Survey and Evaluate Uncertainty Quantification Methodologies

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models with uncertainty quantification, optimization, risk analysis and decision making capabilities. The CCSI Toolset will incorporate commercial and open-source software currently in use by industry and will also develop new software tools as necessary to fill technology gaps identified during execution of the project. The CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. The goal of CCSI is to deliver a toolset that can simulate the scale-up of a broad set of new carbon capture technologies from laboratory scale to full commercial scale. To provide a framework around which the toolset can be developed and demonstrated, we will focus on three Industrial Challenge Problems (ICPs) related to carbon capture technologies relevant to U.S. pulverized coal (PC) power plants. Post combustion capture by solid sorbents is the technology focus of the initial ICP (referred to as ICP A). The goal of the uncertainty quantification (UQ) task (Task 6) is to provide a set of capabilities to the user community for the quantification of uncertainties associated with the carbon capture processes. As such, we will develop, as needed and beyond existing capabilities, a suite of robust and efficient computational tools for UQ to be integrated into a CCSI UQ software framework

Touchscreen interventions and the wellbeing of people with dementia and caregivers: a systematic review

Background: Dementia can have significant detrimental impacts on the wellbeing of those with the disease and their carers. A range of computer-based interventions, including touchscreen-based interventions have been researched for use with this population in the hope that they might improve psychological wellbeing. This article reviews touchscreen-based interventions designed to be used by people with dementia, with a specific focus in assessing their impact on wellbeing. Method: The data bases, PsycInfo, ASSIA, Medline, CINAHL and Cochrane were searched for touchscreen-based interventions designed to be used by people with dementia with reported psychological wellbeing outcomes. Methodological quality was assessed using Pluye et al.’s (2011) Mixed Methods Appraisal Tool (MMAT) checklist. Results: Sixteen papers were eligible. They covered fourteen methodologically diverse interventions. Interventions were reported to be beneficial in relation to mental health, social interaction and sense of mastery. Touchscreen interventions also reportedly benefit informal carers in relation to their perceived burden and the quality of their relationships with the people they care for. Key aspects included the user interface, provision of support, learning style, tailored content, appropriate challenge, ergonomics and users’ dementia progression. Conclusions: Whilst much of the existing research is relatively small-scale, the findings tentatively suggest that touchscreen based interventions can improve the psychological wellbeing of people with dementia, and possibilities for more rigorous future research are suggested

Visual Distraction: An Altered Aiming Spatial Response in Dementia

Background/Aims: Healthy individuals demonstrate leftward bias on visuospatial tasks such as line bisection, which has been attributed to right brain dominance. We investigated whether this asymmetry occurred in patients with probable dementia of the Alzheimer type (pAD) which is associated with neurodegenerative changes affecting temporoparietal regions. Methods: Subjects with pAD and matched controls performed a line bisection task in near and far space under conditions of no distraction, left-sided visual distraction and right-sided visual distraction. Results: Participants with pAD manifested different motor-preparatory ‘aiming’ spatial bias than matched controls. There were significantly greater rightward ‘aiming’ motor-intentional errors both without distraction and with right-sided distraction. Conclusion: ‘Aiming’ motor-preparatory brain activity may be induced by distraction in pAD subjects as compared to typical visual-motor function in controls

Robustness of RISMC Insights under Alternative Aleatory/Epistemic Uncertainty Classifications: Draft Report under the Risk-Informed Safety Margin Characterization (RISMC) Pathway of the DOE Light Water Reactor Sustainability Program

The Risk-Informed Safety Margin Characterization (RISMC) pathway is a set of activities defined under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability Program. The overarching objective of RISMC is to support plant life-extension decision-making by providing a state-of-knowledge characterization of safety margins in key systems, structures, and components (SSCs). A technical challenge at the core of this effort is to establish the conceptual and technical feasibility of analyzing safety margin in a risk-informed way, which, unlike conventionally defined deterministic margin analysis, would be founded on probabilistic characterizations of uncertainty in SSC performance. In the context of probabilistic risk assessment (PRA) technology, there has arisen a general consensus about the distinctive roles of two types of uncertainty: aleatory and epistemic, where the former represents irreducible, random variability inherent in a system, whereas the latter represents a state of knowledge uncertainty on the part of the analyst about the system which is, in principle, reducible through further research. While there is often some ambiguity about how any one contributing uncertainty in an analysis should be classified, there has nevertheless emerged a broad consensus on the meanings of these uncertainty types in the PRA setting. However, while RISMC methodology shares some features with conventional PRA, it will nevertheless be a distinctive methodology set. Therefore, the paradigms for classification of uncertainty in the PRA setting may not fully port to the RISMC environment. Yet the notion of risk-informed margin is based on the characterization of uncertainty, and it is therefore critical to establish a common understanding of uncertainty in the RISMC setting

Variability in the Selection Patterns of Pronghorn: Are they Really Native Prairie Obligates?

In Canada, pronghorn (Antilocapra americana) are primarily considered a native prairie obligate because of their reliance on open grassland vegetation communities, although an assessment of local ecological knowledge suggests that pronghorn in Alberta select a variety of habitat from native prairie to cultivated lands. The primary objective of our study was to assess whether pronghorn in Alberta and Saskatchewan are native prairie obligates. Specifically, we addressed the following questions: 1) do individual pronghorn show similar selection patterns for native prairie and, therefore, support the notion that they are prairie obligates; 2) do pronghorn show consistent resource selection patterns at multiple scales (landscape and within-seasonal range); and 3) to what extent are selection patterns of pronghorn influenced by highways and roads. Within Alberta, we captured, collared, and monitored for one year individual female pronghorn in December 2003 (n = 24), March 2005 (n = 25), and March 2006 (n = 25). A detrended correspondence analysis of patterns of habitat selection revealed three distinct groups of pronghorn (r2 = 0.96, n = 55) that we labeled native, cultivated, and mixed, referring to the dominant land cover in their parturition ranges. We used logistic regression to model resource selection patterns of the three groups of pronghorn during the parturition and winter periods at the landscape and within-seasonal range scales. At the landscape scale, each group of pronghorn had top models consisting of the variables land cover, landform, distance to express highways, distance to arterial roads, and distance to collector roads for both periods. The native and mixed groups were less likely to use annual and perennial cropland than native prairie habitats, whereas the cultivated group was more likely to use annual and perennial cropland. At the within-seasonal range scale, the top models for each group in both seasons consisted of one or more road variables, but the top models exhibited poor model fit. Our results do not show a clear association for native prairie, which we would have expected if pronghorn were native prairie obligates, suggestive of plasticity in behavior. We acknowledge that patterns of habitat selection do not indicate habitat quality or fitness; therefore, to understand the individual- and population-level consequences of selecting sub-optimal habitats, such as agricultural landscapes, further research is needed

Health knowledge among the millennial generation

The Millennial Generation, also known as Generation Y, is the demographic cohort following Generation X, and is generally regarded to be composed of those individuals born between 1980 and 2000. They are the first to grow up in an environment where health-related information is widely available by internet, TV and other electronic media, yet we know very little about the scope of their health knowledge. This study was undertaken to quantify two domains of clinically relevant health knowledge: factual content and ability to solve health related questions (application) in nine clinically related medical areas. Study subjects correctly answered, on average, 75% of health application questions but only 54% of health content questions. Since students were better able to correctly answer questions dealing with applications compared to those on factual content contemporary US high school students may not use traditional hierarchical learning models in acquisition of their health knowledge

Apathy in frontotemporal dementia: Behavioral and neuroimaging correlates

Abstract. We investigated the occurrence of goal-directed motivational change in the form of apathy in patients with frontotemporal dementia (FTD), particularly those with behavioral variant social and executive deficits (bvFTD). Standardized behavioral inventory was employed to survey and compare apathy ratings from patients and caregivers. In cases of bvFTD, apathy ratings were further related to measures of social cognition, executive function, and atrophy on brain MRI. Results indicated that caregivers rated bvFTD patients as having significantly elevated apathy scores though patient self-ratings were normal. Caregiver and self-ratings of FTD samples with progressive nonfluent aphasia and semantic dementia did not differ from healthy controls and their informants. In the bvFTD sample, caregiver apathy scores were not correlated with general cognitive screening or depression scores, but were significantly correlated with social cognition and executive function measures. Voxel-based morphometry revealed that apathy ratings in bvFTD were related to prominent atrophy in the right caudate (including the ventral striatum), the right temporo-parietal junction, right posterior inferior and middle temporal gyri, and left frontal operculum-anterior insula region. Findings suggest that bvFTD is associated with a significant breakdown in goal-directed motivated behavior involving disruption of cortical-basal ganglia circuits that is also related to social and executive function deficits

Representative Atmospheric Plume Development for Elevated Releases

An atmospheric explosion of a low-yield nuclear device will produce a large number of radioactive isotopes, some of which can be measured with airborne detection systems. However, properly equipped aircraft may not arrive in the region where an explosion occurred for a number of hours after the event. Atmospheric conditions will have caused the radioactive plume to move and diffuse before the aircraft arrives. The science behind predicting atmospheric plume movement has advanced enough that the location of the maximum concentrations in the plume can be determined reasonably accurately in real time, or near real time. Given the assumption that an aircraft can follow a plume, this study addresses the amount of atmospheric dilution expected to occur in a representative plume as a function of time past the release event. The approach models atmospheric transport of hypothetical releases from a single location for every day in a year using the publically available HYSPLIT code. The effective dilution factors for the point of maximum concentration in an elevated plume based on a release of a non-decaying, non-depositing tracer can vary by orders of magnitude depending on the day of the release, even for the same number of hours after the release event. However, the median of the dilution factors based on releases for 365 consecutive days at one site follows a power law relationship in time, as shown in Figure S-1. The relationship is good enough to provide a general rule of thumb for estimating typical future dilution factors in a plume starting at the same point. However, the coefficients of the power law function may vary for different release point locations. Radioactive decay causes the effective dilution factors to decrease more quickly with the time past the release event than the dilution factors based on a non-decaying tracer. An analytical expression for the dilution factors of isotopes with different half-lives can be developed given the power law expression for the non-decaying tracer. If the power-law equation for the median dilution factor, Df, based on a non-decaying tracer has the general form Df=a〖×t〗^(-b) for time t after the release event, then the equation has the form Df=e^(-λt)×a×t^(-b) for a radioactive isotope, where λ is the decay constant for the isotope

Uranium in the Near-shore Aquatic Food Chain: Studies on Periphyton and Asian Clams

The benthic aquatic organisms in the near-shore environment of the Columbia River are the first biological receptors that can be exposed to groundwater contaminants coming from the U.S. Department of Energy's Hanford Site. The primary contaminant of concern in the former nuclear fuels processing area at the Site, known as the 300 Area, is uranium. Currently, there are no national clean up criteria for uranium and ecological receptors. This report summarizes efforts to characterize biological uptake of uranium in the food chain of the benthic aquatic organisms and provide information to be used in future assessments of uranium and the ecosystem