SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The paper presents the CARDIAD (complex acceptability region for diagonal dominance) method for achieving the diagonal dominance condition in the inverse Nyquist array approach to the analysis and design of multivariable systems in the frequency domain. A design example is given for a sixth order, 4-input, 4-output model of a turbofan engine.
The multivariable instrumental variable/approximate maximum likelihood (IV/AML) method or recursive time-series analysis is used to identify the multivariable (four inputs-three outputs) dynamics of the Pratt and Whitney F100 engine. A detailed nonlinear engine simulation is used to determine linear engine model structures and parameters at an operating point using open loop data. Also, the IV/AML method is used in a direct identification mode to identify models from actual closed loop engine test data. Models identified from simulated and test data are compared to determine a final model structure and parameterization that can predict engine response for a wide class of inputs. The ability of the IV/AML algorithm to identify useful dynamic models from engine test data is assessed.
The multivariable instrumental variable/approximate maximum likelihood (IV/AML) method of recursive time-series analysis is used to identify the multivariable (four inputs-three outputs) dynamics of the Pratt and Whitney F100 engine. A detailed nonlinear engine simulation is used to determine linear engine model structures and parameters at an operating point using open loop data. Also, the IV/AML method is used in a direct identification made to identify models from actual closed loop engine test data. Models identified from simulated and test data are compared to determine a final model structure and parameterization that can predict engine response for a wide class of inputs. The ability of the IV/AML algorithm to identify useful dynamic models from engine test data is assessed. Previously announced in STAR as N82-20339
The multivariate method for statistical analysis of crater-filling classes, as presently applied to craters of more than 10-km diameter on Mercury, is noted to be superior to current techniques due to the obviation of any amalgamation of data from regions with different histories in order to arrive at the pertinent counting statistics. In this application to the Mercury intercrater plains, the process responsible for emplacement is constrained to be one that leaves the crater class distribution unaltered from that observed on the densely cratered terrain. The analysis explicitly eliminates the viability of the pulse emplacement of volcanics or basin ejecta.
Robustness margin (measure of degree of passivity) defined. Paper presents new approach to analysis of stability of multivariable feedforward-and-feedback control system consisting of exponentially stable linear time-invariant (LTI) feedforward subsystem and nonlinear time-varying (NTV) or dynamic feedback subsystem. New method based on notion of passivity, quantified by robustness margin. Margin provides bound on magnitudes of perturbations, below which perturbations will not make system unstable.
A simple and fundamental problem in cloud electrification is whether or not a cloud can be determined to be producing lightning or not producing lightning, based solely on knowledge of its microphysical (and perhaps environmental) state. A merged database of TRMM radar, microwave and lightning observations and NCEP reanalysis environmental parameters is used to answer this question, for the tropics. The formal skill of traditional, univariate rule-based approaches (e.g., 35 dBZ occurrence at 6 km altitude) is quantified (via the probability of detection (POD), false alarm rate (FAR) and critical skill index (CSI)). Under indiscriminate application to the tropics, peak rule-based CSI for categorization of flashing storms is approximately 50%, with peak POD approximately 67% and minimum FAR approximately 33%, with peak CSI found for radar reflectivity-based parameters at 7-7.5 km altitude (near -15C). Separation of land and ocean domains yields approximately 5-10% gains in CSI over land. Conventional multivariate categorization techniques (discriminant analysis) are then applied, and less conventional (neural network) categorization techniques are also discussed.
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system that has been designed to monitor the Earth's climate with unprecedented absolute radiometric accuracy and SI traceability. Climate Observation System Simulation Experiments (OSSEs) have been generated to simulate CLARREO hyperspectral shortwave imager measurements to help define the measurement characteristics needed for CLARREO to achieve its objectives. To evaluate how well the OSSE-simulated reflectance spectra reproduce the Earth s climate variability at the beginning of the 21st century, we compared the variability of the OSSE reflectance spectra to that of the reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA) is a multivariate decomposition technique used to represent and study the variability of hyperspectral radiation measurements. Using PCA, between 99.7%and 99.9%of the total variance the OSSE and SCIAMACHY data sets can be explained by subspaces defined by six principal components (PCs). To quantify how much information is shared between the simulated and observed data sets, we spectrally decomposed the intersection of the two data set subspaces. The results from four cases in 2004 showed that the two data sets share eight (January and October) and seven (April and July) dimensions, which correspond to about 99.9% of the total SCIAMACHY variance for each month. The spectral nature of these shared spaces, understood by examining the transformed eigenvectors calculated from the subspace intersections, exhibit similar physical characteristics to the original PCs calculated from each data set, such as water vapor absorption, vegetation reflectance, and cloud reflectance.
Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein are CMIP5 (Coupled Model Intercomparison Project - Phase 5) model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP (International Satellite Cloud Climatology Project) and PATMOS-x (Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres - Extended). The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forced CMIP5 models. Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions.
Primary Goal: Assist with the evaluation and measuring of wetlands hydroperiod at the PlumBrook Station using multi-source remote sensing data as part of a larger effort on projecting climate change-related impacts on the station's wetland ecosystems. MTRI expanded on the multi-source remote sensing capabilities to help estimate and measure hydroperiod and the relative soil moisture of wetlands at NASA's Plum Brook Station. Multi-source remote sensing capabilities are useful in estimating and measuring hydroperiod and relative soil moisture of wetlands. This is important as a changing regional climate has several potential risks for wetland ecosystem function. The year two analysis built on the first year of the project by acquiring and analyzing remote sensing data for additional dates and types of imagery, combined with focused field work. Five deliverables were planned and completed: 1) Show the relative length of hydroperiod using available remote sensing datasets 2) Date linked table of wetlands extent over time for all feasible non-forested wetlands 3) Utilize LIDAR data to measure topographic height above sea level of all wetlands, wetland to catchment area radio, slope of wetlands, and other useful variables 4) A demonstration of how analyzed results from multiple remote sensing data sources can help with wetlands vulnerability assessment 5) A MTRI style report summarizing year 2 results. This report serves as a descriptive summary of our completion of these our deliverables. Additionally, two formal meetings were held with Larry Liou and Amanda Sprinzl to provide project updates and receive direction on outputs. These were held on 2/26/15 and 9/17/15 at the Plum Brook Station. Principal Component Analysis (PCA) is a multivariate statistical technique used to identify dominant spatial and temporal backscatter signatures. PCA reduces the information contained in the temporal dataset to the first few new Principal Component (PC) images. Some advantages of PCA include the ability to filter out temporal autocorrelation and reduce speckle to the higher order PC images. A PCA was performed using ERDAS Imagine on a time series of PALSAR dates. Hydroperiod maps were created by separating the PALSAR dates into two date ranges, 2006-2008 and 2010, and performing an unsupervised classification on the PCAs.
We have constructed a captive sample reactor (CSR) to study fast pyrolysis of biomass. The reactor uses a stainless steel wire mesh to surround biomass materials with an isothermal environment by independent controlling of heating rates and pyrolysis temperatures. The vapors produced during pyrolysis are immediately entrained and transported in He carrier gas to a molecular beam mass spectrometer (MBMS). Formation of secondary products is minimized by rapidly quenching the sample support with liquid nitrogen. A range of alkali and alkaline earth metal (AAEM) and transition metal salts were tested to study their effect on composition of primary pyrolysis products. Multivariate curve resolution (MCR) analysis of the MBMS data shows that transition metal salts enhance pyrolysis of carbohydrates and AAEM salts enhances pyrolysis of lignin. This was supported by performing similar separate studies on cellulose, hemicellulose and extracted lignin. The effect of salts on char formation is also discussed.
Purpose: The Head and Neck Intergroup conducted a Phase III randomized trial to determine whether the addition weekly cisplatin to daily radiation therapy (RT) would improve survival in patients with unresectable squamous cell head-and-neck carcinoma. Methods and Materials: Eligible patients were randomized to RT (70 Gy at 1.8-2 Gy/day) or to the identical RT with weekly cisplatin dosed at 20 mg/m{sup 2}. Failure-free survival (FFS) and overall survival (OS) curves were estimated with the Kaplan-Meier method and compared with the log rank test. Results: Between 1982 and 1987, 371 patients were accrued, and 308 patients were found eligible for analysis. Median follow-up was 62 months. The median FFS was 6.5 and 7.2 months for the RT and RT + cisplatin groups, respectively (p = 0.30). The p value for the treatment difference was p = 0.096 in multivariate modeling of FFS (compared to a p = 0.30 in univariate analysis). Expected acute toxicities were significantly increased with the addition of cisplatin except for in-field RT toxicities. Late toxicities were not significantly different except for significantly more esophageal (9% vs. 3%, p = 0.03) and laryngeal (11% vs. 4%, p = 0.05) late toxicities in the RT + cisplatin group. Conclusion: The addition of concurrent weekly cisplatin at 20 mg/m{sup 2} to daily radiation did not improve survival, although there was evidence of activity. Low-dose weekly cisplatin seems to have modest tumor radiosensitization but can increase the risk of late swallowing complications.
Management of soil biological resources to optimise plant production, efficiency of nutrient inputs, and system sustainability is an emerging opportunity for pastoral agriculture. To attain these goals, suitable tools that can assess the functional state of the soil ecosystem must be developed and standardised approaches to their application adopted. Towards this end, we have undertaken comprehensive, high-density functional-gene microarray analysis (GeoChip5) of environmental DNA (eDNA) extracted from 50 pastoral soils. When combined with soil, environmental and management metadata, the information can be used to provide insights into soil biological processes spanning greenhouse gas emissions, through to natural suppression of plant root diseases. To give an example of a structured workflow of analysis in a pastoral system context, we analysed the GeoChip data using a combination of approaches spanning routine univariate methods through to more complex multivariate and network-based analysis. Analyses were restricted to comparing effects of land-use (dairy or ‘other’ farming systems), and exploring relationships of the GeoChip data with the soil properties from each sample. These exemplar analyses introduce a pathway for the application of eDNA approaches (GeoChip or others) to deliver outcomes for pastoral agricultural in New Zealand.
Highlights: • All 14 lysoPCs were dramatically decreased in MD patients. • Acylcarnitines, TGs, PIs, PEs, unsaturated lysoPEs and PCs were significantly increased in MD patients. • PI 38:6, lysoPCs (20:0, 19:0, 18:0, 17:0) may be potentially sensitive and specific biomarkers for MD. Mitochondrial disease (MD) is a rare mitochondrial respiratory chain disorder with a high mortality and extremely challenging to treat. Although genomic, transcriptomic, and proteomic analyses have been performed to investigate the pathogenesis of MD, the role of metabolomics in MD, particularly of lipidomics remains unclear. This study was undertaken to identify potential lipid biomarkers of MD. An untargeted lipidomic approach was used to compare the plasma lipid metabolites in 20 MD patients and 20 controls through Liquid Chromatography coupled to Mass Spectrometry. Volcano plot analysis was performed to identify the different metabolites. Receiver operating characteristic (ROC) curves were constructed and the area under the ROC curves (AUC) was calculated to determine the potentially sensitive and specific biomarkers. A total of 41 lipids were significantly different in MD patients and controls. ROC curve analysis showed the top 5 AUC values of lipids (phosphatidylinositols 38:6, lysoPC 20:0, 19:0, 18:0, 17:0) are more than 0.99. Multivariate ROC curve based exploratory analysis showed the AUC of combination of top 5 lipids is 1, indicating they may be potentially sensitive and specific biomarkers for MD. We propose combination of these lipid species may be more valuable in predicting the development and progression of MD, and this will have important implications for the diagnosis and treatment of MD.
Purpose: This study compared treatment outcomes of stereotactic body radiation therapy (SBRT) with those of surgery in stage I non-small cell lung cancer (NSCLC). Methods and Materials: Eligible studies of SBRT and surgery were retrieved through extensive searches of the PubMed, Medline, Embase, and Cochrane library databases from 2000 to 2012. Original English publications of stage I NSCLC with adequate sample sizes and adequate SBRT doses were included. A multivariate random effects model was used to perform a meta-analysis to compare survival between treatments while adjusting for differences in patient characteristics. Results: Forty SBRT studies (4850 patients) and 23 surgery studies (7071 patients) published in the same period were eligible. The median age and follow-up duration were 74 years and 28.0 months for SBRT patients and 66 years and 37 months for surgery patients, respectively. The mean unadjusted overall survival rates at 1, 3, and 5 years with SBRT were 83.4%, 56.6%, and 41.2% compared to 92.5%, 77.9%, and 66.1% with lobectomy and 93.2%, 80.7%, and 71.7% with limited lung resections. In SBRT studies, overall survival improved with increasing proportion of operable patients. After we adjusted for proportion of operable patients and age, SBRT and surgery had similar estimated overall and disease-free survival. Conclusions: Patients treated with SBRT differ substantially from patients treated with surgery in age and operability. After adjustment for these differences, OS and DFS do not differ significantly between SBRT and surgery in patients with operable stage I NSCLC. A randomized prospective trial is warranted to compare the efficacy of SBRT and surgery.
We present a new method to discriminate periodic from nonperiodic irregularly sampled light curves. We introduce a periodic kernel and maximize a similarity measure derived from information theory to estimate the periods and a discriminator factor. We tested the method on a data set containing 100,000 synthetic periodic and nonperiodic light curves with various periods, amplitudes, and shapes generated using a multivariate generative model. We correctly identified periodic and nonperiodic light curves with a completeness of ∼90% and a precision of ∼95%, for light curves with a signal-to-noise ratio (S/N) larger than 0.5. We characterize the efficiency and reliability of the model using these synthetic light curves and apply the method on the EROS-2 data set. A crucial consideration is the speed at which the method can be executed. Using a hierarchical search and some simplification on the parameter search, we were able to analyze 32.8 million light curves in ∼18 hr on a cluster of GPGPUs. Using the sensitivity analysis on the synthetic data set, we infer that 0.42% of the sources in the LMC and 0.61% of the sources in the SMC show periodic behavior. The training set, catalogs, and source code are all available at http://timemachine.iic.harvard.edu.
Purpose: We examined the impact of intensity modulated radiation therapy (IMRT) on hospitalization rates in the Surveillance, Epidemiology, and End Results (SEER)–Medicare population with anal squamous cell carcinoma (SCC). Methods and Materials: We performed a retrospective cohort study using the SEER-Medicare database. We identified patients with nonmetastatic anal SCC diagnosed between 2001 and 2011 and treated with chemoradiation therapy. We assessed the relation between IMRT and first hospitalization by use of a multivariate competing-risk model, as well as instrumental variable analysis, using provider IMRT affinity as our instrument. Results: Of the 1165 patients included in our study, 458 (39%) received IMRT. IMRT use increased over time and was associated more with regional and provider characteristics than with patient characteristics. The 3- and 6-month cumulative incidences of first hospitalization were 41.9% (95% confidence interval [CI], 37.3%-46.4%) and 47.6% (95% CI, 43.0%-52.2%), respectively, for the IMRT cohort and 46.7% (95% CI, 43.0%-50.4%) and 52.1% (95% CI, 48.4%-55.7%), respectively, for the non-IMRT cohort. IMRT was associated with a decreased hazard of first hospitalization compared with 3-dimensional radiation techniques (hazard ratio, 0.70; 95% CI, 0.58-0.84; P=.0002). Instrumental variable analysis suggested an even greater reduction in hospitalizations with IMRT after controlling for unmeasured confounders. There was a trend toward improved overall survival with IMRT, with an adjusted hazard ratio of 0.77 (95% CI, 0.59-1.00; P=.05). Conclusions: The use of IMRT is associated with reduced hospitalizations in elderly patients with anal SCC. Further work is warranted to understand the long-term health and cost impact of IMRT, particularly for patient subgroups most at risk of toxicity and hospitalization.
Purpose: Patients with human papillomavirus (HPV)–positive oropharyngeal squamous cell carcinoma (OPSCC) have a favorable prognosis. As a result, de-escalation clinical trials are under way. However, approximately 10% of patients will experience distant recurrence even with standard-of-care treatment. Here, we sought to identify novel biomarkers to better risk-stratify HPV-positive patients with OPSCC. Methods and Materials: Gene expression profiling by RNA sequencing (RNA-seq) and quantitative polymerase chain reaction was performed on HPV-positive OPSCC primary tumor specimens from patients with and without distant metastasis (DM). Results: RNA-seq analysis of 39 HPV-positive OPSCC specimens revealed that patients with DM had 2-fold higher E6 gene expression levels than did patients without DM (P=.029). This observation was confirmed in a validation cohort comprising 93 patients with HPV-positive OPSCC. The mean normalized E6 expression level in the 17 recurring primary specimens was 13 ± 2 compared with 8 ± 1 in the remaining 76 nonrecurring primaries (P=.001). Receiver operating characteristic analysis established an E6 expression level of 7.3 as a cutoff for worse recurrence-free survival (RFS). Patients from this cohort with high E6 gene expression (E6-high) (n=51, 55%) had more cancer-related deaths (23% vs 2%, P<.001) and DM (26% vs 5%, P<.001) than did patients with low E6 gene expression (E6-low) (n=42, 45%). Kaplan-Meier survival analysis revealed that E6-high had worse RFS (95% vs 69%, P=.004) and cancer-specific survival (97% vs 79%, P=.007). E6-high maintained statistical significance in multivariate regression models balancing surgery, chemotherapy, nodal stage, and smoking status. Gene set enrichment analysis demonstrated that tumors with high E6 expression were associated with P53, epidermal growth factor receptor, activating transcription factor-2, and transforming growth factor-β signaling pathways. Conclusion: High E6 gene expression level identifies HPV-positive OPSCC patients with 5-fold greater risk of distant disease recurrence and worse cancer-specific survival. Validation in a multi-institutional prospective clinical trial is required to assess the utility of E6 gene expression as a clinically useful prognostic biomarker.
Purpose: To identify single-nucleotide polymorphisms (SNPs) in oxidative stress–related genes associated with risk of late toxicities in breast cancer patients receiving radiation therapy. Methods and Materials: Using a 2-stage design, 305 SNPs in 59 candidate genes were investigated in the discovery phase in 753 breast cancer patients from 2 prospective cohorts from Germany. The 10 most promising SNPs in 4 genes were evaluated in the replication phase in up to 1883 breast cancer patients from 6 cohorts identified through the Radiogenomics Consortium. Outcomes of interest were late skin toxicity and fibrosis of the breast, as well as an overall toxicity score (Standardized Total Average Toxicity). Multivariable logistic and linear regression models were used to assess associations between SNPs and late toxicity. A meta-analysis approach was used to summarize evidence. Results: The association of a genetic variant in the base excision repair gene XRCC1, rs2682585, with normal tissue late radiation toxicity was replicated in all tested studies. In the combined analysis of discovery and replication cohorts, carrying the rare allele was associated with a significantly lower risk of skin toxicities (multivariate odds ratio 0.77, 95% confidence interval 0.61-0.96, P=.02) and a decrease in Standardized Total Average Toxicity scores (−0.08, 95% confidence interval −0.15 to −0.02, P=.016). Conclusions: Using a stage design with replication, we identified a variant allele in the base excision repair gene XRCC1 that could be used in combination with additional variants for developing a test to predict late toxicities after radiation therapy in breast cancer patients.