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A multivariate variational objective analysis-assimilation method. Part 2: Case study results with and without satellite data

The variational multivariate assimilation method described in a companion paper by Achtemeier and Ochs is applied to conventional and conventional plus satellite data. Ground-based and space-based meteorological data are weighted according to the respective measurement errors and blended into a data set that is a solution of numerical forms of the two nonlinear horizontal momentum equations, the hydrostatic equation, and an integrated continuity equation for a dry atmosphere. The analyses serve first, to evaluate the accuracy of the model, and second to contrast the analyses with and without satellite data. Evaluation criteria measure the extent to which: (1) the assimilated fields satisfy the dynamical constraints, (2) the assimilated fields depart from the observations, and (3) the assimilated fields are judged to be realistic through pattern analysis. The last criterion requires that the signs, magnitudes, and patterns of the hypersensitive vertical velocity and local tendencies of the horizontal velocity components be physically consistent with respect to the larger scale weather systems.

Achtemeier, Gary L.↗

Deep Data Analysis of Conductive Phenomena on Complex Oxide Interfaces: Physics from Data Mining

Spatial variability of electronic transport in BiFeO3-CoFe2O4 (BFO-CFO) self-assembled heterostructures is explored using spatially resolved first order reversal curve (FORC) current voltage (IV) mapping. Multivariate statistical analysis of FORC-IV data classifies statistically significant behaviors and maps characteristic responses spatially. In particular, regions of grain, matrix, and grain boundary responses are clearly identified. K-means and Bayesian demixing analysis suggests the characteristic response be separated into four components, with hysteretic type behavior localized at the BFO-CFO tubular interfaces. The conditions under which Bayesian components allow direct physical interpretation are explored, and transport mechanisms at the grain boundaries and individual phases are analyzed. This approach conjoins multivariate statistical analysis with physics-based interpretation, actualizing a robust, universal, data driven approach to problem solving, which can be applied to exploration of local transport and other functional phenomena in other spatially inhomogeneous systems.

big data↗

Real-time fault detection and transient identification using extended Kalman filters - 254

In this paper, real-time fault detection and transient identification are studied with adaptive estimation methods, in particular parallel processing methods by implementing a bank of extended Kalman filters. Adaptive estimation is combined with probabilistic risk assessment to allow for real-time continuous monitoring of initiating events. The approach provides a probability of an initiating event happening. Real-time monitoring of initiating events can reduce labor demand. Each extended Kalman filter is configured to operate at a single configuration, either at normal operation or a faulted state. Fault detection is based on calculating a likelihood function for each extended Kalman filter to determine the posteriori conditional probability that the system configuration is the true configuration. The transient identification is determined by performing a multivariate statistical analysis on each extended Kalman filter to provide a posterior probability assessment that the reactor states and its dynamics are within the allowable limits. The probability distribution being outside the allowable limits indicate a transient has occurred. The combination of parallel processing methods with the multivariate statistical analysis for transient identification allows for the operator to perform transient identification with having a high level of certainty of the current system configuration. We demonstrate the real-time fault detection and transient identification on a simple reactor example to determine the reactor power, reactor temperature, and coolant temperature in the presence of various faults. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Big-Data RHEED analysis for understanding epitaxial film growth processes

Reflection high energy electron diffraction (RHEED) has by now become a standard tool for in-situ monitoring of film growth by pulsed laser deposition and molecular beam epitaxy. Yet despite the widespread adoption and wealth of information in RHEED image, most applications are limited to observing intensity oscillations of the specular spot, and much additional information on growth is discarded. With ease of data acquisition and increased computation speeds, statistical methods to rapidly mine the dataset are now feasible. Here, we develop such an approach to the analysis of the fundamental growth processes through multivariate statistical analysis of RHEED image sequence. This approach is illustrated for growth of LaxCa1-xMnO3 films grown on etched (001) SrTiO3 substrates, but is universal. The multivariate methods including principal component analysis and k-means clustering provide insight into the relevant behaviors, the timing and nature of a disordered to ordered growth change, and highlight statistically significant patterns. Fourier analysis yields the harmonic components of the signal and allows separation of the relevant components and baselines, isolating the assymetric nature of the step density function and the transmission spots from the imperfect layer-by-layer (LBL) growth. These studies show the promise of big data approaches to obtaining more insight into film properties during and after epitaxial film growth. Furthermore, these studies open the pathway to use forward prediction methods to potentially allow significantly more control over growth process and hence final film quality.

Big-Data↗

{sup 1}H NMR-based spectroscopy detects metabolic alterations in serum of patients with early-stage ulcerative colitis

Highlights: •Twenty ulcerative colitis patients and nineteen healthy controls were enrolled. •Increased 3-hydroxybutyrate, glucose, phenylalanine, and decreased lipid were found. •We report early stage diagnosis of ulcerative colitis using NMR-based metabolomics. -- Abstract: Ulcerative colitis (UC) has seriously impaired the health of citizens. Accurate diagnosis of UC at an early stage is crucial to improve the efficiency of treatment and prognosis. In this study, proton nuclear magnetic resonance ({sup 1}H NMR)-based metabolomic analysis was performed on serum samples collected from active UC patients (n = 20) and healthy controls (n = 19), respectively. The obtained spectral profiles were subjected to multivariate data analysis. Our results showed that consistent metabolic alterations were present between the two groups. Compared to healthy controls, UC patients displayed increased 3-hydroxybutyrate, β-glucose, α-glucose, and phenylalanine, but decreased lipid in serum. These findings highlight the possibilities of NMR-based metabolomics as a non-invasive diagnostic tool for UC.

60 APPLIED LIFE SCIENCES↗

Quasar cartography: From black hole to broad-line region scales

A generalized approach to reverberation mapping (RM) is presented, which is applicable to broad- and narrowband photometric data, as well as to spectroscopic observations. It is based on multivariate correlation analysis techniques and, in its present implementation, is able to identify reverberating signals across the accretion disk and the broad-line region (BLR) of active galactic nuclei (AGNs). Statistical tests are defined to assess the significance of time-delay measurements using this approach, and the limitations of the adopted formalism are discussed. It is shown how additional constraints on some of the parameters of the problem may be incorporated into the analysis thereby leading to improved results. When applied to a sample of 14 Seyfert 1 galaxies having good-quality high-cadence photometric data, accretion disk scales and BLR sizes are simultaneously determined, on a case-by-case basis, in most objects. The BLR scales deduced here are in good agreement with the findings of independent spectroscopic RM campaigns. Implications for the photometric RM of AGN interiors in the era of large surveys are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

A Novel Approach to Detect Accelerated Aged and Surface-Mediated Degradation in Explosives by UPLC-ESI-MS.

A new approach was created for studying energetic material degradation. This approach involved detecting and tentatively identifying non-volatile chemical species by liquid chromatography-mass spectrometry (LC-MS) with multivariate statistical data analysis that form as the CL-20 energetic material thermally degraded. Multivariate data analysis showed clear separation and clustering of samples based on sample group: either pristine or aged material. Further analysis showed counter-clockwise trends in the principal components analysis (PCA), a type of multivariate data analysis, Scores plots. These trends may indicate that there was a discrete shift in the chemical markers as the went from pristine to aged material, and then again when the aged CL-20 mixed with a potentially incompatible material was thermally aged for 4, 6, or 9 months. This new approach to studying energetic material degradation should provide greater knowledge of potential degradation markers in these materials.

36 MATERIALS SCIENCE↗

Fuel Cycle Research & Development Technical Monthly – May 2012

Management and Integration LANL - Initial coordination meetings with NE and NA-20 were held the first week of May. Additional meetings, to include NA-82 and the new Proliferation and Terrorism Risk Assessment task are scheduled for June. Work package planning as part of the NTD transition is ongoing. Microcalorimetry LANL - Some parts to attempt repair of a malfunctioning water chiller that has been holding up work on the current detector array have arrived. We will attempt to begin running the compressor/cryostat next week to resume work on commissioning the detector array. We have also been working on a backup plan to temporarily move our system to a different lab space. Completed data analysis and prepared a paper summarizing Pu measurements for peer-review journal. Two members of our team presented work at the SORMA West 2012 conference. Completed data analysis and prepared a milestone report summarizing the development of Monte Carlo tools to study systematic errors. Electrochemical Sensor INL - The second sensor test was stopped short due to the work stand-down. Some activities related to this work have resumed, but not all. The sensor used during the second test was removed from the furnace and it showed cracks and later crumbled when being rinsed for sample preparation. The sensor material will be submitted to SEM analysis once work is resumed in the facilities where analysis is performed. A third sensor test has started. Tests with different arrangements will continue and will be oriented based on post-test analysis of the first three sensor tests. Materials with different annealing temperatures will also be prepared for analysis. Lead slowing down spectrometer LANL - Continued work on perturbation method for LSDS analysis. We are running simulations to delineate issues and are checking additional data libraries to see whether there are differences in simulation results. Electrochemical sensor INL - The second sensor test was stopped short due to the work stand-down. Some activities related to this work have resumed, but not all. The sensor used during the second test was removed from the furnace and it showed cracks and later crumbled when being rinsed for sample preparation. The sensor material will be submitted to SEM analysis once work is resumed in the facilities where analysis is performed. A third sensor test has started. Tests with different arrangements will continue and will be oriented based on post-test analysis of the first three sensor tests. Materials with different annealing temperatures will also be prepared for analysis. Fast Neutron Multiplicity analysis INL - The University of Michigan team continues its work on the post-experiment analysis of the validation data from JRC ISPRA, as well as scoping studies using the simulation tool MCNPX-PoliMi. At INL, our new staff member working on this project is now working to model performance capabilities for the fast-neutrons scintillator design concepts. At INL our primary analysis approach is focused on the Feynman mean-to-variance approach. At the University of Michigan, the primary analysis approach is multiplicity coincidence analysis. Fast Neutron Imaging to Quantify Nuclear Materials ORNL - Completed additional measurements of the two 'trainer' configurations as well as calibration measurements with sources on an x-y stage. The imager was shipped to Pantex for an NA-22 obligation at the end of May. Lead Slowing Down Spectrometer LANL - Continued to look into He4 detector. A Swiss company was located that makes He4 detectors and associated electronics. Had a teleconference with them to assess the possible help we can get from them. We are also looking in to constructing one locally. Ongoing perturbation calculations are providing information on the fundamental systematic error limits of LSDS. In order to achieve separating the contribution of Pu and 235U to the signal, there will need to be tight controls on systematic errors. Multi-isotope Process Monitor PNNL - Attended a training call in advanced multivariate classification and analysis methods. These methods were applied to the multivariate analysis of fuel characteristics based on simulated gamma. Work continued on a computational framework to quantify the impact of gamma-ray counting statistical precision on principal component regression (PCR) analysis of a multi-component (i.e. multi-isotope) gammaray spectrum. Tests of the simulation framework are anticipated to begin in early June. Development of a proposal to instrument H-Canyon is being prepared in conjunction with SRNL and the NNSA's NGSI program is ongoing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Bayesian nonparametric analysis for zero-inflated multivariate count data with application to microbiome study

High-throughput sequencing technology has enabled researchers to profile microbial communities from a variety of environments, but analysis of multivariate taxon count data remains challenging. Here, we develop a Bayesian nonparametric (BNP) regression model with zero inflation to analyse multivariate count data from microbiome studies. A BNP approach flexibly models microbial associations with covariates, such as environmental factors and clinical characteristics. The model produces estimates for probability distributions which relate microbial diversity and differential abundance to covariates, and facilitates community comparisons beyond those provided by simple statistical tests. We compare the model to simpler models and popular alternatives in simulation studies, showing, in addition to these additional community-level insights, it yields superior parameter estimates and model fit in various settings. The model's utility is demonstrated by applying it to a chronic wound microbiome data set and a Human Microbiome Project data set, where it is used to compare microbial communities present in different environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of Optimum Interpolation and Cressman Analyses

The objective of this investigation is to develop a state-of-the-art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies. A three-dimensional multivariate O/I analysis scheme has been developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Baker, W. E.↗

MALDI Orbitrap Mass Spectrometry Profiling of Dysregulated Sulfoglycosphingolipids in Renal Cell Carcinoma Tissues

Matrix-assisted laser desorption/ionization coupled with Orbitrap mass spectrometry (MALDI-Orbitrap-MS) is used for the clinical study of patients with renal cell carcinoma (RCC), as the most common type of kidney cancer. Significant changes in sulfoglycosphingolipid abundances between tumor and autologous normal kidney tissues are observed. First, sulfoglycosphingolipid species in studied RCC samples are identified using high mass accuracy full scan and tandem mass spectra. Subsequently, optimization, method validation, and statistical evaluation of MALDI-MS data for 158 tissues of 80 patients are discussed. More than 120 sulfoglycosphingolipids containing one to five hexosyl units are identified in human RCC samples based on the systematic study of their fragmentation behavior. Many of them are recorded here for the first time. Multivariate data analysis (MDA) methods, i.e., unsupervised principal component analysis (PCA) and supervised orthogonal partial least square discriminant analysis (OPLS-DA), are used for the visualization of differences between normal and tumor samples to reveal the most up- and downregulated lipids in tumor tissues. Obtained results are closely correlated with MALDI mass spectrometry imaging (MSI) and histologic staining. Important steps of the present MALDI-Orbitrap-MS approach are also discussed, such as the selection of best matrix, correct normalization, validation for semiquantitative study, and problems with possible isobaric interferences on closed masses in full scan mass spectra. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comparison of Optimum Interpolation and Cressman Analyses

The development of a state of the art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies was investigated. A three dimensional multivariate O/I analysis scheme was developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Baker, W. E.↗

Intrinsic Dosimetry: Elemental Composition Effects on the Thermoluminescence of Commercial Borosilicate Glass

Intrinsic dosimetry is the method of measuring total absorbed dose received by the walls of a container holding radioactive material. By considering this dose in tandem with the physical characteristics of the radioactive material housed within the container, this method can provide enhanced pathway information for interdicted radioactive samples. Thermoluminescence (TL) dosimetry was used to measure ionizing radiation dose effects on stock borosilicate glass. Differences in TL glow curve shape and intensity were observed for glasses from different geographical origins. The different TL signatures strongly correlated with the concentration of alkaline earth metals and the ratio of sodium to the total amount of alkali metal present in the borosilicate glass.

61 RADIATION PROTECTION AND DOSIMETRY↗

Human Performance of Novice Schedulers for Complex Spaceflight Operations Timelines

Objective: Investigate the effects on human performance as a function of scheduling task complexity for novice schedulers creating spaceflight timelines. Background: Future astronauts will be expected to self-schedule, yet will not be experts in creating timelines that meet complex constraints inherent to spaceflight operations. Method: Conducted a within-subject experiment to measure scheduling efficiency, effectiveness, workload and situation awareness while varying scheduling task complexity factors, namely number of constraints and types of constraints. Results: Fifteen participants completed various scheduling problems. Performance differences were identified between the independent variables. There was a main effect due to the number of constraints and type of constraint for efficiency, effectiveness, and workload. Significant interactions were observed in situation awareness and workload for certain types of constraints. Results also suggest that a lower number of constraints may be manageable by novice schedulers when compared to scheduling activities without constraints. Conclusion: Results suggest that novice schedulers performance decreases with high number of constraints and future scheduling aids may have to be targeted to type of constraint. Application: Knowledge on the effect of scheduling task complexity will help design scheduling systems that will enable self-scheduling for future astronauts. It will also inform other domains that conduct complex scheduling, such as nursing and manufacturing.

scheduling↗

Risk Factors for Brain Metastases in Locally Advanced Non-Small Cell Lung Cancer With Definitive Chest Radiation

Purpose: We intended to identify risk factors that affect brain metastases (BM) in patients with locally advanced non-small cell lung cancer (LA-NSCLC) receiving definitive radiation therapy, which may guide the choice of selective prevention strategies. Methods and Materials: The characteristics of 346 patients with stage III NSCLC treated with thoracic radiation therapy from January 2008 to December 2010 in our institution were retrospectively reviewed. BM rates were analyzed by the Kaplan-Meier method. Multivariate Cox regression analysis was performed to determine independent risk factors for BM. Results: The median follow-up time was 48.3 months in surviving patients. A total of 74 patients (21.4%) experienced BM at the time of analysis, and for 40 (11.7%) of them, the brain was the first site of failure. The 1-year and 3-year brain metastasis rates were 15% and 28.1%, respectively. In univariate analysis, female sex, age ≤60 years, non-squamous cell carcinoma, T3-4, N3, >3 areas of lymph node metastasis, high lactate dehydrogenase and serum levels of tumor markers (CEA, NSE, CA125) before treatment were significantly associated with BM (P<.05). In multivariate analysis, age ≤60 years (P=.004, hazard ratio [HR] = 0.491), non-squamous cell carcinoma (P=.000, HR=3.726), NSE >18 ng/mL (P=.008, HR=1.968) and CA125 ≥ 35 U/mL (P=.002, HR=2.129) were independent risk factors for BM. For patients with 0, 1, 2, and 3 to 4 risk factors, the 3-year BM rates were 7.3%, 18.9%, 35.8%, and 70.3%, respectively (P<.001). Conclusions: Age ≤60 years, non-squamous cell carcinoma, serum NSE >18 ng/mL, and CA125 ≥ 35 U/mL were independent risk factors for brain metastasis. The possibilities of selectively using prophylactic cranial irradiation in higher-risk patients with LA-NSCLC should be further explored in the future.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Association Between Maximal Skin Dose and Breast Brachytherapy Outcome: A Proposal for More Rigorous Dosimetric Constraints

Purpose: Multiple investigations have used the skin distance as a surrogate for the skin dose and have shown that distances <6 mm have been associated with late toxicity after MammoSite brachytherapy. No publications have yet described the relationship between the actual maximal skin dose and the outcome. The present study analyzed the maximal skin dose delivered and the occurrence of late toxicity in a large cohort of patients with prolonged follow-up. Methods: A total of 96 patients treated with breast brachytherapy between 2000 and 2007 for whom complete planning and follow-up data were available were included in the present analysis. The median follow-up was 48 months (range, 24-111). Of the 96 patients, 40 were treated with multicatheter interstitial brachytherapy and 56 with MammoSite. A multivariate statistical analysis was performed to determine the relationship between several dosimetric parameters and patient outcome. Results: The treatment was well tolerated, with 98% of patients experiencing good to excellent cosmesis. Significant late toxicity was uncommon. The maximal dose delivered to the skin was significantly associated with the incidence of any degree of telangiectasia (p = .009) and moderate to severe fibrosis (p = .010). The incidence of late toxicity was significantly increased when the dose to the skin was >4.05 Gy/fraction. Conclusion: The initial skin dose recommendations have been based on safe use and the avoidance of significant toxicity. The results from the present study have suggested that patients might further benefit if more rigorous constraints were applied and if the skin dose were limited to 120% of the prescription dose.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Confocal Raman imaging of skin sections containing hair follicles using classical least squares regression and multivariate curve resolution – alternating least squares

Confocal Raman microscopy (CRM) is applied ex vivo for imaging of the spatial distribution of different skin components in skin sections containing hair follicles. For multivariate data analysis, different methods are used in order to spectrally decompose the reference spectra of the skin components (dermis, viable epidermis, stratum corneum and hair). Classical least squares regression (CLS) and multivariate curve resolution–alternating least squares (MCR-ALS) are chosen as suitable methods. In comparison to other optical methods, the advantage of CRM is molecular specificity and dispensability of labelling dyes, which is e.g. necessary in fluorescence microscopy. Therefore, a useful future application of CRM in combination with multivariate data analysis lies in the analysis of penetration routes of topically applied substances, such as cosmetic formulations or drugs into the skin, which is particularly interesting in and around hair follicles. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Pretreatment Nomogram to Predict the Risk of Acute Urinary Retention After I-125 Prostate Brachytherapy

Purpose: Acute urinary retention (AUR) after iodine-125 (I-125) prostate brachytherapy negatively influences long-term quality of life and therefore should be prevented. We aimed to develop a nomogram to preoperatively predict the risk of AUR. Methods: Using the preoperative data of 714 consecutive patients who underwent I-125 prostate brachytherapy between 2005 and 2008 at our department, we modeled the probability of AUR. Multivariate logistic regression analysis was used to assess the predictive ability of a set of pretreatment predictors and the additional value of a new risk factor (the extent of prostate protrusion into the bladder). The performance of the final model was assessed with calibration and discrimination measures. Results: Of the 714 patients, 57 patients (8.0%) developed AUR after implantation. Multivariate analysis showed that the combination of prostate volume, IPSS score, neoadjuvant hormonal treatment and the extent of prostate protrusion contribute to the prediction of AUR. The discriminative value (receiver operator characteristic area, ROC) of the basic model (including prostate volume, International Prostate Symptom Score, and neoadjuvant hormonal treatment) to predict the development of AUR was 0.70. The addition of prostate protrusion significantly increased the discriminative power of the model (ROC 0.82). Calibration of this final model was good. The nomogram showed that among patients with a low sum score (<18 points), the risk of AUR was only 0%-5%. However, in patients with a high sum score (>35 points), the risk of AUR was more than 20%. Conclusion: This nomogram is a useful tool for physicians to predict the risk of AUR after I-125 prostate brachytherapy. The nomogram can aid in individualized treatment decision-making and patient counseling.

62 RADIOLOGY AND NUCLEAR MEDICINE↗