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Data-Driven Identification of Nonlinear Power System Dynamics Using Output-Only Measurements
Not provided.
Systems Level Analysis and Identification of Pathways and Networks Associated with Liver Fibrosis
Toxic liver injury causes necrosis and fibrosis, which may lead to cirrhosis and liver failure. Despite recent progress in understanding the mechanism of liver fibrosis, our knowledge of the molecular-level details of this disease is still incomplete. The elucidation of networks and pathways associated with liver fibrosis can provide insight into the underlying molecular mechanisms of the disease, as well as identify potential diagnostic or prognostic biomarkers. Towards this end, we analyzed rat gene expression data from a range of chemical exposures that produced observable periportal liver fibrosis as documented in DrugMatrix, a publicly available toxicogenomics database. We identified genes relevant to liver fibrosis using standard differential expression and co-expression analyses, and then used these genes in pathway enrichment and protein-protein interaction (PPI) network analyses. We identified a PPI network module associated with liver fibrosis that includes known liver fibrosis-relevant genes, such as tissue inhibitor of metalloproteinase-1, galectin-3, connective tissue growth factor, and lipocalin-2. We also identified several new genes, such as perilipin-3, legumain, and myocilin, which were associated with liver fibrosis. We further analyzed the expression pattern of the genes in the PPI network module across a wide range of 640 chemical exposure conditions in DrugMatrix and identified early indications of liver fibrosis for carbon tetrachloride and lipopolysaccharide exposures. Although it is well known that carbon tetrachloride and lipopolysaccharide can cause liver fibrosis, our network analysis was able to link these compounds to potential fibrotic damage before histopathological changes associated with liver fibrosis appeared. These results demonstrated that our approach is capable of identifying early-stage indicators of liver fibrosis and underscore its potential to aid in predictive toxicity, biomarker identification, and to generally identify disease-relevant pathways.
Parameter Tuning Analysis for Phase Identification Algorithms in Distribution System Model Calibration.
Abstract not provided.
Identification of Metabolic Pathway Systems
The estimation of parameters in even moderately large biological systems is a significant challenge. This challenge is greatly exacerbated if the mathematical formats of appropriate process descriptions are unknown. To address this challenge, the method of dynamic flux estimation (DFE) was proposed for the analysis of metabolic time series data. Under ideal conditions, the first phase of DFE yields numerical representations of all fluxes within a metabolic pathway system, either as values at each time point or as plots against their substrates and modulators. However, this numerical result does not reveal the mathematical format of each flux. Thus, the second phase of DFE selects functional formats that are consistent with the numerical trends obtained from the first phase. While greatly facilitating metabolic data analysis, DFE is only directly applicable if the pathway system contains as many dependent variables as fluxes. Because most actual systems contain more fluxes than metabolite pools, this requirement is seldom satisfied. Auxiliary methods have been proposed to alleviate this issue, but they are not general. Here we propose strategies that extend DFE toward general, slightly underdetermined pathway systems.
Identification of a linear system from sampled noisy data, part C Final project report
Step input linear system modeling from nonlinear system sampled noisy data based on method of perturbation or quasilinearization of automatic control system data
The effect of system nonlinearities on system noise statistics
The effects are studied of nonlinearities in a baseline communications system on the system noise amplitude statistics. So that a meaningful identification of system nonlinearities can be made, the baseline system is assumed to transmit a single biphase-modulated signal through a relay satellite to the receiving equipment. The significant nonlinearities thus identified include square-law or product devices (e.g., in the carrier reference recovery loops in the receivers), bandpass limiters, and traveling wave tube amplifiers.
Identification of structural dynamics systems using least-square lattice filters
Previously cited in issue 19, no. 2987, Accession no. A82-38965
Gradient methods for identification of distributed parameter systems
Parameter-dependence properties are developed in the context of a linear abstract Cauchy problem governed by a parameter-dependent operator. Of particular interest are problems in which the parameter induces an unbounded perturbation of the evolution operator. Conditions are stated under which the derivative of the state with respect to the parameter possesses certain smoothness properties. These properties lead to local convergence results for a gradient-based estimation algorithm based on quasi-linearization. Numerical results concerning a delay-differential equation indicate the effect of a forcing function on parameter sensitivity.
Parametric Identification of Nonlinear Dynamical Systems
In this project, we looked at the application of harmonic balancing as a tool for identifying parameters (HBID) in a nonlinear dynamical systems with chaotic responses. The main idea is to balance the harmonics of periodic orbits extracted from measurements of each coordinate during a chaotic response. The periodic orbits are taken to be approximate solutions to the differential equations that model the system, the form of the differential equations being known, but with unknown parameters to be identified. Below we summarize the main points addressed in this work. The details of the work are attached as drafts of papers, and a thesis, in the appendix. Our study involved the following three parts: (1) Application of the harmonic balance to a simulation case in which the differential equation model has known form for its nonlinear terms, in contrast to a differential equation model which has either power series or interpolating functions to represent the nonlinear terms. We chose a pendulum, which has sinusoidal nonlinearities; (2) Application of the harmonic balance to an experimental system with known nonlinear forms. We chose a double pendulum, for which chaotic response were easily generated. Thus we confronted a two-degree-of-freedom system, which brought forth challenging issues; (3) A study of alternative reconstruction methods. The reconstruction of the phase space is necessary for the extraction of periodic orbits from the chaotic responses, which is needed in this work. Also, characterization of a nonlinear system is done in the reconstructed phase space. Such characterizations are needed to compare models with experiments. Finally, some nonlinear prediction methods can be applied in the reconstructed phase space. We developed two reconstruction methods that may be considered if the common method (method of delays) is not applicable.
Material Outgassing, Identification and Deposition, MOLIDEP System
The outgassing tests are performed employing a modified vacuum operated Cahn analytical microbalance, identified as the MOLIDEP system. The test measures under high vacuum, the time varying Molecular mass loss of a material sample held at a chosen temperature; it Identifies the outgassing molecular components using an inline SRS 300 amu Residual Gas Analyzer (RGA) and employs a temperature controlled 10 MHz Quartz Crystal Microbalance (QCM) to measure the condensable DEPosits. Both the QCM and the RGA intercept within the conductive passage the outgassing products being evacuated by a turbomolecular pump. The continuous measurements of the mass loss, the rate of loss, the sample temperature, the rate of temperature change, the QCM temperature and the QCM recorded condensable deposits or rate of deposits are saved to an Excel spreadsheet. A separate computer controls the RGA.
Identification of an NADP/thioredoxin system in Chlamydomonas reinhardtii
The protein components of the NADP/thioredoxin system, NADP-thioredoxin reductase (NTR) and thioredoxin h, have been purified and characterized from the green alga, Chlamydomonas reinhardtii. The analysis of this system confirms that photoautotrophic Chlamydomonas cells resemble leaves in having both an NADP- and ferrodoxin-linked thioredoxin redox system. Chlamydomonas thioredoxin h, which is smaller on sodium dodecyl sulfate-polyacrylamide gel electrophoresis than thioredoxin m from the same source, cross-reacted with antisera to thioredoxin h from spinach (Spinacia oleracea L.) and wheat germ (Triticum vulgaris L.) but not with antisera to m or f thioredoxins. In these properties, the thioredoxin h resembled a thioredoxin from Chlamydomonas, designated Ch1, whose sequence was reported recently (P. Decottignies et al., 1991, Eur. J. Biochem. 198, 505-512). The differential reactivity of thioredoxin h with antisera was used to demonstrate that thioredoxin h is enriched outside the chloroplast. The NTR was purified from Chlamydomonas using thioredoxin h from the same source. Similar to its counterpart from other organisms, Chlamydomonas NTR had a subunit size of approx. 36 kDa and was specific for NADPH. Chlamydomonas NTR effectively reduced thioredoxin h from the same source but showed little activity with the other thioredoxins tested, including spinach thioredoxin h and Escherichia coli thioredoxin. Comparison of the reduction of Chlamydomonas thioredoxins m and h by each of the endogenous thioredoxin reductases, NTR and ferredoxin-thioredoxin reductase, revealed a differential specificity of each enzyme for thioredoxin. Thus, NTR showed increased activity with thioredoxin h and ferredoxin-thioredoxin reductase with thioredoxins m and f.
Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)
This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search
Identification of Crew-Systems Interactions and Decision Related Trends
NASA Vehicle System Safety Technology (VSST) project management uses systems analysis to identify key issues and maintain a portfolio of research leading to potential solutions to its three identified technical challenges. Statistical data and published safety priority lists from academic, industry and other government agencies were reviewed and analyzed by NASA Aviation Safety Program (AvSP) systems analysis personnel to identify issues and future research needs related to one of VSST's technical challenges, Crew Decision Making (CDM). The data examined in the study were obtained from the National Transportation Safety Board (NTSB) Aviation Accident and Incident Data System, Federal Aviation Administration (FAA) Accident/Incident Data System and the NASA Aviation Safety Reporting System (ASRS). In addition, this report contains the results of a review of safety priority lists, information databases and other documented references pertaining to aviation crew systems issues and future research needs. The specific sources examined were: Commercial Aviation Safety Team (CAST) Safety Enhancements Reserved for Future Implementation (SERFIs), Flight Deck Automation Issues (FDAI) and NTSB Most Wanted List and Open Recommendations. Various automation issues taxonomies and priority lists pertaining to human factors, automation and flight design were combined to create a list of automation issues related to CDM.
Identification of Scenarios for System Interface Design Evaluation: CAST SE-210 Output 2 Report 5 of 6
This report is one in a series of reports describing research to develop enhanced approaches to design and evaluation of flight deck interaction. The research was conducted to support the Commercial Aviation Safety Team (CAST) response to incidents and accidents caused by failure of the flight crew to maintain aircraft attitude or energy state awareness. This report partially responds to Safety Enhancement (SE) 210.2 (CAST, 2014) by describing development of operational scenarios for evaluation of flight crew interaction. Evaluations of human performance with an interface rely on asking humans to perform operational tasks in an appropriate operational context. The report includes the major sources of material for developing operational scenarios—which include system state, operational tasks, operational context, and safety events—and a method for developing an appropriate set of operational scenarios for interface evaluation.
Pipeline Radionuclide Identification And Mapping (PRIAM) System
Explore the source record for details and available documents.
Identification of Linear Power System Models Using Probing Signals.
Abstract not provided.
Parameter Tuning Analysis for Phase Identification Algorithms in Distribution System Model Calibration.
Abstract not provided.