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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Solar array electrical performance assessment for Space Station Freedom

Electrical power for Space Station Freedom will be generated by large photovoltaic arrays with a beginning of life power requirement of 30.8 kW per array. The solar arrays will operate in a Low Earth Orbit (LEO) over a design life of fifteen years. This paper provides an analysis of the predicted solar array electrical performance over the design life and presents a summary of supporting analysis and test data for the assigned model parameters and performance loss factors. Each model parameter and loss factor is assessed based upon program requirements, component analysis and test data to date. A description of the LMSC performance model future test plans and predicted performance ranges are also given.

Smith, Bryan K.↗
NASA NTRS2021

Going Beyond Hooked Participants: The Nibble- and-Drop Framework for Classifying Citizen Science Participation

Many citizen science (CS) programs aim to grow and sustain a pool of enthusiastic participants who consistently contribute their efforts to a specific scientific endeavor. Consequently, much research has explored CS participants’ motivations and their relationship to participant recruitment and retention. However, much of this research has focused on actively participating citizen scientists. If researchers want to elucidate the relationship between participant factors (such as demographics and motivations) and participant retention, it is necessary to develop a more comprehensive picture of the different degrees of participation in CS. This paper presents a framework for classifying participation throughout the participant’s engagement in a CS project/program. We suggest a CS participation model that captures the dynamic nature of participation across an arc of volunteering. Called the Nibble-and-Drop Framework, the model describes multiple exit points and stages of contribution typical of participation in a CS program. Applying the framework to the NASA GLOBE Observer (GO) CS program, we found that it captured the dynamics of participation in a global-scale, mobile, app-based, contributory style CS project. The framework guided our analysis of how different participant factors correlate with degrees of participation. We found that participants were motivated to initially participate because they wanted to contribute to NASA research and science. Participants who dropped out of the program at various points often initially engaged through specific collection events and did not feel the need to continue contributing beyond the event; other drop-outs doubted whether their contributions were meaningful, showing again the need to ensure that participants understand the value of their engagement in a CS project.

Heather Fischer↗
DOE OSTI2021

A Comparative Techno-Economic Analysis of Renewable Methanol Synthesis Pathways from Biomass and CO2: Preprint

Global demand for methanol as both a chemical precursor and a fuel additive is rising. At the same time, numerous sustainable methanol production pathways are under development which, if commercialized, could present significant environmental benefits over traditional methanol synthesis pathways. There is a need to harmonize the analyses of sustainable pathways using a consistent techno-economic approach to evaluate the potential for commercialization of various pathways. This analysis considers economic and environmental factors critical to market acceptance of three sustainable pathways versus a commercial baseline. We suggest that biomass gasification to methanol represents a near-term viable pathway with high technology readiness level and commercially competitive market price. However, long-term solutions should consider CO2 electrolysis pathways which offer further improvements in sustainability metrics to support global decarbonization efforts.

biomass↗
DOE OSTI2017

Impact of cardiac reverse remodeling after cardiac resynchronization therapy assessed by myocardial perfusion imaging on ventricular arrhythmia

Background: Although cardiac resynchronization therapy (CRT) has been a useful treatment of heart failure, patients with CRT are still in risk of sudden cardiac death due to ventricular arrhythmia. The aim of this study was to investigate the impact of cardiac reverse remodeling after CRT on the prevalence of ventricular tachycardia or fibrillation (VT/VF). Methods and Results: Forty-one heart failure patients (26 men, age 66 ± 10 years), who were implanted with CRT for at least 12 months, were enrolled. All patients received myocardial perfusion imaging (MPI) under CRT pacing to evaluate left ventricle (LV) function, dyssynchrony, and scar. VT/VF episodes during the follow-up period after MPI were recorded by the CRT devices. Sixteen patients (N = 16/41, 39%) were found to have VT/VF. Multivariate Cox regression analysis and receiver operating characteristic curve analysis showed that five risk factors were significant predictors of VT/VF, including increased left ventricle ejection fraction (LVEF) by ≤7% after CRT, low LVEF after CRT (≤30%), change of intrinsic QRS duration (iQRSd) by ≤7 ms, wide iQRSd after CRT (≥121 ms), and high systolic dyssynchrony after CRT (phase standard deviation ≥45.6°). For those patients with all of the 5 risk factors, 85.7% or more developed VT/VF. Conclusions: The characteristics of cardiac reverse remodeling after CRT as assessed by MPI are associated with the prevalence of ventricular arrhythmia.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

A Global Data Analysis for Representing Sediment and Particulate Organic Carbon Yield in Earth System Models

Although sediment yield (SY) from water erosion is ubiquitous and its environmental consequences are well recognized, its impacts on the global carbon cycle remain largely uncertain. This knowledge gap is partly due to the lack of soil erosion modeling in Earth System Models (ESMs), which are important tools used to understand the global carbon cycle and explore its changes. As such, this study analyzed sediment and particulate organic carbon yield (CY) data from 1081 and 38 small catchments (0.1-200 km 2 ), respectively, in different environments across the globe. Using multiple statistical analysis techniques, we explored environmental factors and hydrological processes important for SY and CY modeling in ESMs. Our results show clear correlations of high SY with traditional agriculture, seismicity and heavy storms, as well as strong correlations between SY and annual peak runoff. These highlight the potential limitation of SY models that represent only interrill and rill erosion because shallow overland flow and rill flow have limited transport capacity due to their hydraulic geometry to produce high SY. Further, our results suggest that SY modeling in ESMs should be implemented at the event scale to produce the catastrophic mass transport during episodic events. Several environmental factors such as seismicity and land management that are often not considered in current catchment-scale SY models can be important in controlling global SY. Our analyses show that SY is likely the primary control on CY in small catchments and a statistically significant empirical relationship is established to calculate SY and CY jointly in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Platform for efficient large-scale storage and analysis of multi-omics data in plant and microbial systems (Final Technical Report)

Genomic variation at the sequence level fundamentally affects the phenotypic state of all organisms at all stages of development, while dynamic processes such as changes in the epigenome (e.g. DNA methylation state) and transcriptome regulate the specific phenotype expressed at any given state of development based upon that genomic variation. In plants, DNA methylation is a particularly important mechanism for both regulating transcriptomic expression and for management of genomic variations that could be deleterious to the organism due to the presence of active retrotransposons in plant genomes. While DNA methylation is heritable, it is also dynamic through a given plant’s development and life cycle, particularly during the development from seed to mature specimen suggesting variations in DNA methylation could be critical regulators of biologically and commercially important phenotypes such as time to flowering; in addition, plant DNA methylation is more complex than that of animals, with methylation of CHG and CHH trinucleotides evident in addition to the better-known CG methylation. The complexity of plant DNA methylation and its interplay with genomic sequence variation, transcriptomics and other epigenomic factors demand a storage and analysis framework that can cope with the complexity both within a single specimen and with analyses that span many individuals and even many species, such as attempts to extend models from model organisms to commercially relevant species. In addition to complexity, the rapid development and proliferation of sequencing technology has led to an explosion of data volume that conventional storage and analysis solutions will likely be unable to cope with in the long run. We proposed to study these with suitable distributed storage and computation and therefore for the application of cloud computing to biological analyses; integrate with existing data sources and compatible with virtually any interface use case, from fully automated shell scripts to notebooks and do all these at scale in this STTR grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Uncertainty Quantification Analysis of Both Experimental and CFD Simulation Data of a Bench-scale Fluidized Bed Gasifier

Adequate assessment of the uncertainties in modeling and simulation is becoming an integral part of the simulation based engineering design. The goal of this study is to demonstrate the application of non-intrusive Bayesian uncertainty quantification (UQ) methodology in multiphase (gas-solid) flows with experimental and simulation data, as part of our research efforts to determine the most suited approach for UQ of a bench scale fluidized bed gasifier. UQ analysis was first performed on the available experimental data. Global sensitivity analysis performed as part of the UQ analysis shows that among the three operating factors, steam to oxygen ratio has the most influence on syngas composition in the bench-scale gasifier experiments. An analysis for forward propagation of uncertainties was performed and results show that an increase in steam to oxygen ratio leads to an increase in H2 mole fraction and a decrease in CO mole fraction. These findings are in agreement with the ANOVA analysis performed in the reference experimental study. Another contribution in addition to the UQ analysis is the optimization-based approach to guide to identify next best set of additional experimental samples, should the possibility arise for additional experiments. Hence, the surrogate models constructed as part of the UQ analysis is employed to improve the information gain and make incremental recommendation, should the possibility to add more experiments arise. In the second step, series of simulations were carried out with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was performed on the numerical results. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbon monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier. To improve quality of numerical models used, the effect that uncertainties in reaction models for gasification, char oxidation, carbon monoxide oxidation, and water gas shift will have on the syngas composition at different grid resolution, along with bed temperature were investigated. The global sensitivity analysis showed that among various reaction models employed for water gas shift, gasification, char oxidation, the choice of reaction model for water gas shift has the greatest influence on syngas composition, with gasification reaction model being second. Syngas composition also shows a small sensitivity to temperature of the bed. The hydrodynamic behavior of the bed did not change beyond grid spacing of 18 times the particle diameter. However, the syngas concentration continued to be affected by the grid resolution as low as 9 times the particle diameter. This is due to a better resolution of the phasic interface between the gases and solid that leads to stronger heterogeneous reactions. This report is a compilation of three manuscripts published in peer-reviewed journals for the series of studies mentioned above.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Assessing the predictive impact of factor fixing with an adaptive uncertainty-based approach .

Despite widespread use of factor fixing in environmental modeling, its effect on model predictions has received little attention and is instead commonly presumed to be negligible. We propose a proof-of-concept adaptive method for systematically investigating the impact of factor fixing. The method uses Global Sensitivity Analysis methods to identify groups of sensitive parameters, then quantifies which groups can be safely fixed at nominal values without exceeding a maximum acceptable error, demonstrated using the 21-dimensional Sobol’ G-function. Furthermore, three error measures are considered for quantities of interest, namely Relative Mean Absolute Error, Pearson Product-Moment Correlation and Relative Variance. Results demonstrate that factor fixing may cause large errors in the model results unexpectedly, when preliminary analysis suggests otherwise, and that the default value selected affects the number of factors to fix. To improve the applicability and methodological development of factor fixing, a new research agenda encompassing five opportunities is discussed for further attention.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Study leading to the refinement of the SRB structural analysis program

The constructed SRB math model was used for the analysis of the 85/32/5(VV/VH/theta) cavity collapse load condition for the aft end of the SRB structure. Linear, nonlinear collapse and bifurcation buckling analyses were performed. The linear and bifurcation buckling analyses showed that structural integrity and positive margins of safety are maintained for the applied maximum load case using a design factor of 1.25. The nonlinear collapse analysis predicts stresses in the skirt above the yield for a load factor of 1.0. Applying the 1.25 design factor gives a negative margin of safety against the material ultimate. The predicted collapse occurs at a load factor higher than 1.25.

Jones, W. E.↗
DOE OSTI2023

BSM Sensitivity Analysis and Meta-Modeling Next Steps [Slides]

We performed a global sensitivity analysis of the Bioenergy Scenario Model (BSM), using Elementary Effects analysis to identify potentially influential factors, with a focus on sustainable aviation fuel (SAF) production. The process was iterative and informed key model changes and updates over the course of the study in addition to identifying the key model inputs that affect the cumulative production of SAF from the present through 2050. More work will be performed to gain deeper insight into the sensitivity of individual pathways as part of our larger efforts to develop a reduced-form version of the BSM.

09 BIOMASS FUELS↗
DOE OSTI2015

Rates of Reconstruction Failure in Patients Undergoing Immediate Reconstruction With Tissue Expanders and/or Implants and Postmastectomy Radiation Therapy

Objectives: Mastectomy rates for breast cancer have increased, with a parallel increase in immediate reconstruction. For some women, tissue expander and implant (TE/I) reconstruction is the preferred or sole option. This retrospective study examined the rate of TE/I reconstruction failure (ie, removal of the TE or I with the inability to replace it resulting in no final reconstruction or autologous tissue reconstruction) in patients receiving postmastectomy radiation therapy (PMRT). Methods and Materials: Between 2004 and 2012, 99 women had skin-sparing mastectomies (SSM) or total nipple/areolar skin-sparing mastectomies (TSSM) with immediate TE/I reconstruction and PMRT for pathologic stage II to III breast cancer. Ninety-seven percent had chemotherapy (doxorubicin and taxane-based), 22% underwent targeted therapies, and 78% had endocrine therapy. Radiation consisted of 5000 cGy given in 180 to 200 cGy to the reconstructed breast with or without treatment to the supraclavicular nodes. Median follow-up was 3.8 years. Results: Total TE/I failure was 18% (12% without final reconstruction, 6% converted to autologous reconstruction). In univariate analysis, the strongest predictor of reconstruction failure (RF) was absence of total TE/I coverage (acellular dermal matrix and/or serratus muscle) at the time of radiation. RF occurred in 32.5% of patients without total coverage compared to 9% with coverage (P=.0069). For women with total coverage, the location of the mastectomy scar in the inframammary fold region was associated with higher RF (19% vs 0%, P=.0189). In multivariate analysis, weight was a significant factor for RF, with lower weight associated with a higher RF. Weight appeared to be a surrogate for the interaction of total coverage, thin skin flaps, interval to exchange, and location of the mastectomy scar. Conclusions: RFs in patients receiving PMRT were lowered with total TE/I coverage at the time of radiation by avoiding inframammary fold incisions and with a preferred interval of 6 months to exchange.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction

Abstract Developing prediction models for emerging infectious diseases from relatively small numbers of cases is a critical need for improving pandemic preparedness. Using COVID-19 as an exemplar, we propose a transfer learning methodology for developing predictive models from multi-modal electronic healthcare records by leveraging information from more prevalent diseases with shared clinical characteristics. Our novel hierarchical, multi-modal model ( $${\textsc {TransMED}}$$ T R A N S MED ) integrates baseline risk factors from the natural language processing of clinical notes at admission, time-series measurements of biomarkers obtained from laboratory tests, and discrete diagnostic, procedure and drug codes. We demonstrate the alignment of $${\textsc {TransMED}}$$ T R A N S MED ’s predictions with well-established clinical knowledge about COVID-19 through univariate and multivariate risk factor driven sub-cohort analysis. $${\textsc {TransMED}}$$ T R A N S MED ’s superior performance over state-of-the-art methods shows that leveraging patient data across modalities and transferring prior knowledge from similar disorders is critical for accurate prediction of patient outcomes, and this approach may serve as an important tool in the early response to future pandemics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Nebraska Integrated Carbon Capture and Storage Pre-Feasibility Study

In collaboration with the Nebraska Public Power District (NPPD), the Energy & Environmental Research Center (EERC) has conducted a pre-feasibility study for a commercial-scale carbon dioxide (CO 2 ) geologic storage complex in western Nebraska integrated with potential CO 2 capture at Gerald Gentleman Station (GGS). GGS is the largest coal-fired electricity-generating station in Nebraska, emitting 8.5 million metric tons (Mt) of CO 2 annually, and is located near the town of Sutherland. This pre-feasibility (Phase 1) project has been executed as part of the U.S. Department of Energy (DOE) CarbonSAFE program, a multiphase initiative to support the deployment of large-scale carbon capture and storage (CCS) projects. Each CarbonSAFE project is required to demonstrate the potential to capture and store at least 50 million tonnes (Mt) of CO 2 over a 25-year operational period. The EERC and NPPD established a coordination team to identify challenges to a potential Nebraska CCS project, comprising local stakeholder organizations, which met twice in Lincoln and via several Webinars, providing feedback and guidance throughout the pre-feasibility study. The EERC also secured the technical support of Schlumberger Carbon Services and Computer Modelling Group Ltd. (CMG). The project comprised four technical themes, all using published information sources. Regional and stakeholder analysis, including identification of sensitive environmental areas, potential resource conflicts, and strategies for public outreach. A review of geographic and socioeconomic characteristics, in combination with geologic characterization in the subbasinal analysis described below, identified an area to the southwest and within a 75-mile radius of GGS as the most prospective for development of a storage site. This area largely avoided lands with protected status such as wetlands. A public outreach plan has also been developed for implementation in any further phases of CCS assessment in western Nebraska, for example a CarbonSAFE Phase 2 feasibility study. Scenario analysis, addressing economic and regulatory factors. GGS is the only single major source of CO 2 emissions capable of satisfying the CarbonSAFE 50-Mt scale requirement within the study region. Chemical absorption using amines was identified as the most viable technology for postcombustion CO 2 capture at GGS. The total cost of a CCS project at GGS was estimated to be between $67/tonne CO 2 for capture and auxiliary boiler to minimize parasitic load and $70/tonne CO 2 avoided cost, using the Carnegie-Mellon University Integrated Environmental Control Model (IECM). The total avoided cost included the capture facility and parasitic load, a flue gas desulfurization plant required for the use of amine solvent technology, transport via pipeline, and dedicated storage infrastructure. Nebraska has no legislation in place to address typical CCS-specific issues, for example pore space ownership for storage. Long-term liability, therefore, falls under the U.S. Environmental Protection Agency Underground Injection Control (UIC) Class 6 program regulations. Subbasinal analysis, addressing the potential for a dedicated subsurface “container” to store the required 50-Mt quantity of CO 2 . Modeling and simulation studies identified an area to the southwest of GGS with the potential for storage of 50 Mt CO 2 in the Cloverly Formation, comprising sandstones with interbedded and intermingled shales. The area of review (AOR) that would be required for monitoring under a Class VI operating permit was estimated to be as high as 400–700 square miles, due to uncertain pressure effects. The viability of this storage option is subject to significant uncertainty due to the relatively limited amount of existing characterization data available to the pre-feasibility study; for example, dynamic simulation indicated that the proposed storage rate might require as little as two or as many as 14 injection wells. A key uncertainty is the relative proportion and distribution of sandstone and shale within the Cloverly Formation. A preliminary, semiquantitative risk assessment also suggested uncertainty over storage capacity and injectivity constitute the most significant project risks at this pre-feasibility stage. No assessed risks were considered to rule out the possibility of a project moving to deployment. National Risk Assessment Partnership (NRAP) validation, using software tools developed by the National Energy Technology Laboratory (NETL) to assess risks associated with the potential 50-Mt CO 2 storage complex. NRAP tools were used to assess hypothetical leakage scenarios. Results broadly supported the conclusion of the semiquantitative risk analysis – for example, even worst-case analysis of theoretical leakage scenarios found limited migration rates and impacts. In summary, the work undertaken in this Phase 1 pre-feasibility study has shown that western Nebraska has potential to host a commercial-scale CCS project, including a dedicated storage “container” for 50 Mt of CO 2 . However, the following key challenges would need to be overcome: The business case for deploying CCS projects is uncertain; recently announced federal tax credits and sales of CO 2 for enhanced oil recovery may not cover the full costs of a CCS project at GGS, as estimated by this pre-feasibility study. The potential 50-Mt CO 2 dedicated storage container defined in this pre-feasibility study should be regarded as having a relatively low level of readiness to support a CCS project. Public outreach would be a vital element in western Nebraska, where sensitivities around such environmental issues as water resource protection and pipeline construction would need to be carefully addressed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Outcomes in patients ≥ 80 years with a diagnosis of a hepatopancreaticobiliary (HPB) malignancy

Older patients are underrepresented in oncological clinical trials. The incidence of hepatopancreaticobiliary (HPB) malignancies is higher in older patients, but data on outcomes are lacking. This study assessed patient outcomes in those < 80 and ≥ 80 years with a HPB malignancy seen at a tertiary referral centre, The Christie NHS Foundation Trust. Data on patients with a HPB malignancy were collected retrospectively between 2012 and 2017 via on-line case-note review. Survival was calculated using the Kaplan–Meier method and prognostic factors using log-rank analysis. Of 1421 patients, 10% were ≥ 80 years. Of patients < 80 and ≥ 80 years, 56% and 57% had pancreas cancer, 39% and 36% biliary tract cancer, and 5% and 7% had hepatocellular carcinoma, respectively. Amongst patients ≥ 80 years, 75% had an Eastern Cooperative Oncology Group performance status (ECOG PS) 0–2. Patients ≥ 80 years had higher rates of comorbidity; 28% received systemic anti-cancer therapy (SACT), compared with 62% of patients < 80 years. Best supportive care (BSC) was instituted in 44% of older patients, compared with 13% in those < 80 years. Of patients ≥ 80 years who received SACT, 82% received monotherapy. Median overall survival (OS) for patients receiving palliative SACT was 10.07 months (95% CI 8.89–11.08) and 10.10 months (95% CI 6.30–12.30) in patients < 80 and ≥ 80 years, respectively, p 0.41; ECOG PS (p < 0.001) was prognostic for OS in older patients but Adult Comorbidity Evaluation-27 comorbidity score (p = 0.07, when comparing groups of ACE score ≤ 1 and > 1) was not. Baseline factors were similar in both age cohorts, but more comorbidities were present in older patients. Older patients were less likely to receive SACT, but when they did, they had an equivalent benefit in OS to younger patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Porcine bocavirus NP1 negatively regulates interferon signaling pathway by targeting the DNA-binding domain of IRF9

To subvert host antiviral immune responses, many viruses have evolved countermeasures to inhibit IFN signaling pathway. Porcine bocavirus (PBoV), a newly identified porcine parvovirus, has received attention because it shows clinically high co-infection prevalence with other pathogens in post-weaning multisystemic wasting syndrome (PWMS) and diarrheic piglets. In this study, we screened the structural and non-structural proteins encoded by PBoV and found that the non-structural protein NP1 significantly suppressed IFN-stimulated response element (ISRE) activity and subsequent IFN-stimulated gene (ISG) expression. However, NP1 affected neither the activation and translocation of STAT1/STAT2, nor the formation of the heterotrimeric transcription factor complex ISGF3 (STAT1/STAT2/IRF9). Detailed analysis demonstrated that PBoV NP1 blocked the ISGF3 DNA-binding activity by combining with the DNA-binding domain (DBD) of IRF9. In summary, these results indicate that PBoV NP1 interferes with type I IFN signaling pathway by blocking DNA binding of ISGF3 to attenuate innate immune responses. - Highlights: • Porcine bocavirus (PBoV) NP1 interferes with the IFN α/β signaling pathway. • PBoV NP1 does not prevent STAT1/STAT2 phosphorylation and nuclear translocation. • PBoV NP1 inhibits the DNA-binding activity of ISGF3. • PBoV NP1 interacts with the DNA-binding domain of IRF9.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1996

Method of Testing and Predicting Failures of Electronic Mechanical Systems

A method employing a knowledge base of human expertise comprising a reliability model analysis implemented for diagnostic routines is disclosed. The reliability analysis comprises digraph models that determine target events created by hardware failures human actions, and other factors affecting the system operation. The reliability analysis contains a wealth of human expertise information that is used to build automatic diagnostic routines and which provides a knowledge base that can be used to solve other artificial intelligence problems.

Iverson, David L.↗
DOE OSTI2016

Searching for heavy photons in the HPS Experiment

The Heavy Photon Search (HPS) is a new experiment at Jefferson Lab that searches for a massive U(1) vector boson (known as a heavy photon or A') in the MeV-GeV mass range and coupling weakly to ordinary matter through a kinetic mixing interaction. The HPS experiment seeks to produce heavy photons by electron bremsstrahlung on a fixed target, is sensitive to heavy photon decays to e + e - , and targets the range in heavy photon mass m A' ~ 20 - 600 MeV, and kinetic mixing strength epsilon 2 ~ 10 -5 - 10 -10 . HPS searches for heavy photons using two signatures: a narrow mass resonance and displaced vertices. This dissertation presents the theoretical and experimental motivations for a heavy photon, the design and operation of the HPS experiment, and the displaced vertex search. The data used in this dissertation is the unblinded fraction of the 2015 HPS run, for the period of operation where the HPS silicon vertex tracker (SVT) was operated at its nominal position. This data was recorded from May 13 to May 18, 2015, at a beam energy of 1.056 GeV and a nominal beam current of 50 nA. The integrated luminosity is 119 nb -1 , which is equivalent to 0.172 days of ideal running at the nominal beam current. This dissertation presents results (signal significance and upper limits) from the displaced vertex search in the mass range m A' ~ 20 - 60 MeV, and kinetic mixing strength epsilon 2 ~ 2 × 10 -8 - 10 -10 . This search does not have sufficient sensitivity to exclude a canonical heavy photon at any combination of m A' and epsilon 2 . The strictest limit achieved in this analysis on the production of a particle that decays like a heavy photon is 115 times the expected production cross-section for a heavy photon. Factors limiting the sensitivity of this analysis are discussed. Projections of HPS performance with the full 2015 data set, and with planned improvements to the analysis, are presented. Comparisons are also made to earlier reach estimates.

Uemura, Sho↗