Search NASA⌕ Search

SEARCH · Search NASA

Results for “Ranking methods”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38

Improving compliance with Intersocietal Accreditation Commission (IAC) reporting standards: A serial comparison of 523 labs over seven years

Background: The aim of this study was to evaluate reporting compliance of laboratories applying for serial accreditation by the Intersocietal Accreditation Commission (IAC) and compare compliance based on laboratory characteristics. Methods: All laboratories applying for IAC accreditation for the first time in 2008 and then twice more (2011-2014) were evaluated for compliance with 18 reporting elements. The elements were ranked into three severity groups (high/moderate/low). Results: Reports from 523 laboratories were evaluated. The percentage of laboratories with reporting issues by cycle was 66.2% for cycle 1, 36.7% for cycle 2, and 43.8% for cycle 3 (p < .001). For most of the 18 elements, there was a significant decrease in the percentage of labs with issues. Less moderate and high severity errors were seen over time. Also, the mean non-compliant elements per laboratory decreased from 5.78 ± 2.72 at cycle 1, down to 1.25 ± 1.77 at cycle 3. Conclusions: In facilities applying for 3 consecutive IAC accreditation cycles, reporting compliance with IAC Standards improved between cycles 1-2 and 1-3. No significant improvement occurred between cycles 2-3. Although the quality of reports improved overall, problems remain in quantifying myocardial perfusion defects, documenting report approval date, and integrating stress and imaging reports.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Assessment of beating parameters in human induced pluripotent stem cells enables quantitative in vitro screening for cardiotoxicity

Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes show promise for screening during early drug development. Here, we tested a hypothesis that in vitro assessment of multiple cardiomyocyte physiological parameters enables predictive and mechanistically-interpretable evaluation of cardiotoxicity in a high-throughput format. Human iPSC-derived cardiomyocytes were exposed for 30 min or 24 h to 131 drugs, positive (107) and negative (24) for in vivo cardiotoxicity, in up to 6 concentrations (3 nM to 30 uM) in 384-well plates. Fast kinetic imaging was used to monitor changes in cardiomyocyte function using intracellular Ca{sup 2+} flux readouts synchronous with beating, and cell viability. A number of physiological parameters of cardiomyocyte beating, such as beat rate, peak shape (amplitude, width, raise, decay, etc.) and regularity were collected using automated data analysis. Concentration–response profiles were evaluated using logistic modeling to derive a benchmark concentration (BMC) point-of-departure value, based on one standard deviation departure from the estimated baseline in vehicle (0.3% dimethyl sulfoxide)-treated cells. BMC values were used for cardiotoxicity classification and ranking of compounds. Beat rate and several peak shape parameters were found to be good predictors, while cell viability had poor classification accuracy. In addition, we applied the Toxicological Prioritization Index (ToxPi) approach to integrate and display data across many collected parameters, to derive “cardiosafety” ranking of tested compounds. Multi-parameter screening of beating profiles allows for cardiotoxicity risk assessment and identification of specific patterns defining mechanism-specific effects. These data and analysis methods may be used widely for compound screening and early safety evaluation in drug development. - Highlights: • Induced pluripotent stem cell-derived cardiomyocytes are promising in vitro models. • We tested if evaluation of cardiotoxicity is possible in a high-throughput format. • The assay shows benefits of automated data integration across multiple parameters. • Quantitative assessment of concentration–response is possible using iPSCs. • Multi-parametric screening allows for cardiotoxicity risk assessment.

60 APPLIED LIFE SCIENCES↗

Velocity dispersions and dynamical masses for a large sample of quiescent galaxies at z >1: Improved measures of the growth in mass and size

We present Keck LRIS spectroscopy for a sample of 103 massive (M > 10{sup 10.6} M {sub ☉}) galaxies with redshifts 0.9 < z < 1.6. Of these, 56 are quiescent with high signal-to-noise absorption line spectra, enabling us to determine robust stellar velocity dispersions for the largest sample yet available beyond a redshift of 1. Together with effective radii measured from deep Hubble Space Telescope images, we calculate dynamical masses and address key questions relating to the puzzling size growth claimed by many observers for quiescent galaxies over the redshift interval 0 < z < 2. Our large sample provides the first opportunity to carefully examine the relationship between stellar and dynamical masses at high redshift. We find this relation closely follows that determined locally. We also confirm the utility of the locally established empirical calibration which enables high-redshift velocity dispersions to be estimated photometrically, and we determine its accuracy to be 35%. To address recent suggestions that progenitor bias—the continued arrival of recently quenched larger galaxies—can largely explain the size evolution of quiescent galaxies, we examine the growth at fixed velocity dispersion assuming this quantity is largely unaffected by the merger history. Using the velocity dispersion-age relation observed in the local universe, we demonstrate that significant size and mass growth have clearly occurred in individual systems. Parameterizing the relation between mass and size growth over 0 < z < 1.6 as R∝M {sup α}, we find α = 1.6 ± 0.3, in agreement with theoretical expectations from simulations of minor mergers. Relaxing the assumption that the velocity dispersion is unchanging, we examine growth assuming a constant ranking in galaxy velocity dispersion. This approach is applicable only to the large-dispersion tail of the distribution, but yields a consistent growth rate of α = 1.4 ± 0.2. Both methods confirm that progenitor bias alone is insufficient to explain our new observations and that quiescent galaxies have grown in both size and stellar mass over 0 < z < 1.6.

79 ASTRONOMY AND ASTROPHYSICS↗

Artificial Intelligence Benchmarking

AI benchmarking is a method for evaluating the effectiveness of an AI model using a set of standardized metrics, for example, high school-level math exams. These benchmarks and their results will enable ranking various AI models based on their effectiveness in performing a specific task.

Krishnan, Anjay [Fermilab]↗

Scaling laws for light-weight optics

Scaling laws for light-weight optical systems are examined. A cubic relationship between mirror diameter and weight has been suggested and used by many designers of optical systems as the best description for all light-weight mirrors. A survey of existing light-weight systems in the open literature has been made to clarify this issue. Fifty existing optical systems were surveyed with all varieties of light-weight mirrors including glass and beryllium structured mirrors, contoured mirrors, and very thin solid mirrors. These mirrors were then categorized and weight to diameter ratio was plotted to find a best fit curve for each case. A best fitting curve program tests nineteen different equations and ranks a 'goodness of fit' for each of these equations. The resulting relationship found for each light-weight mirror category helps to quantify light-weight optical systems and methods of fabrication and provides comparisons between mirror types.

Valente, Tina M.↗

System Safety Hazards Assessment in Conceptual Program Trade Studies

Providing a program in the concept development phase with a method of determining system safety benefits of potential concepts has always been a challenge. Lockheed Martin Space and Strategic Missiles has developed a methodology for developing a relative system safety ranking using the potential hazards of each concept. The resulting output supports program decisions with system safety as an evaluation criterion with supporting data for evaluation. This approach begins with a generic hazards list that has been tailored for the program being studied and augmented with an initial hazard analysis. Each proposed concept is assessed against the list of program hazards and ranked in three derived areas. The hazards can be weighted to show those that are of more concern to the program. Sensitivities can be also be determined to test the robustness of the conclusions

Eben, Dennis M.↗

Control of Risks Through the Use of Procedures: A Method for Evaluating the Change in Risk

This paper considers how procedures can be used to control risks faced by an organization and proposes a means of recognizing if a particular procedure reduces risk or contributes to the organization's exposure. The proposed method was developed out of the review of work documents and the governing procedures performed in the wake of the Columbia accident by NASA and the Space Shuttle prime contractor, United Space Alliance, LLC. A technique was needed to understand the rules, or procedural controls, in place at the time in the context of how important the role of each rule was. The proposed method assesses procedural risks, the residual risk associated with a hazard after a procedure's influence is accounted for, by considering each clause of a procedure as a unique procedural control that may be beneficial or harmful. For procedural risks with consequences severe enough to threaten the survival of the organization, the method measures the characteristics of each risk on a scale that is an alternative to the traditional consequence/likelihood couple. The dual benefits of the substitute scales are that they eliminate both the need to quantify a relationship between different consequence types and the need for the extensive history a probabilistic risk assessment would require. Control Value is used as an analog for the consequence, where the value of a rule is based on how well the control reduces the severity of the consequence when operating successfully. This value is composed of two parts: the inevitability of the consequence in the absence of the control, and the opportunity to intervene before the consequence is realized. High value controls will be ones where there is minimal need for intervention but maximum opportunity to actively prevent the outcome. Failure Likelihood is used as the substitute for the conventional likelihood of the outcome. For procedural controls, a failure is considered to be any non-malicious violation of the rule, whether intended or not. The model used for describing the Failure Likelihood considers how well a task was established by evaluating that task on five components. The components selected to define a well established task are: that it be defined, assigned to someone capable, that they be trained appropriately, that the actions be organized to enable proper completion and that some form of independent monitoring be performed. Validation of the method was based on the information provided by a group of experts in Space Shuttle ground processing when they were presented with 5 scenarios that identified a clause from a procedure. For each scenario, they recorded their perception of how important the associated rule was and how likely it was to fail. They then rated the components of Control Value and Failure Likelihood for all the scenarios. The order in which each reviewer ranked the scenarios Control Value and Failure Likelihood was compared to the order in which they ranked the scenarios for each of the associated components; inevitability and opportunity for Control Value and definition, assignment, training, organization and monitoring for Failure Likelihood. This order comparison showed how the components contributed to a relative relationship to the substitute risk element. With the relationship established for Space Shuttle ground processing, this method can be used to gauge if the introduction or removal of a particular rule will increase or decrease the .risk associated with the hazard it is intended to control.

Praino, Gregory T.↗

6D large charge and 2D Virasoro blocks

We compute observables in the interacting rank-one 6D 𝒩 =(2,0) superconformal field theory (SCFT) at large 𝑅-charge. We focus on correlators involving Φ 𝑛 , namely symmetric products of the bottom component of the supermultiplet containing the stress tensor. By using the moduli space effective action and methods from the large-charge expansion, we compute the operator product expansion coefficients ⟨Φ 𝑛 ⁢Φ 𝑚 ⁢Φ 𝑛+𝑚 ⟩ in an expansion in 1/𝑛. The coefficients of the expansion are only partially determined from the 6D perspective, but we manage to fix them order-by-order in 1/𝑛 numerically by utilizing the 6⁢D/2⁢D correspondence. This is made possible by the fact that this 6D observable can be extracted in 2D from a specific double-scaling limit of the vacuum Virasoro block, which can be efficiently computed numerically. We also extend the computation to higher-rank SCFTs, and discuss various applications of our results to 6D as well as 2D.

classical solutions in field theory↗

Design and analysis issues of integrated control systems for high-speed civil transports

A study was conducted to identify, rank, and define development plans for the critical guidance and control design and analysis issues as related to economically viable and environmentally acceptable high-speed civil transport. The issues were identified in a multistep process. First, pertinent literature on supersonic cruise aircraft was reviewed, and experts were consulted to establish the fundamental characteristics and problems inherent to supersonic cruise aircraft. Next, the advanced technologies and strategies being pursued for the high-speed civil transport were considered to determine any additional unique control problems the transport may have. Finally, existing technologies and methods were examined to determine their capabilities for the design and analysis of high-speed civil transport control systems and to identify the shortcomings and issues. Three priority levels - mandatory, highly beneficial, and desirable - were established. Within each of these levels, the issues were further ranked. Technology development plans for each issue were defined. Each plan contains a task breakdown and schedule.

Mccarty, Craig A.↗

Exploration of a Potential Desirability of Outcome Ranking Endpoint for Complicated Intra-Abdominal Infections Using 9 Registrational Trials for Antibacterial Drugs

Abstract Background Desirability of outcome ranking (DOOR) is a novel approach to clinical trial design that incorporates safety and efficacy assessments into an ordinal ranking system to evaluate overall outcomes of clinical trial participants. Here, we derived and applied a disease-specific DOOR endpoint to registrational trials for complicated intra-abdominal infection (cIAI). Methods Initially, we applied an a priori DOOR prototype to electronic patient-level data from 9 phase 3 noninferiority trials for cIAI submitted to the US Food and Drug Administration between 2005 and 2019. We derived a cIAI-specific DOOR endpoint based on clinically meaningful events that trial participants experienced. Next, we applied the cIAI-specific DOOR endpoint to the same datasets and, for each trial, estimated the probability that a participant assigned to the study treatment would have a more desirable DOOR or component outcome than if assigned to the comparator. Results Three key findings informed the cIAI-specific DOOR endpoint: (1) a significant proportion of participants underwent additional surgical procedures related to their baseline infection; (2) infectious complications of cIAI were diverse; and (3) participants with worse outcomes experienced more infectious complications, more serious adverse events, and underwent more procedures. DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 47.4% to 50.3% and were not significantly different. Component analyses depicted risk-benefit assessments of study treatment versus comparator. Conclusions We designed and evaluated a potential DOOR endpoint for cIAI trials to further characterize overall clinical experiences of participants. Similar data-driven approaches can be utilized to create other infectious disease–specific DOOR endpoints.

Immunology↗

Evaluation of soft rubber goods

The performance of rubber goods suitable for use as O-rings, seals, gaskets, bladders and diaphragms under conditions simulating those of the space shuttle were studied. High reliability throughout the 100 flight missions planned for the space shuttle was considered of overriding importance. Accordingly, in addition to a rank ordering of the selected candidate materials based on prolonged fluid compatibility and sealability behavior, basic rheological parameters (such as cyclic hysteresis, stress relaxation, indicated modulus, etc.) were determined to develop methods capable of predicting the cumulative effect of these multiple reuse cycles.

Merz, P. L.↗

Statistical methods for astronomical data with upper limits. II - Correlation and regression

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

Isobe, T.↗

Scaling laws for light weight optics, studies of light weight mirrors mounting and dynamic mirror stress, and light weight mirror and mount designs

Scaling laws for light-weight optical systems are examined. A cubic relationship between mirror diameter and weight has been suggested and used by many designers of optical systems as the best description for all light-weight mirrors. A survey of existing light-weight systems in the open literature was made to clarify this issue. Fifty existing optical systems were surveyed with all varieties of light-weight mirrors including glass and beryllium structured mirrors, contoured mirrors, and very thin solid mirrors. These mirrors were then categorized and weight to diameter ratio was plotted to find a best curve for each case. A best fitting curve program tests nineteen different equations and ranks a goodness-to-fit for each of these equations. The resulting relationship found for each light-weight mirror category helps to quantify light-weight optical systems and methods of fabrication and provides comparisons between mirror types.

Vukobratovich, Daniel↗

Application of regression, variance, and density based global sensitivity methods to integrated VERA-CS and BISON simulations [Application of regression, variance, and density based global sensitivity methods to integrated VERA-CS and BISON simulations]

Uncertainty quantification (UQ) and sensitivity analyses (SA) are performed for coupled simulations between VERA-CS, a coupled pin resolved neutron transport and subchannel thermal hydraulics code, and the fuel performance code BISON. The interface between VERA-CS and BISON is performed in a multiphysics environment known as the LOCA Toolkit for U.S. light water reactors (LOTUS) currently under development at Idaho National Laboratory (INL). A focus is placed on using a variety of SA measures, including two regression based (Pearson and Spearman), one variance based (Sobol indices), and three moment independent measures (Delta moment independent measures with L 1 , L 2 , and L ∞ norms). The problem under inspection is a single assembly depletion case for three fuel cycles. The figures of merit are the minimum departure from nucleate boiling ratio (MDNBR), maximum fuel centerline temperature (MFCT), and gap conductance at peak power (GCPP). SA results show MDNBR to be linear with consistent rankings throughout the fuel cycles. MFCT is linear, but with a change in rankings at the switch from open gap to closed gap models. GCPP is nonlinear at intermediate states that coincide with the onset of contact between fuel and cladding. Furthermore, these nonlinear states allow for the showcasing of higher order SA measures over first order methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15

Abstract Estimating the accuracy of quaternary structural models of protein complexes and assemblies (EMA) is important for predicting quaternary structures and applying them to studying protein function and interaction. The pairwise similarity between structural models is proven useful for estimating the quality of protein tertiary structural models, but it has been rarely applied to predicting the quality of quaternary structural models. Moreover, the pairwise similarity approach often fails when many structural models are of low quality and similar to each other. To address the gap, we developed a hybrid method (MULTICOM_qa) combining a pairwise similarity score (PSS) and an interface contact probability score (ICPS) based on the deep learning inter‐chain contact prediction for estimating protein complex model accuracy. It blindly participated in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 and performed very well in estimating the global structure accuracy of assembly models. The average per‐target correlation coefficient between the model quality scores predicted by MULTICOM_qa and the true quality scores of the models of CASP15 assembly targets is 0.66. The average per‐target ranking loss in using the predicted quality scores to rank the models is 0.14. It was able to select good models for most targets. Moreover, several key factors (i.e., target difficulty, model sampling difficulty, skewness of model quality, and similarity between good/bad models) for EMA are identified and analyzed. The results demonstrate that combining the multi‐model method (PSS) with the complementary single‐model method (ICPS) is a promising approach to EMA.

59 BASIC BIOLOGICAL SCIENCES↗

Space-Time Finite Element Tensor Network Approach for the Time-Dependent Convection–Diffusion–Reaction Equation with Variable Coefficients

In this paper, we present a new space-time Galerkin-like method, where we treat the discretization of spatial and temporal domains simultaneously. This method utilizes a mixed formulation of the tensor-train (TT) and quantized tensor-train (QTT) (please see Section Tensor-Train Decomposition), designed for the finite element discretization (Q1-FEM) of the time-dependent convection–diffusion–reaction (CDR) equation. We reformulate the assembly process of the finite element discretized CDR to enhance its compatibility with tensor operations and introduce a low-rank tensor structure for the finite element operators. Recognizing the banded structure inherent in the finite element framework’s discrete operators, we further exploit the QTT format of the CDR to achieve greater speed and compression. Additionally, we present a comprehensive approach for integrating variable coefficients of CDR into the global discrete operators within the TT/QTT framework. The effectiveness of the proposed method, in terms of memory efficiency and computational complexity, is demonstrated through a series of numerical experiments, including a semi-linear example.

convection–diffusion–reaction equation↗

A compute-bound formulation of Galerkin model reduction for linear time-invariant dynamical systems

This work aims to advance computational methods for projection-based reduced-order models (ROMs) of linear time-invariant (LTI) dynamical systems. For such systems, current practice relies on ROM formulations expressing the state as a rank-1 tensor (i.e., a vector), leading to computational kernels that are memory bandwidth bound and, therefore, ill-suited for scalable performance on modern architectures. This weakness can be particularly limiting when tackling many-query studies, where one needs to run a large number of simulations. This work introduces a reformulation, called rank-2 Galerkin, of the Galerkin ROM for LTI dynamical systems which converts the nature of the ROM problem from memory bandwidth to compute bound. We present the details of the formulation and its implementation, and demonstrate its utility through numerical experiments using, as a test case, the simulation of elastic seismic shear waves in an axisymmetric domain. We quantify and analyze performance and scaling results for varying numbers of threads and problem sizes. In conclusion, we present an end-to-end demonstration of using the rank-2 Galerkin ROM for a Monte Carlo sampling study. We show that the rank-2 Galerkin ROM is one order of magnitude more efficient than the rank-1 Galerkin ROM (the current practice) and about 970 times more efficient than the full-order model, while maintaining accuracy in both the mean and statistics of the field.

97 MATHEMATICS AND COMPUTING↗

Machine learning predicts new anti-CRISPR proteins

The increasing use of CRISPR–Cas9 in medicine, agriculture, and synthetic biology has accelerated the drive to discover new CRISPR–Cas inhibitors as potential mechanisms of control for gene editing applications. Many anti-CRISPRs have been found that inhibit the CRISPR–Cas adaptive immune system. However, comparing all currently known anti-CRISPRs does not reveal a shared set of properties for facile bioinformatic identification of new anti-CRISPR families. Here, we describe AcRanker, a machine learning based method to aid direct identification of new potential anti-CRISPRs using only protein sequence information. Using a training set of known anti-CRISPRs, we built a model based on XGBoost ranking. We then applied AcRanker to predict candidate anti-CRISPRs from predicted prophage regions within self-targeting bacterial genomes and discovered two previously unknown anti-CRISPRs: AcrllA20 (ML1) and AcrIIA21 (ML8). We show that AcrIIA20 strongly inhibits Streptococcus iniae Cas9 (SinCas9) and weakly inhibits Streptococcus pyogenes Cas9 (SpyCas9). We also show that AcrIIA21 inhibits SpyCas9, Streptococcus aureus Cas9 (SauCas9) and SinCas9 with low potency. The addition of AcRanker to the anti-CRISPR discovery toolkit allows researchers to directly rank potential anti-CRISPR candidate genes for increased speed in testing and validation of new anti-CRISPRs. A web server implementation for AcRanker is available online at http://acranker.pythonanywhere.com/.

59 BASIC BIOLOGICAL SCIENCES↗