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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

From the Cluster Temperature Function to the Mass Function at Low Z

This XMM project consisted of three observations of the nearby, hot galaxy cluster Triangulum Australis, one of the cluster center and two offsets. The goal was to measure the radial gas temperature profile out to large radii and derive the total gravitating mass within the radius of average mass overdensity 500. The central pointing also provides data for a detailed two-dimensional gas temperature map of this interesting cluster. We have analyzed all three observations. The derivation of the temperature map using the central pointing is complete, and the paper is soon to be submitted. During the course of this study and of the analysis of archival XMM cluster observations, it became apparent that the commonly used XMM background flare screening techniques are often not accurate enough for studies of the cluster outer regions. The information on the cluster's total masses is contained at large off-center distances, and it is precisely the temperatures for those low-brightness regions that are most affected by the detector background anomalies. In particular, our two offset observations of the Triangulum have been contaminated by the background flares ("bad cosmic weather") to a degree where they could not be used for accurate spectral analysis. This forced us to expand the scope of our project. We needed to devise a more accurate method of screening and modeling the background flares, and to evaluate the uncertainty of the XMM background modeling. To do this, we have analyzed a large number of archival EPIC blank-field and closed-cover observations. As a result, we have derived stricter background screening criteria. It also turned out that mild flares affecting EPIC-pn can be modeled with an adequate accuracy. Such modeling has been used to derive our Triangulum temperature map. The results of our XMM background analysis, including the modeling recipes, are presented in a paper which is in final preparation and will be submitted soon. It will be useful not only for our future analysis but for other XMM cluster observations as well.

Mushotzky, Richard↗
NASA NTRS2007

Development of the Functional Flow Block Diagram for the J-2X Rocket Engine System

The J-2X program calls for the upgrade of the Apollo-era Rocketdyne J-2 engine to higher power levels, using new materials and manufacturing techniques, and with more restrictive safety and reliability requirements than prior human-rated engines in NASA history. Such requirements demand a comprehensive systems engineering effort to ensure success. Pratt & Whitney Rocketdyne system engineers performed a functional analysis of the engine to establish the functional architecture. J-2X functions were captured in six major operational blocks. Each block was divided into sub-blocks or states. In each sub-block, functions necessary to perform each state were determined. A functional engine schematic consistent with the fidelity of the system model was defined for this analysis. The blocks, sub-blocks, and functions were sequentially numbered to differentiate the states in which the function were performed and to indicate the sequence of events. The Engine System was functionally partitioned, to provide separate and unique functional operators. Establishing unique functional operators as work output of the System Architecture process is novel in Liquid Propulsion Engine design. Each functional operator was described such that its unique functionality was identified. The decomposed functions were then allocated to the functional operators both of which were the inputs to the subsystem or component performance specifications. PWR also used a novel approach to identify and map the engine functional requirements to customer-specified functions. The final result was a comprehensive Functional Flow Block Diagram (FFBD) for the J-2X Engine System, decomposed to the component level and mapped to all functional requirements. This FFBD greatly facilitates component specification development, providing a well-defined trade space for functional trades at the subsystem and component level. It also provides a framework for function-based failure modes and effects analysis (FMEA), and a rigorous baseline for the functional architecture.

White, Thomas↗
DOE OSTI2019

The total microbiome functions in bacteria and fungi

Unveiling the relationship between phylogeny and function of the microbiome is crucial to determine its contribution to ecosystem functioning. However, while there is a considerable amount of information on microbial phylogenetic diversity, our understanding of its relationship to functional diversity is still scarce. Here we predicted the total microbiome functions of bacteria and fungi on Earth using the total known functions from level 3 of KEGG Orthology by modelling the increase of functions with increasing diversity of bacteria or fungi. For bacteria and fungi, the unsaturated model described the data significantly better (for both P?<2.2e-16), suggesting the presence of two types of functions. Widespread functions ubiquitous in every living organism that make up two thirds of our current knowledge of microbiome functions are separated from rare functions from specialised enzymes present in only a few species. Given previous estimates on species richness, we predicted a global total of 35.5 million functions in bacteria and 3.2 million in fungi; of which only 0.02% and 0.14% are known today. Our approach highlights the necessity of novel and more sophisticated methods to unveil the entirety of rare functions to fully understand the involvement of the microbiome in ecosystem functioning. SIGNIFICANCE: The functionality of and within a microbial community is generally inferred based on the taxonomic annotation of the organism. However, our understanding of functional diversity and how it relates to taxonomy is still limited. Here we predict the total microbiome functionality in bacteria and fungi on Earth using known and annotated protein-coding sequences in species accumulation curves. Our estimates reveal that the majority of functionality (>99%) could be assigned to yet unknown and rare functions, highlighting that our current knowledge is incomplete and functional inference is thus lackluster.

Bacteria↗
DOE OSTI2016

Local and Global Function Model of the Liver

Purpose: To develop a local and global function model in the liver based on regional and organ function measurements to support individualized adaptive radiation therapy (RT). Methods and Materials: A local and global model for liver function was developed to include both functional volume and the effect of functional variation of subunits. Adopting the assumption of parallel architecture in the liver, the global function was composed of a sum of local function probabilities of subunits, varying between 0 and 1. The model was fit to 59 datasets of liver regional and organ function measures from 23 patients obtained before, during, and 1 month after RT. The local function probabilities of subunits were modeled by a sigmoid function in relating to MRI-derived portal venous perfusion values. The global function was fitted to a logarithm of an indocyanine green retention rate at 15 minutes (an overall liver function measure). Cross-validation was performed by leave-m-out tests. The model was further evaluated by fitting to the data divided according to whether the patients had hepatocellular carcinoma (HCC) or not. Results: The liver function model showed that (1) a perfusion value of 68.6 mL/(100 g · min) yielded a local function probability of 0.5; (2) the probability reached 0.9 at a perfusion value of 98 mL/(100 g · min); and (3) at a probability of 0.03 [corresponding perfusion of 38 mL/(100 g · min)] or lower, the contribution to global function was lost. Cross-validations showed that the model parameters were stable. The model fitted to the data from the patients with HCC indicated that the same amount of portal venous perfusion was translated into less local function probability than in the patients with non-HCC tumors. Conclusions: The developed liver function model could provide a means to better assess individual and regional dose-responses of hepatic functions, and provide guidance for individualized treatment planning of RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Specific Reaction Parameter Density Functional Based on the Meta-Generalized Gradient Approximation: Application to H 2 + Cu(111) and H 2 + Ag(111)

Specific reaction parameter density functionals (SRP-DFs), which can describe dissociative chemisorption reactions on metals to within chemical accuracy, have so far been based on exchange functionals within the generalized gradient approximation (GGA) and on GGA correlation functionals or van der Waals correlation functionals. These functionals are capable of describing the molecule–metal surface interaction accurately, but they suffer from the general GGA problem that this can be done only at the cost of a rather poor description of the metal. Here, we show that it is possible also to construct SRP-DFs for H 2 dissociation on Cu(111) based on meta-GGA functionals, introducing three new functionals based on the “made-simple” (MS) concept. The exchange parts of the three functionals (MS-PBEl, MS-B86bl, and MS-RPBEl) are based on the expressions for the PBE, B86b, and RPBE exchange functionals. Quasi-classical trajectory (QCT) calculations performed with potential energy surfaces (PESs) obtained with the three MS functionals reproduce molecular beam experiments on H 2 , D 2 + Cu(111) with chemical accuracy. Therefore, these three non-empirical functionals themselves are also capable of describing H2 dissociation on Cu(111) with chemical accuracy. Similarly, QCT calculations performed on the MS-PBEl and MS-B86bl PESs reproduced molecular beam and associative desorption experiments on D 2 , H 2 + Ag(111) more accurately than was possible with the SRP48 density functional for H 2 + Cu(111). Also, the three new MS functionals describe the Cu, Ag, Au, and Pt metals more accurately than the all-purpose Perdew–Burke–Ernzerhof (PBE) functional. The only disadvantage we noted of the new MS functionals is that, as found for the example of H 2 + Cu(111), the reaction barrier height obtained by taking weighted averages of the MS-PBEl and MS-RPBEl functionals is tunable over a smaller range (9 kJ/mol) than possible with the standard GGA PBE and RPBE functionals (33 kJ/mol). As a result of this restricted tunability, it is not possible to construct an SRP-DF for H 2 + Ag(111) on the basis of the three examined MS meta-GGA functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

A Generalized, Compactly-Supported Correlation Function for Data Assimilation Applications

Correlation functions play an essential role in modern data assimilation, where they are used to model covariances given a set of tunable parameters or applied as tapering functions to localize covariances in ensemble-based schemes. One of the most widely-used correlation functions in data assimilation is the Gaspari and Cohn (1999) piecewise-rational, compactly-supported parametric correlation function (hereafter referred to as GC99). The GC99 correlation function is useful due to its tunable cut-off parameter c and Gaussian-like shape achieved when the parameter a is set to one-half. These properties are attractive for tapering functions in data assimilation applications. However, the GC99 correlation function is homogeneous over Euclidean 3-space and isotropic when restricted to the sphere, properties that may be less than ideal for some geophysical applications. GC99 is also compactly-supported on a sphere of fixed radius, which requires tuning of the cut-off parameter c that can depend on the specific application. This work presents a generalization of the GC99 correlation function that allows the cut-off parameter c and shape parameter a to vary over space to gain more flexibility in shape while maintaining its compact support property. The function, which we call the Generalized Gaspari Cohn (GenGC) correlation function, introduces inhomogeneity in Euclidean 3-space and anisotropy when restricted to the sphere by allowing both parameters c and a to vary, as functions, over the spatial domain. The GC99 correlation function is a special case of GenGC where the functions c and a are held constant, as fixed parameters rather than functions. The GenGC correlation function also generalizes the follow-on to the work of Gaspari and Cohn (1999) presented in Gaspari et al. (2006), which allowed a to vary while keeping c fixed. We illustrate through simple one- and two-dimensional examples the variety of inhomogeneous and anisotropic correlation functions GenGC can produce by varying c and a over space, and suggest applications where they may be useful in data assimilation, such as covariance modeling or localization. In particular, we describe how the GenGC correlation function can be used to construct covariances using correlation length and variance fields derived from dynamics. For example, the correlation length field for advective dynamics is governed by a partial differential equation (PDE) in N spatial dimensions, where N is the number of space dimensions of the state. Correlation length fields can be determined from this PDE and used with GenGC to construct the corresponding correlations. We can then approximate the full covariance by rescaling by the variance, which also satisfies a PDE in N spatial dimensions for advective dynamics. Thus we can approximate the full covariance without solving the covariance PDE, which is in 2N spatial dimensions, by solving just two PDEs each in only N spatial dimensions. This approach to evolving the correlation length and variance fields, then reconstructing the correlations using GenGC, is suggested as an alternative to current methods of covariance modeling in data assimilation algorithms.

GC99↗
DOE OSTI2016

WE-AB-202-01: Evaluating the Toxicity Reduction with CT-Ventilation Functional Avoidance Radiation Therapy

Purpose: CT-ventilation is an exciting new imaging modality that uses 4DCTs to calculate lung ventilation. Studies have proposed to use 4DCT-ventilation imaging for functional avoidance radiotherapy which implies designing treatment plans to spare functional portions of the lung. Although retrospective studies have been performed to evaluate the dosimetric gains to functional lung; no work has been done to translate the dosimetric gains to an improvement in pulmonary toxicity. The purpose of our work was to evaluate the potential reduction in toxicity for 4DCT-ventilation based functional avoidance. Methods: 70 lung cancer patients with 4DCT imaging were used for the study. CT-ventilation maps were calculated using the patient’s 4DCT, deformable image registrations, and a density-change-based algorithm. Radiation pneumonitis was graded using imaging and clinical information. Log-likelihood methods were used to fit a normal-tissue-complication-probability (NTCP) model predicting grade 2+ radiation pneumonitis as a function of doses (mean and V20) to functional lung (>15% ventilation). For 20 patients a functional plan was generated that reduced dose to functional lung while meeting RTOG 0617-based constraints. The NTCP model was applied to the functional plan to determine the reduction in toxicity with functional planning Results: The mean dose to functional lung was 16.8 and 17.7 Gy with the functional and clinical plans respectively. The corresponding grade 2+ pneumonitis probability was 26.9% with the clinically-used plan and 24.6% with the functional plan (8.5% reduction). The V20-based grade 2+ pneumonitis probability was 23.7% with the clinically-used plan and reduced to 19.6% with the functional plan (20.9% reduction). Conclusion: Our results revealed a reduction of 9–20% in complication probability with functional planning. To our knowledge this is the first study to apply complication probability to convert dosimetric results to toxicity improvement. The results presented in the current work provide seminal data for prospective clinical trials in functional avoidance. YV discloses funding from State of Colorado. TY discloses National Lung Cancer Partnership; Young Investigator Research grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Functional Annotation of Hierarchical Modularity

In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function–hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology) and the association of individual genes or proteins with these concepts (e.g., GO terms), our method will assign a Hierarchical Modularity Score (HMS) to each node in the hierarchy of functional modules; the HMS score and its p{value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of ‘‘enriched’’ functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our method using Saccharomyces cerevisiae data from KEGG and MIPS databases and several other computationally derived and curated datasets. The code and additional supplemental files can be obtained from http:// code.google.com/p/functional-annotation-of-hierarchical-modularity/ (Accessed 2012 March 13).

59 BASIC BIOLOGICAL SCIENCES↗