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At least 1,189 records · Page 66

The evaluation of a semi-automated procedure for classifying corn and soybeans without ground data

Since the launch of Landsat 1 in 1973, research has been conducted with the objective to develop technology which would make it possible to achieve large area crop estimates on the basis of Landsat Multispectral Sensor (MSS) data without the benefit of ground observed training data. The present investigation is concerned with the evaluation of a technology which was developed to produce estimates of corn and soybean acreage in the central U.S. Corn Belt (Iowa, Illinois, and Indiana). A description of the employed technique is provided and details regarding the test of the developed technology are discussed. The obtained results show that considerable progress has been made toward creating an automatic, self-adapting procedure which has favorable bias and variance characteristics.

Metzler, M. D.↗

Quantifying UAS Observation Error Variance Used in Data Assimilation Systems and Its Impact on Predictive Skill

Observation error determines the weights of the observations and background state used in data assimilation to generate analyses. Quantifying observation error is critical for the optimal assimilation of observational data sets. Uncrewed Aircraft System (UAS) observations have shown potential benefits in filling observational gaps in the lower atmosphere; however, characterization of their error characteristics has been limited. To optimize the use of UAS observations in numerical weather prediction, UAS observation error is estimated based on the 3‐cornered hat diagnostic approach which uses three independent estimates of the atmospheric state. This approach is applied to data from the 2018 Lower Atmospheric Profiling Studies at Elevation‐a Remotely‐piloted Aircraft Team Experiment field campaign using collocated UAS and rawinsonde observations along with output from a set of convection‐permitting model simulations. The estimated observation error values for UAS temperature, wind, and relative humidity measurements were found to be only weakly dependent on height AGL with mean values equal to 0.5°C, 0.8 m s −1 , and 3%, respectively. Only the newly estimated observation error for temperature differed from that previously used to assimilate commercial aircraft observations into global models (1.0°C). However, using this reduced temperature observation error produced more accurate mesoscale analyses and forecasts of both terrain‐driven flows and convection initiation generated by colliding outflow boundaries within the San Luis Valley of Colorado.

54 ENVIRONMENTAL SCIENCES↗

A STUDY OF FUNDAMENTAL LIMITATIONS TO STATISTICAL DETECTION OF REDSHIFTED H I FROM THE EPOCH OF REIONIZATION

In this paper, we explore for the first time the relative magnitudes of three fundamental sources of uncertainty, namely, foreground contamination, thermal noise, and sample variance, in detecting the H I power spectrum from the epoch of reionization (EoR). We derive limits on the sensitivity of a Fourier synthesis telescope to detect EoR based on its array configuration and a statistical representation of images made by the instrument. We use the Murchison Widefield Array (MWA) configuration for our studies. Using a unified framework for estimating signal and noise components in the H I power spectrum, we derive an expression for and estimate the contamination from extragalactic point-like sources in three-dimensional k-space. Sensitivity for EoR H I power spectrum detection is estimated for different observing modes with MWA. With 1000 hr of observing on a single field using the 128 tile MWA, EoR detection is feasible (S/N >1 for k ∼< 0.8 Mpc{sup –1}). Bandpass shaping and refinements to the EoR window are found to be effective in containing foreground contamination, which makes the instrument tolerant to imaging errors. We find that for a given observing time, observing many independent fields of view does not offer an advantage over a single field observation when thermal noise dominates over other uncertainties in the derived power spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗

TU-AB-BRC-08: Egs-brachy, a Fast and Versatile Monte Carlo Code for Brachytherapy Applications

Purpose: To introduce egs-brachy, a new, fast, and versatile Monte Carlo code for brachytherapy applications. Methods: egs-brachy is an EGSnrc user-code based on the EGSnrc C++ class library (egs++). Complex phantom, applicator, and source model geometries are built using the egs++ geometry module. egs-brachy uses a tracklength estimator to score collision kerma in voxels. Interaction, spectrum, energy fluence, and phase space scoring are also implemented. Phase space sources and particle recycling may be used to improve simulation efficiency. HDR treatments (e.g. stepping source through dwell positions) can be simulated. Standard brachytherapy seeds, as well as electron and miniature x-ray tube sources are fully modelled. Variance reduction techniques for electron source simulations are implemented (Bremsstrahlung cross section enhancement, uniform Bremsstrahlung splitting, and Russian Roulette). TG-43 parameters of seeds are computed and compared to published values. Example simulations of various treatments are carried out on a single 2.5 GHz Intel Xeon E5-2680 v3 processor core. Results: TG-43 parameters calculated with egs-brachy show excellent agreement with published values. Using a phase space source, 2% average statistical uncertainty in the PTV ((2mm){sup 3} voxels) can be achieved in 10 s for 100 {sup 125}I or {sup 103}Pd seeds in a 36.2 cm{sup 3} prostate PTV, 31 s for 64 {sup 103}Pd seeds in a 64 cm{sup 3} breast PTV, and 56 s for a miniature x-ray tube in a 27 cm{sup 3} breast PTV. Comparable uncertainty is reached in 12 s in a (1 mm){sup 3} water voxel 5 mm away from a COMS 16mm eye plaque with 13 {sup 103}Pd seeds. Conclusion: The accuracy of egs-brachy has been demonstrated through benchmarking calculations. Calculation times are sufficiently fast to allow full MC simulations for routine treatment planning for diverse brachytherapy treatments (LDR, HDR, miniature x-ray tube). egs-brachy will be available as free and open-source software to the medical physics research community. This work is partially funded by the Canada Research Chairs program, the Natural Sciences and Engineering Research Council of Canada, and the Ontario Ministry of Research and Innovation (Ontario Early Researcher Award).

60 APPLIED LIFE SCIENCES↗

On the design of fault-tolerant robotic manipulator systems

Robotic systems are finding increasing use in space applications. Many of these devices are going to be operational on board the Space Station Freedom. Fault tolerance has been deemed necessary because of the criticality of the tasks and the inaccessibility of the systems to maintenance and repair. Design for fault tolerance in manipulator systems is an area within robotics that is without precedence in the literature. In this paper, we will attempt to lay down the foundations for such a technology. Design for fault tolerance demands new and special approaches to design, often at considerable variance from established design practices. These design aspects, together with reliability evaluation and modeling tools, are presented. Mechanical architectures that employ protective redundancies at many levels and have a modular architecture are then studied in detail. Once a mechanical architecture for fault tolerance has been derived, the chronological stages of operational fault tolerance are investigated. Failure detection, isolation, and estimation methods are surveyed, and such methods for robot sensors and actuators are derived. Failure recovery methods are also presented for each of the protective layers of redundancy. Failure recovery tactics often span all of the layers of a control hierarchy. Thus, a unified framework for decision-making and control, which orchestrates both the nominal redundancy management tasks and the failure management tasks, has been derived. The well-developed field of fault-tolerant computers is studied next, and some design principles relevant to the design of fault-tolerant robot controllers are abstracted. Conclusions are drawn, and a road map for the design of fault-tolerant manipulator systems is laid out with recommendations for a 10 DOF arm with dual actuators at each joint.

Tesar, Delbert↗

Two-Year Cosmology Large Angular Scale Surveyor (CLASS) Observations: 40GHz Telescope Pointing, Beam Profile, Window Function, and Polarization Performance

The Cosmology Large Angular Scale Surveyor (CLASS) is a telescope array that observes the cosmic microwave background (CMB) over 75% of the sky from the Atacama Desert, Chile, at frequency bands centered near 40, 90, 150, and 220 GHz. CLASS measures the large angular scale (1°~< θ >=90°) CMB polarization to constrain the tensor-to-scalar ratio at the r ∼ 0.01 level and the optical depth to last scattering to the sample variance limit. This paper presents the optical characterization of the 40 GHz telescope during its first observation era, from 2016 September to 2018 February. High signal-to-noise observations of the Moon establish the pointing and beam calibration. The telescope boresight pointing variation is <0°. 023 (<1.6% of the beam’s full width at half maximum (FWHM)). We estimate beam parameters per detector and in aggregate, as in the CMB survey maps. The aggregate beam has an FWHM of 1°.579 ± 0°.001 and a solid angle of 838 ± 6 μsr, consistent with physical optics simulations. The corresponding beam window function has a sub-percent error per multipole at ℓ < 200. An extended 90° beam map reveals no significant far sidelobes. The observed Moon polarization shows that the instrument polarization angles are consistent with the optical model and that the temperature-to-polarization leakage fraction is <10(exp −4) (95% C.L.). We find that the Moon-based results are consistent with measurements of M42, RCW 38, and Tau A from CLASS’s CMB survey data. In particular, Tau A measurements establish degree- level precision for instrument polarization angles.

Xu, Zhilei↗

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

54 ENVIRONMENTAL SCIENCES↗

Predicting Cycle-to-Cycle Variation With Concurrent Cycles in a Gasoline Direct Injected Engine With Large Eddy Simulations

High cycle-to-cycle variation (CCV) is detrimental to engine performance, as it leads to poor combustion and high noise and vibration. In this work, CCV in a gasoline engine is studied using large eddy simulation (LES). The engine chosen as the basis of this work is a single-cylinder gasoline direct injection (GDI) research engine. Two stoichiometric part-load engine operating points (6 BMEP, 2000 RPM) were evaluated: a non-dilute (0% EGR) case and a dilute (18% EGR) case. The experimental data for both operating conditions had 500 cycles. The measured CCV in IMEP was 1.40% for the non-dilute case and 7.78% for the dilute case. To estimate CCV from simulation, perturbed concurrent cycles of engine simulations were compared to consecutively obtained engine cycles. The motivation behind this is that running consecutive cycles to estimate CCV is quite time-consuming. For example, running 100 consecutive cycles requires 2–3 months (on a typical cluster), however, by running concurrently one can potentially run all 100 cycles at the same time and reduce the overall turnaround time for 100 cycles to the time taken for a single cycle (2 days). The goal of this paper is to statistically determine if concurrent cycles, with a perturbation applied to each individual cycle at the start, can be representative of consecutively obtained cycles and accurately estimate CCV. 100 cycles were run for each case to obtain statistically valid results. The concurrent cycles began at different timings before the combustion event, with the motivation to identify the closest time before spark to minimize the run time. Only a single combustion cycle was run for each concurrent case. The calculated standard deviation of peak pressure and coefficient of variance (COV) of indicated mean effective pressure (IMEP) were compared between the consecutive and concurrent methods to quantify CCV. It was found that the concurrent method could be used to predict CCV with either a velocity or numerical perturbation. Here, a large and small velocity perturbation were compared and both produced correct predictions, implying that the type of perturbation is not important to yield a valid realization. Starting the simulation too close to the combustion event, at intake valve close (IVC) or at spark timing, under-predicted the CCV. When concurrent simulations were initiated during or before the intake even, at start of injection (SOI) or earlier, distinct and valid realizations were obtained to accurately predict CCV for both operating points. By simulating CCV with concurrent cycles, the required wall clock time can be reduced from 2–3 months to 1–2 days. Additionally, the required core-hours can be reduced up to 41%, since only a portion of each cycle needs to be simulated.

42 ENGINEERING↗

Host phylogeny matters: Examining sources of variation in infection risk by blood parasites across a tropical montane bird community in India

Abstract Background Identifying patterns and drivers of infection risk among host communities is crucial to elucidate disease dynamics and predict infectious disease risk in wildlife populations. Blood parasites of the genera Plasmodium and Haemoproteus are a diverse group of vector-borne protozoan parasites that affect bird populations globally. Despite their widespread distribution and exceptional diversity, factors underlying haemosporidian infection risk in wild bird communities remain poorly understood. While some studies have examined variation in avian haemosporidian risk, researchers have primarily focused on host ecological traits without considering host phylogenetic relationships. In this study, we employ a phylogenetically informed approach to examine the association between host ecological traits and haemosporidian infection risk in endemic bird communities in the Western Ghats Sky Islands. Methods We used parasite sequence data based on partial mitochondrial cytochrome b gene, that was amplified from genomic DNA extracted from 1177 birds (28 species) across the Western Ghats to assess infection of birds with haemosporidian parasites. We employed a Bayesian phylogenetic mixed effect modelling approach to test whether haemosporidian infection risk was affected by seven species-specific and four individual-level ecological predictors. We also examined the effect of host phylogenetic relationships on the observed patterns of variation in haemosporidian infection risk by estimating phylogenetic signal. Results Our study shows that host ecological traits and host phylogeny differentially influence infection risk by Plasmodium (generalist parasite) and Haemoproteus (specialist parasite). For Plasmodium , we found that sociality, sexual dimorphism and foraging strata were important ecological predictors. For Haemoproteus , patterns of infection risk among host species were associated with sociality, species elevation and individual body condition. Interestingly, variance in infection risk explained by host phylogeny was higher for Haemoproteus parasites compared to Plasmodium . Conclusions Our study highlights that while host ecological traits promoting parasite exposure and host susceptibility are important determinants of infection risk, host phylogeny also contributes substantially to predicting patterns of haemosporidian infection risk in multi-host communities. Importantly, infection risk is driven by joint contributions of host ecology and host phylogeny and studying these effects together could increase our ability to better understand the drivers of infection risk and predict future disease threats. Graphical abstract

59 BASIC BIOLOGICAL SCIENCES↗

Efficient algorithms for use in probabilistic finite element analysis

This paper investigates the use of Fast Probability Integration (FPI) algorithms in a Finite Element environment. A method allowing the representation of correlated fields in terms of a vector of uncorrelated transformed variables, based on the spectral decomposition of the variance-covariance matrix is developed. The response of the deterministic model corresponding to selected perturbations of these uncorrelated variables is then obtained via a Newton-type iterative scheme. The results of the perturbed problems are used to construct a local representation of the model's behavior in the neighborhood of the deterministic state, which the FPI algorithm will use to estimate the reliability of the system. Although the proposed strategy has thus far only been applied to linear elastostatics, the extension of the method to a broader class of problems appears to be feasible.

Dias, J. B.↗

Evolution of the total ozone field during the breakdown of the Antarctic circumpolar vortex

Nine years of total ozone measurements from the TOMS on Nimbus 7 are used to study the evolution of the Southern Hemisphere total ozone field during the breakdown of the Antarctic circumpolar vortex. The TOMS data provide detailed maps of the morphology of the ozone field and reliable estimates of the vertically integrated meridional transport of ozone during the springtime period when the breakdown occurs (September, October, November). In estimating the ozone transport, chemical effects, including those thought to be responsible for the Antarctic ozone hole, are neglected. This approximation appears to be valid for time scales of a few days to a week. On this time scale, local ozone changes are primarily due to transport. Planetary-scale waves, especially zonal wave numbers 1 and 2 dominate the eddy variance and ozone transport. Wave number 1 is quasistationary, while wave number 2 is eastward moving with a period of about 10 days.

Bowman, Kenneth P.↗

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Belkin, Brenda L.↗

A Posteriori Correction of Forecast and Observation Error Variances

Proposed method of total observation and forecast error variance correction is based on the assumption about normal distribution of "observed-minus-forecast" residuals (O-F), where O is an observed value and F is usually a short-term model forecast. This assumption can be accepted for several types of observations (except humidity) which are not grossly in error. Degree of nearness to normal distribution can be estimated by the symmetry or skewness (luck of symmetry) a(sub 3) = mu(sub 3)/sigma(sup 3) and kurtosis a(sub 4) = mu(sub 4)/sigma(sup 4) - 3 Here mu(sub i) = i-order moment, sigma is a standard deviation. It is well known that for normal distribution a(sub 3) = a(sub 4) = 0.

Rukhovets, Leonid↗

Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new-generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach.While the new algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarsemodes,while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single-scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10-30% in the refractive index, and 10-40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part study.

aerosol retrieval algorithm↗

Kinematically enhanced interpolating operators for boosted hadrons

We propose to use interpolating operators for lattice quantum chromodynamics calculations of highly boosted pions and nucleons with kinematically enhanced ground-state overlap factors at large momentum. Because this kinematic enhancement applies to the signal but not the variance of the correlation function, these interpolating operators can achieve better signal-to-noise ratios at large momentum. We perform proof-of-principle calculations with boosted pions and nucleons using close-to-physical and larger quark masses to explore the utility of our proposal. Results for effective energies and matrix elements, as well as Lanczos ground-state energy estimators, are consistent with theoretical expectations for signal-to-noise improvement at large momenta.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Blinded challenge for precision cosmology with large-scale structure: Results from effective field theory for the redshift-space galaxy power spectrum

An accurate theoretical template for the galaxy power spectrum is key for the success of ongoing and future spectroscopic surveys. We examine to what extent the effective field theory (EFT) of large-scale structure is able to provide such a template and correctly estimate cosmological parameters. To that end, we initiate a blinded challenge to infer cosmological parameters from the redshift-space power spectrum of high-resolution mock catalogs mimicking the BOSS galaxy sample but covering a 100 times larger cumulative volume. This gigantic simulation volume allows us to separate systematic bias due to theoretical modeling from the statistical error due to sample variance. The challenge is to measure three unknown input parameters used in the simulation: the Hubble constant, the matter density fraction, and the clustering amplitude. We present analyses done by two independent teams, who have fitted the mock simulation data generated by yet another independent group. This allows us to avoid any confirmation bias by analyzers and to pin down possible tuning of the specific EFT implementations. Both independent teams have recovered the true values of the input parameters within subpercent statistical errors corresponding to the total simulation volume.

79 ASTRONOMY AND ASTROPHYSICS↗

CV4Quantum: Reducing the Sampling Overhead in Probabilistic Error Cancellation Using Control Variates

Quasiprobabilistic decompositions (QPDs) play a key role in maximizing the utility of near-term quantum hardware. For example, Probabilistic Error Cancellation (PEC) (an error mitigation technique) and circuit cutting (which enables large quantum computations to be performed on quantum hardware with a limited number of qubits) both involve QPDs. Computations based on QPDs typically incur large sampling overheads that grow exponentially with the number of error-terms mitigated or number of circuit-cuts employed, limiting their practical feasibility. In this work, we adapt the control variates variance reduction technique from the statistics literature in order to reduce the sampling overhead in QPD-based computations. We demonstrate our method using simulation experiments that mimic a realistic PEC scenario. In our experiments, we observed a more than 50% reduction in the number of samples needed to achieve a given precision, in more than 50% of the PEC-based estimations performed in the study when using our approach. We discuss how future research on constructing good control variates can lead to even stronger sampling overhead reduction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

TOPEX/POSEIDON tides estimated using a global inverse model

Altimetric data from the TOPEX/POSEIDON mission will be used for studies of global ocean circulation and marine geophysics. However, it is first necessary to remove the ocean tides, which are aliased in the raw data. The tides are constrained by the two distinct types of information: the hydrodynamic equations which the tidal fields of elevations and velocities must satisfy, and direct observational data from tide gauges and satellite altimetry. Here we develop and apply a generalized inverse method, which allows us to combine rationally all of this information into global tidal fields best fitting both the data and the dynamics, in a least squares sense. The resulting inverse solution is a sum of the direct solution to the astronomically forced Laplace tidal equations and a linear combination of the representers for the data functionals. The representer functions (one for each datum) are determined by the dynamical equations, and by our prior estimates of the statistics or errors in these equations. Our major task is a direct numerical calculation of these representers. This task is computationally intensive, but well suited to massively parallel processing. By calculating the representers we reduce the full (infinite dimensional) problem to a relatively low-dimensional problem at the outset, allowing full control over the conditioning and hence the stability of the inverse solution. With the representers calculated we can easily update our model as additional TOPEX/POSEIDON data become available. As an initial illustration we invert harmonic constants from a set of 80 open-ocean tide gauges. We then present a practical scheme for direct inversion of TOPEX/POSEIDON crossover data. We apply this method to 38 cycles of geophysical data records (GDR) data, computing preliminary global estimates of the four principal tidal constituents, M(sub 2), S(sub 2), K(sub 1) and O(sub 1). The inverse solution yields tidal fields which are simultaneously smoother, and in better agreement with altimetric and ground truth data, than previously proposed tidal models. Relative to the 'default' tidal corrections provided with the TOPEX/POSEIDON GDR, the inverse solution reduces crossover difference variances significantly (approximately 20-30%), even though only a small number of free parameters (approximately equal to 1000) are actually fit to the crossover data.

Egbert, Gary D.↗