Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Sequence”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Isolation and characterization of 13 microsatellite loci for the Neotropical otter, Lontra longicaudis, by next generation sequencing

The Neotropical otter, Lontra longicaudis, is an ecologically important species for freshwater ecosystems that is threatened due to habitat destruction and hunting. However, there is limited information regarding the population sizes, genetic diversity, genetic structure and gene flow of the species, which is crucial for the elaboration of conservation plans. The aim of this study was to isolate and characterize microsatellites for L. longicaudis, using Illumina paired-end-sequencing. Initial amplification tests were performed in 48 loci, out of which, 13 yielded high-quality PCR products and thus were further evaluated. Genetic diversity and discrimination power of the 13 microsatellite loci was assessed using 19 non-invasive samples collected in the Jamapa basin in Veracruz, Mexico and blood samples from six captive individuals. All loci were polymorphic, the number of alleles per locus ranged from 4 to 10, the observed heterozygosity from 0.21 to 0.69, and the expected heterozygosity from 0.55 to 0.82. The combined set of 13 microsatellites showed a high power for discriminating among individuals (probability of identity P ID = 1.551 × 10 -16 ) and among siblings (probability of identity of siblings P IDSIB = 3.349 × 10 -06 ). A combination of nine loci are sufficient to discriminate among siblings with high confidence (P IDSIB < 0.0001). The new set of microsatellites for the Neotropical otter reported here will provide a useful genetic tool to assess population genetic patterns and ecological parameters of the species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Structural Basis and Sequence Rules for Substrate Recognition by Tankyrase Explain the Basis for Cherubism Disease

The poly(ADP-ribose)polymerases Tankyrase 1/2 (TNKS/TNKS2) catalyze the covalent linkage of ADP-ribose polymer chains onto target proteins, regulating their ubiquitylation, stability, and function. Dysregulation of substrate recognition by Tankyrases underlies the human disease cherubism. Tankyrases recruit specific motifs (often called RxxPDG hexapeptides) in their substrates via an N-terminal region of ankyrin repeats. These ankyrin repeats form five domains termed ankyrin repeat clusters (ARCs), each predicted to bind substrate. Here we report crystal structures of a representative ARC of TNKS2 bound to targeting peptides from six substrates. Using a solution-based peptide library screen, we derive a rule-based consensus for Tankyrase substrates common to four functionally conserved ARCs. This 8-residue consensus allows us to rationalize all known Tankyrase substrates and explains the basis for cherubism-causing mutations in the Tankyrase substrate 3BP2. Structural and sequence information allows us to also predict and validate other Tankyrase targets, including Disc1, Striatin, Fat4, RAD54, BCR, and MERIT40.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Time sequence gamma-spectrometry of irradiated salt

Persisted Memory Mapping File (MMF) techniques have developed for the processing and analysis of time-stamped list (TLIST) mode data collected from an irradiated salt sample. This is a new technique that is unique to this research and enables additional information to be obtained from a conventional pulse height analysis (PHA) gamma-spectrometry acquisition. A salt sample was irradiated using a DT neutron generator and immediately measured using TLIST acquisition for 1 month to generate a 22 GB data file. MMF techniques were used to process the file without size restrictions at a rate of 388.5 MB minute-1, with instant access to any position within the file, separating the file into a series of time sequenced spectra suitable for PHA analysis. This enabled 14 activation products to be identified at different time intervals (41Ar, 80Br, 80mBr, 47Ca, 34mCl, 38Cl, 42K, 43K, 56Mn, 22Na, 24Na, 85Sr, 87mSr and 69mZn), and 6 radionuclides (80Br, 47Ca, 34mCl, 56Mn, 24Na and 87mSr) to be definitively confirmed based upon their measured half-life. Using this technique, the detection of 47Ca, and in-growth of its 47Sc progeny, was demonstrated as useful for calculating the time since irradiation.

Burnett, Jonathan L.↗
DOE OSTI2022

Sequence Modulates Polypeptoid Hydration Water Structure and Dynamics

We use molecular dynamics simulations to investigate the effect of polypeptoid sequence on the structure and dynamics of its hydration waters. Polypeptoids provide an excellent platform to study small-molecule hydration in disordered polymers, as they can be precisely synthesized with a variety of sidechain chemistries. We examine water behavior near a set of peptoid oligomers in which the number and placement of nonpolar versus polar sidechains are systematically varied. To do this, we leverage a new computational workflow enabling accurate sampling of polypeptoid conformations. We find that the hydration waters are less dense, are more tetrahedral, and have slower dynamics compared to bulk water. The magnitude of these shifts increases with the number of nonpolar groups. Here, we also find that shifts in the water structure and dynamics are strongly correlated, suggesting that experimental insight into the dynamics of hydration water obtained by Overhauser dynamic nuclear polarization (ODNP) also contains information about water structural properties. We then demonstrate the ability of ODNP to probe site-specific dynamics of hydration water near these model peptoid systems.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Complete genome sequencing of a multidrug-resistant and human-invasive Salmonella enterica serovar Typhimurium strain of the emerging sequence type 213 genotype

Salmonella enterica subsp. enterica serovar Typhimurium strain YU39 was isolated in 2005 in the state of Yucatán, Mexico, from a human systemic infection. The YU39 strain is representative of the multidrug-resistant emergent sequence type 213 (ST213) genotype. The YU39 complete genome is composed of a chromosome and seven plasmids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Two-Level Adaptive Algebraic Multigrid for a Sequence of Problems with Slowly Varying Random Coefficients [Adaptive Algebraic Multigrid for Sequence of Problems with Slowly Varying Random Coefficients]

Our paper proposes an adaptive strategy for reusing a previously constructed coarse space by algebraic multigrid to construct a two-level solver for a problem with nearby characteristics. Furthermore, a main target application is the solution of the linear problems that appear throughout a sequence of Markov chain Monte Carlo simulations of subsurface flow with uncertain permeability field. We demonstrate the efficacy of the method with extensive set of numerical experiments.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Dusty debris clouds around main sequence and post-main sequence stars

During the past decade, infrared observations by IRAS and from the ground have revealed that many stars are orbited by dusty debris disks. Somewhat more indirect arguments indicate that many of these systems also contain asteroids, comets, and/or planets, thereby suggesting that planetary systems may be quite common in the Milky Way. Dust clouds at the main sequence K5 star HD 98800 and the white dwarf Giclas 29-38 are particularly noteworthy and mysterious.

Zuckerman, B.↗
NASA NTRS2017

Beyond DNA Sequencing in Space: Current and Future Omics Capabilities of the Biomolecule Sequencer Payload

Why do we need a DNA sequencer to support the human exploration of space? (A) Operational environmental monitoring; (1) Identification of contaminating microbes, (2) Infectious disease diagnosis, (3) Reduce down mass (sample return for environmental monitoring, crew health, etc.). (B) Research; (1) Human, (2) Animal, (3) Microbes/Cell lines, (4) Plant. (C) Med Ops; (1) Response to countermeasures, (2) Radiation, (3) Real-time analysis can influence medical intervention. (C) Support astrobiology science investigations; (1) Technology superiorly suited to in situ nucleic acid-based life detection, (2) Functional testing for integration into robotics for extraplanetary exploration mission.

Wallace, Sarah↗
DOE OSTI2020

Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory

To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.

Bi-RNN model↗
DOE OSTI2020

Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings

The U.S. power grid is transforming to become smarter, cleaner, and more effi- cient. This is leading to the addition of significant distributed variable renew- able generation. Due to the variable nature of renewable generation, the short- and long-term supply-demand imbalances are less predictable, and conventional approaches to mitigating the imbalance will not be efficient or cost-effective. To address this challenge, transactive control technologies have been proposed which balance energy generation and consumption with market activity and in- frastructural limitations. Transactive control requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical gray- and black-box models have been widely used to express flexibility, and although these approaches are generally easy to construct and simple to use, they do not capture the non-linear behavior that some end-use loads represent . Machine learning approaches have been proposed to address this limitation. Although deep learning approaches for forecasting end-use loads have been explored, certain aspects of the application of deep models to load forecasting are not well understood. These aspects include how much training data is required, and how models should be structured and trained. To that end, this work explores how to approach applying deep recurrent neural networks to short-term electrical load forecasting with a case study of four commercial office buildings. We identify data requirements for training accurate models of whole building electricity use conditioned on outdoor temperature, provide insight into model hyperparameter sensitivity, and demonstrate how readily models can be generalized to unseen buildings.

Skomski, Elliott↗