone layer emerged in the early 1970s. But international regulations to mitigate the most serious effects were not adopted until the mid-1980s. This case holds lessons for addressing more complex environmental problems. Concepts that should inform discussion include 'latency,' 'counter-factual scenario based on the Precautionary Principle,' 'inter-generational burden sharing,' and 'estimating global costs under factual and counter-factual regulatory scenarios.' Stringent regulations were adopted when large scientific uncertainty existed, and the environmental problem would have been prevented or more rapidly mitigated, at relatively modest incremental price, but for a time delay before more rigorous Precautionary measures were implemented. Will history repeat itself in the case of climate change?

  2. Atomic clusters with addressable complexity

    NASA Astrophysics Data System (ADS)

    Wales, David J.

    2017-02-01

    A general formulation for constructing addressable atomic clusters is introduced, based on one or more reference structures. By modifying the well depths in a given interatomic potential in favour of nearest-neighbour interactions that are defined in the reference(s), the potential energy landscape can be biased to make a particular permutational isomer the global minimum. The magnitude of the bias changes the resulting potential energy landscape systematically, providing a framework to produce clusters that should self-organise efficiently into the target structure. These features are illustrated for small systems, where all the relevant local minima and transition states can be identified, and for the low-energy regions of the landscape for larger clusters. For a 55-particle cluster, it is possible to design a target structure from a transition state of the original potential and to retain this structure in a doubly addressable landscape. Disconnectivity graphs based on local minima that have no direct connections to a lower minimum provide a helpful way to visualise the larger databases. These minima correspond to the termini of monotonic sequences, which always proceed downhill in terms of potential energy, and we identify them as a class of biminimum. Multiple copies of the target cluster are treated by adding a repulsive term between particles with the same address to maintain distinguishable targets upon aggregation. By tuning the magnitude of this term, it is possible to create assemblies of the target cluster corresponding to a variety of structures, including rings and chains.

  3. Uncertainty in Integrated Assessment Scenarios

    SciTech Connect

    Mort Webster

    2005-10-17

    The determination of climate policy is a decision under uncertainty. The uncertainty in future climate change impacts is large, as is the uncertainty in the costs of potential policies. Rational and economically efficient policy choices will therefore seek to balance the expected marginal costs with the expected marginal benefits. This approach requires that the risks of future climate change be assessed. The decision process need not be formal or quantitative for descriptions of the risks to be useful. Whatever the decision procedure, a useful starting point is to have as accurate a description of climate risks as possible. Given the goal of describing uncertainty in future climate change, we need to characterize the uncertainty in the main causes of uncertainty in climate impacts. One of the major drivers of uncertainty in future climate change is the uncertainty in future emissions, both of greenhouse gases and other radiatively important species such as sulfur dioxide. In turn, the drivers of uncertainty in emissions are uncertainties in the determinants of the rate of economic growth and in the technologies of production and how those technologies will change over time. This project uses historical experience and observations from a large number of countries to construct statistical descriptions of variability and correlation in labor productivity growth and in AEEI. The observed variability then provides a basis for constructing probability distributions for these drivers. The variance of uncertainty in growth rates can be further modified by expert judgment if it is believed that future variability will differ from the past. But often, expert judgment is more readily applied to projected median or expected paths through time. Analysis of past variance and covariance provides initial assumptions about future uncertainty for quantities that are less intuitive and difficult for experts to estimate, and these variances can be normalized and then applied to mean

  4. Equivalence theorem of uncertainty relations

    NASA Astrophysics Data System (ADS)

    Li, Jun-Li; Qiao, Cong-Feng

    2017-01-01

    We present an equivalence theorem to unify the two classes of uncertainty relations, i.e. the variance-based ones and the entropic forms, showing that the entropy of an operator in a quantum system can be built from the variances of a set of commutative operators. This means that an uncertainty relation in the language of entropy may be mapped onto a variance-based one, and vice versa. Employing the equivalence theorem, alternative formulations of entropic uncertainty relations are obtained for the qubit system that are stronger than the existing ones in the literature, and variance-based uncertainty relations for spin systems are reached from the corresponding entropic uncertainty relations.

  5. Reformulating the Quantum Uncertainty Relation.

    PubMed

    Li, Jun-Li; Qiao, Cong-Feng

    2015-08-03

    Uncertainty principle is one of the cornerstones of quantum theory. In the literature, there are two types of uncertainty relations, the operator form concerning the variances of physical observables and the entropy form related to entropic quantities. Both these forms are inequalities involving pairwise observables, and are found to be nontrivial to incorporate multiple observables. In this work we introduce a new form of uncertainty relation which may give out complete trade-off relations for variances of observables in pure and mixed quantum systems. Unlike the prevailing uncertainty relations, which are either quantum state dependent or not directly measurable, our bounds for variances of observables are quantum state independent and immune from the "triviality" problem of having zero expectation values. Furthermore, the new uncertainty relation may provide a geometric explanation for the reason why there are limitations on the simultaneous determination of different observables in N-dimensional Hilbert space.

  6. Uncertainty and risk in wildland fire management: a review.

    PubMed

    Thompson, Matthew P; Calkin, Dave E

    2011-08-01

    Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to treatments, and of spatiotemporal dynamics involving disturbance regimes and climate change. This work attempts to systematically align sources of uncertainty with the most appropriate decision support methodologies, in order to facilitate cost-effective, risk-based wildfire planning efforts. We review the state of wildfire risk assessment and management, with a specific focus on uncertainties challenging implementation of integrated risk assessments that consider a suite of human and ecological values. Recent advances in wildfire simulation and geospatial mapping of highly valued resources have enabled robust risk-based analyses to inform planning across a variety of scales, although improvements are needed in fire behavior and ignition occurrence models. A key remaining challenge is a better characterization of non-market resources at risk, both in terms of their response to fire and how society values those resources. Our findings echo earlier literature identifying wildfire effects analysis and value uncertainty as the primary challenges to integrated wildfire risk assessment and wildfire management. We stress the importance of identifying and characterizing uncertainties in order to better quantify and manage them. Leveraging the most appropriate decision support tools can facilitate wildfire risk assessment and ideally improve decision-making.

  7. Uncertainty Analysis and Expert Judgment in Seismic Hazard Analysis

    NASA Astrophysics Data System (ADS)

    Klügel, Jens-Uwe

    2011-01-01

    The large uncertainty associated with the prediction of future earthquakes is usually regarded as the main reason for increased hazard estimates which have resulted from some recent large scale probabilistic seismic hazard analysis studies (e.g. the PEGASOS study in Switzerland and the Yucca Mountain study in the USA). It is frequently overlooked that such increased hazard estimates are characteristic for a single specific method of probabilistic seismic hazard analysis (PSHA): the traditional (Cornell-McGuire) PSHA method which has found its highest level of sophistication in the SSHAC probability method. Based on a review of the SSHAC probability model and its application in the PEGASOS project, it is shown that the surprising results of recent PSHA studies can be explained to a large extent by the uncertainty model used in traditional PSHA, which deviates from the state of the art in mathematics and risk analysis. This uncertainty model, the Ang-Tang uncertainty model, mixes concepts of decision theory with probabilistic hazard assessment methods leading to an overestimation of uncertainty in comparison to empirical evidence. Although expert knowledge can be a valuable source of scientific information, its incorporation into the SSHAC probability method does not resolve the issue of inflating uncertainties in PSHA results. Other, more data driven, PSHA approaches in use in some European countries are less vulnerable to this effect. The most valuable alternative to traditional PSHA is the direct probabilistic scenario-based approach, which is closely linked with emerging neo-deterministic methods based on waveform modelling.

  8. An Iterative Uncertainty Assessment Technique for Environmental Modeling

    SciTech Connect

    Engel, David W.; Liebetrau, Albert M.; Jarman, Kenneth D.; Ferryman, Thomas A.; Scheibe, Timothy D.; Didier, Brett T.

    2004-06-28

    The reliability of and confidence in predictions from model simulations are crucial--these predictions can significantly affect risk assessment decisions. For example, the fate of contaminants at the U.S. Department of Energy's Hanford Site has critical impacts on long-term waste management strategies. In the uncertainty estimation efforts for the Hanford Site-Wide Groundwater Modeling program, computational issues severely constrain both the number of uncertain parameters that can be considered and the degree of realism that can be included in the models. Substantial improvements in the overall efficiency of uncertainty analysis are needed to fully explore and quantify significant sources of uncertainty. We have combined state-of-the-art statistical and mathematical techniques in a unique iterative, limited sampling approach to efficiently quantify both local and global prediction uncertainties resulting from model input uncertainties. The approach is designed for application to widely diverse problems across multiple scientific domains. Results are presented for both an analytical model where the response surface is ''known'' and a simplified contaminant fate transport and groundwater flow model. The results show that our iterative method for approximating a response surface (for subsequent calculation of uncertainty estimates) of specified precision requires less computing time than traditional approaches based upon noniterative sampling methods.

  9. Resource Materials on Scientific Integrity Issues.

    ERIC Educational Resources Information Center

    Macrina, Francis L., Ed.; Munro, Cindy L., Ed.

    1993-01-01

    The annotated bibliography contains 26 citations of books, monographs, and articles that may be useful to faculty and students in courses on scientific integrity. Topics addressed include ethical and legal considerations, fraud, technical writing and publication, intellectual property, notetaking, case study approach, conflict of interest, and…

  10. Advances in Scientific Investigation and Automation.

    ERIC Educational Resources Information Center

    Abt, Jeffrey; And Others

    1987-01-01

    Six articles address: (1) the impact of science on the physical examination and treatment of books; (2) equipment for physical examination of books; (3) research using the cyclotron for historical analysis; (4) scientific analysis of paper and ink in early maps; (5) recent advances in automation; and (6) cataloging standards. (MES)

  11. Database Handling Software and Scientific Applications.

    ERIC Educational Resources Information Center

    Gabaldon, Diana J.

    1984-01-01

    Discusses the general characteristics of database management systems and file systems. Also gives a basic framework for evaluating such software and suggests characteristics that should be considered when buying software for specific scientific applications. A list of vendor addresses for popular database management systems is included. (JN)

  12. Teaching Scientific Analogies: A Proposed Model.

    ERIC Educational Resources Information Center

    Zeitoun, Hassan Hussein

    Cognitive psychologists have recently alluded to the role analogies might play in learning unfamiliar topics. However, since the use of analogies in science teaching has not been adequately addressed, analogies mean different things to different people. Therefore, a model for the teaching of scientific analogies is proposed. A theoretical…

  13. Developmental Change in Notetaking during Scientific Inquiry

    ERIC Educational Resources Information Center

    Garcia-Mila, Merce; Andersen, Christopher

    2007-01-01

    This paper addresses the development in children's and adults' awareness of the benefits of writing through the analysis of change in notetaking while engaged in scientific inquiry over 10 weeks. Participants were given a notebook that they could choose to use. Our results indicate consistent differences between the performance of adults versus…

  14. Mythical thinking, scientific discourses and research dissemination.

    PubMed

    Hroar Klempe, Sven

    2011-06-01

    This article focuses on some principles for understanding. By taking Anna Mikulak's article "Mismatches between 'scientific' and 'non-scientific' ways of knowing and their contributions to public understanding of science" (IPBS 2011) as a point of departure, the idea of demarcation criteria for scientific and non-scientific discourses is addressed. Yet this is juxtaposed with mythical thinking, which is supposed to be the most salient trait of non-scientific discourses. The author demonstrates how the most widespread demarcation criterion, the criterion of verification, is self-contradictory, not only when it comes to logic, but also in the achievement of isolating natural sciences from other forms of knowledge. According to Aristotle induction is a rhetorical device and as far as scientific statements are based on inductive inferences, they are relying on humanities, which rhetoric is a part of. Yet induction also has an empirical component by being based on sense-impressions, which is not a part of the rhetoric, but the psychology. Also the myths are understood in a rhetorical (Lévi-Strauss) and a psychological (Cassirer) perspective. Thus it is argued that both scientific and non-scientific discourses can be mythical.

  15. Detectability and Interpretational Uncertainties: Considerations in Gauging the Impacts of Land Disturbance on Streamflow

    EPA Science Inventory

    Hydrologic impacts of land disturbance and management can be confounded by rainfall variability. As a consequence, attempts to gauge and quantify these effects through streamflow monitoring are typically subject to uncertainties. This paper addresses the quantification and deline...

  16. Parameter uncertainty analysis for the annual phosphorus loss estimator (APLE) model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Technical abstract: Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, we conduct an uncertainty analys...

  17. Sensitivity and uncertainty analysis for the annual phosphorus loss estimator model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that there are inherent uncertainties with model predictions, limited studies have addressed model prediction uncertainty. In this study we assess the effect of model input error on predict...

  18. Estimating the magnitude of prediction uncertainties for field-scale P loss models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, an uncertainty analysis for the Annual P Loss Estima...

  19. Sensitivity and uncertainty analysis for a field-scale P loss model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that there are inherent uncertainties with model predictions, limited studies have addressed model prediction uncertainty. In this study we assess the effect of model input error on predict...

  20. [Themes addressed in nursing consultation: integrative literature review].

    PubMed

    de Oliveira, Sherida Karanini Paz; Queiroz, Ana Paula Oliveira; Matos, Diliane Paiva de Melo; de Moura, Alline Falconieri; Lima, Francisca Elisângela Teixeira

    2012-01-01

    The study aimed to analyze the aspects of the nursing consultation (NC) in scientific publications. It was conducted an integrative literature review available in databases: LILACS, PUBMED, CINAHL and COCHRANE. 31 articles were selected that met the inclusion criteria. The themes most addressed on the NC were: factors affecting the NC, time and cost of consultations, assessment of nursing records, use of interview scripts, communication, systematization of nursing care, meaning and importance of the NC to promote health. It was concluded that various aspects of nursing consultation are being addressed in the articles analyzed. However, studies are needed to confirm its efficacy.

  1. Sources of Uncertainty in Climate Change Projections of Precipitation

    NASA Astrophysics Data System (ADS)

    Gutmann, Ethan; Clark, Martyn; Eidhammer, Trude; Ikeda, Kyoko; Deser, Clara; Brekke, Levi; Arnold, Jeffrey; Rasmussen, Roy

    2016-04-01

    Predicting the likely changes in precipitation due to anthropogenic climate influences is one of the most important problems in earth science today. This problem is complicated by the enormous uncertainty in current predictions. Until all such sources of uncertainty are adequately addressed and quantified, we can not know what changes may be predictable, and which masked by the internal variability of the climate system itself. Here we assess multiple sources of uncertainty including those due to internal variability, climate model selection, emissions scenario, regional climate model physics, and statistical downscaling methods. This work focuses on the Colorado Rocky Mountains because these mountains serve as the water towers for much of the western United States, but the results are more broadly applicable, and results will be presented covering the Columbia River Basin and the California Sierra Nevadas as well. Internal variability is assessed using 30 members of the CESM Large Ensemble. Uncertainty due to the choice of climate models is assessed using 100 climate projections from the CMIP5 archive, including multiple emissions scenarios. Uncertainty due to regional climate model physics is assessed using a limited set of high-resolution Weather Research and Forecasting (WRF) model simulations in comparison to a larger multi-physics ensemble using the Intermediate Complexity Atmospheric Research (ICAR) model. Finally, statistical downscaling uncertainty is assessed using multiple statistical downscaling models. In near-term projections (25-35 years) internal variability is the largest source of uncertainty; however, over longer time scales (70-80 years) other sources of uncertainty become more important, with the importance of different sources of uncertainty varying depending on the metric assessed.

  2. Scientific integrity memorandum

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2009-03-01

    U.S. President Barack Obama signed a presidential memorandum on 9 March to help restore scientific integrity in government decision making. The memorandum directs the White House Office of Science and Technology Policy to develop a strategy within 120 days that ensures that "the selection of scientists and technology professionals for science and technology positions in the executive branch is based on those individuals' scientific and technological knowledge, credentials, and experience; agencies make available to the public the scientific or technological findings or conclusions considered or relied upon in policy decisions; agencies use scientific and technological information that has been subject to well-established scientific processes such as peer review; and agencies have appropriate rules and procedures to ensure the integrity of the scientific process within the agency, including whistleblower protection."

  3. Uncertainties Quantification and Propagation of Multiple Correlated Variables with Limited Samples

    NASA Astrophysics Data System (ADS)

    Zhanpeng, Shen; Xueqian, Chen; Xinen, Liu; Chaoping, Zang

    2016-09-01

    In order to estimate the reliability of an engineering structure based on limited test data, it is distinctly important to address both the epistemic uncertainty from lacking in samples and correlations between input uncertain variables. Both the probability boxes theory and copula function theory are utilized in proposed method to represent uncertainty and correlation of input variables respectively. Moreover, the uncertainty of response of interest is obtained by uncertainty propagation of correlated input variables. Nested sampling technique is adopted here to insure the propagation is always feasible and the response's uncertainty is characterized by a probability box. Finally, a numerical example illustrates the validity and effectiveness of our method. The results indicate that the epistemic uncertainty cannot be conveniently ignored when available samples are very limited and correlations among input variables may significantly affect the uncertainty of responses.

  4. Estimation of Measurement Uncertainties for the DGT Passive Sampler Used for Determination of Copper in Water

    PubMed Central

    Rauch, Sebastien; Morrison, Gregory M.

    2014-01-01

    Diffusion-based passive samplers are increasingly used for water quality monitoring. While the overall method robustness and reproducibility for passive samplers in water are widely reported, there has been a lack of a detailed description of uncertainty sources. In this paper an uncertainty budget for the determination of fully labile Cu in water using a DGT passive sampler is presented. Uncertainty from the estimation of effective cross-sectional diffusion area and the instrumental determination of accumulated mass of analyte are the most significant sources of uncertainty, while uncertainties from contamination and the estimation of diffusion coefficient are negligible. The results presented highlight issues with passive samplers which are important to address if overall method uncertainty is to be reduced and effective strategies to reduce overall method uncertainty are presented. PMID:25258629

  5. New challenges on uncertainty propagation assessment of flood risk analysis

    NASA Astrophysics Data System (ADS)

    Martins, Luciano; Aroca-Jiménez, Estefanía; Bodoque, José M.; Díez-Herrero, Andrés

    2016-04-01

    Natural hazards, such as floods, cause considerable damage to the human life, material and functional assets every year and around the World. Risk assessment procedures has associated a set of uncertainties, mainly of two types: natural, derived from stochastic character inherent in the flood process dynamics; and epistemic, that are associated with lack of knowledge or the bad procedures employed in the study of these processes. There are abundant scientific and technical literature on uncertainties estimation in each step of flood risk analysis (e.g. rainfall estimates, hydraulic modelling variables); but very few experience on the propagation of the uncertainties along the flood risk assessment. Therefore, epistemic uncertainties are the main goal of this work, in particular,understand the extension of the propagation of uncertainties throughout the process, starting with inundability studies until risk analysis, and how far does vary a proper analysis of the risk of flooding. These methodologies, such as Polynomial Chaos Theory (PCT), Method of Moments or Monte Carlo, are used to evaluate different sources of error, such as data records (precipitation gauges, flow gauges...), hydrologic and hydraulic modelling (inundation estimation), socio-demographic data (damage estimation) to evaluate the uncertainties propagation (UP) considered in design flood risk estimation both, in numerical and cartographic expression. In order to consider the total uncertainty and understand what factors are contributed most to the final uncertainty, we used the method of Polynomial Chaos Theory (PCT). It represents an interesting way to handle to inclusion of uncertainty in the modelling and simulation process. PCT allows for the development of a probabilistic model of the system in a deterministic setting. This is done by using random variables and polynomials to handle the effects of uncertainty. Method application results have a better robustness than traditional analysis

  6. Integrated uncertainty assessment of flow predictions in a Swiss catchment

    NASA Astrophysics Data System (ADS)

    Honti, M.; Stamm, C.; Reichert, P.

    2012-04-01

    Despite the vivid scientific debate on the suitability of RCM predictions for hydrological forecasting, impact studies relying on climatic input data and hydrological models are still the exclusive methods to provide some insight into the expected evolution of streams in the close future. While the climatic uncertainty is usually considered being dominant in such studies, more and more sophisticated uncertainty assessment methods reveal that the uncertainty of our hydrological models has been systematically underestimated by inappropriate assessment methods and that our predictive power for the present conditions can be as weak as it was considered for the future. The integrated treatment of various uncertainty sources allows us to quantify the overall predictive uncertainty for such studies and to decide if the anticipated impacts are relevant compared to the existing uncertainty. The Mönchaltorfer Aa catchment (46 km2) in Switzerland was modelled as a case study. A conceptual rainfall-runoff model was calibrated on measured discharge data with Bayesian parameter inference assuming a statistical error process that can account for various uncertainty sources. Climatic input data were produced by statistical downscaling from the outputs of 10 ENSEMBLES GCM-RCM model chains for the A1B emission scenario with the time horizon of 2050. Hourly rainfall data were produced with the Neyman-Scott rectangular pulses model (Rodriguez-Iturbe et al. 1987) while other weather parameters were generated on daily scale with the UKCP09 weather generator (Murphy et al. 2009). Expected landuse changes were assessed by creating divergent regional storylines from countrywide socio-economic scenarios. Despite the good performance of the hydrological model (Nash-Sutcliffe =0.8), its total predictive uncertainty was significant even for the present conditions. Due to the significant contribution of input uncertainty, individual flood peaks could be predicted with poor confidence. However

  7. Identifying and Addressing Vaccine Hesitancy

    PubMed Central

    Kestenbaum, Lori A.; Feemster, Kristen A.

    2015-01-01

    In the 20th century, the introduction of multiple vaccines significantly reduced childhood morbidity, mortality, and disease outbreaks. Despite, and perhaps because of, their public health impact, an increasing number of parents and patients are choosing to delay or refuse vaccines. These individuals are described as vaccine hesitant. This phenomenon has developed due to the confluence of multiple social, cultural, political and personal factors. As immunization programs continue to expand, understanding and addressing vaccine hesitancy will be crucial to their successful implementation. This review explores the history of vaccine hesitancy, its causes, and suggested approaches for reducing hesitancy and strengthening vaccine acceptance. PMID:25875982

  8. Identifying and addressing vaccine hesitancy.

    PubMed

    Kestenbaum, Lori A; Feemster, Kristen A

    2015-04-01

    In the 20th century, the introduction of multiple vaccines significantly reduced childhood morbidity, mortality, and disease outbreaks. Despite, and perhaps because of, their public health impact, an increasing number of parents and patients are choosing to delay or refuse vaccines. These individuals are described as "vaccine hesitant." This phenomenon has developed due to the confluence of multiple social, cultural, political, and personal factors. As immunization programs continue to expand, understanding and addressing vaccine hesitancy will be crucial to their successful implementation. This review explores the history of vaccine hesitancy, its causes, and suggested approaches for reducing hesitancy and strengthening vaccine acceptance.

  9. Nanoscale content-addressable memory

    NASA Technical Reports Server (NTRS)

    Davis, Bryan (Inventor); Principe, Jose C. (Inventor); Fortes, Jose (Inventor)

    2009-01-01

    A combined content addressable memory device and memory interface is provided. The combined device and interface includes one or more one molecular wire crossbar memories having spaced-apart key nanowires, spaced-apart value nanowires adjacent to the key nanowires, and configurable switches between the key nanowires and the value nanowires. The combination further includes a key microwire-nanowire grid (key MNG) electrically connected to the spaced-apart key nanowires, and a value microwire-nanowire grid (value MNG) electrically connected to the spaced-apart value nanowires. A key or value MNGs selects multiple nanowires for a given key or value.

  10. Addressing inequities in healthy eating.

    PubMed

    Friel, Sharon; Hattersley, Libby; Ford, Laura; O'Rourke, Kerryn

    2015-09-01

    What, when, where and how much people eat is influenced by a complex mix of factors at societal, community and individual levels. These influences operate both directly through the food system and indirectly through political, economic, social and cultural pathways that cause social stratification and influence the quality of conditions in which people live their lives. These factors are the social determinants of inequities in healthy eating. This paper provides an overview of the current evidence base for addressing these determinants and for the promotion of equity in healthy eating.

  11. Addressing the workforce pipeline challenge

    SciTech Connect

    Leonard Bond; Kevin Kostelnik; Richard Holman

    2006-11-01

    A secure and affordable energy supply is essential for achieving U.S. national security, in continuing U.S. prosperity and in laying the foundations to enable future economic growth. To meet this goal the next generation energy workforce in the U.S., in particular those needed to support instrumentation, controls and advanced operations and maintenance, is a critical element. The workforce is aging and a new workforce pipeline, to support both current generation and new build has yet to be established. The paper reviews the challenges and some actions being taken to address this need.

  12. Uncertainties of Mayak urine data

    SciTech Connect

    Miller, Guthrie; Vostrotin, Vadim; Vvdensky, Vladimir

    2008-01-01

    For internal dose calculations for the Mayak worker epidemiological study, quantitative estimates of uncertainty of the urine measurements are necessary. Some of the data consist of measurements of 24h urine excretion on successive days (e.g. 3 or 4 days). In a recent publication, dose calculations were done where the uncertainty of the urine measurements was estimated starting from the statistical standard deviation of these replicate mesurements. This approach is straightforward and accurate when the number of replicate measurements is large, however, a Monte Carlo study showed it to be problematic for the actual number of replicate measurements (median from 3 to 4). Also, it is sometimes important to characterize the uncertainty of a single urine measurement. Therefore this alternate method has been developed. A method of parameterizing the uncertainty of Mayak urine bioassay measmements is described. The Poisson lognormal model is assumed and data from 63 cases (1099 urine measurements in all) are used to empirically determine the lognormal normalization uncertainty, given the measurement uncertainties obtained from count quantities. The natural logarithm of the geometric standard deviation of the normalization uncertainty is found to be in the range 0.31 to 0.35 including a measurement component estimated to be 0.2.

  13. Scientific Journalism in Armenia

    NASA Astrophysics Data System (ADS)

    Farmanyan, S. V.; Mickaelian, A. M.

    2015-07-01

    In the present study, the problems of scientific journalism and activities of Armenian science journalists are presented. Scientific journalism in the world, forms of its activities, Armenian Astronomical Society (ArAS) press-releases and their subjects, ArAS website "Mass Media News" section, annual and monthly calendars of astronomical events, and "Astghagitak" online journal are described. Most interesting astronomical subjects involved in scientific journalism, reasons for non-satisfactory science outreach and possible solutions are discussed.

  14. Sequestration: Documenting and Assessing Lessons Learned Would Assist DOD in Planning for Future Budget Uncertainty

    DTIC Science & Technology

    2015-05-01

    Future Budget Uncertainty 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK...SEQUESTRATION Documenting and Assessing Lessons Learned Would Assist DOD in Planning for Future Budget Uncertainty...UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) U.S. Government Accountability Office,441 G Street NW,Washington,DC,20548 8

  15. Credible Computations: Standard and Uncertainty

    NASA Technical Reports Server (NTRS)

    Mehta, Unmeel B.; VanDalsem, William (Technical Monitor)

    1995-01-01

    The discipline of computational fluid dynamics (CFD) is at a crossroad. Most of the significant advances related to computational methods have taken place. The emphasis is now shifting from methods to results. Significant efforts are made in applying CFD to solve design problems. The value of CFD results in design depends on the credibility of computed results for the intended use. The process of establishing credibility requires a standard so that there is a consistency and uniformity in this process and in the interpretation of its outcome. The key element for establishing the credibility is the quantification of uncertainty. This paper presents salient features of a proposed standard and a procedure for determining the uncertainty. A customer of CFD products - computer codes and computed results - expects the following: A computer code in terms of its logic, numerics, and fluid dynamics and the results generated by this code are in compliance with specified requirements. This expectation is fulfilling by verification and validation of these requirements. The verification process assesses whether the problem is solved correctly and the validation process determines whether the right problem is solved. Standards for these processes are recommended. There is always some uncertainty, even if one uses validated models and verified computed results. The value of this uncertainty is important in the design process. This value is obtained by conducting a sensitivity-uncertainty analysis. Sensitivity analysis is generally defined as the procedure for determining the sensitivities of output parameters to input parameters. This analysis is a necessary step in the uncertainty analysis, and the results of this analysis highlight which computed quantities and integrated quantities in computations need to be determined accurately and which quantities do not require such attention. Uncertainty analysis is generally defined as the analysis of the effect of the uncertainties

  16. Uncertainty relations for characteristic functions

    NASA Astrophysics Data System (ADS)

    Rudnicki, Łukasz; Tasca, D. S.; Walborn, S. P.

    2016-02-01

    We present the uncertainty relation for the characteristic functions (ChUR) of the quantum mechanical position and momentum probability distributions. This inequality is more general than the Heisenberg uncertainty relation and is saturated in two extreme cases for wave functions described by periodic Dirac combs. We further discuss a broad spectrum of applications of the ChUR; in particular, we constrain quantum optical measurements involving general detection apertures and provide the uncertainty relation that is relevant for loop quantum cosmology. A method to measure the characteristic function directly using an auxiliary qubit is also briefly discussed.

  17. Assessing uncertainty in physical constants

    NASA Astrophysics Data System (ADS)

    Henrion, Max; Fischhoff, Baruch

    1986-09-01

    Assessing the uncertainty due to possible systematic errors in a physical measurement unavoidably involves an element of subjective judgment. Examination of historical measurements and recommended values for the fundamental physical constants shows that the reported uncertainties have a consistent bias towards underestimating the actual errors. These findings are comparable to findings of persistent overconfidence in psychological research on the assessment of subjective probability distributions. Awareness of these biases could help in interpreting the precision of measurements, as well as provide a basis for improving the assessment of uncertainty in measurements.

  18. LDRD Final Report: Capabilities for Uncertainty in Predictive Science.

    SciTech Connect

    Phipps, Eric Todd; Eldred, Michael S; Salinger, Andrew G.; Webster, Clayton G.

    2008-10-01

    Predictive simulation of systems comprised of numerous interconnected, tightly coupled com-ponents promises to help solve many problems of scientific and national interest. Howeverpredictive simulation of such systems is extremely challenging due to the coupling of adiverse set of physical and biological length and time scales. This report investigates un-certainty quantification methods for such systems that attempt to exploit their structure togain computational efficiency. The traditional layering of uncertainty quantification aroundnonlinear solution processes is inverted to allow for heterogeneous uncertainty quantificationmethods to be applied to each component in a coupled system. Moreover this approachallows stochastic dimension reduction techniques to be applied at each coupling interface.The mathematical feasibility of these ideas is investigated in this report, and mathematicalformulations for the resulting stochastically coupled nonlinear systems are developed.3

  19. On the formulation of a minimal uncertainty model for robust control with structured uncertainty

    NASA Technical Reports Server (NTRS)

    Belcastro, Christine M.; Chang, B.-C.; Fischl, Robert

    1991-01-01

    In the design and analysis of robust control systems for uncertain plants, representing the system transfer matrix in the form of what has come to be termed an M-delta model has become widely accepted and applied in the robust control literature. The M represents a transfer function matrix M(s) of the nominal closed loop system, and the delta represents an uncertainty matrix acting on M(s). The nominal closed loop system M(s) results from closing the feedback control system, K(s), around a nominal plant interconnection structure P(s). The uncertainty can arise from various sources, such as structured uncertainty from parameter variations or multiple unsaturated uncertainties from unmodeled dynamics and other neglected phenomena. In general, delta is a block diagonal matrix, but for real parameter variations delta is a diagonal matrix of real elements. Conceptually, the M-delta structure can always be formed for any linear interconnection of inputs, outputs, transfer functions, parameter variations, and perturbations. However, very little of the currently available literature addresses computational methods for obtaining this structure, and none of this literature addresses a general methodology for obtaining a minimal M-delta model for a wide class of uncertainty, where the term minimal refers to the dimension of the delta matrix. Since having a minimally dimensioned delta matrix would improve the efficiency of structured singular value (or multivariable stability margin) computations, a method of obtaining a minimal M-delta would be useful. Hence, a method of obtaining the interconnection system P(s) is required. A generalized procedure for obtaining a minimal P-delta structure for systems with real parameter variations is presented. Using this model, the minimal M-delta model can then be easily obtained by closing the feedback loop. The procedure involves representing the system in a cascade-form state-space realization, determining the minimal uncertainty matrix

  20. A Scientific Approach to Teaching about Evolution and Special Creation.

    ERIC Educational Resources Information Center

    Lawson, Anton E.

    1999-01-01

    Presents a lesson that addresses the scientific aspects of the evolution versus special creation controversy by having students gather evidence from the fossil record and analyze that evidence using critical-thinking skills. Contains 13 references. (WRM)

  1. Life and Scientific Work of Peter Guthrie Tait

    NASA Astrophysics Data System (ADS)

    Gilston Knott, Cargill

    2015-04-01

    Preface; 1. Memoir - Peter Guthrie Tait; 2. Experimental work; 3. Mathematical work; 4. Quaternions; 5. Thomson and Tait, 'Tand T', or Thomson and Tait's natural philosophy; 6. Other books; 7. Addresses, reviews, and correspondence; 8. Popular scientific articles; Bibliography; Index.

  2. Uncertainty and precaution in environmental management.

    PubMed

    Krayer von Krauss, M; van Asselt, M B A; Henze, M; Ravetz, J; Beck, M B

    2005-01-01

    In this paper, two different visions of the relationship between science and policy are contrasted with one another: the "modern" vision and the "precautionary" vision. Conditions which must apply in order to invoke the Precautionary Principle are presented, as are some of the main challenges posed by the principle. The following central question remains: If scientific certainty cannot be provided, what may then justify regulatory interventions, and what degree of intervention is justifiable? The notion of "quality of information" is explored, and it is emphasized that there can be no absolute definition of good or bad quality. Collective judgments of quality are only possible through deliberation on the characteristics of the information, and on the relevance of the information to the policy context. Reference to a relative criterion therefore seems inevitable and legal complexities are to be expected. Uncertainty is presented as a multidimensional concept, reaching far beyond the conventional statistical interpretation of the concept. Of critical importance is the development of methods for assessing qualitative categories of uncertainty. Model quality assessment should observe the following rationale: identify a model that is suited to the purpose, yet bears some reasonable resemblance to the "real" phenomena. In this context, "purpose" relates to the policy and societal contexts in which the assessment results are to be used. It is therefore increasingly agreed that judgment of the quality of assessments necessarily involves the participation of non-modellers and non-scientists. A challenging final question is: How to use uncertainty information in policy contexts? More research is required in order to answer this question.

  3. Space Surveillance Network Scheduling Under Uncertainty: Models and Benefits

    NASA Astrophysics Data System (ADS)

    Valicka, C.; Garcia, D.; Staid, A.; Watson, J.; Rintoul, M.; Hackebeil, G.; Ntaimo, L.

    2016-09-01

    Advances in space technologies continue to reduce the cost of placing satellites in orbit. With more entities operating space vehicles, the number of orbiting vehicles and debris has reached unprecedented levels and the number continues to grow. Sensor operators responsible for maintaining the space catalog and providing space situational awareness face an increasingly complex and demanding scheduling requirements. Despite these trends, a lack of advanced tools continues to prevent sensor planners and operators from fully utilizing space surveillance resources. One key challenge involves optimally selecting sensors from a network of varying capabilities for missions with differing requirements. Another open challenge, the primary focus of our work, is building robust schedules that effectively plan for uncertainties associated with weather, ad hoc collections, and other target uncertainties. Existing tools and techniques are not amenable to rigorous analysis of schedule optimality and do not adequately address the presented challenges. Building on prior research, we have developed stochastic mixed-integer linear optimization models to address uncertainty due to weather's effect on collection quality. By making use of the open source Pyomo optimization modeling software, we have posed and solved sensor network scheduling models addressing both forms of uncertainty. We present herein models that allow for concurrent scheduling of collections with the same sensor configuration and for proactively scheduling against uncertain ad hoc collections. The suitability of stochastic mixed-integer linear optimization for building sensor network schedules under different run-time constraints will be discussed.

  4. Uncertainties in hydrological extremes projections and its effects on decision-making processes in an Amazonian sub-basin.

    NASA Astrophysics Data System (ADS)

    Andres Rodriguez, Daniel; Garofolo, Lucas; Lazaro Siqueira Junior, Jose

    2013-04-01

    Uncertainties in Climate Change projections are affected by irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process. Such uncertainties affect the impact studies, complicating the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. Through these kinds of analyses it is possible to identify critical issues, which must be deeper studied. For this study we used several future's projections from General Circulation Models to feed a Hydrological Model, applied to the Amazonian sub-basin of Ji-Paraná. Hydrological Model integrations are performed for present historical time (1970-1990) and for future period (2010-2100). Extreme values analyses are performed to each simulated time series and results are compared with extremes events in present time. A simple approach to identify potential vulnerabilities consists of evaluating the hydrologic system response to climate variability and extreme events observed in the past, comparing them with the conditions projected for the future. Thus it is possible to identify critical issues that need attention and more detailed studies. For the goal of this work, we used socio-economic data from Brazilian Institute of Geography and Statistics, the Operator of the National Electric System, the Brazilian National Water Agency and scientific and press published information. This information is used to characterize impacts associated to extremes hydrological events in the basin during the present historical time and to evaluate potential impacts in the future face to the different hydrological projections. Results show inter-model variability results in a broad dispersion on projected extreme's values. The impact of such dispersion is differentiated for different aspects of socio-economic and natural systems and must be carefully

  5. Estimations of uncertainties of frequencies

    NASA Astrophysics Data System (ADS)

    Eyer, Laurent; Nicoletti, Jean-Marc; Morgenthaler, Stephan

    2016-10-01

    Diverse variable phenomena in the Universe are periodic. Astonishingly many of the periodic signals present in stars have timescales coinciding with human ones (from minutes to years). The periods of signals often have to be deduced from time series which are irregularly sampled and sparse, furthermore correlations between the brightness measurements and their estimated uncertainties are common. The uncertainty on the frequency estimation is reviewed. We explore the astronomical and statistical literature, in both cases of regular and irregular samplings. The frequency uncertainty is depending on signal to noise ratio, the frequency, the observational timespan. The shape of the light curve should also intervene, since sharp features such as exoplanet transits, stellar eclipses, raising branches of pulsation stars give stringent constraints. We propose several procedures (parametric and nonparametric) to estimate the uncertainty on the frequency which are subsequently tested against simulated data to assess their performances.

  6. Climate Projections and Uncertainty Communication.

    PubMed

    Joslyn, Susan L; LeClerc, Jared E

    2016-01-01

    Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists' estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested in two experiments. Results suggest that including uncertainty estimates along with climate projections leads to an increase in participants' trust in the information. Analyses explored the roles of time, place, demographic differences (e.g., age, gender, education level, political party affiliation), and initial belief in climate change. Implications are discussed in terms of the potential benefit of adding uncertainty estimates to public climate projections.

  7. The Value of Addressing Patient Preferences.

    PubMed

    Allen, Jeff D; Stewart, Mark D; Roberts, Samantha A; Sigal, Ellen V

    2017-02-01

    Recent scientific progress is, in some cases, leading to transformative new medicines for diseases that previously had marginal or even no treatment options. This offers great promise for people affected by these diseases, but it has also placed stress on the health care system in terms of the growing cost associated with some new interventions. Effort has been taken to create tools to help patients and health care providers assess the value of new medical innovations. These tools may also provide the basis for assessing the price associated with new medical products. Given the growing expenditures in health care, value frameworks present an opportunity to evaluate new therapeutic options in the context of other treatments and potentially lead to a more economically sustainable health care system. In summary, the contribution to meaningful improvements in health outcomes is the primary focus of any assessment of the value of a new intervention. A component of such evaluations, however, should factor in timely access to new products that address an unmet medical need, as well as the magnitude of that beneficial impact. To achieve these goals, value assessment tools should allow for flexibility in clinical end points and trial designs, incorporate patient preferences, and continually evolve as new evidence, practice patterns, and medical progress advance.

  8. Content-addressable holographic databases

    NASA Astrophysics Data System (ADS)

    Grawert, Felix; Kobras, Sebastian; Burr, Geoffrey W.; Coufal, Hans J.; Hanssen, Holger; Riedel, Marc; Jefferson, C. Michael; Jurich, Mark C.

    2000-11-01

    Holographic data storage allows the simultaneous search of an entire database by performing multiple optical correlations between stored data pages and a search argument. We have recently developed fuzzy encoding techniques for this fast parallel search and demonstrated a holographic data storage system that searches digital data records with high fidelity. This content-addressable retrieval is based on the ability to take the two-dimensional inner product between the search page and each stored data page. We show that this ability is lost when the correlator is defocussed to avoid material oversaturation, but can be regained by the combination of a random phase mask and beam confinement through total internal reflection. Finally, we propose an architecture in which spatially multiplexed holograms are distributed along the path of the search beam, allowing parallel search of large databases.

  9. Addressing viral resistance through vaccines

    PubMed Central

    Laughlin, Catherine; Schleif, Amanda; Heilman, Carole A

    2015-01-01

    Antimicrobial resistance is a serious healthcare concern affecting millions of people around the world. Antiviral resistance has been viewed as a lesser threat than antibiotic resistance, but it is important to consider approaches to address this growing issue. While vaccination is a logical strategy, and has been shown to be successful many times over, next generation viral vaccines with a specific goal of curbing antiviral resistance will need to clear several hurdles including vaccine design, evaluation and implementation. This article suggests that a new model of vaccination may need to be considered: rather than focusing on public health, this model would primarily target sectors of the population who are at high risk for complications from certain infections. PMID:26604979

  10. Addressing Failures in Exascale Computing

    SciTech Connect

    Snir, Marc; Wisniewski, Robert; Abraham, Jacob; Adve, Sarita; Bagchi, Saurabh; Balaji, Pavan; Belak, J.; Bose, Pradip; Cappello, Franck; Carlson, Bill; Chien, Andrew; Coteus, Paul; DeBardeleben, Nathan; Diniz, Pedro; Engelmann, Christian; Erez, Mattan; Fazzari, Saverio; Geist, Al; Gupta, Rinku; Johnson, Fred; Krishnamoorthy, Sriram; Leyffer, Sven; Liberty, Dean; Mitra, Subhasish; Munson, Todd; Schreiber, Rob; Stearley, Jon; Van Hensbergen, Eric

    2014-01-01

    We present here a report produced by a workshop on Addressing failures in exascale computing' held in Park City, Utah, 4-11 August 2012. The charter of this workshop was to establish a common taxonomy about resilience across all the levels in a computing system, discuss existing knowledge on resilience across the various hardware and software layers of an exascale system, and build on those results, examining potential solutions from both a hardware and software perspective and focusing on a combined approach. The workshop brought together participants with expertise in applications, system software, and hardware; they came from industry, government, and academia, and their interests ranged from theory to implementation. The combination allowed broad and comprehensive discussions and led to this document, which summarizes and builds on those discussions.

  11. Addressing failures in exascale computing

    SciTech Connect

    Snir, Marc; Wisniewski, Robert W.; Abraham, Jacob A.; Adve, Sarita; Bagchi, Saurabh; Balaji, Pavan; Belak, Jim; Bose, Pradip; Cappello, Franck; Carlson, William; Chien, Andrew A.; Coteus, Paul; Debardeleben, Nathan A.; Diniz, Pedro; Engelmann, Christian; Erez, Mattan; Saverio, Fazzari; Geist, Al; Gupta, Rinku; Johnson, Fred; Krishnamoorthy, Sriram; Leyffer, Sven; Liberty, Dean; Mitra, Subhasish; Munson, Todd; Schreiber, Robert; Stearly, Jon; Van Hensbergen, Eric

    2014-05-01

    We present here a report produced by a workshop on “Addressing Failures in Exascale Computing” held in Park City, Utah, August 4–11, 2012. The charter of this workshop was to establish a common taxonomy about resilience across all the levels in a computing system; discuss existing knowledge on resilience across the various hardware and software layers of an exascale system; and build on those results, examining potential solutions from both a hardware and software perspective and focusing on a combined approach. The workshop brought together participants with expertise in applications, system software, and hardware; they came from industry, government, and academia; and their interests ranged from theory to implementation. The combination allowed broad and comprehensive discussions and led to this document, which summarizes and builds on those discussions.

  12. Light addressable photoelectrochemical cyanide sensor

    SciTech Connect

    Licht, S.; Myung, N.; Sun, Y.

    1996-03-15

    A sensor is demonstrated that is capable of spatial discrimination of cyanide with use of only a single stationary sensing element. Different spatial regions of the sensing element are light activated to reveal the solution cyanide concentration only at the point of illumination. In this light addressable photoelectrochemical (LAP) sensor the sensing element consists of an n-CdSe electrode immersed in solution, with the open-circuit potential determined under illumination. In alkaline ferro-ferri-cyanide solution, the open-circuit photopotential is highly responsive to cyanide, with a linear response of (120 mV) log [KCN]. LAP detection with a spatial resolution of {+-}1 mm for cyanide detection is demonstrated. The response is almost linear for 0.001-0.100 m cyanide with a resolution of 5 mV. 38 refs., 7 figs., 1 tab.

  13. Dynamical Realism and Uncertainty Propagation

    NASA Astrophysics Data System (ADS)

    Park, Inkwan

    In recent years, Space Situational Awareness (SSA) has become increasingly important as the number of tracked Resident Space Objects (RSOs) continues their growth. One of the most significant technical discussions in SSA is how to propagate state uncertainty in a consistent way with the highly nonlinear dynamical environment. In order to keep pace with this situation, various methods have been proposed to propagate uncertainty accurately by capturing the nonlinearity of the dynamical system. We notice that all of the methods commonly focus on a way to describe the dynamical system as precisely as possible based on a mathematical perspective. This study proposes a new perspective based on understanding dynamics of the evolution of uncertainty itself. We expect that profound insights of the dynamical system could present the possibility to develop a new method for accurate uncertainty propagation. These approaches are naturally concluded in goals of the study. At first, we investigate the most dominant factors in the evolution of uncertainty to realize the dynamical system more rigorously. Second, we aim at developing the new method based on the first investigation enabling orbit uncertainty propagation efficiently while maintaining accuracy. We eliminate the short-period variations from the dynamical system, called a simplified dynamical system (SDS), to investigate the most dominant factors. In order to achieve this goal, the Lie transformation method is introduced since this transformation can define the solutions for each variation separately. From the first investigation, we conclude that the secular variations, including the long-period variations, are dominant for the propagation of uncertainty, i.e., short-period variations are negligible. Then, we develop the new method by combining the SDS and the higher-order nonlinear expansion method, called state transition tensors (STTs). The new method retains advantages of the SDS and the STTs and propagates

  14. Thermodynamic and relativistic uncertainty relations

    NASA Astrophysics Data System (ADS)

    Artamonov, A. A.; Plotnikov, E. M.

    2017-01-01

    Thermodynamic uncertainty relation (UR) was verified experimentally. The experiments have shown the validity of the quantum analogue of the zeroth law of stochastic thermodynamics in the form of the saturated Schrödinger UR. We have also proposed a new type of UR for the relativistic mechanics. These relations allow us to consider macroscopic phenomena within the limits of the ratio of the uncertainty relations for different physical quantities.

  15. Scientific Notation Watercolor

    ERIC Educational Resources Information Center

    Linford, Kyle; Oltman, Kathleen; Daisey, Peggy

    2016-01-01

    (Purpose) The purpose of this paper is to describe visual literacy, an adapted version of Visual Thinking Strategy (VTS), and an art-integrated middle school mathematics lesson about scientific notation. The intent of this lesson was to provide students with a real life use of scientific notation and exponents, and to motivate them to apply their…

  16. Scientific rigor through videogames.

    PubMed

    Treuille, Adrien; Das, Rhiju

    2014-11-01

    Hypothesis-driven experimentation - the scientific method - can be subverted by fraud, irreproducibility, and lack of rigorous predictive tests. A robust solution to these problems may be the 'massive open laboratory' model, recently embodied in the internet-scale videogame EteRNA. Deploying similar platforms throughout biology could enforce the scientific method more broadly.

  17. 3 CFR - Scientific Integrity

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Departments and Agencies Science and the scientific process must inform and guide decisions of my..., and protection of national security. The public must be able to trust the science and scientific..., and integrity. By this memorandum, I assign to the Director of the Office of Science and...

  18. Communicating Climate Uncertainties: Challenges and Opportunities Related to Spatial Scales, Extreme Events, and the Warming 'Hiatus'

    NASA Astrophysics Data System (ADS)

    Casola, J. H.; Huber, D.

    2013-12-01

    Many media, academic, government, and advocacy organizations have achieved sophistication in developing effective messages based on scientific information, and can quickly translate salient aspects of emerging climate research and evolving observations. However, there are several ways in which valid messages can be misconstrued by decision makers, leading them to inaccurate conclusions about the risks associated with climate impacts. Three cases will be discussed: 1) Issues of spatial scale in interpreting climate observations: Local climate observations may contradict summary statements about the effects of climate change on larger regional or global spatial scales. Effectively addressing these differences often requires communicators to understand local and regional climate drivers, and the distinction between a 'signal' associated with climate change and local climate 'noise.' Hydrological statistics in Missouri and California are shown to illustrate this case. 2) Issues of complexity related to extreme events: Climate change is typically invoked following a wide range of damaging meteorological events (e.g., heat waves, landfalling hurricanes, tornadoes), regardless of the strength of the relationship between anthropogenic climate change and the frequency or severity of that type of event. Examples are drawn from media coverage of several recent events, contrasting useful and potentially confusing word choices and frames. 3) Issues revolving around climate sensitivity: The so-called 'pause' or 'hiatus' in global warming has reverberated strongly through political and business discussions of climate change. Addressing the recent slowdown in warming yields an important opportunity to raise climate literacy in these communities. Attempts to use recent observations as a wedge between climate 'believers' and 'deniers' is likely to be counterproductive. Examples are drawn from Congressional testimony and media stories. All three cases illustrate ways that decision

  19. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    This paper presents the formulation of an uncertainty quantification challenge problem consisting of five subproblems. These problems focus on key aspects of uncertainty characterization, sensitivity analysis, uncertainty propagation, extreme-case analysis, and robust design.

  20. Pharmacological Fingerprints of Contextual Uncertainty

    PubMed Central

    Ruge, Diane; Stephan, Klaas E.

    2016-01-01

    Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking. Here we assess the roles of noradrenaline, acetylcholine, and dopamine within a single, unified computational framework of uncertainty. Using pharmacological interventions in a sample of 128 healthy human volunteers and a hierarchical Bayesian learning model, we characterise the influences of noradrenergic, cholinergic, and dopaminergic receptor antagonism on individual computations of uncertainty during a probabilistic serial reaction time task. We propose that noradrenaline influences learning of uncertain events arising from unexpected changes in the environment. In contrast, acetylcholine balances attribution of uncertainty to chance fluctuations within an environmental context, defined by a stable set of probabilistic associations, or to gross environmental violations following a contextual switch. Dopamine supports the use of uncertainty representations to engender fast, adaptive responses. PMID:27846219

  1. Uncertainty of empirical correlation equations

    NASA Astrophysics Data System (ADS)

    Feistel, R.; Lovell-Smith, J. W.; Saunders, P.; Seitz, S.

    2016-08-01

    The International Association for the Properties of Water and Steam (IAPWS) has published a set of empirical reference equations of state, forming the basis of the 2010 Thermodynamic Equation of Seawater (TEOS-10), from which all thermodynamic properties of seawater, ice, and humid air can be derived in a thermodynamically consistent manner. For each of the equations of state, the parameters have been found by simultaneously fitting equations for a range of different derived quantities using large sets of measurements of these quantities. In some cases, uncertainties in these fitted equations have been assigned based on the uncertainties of the measurement results. However, because uncertainties in the parameter values have not been determined, it is not possible to estimate the uncertainty in many of the useful quantities that can be calculated using the parameters. In this paper we demonstrate how the method of generalised least squares (GLS), in which the covariance of the input data is propagated into the values calculated by the fitted equation, and in particular into the covariance matrix of the fitted parameters, can be applied to one of the TEOS-10 equations of state, namely IAPWS-95 for fluid pure water. Using the calculated parameter covariance matrix, we provide some preliminary estimates of the uncertainties in derived quantities, namely the second and third virial coefficients for water. We recommend further investigation of the GLS method for use as a standard method for calculating and propagating the uncertainties of values computed from empirical equations.

  2. Uncertainty assessment tool for climate change impact indicators

    NASA Astrophysics Data System (ADS)

    Otto, Juliane; Keup-Thiel, Elke; Jacob, Daniela; Rechid, Diana; Lückenkötter, Johannes; Juckes, Martin

    2015-04-01

    A major difficulty in the study of climate change impact indicators is dealing with the numerous sources of uncertainties of climate and non-climate data . Its assessment, however, is needed to communicate to users the degree of certainty of climate change impact indicators. This communication of uncertainty is an important component of the FP7 project "Climate Information Portal for Copernicus" (CLIPC). CLIPC is developing a portal to provide a central point of access for authoritative scientific information on climate change. In this project the Climate Service Center 2.0 is in charge of the development of a tool to assess the uncertainty of climate change impact indicators. The calculation of climate change impact indicators will include climate data from satellite and in-situ observations, climate models and re-analyses, and non-climate data. There is a lack of a systematic classification of uncertainties arising from the whole range of climate change impact indicators. We develop a framework that intends to clarify the potential sources of uncertainty of a given indicator and provides - if possible - solutions how to quantify the uncertainties. To structure the sources of uncertainties of climate change impact indicators, we first classify uncertainties along a 'cascade of uncertainty' (Reyer 2013). Our cascade consists of three levels which correspond to the CLIPC meta-classification of impact indicators: Tier-1 indicators are intended to give information on the climate system. Tier-2 indicators attempt to quantify the impacts of climate change on biophysical systems (i.e. flood risks). Tier-3 indicators primarily aim at providing information on the socio-economic systems affected by climate change. At each level, the potential sources of uncertainty of the input data sets and its processing will be discussed. Reference: Reyer, C. (2013): The cascade of uncertainty in modeling forest ecosystem responses to environmental change and the challenge of sustainable

  3. Nazified Science: The Shifting Relations between Scientific and Political Discourse.

    ERIC Educational Resources Information Center

    Schwartzman, Roy

    In an effort to deal with a single aspect of a multifaceted interaction between technical and social discourse, this essay examines the movement of scientific discourse between the realms of politics and science. The paper addresses the effects on scientific methodology wrought by the Nazi employment of science as a basis for racial politics. The…

  4. Analogy and Intersubjectivity: Political Oratory, Scholarly Argument and Scientific Reports.

    ERIC Educational Resources Information Center

    Gross, Alan G.

    1983-01-01

    Focuses on the different ways political oratory, scholarly argument, and scientific reports use analogy. Specifically, analyzes intersubjective agreement in Franklin D. Roosevelt's First Inaugural address, the scholarly argument between Sir Karl Popper and Thomas S. Kuhn, and the scientific reports of various mathematicians and scientists. (PD)

  5. 50 CFR 21.23 - Scientific collecting permits.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... WILDLIFE AND PLANTS (CONTINUED) MIGRATORY BIRD PERMITS Specific Permit Provisions § 21.23 Scientific... take, transport, or possess migratory birds, their parts, nests, or eggs for scientific research or... appropriate Regional Director (Attention: Migratory bird permit office). You can find addresses for...

  6. 50 CFR 21.23 - Scientific collecting permits.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... WILDLIFE AND PLANTS (CONTINUED) MIGRATORY BIRD PERMITS Specific Permit Provisions § 21.23 Scientific... take, transport, or possess migratory birds, their parts, nests, or eggs for scientific research or... appropriate Regional Director (Attention: Migratory bird permit office). You can find addresses for...

  7. 50 CFR 21.23 - Scientific collecting permits.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... WILDLIFE AND PLANTS (CONTINUED) MIGRATORY BIRD PERMITS Specific Permit Provisions § 21.23 Scientific... take, transport, or possess migratory birds, their parts, nests, or eggs for scientific research or... appropriate Regional Director (Attention: Migratory bird permit office). You can find addresses for...

  8. [Scientific journals of medical students in Latin-America].

    PubMed

    Cabrera-Samith, Ignacio; Oróstegui-Pinilla, Diana; Angulo-Bazán, Yolanda; Mayta-Tristán, Percy; Rodríguez-Morales, Alfonso J

    2010-11-01

    This article deals with the history and evolution of student's scientific journals in Latin-America, their beginnings, how many still exist and which is their future projection. Relevant events show the growth of student's scientific journals in Latin-America and how are they working together to improve their quality. This article is addressed not only for Latin American readers but also to worldwide readers. Latin American medical students are consistently working together to publish scientific research, whose quality is constantly improving.

  9. MeshTV: scientific visualization and graphical analysis software

    SciTech Connect

    Brugger, E S; Roberts, L; Wookey, S G

    1999-02-08

    The increasing data complexity engendered by the Accelerated Scientific Computing Initiative (ASCI) requires more capability in our scientific visualization software. B Division at Lawrence Livermore National Laboratory (LLNL) addresses these new and changing requirements with MeshTV. We began work on MeshTV around eight years ago, and have progressively refined the software to provide improved scientific analysis and visualization to well over 100 users at Liver-more, Los Alamos, Sandia, and in private industry. (U)

  10. Relational grounding facilitates development of scientifically useful multiscale models

    PubMed Central

    2011-01-01

    We review grounding issues that influence the scientific usefulness of any biomedical multiscale model (MSM). Groundings are the collection of units, dimensions, and/or objects to which a variable or model constituent refers. To date, models that primarily use continuous mathematics rely heavily on absolute grounding, whereas those that primarily use discrete software paradigms (e.g., object-oriented, agent-based, actor) typically employ relational grounding. We review grounding issues and identify strategies to address them. We maintain that grounding issues should be addressed at the start of any MSM project and should be reevaluated throughout the model development process. We make the following points. Grounding decisions influence model flexibility, adaptability, and thus reusability. Grounding choices should be influenced by measures, uncertainty, system information, and the nature of available validation data. Absolute grounding complicates the process of combining models to form larger models unless all are grounded absolutely. Relational grounding facilitates referent knowledge embodiment within computational mechanisms but requires separate model-to-referent mappings. Absolute grounding can simplify integration by forcing common units and, hence, a common integration target, but context change may require model reengineering. Relational grounding enables synthesis of large, composite (multi-module) models that can be robust to context changes. Because biological components have varying degrees of autonomy, corresponding components in MSMs need to do the same. Relational grounding facilitates achieving such autonomy. Biomimetic analogues designed to facilitate translational research and development must have long lifecycles. Exploring mechanisms of normal-to-disease transition requires model components that are grounded relationally. Multi-paradigm modeling requires both hyperspatial and relational grounding. PMID:21951817

  11. The NIST Simple Guide for Evaluating and Expressing Measurement Uncertainty

    NASA Astrophysics Data System (ADS)

    Possolo, Antonio

    2016-11-01

    NIST has recently published guidance on the evaluation and expression of the uncertainty of NIST measurement results [1, 2], supplementing but not replacing B. N. Taylor and C. E. Kuyatt's (1994) Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results (NIST Technical Note 1297) [3], which tracks closely the Guide to the expression of uncertainty in measurement (GUM) [4], originally published in 1995 by the Joint Committee for Guides in Metrology of the International Bureau of Weights and Measures (BIPM). The scope of this Simple Guide, however, is much broader than the scope of both NIST Technical Note 1297 and the GUM, because it attempts to address several of the uncertainty evaluation challenges that have arisen at NIST since the 1990s, for example to include molecular biology, greenhouse gases and climate science measurements, and forensic science. The Simple Guide also expands the scope of those two other guidance documents by recognizing observation equations (that is, statistical models) as bona fide measurement models. These models are indispensable to reduce data from interlaboratory studies, to combine measurement results for the same measurand obtained by different methods, and to characterize the uncertainty of calibration and analysis functions used in the measurement of force, temperature, or composition of gas mixtures. This presentation reviews the salient aspects of the Simple Guide, illustrates the use of models and methods for uncertainty evaluation not contemplated in the GUM, and also demonstrates the NIST Uncertainty Machine [5] and the NIST Consensus Builder, which are web-based applications accessible worldwide that facilitate evaluations of measurement uncertainty and the characterization of consensus values in interlaboratory studies.

  12. Cumulative uncertainty in measured streamflow and water quality data for small watersheds

    USGS Publications Warehouse

    Harmel, R.D.; Cooper, R.J.; Slade, R.M.; Haney, R.L.; Arnold, J.G.

    2006-01-01

    The scientific community has not established an adequate understanding of the uncertainty inherent in measured water quality data, which is introduced by four procedural categories: streamflow measurement, sample collection, sample preservation/storage, and laboratory analysis. Although previous research has produced valuable information on relative differences in procedures within these categories, little information is available that compares the procedural categories or presents the cumulative uncertainty in resulting water quality data. As a result, quality control emphasis is often misdirected, and data uncertainty is typically either ignored or accounted for with an arbitrary margin of safety. Faced with the need for scientifically defensible estimates of data uncertainty to support water resource management, the objectives of this research were to: (1) compile selected published information on uncertainty related to measured streamflow and water quality data for small watersheds, (2) use a root mean square error propagation method to compare the uncertainty introduced by each procedural category, and (3) use the error propagation method to determine the cumulative probable uncertainty in measured streamflow, sediment, and nutrient data. Best case, typical, and worst case "data quality" scenarios were examined. Averaged across all constituents, the calculated cumulative probable uncertainty (??%) contributed under typical scenarios ranged from 6% to 19% for streamflow measurement, from 4% to 48% for sample collection, from 2% to 16% for sample preservation/storage, and from 5% to 21% for laboratory analysis. Under typical conditions, errors in storm loads ranged from 8% to 104% for dissolved nutrients, from 8% to 110% for total N and P, and from 7% to 53% for TSS. Results indicated that uncertainty can increase substantially under poor measurement conditions and limited quality control effort. This research provides introductory scientific estimates of

  13. A Commentary on Innovation and Emerging Scientific Careers: Is Social Work Prepared to Compete in Today's Scientific Marketplace?

    ERIC Educational Resources Information Center

    Craddock, Jaih B.

    2017-01-01

    The aim of this article is to address some of the questions Dr. Paula S. Nurius presents in her article, "Innovation and Emerging Scientific Careers: Is Social Work Prepared to Compete in Today?s Scientific Marketplace?" Specifically, this article will focus on what we can do to better prepare our emerging research scholars to be…

  14. MO-E-BRE-01: Determination, Minimization and Communication of Uncertainties in Radiation Therapy

    SciTech Connect

    Van Dyk, J; Palta, J; Bortfeld, T; Mijnheer, B

    2014-06-15

    Medical Physicists have a general understanding of uncertainties in the radiation treatment process, both with respect to dosimetry and geometry. However, there is a desire to be more quantitative about uncertainty estimation. A recent International Atomic Energy Agency (IAEA) report (about to be published) recommends that we should be as “accurate as reasonably achievable, technical and biological factors being taken into account”. Thus, a single recommendation as a goal for accuracy in radiation therapy is an oversimplification. That report also suggests that individual clinics should determine their own level of uncertainties for their specific treatment protocols. The question is “how do we implement this in clinical practice”? AAPM Monograph 35 (2011 AAPM Summer School) addressed many specific aspects of uncertainties in each of the steps of a course of radiation treatment. The intent of this symposium is: (1) to review uncertainty considerations in the entire radiation treatment process including uncertainty determination for each step and uncertainty propagation for the total process, (2) to consider aspects of robust optimization which optimizes treatment plans while protecting them against uncertainties, and (3) to describe various methods of displaying uncertainties and communicating uncertainties to the relevant professionals. While the theoretical and research aspects will also be described, the emphasis will be on the practical considerations for the medical physicist in clinical practice. Learning Objectives: To review uncertainty determination in the overall radiation treatment process. To consider uncertainty modeling and uncertainty propagation. To highlight the basic ideas and clinical potential of robust optimization procedures to generate optimal treatment plans that are not severely affected by uncertainties. To describe methods of uncertainty communication and display.

  15. A region addresses patient safety.

    PubMed

    Feinstein, Karen Wolk; Grunden, Naida; Harrison, Edward I

    2002-06-01

    The Pittsburgh Regional Healthcare Initiative (PRHI) is a coalition of 35 hospitals, 4 major insurers, more than 30 major and small-business health care purchasers, dozens of corporate and civic leaders, organized labor, and partnerships with state and federal government all working together to deliver perfect patient care throughout Southwestern Pennsylvania. PRHI believes that in pursuing perfection, many of the challenges facing today's health care delivery system (eg, waste and error in the delivery of care, rising costs, frustration and shortage among clinicians and workers, financial distress, overcapacity, and lack of access to care) will be addressed. PRHI has identified patient safety (nosocomial infections and medication errors) and 5 clinical areas (obstetrics, orthopedic surgery, cardiac surgery, depression, and diabetes) as ideal starting points. In each of these areas of work, PRHI partners have assembled multifacility/multidisciplinary groups charged with defining perfection, establishing region-wide reporting systems, and devising and implementing recommended improvement strategies and interventions. Many design and conceptual elements of the PRHI strategy are adapted from the Toyota Production System and its Pittsburgh derivative, the Alcoa Business System. PRHI is in the proof-of-concept phase of development.

  16. Decisions on new product development under uncertainties

    NASA Astrophysics Data System (ADS)

    Huang, Yeu-Shiang; Liu, Li-Chen; Ho, Jyh-Wen

    2015-04-01

    In an intensively competitive market, developing a new product has become a valuable strategy for companies to establish their market positions and enhance their competitive advantages. Therefore, it is essential to effectively manage the process of new product development (NPD). However, since various problems may arise in NPD projects, managers should set up some milestones and subsequently construct evaluative mechanisms to assess their feasibility. This paper employed the approach of Bayesian decision analysis to deal with the two crucial uncertainties for NPD, which are the future market share and the responses of competitors. The proposed decision process can provide a systematic analytical procedure to determine whether an NPD project should be continued or not under the consideration of whether effective usage is being made of the organisational resources. Accordingly, the proposed decision model can assist the managers in effectively addressing the NPD issue under the competitive market.

  17. Communicating uncertainties in natural hazard forecasts

    NASA Astrophysics Data System (ADS)

    Stein, Seth; Geller, Robert J.

    2012-09-01

    Natural hazards research seeks to help society develop strategies that appropriately balance risks and mitigation costs in addressing potential imminent threats and possible longer-term hazards. However, because scientists have only limited knowledge of the future, they must also communicate the uncertainties in what they know about the hazards. How to do so has been the subject of extensive recent discussion [Sarewitz et al., 2000; Oreskes, 2000; Pilkey and Pilkey-Jarvis, 2006]. One approach is General Colin Powell's charge to intelligence officers [Powell, 2012]: "Tell me what you know. Tell me what you don't know. Then tell me what you think. Always distinguish which is which." In dealing with natural hazards, the last point can be modified to "which is which and why." To illustrate this approach, it is helpful to consider some successful and unsuccessful examples [Stein, 2010; Stein et al., 2012].

  18. Reducing long-term reservoir performance uncertainty

    SciTech Connect

    Lippmann, M.J.

    1988-04-01

    Reservoir performance is one of the key issues that have to be addressed before going ahead with the development of a geothermal field. In order to select the type and size of the power plant and design other surface installations, it is necessary to know the characteristics of the production wells and of the produced fluids, and to predict the changes over a 10--30 year period. This is not a straightforward task, as in most cases the calculations have to be made on the basis of data collected before significant fluid volumes have been extracted from the reservoir. The paper describes the methodology used in predicting the long-term performance of hydrothermal systems, as well as DOE/GTD-sponsored research aimed at reducing the uncertainties associated with these predictions. 27 refs., 1 fig.

  19. Optimal fingerprinting under multiple sources of uncertainty

    NASA Astrophysics Data System (ADS)

    Hannart, Alexis; Ribes, Aurélien; Naveau, Philippe

    2014-02-01

    Detection and attribution studies routinely use linear regression methods referred to as optimal fingerprinting. Within the latter methodological paradigm, it is usually recognized that multiple sources of uncertainty affect both the observations and the simulated climate responses used as regressors. These include for instance internal variability, climate model error, or observational error. When all errors share the same covariance, the statistical inference is usually performed with the so-called total least squares procedure, but to date no inference procedure is readily available in the climate literature to treat the general case where this assumption does not hold. Here we address this deficiency. After a brief outlook on the error-in-variable models literature, we describe an inference procedure based on likelihood maximization, inspired by a recent article dealing with a similar situation in geodesy. We evaluate the performance of our approach via an idealized test bed. We find the procedure to outperform existing procedures when the latter wrongly neglect some sources of uncertainty.

  20. Visualizing uncertainty in biological expression data

    NASA Astrophysics Data System (ADS)

    Holzhüter, Clemens; Lex, Alexander; Schmalstieg, Dieter; Schulz, Hans-Jörg; Schumann, Heidrun; Streit, Marc

    2012-01-01

    Expression analysis of ~omics data using microarrays has become a standard procedure in the life sciences. However, microarrays are subject to technical limitations and errors, which render the data gathered likely to be uncertain. While a number of approaches exist to target this uncertainty statistically, it is hardly ever even shown when the data is visualized using for example clustered heatmaps. Yet, this is highly useful when trying not to omit data that is "good enough" for an analysis, which otherwise would be discarded as too unreliable by established conservative thresholds. Our approach addresses this shortcoming by first identifying the margin above the error threshold of uncertain, yet possibly still useful data. It then displays this uncertain data in the context of the valid data by enhancing a clustered heatmap. We employ different visual representations for the different kinds of uncertainty involved. Finally, it lets the user interactively adjust the thresholds, giving visual feedback in the heatmap representation, so that an informed choice on which thresholds to use can be made instead of applying the usual rule-of-thumb cut-offs. We exemplify the usefulness of our concept by giving details for a concrete use case from our partners at the Medical University of Graz, thereby demonstrating our implementation of the general approach.

  1. Uncertainty in Vs30-based site response

    USGS Publications Warehouse

    Thompson, Eric; Wald, David J.

    2016-01-01

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

  2. Scheduling Future Water Supply Investments Under Uncertainty

    NASA Astrophysics Data System (ADS)

    Huskova, I.; Matrosov, E. S.; Harou, J. J.; Kasprzyk, J. R.; Reed, P. M.

    2014-12-01

    Uncertain hydrological impacts of climate change, population growth and institutional changes pose a major challenge to planning of water supply systems. Planners seek optimal portfolios of supply and demand management schemes but also when to activate assets whilst considering many system goals and plausible futures. Incorporation of scheduling into the planning under uncertainty problem strongly increases its complexity. We investigate some approaches to scheduling with many-objective heuristic search. We apply a multi-scenario many-objective scheduling approach to the Thames River basin water supply system planning problem in the UK. Decisions include which new supply and demand schemes to implement, at what capacity and when. The impact of different system uncertainties on scheme implementation schedules are explored, i.e. how the choice of future scenarios affects the search process and its outcomes. The activation of schemes is influenced by the occurrence of extreme hydrological events in the ensemble of plausible scenarios and other factors. The approach and results are compared with a previous study where only the portfolio problem is addressed (without scheduling).

  3. Methodology for qualitative uncertainty assessment of climate impact indicators

    NASA Astrophysics Data System (ADS)

    Otto, Juliane; Keup-Thiel, Elke; Rechid, Diana; Hänsler, Andreas; Pfeifer, Susanne; Roth, Ellinor; Jacob, Daniela

    2016-04-01

    The FP7 project "Climate Information Portal for Copernicus" (CLIPC) is developing an integrated platform of climate data services to provide a single point of access for authoritative scientific information on climate change and climate change impacts. In this project, the Climate Service Center Germany (GERICS) has been in charge of the development of a methodology on how to assess the uncertainties related to climate impact indicators. Existing climate data portals mainly treat the uncertainties in two ways: Either they provide generic guidance and/or express with statistical measures the quantifiable fraction of the uncertainty. However, none of the climate data portals give the users a qualitative guidance how confident they can be in the validity of the displayed data. The need for such guidance was identified in CLIPC user consultations. Therefore, we aim to provide an uncertainty assessment that provides the users with climate impact indicator-specific guidance on the degree to which they can trust the outcome. We will present an approach that provides information on the importance of different sources of uncertainties associated with a specific climate impact indicator and how these sources affect the overall 'degree of confidence' of this respective indicator. To meet users requirements in the effective communication of uncertainties, their feedback has been involved during the development process of the methodology. Assessing and visualising the quantitative component of uncertainty is part of the qualitative guidance. As visual analysis method, we apply the Climate Signal Maps (Pfeifer et al. 2015), which highlight only those areas with robust climate change signals. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Reference Pfeifer, S., Bülow, K., Gobiet, A., Hänsler, A., Mudelsee, M., Otto, J., Rechid, D., Teichmann, C. and Jacob, D.: Robustness of Ensemble Climate Projections

  4. Administrative automation in a scientific environment

    NASA Technical Reports Server (NTRS)

    Jarrett, J. R.

    1984-01-01

    Although the scientific personnel at GSFC were advanced in the development and use of hardware and software for scientific applications, resistance to the use of automation or purchase of terminals, software and services, specifically for administrative functions was widespread. The approach used to address problems and constraints and plans for administrative automation within the Space and Earth Sciences Directorate are delineated. Accomplishments thus far include reduction of paperwork and manual efforts; improved communications through telemail and committees; additional support staff; increased awareness at all levels on ergonomic concerns and the need for training; better equipment; improved ADP skills through experience; management commitment; and an overall strategy for automating.

  5. RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY

    SciTech Connect

    Salaymeh, S.; Ashley, W.; Jeffcoat, R.

    2010-06-17

    It is difficult to overestimate the importance that physical measurements performed with nondestructive assay instruments play throughout the nuclear fuel cycle. They underpin decision making in many areas and support: criticality safety, radiation protection, process control, safeguards, facility compliance, and waste measurements. No physical measurement is complete or indeed meaningful, without a defensible and appropriate accompanying statement of uncertainties and how they combine to define the confidence in the results. The uncertainty budget should also be broken down in sufficient detail suitable for subsequent uses to which the nondestructive assay (NDA) results will be applied. Creating an uncertainty budget and estimating the total measurement uncertainty can often be an involved process, especially for non routine situations. This is because data interpretation often involves complex algorithms and logic combined in a highly intertwined way. The methods often call on a multitude of input data subject to human oversight. These characteristics can be confusing and pose a barrier to developing and understanding between experts and data consumers. ASTM subcommittee C26-10 recognized this problem in the context of how to summarize and express precision and bias performance across the range of standards and guides it maintains. In order to create a unified approach consistent with modern practice and embracing the continuous improvement philosophy a consensus arose to prepare a procedure covering the estimation and reporting of uncertainties in non destructive assay of nuclear materials. This paper outlines the needs analysis, objectives and on-going development efforts. In addition to emphasizing some of the unique challenges and opportunities facing the NDA community we hope this article will encourage dialog and sharing of best practice and furthermore motivate developers to revisit the treatment of measurement uncertainty.

  6. Seabed variability and its influence on acoustic prediction uncertainty

    NASA Astrophysics Data System (ADS)

    Holland, Charles W.; Calder, Brian; Kraft, Barbara; Mayer, Larry; Goff, John; Harrison, Chris

    2005-09-01

    Kevin LePage (Naval Research Laboratory, Washington, DC), Robert I. Odom (University of Washington, Applied Physics Laboratory), Irina Overeem, James Syvitski (University of Colorado, INSTAAR, Boulder, CO) and Lincoln Pratson (Duke University, Durham, NC). The weakest link in performance prediction for naval systems operating in coastal regions is the environmental data that drive the models. In shallow-water downward refracting environments, the seabed properties and morphology often are the controlling environmental factors. In order to address the issue of uncertainty in seabed properties, we focused on two overarching goals: (1) assess and characterize seafloor variability in shelf environments, (2) determine the impact of the seafloor variability on acoustic prediction uncertainty. Our inherently multidisciplinary approach brought marine geology/geophysics and ocean acoustics together at the intersection of geoacoustic modeling. This talk will review results from a 3-year collaboration under the ONR Capturing Uncertainty DRI. [Work supported by the Office of Naval Research.

  7. Entropic uncertainty and measurement reversibility

    NASA Astrophysics Data System (ADS)

    Berta, Mario; Wehner, Stephanie; Wilde, Mark M.

    2015-11-01

    The entropic uncertainty relation with quantum side information (EUR-QSI) from [Berta et al., Nat. Phys. 6, 659 (2010)] is a unifying principle relating two distinctive features of quantum mechanics: quantum uncertainty due to measurement incompatibility, and entanglement. In these relations, quantum uncertainty takes the form of preparation uncertainty where one of two incompatible measurements is applied. In particular, the "uncertainty witness" lower bound in the EUR-QSI is not a function of a post-measurement state. An insightful proof of the EUR-QSI from [Coles et al., Phys. Rev. Lett. 108, 210405 (2012)] makes use of a fundamental mathematical consequence of the postulates of quantum mechanics known as the non-increase of quantum relative entropy under quantum channels. Here, we exploit this perspective to establish a tightening of the EUR-QSI which adds a new state-dependent term in the lower bound, related to how well one can reverse the action of a quantum measurement. As such, this new term is a direct function of the post-measurement state and can be thought of as quantifying how much disturbance a given measurement causes. Our result thus quantitatively unifies this feature of quantum mechanics with the others mentioned above. We have experimentally tested our theoretical predictions on the IBM Quantum Experience and find reasonable agreement between our predictions and experimental outcomes.

  8. Uncertainty Quantification for Airfoil Icing

    NASA Astrophysics Data System (ADS)

    DeGennaro, Anthony Matteo

    Ensuring the safety of airplane flight in icing conditions is an important and active arena of research in the aerospace community. Notwithstanding the research, development, and legislation aimed at certifying airplanes for safe operation, an analysis of the effects of icing uncertainties on certification quantities of interest is generally lacking. The central objective of this thesis is to examine and analyze problems in airfoil ice accretion from the standpoint of uncertainty quantification. We focus on three distinct areas: user-informed, data-driven, and computational uncertainty quantification. In the user-informed approach to uncertainty quantification, we discuss important canonical icing classifications and show how these categories can be modeled using a few shape parameters. We then investigate the statistical effects of these parameters. In the data-driven approach, we build statistical models of airfoil ice shapes from databases of actual ice shapes, and quantify the effects of these parameters. Finally, in the computational approach, we investigate the effects of uncertainty in the physics of the ice accretion process, by perturbing the input to an in-house numerical ice accretion code that we develop in this thesis.

  9. Entropic uncertainty and measurement reversibility

    NASA Astrophysics Data System (ADS)

    Berta, Mario; Wehner, Stephanie; Wilde, Mark M.

    2016-07-01

    The entropic uncertainty relation with quantum side information (EUR-QSI) from (Berta et al 2010 Nat. Phys. 6 659) is a unifying principle relating two distinctive features of quantum mechanics: quantum uncertainty due to measurement incompatibility, and entanglement. In these relations, quantum uncertainty takes the form of preparation uncertainty where one of two incompatible measurements is applied. In particular, the ‘uncertainty witness’ lower bound in the EUR-QSI is not a function of a post-measurement state. An insightful proof of the EUR-QSI from (Coles et al 2012 Phys. Rev. Lett. 108 210405) makes use of a fundamental mathematical consequence of the postulates of quantum mechanics known as the non-increase of quantum relative entropy under quantum channels. Here, we exploit this perspective to establish a tightening of the EUR-QSI which adds a new state-dependent term in the lower bound, related to how well one can reverse the action of a quantum measurement. As such, this new term is a direct function of the post-measurement state and can be thought of as quantifying how much disturbance a given measurement causes. Our result thus quantitatively unifies this feature of quantum mechanics with the others mentioned above. We have experimentally tested our theoretical predictions on the IBM quantum experience and find reasonable agreement between our predictions and experimental outcomes.

  10. Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments

    USGS Publications Warehouse

    Littell, Jeremy S.; Mauger, Guillaume S.; Salathe, Eric P.; Hamlet, Alan F.; Lee, Se-Yeun; Stumbaugh, Matt R.; Elsner, Marketa; Norheim, Robert; Lutz, Eric R.; Mantua, Nathan J.

    2014-01-01

    The purpose of this project was to (1) provide an internally-consistent set of downscaled projections across the Western U.S., (2) include information about projection uncertainty, and (3) assess projected changes of hydrologic extremes. These objectives were designed to address decision support needs for climate adaptation and resource management actions. Specifically, understanding of uncertainty in climate projections – in particular for extreme events – is currently a key scientific and management barrier to adaptation planning and vulnerability assessment. The new dataset fills in the Northwest domain to cover a key gap in the previous dataset, adds additional projections (both from other global climate models and a comparison with dynamical downscaling) and includes an assessment of changes to flow and soil moisture extremes. This new information can be used to assess variations in impacts across the landscape, uncertainty in projections, and how these differ as a function of region, variable, and time period. In this project, existing University of Washington Climate Impacts Group (UW CIG) products were extended to develop a comprehensive data archive that accounts (in a reigorous and physically based way) for climate model uncertainty in future climate and hydrologic scenarios. These products can be used to determine likely impacts on vegetation and aquatic habitat in the Pacific Northwest (PNW) region, including WA, OR, ID, northwest MT to the continental divide, northern CA, NV, UT, and the Columbia Basin portion of western WY New data series and summaries produced for this project include: 1) extreme statistics for surface hydrology (e.g. frequency of soil moisture and summer water deficit) and streamflow (e.g. the 100-year flood, extreme 7-day low flows with a 10-year recurrence interval); 2) snowpack vulnerability as indicated by the ratio of April 1 snow water to cool-season precipitation; and, 3) uncertainty analyses for multiple climate

  11. Cascading rainfall uncertainty into flood inundation impact models

    NASA Astrophysics Data System (ADS)

    Souvignet, Maxime; Freer, Jim E.; de Almeida, Gustavo A. M.; Coxon, Gemma; Neal, Jeffrey C.; Champion, Adrian J.; Cloke, Hannah L.; Bates, Paul D.

    2014-05-01

    Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade, and how best to approach this, is still poorly understood. This requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and finally the hydraulic flood wave propagation based on the runoff predictions. Improving the characterisation of uncertainty, and what is important to include, in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures using the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions that are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated

  12. Uncertainty and urban water recharge for managing groundwater availability using decision support.

    PubMed

    Passarello, M C; Pierce, S A; Sharp, J M

    2014-01-01

    Quantifying groundwater availability depends upon sound methods and the use of integrated models. To determine availability or sustainable yield, the influence of scientific uncertainty from key sources, such as anthropogenic recharge, must be considered. This study evaluates uncertainty in recharge interpretations on the modeled available water balance for an urban case in Texas, USA. Analyses are completed using the Groundwater Decision Support System, which is a research code-base for an integrated modeling. The case study develops spatially and temporally resolved recharge interpretations based on NEXRAD precipitation and detailed land use data. Results demonstrate the implications of scientific uncertainty as it influences recommendations for policy and urban water management decisions that are based on modeled outputs. Geospatial methods account for spatial and temporal components and can be replicated for other systems. These methods are also useful for resolving uncertainty in relation to the influence of urbanization on recharge through land use change.

  13. OPENING ADDRESS: Heterostructures in Semiconductors

    NASA Astrophysics Data System (ADS)

    Grimmeiss, Hermann G.

    1996-01-01

    Good morning, Gentlemen! On behalf of the Nobel Foundation, I should like to welcome you to the Nobel Symposium on "Heterostructures in Semiconductors". It gives me great pleasure to see so many colleagues and old friends from all over the world in the audience and, in particular, to bid welcome to our Nobel laureates, Prof. Esaki and Prof. von Klitzing. In front of a different audience I would now commend the scientific and technological importance of heterostructures in semiconductors and emphatically emphasise that heterostructures, as an important contribution to microelectronics and, hence, information technology, have changed societies all over the world. I would also mention that information technology is one of the most important global key industries which covers a wide field of important areas each of which bears its own character. Ever since the invention of the transistor, we have witnessed a fantastic growth in semiconductor technology, leading to more complex functions and higher densities of devices. This development would hardly be possible without an increasing understanding of semiconductor materials and new concepts in material growth techniques which allow the fabrication of previously unknown semiconductor structures. But here and today I will not do it because it would mean to carry coals to Newcastle. I will therefore not remind you that heterostructures were already suggested and discussed in detail a long time before proper technologies were available for the fabrication of such structures. Now, heterostructures are a foundation in science and part of our everyday life. Though this is certainly true, it is nevertheless fair to say that not all properties of heterostructures are yet understood and that further technologies have to be developed before a still better understanding is obtained. The organisers therefore hope that this symposium will contribute not only to improving our understanding of heterostructures but also to opening new

  14. Improved best estimate plus uncertainty methodology including advanced validation concepts to license evolving nuclear reactors

    SciTech Connect

    Unal, Cetin; Williams, Brian; Mc Clure, Patrick; Nelson, Ralph A

    2010-01-01

    Many evolving nuclear energy programs plan to use advanced predictive multi-scale multi-physics simulation and modeling capabilities to reduce cost and time from design through licensing. Historically, the role of experiments was primary tool for design and understanding of nuclear system behavior while modeling and simulation played the subordinate role of supporting experiments. In the new era of multi-scale multi-physics computational based technology development, the experiments will still be needed but they will be performed at different scales to calibrate and validate models leading predictive simulations. Cost saving goals of programs will require us to minimize the required number of validation experiments. Utilization of more multi-scale multi-physics models introduces complexities in the validation of predictive tools. Traditional methodologies will have to be modified to address these arising issues. This paper lays out the basic aspects of a methodology that can be potentially used to address these new challenges in design and licensing of evolving nuclear technology programs. The main components of the proposed methodology are verification, validation, calibration, and uncertainty quantification. An enhanced calibration concept is introduced and is accomplished through data assimilation. The goal is to enable best-estimate prediction of system behaviors in both normal and safety related environments. To achieve this goal requires the additional steps of estimating the domain of validation and quantification of uncertainties that allow for extension of results to areas of the validation domain that are not directly tested with experiments, which might include extension of the modeling and simulation (M&S) capabilities for application to full-scale systems. The new methodology suggests a formalism to quantify an adequate level of validation (predictive maturity) with respect to required selective data so that required testing can be minimized for cost

  15. Anatomy of scientific evolution.

    PubMed

    Yun, Jinhyuk; Kim, Pan-Jun; Jeong, Hawoong

    2015-01-01

    The quest for historically impactful science and technology provides invaluable insight into the innovation dynamics of human society, yet many studies are limited to qualitative and small-scale approaches. Here, we investigate scientific evolution through systematic analysis of a massive corpus of digitized English texts between 1800 and 2008. Our analysis reveals great predictability for long-prevailing scientific concepts based on the levels of their prior usage. Interestingly, once a threshold of early adoption rates is passed even slightly, scientific concepts can exhibit sudden leaps in their eventual lifetimes. We developed a mechanistic model to account for such results, indicating that slowly-but-commonly adopted science and technology surprisingly tend to have higher innate strength than fast-and-commonly adopted ones. The model prediction for disciplines other than science was also well verified. Our approach sheds light on unbiased and quantitative analysis of scientific evolution in society, and may provide a useful basis for policy-making.

  16. Ethics of scientific publication

    PubMed Central

    Mandal, Jharna; Ponnambath, Dinoop Korol; Parija, Subhash Chandra

    2016-01-01

    Published scientific research breeds the development of clinical management guidelines and pathways. Currently, scholarly proficiency is assessed using numerous primitive metrics for incentives that can kindle publication of hoax or flawed research content. Such flawed data can lead to wastage of resources, time, and most importantly harm to the society. Authors, editors, and peer reviewers need to be genuine in conducting, analyzing, and publication of scientific research. Institutions need to be aware and utilize advanced metrics to assess the scientific reputation of researchers. This short review discusses in brief the common authorship and editorial ethical issues encountered in scientific publication and the newer metrics available for the assessment of scholarly excellence. Editors and peer reviewers need to be acquainted with the common ethical issues and follow consensus international guidelines on publication ethics to tackle them appropriately. PMID:27722097

  17. Anatomy of Scientific Evolution

    PubMed Central

    Yun, Jinhyuk; Kim, Pan-Jun; Jeong, Hawoong

    2015-01-01

    The quest for historically impactful science and technology provides invaluable insight into the innovation dynamics of human society, yet many studies are limited to qualitative and small-scale approaches. Here, we investigate scientific evolution through systematic analysis of a massive corpus of digitized English texts between 1800 and 2008. Our analysis reveals great predictability for long-prevailing scientific concepts based on the levels of their prior usage. Interestingly, once a threshold of early adoption rates is passed even slightly, scientific concepts can exhibit sudden leaps in their eventual lifetimes. We developed a mechanistic model to account for such results, indicating that slowly-but-commonly adopted science and technology surprisingly tend to have higher innate strength than fast-and-commonly adopted ones. The model prediction for disciplines other than science was also well verified. Our approach sheds light on unbiased and quantitative analysis of scientific evolution in society, and may provide a useful basis for policy-making. PMID:25671617

  18. STARPROBE: Scientific rationale

    NASA Technical Reports Server (NTRS)

    Underwood, J. H. (Editor); Randolph, J. E. (Editor)

    1982-01-01

    The scientific rationale and instrumentation problems in the areas of solar internal dynamics and relativity, solar plasma and particle dynamics, and solar atmosphere structure were studied. Current STARPROBE mission and system design concepts are summarized.

  19. Report: Scientific Software.

    ERIC Educational Resources Information Center

    Borman, Stuart A.

    1985-01-01

    Discusses various aspects of scientific software, including evaluation and selection of commercial software products; program exchanges, catalogs, and other information sources; major data analysis packages; statistics and chemometrics software; and artificial intelligence. (JN)

  20. Scientific data requirements

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Each Scientific Data Requirement (SDR) is summarized in terms of professional discipline, research program, technical description, related parameters, geographical extent, resolution, error tolerance,space-based sensors systems, personnel, implementation expert, notes, and references.