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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Relationships among DNA hypomethylation, Cd, and Pb exposure and risk of cigarette smoking-related urothelial carcinoma

Cigarette smoking and environmental exposure to heavy metals are important global health issues, especially for urothelial carcinoma (UC). However, the effects of cadmium and lead exposure, as well as the levels of DNA hypomethylation, on UC risk are limited. We evaluated the possible exposure sources of Cd and Pb and the relationship among DNA hypomethylation, urinary Cd and Pb levels, and UC risk. We recruited 209 patients with UC and 417 control patients for a hospital-based case–control study between June 2011 and August 2014. We collected environmental exposure-related information with questionnaires. Blood and urine samples were analyzed to measure the Cd and Pb exposure and 5-methyl-2′-deoxycytidine levels as a proxy for DNA methylation. Multivariate logistic regression and 95% confidence intervals were applied to estimate the risk for UC. Study participants with high Cd and Pb exposure in blood or urine had significantly increased risk of UC, especially among the smokers. After adjusting for age and gender, the possible connections of individual cumulative cigarette smoking or herb medicine exposure with the increased levels of Cd and Pb were observed in the controls. Participants with 8.66%–12.39% of DNA hypomethylation had significantly increased risk of UC compared with those with ≥ 12.39% of DNA hypomethylation. Environmental factors including cigarette smoking and herb medicine may contribute to the internal dose of heavy metals levels. Repeat measurements of heavy metals with different study design, detailed dietary information, and types of herb medicine should be recommended for exploring UC carcinogenesis in future studies. - Highlights: • Smoking and herb medicine ingestion is associated with increased urinary Cd and Pb levels. • Urinary levels of Cd and Pb are associated with increased risk of UC. • UC carcinogenesis might have partially resulted from DNA hypomethylation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Forecasting of municipal solid waste quantity in a developing country using multivariate grey models

Highlights: • Grey model can be used to forecast MSW quantity accurately with the limited data. • Prediction interval overcomes the uncertainty of MSW forecast effectively. • A multivariate model gives accuracy associated with factors affecting MSW quantity. • Population, urbanization, employment and household size play role for MSW quantity. - Abstract: In order to plan, manage and use municipal solid waste (MSW) in a sustainable way, accurate forecasting of MSW generation and composition plays a key role. It is difficult to carry out the reliable estimates using the existing models due to the limited data available in the developing countries. This study aims to forecast MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. For multivariate models, the representative factors of residential and commercial sectors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory. Results show that GMC (1, 5), the grey model with convolution integral, is the most accurate with the least error of 1.16% MAPE. MSW collected would increase 1.40% per year from 43,435–44,994 tonnes per day in 2013 to 55,177–56,735 tonnes per day in 2030. This model also illustrates that population density is the most important factor affecting MSW collected, followed by urbanization, proportion employment and household size, respectively. These mean that the representative factors of commercial sector may affect more MSW collected than that of residential sector. Results can help decision makers to develop the measures and policies of waste management in long term period.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

When will low-contrast features be visible in a STEM X-ray spectrum image?

When will a small or low-contrast feature, such as an embedded second-phase particle, be visible in a scanning transmission electron microscopy (STEM) X-ray map? This work illustrates a computationally inexpensive method to simulate X-ray maps and spectrum images (SIs), based upon the equations of X-ray generation and detection. To particularize the general procedure, an example of nanostructured ferritic alloy (NFA) containing nm-sized Y 2 Ti 2 O 7 embedded precipitates in ferritic stainless steel matrix is chosen. The proposed model produces physically appearing simulated SI data sets, which can either be reduced to X-ray dot maps or analyzed via multivariate statistical analysis. Comparison to NFA X-ray maps acquired using three different STEM instruments match the generated simulations quite well, despite the large number of simplifying assumptions used. A figure of merit of electron dose multiplied by X-ray collection solid angle is proposed to compare feature detectability from one data set (simulated or experimental) to another. The proposed method can scope experiments that are feasible under specific analysis conditions on a given microscope. As a result, future applications, such as spallation proton–neutron irradiations, core-shell nanoparticles, or dopants in polycrystalline photovoltaic solar cells, are proposed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

The Chemistry Graduate Student Experience: Findings from an ACS Survey

Graduate training is a key element in producing a scientific workforce that reflects the nation’s diversity. This paper examines data from a 2013 American Chemical Society (ACS) survey of 2,544 chemistry masters and doctoral students and reveals barriers to reaching this goal. Multivariate statistical analyses indicate that women reported significantly less supportive relationships with advisors. Women were less likely to plan to finish their degrees, and for PhD students, the discrepancy was larger for students at the start of their graduate program. Women were also less likely to pursue the next level of training, and the gender difference related to postdoctoral plans was greater for those who identified with a racial-ethnic group traditionally underrepresented in chemistry (underrepresented minority, URM). URM students who were beyond the first year of their graduate program reported significantly less supportive relationships with peers. They were also less likely to have funding sufficient to meet their needs and more often used personal resources including loans. Despite these difficulties, URM students were more likely to definitely plan to finish their degrees, and men who identified as URM were more likely to plan to pursue postdoctoral work. Independent of gender and identification as URMs, students in more highly ranked schools reported less advisor support. Extensive open-ended comments indicated that large proportions of the students desired more attention and meaningful feedback from advisors and changes within their programs to promote support for students and advisor accountability. Suggestions for future research are given, and a companion commentary discusses needed directions for change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Representations of Precipitation Diurnal Cycle in the Amazon as Simulated by Observationally Constrained Cloud‐System Resolving and Global Climate Models

Abstract The ability of an observationally‐constrained cloud‐system resolving model (Weather Research and Forecasting; WRF, 4‐km grid spacing) and a global climate model (Energy Exascale Earth System Model; E3SM, 1‐degree grid spacing) to represent the precipitation diurnal cycle over the Amazon basin during the 2014 wet season is assessed. The WRF model coupled with a 3‐D variational data assimilation scheme reproduces the spatial variability of the precipitation diurnal cycle over the basin and the lifecycle of westward propagating MCSs initiated by the coastal sea‐breeze front. In contrast, a single morning peak in rainfall is produced by E3SM for simulations despite the nudging of large‐scale winds toward global reanalysis, indicating precipitation in E3SM is largely controlled by local convection associated with diurnal heating. The role of propagating MCS on the environment are discussed by using a multivariate perturbation analysis. We also find that the advection of moisture perturbations from ocean to inland regions have a higher correlation with the occurrence of MCSs in the Amazon than the intensity of colder air intrusion associated with sea breezes along the coast. Moreover, the presence of large cold pools over the central Amazon basin are responsible for the maintenance of propagating deep convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Conserved Macromolecular Architecture of Poplar Secondary Cell Walls Revealed by ssNMR and Atomistic Modeling

The macromolecular architecture of plant secondary cell walls governs wood's mechanical and biochemical properties, yet its natural intra-species variability remains poorly characterized. Here, we combined 13C solid-state NMR (ssNMR), multivariate statistical analysis, and molecular modeling to profile nanoscale structure across 13 genetically diverse Populus trichocarpa genotypes grown in 13C-enriched atmospheres. SsNMR-derived phenotypes spanning composition, structure, mobility, and inter-polymer proximities reveal a conserved architecture, with a subtle yet coordinated variation organizing into dominant structural and secondary mobility axes. A representative atomistic model captures these features and reproduces experimental metrics. Molecular dynamics simulations support a weak but consistent positive correlation between cellulose abundance and crystalline-like order, with interior cellulose chains enriched in tg (trans-gauche) conformations without expanding crystalline cores. Together, experiment and simulation reveal a genetically buffered, broadly conserved nanoscale architecture across genotypes, where subtle fine-tuning of cellulose bundling and matrix packing balances mechanical performance with biological function.

09 BIOMASS FUELS↗
DOE OSTI2012

Integration of Gas Chromatography Mass Spectrometry Methods for Differentiating Ricin Preparation Methods

The investigation of crimes involving chemical or biological agents is infrequent, but presents unique analytical challenges. The protein toxin ricin is encountered more frequently than other agents and is found in the seeds of the castor plant Ricinus communis. Typically, the toxin is extracted from castor seeds utilizing a variety of different recipes that result in varying purity of the toxin. Moreover, these various purification steps can also leave or differentially remove a variety of exogenous and endogenous residual components with the toxin that may indicate the type and number of purification steps involved. We have applied three gas chromatographic - mass spectrometric (GC-MS) based analytical methods to measure the variation in seed carbohydrates and castor oil ricinoleic acid as well as the presence of solvents used for purification. These methods were applied to the same samples prepared using four previously identified toxin preparation methods starting from four varieties of castor seeds. The individual data sets for seed carbohydrate profiles, ricinoleic acid or acetone amount each provided information capable of differentiating different types of toxin preparations across seed types. However, the integration of the data sets using multivariate factor analysis provided a clear distinction of all samples based on the preparation method and independent of the seed source. In particular the abundance of mannose, arabinose, fucose, ricinoleic acid and acetone were shown to be important differentiating factors. These complementary tools provide a more confident determination of the method of toxin preparation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Soft Classification of Diffractive Interactions at the LHC

Multivariate machine learning techniques provide an alternative to the rapidity gap method for event-by-event identification and classification of diffraction in hadron-hadron collisions. Traditionally, such methods assign each event exclusively to a single class producing classification errors in overlap regions of data space. As an alternative to this so called hard classification approach, we propose estimating posterior probabilities of each diffractive class and using these estimates to weigh event contributions to physical observables. It is shown with a Monte Carlo study that such a soft classification scheme is able to reproduce observables such as multiplicity distributions and relative event rates with a much higher accuracy than hard classification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

A coarse-grained transport model for neutral particles in turbulent plasmas

The transport of neutral particles in turbulent plasmas is addressed from the prospect of developing coarse-grained transport models which can be implemented in code suites like B2-EIRENE, currently used for designing the ITER divertor. The statistical properties of turbulent fluctuations are described by a multivariate Gamma distribution able to retain space and time correlations through a proper choice of covariance function. We show that in the scattering free case, relevant for molecules and impurity atoms, the average neutral particle density obeys a Boltzmann equation with an ionization rate renormalized by fluctuations. This result lends itself to a straightforward implementation in the EIRENE Monte Carlo solver for neutral particles. Special emphasis is put on the inclusion of time correlations, and in particular on the ballistic motion of coherent turbulent structures. The role of these time dependent effects is discussed for D{sub 2} molecules and beryllium atoms. The sensitivity of our results to the assumptions on the statistical properties of fluctuations is investigated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Geometry optimization for micro-pressure sensor considering dynamic interference

Presented is the geometry optimization for piezoresistive absolute micro-pressure sensor. A figure of merit called the performance factor (PF) is defined as a quantitative index to describe the comprehensive performances of a sensor including sensitivity, resonant frequency, and acceleration interference. Three geometries are proposed through introducing islands and sensitive beams into typical flat diaphragm. The stress distributions of sensitive elements are analyzed by finite element method. Multivariate fittings based on ANSYS simulation results are performed to establish the equations about surface stress, deflection, and resonant frequency. Optimization by MATLAB is carried out to determine the dimensions of the geometries. Convex corner undercutting is evaluated. Each PF of the three geometries with the determined dimensions is calculated and compared. Silicon bulk micromachining is utilized to fabricate the prototypes of the sensors. The outputs of the sensors under both static and dynamic conditions are tested. Experimental results demonstrate the rationality of the defined performance factor and reveal that the geometry with quad islands presents the highest PF of 210.947 Hz{sup 1/4}. The favorable overall performances enable the sensor more suitable for altimetry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Communication: Newton homotopies for sampling stationary points of potential energy landscapes

One of the most challenging and frequently arising problems in many areas of science is to find solutions of a system of multivariate nonlinear equations. There are several numerical methods that can find many (or all if the system is small enough) solutions but they all exhibit characteristic problems. Moreover, traditional methods can break down if the system contains singular solutions. Here, we propose an efficient implementation of Newton homotopies, which can sample a large number of the stationary points of complicated many-body potentials. We demonstrate how the procedure works by applying it to the nearest-neighbor ϕ{sup 4} model and atomic clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Various forms of indexing HDMR for modelling multivariate classification problems

The Indexing HDMR method was recently developed for modelling multivariate interpolation problems. The method uses the Plain HDMR philosophy in partitioning the given multivariate data set into less variate data sets and then constructing an analytical structure through these partitioned data sets to represent the given multidimensional problem. Indexing HDMR makes HDMR be applicable to classification problems having real world data. Mostly, we do not know all possible class values in the domain of the given problem, that is, we have a non-orthogonal data structure. However, Plain HDMR needs an orthogonal data structure in the given problem to be modelled. In this sense, the main idea of this work is to offer various forms of Indexing HDMR to successfully model these real life classification problems. To test these different forms, several well-known multivariate classification problems given in UCI Machine Learning Repository were used and it was observed that the accuracy results lie between 80% and 95% which are very satisfactory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

The use of experimental design to find the operating maximum power point of PEM fuel cells

Proton Exchange Membrane (PEM) Fuel Cells are difficult to model due to their complex nonlinear nature. In this paper, the development of a PEM Fuel Cells mathematical model based on the Design of Experiment methodology is described. The Design of Experiment provides a very efficient methodology to obtain a mathematical model for the studied multivariable system with only a few experiments. The obtained results can be used for optimization and control of the PEM Fuel Cells systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Oxidation state and interfacial effects on oxygen vacancies in tantalum pentoxide

First-principles density-functional theory calculations are used to study the atomistic structure, structural energetics, and electron density near the O monovacancy (V{sub O}{sup n}; n = 0,1+,2+) in both bulk, amorphous tantalum pentoxide (a-Ta{sub 2}O{sub 5}), and also at vacuum and metallic Ta interfaces. We calculate multivariate vacancy formation energies to evaluate stability as a function of oxidation state, distance from interface plane, and Fermi energy. V{sub O}{sup n} of all oxidation states preferentially segregates at both Ta and vacuum interfaces, where the metallic interface exhibits global formation energy minima. In a-Ta{sub 2}O{sub 5}, V{sub O}{sup 0} is characterized by structural contraction and electron density localization, while V{sub O}{sup 2+} promotes structural expansion and is depleted of electron density. In contrast, interfacial V{sub O}{sup 0} and V{sub O}{sup 2+} show nearly indistinguishable ionic and electronic signatures indicative of a reduced V{sub O} center. Interfacial V{sub O}{sup 2+} extracts electron density from metallic Ta, indicating that V{sub O}{sup 2+} is spontaneously reduced at the expense of the metal. This oxidation/reduction behavior suggests careful selection and processing of both oxide layer and metal electrodes for engineering memristor device operation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Symmetric polynomials in information theory: Entropy and subentropy

Entropy and other fundamental quantities of information theory are customarily expressed and manipulated as functions of probabilities. Here we study the entropy H and subentropy Q as functions of the elementary symmetric polynomials in the probabilities and reveal a series of remarkable properties. Derivatives of all orders are shown to satisfy a complete monotonicity property. H and Q themselves become multivariate Bernstein functions and we derive the density functions of their Levy-Khintchine representations. We also show that H and Q are Pick functions in each symmetric polynomial variable separately. Furthermore, we see that H and the intrinsically quantum informational quantity Q become surprisingly closely related in functional form, suggesting a special significance for the symmetric polynomials in quantum information theory. Using the symmetric polynomials, we also derive a series of further properties of H and Q.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Detecting the relationship between economic growth, CO{sub 2} and energy consumption by using panel data approach

Many scholars have shown their interest into the relationship between energy consumption (EC), gross domestic product (GDP) and emissions. The main objective of this study is to investigate the relationship between GDP, EC and CO{sub 2} within multivariate model by using panel data method in Asian countries; Korea, Malaysia, Japan and China for annually data during the period 1960 to 2010. The main finding shows that CO{sub 2} can be explained more than 86% & 78% by EC and GDP in each of cross section model and period model respectively. As a result of that, CO{sub 2} emissions should be considered as an important factor in energy consumption and gross domestic product by policy maker.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗