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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Amputation effects on the underlying complexity within transtibial amputee ankle motion

The presence of chaos in walking is considered to provide a stable, yet adaptable means for locomotion. This study examined whether lower limb amputation and subsequent prosthetic rehabilitation resulted in a loss of complexity in amputee gait. Twenty-eight individuals with transtibial amputation participated in a 6 week, randomized cross-over design study in which they underwent a 3 week adaptation period to two separate prostheses. One prosthesis was deemed “more appropriate” and the other “less appropriate” based on matching/mismatching activity levels of the person and the prosthesis. Subjects performed a treadmill walking trial at self-selected walking speed at multiple points of the adaptation period, while kinematics of the ankle were recorded. Bilateral sagittal plane ankle motion was analyzed for underlying complexity through the pseudoperiodic surrogation analysis technique. Results revealed the presence of underlying deterministic structure in both prostheses and both the prosthetic and sound leg ankle (discriminant measure largest Lyapunov exponent). Results also revealed that the prosthetic ankle may be more likely to suffer loss of complexity than the sound ankle, and a “more appropriate” prosthesis may be better suited to help restore a healthy complexity of movement within the prosthetic ankle motion compared to a “less appropriate” prosthesis (discriminant measure sample entropy). Results from sample entropy results are less likely to be affected by the intracycle periodic dynamics as compared to the largest Lyapunov exponent. Adaptation does not seem to influence complexity in the system for experienced prosthesis users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

astroABC : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation

Given the complexity of modern cosmological parameter inference where we arefaced with non-Gaussian data and noise, correlated systematics and multi-probecorrelated data sets, the Approximate Bayesian Computation (ABC) method is apromising alternative to traditional Markov Chain Monte Carlo approaches in thecase where the Likelihood is intractable or unknown. The ABC method is called"Likelihood free" as it avoids explicit evaluation of the Likelihood by using aforward model simulation of the data which can include systematics. Weintroduce astroABC, an open source ABC Sequential Monte Carlo (SMC) sampler forparameter estimation. A key challenge in astrophysics is the efficient use oflarge multi-probe datasets to constrain high dimensional, possibly correlatedparameter spaces. With this in mind astroABC allows for massive parallelizationusing MPI, a framework that handles spawning of jobs across multiple nodes. Akey new feature of astroABC is the ability to create MPI groups with differentcommunicators, one for the sampler and several others for the forward modelsimulation, which speeds up sampling time considerably. For smaller jobs thePython multiprocessing option is also available. Other key features include: aSequential Monte Carlo sampler, a method for iteratively adapting tolerancelevels, local covariance estimate using scikit-learn's KDTree, modules forspecifying optimal covariance matrix for a component-wise or multivariatenormal perturbation kernel, output and restart files are backed up everyiteration, user defined metric and simulation methods, a module for specifyingheterogeneous parameter priors including non-standard prior PDFs, a module forspecifying a constant, linear, log or exponential tolerance level,well-documented examples and sample scripts. This code is hosted online athttps://github.com/EliseJ/astroABC

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Population genomics of the eastern cottonwood ( Populus deltoides )

Abstract Despite its economic importance as a bioenergy crop and key role in riparian ecosystems, little is known about genetic diversity and adaptation of the eastern cottonwood ( Populus deltoides ). Here, we report the first population genomics study for this species, conducted on a sample of 425 unrelated individuals collected in 13 states of the southeastern United States. The trees were genotyped by targeted resequencing of 18,153 genes and 23,835 intergenic regions, followed by the identification of single nucleotide polymorphisms ( SNP s). This natural P. deltoides population showed low levels of subpopulation differentiation ( F ST = 0.022–0.106), high genetic diversity (θ W = 0.00100, π = 0.00170), a large effective population size ( N e ≈ 32,900), and low to moderate levels of linkage disequilibrium. Additionally, genomewide scans for selection (Tajima's D ), subpopulation differentiation ( X T X ), and environmental association analyses with eleven climate variables carried out with two different methods ( LFMM and BAYENV 2) identified genes putatively involved in local adaptation. Interestingly, many of these genes were also identified as adaptation candidates in another poplar species, Populus trichocarpa , indicating possible convergent evolution. This study constitutes the first assessment of genetic diversity and local adaptation in P. deltoides throughout the southern part of its range, information we expect to be of use to guide management and breeding strategies for this species in future, especially in the face of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Rietveld refinement of the structures of 1.0 C-S-H and 1.5 C-S-H

Low-Q region Rietveld analyses were performed on C-S-H synchrotron XRD patterns, using the software MAUD. Two different crystal structures of tobermorite 11 A were used as a starting model: monoclinic ordered Merlino tobermorite, and orthorhombic disordered Hamid tobermorite. Structural modifications were required to adapt the structures to the chemical composition and the different interlayer spacing of the C-S-H samples. Refinement of atomic positions was done by using special constraints called fragments that maintain interatomic distances and orientations within atomic polyhedra. Anisotropic crystallite size refinement showed that C-S-H has a nanocrystalline disordered structure with a preferred direction of elongation of the nanocrystallites in the plane of the Ca interlayer. The quality of the fit showed that the monoclinic structure gives a more adequate representation of C-S-H, whereas the disordered orthorhombic structure can be considered a more realistic model if the lack of long-range order of the silica chain along the c-direction is assumed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Asteroid models from photometry and complementary data sources

I discuss inversion methods for asteroid shape and spin reconstruction with photometry (lightcurves) and complementary data sources such as adaptive optics or other images, occultation timings, interferometry, and range-Doppler radar data. These are essentially different sampling modes (generalized projections) of plane-of-sky images. An important concept in this approach is the optimal weighting of the various data modes. The maximum compatibility estimate, a multi-modal generalization of the maximum likelihood estimate, can be used for this purpose. I discuss the fundamental properties of lightcurve inversion by examining the two-dimensional case that, though not usable in our three-dimensional world, is simple to analyze, and it shares essentially the same uniqueness and stability properties as the 3-D case. After this, I review the main aspects of 3-D shape representations, lightcurve inversion, and the inclusion of complementary data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Radiological Survey of Contaminated Installations of Research Reactor before Dismantling in High Dose Conditions with Complex for Remote Measurements of Radioactivity - 12069

Decontamination and decommissioning of the research reactors MR (Testing Reactor) and RFT (Reactor of Physics and Technology) has recently been initiated in the National Research Center (NRC) 'Kurchatov institute', Moscow. These research reactors have a long history and many installations - nine loop facilities for experiments with different kinds of fuel. When decommissioning nuclear facilities it is necessary to measure the distribution of radioactive contamination in the rooms and at the equipment at high levels of background radiation. At 'Kurchatov Institute' some special remote control measuring systems were developed and they are applied during dismantling of the reactors MR and RFT. For a survey of high-level objects a radiometric system mounted on the robotic Brokk vehicle is used. This system has two (4π and collimated) dose meters and a high resolution video camera. Maximum measured dose rate for this system is ∼8.5 Sv/h. To determine the composition of contaminants, a portable spectrometric system is used. It is a remotely controlled, collimated detector for scanning the distribution of radioactive contamination. To obtain a detailed distribution of contamination a remote-controlled gamma camera is applied. For work at highly contaminated premises with non-uniform background radiation, another camera is equipped with rotating coded mask (coded aperture imaging). As a result, a new system of instruments for remote radioactivity measurements with wide range of sensitivity and angular resolution was developed. The experience and results of measurements in different areas of the reactor and at its loop installations, with emphasis on the radioactive survey of highly-contaminated samples, are presented. These activities are conducted under the Federal Program for Nuclear and Radiation Safety of Russia. Adaptation of complex remote measurements of radioactivity and survey of contaminated installations of research reactor before dismantling in high dose conditions has proven successful. The radioactivity measuring devices for operation at high, non-uniform dose background were tested in the field and a new data of measurement of contamination distribution in the premises and installations were obtained. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Multi-channel optical detection system and method for multi-chamber assays

A multi-channel optical detection system includes a base unit adapted to receive a multi-chamber assay cartridge having a plurality of reaction chambers loaded with a sample and an optical detection reagent, and an optical detection unit having a multi-channel optical block having a plurality of detection channels each with an associated light source, and an optic sensor. The optical detection unit is connectable to the base unit so that interrogation ports of the detection channels are optically aligned with optically transparent windows of the reaction chambers of a loaded cartridge, so that upon initialization, light sources are activated to interrogate reaction products in the reaction chambers and detect the optical responses therefrom.

Dugan, Lawrence C.↗
DOE OSTI2018

Efficient Surrogate Model Development: Impact of Sample Size and Underlying Model Dimensions

This study compares eight surrogate-model construction approaches using computational experiments. Here, the construction approaches considered include: Artificial Neural Networks (ANNs), Automated Learning of Algebraic Models using Optimization (ALAMO), Radial Basis Networks (RBNs), Extreme Learning Machines (ELMs), Gaussian Progress Regression (GPR), Random Forests (RFs), Support Vector Regression (SVR), and Multivariate Adaptive Regression Splines. Each approach is used to construct surrogate models for predicting the outputs of thirty-four test functions. The data used to construct surrogate models were generated using Latin Hypercube Sampling (LHS), Halton and Sobol sampling methods. We studied the impact of sampling method, sample size, and challenge function characteristics on the accuracy of surrogate model predictions. Our results revealed that for smaller sample sizes, on average, surrogate models trained using the data points generated by Sobol sequences provided the best estimation for all surrogate model construction approaches. As the sample size increased, the impact of sampling methods diminished. The comparison of surrogate-modeling construction approaches at large sample sizes revealed that surrogate models trained using ANN, ALAMO, and ELM yielded smaller root mean squared error and higher adjusted R-squared values than the models trained using the rest of the approaches.

42 ENGINEERING↗
DOE OSTI2021

Cosmic Inference: Constraining Parameters with Observations and a Highly Limited Number of Simulations

We look at cosmological probes that pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters that characterize the underlying physical system-our universe, from these observations and theoretical forward-modeling. The only way to accurately forward-model physical behavior on small scales is via expensive numerical simulations, which are further “emulated” due to their high cost. Emulators are commonly built with a set of simulations covering the parameter space with Latin hypercube sampling and an interpolation procedure; the aim is to establish an approximately constant prediction error across the hypercube. In this paper, we provide a description of a novel statistical framework for obtaining accurate parameter constraints. The proposed framework uses multi-output Gaussian process emulators that are adaptively constructed using Bayesian optimization methods with the goal of maintaining a low emulation error in the region of the hypercube preferred by the observational data. In this paper, we compare several approaches for constructing multi-output emulators that enable us to take possible inter-output correlations into account while maintaining the efficiency needed for inference. Using a Lyα forest flux power spectrum, we demonstrate that our adaptive approach requires considerably fewer-by a factor of a few in the Lyα P(k) case considered here-simulations compared to the emulation based on Latin hypercube sampling, and that the method is more robust in reconstructing parameters and their Bayesian credible intervals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Large-Area Graphene Films as Target Surfaces for Highly Reproducible Matrix-Assisted Laser Desorption Ionization Suitable for Quantitative Mass Spectrometry

Due to the known sweet-spot issues that intrinsically arise from inhomogeneous formation of matrix-analyte crystals utilized as samples in matrix-assisted laser desorption ionization (MALDI) mass spectrometry, its reproducibility and thus its applications for quantification have been somewhat limited. In this paper, we report a simple strategy to improve the uniformity of matrix-analyte crystal spots, which we realized by adapting large-area graphene films, i.e., non-inert, interacting surfaces, as target surfaces. In this example, the graphitic surfaces of the graphene films interact with excess matrix molecules during the sample drying process, which induces spontaneous formation of optically uniform MALDI sample crystal layers on the film surfaces. Further, mass spectrometric imaging reveals that the visible uniformity is indeed accompanied by reproducible MALDI ionization over an entire sample spot, which greatly suppresses the appearance of sweet spots. The results of this study confirm that the proposed method achieves good linear responses of ion intensity to the analyte concentration (R{sup 2} > 0.99) with small relative standard deviations (σ < 10%), which is a range applicable for quantitative measurements using MALDI mass spectrometry. .

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Rapid in situ nutrient element distribution in plants and soils using laser-induced breakdown spectroscopy ($\mathrm{LIBS}$)

The aim of this study is to develop and test the applicability of a rapid in situ plant chemistry profiling technique to determine elemental composition of small-volume plant and soil samples obtained from a woody bioenergy crop species, Populus trichocarpa. Expanding the research tools available to characterize the nutrient element correlations among plant tissue types and soil depths is a critical need in the path of understanding productivity and adaptation of plants to variations in external abiotic and biotic factors and developing sustainable perennial bioenergy crops that are co-optimized for biomass valorization aboveground and carbon sequestration belowground. Several plant root, stem, and soil samples were tested using laser-induced breakdown spectroscopy (LIBS) to evaluate the presence and distribution of nutrient elements. Samples were tested as collected and after being dried and cross sectioned to evaluate the effectiveness of using LIBS for in situ analysis on plant samples. The collected LIBS spectra show the elemental peaks were the same in both the as collected and prepared samples for roots and stems. Qualitative amounts of elements such as H, C, N, O, Li, Na, Mg, K, Ca, Fe, Al, and Si were able to be identified rapidly in raw samples. Here in this report we demonstrate suitability of LIBS in obtaining rapid, in situ, elemental distribution in plant and soil samples, utilizing only small sample volumes and minimal sample preparation. This demonstration opens up a new rapid phenotyping avenue necessary to fill the asymmetrical knowledge gaps in belowground performance of plant systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Marine Corps Base Camp Lejeune NRE Carbon Flux

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.In situ CO2 sensors were deployed on the AVPs at Stones Bay and Morgans Bay between AEM-1 ongoing bi-monthly discrete sampling events. CO2 fluxes were calculated using measured pCO2, and pCO2 estimated based on a linear interpolation of measured pCO2 (between start and end of each deployment). The intention of this dataset is to asses whether such a linear interpolation of pCO2 introduces a significant error to CO2 flux calculations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Np-237 LoD Measurement by TIMS-Multi-Ion Counting Total Evaporation [Poster]

Requests for ultra-low-level 237 Np analyses highlight the importance of a robust chemical purification and measurement technique for Np. In FY2022, LANL is quantifying the instrumental 237 Np LoD. Need to incorporate a chemical purification procedure for TIMS-MICTE sample preparation. What is the recovery of the chemical purification procedure? What is the ultimate detection limit that can be achieved while incorporating a chemical purification procedure? We have adapted and refined the Pu TIMS-MICTE method for Np analyses. We have determined expected uncertainties for 237 Np TIMS-MICTE measurements. We have increased sensitivity through technique improvements. We have improved method reliability for Np analyses and increased throughput. Apply knowledge gained from progress made in FY2022 to further develop Np sample purification and analyses by TIMSMICTE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multi-level Monte Carlo methods in chemical applications with Lennard-Jones potentials and other landscapes with isolated singularities

We describe and compare outcomes of various Multi-Level Monte Carlo (MLMC) method variants, motivated by the potential of improved computational efficiency over rejection based Monte Carlo, which scales poorly with problem dimension. With an eye toward its application to computational chemical physics, we test MLMC's ability to sample trajectories on two problems — a familiar double-well potential, with known stationary distributions, and a Lennard-Jones solid potential (a Galton Board). By sampling Brownian motion trajectories, we are able to compute expectations of observable averages. These multi-basin potential energy problems capture the essence of the challenges with using MLMC, namely, maintaining correspondence of sample paths as time-resolution is varied. Addressing this challenge properly can lead to MLMC significantly outperforming standard Monte Carlo path sampling. We describe the essence of this problem and suggest strategies that circumvent diverging multilevel sample paths for an important class of problems. In the tests we also compare the computational cost of several, “adaptive,” variants of MLMC. Our results demonstrate that MLMC overcomes the collision, time scale limitation of the more familiar Brownian path MC samplers, and our implementation provides tunable error thresholds, making MLMC a promising candidate for application to larger and more complex molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Longitudinal Investigation of Adaptive Functioning Following Conformal Irradiation for Pediatric Craniopharyngioma and Low-Grade Glioma

Purpose: Children treated for brain tumors with conformal radiation therapy experience preserved cognitive outcomes. Early evidence suggests that adaptive functions or independent-living skills may be spared. This longitudinal investigation prospectively examined intellectual and adaptive functioning during the first 5 years following irradiation for childhood craniopharyngioma and low-grade glioma (LGG). The effect of visual impairment on adaptive outcomes was investigated. Methods and Materials: Children with craniopharyngioma (n=62) and LGG (n=77) were treated using conformal or intensity modulated radiation therapy. The median age was 8.05 years (3.21-17.64 years) and 8.09 years (2.20-19.27 years), respectively. Serial cognitive evaluations including measures of intelligence quotient (IQ) and the Vineland Adaptive Behavior Scales (VABS) were conducted at preirradiation baseline, 6 months after treatment, and annually through 5 years. Five hundred eighty-eight evaluations were completed during the follow-up period. Results: Baseline assessment revealed no deficits in IQ and VABS indices for children with craniopharyngioma, with significant (P<.05) longitudinal decline in VABS Communication and Socialization indices. Clinical factors associated with more rapid decline included females and preirradiation chemotherapy (interferon). The only change in VABS Daily Living Skills correlated with IQ change (r=0.34; P=.01) in children with craniopharyngioma. Children with LGG performed below population norms (P<.05) at baseline on VABS Communication, Daily Living Indices, and the Adaptive Behavior Composite, with significant (P<.05) longitudinal decline limited to VABS Communication. Older age at irradiation was a protective factor against longitudinal decline. Severe visual impairment did not independently correlate with poorer adaptive outcomes for either tumor group. Conclusions: There was relative sparing of postirradiation functional outcomes over time in this sample. Baseline differences in functional abilities before the initiation of irradiation suggested that other factors influence functional outcomes above and beyond the effects of irradiation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Superior CO 2 /N 2 separation performance of highly branched Poly(1,3 dioxolane) plasticized by polyethylene glycol

With its high content of CO 2 -philic ether oxygen groups, poly(1,3-dioxolane) (PDXLA) has emerged as an attractive platform to achieve excellent CO 2 /N 2 separation properties for post-combustion carbon capture. Herein we demonstrate that the separation properties of PDXLA can be further enhanced by plasticizing with miscible polyethylene glycol (PEG)-based additives using an integrated experimentation and modeling approach. The effects of the chain end groups and loading level of the additives on the physical properties of the blends are thoroughly investigated, including glass transition temperature (T g ), fractional free volume, and gas transport properties, and the effects can be satisfactorily described using models available for homogeneous blends. Notably, a T g -integrated free volume model is adapted to successfully interpret the unified effect of the blend composition and temperature on gas diffusivity and permeability. A sample containing 45 mass% PEG dimethyl ether (PEGDME with a molecular mass of 240 g/mol) displays stable mixed-gas CO 2 permeability of 1540 Barrer and CO 2 /N 2 selectivity of 40 when challenged with a model flue gas at 60 °C, outperforming Robeson's 2008 upper bound. Elucidating how small plasticizers impact gas transport in homogeneous blends may unravel a facile way to design high-performance membranes for gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Space‐Time Causal Discovery in Earth System Science: A Local Stencil Learning Approach

Causal discovery tools enable scientists to infer meaningful relationships from observational data, spurring advances in fields as diverse as biology, economics, and climate science. Despite these successes, the application of causal discovery to space-time systems remains immensely challenging due to the high-dimensional nature of the data. For example, in climate sciences, modern observational temperature records over the past few decades regularly measure thousands of locations around the globe. To address these challenges, we introduce Causal Space-Time Stencil Learning (CaStLe), a novel meta-algorithm for discovering causal structures in complex space-time systems. CaStLe leverages regularities in local space-time dependencies to learn governing global dynamics. This local perspective eliminates spurious confounding and drastically reduces sample complexity, making space-time causal discovery practical and effective. For causal discovery, CaStLe flexibly accepts any appropriately adapted time series causal discovery algorithm to recover local causal structures. These advances enable causal discovery of geophysical phenomena that were previously unapproachable, including non-periodic, transient phenomena such as volcanic eruption plumes. Regularities in local space-time dependencies are transformed into informative spatial replicates, which actually improve CaStLe's performance when applied to ever-larger spatial grids. We successfully apply CaStLe to discover the atmospheric dynamics governing the climate response to the 1991 Mount Pinatubo volcanic eruption. We provide validation experiments to demonstrate the effectiveness of CaStLe over existing causal-discovery frameworks on a range of geophysics-inspired benchmarks while identifying the method's limitations and domains where its assumptions may not hold.

Nichol, J. Jake [Univ. of New Mexico, Albuquerque,↗
DOE OSTI2011

FAR-INFRARED PROPERTIES OF LYMAN BREAK GALAXIES FROM COSMOLOGICAL SIMULATIONS

Utilizing state-of-the-art adaptive mesh refinement cosmological hydrodynamic simulations with ultra-high resolution (114 h{sup -1} pc) and a large sample size ({>=}3300 galaxies of stellar mass {>=}10{sup 9} M{sub Sun }), we show how the stellar light of Lyman break galaxies at z = 2 is distributed between optical/ultraviolet (UV) and far-infrared (FIR) bands. With a single scalar parameter for dust obscuration we can simultaneously reproduce the observed UV luminosity function for the entire range (3-100 M{sub Sun} yr{sup -1}) and extant FIR luminosity function at the bright end ({>=}20 M{sub Sun} yr{sup -1}). We quantify that galaxies more massive or having higher star formation rate (SFR) tend to have larger amounts of dust obscuration mostly due to a trend in column density and in a minor part due to a mass (or SFR)-metallicity relation. It is predicted that the FIR luminosity function in the range SFR = 1-100 M{sub Sun} yr{sup -1} is a power law with a slope of about -1.7. We further predict that there is a 'galaxy desert' at SFR{sub FIR} < 0.02(SFR{sub UV}/10 M{sub Sun} yr{sup -1}){sup 2.1} M{sub Sun} yr{sup -1} in the SFR{sub UV} - SFR{sub FIR} plane. Detailed distributions of SFR{sub FIR} at a fixed SFR{sub UV} are presented. Upcoming observations by the Atacama Large Millimeter Array should test this model. If confirmed, it validates the predictions of the standard cold dark matter model and has important implications on the intrinsic SFR function of galaxies at high redshift.

79 ASTRONOMY AND ASTROPHYSICS↗