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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 37 records · Page 2

Differential localization of cytoplasmic myosin II isoforms A and B in avian interphase and dividing embryonic and immortalized cardiomyocytes and other cell types in vitro

Two principal isoforms of cytoplasmic myosin II, A and B (CMIIA and CMIIB), are present in different proportions in different tissues. Isoform-specific monoclonal and polyclonal antibodies to avian CMIIA and CMIIB reveal the cellular distributions of these isoforms in interphase and dividing embryonic avian cardiac, intestinal epithelial, spleen, and dorsal root ganglia cells in primary cell culture. Embryonic cardiomyocytes react with antibodies to CMIIB but not to CMIIA, localize CMIIB in stress-fiber-like-structures during interphase, and markedly concentrate CMIIB in networks in the cleavage furrow during cytokinesis. In contrast, cardiac fibroblasts localize both CMIIA and CMIIB in stress fibers and networks during interphase, and demonstrate slight and independently regulated concentration of CMIIA and CMIIB in networks in their cleavage furrows. V-myc-immortalized cardiomyocytes, an established cell line, have regained the ability to express CMIIA, as well as CMIIB, and localize both CMIIA and CMIIB in stress fibers and networks in interphase cells and in cleavage furrows in dividing cells. Conversely, some intestinal epithelial, spleen, and dorsal root ganglia interphase cells express only CMIIA, organized primarily in networks. Of these, intestinal epithelial cells express both CMIIA and CMIIB when they divide, whereas some dividing cells from both spleen and dorsal root ganglia express only CMIIA and concentrate it in their cleavage furrows. These results suggest that within a given tissue, different cell types express different isoforms of CMII, and that cells expressing either CMIIA or CMIIB alone, or simultaneously, can form a cleavage furrow and divide.

NASA Discipline Developmental Biology↗

Alterations in skeletal muscle related to impaired physical mobility: an empirical model

The objective of this investigation was to study impaired physical mobility and the resulting skeletal muscle atrophy. An animal model was used to study morphological adaptations of the soleus and plantaris muscles to decreased loading induced by hindlimb suspension of an adult rat for 7, 14, and 28 consecutive days. Alterations in weight, skeletal muscle growth, and changes in fiber type composition were studied in synergistic plantar flexors of the rat hindlimb. Body weight and the soleus muscle mass to body mass ratio demonstrated significant progressive atrophy over th 28-day experimental period with the most significant changes occurring in the first 7 days of hindlimb suspension. Hindlimb suspension produced atrophy of Type I and Type IIa muscle fibers as demonstrated by significant decreases in fiber cross-sectional area (micron 2). These latter changes account for the loss of contractile force production reported in the rat following hindlimb unloading. When compared to traditional models of hindlimb suspension and immobilization, the ISC model produces a less severe atrophy while maintaining animal mobility and health. We conclude that it is the preferred animal model to address nursing questions of impaired physical mobility.

Non-NASA Center↗

Evidence for reduced cancellous bone mass in the spontaneously hypertensive rat

The histomorphometric changes in the proximal tibial metaphysis and epiphyseal growth plate and midtibial shaft of 26-week-old spontaneously hypertensive rats (SHR) compared with those of the corresponding normotensive Wistar-Kyoto (WKY) rats were studied. A decrease in body weight, growth plate thickness, and longitudinal growth rate of the proximal tibial epiphysis, trabecular bone volume, trabecular thickness and number, the number of osteoblasts and osteoprogenitor cells per millimeter square surface of the proximal tibial metaphysis, periosteal and endocortical apposition rate and bone formation rate of the tibial diaphysis were observed in the SHR. Additionally, systolic blood pressure, the number of osteoclasts per millimeter square surface and average number of nuclei per osteoclast of the proximal tibial metaphysis were significantly increased. Thus, osteoclastic activity is dominant over osteoblastic and chondroblastic activity in the SHR that results in a cancellous bone deficit in the skeleton. It will require additional work to ascertain the underlying cause for this condition as several factors in the SHR with a potential for causing this change are present, including elevated parathyroid hormone (PTH), depressed 1,25-(OH)2D3, low calcium absorption, reduced body weight (reduced loading) elevated blood pressure and possibly other direct cell differences in the mutant strain. At present elevated PTH and adaptation to underloading from reduced weight are postulated to be a likely cause, but additional studies are required to test this interpretation.

NASA Discipline Musculoskeletal↗

Subjective response of people to simulated sonic booms in their homes

In order to determine the effect of the number of sonic boom occurrences on annoyance, a computer-based system was developed for studying the subjective response of people to the occurrence of simulated sonic booms in their homes. The system provided a degree of control over the noise exposure not found in community surveys and a degree of situational realism not available in the laboratory. A system was deployed for eight weeks in each of 33 homes. Each day from 4 to 63 sonic booms were played as the test subject went about his or her normal activities. At the end of the day, the test subjects rated their annoyance to the sonic booms heard during the day. The sonic booms consisted of different combinations of waveforms, levels, and occurrence rates. The experiment confirmed that the increase in annoyance resulting from multiple occurrences can be modeled by the addition of the term "10 * log(number of occurrences)" to the sonic boom level. Of several noise metrics considered, perceived level was the best annoyance predictor. Comparisons of the subjective responses to the different sonic boom waveforms found no differences that were not accounted for by the noise metrics.

Noise, Transportation/adverse effects↗

As-built design specification for proportion estimate software subsystem

The Proportion Estimate Processor evaluates four estimation techniques in order to get an improved estimate of the proportion of a scene that is planted in a selected crop. The four techniques to be evaluated were provided by the techniques development section and are: (1) random sampling; (2) proportional allocation, relative count estimate; (3) proportional allocation, Bayesian estimate; and (4) sequential Bayesian allocation. The user is given two options for computation of the estimated mean square error. These are referred to as the cluster calculation option and the segment calculation option. The software for the Proportion Estimate Processor is operational on the IBM 3031 computer.

Obrien, S.↗

A distributed scheduling algorithm for heterogeneous real-time systems

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

Zeineldine, Osman↗

Optimal spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.

Rao, R. G. S.↗

Empirical Analysis of EEG and ERPs for Psychophysiological Adaptive Task Allocation

The present study was designed to test the efficacy of using Electroencephalogram (EEG) and Event-Related Potentials (ERPs) for making task allocation decisions. Thirty-six participants were randomly assigned to an experimental, yoked, or control group condition. Under the experimental condition, a tracking task was switched between task modes based upon the participant's EEG. The results showed that the use of adaptive aiding improved performance and lowered subjective workload under negative feedback as predicted. Additionally, participants in the adaptive group had significantly lower RMSE and NASA-TLX ratings than participants in either the yoked or control group conditions. Furthermore, the amplitudes of the N1 and P3 ERP components were significantly larger under the experimental group condition than under either the yoked or control group conditions. These results are discussed in terms of the implications for adaptive automation design.

Prinzel, Lawrence J., III↗

Linear discriminant analysis with misallocation in training samples

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

Chhikara, R.↗

PACE Technical Report Series, Volume 6: Data Product Requirements and Error Budgets Consensus Document

This chapter summarizes ocean color science data product requirements for the Plankton, Aerosol, Cloud,ocean Ecosystem (PACE) mission's Ocean Color Instrument (OCI) and observatory. NASA HQ delivered Level-1 science data product requirements to the PACE Project, which encompass data products to be produced and their associated uncertainties. These products and uncertainties ultimately determine the spectral nature of OCI and the performance requirements assigned to OCI and the observatory. This chapter ultimately serves to provide context for the remainder of this volume, which describes tools developed that allocate these uncertainties into their components, including allowable OCI systematic and random uncertainties, observatory geo location uncertainties, and geophysical model uncertainties.

Cetinic, Ivona↗

Evaluation of the procedure 1A component of the 1980 US/Canada wheat and barley exploratory experiment

Several techniques which use clusters generated by a new clustering algorithm, CLASSY, are proposed as alternatives to random sampling to obtain greater precision in crop proportion estimation: (1) Proportional Allocation/relative count estimator (PA/RCE) uses proportional allocation of dots to clusters on the basis of cluster size and a relative count cluster level estimate; (2) Proportional Allocation/Bayes Estimator (PA/BE) uses proportional allocation of dots to clusters and a Bayesian cluster-level estimate; and (3) Bayes Sequential Allocation/Bayesian Estimator (BSA/BE) uses sequential allocation of dots to clusters and a Bayesian cluster level estimate. Clustering in an effective method in making proportion estimates. It is estimated that, to obtain the same precision with random sampling as obtained by the proportional sampling of 50 dots with an unbiased estimator, samples of 85 or 166 would need to be taken if dot sets with AI labels (integrated procedure) or ground truth labels, respectively were input. Dot reallocation provides dot sets that are unbiased. It is recommended that these proportion estimation techniques are maintained, particularly the PA/BE because it provides the greatest precision.

Chapman, G. M.↗

Dynamic decisions and work load in multitask supervisory control

A paradigm is developed for the problem of allocating in time a single resource to multiple simultaneous task demands which appear randomly, last for various periods, and offer varying rewards for service. Based upon a dynamic optimizing algorithm plus an estimator, and including response time and future discounting constraints, a model of the human decisionmaker is compared to experimental results for human subjects performing such a task at a computer-graphics terminal. Results indicate a reasonable fit, under various model parameters and task conditions, and suggest interesting hypotheses about the nature of human 'planning ahead' and mental work load.

Tulga, M. K.↗

Automated Construction of Artificial Lattice Structures with Designer Electronic States

Manipulating matter with a scanning tunneling microscope (STM) enables the creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of the designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating carbon monoxide (CO) molecules on a copper substrate by using the STM tip. The automated workflow combines molecule detection and manipulation, employing deep-learning-based object detection to locate CO molecules and linear assignment algorithms to allocate these molecules to designated target sites. We initially perform molecule maneuvering based on randomized parameter sampling for sample bias, tunneling current set point, and manipulation speed. This data set is then structured into an action trajectory used to train an RL agent. The model is subsequently deployed on the STM for real-time fine-tuning of the manipulation parameters during structure construction. Our approach incorporates path-planning protocols coupled with active drift compensation to enable atomically precise fabrication of structures with significantly reduced human input while realizing larger-scale artificial lattices with the desired electronic properties. Furthermore, using our approach, we demonstrate the automated construction of an extended artificial graphene lattice and confirm the existence of a characteristic Dirac point in its electronic structure. Further challenges regarding the RL-based structural assembly scalability are discussed.

Algorithms↗

A Dynamic Testing Complexity Metric

This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.

Voas, Jeffrey↗

Sharing Resources In Mobile/Satellite Communications

Report presents preliminary theoretical analysis of several alternative schemes for allocation of satellite resource among terrestrial subscribers of landmobile/satellite communication system. Demand-access and random-access approaches under code-division and frequency-division concepts compared.

Yan, Tsun-Yee↗

Two Extremely Red Galaxies

This report concerns one of the major observational studies in the ISO Central Programme, the ISO Normal Galaxy Survey. This is a survey of an unbiased sample of spiral and lenticular galaxies selected from the Revised Shapley-Ames Catalog. It is therefore optically-selected, with a brightness limit of blue magnitude = 12, and otherwise randomly chosen. The original sample included 150 galaxies, but this was reduced to 74 when the allocated observing time was expended because the ISO overheads encountered in flight were much larger than predicted.

Joseph, Robert D.↗

Learning linear optical circuits with coherent states

We analyze the energy and training data requirements for supervised learning of an M-mode linear optical circuit by minimizing an empirical risk defined solely from the action of the circuit on coherent states. When the linear optical circuit acts non-trivially only on k < M unknown modes (i.e. a linear optical k-junta), we provide an energy-efficient, adaptive algorithm that identifies the junta set and learns the circuit. We compare two schemes for allocating a total energy, E, to the learning algorithm. In the first scheme, each of the T random training coherent states has energy E/T. In the second scheme, a single random MT-mode coherent state with energy E is partitioned into T training coherent states. The latter scheme exhibits a polynomial advantage in training data size sufficient for convergence of the empirical risk to the full risk due to concentration of measure on the $(2MT-1)$-sphere. Specifically, generalization bounds for both schemes are proven, which indicate that for ε-approximation of the full risk by the empirical risk with high probability, $O(E^{2/3}M^{2/3}/\epsilon^{2/3})$ training states are sufficient for the first scheme and $O(E^{1/3}M^{1/3}/\epsilon^{2/3})$ training states are sufficient for the second scheme.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Superstructure Optimization of Waste Plastic Pyrolysis, Integrating Thermal, Catalytic, and Plasma Technologies with Machine Learning

Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.

Life cycle assessment↗