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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optical Control of Adaptive Nanoscale Domain Networks

Adaptive networks can sense and adjust to dynamic environments to optimize their performance. Understanding their nanoscale responses to external stimuli is essential for applications in nanodevices and neuromorphic computing. However, it is challenging to image such responses on the nanoscale with crystallographic sensitivity. Here, the evolution of nanodomain networks in (PbTiO 3 ) n /(SrTiO 3 ) n superlattices (SLs) is directly visualized in real space as the system adapts to ultrafast repetitive optical excitations that emulate controlled neural inputs. The adaptive response allows the system to explore a wealth of metastable states that are previously inaccessible. Their reconfiguration and competition are quantitatively measured by scanning x-ray nanodiffraction as a function of the number of applied pulses, in which crystallographic characteristics are quantitatively assessed by assorted diffraction patterns using unsupervised machine-learning methods. The corresponding domain boundaries and their connectivity are drastically altered by light, holding promise for light-programable nanocircuits in analogy to neuroplasticity. Phase-field simulations elucidate that the reconfiguration of the domain networks is a result of the interplay between photocarriers and transient lattice temperature. The demonstrated optical control scheme and the uncovered nanoscopic insights open opportunities for the remote control of adaptive nanoscale domain networks.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Adaptive laboratory evolution for increased temperature tolerance of the diatom Nitzschia inconspicua

Abstract Outdoor microalgal cultivation for the production of valuable biofuels and bioproducts typically requires high insolation and strains with high thermal (>37°C) tolerance. While some strains are naturally thermotolerant, other strains of interest require improved performance at elevated temperatures to enhance industrial viability. In this study, adaptive laboratory evolution (ALE) was performed for over 300 days using consecutive 0.5°C temperature increases in a constant temperature incubator to attain greater thermal tolerance in the industrially relevant diatom Nitzschia inconspicua str. Hildebrandi. The adapted strain was able to grow at a constant temperature of 37.5°C; whereas this constant temperature was lethal to the parental control, which had an upper‐temperature boundary of 35.5°C before adaptive evolution. Several high‐temperature clonal isolates were obtained from the evolved population following ALE, and increased temperature tolerance was observed in the clonal, parent, and non‐clonal adapted cultures. This ALE method demonstrates the development of enhanced industrial algal strains without the production of genetically modified organisms (GMOs).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

The adaptive mesh method based on HOC difference scheme for convection diffusion equations with boundary layers

In this paper, an adaptive mesh method is proposed to generate orthogonal nonuniform mesh for 2D rectangular computational domain. The algorithm adopts the dimension split idea which redistribute the mesh on each direction sequently. This approach efficiently decreases the difficultly of algorithm and enables the adapted mesh to be orthogonal. The adaptive mesh method can redistribute the mesh based on the solution without specifying the location of the boundary layer or the grid distribution function to generate the nonuniform mesh in advance. To verify the effectiveness and robustness of the algorithm, the presented method combined with the HOC difference scheme on nonuniform grid is used to solve the 1D and 2D convection diffusion problems with boundary layers. Besides, the multigrid method is used to accelerate the iterative convergence speed. The numerical solutions of adaptive mesh is more flexible than uniform or nonuniform grids methods if the location of the boundary layers is unknown in advance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Improving the Usability of Integrated Assessment for Adaptation Practice: Insights from the U.S. Southeast Energy Sector

Energy systems comprise a key sector of the U.S. economy, and one that has been identified as potentially vulnerable to the effects of climate variability and change. However, understanding of adaptation processes in energy companies and private entities more broadly is limited. It is unclear, for example, the extent to which energy companies are well-served by existing knowledge and tools emerging from the impacts, adaptation and vulnerability (IAV) and integrated assessment modeling (IAM) communities and/or what experiments, analyses, and model results have practical utility for informing adaptation in the energy sector. As part of a regional IAM development project, we investigated available evidence of adaptation processes in the energy sector, with a particular emphasis on the U.S. Southeast and Gulf Coast region. A mixed methods approach of literature review and semi-structured interviews with key informants from energy utilities was used to compare existing knowledge from the IAV community with that of regional stakeholders. That comparison revealed that much of the IAV literature on the energy sector is climate-centric and therefore disconnected from the more integrated decision-making processes and institutional perspectives of energy utilities. Increasing the relevance of research and assessment for the energy sector will necessitate a greater investment in integrated assessment and modeling efforts that respond to practical decision-making needs as well as greater collaboration between energy utilities and researchers in the design, execution, and communication of those efforts.

de Bremond, Ariane↗
DOE OSTI2026

Comparative genomics provides insights into the cold adaptation of endophytic fungi associated with Deschampsia antarctica

Endophytic fungi from Deschampsia antarctica , the southernmost flowering plant, provide insights into the cold adaptation mechanisms of plant-associated fungi in extreme environments. This study presents the genome sequences and comparative analysis of eight fungal isolates from D. antarctica leaves. These Antarctic fungal isolates were analyzed alongside 121 plant-associated fungal genomes to uncover signatures of adaptation and endophytic specialization. Antarctic endophytes show striking patterns, including reduced genome size (∼26.3 Mb on average), streamlined gene content (∼8844 genes), and notably small secretomes (∼288 proteins). Despite this reduced gene repertoire, they maintain a robust set of genes encoding carbohydrate-active enzymes (CAZymes) but lack those for lignin and bacterial cell wall degradation, indicating a symbiotic lifestyle that avoids host damage and predation. One isolate, Alternaria sp. UNIPAMPA017 stood out, with 26% of its genome occupied by transposable elements. Lifestyle, rather than phylogeny, was the main driver of CAZyme and secretome profiles, underscoring ecological convergence. Compared to endophytes from Arabidopsis and Populus, D. antarctica endophytes harbor fewer pectin-degrading enzymes, reflecting their adaptation to the cell wall structure of their monocot host. Together, these fungi reveal a pattern of genomic reduction and functional fine-tuning, hallmarks of life adapted to persist in cold, nutrient-scarce niches.

Ascomycota↗
DOE OSTI2022

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

First Clinical Release of an Online, Adaptive, Aperture-Based Image-Guided Radiotherapy Strategy in Intensity-Modulated Radiotherapy to Correct for Inter- and Intrafractional Rotations of the Prostate

Purpose: We developed and evaluated a correction strategy for prostate rotations using direct adaptation of segments in intensity-modulated radiotherapy (IMRT). Method and Materials: Implanted fiducials (four gold markers) were used to determine interfractional translations, rotations, and dilations of the prostate. We used hybrid imaging: The markers were automatically detected in two pretreatment planar X-ray projections; their actual position in three-dimensional space was reconstructed from these images at first. The structure set comprising prostate, seminal vesicles, and adjacent rectum wall was transformed accordingly in 6 degrees of freedom. Shapes of IMRT segments were geometrically adapted in a class solution forward-planning approach, derived within seconds on-site and treated immediately. Intrafractional movements were followed in MV electronic portal images captured on the fly. Results: In 31 of 39 patients, for 833 of 1013 fractions (supine, flat couch, knee support, comfortably full bladder, empty rectum, no intraprostatic marker migrations >2 mm of more than one marker), the online aperture adaptation allowed safe reduction of margins clinical target volume-planning target volume (prostate) down to 5 mm when only interfractional corrections were applied: Dominant L-R rotations were found to be 5.3 Degree-Sign (mean of means), standard deviation of means {+-}4.9 Degree-Sign , maximum at 30.7 Degree-Sign . Three-dimensional vector translations relative to skin markings were 9.3 {+-} 4.4 mm (maximum, 23.6 mm). Intrafractional movements in 7.7 {+-} 1.5 min (maximum, 15.1 min) between kV imaging and last beam's electronic portal images showed further L-R rotations of 2.5 Degree-Sign {+-} 2.3 Degree-Sign (maximum, 26.9 Degree-Sign ), and three-dimensional vector translations of 3.0 {+-}3.7 mm (maximum, 10.2 mm). Addressing intrafractional errors could further reduce margins to 3 mm. Conclusion: We demonstrated the clinical feasibility of an online adaptive image-guided, intensity-modulated prostate protocol on a standard linear accelerator to correct 6 degrees of freedom of internal organ motion, allowing safe and straightforward implementation of margin reduction and dose escalation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Toward Online Adaptive Hyperthermia Treatment Planning: Correlation Between Measured and Simulated Specific Absorption Rate Changes Caused by Phase Steering in Patients

Purpose: Hyperthermia is the clinical application of heat, in which tumor temperatures are raised to 40°C to 45°C. This proven radiation and chemosensitizer significantly improves clinical outcome for several tumor sites. Earlier studies of the use of pre-treatment planning for hyperthermia showed good qualitative but disappointing quantitative reliability. The purpose of this study was to investigate whether hyperthermia treatment planning (HTP) can be used more reliably for online adaptive treatment planning during locoregional hyperthermia treatments. Methods and Materials: This study included 78 treatment sessions for 15 patients with non-muscle-invasive bladder cancer. At the start of treatments, temperature rise measurements were performed with 3 different antenna settings optimized for each patient, from which the absorbed power (specific absorption rate [SAR]) was derived. HTP was performed based on a computed tomography (CT) scan in treatment position with the bladder catheter in situ. The SAR along the thermocouple tracks was extracted from the simulated SAR distributions. Correlations between measured and simulated (average) SAR values were determined. To evaluate phase steering, correlations between the changes in simulated and measured SAR values averaged over the thermocouple probe were determined for all 3 combinations of antenna settings. Results: For 42% of the individual treatment sessions, the correlation coefficient between measured and simulated SAR profiles was higher than 0.5, whereas 58% showed a weak correlation (R of <0.5). The overall correlation coefficient between measured and simulated average SAR was weak (R=0.31; P<.001). The measured and simulated changes in average SAR after adapting antenna settings correlated much better (R=0.70; P<.001). The ratio between the measured and simulated quotients of maximum and average SARs was 1.03 ± 0.26 (mean ± SD), indicating that HTP can also correctly predict the relative amplitude of SAR peaks. Conclusions: HTP can correctly predict SAR changes after adapting antenna settings during hyperthermia treatments. This allows online adaptive treatment planning, assisting the operator in determining antenna settings resulting in increased tumor temperatures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Head and Neck Margin Reduction With Adaptive Radiation Therapy: Robustness of Treatment Plans Against Anatomy Changes

Purpose: We set out to investigate loss of target coverage from anatomy changes in head and neck cancer patients as a function of applied safety margins and to verify a cone beam computed tomography (CBCT)–based adaptive strategy with an average patient anatomy to overcome possible target underdosage. Methods and Materials: For 19 oropharyngeal cancer patients, volumetric modulated arc therapy treatment plans (2 arcs; simultaneous integrated boost, 70 and 54.25 Gy; 35 fractions) were automatically optimized with uniform clinical target volume (CTV)–to–planning target volume margins of 5, 3, and 0 mm. We applied b-spline CBCT–to–computed tomography (CT) deformable registration to allow recalculation of the dose on modified CT scans (planning CT deformed to daily CBCT following online positioning) and dose accumulation in the planning CT scan. Patients with deviations in primary or elective CTV coverage >2 Gy were identified as candidates for adaptive replanning. For these patients, a single adaptive intervention was simulated with an average anatomy from the first 10 fractions. Results: Margin reduction from 5 mm to 3 mm to 0 mm generally led to an organ-at-risk (OAR) mean dose (D{sub mean}) sparing of approximately 1 Gy/mm. CTV shrinkage was mainly seen in the elective volumes (up to 10%), likely related to weight loss. Despite online repositioning, substantial systematic errors were present (>3 mm) in lymph node CTV, the parotid glands, and the larynx. Nevertheless, the average increase in OAR dose was small: maximum of 1.2 Gy (parotid glands, D{sub mean}) for all applied margins. Loss of CTV coverage >2 Gy was found in 1, 3, and 7 of 73 CTVs, respectively. Adaptive intervention in 0-mm plans substantially improved coverage: in 5 of 7 CTVs (in 6 patients) to <2 Gy of initially planned. Conclusions: Volumetric modulated arc therapy head and neck cancer treatment plans with 5-mm margins are robust for anatomy changes and show a modest increase in OAR dose. Margin reduction improves OAR sparing with approximately 1 Gy/mm at the expense of target coverage in a subgroup of patients. Patients at risk of CTV underdosage >2 Gy in 0-mm plans may be identified early in treatment using dose accumulation. A single intervention with an average anatomy derived from CBCT effectively mitigates discrepancies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Adaptive scapula bone remodeling computational simulation: Relevance to regenerative medicine

Shoulder arthroplasty success has been attributed to many factors including, bone quality, soft tissue balancing, surgeon experience, and implant design. Improved long-term success is primarily limited by glenoid implant loosening. Prosthesis design examines materials and shape and determines whether the design should withstand a lifetime of use. Finite element (FE) analyses have been extensively used to study stresses and strains produced in implants and bone. However, these static analyses only measure a moment in time and not the adaptive response to the altered environment produced by the therapeutic intervention. Computational analyses that integrate remodeling rules predict how bone will respond over time. Recent work has shown that subject-specific two- and three dimensional adaptive bone remodeling models are feasible and valid. Feasibility and validation were achieved computationally, simulating bone remodeling using an intact human scapula, initially resetting the scapular bone material properties to be uniform, numerically simulating sequential loading, and comparing the bone remodeling simulation results to the actual scapula’s material properties. Three-dimensional scapula FE bone model was created using volumetric computed tomography images. Muscle and joint load and boundary conditions were applied based on values reported in the literature. Internal bone remodeling was based on element strain-energy density. Initially, all bone elements were assigned a homogeneous density. All loads were applied for 10 iterations. After every iteration, each bone element’s remodeling stimulus was compared to its corresponding reference stimulus and its material properties modified. The simulation achieved convergence. At the end of the simulation the predicted and actual specimen bone apparent density were plotted and compared. Location of high and low predicted bone density was comparable to the actual specimen. High predicted bone density was greater than actual specimen. Low predicted bone density was lower than actual specimen. Differences were probably due to applied muscle and joint reaction loads, boundary conditions, and values of constants used. Work is underway to study this. Nonetheless, the results demonstrate three dimensional bone remodeling simulation validity and potential. Such adaptive predictions take physiological bone remodeling simulations one step closer to reality. Computational analyses are needed that integrate biological remodeling rules and predict how bone will respond over time. We expect the combination of computational static stress analyses together with adaptive bone remodeling simulations to become effective tools for regenerative medicine research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Parallel adaptive wavelet collocation method for PDEs

A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented. The parallelization is achieved by developing an asynchronous parallel wavelet transform, which allows one to perform parallel wavelet transform and derivative calculations with only one data synchronization at the highest level of resolution. The data are stored using tree-like structure with tree roots starting at a priori defined level of resolution. Both static and dynamic domain partitioning approaches are developed. For the dynamic domain partitioning, trees are considered to be the minimum quanta of data to be migrated between the processes. This allows fully automated and efficient handling of non-simply connected partitioning of a computational domain. Dynamic load balancing is achieved via domain repartitioning during the grid adaptation step and reassigning trees to the appropriate processes to ensure approximately the same number of grid points on each process. The parallel efficiency of the approach is discussed based on parallel adaptive wavelet-based Coherent Vortex Simulations of homogeneous turbulence with linear forcing at effective non-adaptive resolutions up to 2048{sup 3} using as many as 2048 CPU cores.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Investigating uncertainties in human adaptation and their impacts on water scarcity in the Colorado river Basin, United States

The Colorado River Basin (CRB) supports the water supply for seven states and forty million people in the Western United States (US) and has been suffering an extensive drought for more than two decades. As climate change continues to reshape water resources distribution in the CRB, its impact can differ in intensity and location, resulting in variations in human adaptation behaviors. The feedback from human systems in response to the environmental changes and the associated uncertainty is critical to water resources management, especially for water-stressed basins. This paper investigates how human adaptation affects water scarcity uncertainty in the CRB and highlights the uncertainties in human behavior modeling. Our focus is on agricultural water consumption, as approximately 80% of the water consumption in the CRB is used in agriculture. We adopted a coupled agent-based and water resources modeling approach for exploring human-water system dynamics, in which an agent is a human behavior model that simulates a farmer’s water consumption decisions. We examined uncertainties at the system, agent, and parameter levels through uncertainty, clustering, and sensitivity analyses. The uncertainty analysis results suggest that the CRB water system may experience 13 to 30 years of water shortage during the 2019–2060 simulation period, depending on the paths of farmers’ adaptation. The clustering analysis identified three decision-making classes: bold, prudent, and forward-looking, and quantified the probabilities of an agent belonging to each class. The sensitivity analysis results indicated agents whose decision-making models require further investigation and the parameters with the higher uncertainty reduction potentials. Here, by conducting numerical experiments with the coupled model, this paper presents quantitative and qualitative information about farmers’ adaptation, water scarcity uncertainties, and future research directions for improving human behavior modeling.

Agent-based modeling↗
DOE OSTI2011

The Dosimetric Effect of Zipper Artifacts on TomoTherapy Adaptive Dose Calculation-A Phantom Study

Tomotherapy adaptive dose calculation offers the ability to verify and adjust the therapeutic plan during the treatment. Using tomotherapy adaptive dose calculation, the planned fluence pattern can be used to recalculate the dose distribution on pretreatment megavoltage computed tomography (MVCT) images. Zipper artifacts, which appear as increased density in the central region of MVCT images, may affect the accuracy of adaptive dose recalculation. The purpose of this study was to evaluate the dosimetric effects of zipper artifacts on tomotherapy adaptive dose calculation. MVCT images of a cylindrical water phantom of 22-cm diameter were acquired on a tomotherapy system. The zipper artifacts were enclosed by a cylindrical planning target volume (PTV) contoured on these images. For comparison, artifact-free images were created by replacing the computed tomography (CT) numbers of zipper artifacts with the mean CT number of water. Treatment plans were generated by giving a uniform dose of 2 Gy to the PTV based on these modified images; it was then applied to the images that have the zipper artifacts. The impacts of different pitch ratios on the artifacts were assessed. The dose distribution differences between the 2 sets of images were compared. The absorbed dose that covered 95% volume of PTV and maximum dose, minimum dose, and mean dose of the PTV were also calculated and compared. The water phantom was scanned on the tomotherapy system twice per week for 12 consecutive weeks. The mean CT number of zipper artifacts (101 HU) was three times higher than that of water (34 HU). The CT number value and location of zipper artifacts were not affected by the pitch ratio. Gamma analysis was performed between the original and recalculated dose distributions. The discrepancies between the isodose distributions calculated by two sets of images were within 1%/1-mm tolerance. The dosimetric impact from zipper artifacts was found insignificant such that the recalculated dose was underestimated by less than 0.5%.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

Feasibility of an online adaptive replanning method for cranial frameless intensity-modulated radiosurgery

To introduce an approach for online adaptive replanning (i.e., dose-guided radiosurgery) in frameless stereotactic radiosurgery, when a 6-dimensional (6D) robotic couch is not available in the linear accelerator (linac). Cranial radiosurgical treatments are planned in our department using intensity-modulated technique. Patients are immobilized using thermoplastic mask. A cone-beam computed tomography (CBCT) scan is acquired after the initial laser-based patient setup (CBCT{sub setup}). The online adaptive replanning procedure we propose consists of a 6D registration-based mapping of the reference plan onto actual CBCT{sub setup}, followed by a reoptimization of the beam fluences (“6D plan”) to achieve similar dosage as originally was intended, while the patient is lying in the linac couch and the original beam arrangement is kept. The goodness of the online adaptive method proposed was retrospectively analyzed for 16 patients with 35 targets treated with CBCT-based frameless intensity modulated technique. Simulation of reference plan onto actual CBCT{sub setup}, according to the 4 degrees of freedom, supported by linac couch was also generated for each case (4D plan). Target coverage (D99%) and conformity index values of 6D and 4D plans were compared with the corresponding values of the reference plans. Although the 4D-based approach does not always assure the target coverage (D99% between 72% and 103%), the proposed online adaptive method gave a perfect coverage in all cases analyzed as well as a similar conformity index value as was planned. Dose-guided radiosurgery approach is effective to assure the dose coverage and conformity of an intracranial target volume, avoiding resetting the patient inside the mask in a “trial and error” way so as to remove the pitch and roll errors when a robotic table is not available.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Enhancement of the safety of live influenza vaccine by attenuating mutations from cold-adapted hemagglutinin

In our previous study, X-31ca-based H5N1 LAIVs, in particular, became more virulent in mice than the X-31ca MDV, possibly by the introduction of the surface antigens of highly pathogenic H5N1 influenza virus, implying that additional attenuation is needed in this cases to increase the safety level of the vaccine. In this report we suggest an approach to further increase the safety of LAIV through additional cold-adapted mutations in the hemagglutinin. The cold-adaptation of X-31 virus resulted in four amino acid mutations in the HA. We generated a panel of 7:1 reassortant viruses each carrying the hemagglutinins with individual single amino acid mutations. We examined their phenotypes and found a major attenuating mutation, N81K. This attenuation marker conferred additional temperature-sensitive and attenuation phenotype to the LAIV. Our data indicate that the cold-adapted mutation in the HA confers additional attenuation to the LAIV strain, without compromising its productivity and immune response. - Highlights: • Cold-adaptation process induced four amino acid mutations in the HA of X-31 virus. • The four mutations in the HA also contributed to attenuation of the X-31ca virus • N81K mutation was the most significant marker for the attenuation of X-31ca virus. • Introduction of N81K mutation into H3N2 LAIV further attenuated the vaccine. • This approach provides a useful guideline for enhancing the safety of the LAIVs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Genetic characterization of an adapted pandemic 2009 H1N1 influenza virus that reveals improved replication rates in human lung epithelial cells

The 2009 influenza pandemic originated from a swine-origin H1N1 virus, which, although less pathogenic than anticipated, may acquire additional virulence-associated mutations in the future. To estimate the potential risk, we sequentially passaged the isolate A/Hamburg/04/2009 in A549 human lung epithelial cells. After passage 6, we observed a 100-fold increased replication rate. High-throughput sequencing of viral gene segments identified five dominant mutations, whose contribution to the enhanced growth was analyzed by reverse genetics. The increased replication rate was pinpointed to two mutations within the hemagglutinin (HA) gene segment (HA{sub 1} D130E, HA{sub 2} I91L), near the receptor binding site and the stem domain. The adapted virus also replicated more efficiently in mice in vivo. Enhanced replication rate correlated with increased fusion pH of the HA protein and a decrease in receptor affinity. Our data might be relevant for surveillance of pre-pandemic strains and development of high titer cell culture strains for vaccine production. - Highlights: • We observed a spontaneous mutation of a 2009-pandemic H1N1 influenza virus in vitro. • The adaptation led to a 100-fold rise in replication rate in human A549 cells. • Adaptation was caused by two mutations in the HA gene segment. • Adaptation correlates with increased fusion pH and decreased receptor affinity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Adaptive Data-Driven Deep-Learning Surrogate Model for Frontal Polymerization in Dicyclopentadiene

Frontal polymerization (FP) is a self-sustaining curing process that enables rapid and energy-efficient manufacturing of thermoset polymers and composites. Computational methods conventionally used to simulate the FP process are time-consuming, and repeating simulations are required for sensitivity analysis, uncertainty quantification, or optimization of the manufacturing process. Here, in this work, we develop an adaptive surrogate deep-learning model for FP of dicyclopentadiene (DCPD), which predicts the evolution of temperature and degree of cure orders of magnitude faster than the finite-element method (FEM). The adaptive algorithm provides a strategy to select training samples efficiently and save computational costs by reducing the redundancy of FEM-based training samples. The adaptive algorithm calculates the residual error of the FP governing equations using automatic differentiation of the deep neural network. A probability density function expressed in terms of the residual error is used to select training samples from the Sobol sequence space. The temperature and degree of cure evolution of each training sample are obtained by a 2D FEM simulation. The adaptive method is more efficient and has a better prediction accuracy than the random sampling method. With the well-trained surrogate neural network, the FP characteristics (front speed, shape, and temperature) can be extracted quickly from the predicted temperature and degree-of-cure fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Anion transport as a target of adaption to perchlorate in sulfate-reducing communities

Inhibitors can be used to control the functionality of microbial communities by targeting specific metabolisms. The targeted inhibition of dissimilatory sulfate reduction limits the generation of toxic and corrosive hydrogen sulfide across several industrial systems. Sulfate-reducing microorganisms (SRM) are specifically inhibited by sulfate analogs, such as perchlorate. Previously, we showed pure culture SRM adaptation to perchlorate stress through mutation of the sulfate adenylyltransferase, a central enzyme in the sulfate reduction pathway. Here, we explored adaptation to perchlorate across unconstrained SRM on a community scale. We followed natural and bio-augmented sulfidogenic communities through serial transfers in increasing concentrations of perchlorate. Our results demonstrated that perchlorate stress altered community structure by initially selecting for innately more resistant strains. Isolation, whole-genome sequencing, and molecular biology techniques allowed us to define subsequent genetic mechanisms of adaptation that arose across the dominant adapting SRM. Changes in the regulation of divalent anion:sodium symporter family transporters led to increased intracellular sulfate to perchlorate ratios, allowing SRM to escape the effects of competitive inhibition. Thus, in contrast to pure-culture results, SRM in communities cope with perchlorate stress via changes in anion transport and its regulation. Finally, this highlights the value of probing evolutionary questions in an ecological framework, bridging the gap between ecology, evolution, genomics, and physiology.

59 BASIC BIOLOGICAL SCIENCES↗