Development of Graphical User Interface and Spectral Fitting Tool for NEQAIR
Create a GUI and spectral fitting tool for NEQAIR
SEARCH · Search NASA
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.
Create a GUI and spectral fitting tool for NEQAIR
This study presents experimental results of impact and subsequent compression after impact (CAI) strength testing of sandwich structure representative of most of the acreage of a Payload Adaptor Fitting (PAF) that has been built at NASA’s Marshall Space Flight Center (MSFC). An instrumented drop weight tower was used to inflict different levels of impact damage to specimens. Load versus deflection of impact curves, visual damage, dent depth, damage as ascertained by thermography and cross-sectional microscopy were evaluated as part of the damage resistance of the structure. Compression After Impact (CAI) was performed to assess damage tolerance. The results show that at the amount of visual damage was highly dependent on whether the peel ply was present on the surface of the structure. The peel ply had some effect on the CAI strength values since the specimens with peel ply showed a 14% higher average CAI strength value. For all specimens tested in this study, CAI versus damage and CAI versus impact energy curves were plotted and it was found that damage size was a good indicator of CAI strength. It is suggested to use a b-basis damage tolerance curve based on damage size as a conservative measure of the load carrying capability of the sandwich structure with impact damage.
The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.
In this work, the density fitting (DF) approximation is added to the restricted Hartree–Fock (RHF) implementation in the JuliaChem computational chemistry code. Utilizing a DF algorithm that uses symmetry and integral screening, a significant reduction in time to compute the Fock matrix is achieved. The symmetry and screening DF-RHF techniques were adapted to be performed on graphics processing units (GPUs), which are well suited to perform the matrix multiplications that comprise the bulk of the Fock build time in DF-RHF. The JuliaChem DF-RHF GPU algorithm employs a novel approach that automatically switches between two DF-RHF algorithms depending on the number of basis functions in the calculation. The JuliaChem GPU DF-RHF implementation demonstrates up to 2× speedup for Fock build times compared to the existing best-in-class GPU DF-RHF implementation by operating directly on screened intermediate matrices. Due to the high portability of the Julia language code, the JuliaChem CPU and GPU DF-RHF implementations could be benchmarked on a variety of CPU and GPU architectures from multiple hardware vendors.
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.
Mycorrhizal fungi are essential to the establishment of the vast majority of plant species but are often conceptualized with contradictory roles in plant community assembly. On the one hand, host-specific mycorrhizal fungi may allow a plant to be competitively dominant by enhancing growth. On the other hand, host-specific mycorrhizal fungi with different functional capabilities may increase nutrient niche partitioning, allowing plant species to coexist. Here, to resolve the balance of these two contradictory forces, we used a controlled greenhouse study to manipulate the presence of two main types of mycorrhizal fungus, ectomycorrhizal fungi and arbuscular mycorrhizal fungi, and used a range of conspecific and heterospecific competitor densities to investigate the role of mycorrhizal fungi in plant competition and coexistence. We find that the presence of arbuscular mycorrhizal fungi equalizes fitness differences between plants and stabilizes competition to create conditions for host species coexistence. Furthermore, our results show how below-ground mutualisms can shift outcomes of plant competition and that a holistic view of plant communities that incorporates their mycorrhizal partners is important in predicting plant community dynamics.
Many factors contribute to the ability of a microbial species to persist when encountering complexly contaminated environments, including time of exposure, the nature and concentration of contaminants, availability of nutritional resources, and possession of a combination of appropriate molecular mechanisms needed for survival. Herein we sought to identify genes that are most important for survival of Gram-negative Enterobacteriaceae in contaminated groundwater environments containing high concentrations of nitrate and metals using the metal-tolerant Oak Ridge Reservation isolate, Pantoea sp. MT58 (MT58). Survival fitness experiments in which a randomly barcoded transposon insertion (RB-TnSeq) library of MT58 was exposed directly to contaminated Oak Ridge Reservation groundwater samples from across a nitrate and mixed metal contamination plume were used to identify genes important for survival with increasing exposure times and concentrations of contaminants, and availability of a carbon source. Genes involved in controlling and using carbon, encoding transcriptional regulators, and related to Gram-negative outer membrane processes were among those found to be important for survival in contaminated Oak Ridge Reservation groundwater. A comparative genomics analysis of 75 Pantoea genus strains allowed us to further separate the survival determinants into core and non-core genes in the Pantoea pangenome, revealing insights into the survival of subsurface microorganisms during contaminant plume intrusion.
ABSTRACT We obtain a quantitative star formation history (SFH) of a shell-like structure (‘shell’) located in the northeastern part of the Small Magellanic Cloud (SMC). We use the Survey of the MAgellanic Stellar History to derive colour–magnitude diagrams (CMDs), reaching below the oldest main-sequence turnoff, from which we compute the SFHs with CMD-fitting techniques. We present, for the first time, a novel technique that uses red clump (RC) stars from the CMDs to assess and account for the SMC’s line-of-sight depth effect present during the SFH derivation. We find that accounting for this effect recovers a more accurate SFH. We quantify an $\sim$7 kpc line-of-sight depth present in the CMDs, in good agreement with depth estimates from RC stars in the northeastern SMC. By isolating the stellar content of the northeastern shell and incorporating the line-of-sight depth into our calculations, we obtain an unprecedentedly detailed SFH. We find that the northeastern shell is primarily composed of stars younger than $\sim$500 Myr, with significant star formation enhancements around $\sim$250 and $\sim$450 Myr. These young stars are the main contributors to the shell’s structure. We show synchronicity between the northeastern shell’s SFH with the Large Magellanic Cloud’s (LMC) northern arm, which we attribute to the interaction history of the SMC with the LMC and the Milky Way (MW) over the past $\sim$500 Myr. Our results highlight the complex interplay of ram pressure stripping and the influence of the MW’s circumgalactic medium in shaping the SMC’s northeastern shell.
Redox-Electrodialysis (r-ED) is an electrochemical desalination cell architecture that has recently received considerable interest, due to its low energy demand relative to electrochemical desalination technologies that rely on electrode-based ion removal. To further improve the energy efficiency of r-ED, we developed a lumped mathematical model with no adjustable parameters to investigate the various sources of overpotential within the cell. Existing models of electrodialysis and r-ED cells either do not accurately incorporate all phenomena contributing to the overpotential or utilize empirical fitting parameters. The model developed here indicates that ohmic overpotentials, especially in the diluate chamber, are the most significant contributors to energy losses. Based on this insight, we hypothesized that adding an ion exchange resin wafer in the diluate compartment would increase the ionic conductivity and decrease the energy demand. Experimental results showed an 18% reduction in specific energy use while achieving the same degree of salt removal (20 mM to 12 mM). Furthermore, the resin wafer enabled complete desalination to potable drinking levels at a current density previously unachievable within practical operating voltage limits (4.93 mA cm -2 ). We also expanded the model to explore differences in r-ED energy use between configurations using multiple cells and a single cell with increased area.
Within the Fermi National Accelerator complex, there exist various water systems that support accelerator operations. One of these systems is extremely vital to the operation of the machine; that is the cooling system. The cooling system consists of nine relatively large heat exchangers that take untreated pond water and use it to cool the process fluid that further cools machine components. Over the 30 years these heat exchangers have been in operation, they have undergone significant material loss on the channels. This material loss, due to various forms of corrosion such as galvanic and microbiologically influenced corrosion (MIC) and possibly others, has deteriorated more than 80% of the nominal wall thickness of some of the exchangers and placed them in a questionable state. ASME FFS-1 (API 579) has been applied to address the condition of the heat exchangers due to their noncompliance with the governing code, BPVC Sec. VIII Div. 1. The assessments encompassed ASME FFS-1 parts 4: General Metal Loss and 9: Crack Like Flaw using level 1, 2, and 3 analysis techniques based on inspection data obtained by API 510 inspections. Level 1 and 2 assessments were deemed unfit for the corroded regions due to their location relative to a major structural discontinuity (channel to tube-sheet joint), so a level 3 analysis was conducted according to ASME Sec. VIII Div. 2 (design by analysis) rules for pressure vessels. Supplemental information included pond water tests to determine an accurate future corrosion allowance due to lacking inspection history. A leak before break (LBB) route was chosen to evaluate the possibility of leaking prior to the onset of failure. The analysis of one heat exchanger shows that the possibility the channel will develop a pinhole leak over 2.5 more years of operation should not be overlooked, but burst was unlikely from operation. The use of fracture mechanics show, that if a through-wall crack were to develop, it would not propagate further than the channel geometry and cause a leak not greater than 35 GPM. Using ASME Section XI Code Case N-705-1, allowing us to operate with a leak until the next outage given certain operating conditions and developing a leak mitigation procedure, this heat exchanger is deemed fit-for-service.
In systems and network neuroscience, many common practices in brain connectomic analysis are often not properly scrutinized. One such practice is mapping a predetermined set of sub-circuits, like functional networks (FNs), onto subjects’ functional connectomes (FCs) without adequately assessing the information-theoretic appropriateness of the partition. Another practice that goes unchallenged is thresholding weighted FCs to remove spurious connections without justifying the chosen threshold. This paper leverages recent theoretical advances in Stochastic Block Models (SBMs) to formally define and quantify the information-theoretic fitness (e.g., prominence) of a predetermined set of FNs when mapped to individual FCs under different fMRI task conditions. Our framework allows for evaluating any combination of FC granularity, FN partition, and thresholding strategy, thereby optimizing these choices to preserve the important topological features of the human brain connectomes. By applying to the Human Connectome Project with Schaefer parcellations at multiple levels of granularity, the framework showed that the common thresholding value of 0.25 was indeed information-theoretically valid for group-average FCs, despite its previous lack of justification. Our results pave the way for the proper use of FNs and thresholding methods, and provide insights for future research in individualized parcellations.
The release of PES-L EARN version 1.0 as an open-source software package for the automatic construction of machine learning models of semi-global molecular potential energy surfaces (PESs) is presented. Improvements to PES-L EARN ’s interoperability are stressed with new Python API that simplifies workflows for PES construction via interaction with QCSchema input and output infrastructure. In addition, a new machine learning method is introduced to PES-L EARN : kernel ridge regression (KRR). The capabilities of KRR are emphasized with examination of select semi-global PESs. All machine learning methods available in PES-L EARN are benchmarked with benzene and ethanol datasets from the rMD17 database to illustrate PES-L EARN ’s performance ability. Fitting performance and timings are assessed for both systems. Finally, the ability to predict gradients with neural network models is presented and benchmarked with ethanol and benzene. PES-L EARN is an active project and welcomes community suggestions and contributions.
We present an efficient implementation of ab initio many-body quantum embedding and local correlation methods for infinite periodic systems through translational symmetry adapted interpolative separable density fitting, an approach which reduces the scaling of the calculations to only linear with the number of k-points. Employing this methodology, we compute correlated ground-state coupled cluster energies within density matrix embedding and local natural orbital correlation frameworks for both weakly and strongly correlated solids, using up to 1000 k-points. By extrapolating the local correlation domains and k-point sampling we further obtain estimates of the full coupled cluster with singles, doubles, and perturbative triples ground-state energies in the thermodynamic limit.
Temperature measurements of black body most closely fitting solar extraterrestrial spectrum
Check valve with a cylindrical flanged tube body is used in standard AN fittings. The valve also has an easily removable spring-loaded piston.
Testing hearing by using speech audiometry to determine word group perception in fitness examinations of flight personnel
Algorithm for summing orthogonal polynomial series and derivatives with applications to curve fitting and interpolation
Body-fitted restraint harness enables workers to safely and conveniently handle critical components during their installation or removal. Since the harness supports the components, the worker is able to maneuver through restricted areas with his hands free. It is easily put on, adjusted, and removed, or comfortably worn without interfering with normal activities.