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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
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 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 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↗
DOE OSTI2019

Adaptive responses of animals to climate change are most likely insufficient

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Quantifying the local adaptive landscape of a nascent bacterial community

Abstract The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes (“L” and “S”) shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

The dynamics of adaptive genetic diversity during the early stages of clonal evolution

The dynamics of genetic diversity in large clonally evolving cell populations are poorly understood, despite having implications for the treatment of cancer and microbial infections. Here, we combine barcode lineage tracking, sequencing of adaptive clones and mathematical modelling of mutational dynamics to understand adaptive diversity changes during experimental evolution of Saccharomyces cerevisiae under nitrogen and carbon limitation. We find that, despite differences in beneficial mutational mechanisms and fitness effects, early adaptive genetic diversity increases predictably, driven by the expansion of many single-mutant lineages. Furthermore, a crash in adaptive diversity follows, caused by highly fit double-mutant ‘jackpot’ clones that are fed from exponentially growing single mutants, a process closely related to the classic Luria–Delbrück experiment. The diversity crash is likely to be a general feature of asexual evolution with clonal interference; however, both its timing and magnitude are stochastic and depend on the population size, the distribution of beneficial fitness effects and patterns of epistasis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Fine-scale contemporary recombination variation and its fitness consequences in adaptively diverging stickleback fish

Despite deep evolutionary conservation, recombination rates vary greatly across the genome and among individuals, sexes and populations. Yet the impact of this variation on adaptively diverging populations is not well understood. Here we characterized fine-scale recombination landscapes in an adaptively divergent pair of marine and freshwater populations of threespine stickleback from River Tyne, Scotland. Through whole-genome sequencing of large nuclear families, we identified the genomic locations of almost 50,000 crossovers and built recombination maps for marine, freshwater and hybrid individuals at a resolution of 3.8 kb. We used these maps to quantify the factors driving variation in recombination rates. We found strong heterochiasmy between sexes but also differences in recombination rates among ecotypes. Hybrids showed evidence of significant recombination suppression in overall map length and in individual loci. Recombination rates were lower not only within individual marine–freshwater-adaptive loci, but also between loci on the same chromosome, suggesting selection on linked gene ‘cassettes’. Through temporal sampling along a natural hybrid zone, we found that recombinants showed traits associated with reduced fitness. Our results support predictions that divergence in cis-acting recombination modifiers, whose functions are disrupted in hybrids, may play an important role in maintaining differences among adaptively diverging populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The Marchantia polymorpha pangenome reveals ancient mechanisms of plant adaptation to the environment

Plant adaptation to terrestrial life started 450 million years ago and has played a major role in the evolution of life on Earth. The genetic mechanisms allowing this adaptation to a diversity of terrestrial constraints have been mostly studied by focusing on flowering plants. Here, we gathered a collection of 133 accessions of the model bryophyte Marchantia polymorpha and studied its intraspecific diversity using selection signature analyses, a genome-environment association study and a pangenome. We identified adaptive features, such as peroxidases or nucleotide-binding and leucine-rich repeats (NLRs), also observed in flowering plants, likely inherited from the first land plants. The M. polymorpha pangenome also harbors lineage-specific accessory genes absent from seed plants. We conclude that different land plant lineages still share many elements from the genetic toolkit evolved by their most recent common ancestor to adapt to the terrestrial habitat, refined by lineage-specific polymorphisms and gene family evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A variational framework for residual-based adaptivity in neural PDE solvers and operator learning

Residual-based adaptive strategies are widely used in scientific machine learning yet remain largely heuristic. We introduce a variational framework that formalizes these methods through convex transformations of the residual, where different transformations correspond to distinct objective functionals. For instance, exponential weights target uniform error minimization, while linear weights recover quadratic error minimization. This perspective reveals adaptive weighting as a means of selecting sampling distributions that optimize a primal objective, directly linking discretization choices to error metrics. This principled approach yields three key benefits: it enables systematic design of adaptive schemes, reduces discretization error by lowering estimator variance, and enhances learning dynamics by improving gradient signal-to-noise ratio. Extending the framework to operator learning, we demonstrate substantial performance gains across diverse optimizers and architectures. Our results provide a theoretical perspective for residual-based adaptivity and establish a foundation for principled discretization and training.

97 MATHEMATICS AND COMPUTING↗