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At least 145 records · Page 8

Identifying a regional aerosol baseline in the eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high-submicron-number-concentration aerosol events

Abstract. High-time-resolution measurements of in situ aerosol and cloud properties provide the ability to study regional atmospheric processes that occur on timescales of minutes to hours. However, one limitation to this approach is that continuous measurements often include periods when the data collected are not representative of the regional aerosol. Even at remote locations, submicron aerosols are pervasive in the ambient atmosphere with many sources. Therefore, periods dominated by local aerosol should be identified before conducting subsequent analyses to understand aerosol regional processes and aerosol–cloud interactions. Here, we present a novel method to validate the identification of regional baseline aerosol data by applying a mathematical algorithm to the data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility in the eastern North Atlantic (ENA). The ENA central facility (C1) includes an aerosol observing system (AOS) for the measurement of aerosol physical, optical, and chemical properties at time resolutions from seconds to minutes. A second temporary supplementary facility (S1), located ∼0.75 km from C1, was deployed for ∼1 year during the Aerosol and Cloud Experiments (ACE-ENA) campaign in 2017. First, we investigate the local aerosol at both locations. We associate periods of high submicron number concentration (Ntot) in the fine-mode condensation particle counter (CPC) and size distributions from the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) as a function of wind direction using a meteorology sensor with local sources. Elevated concentrations of Aitken-mode (< 100 nm diameter) particles were observed in correspondence with the wind directions associated with airport operations. At ENA, the Graciosa Airport and its associated activities were found to be the main sources of high-concentration aerosol events at ENA, causing peaks in 1 min Ntot that exceeded 8000 and 10 000 cm−3 at C1, in summer and winter, respectively, and 5000 cm−3 at S1 in summer. Periods with high Ntot not associated with these wind directions were also observed. As a result, the diverse local sources at ENA yielded a poor relationship between Ntot measurements collected at C1 and S1 (R2=0.03 with a slope =0.05±0.001). As a first approach to mask these events, the time periods when the wind direction was associated with the airport operations (west to northwest and southeast to south at C1 and east to south at S1) were applied. The meteorological masks removed 38.9 % of the data at C1 and 43.4 % at S1, and they did not significantly improve the relationship between the two sites (R2=0.18 with a slope =0.06±0.001). Due to the complexity of high-Ntot events observed at ENA, we develop and validate a mathematical ENA Aerosol Mask (ENA-AM) to identify high-Ntot events using 1 min resolution data from the AOS CPC at C1 and S1. After its parameterization and application, ENA-AM generated a high correlation between Ntot in the summer at C1 and S1 (R2=0.87 with a slope =0.84±0.001). We identified the regional baseline at ENA to be 428±228 cm−3 in the summer and 346±223 cm−3 in the winter. Lastly, we compared masked measurements from the AOS with the ARM Aerial Facility (AAF) during flights over C1 in the summer to understand submicron aerosol vertical mixing over C1. The high correlation (R2=0.71 with a slope of 1.04±0.01) observed between C1 and the AAF Ntot collected within an area of 10 km surrounding ENA and at altitudes < 500 m indicated that the submicron aerosol at ENA was well mixed within the first 500 m of the marine boundary layer during the month of July during ACE-ENA. Our novel method for determining a regional aerosol baseline at ENA can be applied to other time periods and at other locations with validation by a secondary site or additional collocated measurements.

54 ENVIRONMENTAL SCIENCES↗

3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves

Selection for yield at high planting density has reshaped the leaf canopy of maize, improving photosynthetic productivity in high density settings. Further optimization of canopy architecture may be possible. However, measuring leaf angles, the widely studied component trait of leaf canopy architecture, by hand is a labor and time intensive process. Here, we use multiple, calibrated, 2D images to reconstruct the 3D geometry of individual sorghum plants using a voxel carving based algorithm. Automatic skeletonization and segmentation of these 3D geometries enable quantification of the angle of each leaf for each plant. The resulting measurements are both heritable and correlated with manually collected leaf angles. This automated and scaleable reconstruction approach was employed to measure leaf-by-leaf angles for a population of 366 sorghum plants at multiple time points, resulting in 971 successful reconstructions and 3,376 leaf angle measurements from individual leaves. A genome wide association study conducted using aggregated leaf angle data identified a known large effect leaf angle gene, several previously identified leaf angle QTL from a sorghum NAM population, and novel signals. Genome wide association studies conducted separately for three individual sorghum leaves identified a number of the same signals, a previously unreported signal shared across multiple leaves, and signals near the sorghum orthologs of two maize genes known to influence leaf angle. Automated measurement of individual leaves and mapping variants associated with leaf angle reduce the barriers to engineering ideal canopy architectures in sorghum and other grain crops.

3D reconstruction↗

DISCo-microbe: design of an identifiable synthetic community of microbes

Microbiomes are extremely important for their host organisms, providing many vital functions and extending their hosts’ phenotypes. Natural studies of host-associated microbiomes can be difficult to interpret due to the high complexity of microbial communities, which hinders our ability to track and identify individual members along with the many factors that structure or perturb those communities. For this reason, researchers have turned to synthetic or constructed communities in which the identities of all members are known. However, due to the lack of tracking methods and the difficulty of creating a more diverse and identifiable community that can be distinguished through next-generation sequencing, most such in vivo studies have used only a few strains. To address this issue, we developed DISCo-microbe, a program for the design of an identifiable synthetic community of microbes for use in in vivo experimentation. The program is composed of two modules; (1) create, which allows the user to generate a highly diverse community list from an input DNA sequence alignment using a custom nucleotide distance algorithm, and (2) subsample, which subsamples the community list to either represent a number of grouping variables, including taxonomic proportions, or to reach a user-specified maximum number of community members. As an example, we demonstrate the generation of a synthetic microbial community that can be distinguished through amplicon sequencing. The synthetic microbial community in this example consisted of 2,122 members from a starting DNA sequence alignment of 10,000 16S rRNA sequences from the Ribosomal Database Project. We generated simulated Illumina sequencing data from the constructed community and demonstrate that DISCo-microbe is capable of designing diverse communities with members distinguishable by amplicon sequencing. Using the simulated data we were able to recover sequences from between 97–100% of community members using two different post-processing workflows. Furthermore, 97–99% of sequences were assigned to a community member with zero sequences being misidentified. We then subsampled the community list using taxonomic proportions to mimic a natural plant host–associated microbiome, ultimately yielding a diverse community of 784 members. DISCo-microbe can create a highly diverse community list of microbes that can be distinguished through 16S rRNA gene sequencing, and has the ability to subsample (i.e., design) the community for the desired number of members and taxonomic proportions. Although developed for bacteria, the program allows for any alignment input from any taxonomic group, making it broadly applicable. The software and data are freely available from GitHub and Python Package Index (PYPI).

16S rRNA↗

Fracture trends identified by ERTS-1 imagery in Utah and Nevada

The author has identified the following significant results. In the Utah-Nevada area, linear structural trends recorded on ERTS-1 imagery conform in part to previously recognized structures. In addition, the ERTS-1 imagery reveals cryptic structures not previously identified and not readily apparent in other imagery. These structures are illustrated by prominent east-west trending structures which appear to be concentrated in pre-volcanic rocks. This suggests that the structures are older than many of those with other trends which are equally prominent in volcanic and non-volcanic terrain. Since the older east-west structures may have controlled early Tertiary emplacement of magma or the ascent of mineralizing fluids, their recognition is important in minerial exploration. Soil-gas sampling and analysis for mercury content is being continued over structures, and projected trends of buried structures which appear, from studies of ERTS-1 imagery, to be favorable to mineralization. Comparison of ERTS-1 and Skylab imagery indicated that ERTS-1 imagery records more previously unrecognized linear structures than the Skylab imagery. In differentiating and identifying different rock types, the Skylab imagery appears to be more effective.

Jensen, M. L.↗

On identifying transfer functions and state equations for linear systems.

Two methods are established for identifying constant-coefficient, C to the 2n power type of noise-free linear systems if the time response data of the input-output or of all states are known. 2n response data are required to identify an nth-order transfer function or state equation for an unknown linear system. The order of the unknown system can be identified by checking a sequence of determinants. The Z transform and its inversion are mainly used.

Shieh, L. S.↗

Parameter identifiability of linear dynamical systems

It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.

Glover, K.↗

On the identifiability of linear dynamical systems

Consider the situation in which the unknown parameters of a stationary linear system may be parametrized by a set of unknown parameters. The question thus arises of when such a set of parameters can be uniquely identified on the basis of observed data. This problem is considered here both in the case of input and output observations and in the case of output observations in the presence of a white noise input. Conditions for local identifiability are derived for both situations and a sufficient condition for global identifiability is given for the former situation, i.e., when simultaneous input and output observations are available.

Glover, K.↗

Controller design and parameter identifiability studies for a large space antenna

The problem of control systems synthesis and parameter identifiability are considered for a large, space-based antenna. Two methods are considered for control system synthesis, the first of which uses torque actuators and collocated attitude and rate sensors, and the second method is based on the linear-quadratic-Gaussian (LQG) control theory. The predicted performance obtained by computing variances of pointing, surface and feed misalignment errors in the presence of sensor noise indicates that the LQG-based controller yields superior results. Since controller design requires the knowledge of the system parameters, the identifiability of the structural parameters is investigated by obtaining Cramer-Rao lower bounds. The modal frequencies are found to have the best identifiability, followed by damping ratios, and mode-slopes.

Joshi, S. M.↗

Near Identifiability of Dynamical Systems

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

Hadaegh, F. Y.↗

Structural error and identifiability

In most identification problems, the possibility of identifying a model from the observation of input and output is approached by first assuming that the model is an exact representation of the process. Since models are only approximations to a real process, this paper presents a concrete way of taking into account the difference in structure between the model and the process it represents. The identifiability problem is reformulated on the basis of equivalence and near-equivalence between model and process. Necessary and sufficient conditions under which the differences between the outputs of the process and a model remains within a desired bound in the presence of modeling error are given. Necessary and sufficient conditions for the identifiability of parameters are presented.

Hadaegh, F. Y.↗

Analysis of adaptive identifiers in the presence of unmodelled dynamics: Averaging and tuned parameters

The behavior of a standard identifier is analyzed for the case in which the plant contains additional dynamics, called unmodeled dynamics, which invalidate the known order assumption. An input richness condition is obtained that does not depend on the order of the unmmodeled dynamics to guarantee persistency of excitation (PE) of the regressor. It is shown that the PE condition leads to a BIBO stability property for the identifier. The method of averaging is used to define formally the notion of tuned parameters as the equilibrium of the identifier-averaged system. It is shown that the tuned parameters always exist and that the actual parameters converge to some neighborhood of the tuned parameters. An explicit expression is derived to calculate and interpret them as the fixed parameter values that minimize the mean-squared output error.

Mason, J. E.↗

Torsional vestibulo-ocular reflex measurements for identifying otolith asymmetries possibly related to space motion sickness susceptibility

Recent studies have identified significant correlations between space motion sickness susceptibility and measures of disconjugate torsional eye movements recorded during parabolic flights. These results support an earlier proposal which hypothesized that an asymmetry of otolith function between the two ears is the cause of space motion sickness. It may be possible to devise experiments that can be performed in the 1 g environment on earth that could identify and quantify the presence of asymmetric otolith function. This paper summarizes the known physiological and anatomical properties of the otolith organs and the properties of the torsional vestibulo-ocular reflex which are relevant to the design of a stimulus to identify otolith asymmetries. A specific stimulus which takes advantage of these properties is proposed.

Peterka, Robert J.↗

On identified predictive control

Self-tuning control algorithms are potential successors to manually tuned PID controllers traditionally used in process control applications. A very attractive design method for self-tuning controllers, which has been developed over recent years, is the long-range predictive control (LRPC). The success of LRPC is due to its effectiveness with plants of unknown order and dead-time which may be simultaneously nonminimum phase and unstable or have multiple lightly damped poles (as in the case of flexible structures or flexible robot arms). LRPC is a receding horizon strategy and can be, in general terms, summarized as follows. Using assumed long-range (or multi-step) cost function the optimal control law is found in terms of unknown parameters of the predictor model of the process, current input-output sequence, and future reference signal sequence. The common approach is to assume that the input-output process model is known or separately identified and then to find the parameters of the predictor model. Once these are known, the optimal control law determines control signal at the current time t which is applied at the process input and the whole procedure is repeated at the next time instant. Most of the recent research in this field is apparently centered around the LRPC formulation developed by Clarke et al., known as generalized predictive control (GPC). GPC uses ARIMAX/CARIMA model of the process in its input-output formulation. In this paper, the GPC formulation is used but the process predictor model is derived from the state space formulation of the ARIMAX model and is directly identified over the receding horizon, i.e., using current input-output sequence. The underlying technique in the design of identified predictive control (IPC) algorithm is the identification algorithm of observer/Kalman filter Markov parameters developed by Juang et al. at NASA Langley Research Center and successfully applied to identification of flexible structures.

Bialasiewicz, Jan T.↗

Effect of Uncertainty of Identified Parameters on Structural Damage Detection

This paper presents a study of the effect of the uncertainty of identified parameters on the damage detection of structure. The identified parameters, which are obtained by applying system identification algorithms to analyze the time-domain response data, have uncertainty due to noise, environmental change, etc. The damage of some structural elements may have less effect on the identified parameters than noise or environmental change, so some damage situations cannot be distinguished under these circumstances. An algorithm is presented to determine whether the considered damage can be distinguished. A twenty-bay truss structure is used to demonstrate and verify the study.

Davidson, Mario↗

Multiple Changes to Reusable Solid Rocket Motors, Identifying Hidden Risks

The Space Shuttle Reusable Solid Rocket Motor (RSRM) baseline is subject to various changes. Changes are necessary due to safety and quality improvements, environmental considerations, vendor changes, obsolescence issues, etc. The RSRM program has a goal to test changes on full-scale static test motors prior to flight due to the unique RSRM operating environment. Each static test motor incorporates several significant changes and numerous minor changes. Flight motors often implement multiple changes simultaneously. While each change is individually verified and assessed, the potential for changes to interact constitutes additional hidden risk. Mitigating this risk depends upon identification of potential interactions. Therefore, the ATK Thiokol Propulsion System Safety organization initiated the use of a risk interaction matrix to identify potential interactions that compound risk. Identifying risk interactions supports flight and test motor decisions. Uncovering hidden risks of a full-scale static test motor gives a broader perspective of the changes being tested. This broader perspective compels the program to focus on solutions for implementing RSRM changes with minimal/mitigated risk. This paper discusses use of a change risk interaction matrix to identify test challenges and uncover hidden risks to the RSRM program.

Greenhalgh, Phillip O.↗

Torsional vestibulo-ocular reflex measurements for identifying otolith asymmetries possibly related to space motion sickness susceptibility

Recent studies by Diamond and Markham have identified significant correlations between space motion sickness susceptibility and measures of disconjugate torsional eye movements recorded during parabolic flights. These results support an earlier proposal by von Baumgarten and Thumler which hypothesized that an asymmetry of otolith function between the two ears is the cause of space motion sickness. It may be possible to devise experiments that can be performed in the 1 g environment on earth that could identify and quantify the presence of asymmetric otolith function. This paper summarizes the known physiological and anatomical properties of the otolith organs and the properties of the torsional vestibulo-ocular reflex which are relevant to the design of a stimulus to identify otolith asymmetries. A specific stimulus which takes advantage of these properties is proposed.

Non-NASA Center↗

Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis

A family of G-protein-coupled receptors is believed to mediate the recognition of odor molecules. In order to identify potential ligand-binding residues, we have applied correlated mutation analysis to receptor sequences from the rat. This method identifies pairs of sequence positions where residues remain conserved or mutate in tandem, thereby suggesting structural or functional importance. The analysis supported molecular modeling studies in suggesting several residues in positions that were consistent with ligand-binding function. Two of these positions, dominated by histidine residues, may play important roles in ligand binding and could confer broad specificity to mammalian odor receptors. The presence of positive (overdominant) selection at some of the identified positions provides additional evidence for roles in ligand binding. Higher-order groups of correlated residues were also observed. Each group may interact with an individual ligand determinant, and combinations of these groups may provide a multi-dimensional mechanism for receptor diversity.

NASA Discipline Neuroscience↗

Hematite at Meridiani Planum and Gusev Crater as identified by the Moessbauer Spectrometer MIMOS II

The Moessbauer (MB) spectrometers on the MER rovers Opportunity and Spirit, which landed on Mars in January 2004, have identified the iron-containing mineral hematite (a-Fe2O3) at both landing sites. On Earth, hematite can occur either by itself or with other iron oxides as massive deposits, in veins , and as particles dispersed through a silicate or other matrix material. Hematite particle size can range from nanophase (superparamagnetic) to multidomain and particle shape ranges from equant to acicular to platy. Fine-grained hematite is red in color and is a pigmenting agent. Coarse-grained hematite can be spectrally neutral (gray) at visible wavelengths. Substitutional impurities, particularly Al, are common in hematite. Chemically pure, coarse-grained, and well-crystalline hematite has a magnetic transition (the Morin transition) at ~260 K. Moessbauer spectra, recorded as a function of temperature, provide a way to characterize Martian hematite with respect to some of the physical and chemical characteristics. At Meridiani Planum besides the iron-sulfate mineral jarosite also the Fe-oxide hematite has been identified by the Moessbauer spectrometer, mainly in three distinct types of reservoir: - outcrop matrix material dominated by the mineral jarosite in the MB spectrum, certain basaltic soils, and mm-sized spherules dubbed blueberries. Moessbauer spectra of each reservoir yield a distinct set of hyperfine parameters for hematite, suggesting different degrees of crystallinity and particle size. The hematite found by MB instrument MIMOS II in the outcrop material shows the Morin transition at relatively high temperatures (ca. 250 K) which is an indication of pure and well-crystallized hematite. The source of the hematite in the Blueberries as identified by Moessbauer spectroscopy, and also by MiniTES, is not known. These spherules, covering nearly the whole landing site area (Eagle crater, plains, Endurance crater), may be concretions formed in the outcrop involving aqueous processes. They are dispersed throughout the hematite containing jarositic outcrop material. According to Moessbauer analysis the dominating iron-bearing mineral in the spherules is hematite, and jarosite not been detected so far in significant amounts. But there are some places with hematite showing characteristics different from the hematite described above: (1) the soil at B023_HematiteSlope_Hema2 has some blueberries, but the MB did not seem to intercept any. The temperature dependence of its MB parameters are different from those of blueberries. (2) B049_RasberryNewton_Filling shows a unique Hm MB signature, as well as (3) B051_RealSharksTooth_Enamel1.

Klingelhoefer, G.↗