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At least 1,135 records · Page 63

Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

ABSTRACT Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing‐ like lipid biosynthesis, flavinogenesis, and halotolerance – yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica , Debaryomyces hansenii , and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a “network‐first” approach where a generalized metabolic network serves as a scaffold for mapping genes and a “cluster‐first” approach where unsupervised machine learning co‐expression analysis clusters genes. Both approaches provide insight into strain behavior. The network‐first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster‐first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions.

Weintraub, Sarah J. [Department of Bioinformatics ↗

Fuzzy Logic Controller Stability Analysis Using a Satisfiability Modulo Theories Approach

While many widely accepted methods and techniques exist for validation and verification of traditional controllers, at this time no solutions have been accepted for Fuzzy Logic Controllers (FLCs). Due to the highly nonlinear nature of such systems, and the fact that developing a valid FLC does not require a mathematical model of the system, it is quite difficult to use conventional techniques to prove controller stability. Since safety-critical systems must be tested and verified to work as expected for all possible circumstances, the fact that FLC controllers cannot be tested to achieve such requirements poses limitations on the applications for such technology. Therefore, alternative methods for verification and validation of FLCs needs to be explored. In this study, a novel approach using formal verification methods to ensure the stability of a FLC is proposed. Main research challenges include specification of requirements for a complex system, conversion of a traditional FLC to a piecewise polynomial representation, and using a formal verification tool in a nonlinear solution space. Using the proposed architecture, the Fuzzy Logic Controller was found to always generate negative feedback, but inconclusive for Lyapunov stability.

Fuzzy Logic Controller↗

Fuzzy Logic Controller Stability Analysis Using a Satisfiability Modulo Theories Approach

While many widely accepted methods and techniques exist for validation and verification of traditional controllers, at this time no solutions have been accepted for Fuzzy Logic Controllers (FLCs). Due to the highly nonlinear nature of such systems, and the fact that developing a valid FLC does not require a mathematical model of the system, it is quite difficult to use conventional techniques to prove controller stability. Since safety-critical systems must be tested and verified to work as expected for all possible circumstances, the fact that FLC controllers cannot be tested to achieve such requirements poses limitations on the applications for such technology. Therefore, alternative methods for verification and validation of FLCs needs to be explored. In this study, a novel approach using formal verification methods to ensure the stability of a FLC is proposed. Main research challenges include specification of requirements for a complex system, conversion of a traditional FLC to a piecewise polynomial representation, and using a formal verification tool in a nonlinear solution space. Using the proposed architecture, the Fuzzy Logic Controller was found to always generate negative feedback, but inconclusive for Lyapunov stability.

Fuzzy Logic Controller↗

Detecting differential protein abundance by combining peptide level P -values

The majority of methods for detecting differentially abundant proteins between samples in label-free LC-MS bottom-up proteomics experiments rely on statistically testing inferred protein abundances derived from peptide ionization intensities or averaging peptide level statistics. Here in this paper, we statistically test peptide ionization intensities directly and combine the resulting dependent P-values using the Empirical Brown's Method (EBM), avoiding error introduced through the estimation of protein abundances or summarizing test statistics. We show that on a spike-in proteomics dataset, a peptide level approach using EBM outperforms differential abundance detection using a protein level approach and several analysis workflows, including MSstats. Additionally, we demonstrate the effectiveness of this approach by detecting enriched proteins from an activity-based protein profiling dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Variability of particulate organic carbon concentration in the north polar Atlantic based on ocean color observations with Sea-viewing Wide Field-of-view Sensor (SeaWiFS)

We use satellite data from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to investigate distributions of particulate organic carbon (POC) concentration in surface waters of the north polar Atlantic Ocean during the spring summer season (April through August) over a 6-year period from 1998 through 2003. By use of field data collected at sea, we developed regional relationships for the purpose of estimating POC from remote-sensing observations of ocean color. Analysis of several approaches used in the POC algorithm development and match-up analysis of coincident in situ derived and satellite-derived estimates of POC resulted in selection of an algorithm that is based on the blue-to-green ratio of remote-sensing reflectance R(sub rs) (or normalized water-leaving radiance L(sub wn)). The application of the selected algorithm to a 6-year record of SeaWiFS monthly composite data of L(sub wn) revealed patterns of seasonal and interannual variability of POC in the study region. For example, the results show a clear increase of POC throughout the season. The lowest values, generally less than 200 mg per cubic meters, and at some locations often less than 50 mg per cubic meters, were observed in April. In May and June, POC can exceed 300 or even 400 mg per cubic meters in some parts of the study region. Patterns of interannual variability are intricate, as they depend on the geographic location within the study region and particular time of year (month) considered. By comparing the results averaged over the entire study region and the entire season (April through August) for each year separately, we found that the lowest POC occurred in 2001 and the highest POC occurred in 2002 and 1999.

Stramska, Malgorzata↗

An interleave retrieval method for oversampled limb scans

Rodgers presents a general approach for error analysis of retrievals based on a linearization of the retrieval problem. This approach allows calculation of retrieval error from uncertainties in the input radiances and in each of the forward radiance model parameters. These terms are weighted according to the sensitivity of the retrieval to each of them. We use this framework to describe the results of an error analysis performed on HALOE data. This paper will show the effect of using over sampled profile data and an interleave retrieval technique by application of formal error analysis.

Gordley, Larry L.↗

Analysis of the turbostratic structures in PAN-based carbon fibers with wide-angle x-ray diffraction

Carbon fiber (CF) is a versatile material renowned for its excellent mechanical, thermal, and electrical properties. Polyacrylonitrile (PAN)-based CFs dominate the market due to their high tensile strength, rendering them suitable for structural applications in a wide variety of applications ranging from sporting goods to aerospace. Over five decades of commercial development of PAN-based CF has resulted in a range of varieties with different tensile moduli and tensile strengths. The microstructures, nanostructures, and crystal structures of PAN-based CF play pivotal roles in the macroscale properties of this material. In particular, the crystal structure and crystallite orientation in CF is closely related to the mechanical properties. The crystal structure of PAN-based CF generally consists of turbostratic carbon, which is a disordered form of graphite, the characteristics of which can be effectively characterized in a bulk format through wide-angle x-ray diffraction (WAXD). In this work, we employed a three-part approach to the analysis of WAXD patterns collected from four intermediate modulus PAN-based CFs. The approach incorporates a Scherrer analysis, a Debye analysis, and an orientational analysis to provide precise estimates of crystallite sizes, crystallite distributions, and crystallite orientations with the fiber axis. Furthermore, the results presented here suggest that intermediate modulus PAN-based CF mostly consists of small turbostratic crystallites (<4 nm), with larger crystallites having increased orientation with the fiber axis. The results here imply the presence of curvature and/or wrinkling of the turbostratic layers within the CF structure.

36 MATERIALS SCIENCE↗

The Aeronautical Data Link: Decision Framework for Architecture Analysis

A decision analytic approach that develops optimal data link architecture configuration and behavior to meet multiple conflicting objectives of concurrent and different airspace operations functions has previously been developed. The approach, premised on a formal taxonomic classification that correlates data link performance with operations requirements, information requirements, and implementing technologies, provides a coherent methodology for data link architectural analysis from top-down and bottom-up perspectives. This paper follows the previous research by providing more specific approaches for mapping and transitioning between the lower levels of the decision framework. The goal of the architectural analysis methodology is to assess the impact of specific architecture configurations and behaviors on the efficiency, capacity, and safety of operations. This necessarily involves understanding the various capabilities, system level performance issues and performance and interface concepts related to the conceptual purpose of the architecture and to the underlying data link technologies. Efficient and goal-directed data link architectural network configuration is conditioned on quantifying the risks and uncertainties associated with complex structural interface decisions. Deterministic and stochastic optimal design approaches will be discussed that maximize the effectiveness of architectural designs.

Morris, A. Terry↗

Analysis of Logistics in Support of a Human Lunar Outpost

Strategic level analysis of the integrated behavior of lunar transportation system and lunar surface system architecture options is performed to inform NASA Constellation Program senior management on the benefit, viability, affordability, and robustness of system design choices. This paper presents an overview of the approach used to perform the campaign (strategic) analysis, with an emphasis on the logistics modeling and the impacts of logistics resupply on campaign behavior. An overview of deterministic and probabilistic analysis approaches is provided, with a discussion of the importance of each approach to understanding the integrated system behavior. The logistics required to support lunar surface habitation are analyzed from both 'macro-logistics' and 'micro-logistics' perspectives, where macro-logistics focuses on the delivery of goods to a destination and micro-logistics focuses on local handling of re-supply goods at a destination. An example campaign is provided to tie the theories of campaign analysis to results generation capabilities.

Cirillo, William↗

Environmental Control and Life Support Systems technology options for Space Station application

Continuous assessments regarding the suitability of candidate technologies for manned Space Stations will be needed over the next several years to obtain a basis for recommending the optimum system for an Initial Operating Capability (IOC) Space Station which is to be launched in the early 1990's. This paper has the objective to present analysis programs, the candidate recommendations, and the recommended approach for integration these candidates into the NASA Space Station reference configuration. Attention is given to ECLSS (Environmental Control and Life Support System) technology assessment program, an analysis approach for candidate technology recommendations, mission model variables, a candidate integration program, metabolic oxygen recovery, urine/flush water and all waste water recovery, wash water and condensate water recovery, and an integration analysis.

Hall, J. B., Jr.↗

Optimal design and evaluation criteria for acoustic emission pulse signature analysis

Successful pulse recording and evaluation is strongly dependent on the instrumentation system selected and the method of analyzing the pulse signature. The paper studies system design, signal analysis techniques, and interdependences with a view toward defining optimal approaches to pulse signal analysis. For this purpose, the instrumentation system is modeled, and analytical pulses, representative of the types of acoustic emissions to be distinguished are passed through the system. Particular attention is given to comparing frequency spectrum analysis and deconvolution referred to as time domain reconstruction of the pulse or pulse train. The possibility of optimal transducer-filter system parameters is investigated. Deconvolution of a pulse is shown to be a superior approach for transient pulse analysis. Reshaping of a transducer output back to the original input pulse is possible and gives an accurate representation of the generating pulse in the time domain. Any definable transducer and filter system can be used for measurement of pulses by means of the deconvolution method. Selection of design variables for general usage is discussed.

Houghton, J. R.↗

Alternating conduction and convection drying of paper – an experimental analysis with a continuous data acquisition approach

In conventional multi-cylinder drying of paper and board, both conductive drying from steam-heated dryer cylinders and convective drying by flowing air over the paper surface in the pockets are used. Conductive drying from steam-heated drying cylinders is a critical component in providing the necessary thermal energy to paper and board as they dry. Steam temperature and internal and external resistances at the contacting surface are critical process parameters influencing the conductive drying process. An experimental setup was developed to study the alternating conductive and convective drying of paper and board. Paper sheet moisture, temperature, and temperature distribution within the heated platen and the instantaneous heat flux as the sheet was being dried were measured. The instantaneous heat flux, contact heat transfer coefficient, and drying rates were determined as drying proceeds. Experimental results, as well as comparisons to literature and commercial data, are presented. The conductive heat transfer coefficients determined were compared to traditional correlations normally used in the modeling of paper drying. Similarly, the convective heat and mass transfer coefficients are also determined and compared to literature data. In addition to the evaluation of alternating conductive and convective drying characteristics of paper and board, the potential inclusion of auxiliary energy components will also be included. Experimental results from the conduction and convection drying system are presented. Furthermore, this data will be useful in process development, intensification of manufacturing processes, and modeling and simulation of paper drying processes.

42 ENGINEERING↗

What more can be done with XPS? Highly informative but underused approaches to XPS data collection and analysis

Because of the importance of surfaces and interfaces in many scientific and technological areas, the use of x-ray photoelectron spectroscopy (XPS) has been growing exponentially. Although XPS is being used to obtain useful information about the surface composition of samples, much more information about materials and their properties can be extracted from XPS data than commonly obtained. This paper describes some of the areas where alternative analysis methods or experimental design can obtain information about the near-surface region of a sample, often information not available in other ways. Experienced XPS analysts are familiar with many of these methods, but they may not be known to new or casual XPS users, and sometimes, they have not been used because of an inappropriately assumed complexity. The information available includes optical, electronic, and electrical properties; nanostructure; expanded chemical information; and enhanced analysis of biological materials and solid/liquid interfaces. Many of these analyses can be conducted on standard laboratory XPS systems, with either no or relatively minor system alterations. Topics discussed include (1) considerations beyond the “traditional” uniform surface layer composition calculation, (2) using the Auger parameter to determine a sample property, (3) use of the D parameter to identify sp 2 and sp 3 carbon information, (4) information from the XPS valence band, (5) using cryocooling to expand range of samples that can be analyzed and minimize damage, and (6) using electrical potential effects on XPS signals to extract chemically resolved electrical measurements including band alignment and electrical property information.

Baer, Donald R. [Pacific Northwest National Labora↗

Machine learning approaches to streamline and enhance the analysis of multiscale imaging data for bioaerosol and soil particles

Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.

54 ENVIRONMENTAL SCIENCES↗

Enhancing CO 2 Storage Complex Characterization in the Williston Basin: An Integrated Approach of Petrophysical Evaluation and Core Analysis

Conference presentation at Carbon Capture, Utilization, and Storage (CCUS) Conference 2024, Houston, Texas, March 11–13, 2024. Petrophysics and core analysis are pivotal in carbon capture and storage (CCS). An integrated workflow including conventional and advanced well logs and core analysis (CCAL and SCAL) was developed to characterize the Broom Creek Formation as the target reservoir to store CO 2 in a CCS project in North Dakota.

02 PETROLEUM↗

A topological approach to computer-aided sensitivity analysis

Sensitivities of any arbitrary system are calculated using general purpose digital computer with available software packages for transfer function analysis. Sensitivity shows how element variation within system affects system performance. Signal flow graph illustrates topological system behavior and relationship among parameters in system.

Chan, S. P.↗

A comparison of two approaches for category identification and classification analysis from an agricultural scene

Supervised and unsupervised classification modes are discussed in light of the multidisciplinary, high data rate requirements of the ERTS satellites soon to be launched. Inadequacies of each system in light of these requirements are noted and a compromise solution to the data classification system is proposed. An example of results obtained with an implementation of this system are shown and compared with results from a supervised classification scheme.

Schell, J. A.↗