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At least 1,531 records · Page 85

Impact of acute temperature and air pollution exposures on adult lung function: A panel study of asthmatics

Background Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM 2.5 ) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. Methods and findings Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV 1 )), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM 2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM 2.5 , DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM 2.5 , but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM 2.5 , had a significant association with FEV 1 . When DBGT and PM 2.5 exposures were placed in the same model, the strongest association between cumulative PM 2.5 exposures and the use of rescue bronchodilator was identified at the 0–24 hours (OR = 1.030; 95% CI = 1.012–1.049; p-value = 0.001) and 0–48 hours (OR = 1.030; 95% CI = 1.013–1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (β = 3.257; SE = 0.879; p-value>0.001) and 0–6 hours (β = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV 1 . No significant interactions between DBGT and PM 2.5 were observed for rescue bronchodilator use or FEV 1 . Conclusions Short-term increases in PM 2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV 1 ). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM 2.5 and DBGT on lung function in asthmatics.

60 APPLIED LIFE SCIENCES↗

Functional Programming in Computer Science

We explore functional programming through a 16-week internship at Los Alamos National Laboratory. Functional programming is a branch of computer science that has exploded in popularity over the past decade due to its high-level syntax, ease of parallelization, and abundant applications. First, we summarize functional programming by listing the advantages of functional programming languages over the usual imperative languages, and we introduce the concept of parsing. Second, we discuss the importance of lambda calculus in the theory of functional programming. Lambda calculus was invented by Alonzo Church in the 1930s to formalize the concept of effective computability, and every functional language is essentially some implementation of lambda calculus. Finally, we display the lasting products of the internship: additions to a compiler and runtime system for the pure functional language STG, including both a set of tests that indicate the validity of updates to the compiler and a compiler pass that checks for illegal instances of duplicate names.

97 MATHEMATICS AND COMPUTING↗

Breaking the Bottleneck of Genomes: Understanding Gene Function Across Taxa Workshop Report

In the last few decades, high-throughput technologies using various “omics” have enabled unprecedented views of biological systems at the molecular level. In parallel, the integration of omic datasets using computational modeling has provided new understanding of biological processes in organisms relevant to the U.S. Department of Energy’s (DOE) missions in energy and the environment. Collectively, these developments have spearheaded the advancement of systems biology, which can be viewed as a holistic approach for deciphering the complexity of biological systems. However, as high-throughput omic technologies and integrative systems biology efforts have improved our understanding of some biological systems, analyzing and finding meaningful answers within these massive datasets remain extremely challenging, in large part due to the lack of fundamental knowledge of gene function. Indeed, all sequenced genomes, both microbes and plants, contain large numbers of genes of “unknown function” that significantly limit scientists’ ability to model, predict, and engineer organisms with enhanced functions relevant to DOE. Current methodologies can be employed to decipher gene function, but they are typically slow, laborious, inefficient, and not scalable. This “bottleneck” in genome understanding could be broken with new, innovative, and transformative experimental tools, datasets, and computation that can define gene function on a massive and high-throughput scale compatible with the pace of DNA sequencing. In light of this grand challenge, DOE’s Office of Biological and Environmental Research (BER) convened the Breaking the Bottleneck of Genomes: Understanding Gene Function Across Taxa workshop on November 1–2, 2018. This workshop brought together leaders in microbiology, plant sciences, technology, and computation, who collectively identified the experimental and data analysis gaps preventing large-scale gene function determination as well as opportunities for overcoming these gaps.

59 BASIC BIOLOGICAL SCIENCES↗

Draft Electric Rule 21 Test Protocols for Advanced Inverter Functions

Disclaimer: The following document includes draft certification protocols and should not be viewed as a consensus-based performance standard. Distributed energy resources (DERs), such as photovoltaic (PV) systems, when deployed in a large scale, are capable of significantly influencing the operation of bulk and local power systems. Looking to the future, European and American stakeholders are working on standards to make it possible to manage the potentially complex interactions between DER and the power system. One of the jurisdictions considering modifications to the DER interconnection requirements is California. To determine what changes could improve electric grid reliability and allow greater penetrations of renewable energy, the California Public Utilities Commission (CPUC) and the California Energy Commission (CEC), in conjunction with consultant Frances Cleveland, convened the Smart Inverter Working Group (SIWG) in January 2013. The SIWG--composed of state agencies, utility engineers, national laboratories, manufacturers, trade associations, and advocacy groups--provided the CPUC a set of recommendations in early 2014 1 . The recommendations included specific advanced DER functions and interoperability requirements, along with a proposed timeline, for California to add new capabilities to grid-interconnected DER. On August 18, 2014 the three California Investor-Owned Utilities (IOUs)--Pacific Gas and Electric Company (PG&E), Southern California Edison Company (SCE) and San Diego Gas & Electric Company (SDG&E)--drafted a Advice Letter filing to the CPUC setting forth revisions to Electric Tariff Rule 21 to conform to the seven recommendations made by the Working Group 2 . After a comment period, the CPUC issued an update to the IOU recommendations 3 . At the time of this publication, there was no final legal ruling on the CPUC Rulemaking (R.) 11-09-011 ("Order Instituting Rulemaking on the Commission's Own Motion to improve distribution level interconnection rules and regulations for certain classes of electric generators and electric storage resources"). In the U.S., Nationally Recognized Test Laboratories (NRTLs) independently verify products to safety and functional standards. PV inverters are certified to Underwriters Laboratories (UL) Standard 1741 4 . However, new advanced inverter functions described in the SIWG and IOU proposals are not included in this standard, so there is a critical need to develop test protocols for these functions in preparation of a positive ruling by the CPUC. Through a California Solar Initiative Grant, Sandia National Laboratories (Sandia or SNL), Underwriters Laboratories (UL), Electric Power Research Institute, Inc. (EPRI), Xanthus Consulting, SunSpec Alliance, Loggerware, and utility and PV inverter manufacturers have collaborated to draft this certification protocol for the Rule 21 SIWG Phase 1 advanced inverter functions. This report also includes test procedures for Phase 2 and Phase 3 functions that will be demonstrated later in the CSI4 project. This collaborative effort was performed in close junction with the UL 1741 Standards Technical Panel (STP) working group. This document represents a snapshot of the draft testing protocols at the time of publication and not a consensus certification protocol for advanced inverters. 1 California Public Utilities Commission, "Recommendations for Updating the Technical Requirements for Inverters in Distributed Energy Resources, Smart Inverter Working Group Recommendations," Filed 7 Feb 2014. 2 J.J. Newlander, R.G. Litteneker, S.W. Walter, M. Dwyer, Joint motion of Pacific Gas and Electric Company (U 39 E), Southern California Edison Company (U 338 E) and San Diego Gas & Electric Company (U 902 E) regarding implementation of smart inverter functionalities, Rulemaking 11-09-011 Advice Letter, 18 July, 2014. 3 J.T. Sullivan, CPUC Rulemaking 11-09-011 Agenda ID #13460, 13 Nov, 2014. 4 Underwriters Laboratories Std. 1741 Ed. 2, "Inverters, Converters, Controllers and Interconnection System Equipment for use with Distributed Energy Resources," 2010.

42 ENGINEERING↗

An efficient method to estimate the probability density of seismic Green's functions

We present a computationally efficient method to approximate the probability distribution of seismic Green's functions given the uncertainty of an Earth model. The method is based on the Karhunen-Loève (KL) theorem and an approximation of the Green's function (or seismogram) covariance. Using Monte Carlo (MC) simulations as a control case, we demonstrate that our KL-based method can accurately reproduce a probability distribution of seismograms that results from an uncertain Earth model for a MC-derived seismogram covariance. We then describe a method to estimate the covariance of the seismograms resulting from those Earth models that is not based on MC simulations. We use the estimated Green's function covariance in conjunction with our KL-based method to produce a Green's function probability distribution, and compare that distribution to a Green's function probability distribution produced using a MC finite difference method. We find that the Green's function probability distribution approximated using our KL-based method generally mimics that produced using the MC simulations, especially for direct-arriving body waves. However the accuracy of the KL-based method generally decreases for later times in the simulated Green's function distribution.

58 GEOSCIENCES↗

Functional characterization of glycosyltransferases in duckweed to enable predictive biology

Glycosyltransferases (GTs) catalyze the formation of glycosidic linkages to produce almost all complex carbohydrates. This project used a multi-disciplinary, high-throughput (HTP) biochemical and computational biology approach focused on duckweed as a model energy crop, to study carbohydrate metabolic processes. To achieve this, developed and carried out out high-throughput (HTP) functional characterization of plant glycosyltransferases (GTs) role of enzymatic microenvironments be assessed through a combined proteomic and computational biology approach, and the combined data was used to populate deep-learning frameworks to predict plant GT function. Functional validation achieved through this research is being used to assign gene function and study plant processes at the systems level to efficiently link the genome sequence with gene function. Together, the combined approaches used within this study provide a foundation for how computational prediction, in combination with high-throughput functional validation, can be used to study plant processes at the systems level and translate knowledge gained to efficiently link genome sequence with gene function in a species agnostic manner.

09 BIOMASS FUELS↗

Equation-of-Motion Coupled-Cluster Cumulant Green’s Function for Excited States and X-ray Spectra

Green’s function methods within many-body perturbation theory provide a general framework for treating electronic correlations in excited states and spectra. Conventional methods using the Dyson equation or the cumulant expansion are typically based on the GW self-energy approximation. In order to extend this approximation in molecular systems, a non-perturbative real-time coupled-cluster cumulant Green’s function approach has been introduced, where the cumulant is obtained as the solution to a set of coupled first order, non-linear differential equations. This approach naturally includes non-linear corrections to conventional cumulant Green’s function techniques where the cumulant is linear in the GW self-energy. The method yields the spectral function associated with the core Green’s function, which is directly related to the x-ray photoemission spectra (XPS) of molecular systems. The approach also yields very good results for binding energies and satellite excitations. The x-ray absorption spectrum (XAS) is then obtained as a convolution of the core spectral function and an effective one-body absorption spectrum. Here this approach is extended to include the full coupled-cluster-singles (CCS) core Green’s function by including the complete form of the non-linear contributions to the cumulant as well as all single, double, and triple cluster excitations in the CC amplitude equations. This approach naturally builds in orthogonality and shake-up effects analogous to those in the Mahan-Noizeres-de Dominicis edge singularity corrections that enhance the XAS near the edge. Themethod is illustrated for the XPS and XAS of NH 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Evolutionary Yield Function Model Based on Plastic Work and Non-Associated Flow Rule

A constitutive law was developed based on the evolutionary yield function to account for the evolution of anisotropy induced by the plastic deformation. For the effective description of anisotropy, the yield stress function and plastic potential were separately defined based on the non-associated flow rule. In particular, for the description of the equivalent status, the accumulated plastic work was employed as an alternative to the accumulated plastic strain. Numerical formulations based on the plastic work were also derived in case the hardening rule, as well as the evolution of the plastic potential and yield stress function, were defined in terms of the plastic work. The developed constitutive law was characterized using the mechanical properties of the multi-phase BAO QP980 steel and niobium sheets at room temperature. From the uniaxial tension tests and the balanced biaxial tension test, separate sets of anisotropic coefficients for each of the plastic potential and yield stress functions were obtained as a function of the plastic work. By comparing with non-evolving yield functions, the importance of the developed constitutive law to properly describe the evolution of the plastic potential and yield function were validated.

Park, Taejoon↗

The next generation virgo cluster survey (NGVS). XIII. The luminosity and mass function of galaxies in the core of the virgo cluster and the contribution from disrupted satellites

We present measurements of the galaxy luminosity and stellar mass function in a 3.71 deg{sup 2} (0.3 Mpc{sup 2}) area in the core of the Virgo Cluster, based on u{sup ∗} griz data from the Next Generation Virgo Cluster Survey (NGVS). The galaxy sample—which consists of 352 objects brighter than M {sub g} = −9.13 mag, the 50% completeness limit of the survey—reaches 2.2 mag deeper than the widely used Virgo Cluster Catalog and at least 1.2 mag deeper than any sample previously used to measure the luminosity function in Virgo. Using a Bayesian analysis, we find a best-fit faint-end slope of α = −1.33 ± 0.02 for the g-band luminosity function; consistent results are found for the stellar mass function and the luminosity function in the other four NGVS bandpasses. We discuss the implications for the faint-end slope of adding 92 ultracompact dwarfs (UCDs)—previously compiled by the NGVS in this region—to the galaxy sample, assuming that UCDs are the stripped remnants of nucleated dwarf galaxies. Under this assumption, the slope of the luminosity function (down to the UCD faint magnitude limit, M {sub g} = −9.6 mag) increases dramatically, up to α = −1.60 ± 0.06 when correcting for the expected number of disrupted non-nucleated galaxies. We also calculate the total number of UCDs and globular clusters that may have been deposited in the core of Virgo owing to the disruption of satellites, both nucleated and non-nucleated. We estimate that ∼150 objects with M {sub g} ≲ −9.6 mag and that are currently classified as globular clusters might, in fact, be the nuclei of disrupted galaxies. We further estimate that as many as 40% of the (mostly blue) globular clusters in the Virgo core might once have belonged to such satellites; these same disrupted satellites might have contributed ∼40% of the total luminosity in galaxies observed in the core region today. Finally, we use an updated Local Group galaxy catalog to provide a new measurement of the luminosity function of Local Group satellites, α = −1.21 ± 0.05, which is only 1.7σ shallower than measured in the core of the Virgo Cluster.

79 ASTRONOMY AND ASTROPHYSICS↗

Estimation of correlation functions by stochastic approximation.

Consideration of the autocorrelation function of a zero-mean stationary random process. The techniques are applicable to processes with nonzero mean provided the mean is estimated first and subtracted. Two recursive techniques are proposed, both of which are based on the method of stochastic approximation and assume a functional form for the correlation function that depends on a number of parameters that are recursively estimated from successive records. One technique uses a standard point estimator of the correlation function to provide estimates of the parameters that minimize the mean-square error between the point estimates and the parametric function. The other technique provides estimates of the parameters that maximize a likelihood function relating the parameters of the function to the random process. Examples are presented.

Habibi, A.↗

A novel methodology for radiative transfer in a planetary atmosphere. I - The functions a exponent m and b exponent m of anisotropic scattering

The original problem of anisotropic scattering in an atmosphere illuminated by a unidirectional source is replaced by an analogous formulation where the incident light is omnidirectional. A radiative-transfer equation for the omnidirectional case is obtained in which the direction of illumination plays no role and the source-function analog, Sobolev's (1972) source function Phi exponent m, contains only a single integral term. For radiation incident on the top or the bottom of the atmosphere, this equation involves the functions b exponent m and h exponent m, respectively, with m corresponding to the order of the harmonic component of the scattered radiation field; these two functions are shown to be only one through some simple reciprocity relations. The transfer problem is then reformulated for the function a exponent m, in which case the source-function analog (Sobolev's function D exponent m) involves incident direction.

Fymat, A. L.↗

A study of the effect of forcing function characteristics on human operator dynamics in manual control

The effect of the spectrum of the forcing function on the human pilot dynamics in manual control was investigated. A simple compensatory tracking experiment was conducted, where the controlled element was of a second-order dynamics and the forcing function was a random noise having a dominant frequency. The dominant frequency and the power of the forcing function were two variable parameters during the experiment. The results show that the human pilot describing functions are dependent not only on the dynamics of the controlled element, but also on the characteristics of the forcing function. This suggests that the human pilot behavior should be expressed by the transfer function taking into consideration his ability to sense and predict the forcing function.

Washizu, K.↗

Investigation of numerical properties of Hovenier's exit function equation for multiple scattering of light

A technique of deriving Hovenier's exit function equation (1978) for multiple scattering, starting with a set of invariant imbedding equations, is presented. The feasibility of the exit function equation as a means to obtain reflection and transmission functions is investigated for isotropic, Rayleigh, and Henyey-Greenstein phase functions with emphasis on the numerical stability, accuracy and timing. It is possible to compute the reflection function rather accurately with an efficiency comparable to that of the standard doubling technique for the same phase functions with moderate anisotropy. The resulting transmission is slightly less accurate than the reflection function, but it may be acceptable for practical purposes.

Kawabata, K.↗

Stellar luminosity functions in the R, I, J, and K bands obtained by transformation from the visual band

The stellar luminosity function that has been measured in the visual band into the R, I, J, and K bands, where it has not yet been obtained directly, is transformed. The transformation is effected by subdividing the total visual function, which includes all stars, into subluminosity functions for each luminosity class (supergiants through white dwarfs), applying the known (V - D) color, D = R, I, J, K for each spectral type, and then summing the resultant transformed subluminosity functions into a total luminosity function for the band D. Simple analytic forms that accurately fit the transformed luminosity functions are given. Consideration is also given to the possibility of a systematic error resulting from the existence of a very red stellar population not accounted for in the visual band luminosity function

Mamon, G. A.↗

Number of terms required in the Fourier expansion of the reflection function for optically thick atmospheres

Computational results are presented for the separate terms in the Fourier expansion of the phase function and the reflection function of a semiinfinite, conservatively scattering atmosphere composed of cloud particles. The calculations involve successive applications of invariant imbedding, doubling, and asymptotic fitting methods to cover the range from very thin to very thick atmospheres. From the results, the ratio of the total reflection function to the first-order reflection function is determined as well as the number of terms required to describe the reflection function to an accuracy of 0.1 percent. The number of terms required depends strongly on the zenith angles of incidence and reflection as well as on details of the phase function. These results are compared with similar results obtained for a Henyey-Greenstein phase function having the same asymmetry factor as in the cloud model.

King, M. D.↗

Characteristics of electron velocity distribution functions in the solar wind derived from the Helios plasma experiment

The details of the shapes of three typical electron distribution functions observed by the Helios 1 and 2 probes in the solar wind between 0.3 AU and 1 AU are analyzed and compared with theoretical predictions. These are (1) a distribution function with a narrow 'strahl' (narrow beam), which is extremely anisotropic and skewed with respect to the magnetic field direction at particle energies above 100 eV; (2) a distribution function with a broad 'strahl', less anisotropic and skewed; and (3) a nearly isotropic distribution function. For each distribution function, a sudden change in the slope was discerned, separating the 'core' at lower energies from the 'halo' at higher energies. The most obvious differences of the analyzed electron distribution functions were observed at energies above 50-100 eV. The possible origins for the observed features of the distribution functions are discussed.

Pilipp, W. G.↗

Cosmological parameters and evolution of the galaxy luminosity function

The relationship between the observed distribution of discrete sources of a flux limited sample, the luminosity function of these sources, and the cosmological model is discussed. It is stressed that some assumptions about the form and evolution of the luminosity function must be made in order to determine the cosmological parameters from the observed distribution of sources. Presented is a method to test the validity of these assumptions using the observations. It is shown how, using higher moments of the observed distribution, one can determine, independently of the cosmological model, all parameters of the luminosity function except those describing evolution of the density and the luminosity of the luminosity function. These methods are applied to the sample of approximately 1000 galaxies recently used by Loh and Spillar to determine a value of the cosmological density parameter Omega approx = 1. It is shown that the assumptions made by Loh and Spillar about the luminosity function are inconsistent with the data, and that a self-consistent treatment of the data indicates a lower value of Omega approx = 0.2 and a flatter luminosity function. It should be noted, however, that incompleteness in the sample could cause a flattening of the luminosity function and lower the calculated value of Omega and that uncertainty in the values of these parameters due to random fluctuations is large.

Caditz, David↗

Functional reasoning in diagnostic problem solving

This work is one facet of an integrated approach to diagnostic problem solving for aircraft and space systems currently under development. The authors are applying a method of modeling and reasoning about deep knowledge based on a functional viewpoint. The approach recognizes a level of device understanding which is intermediate between a compiled level of typical Expert Systems, and a deep level at which large-scale device behavior is derived from known properties of device structure and component behavior. At this intermediate functional level, a device is modeled in three steps. First, a component decomposition of the device is defined. Second, the functionality of each device/subdevice is abstractly identified. Third, the state sequences which implement each function are specified. Given a functional representation and a set of initial conditions, the functional reasoner acts as a consequence finder. The output of the consequence finder can be utilized in diagnostic problem solving. The paper also discussed ways in which this functional approach may find application in the aerospace field.

Sticklen, Jon↗