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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Classification System for Identifying Women at Risk for Altered Partial Breast Irradiation Recommendations After Breast Magnetic Resonance Imaging

Purpose: To study the utility of preoperative breast MRI for partial breast irradiation (PBI) patient selection, using multivariable analysis of significant risk factors to create a classification rule. Methods and Materials: Between 2002 and 2009, 712 women with newly diagnosed breast cancer underwent preoperative bilateral breast MRI at Mayo Clinic Florida. Of this cohort, 566 were retrospectively deemed eligible for PBI according to the National Surgical Adjuvant Breast and Bowel Project Protocol B-39 inclusion criteria using physical examination, mammogram, and/or ultrasound. Magnetic resonance images were then reviewed to determine their impact on patient eligibility. The patient and tumor characteristics were evaluated to determine risk factors for altered PBI eligibility after MRI and to create a classification rule. Results: Of the 566 patients initially eligible for PBI, 141 (25%) were found ineligible because of pathologically proven MRI findings. Magnetic resonance imaging detected additional ipsilateral breast cancer in 118 (21%). Of these, 62 (11%) had more extensive disease than originally noted before MRI, and 64 (11%) had multicentric disease. Contralateral breast cancer was detected in 28 (5%). Four characteristics were found to be significantly associated with PBI ineligibility after MRI on multivariable analysis: premenopausal status (P=.021), detection by palpation (P<.001), first-degree relative with a history of breast cancer (P=.033), and lobular histology (P=.002). Risk factors were assigned a score of 0-2. The risk of altered PBI eligibility from MRI based on number of risk factors was 0:18%; 1:22%; 2:42%; 3:65%. Conclusions: Preoperative bilateral breast MRI altered the PBI recommendations for 25% of women. Women who may undergo PBI should be considered for breast MRI, especially those with lobular histology or with 2 or more of the following risk factors: premenopausal, detection by palpation, and first-degree relative with a history of breast cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Can Locoregional Treatment of the Primary Tumor Improve Outcomes for Women With Stage IV Breast Cancer at Diagnosis?

Purpose: To examine the effect of locoregional treatment (LRT) of the primary tumor on survival in patients with Stage IV breast cancer at diagnosis. Methods and Materials: The study cohort comprised 733 women referred to the British Columbia Cancer Agency between 1996 and 2005 with newly diagnosed clinical or pathologic M1 breast cancer. Tumor and treatment characteristics, overall survival (OS), and locoregional progression-free survival were compared between patients treated with (n = 378) and without (n = 355) LRT of the primary disease. Multivariable analysis was performed with Cox regression modeling. Results: The median follow-up time was 1.9 years. LRT consisted of surgery alone in 67% of patients, radiotherapy alone in 22%, and both in 11%. LRT was used more commonly in women with age <50 years, Eastern Cooperative Oncology Group (ECOG) performance status 0-1, Stage T1-2 tumors, N0-1 disease, limited M1 burden, and asymptomatic M1 disease (all p < 0.05). Systemic therapy was used in 92% of patients who underwent LRT and 85% of patients who did not. In patients treated with LRT compared with those without LRT, the 5-year OS rates were 21% vs. 14% (p < 0.001), and the rates of locoregional progression-free survival were 72% vs. 46% (p < 0.001). Among 378 patients treated with LRT, the rates of 5-year OS were higher in patients with age <50, ECOG performance status 0-1, estrogen receptor-positive disease, clear surgical margins, single subsite, bone-only metastasis, and one to four metastatic lesions (all p < 0.003). On multivariable analysis, LRT was associated with improved OS (hazard ratio, 0.78; 95% confidence interval, 0.64-0.94, p = 0.009). Conclusion: Locoregional treatment of the primary disease is associated with improved survival in some women with Stage IV breast cancer at diagnosis. Among those treated with LRT, the most favorable rates of survival were observed in subsets with young age, good performance status, estrogen receptor-positive disease, clear margins, and distant disease limited to one subsite, bone-only involvement, or fewer than five metastatic lesions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Stage Presentation, Care Patterns, and Treatment Outcomes for Squamous Cell Carcinoma of the Penis

Purpose: Penile squamous cell carcinoma (SCC) is a rare entity, with few published series on outcomes. We evaluated the stage distributions and outcomes for surgery and radiation therapy in a U.S. population database. Methods and Materials: Subjects with SCC of the penis were identified using the National Cancer Institute Surveillance, Epidemiology and End Results (SEER) Program database between 1988 and 2006. Descriptive statistics were performed, and cause-specific survival (CSS) was estimated using Kaplan-Meier analysis. Comparisons of treatment modalities were analyzed using multivariate Cox regression. Subjects were staged using American Joint Committee on Cancer, sixth edition, criteria. Results: There were 2458 subjects identified. The median age was 66.8 years (range, 17-102 years). Grade 2 disease was present in 94.5% of cases. T1, T2, T3, T4, and Tx disease was present in 64.8%, 17.1%, 9.5%, 2.1%, and 6.5% of cases, respectively. N0, N1, N2, N3, and Nx disease was noted in 61.6%, 6.9%, 4.0%, 3.7%, and 23.8% of cases, respectively. M1 disease was noted in 2.5% of subjects. Individuals of white ethnicity accounted for 85.1% of cases. Lymphadenectomy was performed in 16.7% of cases. The CSS for all patients at 5 and 10 years was 80.8% and 78.6%. By multivariable analysis grades 2 and 3 disease, T3 stage, and positive lymph nodes were adverse prognostic factors for CSS. Conclusion: SCC of the penis often presents as early-stage T1, N0, M0, grade 1, or grade 2 disease. The majority of patients identified were treated with surgery, and only a small fraction of patients received radiation therapy alone or as adjuvant therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Comparing gas composition from fast pyrolysis of live foliage measured in bench-scale and fire-scale experiments

Background: Fire models have used pyrolysis data from oxidising and non-oxidising environments for flaming combustion. In wildland fires pyrolysis, flaming and smouldering combustion typically occur in an oxidising environment (the atmosphere). Aims: Using compositional data analysis methods, determine if the composition of pyrolysis gases measured in non-oxidising and ambient (oxidising) atmospheric conditions were similar. Methods: Permanent gases and tars were measured in a fuel-rich (non-oxidising) environment in a flat flame burner (FFB). Permanent and light hydrocarbon gases were measured for the same fuels heated by a fire flame in ambient atmospheric conditions (oxidising environment). Log-ratio balances of the measured gases common to both environments (CO, CO 2 , CH 4 , H 2 , C 6 H 6 O (phenol), and other gases) were examined by principal components analysis (PCA), canonical discriminant analysis (CDA) and permutational multivariate analysis of variance (PERMANOVA). Key results: Mean composition changed between the non-oxidising and ambient atmosphere samples. PCA showed that flat flame burner (FFB) samples were tightly clustered and distinct from the ambient atmosphere samples. CDA found that the difference between environments was defined by the CO-CO 2 log-ratio balance. PERMANOVA and pairwise comparisons found FFB samples differed from the ambient atmosphere samples which did not differ from each other. Conclusion: Relative composition of these pyrolysis gases differed between the oxidising and non-oxidising environments. This comparison was one of the first comparisons made between bench-scale and field scale pyrolysis measurements using compositional data analysis. Implications: These results indicate the need for more fundamental research on the early time-dependent pyrolysis of vegetation in the presence of oxygen.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Novel principal component analysis tool based on python for analysis of complex spectra of time-of-flight secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis tool, which can simultaneously provide elemental, isotopic, and molecular information with part per million (ppm) sensitivity. However, each spectrum may be composed of hundreds of ion signals, which makes the spectra data complex. Principal component analysis (PCA) is a multivariate analysis technique that has been widely used to figure out the variances among samples in ToF-SIMS spectra data analysis and is showing great success in the explanation of complex ToF-SIMS spectra. So far, several software tools have been developed for PCA of ToF-SIMS spectra; however, none of them are freely available. Such a situation leads to some difficulties in extending applications of PCA to various research fields. More importantly, it has long been challenging for common researchers to understand PCA plots and extract chemical differences among samples. In this work, we developed a new and flexible software tool (named “advanced spectra pca toolbox”) based on python for PCA of complex ToF-SIMS spectra along with an easy-to-read manual. It can generate data analysis reports automatically to explain chemical differences among samples, allowing less experienced researchers to easily understand tricky PCA results. Moreover, it is expandable and compatible with artificial intelligence/machine learning functions. Pure goethite and different lignin adsorbed goethite samples were used as a model system to demonstrate our new software tool, proving that our software tool can be readily used in complex spectra data processing. Our new software tool is open-source, convenient, flexible, and expandable. We expect this open-source tool will benefit the ToF-SIMS community.

47 OTHER INSTRUMENTATION↗
NASA NTRS1979

Statistical analysis of multivariate atmospheric variables

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Tubbs, J. D.↗
NASA NTRS2013

Analysis of Multivariate Experimental Data Using A Simplified Regression Model Search Algorithm

A new regression model search algorithm was developed that may be applied to both general multivariate experimental data sets and wind tunnel strain-gage balance calibration data. The algorithm is a simplified version of a more complex algorithm that was originally developed for the NASA Ames Balance Calibration Laboratory. The new algorithm performs regression model term reduction to prevent overfitting of data. It has the advantage that it needs only about one tenth of the original algorithm's CPU time for the completion of a regression model search. In addition, extensive testing showed that the prediction accuracy of math models obtained from the simplified algorithm is similar to the prediction accuracy of math models obtained from the original algorithm. The simplified algorithm, however, cannot guarantee that search constraints related to a set of statistical quality requirements are always satisfied in the optimized regression model. Therefore, the simplified algorithm is not intended to replace the original algorithm. Instead, it may be used to generate an alternate optimized regression model of experimental data whenever the application of the original search algorithm fails or requires too much CPU time. Data from a machine calibration of NASA's MK40 force balance is used to illustrate the application of the new search algorithm.

Ulbrich, Norbert M.↗
NASA NTRS2018

A Predictive Model for Lake Chad Total Surface Water Area Using Remotely Sensed and Modeled Hydrological and Meteorological Parameters and Multivariate Regression Analysis

Lake Chad is an endorheic lake in the Sahel region of Africa at the southern edge of the Sahara Desert. The lake, which is well known for its dramatic decrease in surface area during the 1970s and 1980s, experiences an annual flood resulting in a maximum total surface water area generally during February or March, though sometimes earlier or later. People along the shores of Lake Chad make their living fishing, farming, and raising livestock and have a vested interest in knowing when and how extensive the annual flooding will be, particularly those practicing recession farming in which the fertile ground of previously flooded area is used for planting crops. In this study, the authors investigate the relationship between lake and basin parameters, including rainfall, basin evapotranspiration, lake evapotranspiration, lake elevation, total surface water area, and the previous year’s total surface water area, and develop equations for each dry season month (except November) linking total surface water area to the other parameters. The resulting equations allow the user to estimate the December average monthly total surface water area of the lake in late November, and to make the estimates for January to May in early December. Based on the results of a Leave One Out Cross Validation analysis, the equations for lake area are estimated to have an average absolute error ranging from 5.3 percent (for February estimates) to 7.6 percent (for May estimates).

Lake Chad↗