Preliminary estimates of environmental exposure for fuel and exhaust products, volume i. part i- methods and preliminary estimates for msfc. part 2- recommended experimental design for msfc

Environmental exposure for fuel and exhaust products with preliminary estimate

Curate and storyspace: an ontology and web-based environment for describing curatorial narratives

Existing metadata schemes and content management systems used by museums focus on describing the heritage objects that the museum holds in its collection. These are used to manage and describe individual heritage objects according to properties such as artist, date and preservation requirements. Curatorial narratives, such as physical or online exhibitions tell a story that spans across heritage objects and have a meaning that does not necessarily reside in the individual heritage objects themselves. Here we present curate, an ontology for describing curatorial narratives. This draws on structuralist accounts that distinguish the narrative from the story and plot, and also a detailed analysis of two museum exhibitions and the curatorial processes that contributed to them. Storyspace, our web based interface and API to the ontology, is being used by curatorial staff in two museums to model curatorial narratives and the processes through which they are constructed

High Rayleigh number convection with double diffusive fingers

An electrodeposition cell is used to sustain a destabilizing concentration difference of copper ions in aqueous solution between the top and bottom boundaries of the cell. The resulting convecting motion is analogous to Rayleigh-B\'enard convection at high Prandtl numbers. In addition, a stabilizing temperature gradient is imposed across the cell. Even for thermal buoyancy two orders of magnitude smaller than chemical buoyancy, the presence of the weak stabilizing gradient has a profound effect on the convection pattern. Double diffusive fingers appear in all cases. The size of these fingers and the flow velocities are independent of the height of the cell, but they depend on the ion concentration difference between top and bottom boundaries as well as on the imposed temperature gradient. The scaling of the mass transport is compatible with previous results on double diffusive convection

Affinity Chromatography: A Historical Perspective

Affinity chromatography is one of the most selective and versatile forms of liquid chromatography for the separation or analysis of chemicals in complex mixtures. This method makes use of a biologically related agent as the stationary phase, which provides an affinity column with the ability to bind selectively and reversibly to a given target in a sample. This review examines the early work in this method and various developments that have lead to the current status of this technique. The general principles of affinity chromatography are briefly described as part of this discussion. Past and recent efforts in the generation of new binding agents, supports, and immobilization methods for this method are considered. Various applications of affinity chromatography are also summarized, as well as the influence this field has played in the creation of other affinity-based separation or analysis methods

Multiresolution community detection for megascale networks by information-based replica correlations

We use a Potts model community detection algorithm to accurately and quantitatively evaluate the hierarchical or multiresolution structure of a graph. Our multiresolution algorithm calculates correlations among multiple copies ("replicas") of the same graph over a range of resolutions. Significant multiresolution structures are identified by strongly correlated replicas. The average normalized mutual information, the variation of information, and other measures in principle give a quantitative estimate of the "best" resolutions and indicate the relative strength of the structures in the graph. Because the method is based on information comparisons, it can in principle be used with any community detection model that can examine multiple resolutions. Our approach may be extended to other optimization problems. As a local measure, our Potts model avoids the "resolution limit" that affects other popular models. With this model, our community detection algorithm has an accuracy that ranks among the best of currently available methods. Using it, we can examine graphs over 40 million nodes and more than one billion edges. We further report that the multiresolution variant of our algorithm can solve systems of at least 200000 nodes and 10 million edges on a single processor with exceptionally high accuracy. For typical cases, we find a super-linear scaling, O(L^{1.3}) for community detection and O(L^{1.3} log N) for the multiresolution algorithm where L is the number of edges and N is the number of nodes in the system.Comment: 19 pages, 14 figures, published version with minor change

Non-Competitive Peak Decay Analysis Of Drugprotein Dissociation By High-Performance Affinity Chromatography

The peak decay method is an affinity chromatographic technique that has been used to examine the dissociation of solutes from immobilized ligands in the presence of excess displacing agent. However, it can be difficult to find a displacing agent that does not interfere with detection of the eluting analyte. In this study, a non-competitive peak decay method was developed in which no displacing agent was required for analyte elution. This method was evaluated for the study of drug-protein interactions by using it along with high-performance affinity chromatography to measure the dissociation rate constants for R- and S-warfarin from columns containing immobilized human serum albumin (HSA). Several factors were considered in the optimization of this method, including the amount of applied analyte, the column size, and the flow rate. The dissociation rate constants for R- and S-warfarin from HSA were measured at several temperatures by this approach, giving values of 0.56 (± 0.01) and 0.66 (± 0.01) s−1 at pH 7.4 and 37°C. These results were in good agreement with previous values obtained by other methods. This approach is not limited to warfarin and HSA but could be employed in studying additional drug-protein interactions or other systems with weak-to-moderate binding

Adenosine-induced ST segment depression with normal perfusion

Background: Intravenous adenosine in conjunction with myocardial perfusion imaging is commonly used for the detection of coronary artery disease and risk assessment. We have previously shown that patients with ischemic changes on the 12-lead electrocardiogram (ECG) in response to adenosine but with normal perfusion pattern have a benign outcome on shortintermediate follow-up. The long-term outcome of these patients is unknown. Methods: Patients with ischemic ECG response (≥ 1 mm ST depression) to adenosine infusion but with normal perfusion on single-photon emission computed tomography (SPECT) imaging in the absence of a history of myocardial infarction or coronary revascularization were followed up for mortality, myocardial infarctions, and coronary revascularization. Results: The cohort consisted of 73 patients (81% women) who were followed up for mortality for a mean of 61 ± 15 months. There were 10 deaths, and the cause of death was determined to be non-cardiac in half of those. Follow-up for the other endpoints was complete for 21 ± 10 months during which no patient had myocardial infarction and seven underwent coronary revascularization. Conclusions: Patients with ischemic ECG response to intravenous adenosine administration and normal perfusion on SPECT are at low risk of cardiovascular events. The ST segment response to adenosine in this setting is likely related to non-ischemic mechanisms

Non-Competitive Peak Decay Analysis Of Drugprotein Dissociation By High-Performance Affinity Chromatography

The peak decay method is an affinity chromatographic technique that has been used to examine the dissociation of solutes from immobilized ligands in the presence of excess displacing agent. However, it can be difficult to find a displacing agent that does not interfere with detection of the eluting analyte. In this study, a non-competitive peak decay method was developed in which no displacing agent was required for analyte elution. This method was evaluated for the study of drug-protein interactions by using it along with high-performance affinity chromatography to measure the dissociation rate constants for R- and S-warfarin from columns containing immobilized human serum albumin (HSA). Several factors were considered in the optimization of this method, including the amount of applied analyte, the column size, and the flow rate. The dissociation rate constants for R- and S-warfarin from HSA were measured at several temperatures by this approach, giving values of 0.56 (± 0.01) and 0.66 (± 0.01) s−1 at pH 7.4 and 37°C. These results were in good agreement with previous values obtained by other methods. This approach is not limited to warfarin and HSA but could be employed in studying additional drug-protein interactions or other systems with weak-to-moderate binding

Robust Structured Low-Rank Approximation on the Grassmannian

Over the past years Robust PCA has been established as a standard tool for reliable low-rank approximation of matrices in the presence of outliers. Recently, the Robust PCA approach via nuclear norm minimization has been extended to matrices with linear structures which appear in applications such as system identification and data series analysis. At the same time it has been shown how to control the rank of a structured approximation via matrix factorization approaches. The drawbacks of these methods either lie in the lack of robustness against outliers or in their static nature of repeated batch-processing. We present a Robust Structured Low-Rank Approximation method on the Grassmannian that on the one hand allows for fast re-initialization in an online setting due to subspace identification with manifolds, and that is robust against outliers due to a smooth approximation of the $\ell_p$-norm cost function on the other hand. The method is evaluated in online time series forecasting tasks on simulated and real-world data