Visualizing DIII-D Tokarnak Magnetic Field Lines

We demonstrate the use of a combination of perceptually effective techniques for visualizing magnetic field data from the DIII-D Tokamak. These techniques can be implemented to run very efficiently on machines with hardware support for OpenGL. Interactive speeds facilitate clear communication of magnetic field structure, enhancing fusion scientists' understanding of their data, and thereby accelerating their research

Science-Driven Network Requirements for ESnet

The Energy Sciences Network (ESnet) is the primary providerof network connectivity for the US Department of Energy Office ofScience, the single largest supporter of basic research in the physicalsciences in the United States. In support of the Office of Scienceprograms, ESnet regularly updates and refreshes its understanding of thenetworking requirements of the instruments, facilities and scientiststhat it serves. This focus has helped ESnet to be a highly successfulenabler of scientific discovery for over 20 years. In August, 2002 theDOE Office of Science organized a workshop to characterize the networkingrequirements for Office of Science programs. Networking and middlewarerequirements were solicited from a representative group of scienceprograms. The workshop was summarized in two documents the workshop finalreport and a set of appendixes. This document updates the networkingrequirements for ESnet as put forward by the science programs listed inthe 2002 workshop report. In addition, three new programs have beenadded. Theinformation was gathered through interviews with knowledgeablescientists in each particular program or field

Cysteamine inhibits lysosomal oxidation of low density lipoprotein in human macrophages and reduces atherosclerosis in mice

Background and aims: We have shown previously that low density lipoprotein (LDL) aggregated by vortexing is internalised by macrophages and oxidised by iron in lysosomes to form the advanced lipid/protein oxidation product ceroid. We have now used sphingomyelinase-aggregated LDL, a more pathophysiological form of aggregated LDL, to study lysosomal oxidation of LDL and its inhibition by antioxidants, including cysteamine (2-aminoethanethiol) which concentrates in lysosomes by several orders of magnitude. We have also investigated the effect of cysteamine on atherosclerosis in mice. Methods: LDL was incubated with sphingomyelinase, which increased its average particle diameter from 26 to 170 nm, and was then incubated for up to 7 days with human monocyte-derived macrophages. LDL receptor-deficient mice were fed a Western diet (19-22 per group) and some given cysteamine in their drinking water at a dose equivalent to that used in cystinosis patients. The extent of atherosclerosis in the aortic root and the rest of the aorta was measured. Results: Confocal microscopy revealed lipid accumulation in lysosomes in the cultured macrophages. Large amounts of ceroid were produced, which colocalised with the lysosomal marker LAMP2. The antioxidants cysteamine, butylated hydroxytoluene, amifostine and its active metabolite WR-1065, inhibited the production of ceroid. Cysteamine at concentrations well below those expected to be present in lysosomes inhibited the oxidation of LDL by iron ions at lysosomal pH (pH 4.5) for prolonged periods. Finally, we showed that the extent of atherosclerotic lesions in the aortic root and arch of mice was significantly reduced by cysteamine. Conclusions: These results support our hypothesis that lysosomal oxidation of LDL is important in atherosclerosis and hence antioxidant drugs that concentrate in lysosomes might provide a novel therapy for this disease

A National Collaboratory to Advance the Science of High Temperature Plasma Physics for Magnetic Fusion

This report summarizes the work of the National Fusion Collaboratory (NFC) Project to develop a persistent infrastructure to enable scientific collaboration for magnetic fusion research. The original objective of the NFC project was to develop and deploy a national FES Grid (FusionGrid) that would be a system for secure sharing of computation, visualization, and data resources over the Internet. The goal of FusionGrid was to allow scientists at remote sites to participate as fully in experiments and computational activities as if they were working on site thereby creating a unified virtual organization of the geographically dispersed U.S. fusion community. The vision for FusionGrid was that experimental and simulation data, computer codes, analysis routines, visualization tools, and remote collaboration tools are to be thought of as network services. In this model, an application service provider (ASP provides and maintains software resources as well as the necessary hardware resources. The project would create a robust, user-friendly collaborative software environment and make it available to the US FES community. This Grid's resources would be protected by a shared security infrastructure including strong authentication to identify users and authorization to allow stakeholders to control their own resources. In this environment, access to services is stressed rather than data or software portability

Sulforaphane restores cellular glutathione levels and reduces chronic periodontitis neutrophil hyperactivity in vitro

The production of high levels of reactive oxygen species by neutrophils is associated with the local and systemic destructive phenotype found in the chronic inflammatory disease periodontitis. In the present study, we investigated the ability of sulforaphane (SFN) to restore cellular glutathione levels and reduce the hyperactivity of circulating neutrophils associated with chronic periodontitis. Using differentiated HL60 cells as a neutrophil model, here we show that generation of extracellular O2 . - by the nicotinamide adenine dinucleotide (NADPH) oxidase complex is increased by intracellular glutathione depletion. This may be attributed to the upregulation of thiol regulated acid sphingomyelinase driven lipid raft formation. Intracellular glutathione was also lower in primary neutrophils from periodontitis patients and, consistent with our previous findings, patients neutrophils were hyper-reactive to stimuli. The activity of nuclear factor erythroid-2-related factor 2 (Nrf2), a master regulator of the antioxidant response, is impaired in circulating neutrophils from chronic periodontitis patients. Although patients' neutrophils exhibit a low reduced glutathione (GSH)/oxidised glutathione (GSSG) ratio and a higher total Nrf2 level, the DNA-binding activity of nuclear Nrf2 remained unchanged relative to healthy controls and had reduced expression of glutamate cysteine ligase catalytic (GCLC), and modifier (GCLM) subunit mRNAs, compared to periodontally healthy subjects neutrophils. Pre-treatment with SFN increased expression of GCLC and GCM, improved intracellular GSH/GSSG ratios and reduced agonist-activated extracellular O2 . - production in both dHL60 and primary neutrophils from patients with periodontitis and controls. These findings suggest that a deficiency in Nrf2-dependent pathways may underpin susceptibility to hyper-reactivity in circulating primary neutrophils during chronic periodontitis. © 2013 Dias et al

The impact of high-emission event duration on the effectiveness of monthly, quarterly, semi-annual and annual emission measurements

Methane emission measurements are important elements in quantifying and mitigating methane emissions from oil and gas systems. Short duration remote sensing measurements of methane emissions are becoming economically feasible and deployable at large scale, but interpretation of these snapshot measurements is complex due to the inherent spatial and temporal variability of methane emissions. Even if measurement technologies have no uncertainty, short duration sampling of these complex temporal emission patterns introduces a sampling uncertainty. This work examines the sampling uncertainties associated with monthly, quarterly, semi-annual and annual short-duration measurements of methane emissions for a group of fifty sample sites selected to replicate conditions in the Barnett Shale oil and gas production region. One of the key characteristics of Barnett Shale methane emissions is the presence of high-emission rate events which contribute to approximately half of total emissions. These high-emission events typically account for only 1-2% of emission rate observations in the Barnett Shale and are of uncertain duration. Analyses were conducted to assess how the duration of these high-emission events impacts the accuracy of remote sensing measurements of methane emissions, conducted with frequencies ranging from monthly to annual. Emissions from pneumatic controllers, pneumatic pumps, tanks, and leaks, which collectively account for approximately half of emissions in the Barnett Shale, are accurately captured with annual sampling frequencies. The addition of high-emission events increases the required number of measurements to maintain a targeted level of uncertainty, even under the assumption of no measurement uncertainty. If emission events have a one-week duration, a monthly sampling frequency has an estimated sampling error >15% for the types of sources in the Barnett Shale, due to the inherent variability of the magnitudes of the high emission rate events. The error associated with short-duration sampling increases as the duration of the high-emission events becomes shorter, suggesting that understanding the temporal persistence of significant emission events is important to consider when designing measurement protocols

Methods for spatial extrapolation of methane measurements in constructing regional estimates from sample populations

Reporting initiatives for methane emissions from oil and gas operations are broadly shifting towards measurement-informed inventories. Measurement campaigns typically measure a subpopulation of facilities, and these measurements are extrapolated to a larger region or basin. Methane emissions from oil and gas systems are inherently variable and intermittent, which makes it difficult to determine whether a sample population is sufficiently large to be representative of a larger region. This work proposes a framework using a case study of an operator in the Green River Basin that assesses selection of sample populations, extrapolation of measurements to a larger region, and methods for estimating the error associated with extrapolation. This work also identifies a new metric, the capture ratio, which has a strong correlation with extrapolation error (Spearman’s correlation coefficient = -0.75). The strength of this correlation between the capture ratio, which takes into account the skewness of source-level emissions, and extrapolation error suggests that understanding the distributions of source-level emissions distributions is necessary when identifying sample populations and extrapolating measurements. The results from this work can be broadly applied to inform the selection and extrapolation of site measurements when developing methane emission inventories

Impact of the High-Emission Event Duration and Sampling Frequency on the Uncertainty in Emission Estimates

Short duration remote sensing measurements of methane emissions from oil and gas operations are being deployed at a large scale, but interpretation of these snapshot measurements is complex due to the spatial and temporal variability of methane emissions. The accuracy and precision of annual emission estimates extrapolated from short duration measurements depend on the measurement frequency and complexity of temporal emission patterns. This work examines sampling uncertainties associated with short duration measurements of varying frequencies for methane emissions from a group of sites representing the Barnett Shale region. Routine, frequent emissions are accurately captured with minimal bias through semiannual sampling; however, infrequent high-emission rate events increase the error associated with annual emission estimates, even under the assumption of no measurement uncertainty. If emission events have a duration of ≤1 week, monthly sampling has an estimated sampling error of >15%. For quarterly sampling with emission events that persist for ≤1 month, the sampling error is >30%. There is also negative bias associated with quarterly, semiannual, and annual sampling, which suggests infrequent campaigns may be systemically underestimating emissions. The sampling error increases as the duration of the high-emission events becomes shorter, making the temporal persistence of emission events an important factor in designing measurement protocols