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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.

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At least 811 records · Page 45

Organic Aerosol Component (OACOMP) Value-Added Product (Report)

Significantly improved returns in their aerosol chemistry data can be achieved via the development of a value-added product (VAP) of deriving OA components, called Organic Aerosol Components (OACOMP). OACOMP is primarily based on multivariate analysis of the measured organic mass spectral matrix. The key outputs of OACOMP are the concentration time series and the mass spectra of OA factors that are associated with distinct sources, formation and evolution processes, and physicochemical properties.

54 ENVIRONMENTAL SCIENCES↗

Automated Characterization of Spent Fuel through the Multi-Isotope Process (MIP) Monitor

This research developed an algorithm for characterizing spent nuclear fuel (SNF) samples based on simulated gamma spectra. The gamma spectra for a variety of light water reactor fuels typical of those found in the United States were simulated. Fuel nuclide concentrations were simulated in ORIGEN-ARP for 1296 fuel samples with a variety of reactor designs, initial enrichments, burn ups, and cooling times. The results of the ORIGEN-ARP simulation were then input to SYNTH to simulate the gamma spectrum for each sample. These spectra were evaluated with partial least squares (PLS)-based multivariate analysis methods to characterize the fuel according to reactor type (pressurized or boiling water reactor), enrichment, burn up, and cooling time. Characterizing some of the features in series by using previously estimated features in the prediction greatly improves the performance. By first classifying the spent fuel reactor type and then using type-specific models, the prediction error for enrichment, burn up, and cooling time improved by a factor of two to four. For some features, the prediction was further improved by including additional information, such as including the predicted burn up in the estimation of cooling time. The optimal prediction flow was determined based on the simulated data. A PLS discriminate analysis model was developed which perfectly classified SNF reactor type. Burn up was predicted within 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment within approximately 2% RMSPE.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Measurement of the E Polarization Observable for yd --> pi^-p(p_s), yd-->K^0Lambda(p_s), and yd-->pi^+pi^-d(0) using CLAS g14 data at Jefferson Lab

Photoproduction of mesons from the nucleon has a long and ongoing tradition for exploring nucleon excitations and the baryon-baryon interaction. Polarization observables which play a role in the photoproduction mechanism are, therefore, essential in addition to the differential cross section. The CLAS collaboration at Jefferson Lab, has been active in measuring these observables, but until now only on a proton targets. However, a comprehensive picture of the pseudoscalar meson photoproduction requires neutron data as well. That is, paired measurements of observables in p and n reactions are necessary to disentangle the photoproduction mechanism on the basis of isospin I = 0, and I = 1 photo-coupling transition amplitudes. The g14 experiment with 'HDIce,' a longitudinally polarized solid target of molecular hydrogen-deuteride with low background contamination from other nuclear species, provided an unique opportunity to measure several polarization observables|for the first time|on the neutron for different channels. In particular, we present our measurements of the E beam-target polarization observable, which requires circularly polarized beam and a longitudinally polarized target, for p pi^-, K^0Lambda, and K^0Sigma^0 channels in the energy range of 1.5 lte W lte 2.3 GeV. In addition, we also utilized the g14 dataset to investigate the intrinsic spin of a possible dibaryonic ND bound state by measuring the E (beam-target) observable on the d-pi^+/-d channel of the reaction yd --> pi^+pi^-d(0). Finally, this thesis also discusses a highly efficient multivariate analysis method called Boosted Decision Trees, which we employed extensively for this work and which has not been used before in CLAS data analysis.

Ho, Dao↗

Delayed HIV diagnosis common in Sweden, 2003–2010

Background: Early diagnosis of HIV is important for the prognosis of individual patients, because antiretroviral treatment can be started at the appropriate time, and for public health, because transmission can be prevented. Methods: Data were collected from 767 HIV patients who were diagnosed in Sweden during 2003–2010 and were infected in Sweden or born in Sweden and infected abroad. A recent infection testing algorithm (RITA) was applied to BED-EIA test results (OD-n < 0.8), CD4 counts (≥ 200 cells/μl), and clinical information. A recent infection classification was used as indicator for early diagnosis. Time trends in early diagnosis were investigated to detect population changes in HIV testing behavior. Patients with early diagnosis were compared to patients with delayed diagnosis with respect to age, gender, transmission route, and country of infection (Sweden or abroad). Results: Early diagnosis was observed in 271 patients (35%). There was no statistically significant time trend in the yearly percentage of patients with early diagnosis in the entire study group (p = 0.836) or in subgroups. Early diagnosis was significantly more common in men who have sex men (MSM) (45%) than in heterosexuals (21%) and injecting drug users (27%) (p < 0.001 and p = 0.001, respectively) in both univariate and multivariable analyses. The only other factor that remained associated with early diagnosis in multivariable analysis was young age group. Conclusion: Approximately one-third of the study patients were diagnosed early with no significant change over time. Delayed HIV diagnosis is a considerable problem in Sweden, which does not appear to diminish.

delayed diagnosis↗

Evaluating lignocellulosic biomass, its derivatives, and downstream products with Raman spectroscopy

The creation of fuels, chemicals, and materials from plants can aid in replacing products fabricated from non-renewable energy sources. Before using biomass in downstream applications, it must be characterized to assess chemical traits, such as cellulose, lignin, or lignin monomer content, or the sugars released following an acid or enzymatic hydrolysis. The measurement of these traits allows researchers to gage the recalcitrance of the plants and develop efficient deconstruction strategies to maximize yields. Standard methods for assessing biomass phenotypes often have experimental protocols that limit their use for screening sizeable numbers of plant species. Raman spectroscopy, a non-destructive, non-invasive vibrational spectroscopy technique, is capable of providing qualitative, structural information and quantitative measurements. Applications of Raman spectroscopy have aided in alleviating the constraints of standard methods by coupling spectral data with multivariate analysis to construct models capable of predicting analytes. Hydrolysis and fermentation products, such as glucose and ethanol, can be quantified off-, at-, or on-line. Raman imaging has enabled researchers to develop a visual understanding of reactions, such as different pretreatment strategies, in real-time, while also providing integral chemical information. Finally, this review provides an overview of what Raman spectroscopy is, and how it has been applied to the analysis of whole lignocellulosic biomass, its derivatives, and downstream process monitoring.

09 BIOMASS FUELS↗

Editorial: Biomass Modification, Characterization, and Process Monitoring Analytics to Support Biofuel and Biomaterial Production

This Frontiers Research Topic journeys through various challenges facing researchers seeking to develop fuels and products derived from lignocellulosic biomass. These challenges include: the rapid quantification of plant cell wall chemistry, enabling yields of potential monomeric sugars to be assessed, identification of plants possessing ideal trait that can be brought to the forefront of research efforts; once the native plant chemistry is known, how can yields be improved by chemically or genetically altering plant cell walls to reduce recalcitrance; does genetic modification of plants to increase accessibility to saccharification enzymes hinder the plant’s growth and/or function; are the innovative methods identified by researchers cost-effective and scalable to a commercial level? These topics are a sampling of the obstacles researchers combat when nominating a specific plant for downstream applications or implementing new deconstruction, genetic, or measurement strategies. How well can different plants can be broken down into useful, downstream precursor molecules? Efforts to develop a lucid picture of the chemical composition of abundant, diverse plants being explored as potential starting feedstocks has resulted in the evolution of high-throughput techniques that permit many more samples to be screened in much shorter periods of time. Advances in thermochemical and spectroscopic techniques have enabled the screening of thousands of plants for different phenotypes, such as cell-wall composition and monomeric sugar release. Some instrumental methods have been coupled with multivariate analysis, providing elegant chemometric predictive models enabling the accelerated identification of potential feedstocks. Rapid instrumental techniques have been developed for real-time monitoring of diverse processes, such as the efficacy of specific pretreatment strategies, or downstream products, such as biofuels and biomaterials. Real-time process monitoring techniques are needed for all stages of the feedstocks-to-biofuels conversion process to maximize efficiency and lower costs by monitoring and optimizing performance. These approaches allow researchers to adjust experimental conditions during, rather than at the conclusion, of processes, thereby decreasing overhead expenses.

09 BIOMASS FUELS↗

Within and Among Fish Species Differences in Simulated Turbine Blade Strike Mortality: Limits on the Use of Surrogacy for Untested Species

Use of surrogacy remains a useful method for prioritizing research on representatives of at-risk groups of fishes, yet quantifiable evidence in support of its use is generally not available. Blade strike impact represents one of the most traumatic stressors experienced by fish during non-volitional movements through hydropower turbines. Here, we use data generated from laboratory trials on blade strike impact experiments to directly test use of surrogacy for salmonid and clupeid fishes. Results of logistic regression indicated that a -taxonomic (genus) variable was not a significant predictor of mortality among large rainbow trout and brook trout. Similar results were found for young-of-the-year shad species, but genus-level taxonomy was a significant predictor of mortality while species was not. Multivariate analysis of morphometric data showed that shad clustered together based on similarities in fish shape which was also closely associated with genus. Logistic regression including size as a major covariate suggested total fish length was not a significant predictor of mortality, yet dose–response data suggest differential susceptibility to lower strike velocities. We suggest that use of surrogacy among species is justifiable but should be avoided within a species since the effects of size remain unclear.

59 BASIC BIOLOGICAL SCIENCES↗

An evaluation of prognostic factors, oncologic outcomes, and management for primary and recurrent squamous cell carcinoma of the vulva

Objective: To evaluate prognostic factors, outcomes, and management patterns of patients treated for squamous cell carcinoma of the vulva. Methods: One hundred sixty-four women were retrospectively identified with primary squamous cell carcinoma of the vulva treated at our institution between 1/1996–12/2018. Descriptive statistics were performed on patient, tumor, and treatment characteristics. The χ 2 tests and t-tests were used to compare categorical variables and continuous variables, respectively. Recurrence free survival (RFS), overall survival (OS), and disease-specific survival (DSS) were analyzed with Kaplan-Meier estimates, the log-rank test, and Cox proportional hazards. Results: Median follow-up was 52.5 months. Five-year RFS was 67.9%, 60.0%, 42.1%, and 20.0% for stage I–IV, respectively. Five-year DSS was 86.2%, 81.6%, 65.0%, and 42.9% for stage I–IV, respectively. On multivariate analysis, positive margins predicted overall RFS (hazard ratio [HR]=3.55; 95% confidence interval [CI]=1.18–10.73; p=0.025), while presence of lichen sclerosus on pathology (HR=2.78; 95% CI=1.30–5.91; p=0.008) predicted local RFS. OS was predicted by nodal involvement (HR=2.51; 95% CI=1.02–6.13; p=0.043) and positive margins (HR=5.19; 95% CI=2.03–13.26; p=0.001). Adjuvant radiotherapy significantly improved RFS (p=0.016) and DSS (p=0.012) in node-positive patients. Median survival after treatment of local, groin, and pelvic/distant recurrence was 52, 8, and 5 months, respectively. Conclusion: For primary treatment, more conservative surgical approaches can be considered with escalation of treatment in patients with concurrent precursor lesions, positive margins, and/or nodal involvement. Further studies are warranted to improve risk stratification in order to optimize treatment paradigms for vulvar cancer patients.

60 APPLIED LIFE SCIENCES↗

On scaling techniques

An introductory review of the principles of scaling with emphasis on ride quality work is presented. It will be divided into six parts as follows: (1) definition of scaling, (2) scope and goals of scaling, (3) scaling techniques (with emphasis on rating scale, magnitude estimation procedures and cross-modality matching), (4) laboratory vs. field studies, (5) multivariate analysis; and (6) selected references.

Source record↗

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

Siapkaras, A.↗

Methods for presentation and display of multivariate data

Methods for the presentation and display of multivariate data are discussed with emphasis placed on the multivariate analysis of variance problems and the Hotelling T(2) solution in the two-sample case. The methods utilize the concepts of stepwise discrimination analysis and the computation of partial correlation coefficients.

Myers, R. H.↗

Identifying environmental features for land management decisions

The benefits of changes in management organization and facilities for the Center for Remote Sensing and Cartography in Utah are reported as well as interactions with and outreach to state and local agencies. Completed projects are described which studied (1) Unita Basin wetland/land use; (2) Davis County foothill development; (3) Farmington Bay shoreline fluctuation; (4) irrigation detection; and (5) satellite investigation of snow cover/mule deer relationships. Techniques developed for composite computer mapping, contrast enhancement, U-2 CIR/LANDSAT digital interface; factor analysis, and multivariate statistical analysis are described.

Source record↗

Update and review of accuracy assessment techniques for remotely sensed data

Research performed in the accuracy assessment of remotely sensed data is updated and reviewed. The use of discrete multivariate analysis techniques for the assessment of error matrices, the use of computer simulation for assessing various sampling strategies, and an investigation of spatial autocorrelation techniques are examined.

Congalton, R. G.↗

Multivariate optimum interpolation of surface pressure and surface wind over oceans

The present multivariate analysis method for surface pressure and winds incorporates ship wind observations into the analysis of surface pressure. For the specific case of 0000 GMT, on February 3, 1979, the additional data resulted in a global rms difference of 0.6 mb; individual maxima as larse as 5 mb occurred over the North Atlantic and East Pacific Oceans. These differences are noted to be smaller than the analysis increments to the first-guess fields.

Bloom, S. C.↗

Multidisciplinary optimization of controlled space structures with global sensitivity equations

A new method for the preliminary design of controlled space structures is presented. The method coordinates standard finite element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structures and control systems of a spacecraft. Global sensitivity equations are a key feature of this method. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Fifteen design variables are used to optimize truss member sizes and feedback gain values. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporating the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables. The solution of the demonstration problem is an important step toward a comprehensive preliminary design capability for structures and control systems. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines.

Padula, Sharon L.↗

Multidisciplinary optimization of a controlled space structure using 150 design variables

A controls-structures interaction design method is presented. The method coordinates standard finite-element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structure and control system of a spacecraft. Global sensitivity equations are used to account for coupling between the disciplines. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Design problems using 15, 63, and 150 design variables to optimize truss member sizes and feedback gain values are solved and the results are presented. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporation of the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables.

James, Benjamin B.↗

Orthostatic function during a stand test before and after head-up or head-down bedrest

The effects of head-down or head-up bedrest at -5, +10, +20, or +42 deg (simulating 0, 1/6, 1/3, and 2/3 g, respectively) for 6 hrs on four different days on the orthostatic tolerance were investigated by measuring relevant physiological reactions to orthostatic test taken before and after bedrest sessions. The multivariate analysis of variance statistical analyses indicates that there was no angle effect on any of the cardiovascular parameters monitored during the last 3 min of the stand test, suggesting that partial gravity loads would have no effect on the cardiovascular deconditioning exhibited postflight. There was, however, a significant elevation in the heart rate post-bedrest, and the heart rate increased on standing. Results from the stand test pre- and post-bedrest at -5 deg (but not at +10, +20, and +42 deg) were similar to those observed after space flight.

Lathers, Claire M.↗

Multidisciplinary optimization of a controlled space structure using 150 design variables

A general optimization-based method for the design of large space platforms through integration of the disciplines of structural dynamics and control is presented. The method uses the global sensitivity equations approach and is especially appropriate for preliminary design problems in which the structural and control analyses are tightly coupled. The method is capable of coordinating general purpose structural analysis, multivariable control, and optimization codes, and thus, can be adapted to a variety of controls-structures integrated design projects. The method is used to minimize the total weight of a space platform while maintaining a specified vibration decay rate after slewing maneuvers.

James, Benjamin B.↗