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DOE OSTI2011

Effect of Energy Efficiency Standards on Natural Gas Prices

A primary justification for the establishment of energy efficiency standards for home appliances is the existence of information deficiencies and externalities in the market for appliances. For example, when a long-term homeowner purchases a new gas-fired water heater, she will maximize the value of her purchase by comparing the life-cycle cost of ownership of available units, including both total installed cost - purchase price plus installation costs - and operating cost in the calculus. Choice of the appliance with the lowest life-cycle costs leads to the most economically efficient balance between capital cost and fuel cost. However, if the purchaser's expected period of ownership is shorter than the useful life of the appliance, or the purchaser does not pay for the fuel used by the appliance, as is often the case with rental property, fuel cost will be external to her costs, biasing her decision toward spending less on fuel efficiency and resulting in the purchase of an appliance with greater than optimal fuel usage. By imposing an efficiency standard on appliances, less efficient appliances are made unavailable, precluding less efficient purchases and reducing fuel usage. The reduction in fuel demanded by residential users affects the total demand for such fuels as natural gas, for example. Reduced demand implies that residential customers are willing to purchase less gas at each price level. That is, the demand curve, labeled D 0 in Figure 1, shifts to the left to D 1 . If there is no change in the supply function, the supply curve will intersect the demand curve at a lower price. Residential demand is only one component of the total demand for natural gas. It is possible that total demand will decline very little if demand in other sectors increases substantially in response to a decline in the price. If demand does decrease, modeling studies generally confirm the intuition that reductions in demand for natural gas will result in reductions in its price as seen at the wellhead (Wiser 2007). The magnitude of the effect on price relative to the demand reduction, and the mechanism through which it occurs, is less well established. This report attempts to quantify the potential effects of reduced demand for natural gas in the residential sector, in response to the implementation of an energy efficiency standard for water heaters.

03 NATURAL GAS↗

DOE OSTI2025

RINO: Renormalization Group Invariance with No Labels

A common challenge with supervised machine learning (ML) in high energy physics (HEP) is the reliance on simulations for labeled data, which can often mismodel the underlying collision or detector response. To help mitigate this problem of domain shift, we propose RINO (Renormalization Group Invariance with No Labels), a self-supervised learning approach that can instead pretrain models directly on collision data, learning embeddings invariant to renormalization group flow scales. In this work, we pretrain a transformer-based model on jets originating from quantum chromodynamic (QCD) interactions from the JetClass dataset, emulating real QCD-dominated experimental data, and then finetune on the JetNet dataset -- emulating simulations -- for the task of identifying jets originating from top quark decays. RINO demonstrates improved generalization from the JetNet training data to JetClass data compared to supervised training on JetNet from scratch, demonstrating the potential for RINO pretraining on real collision data followed by fine-tuning on small, high-quality MC datasets, to improve the robustness of ML models in HEP.

Hao, Zichun [Caltech] (ORCID:0000000256244907)↗

NASA NTRS1992

Nucleotide-Protectable Labeling of Sulfhydryl Groups in Subunit I of the ATPhase from Halobacterium Saccharovorum

A membrane-bound ATPase from the archaebacterium Halobacterium saccharovorum is inhibited by N-ethyl-maleimide in a nucleotide-protectable manner. When the enzyme was incubated with N-[C-14]jethylmaleimide, the bulk of radioactivity was as- sociated with the 87,000-Da subunit (subunit 1). ATP, ADP, or AMP reduced incorporation of the inhibitor. No charge shift of subunit I was detected following labeling with N-ethylmaleimide, indicating an electroneutral reaction. The results are consistent with the selective modification of sulfhydryl groups in subunit I at or near the catalytic site and are further evidence of a resemblance between this archaebacterial ATPase and the vacuolar-type ATPases.

Sulzner, Michael↗

DOE OSTI2022

Automated Shift Detection in Sensor-Based PV Power and Irradiance Time Series

PV power and irradiance sensor-based measurements are prone to error, resulting in issues such as time series data shifts. In this research, a changepoint detection (CPD) algorithm that automatically detects data shifts in sensor-based time series is introduced. Data shift periods in 101 daily PV power and irradiance time series were labeled manually by two solar experts. These data streams represent sensor-based measurements, and display a variety of data shift behaviors. A changepoint detection algorithm was tuned using the 101 labeled data streams, with each model configuration's ability to detect labeled changepoints benchmarked using metrics such as F1-score, recall, and Rand Index. Best performing models on seasonality-corrected data streams include the Pruned Exact Linear (PELT) method, the Binary Segmentation method, and the Bottom-Up method, all scoring an average F1-score of 0.76 or greater at detecting labeled changepoints within a 30-day window across the labeled data sets. Pending approval, we plan to release the labeled data sets for this research on NREL's DuraMAT Data Hub, and the associated algorithm in the Python PVAnalytics package. By supplying the training sets and algorithm, we hope to encourage further development in this research space.

data shift↗

NASA NTRS2001

Culturability as an indicator of succession in microbial communities

Successional theory predicts that opportunistic species with high investment of energy in reproduction and wide niche width will be replaced by equilibrium species with relatively higher investment of energy in maintenance and narrower niche width as communities develop. Since the ability to rapidly grow into a detectable colony on nonselective agar medium could be considered as characteristic of opportunistic types of bacteria, the percentage of culturable cells may be an indicator of successional state in microbial communities. The ratios of culturable cells (colony forming units on R2A agar) to total cells (acridine orange direct microscopic counts) and culturable cells to active cells (reduction of 5-cyano-2,3-ditolyl tetrazolium chloride) were measured over time in two types of laboratory microcosms (the rhizosphere of hydroponically grown wheat and aerobic, continuously stirred tank reactors containing plant biomass) to determine the effectiveness of culturabilty as an index of successional state. The culturable cell:total cell ratio in the rhizosphere decreased from approximately 0.25 to less than 0.05 during the first 30-50 days of plant growth, and from 0.65 to 0.14 during the first 7 days of operation of the bioreactor. The culturable cell:active cell ratio followed similar trends, but the values were consistently greater than the culturable cell:total cell ratio, and even exceeded I in early samples. Follow-up studies used a cultivation-independent method, terminal restriction fragment length polymorphisms (TRFLP) from whole community DNA, to assess community structure. The number of TRFLP peaks increased with time, while the number of culturable types did not, indicating that the general decrease in culturability is associated with a shift in community structure. The ratio of respired to assimilated C-14-labeled amino acids increased with the age of rhizosphere communities, supporting the hypothesis that a shift in resource allocation from growth to maintenance occurs with time. Results from this work indicate that the percentage of culturable cells may be a useful method for assessing the successional state of microbial communities.

NASA Center KSC↗

DOE OSTI2020

Distinguishing Potassium Channel Resting State Conformations in Live Cells with Environment-Sensitive Fluorescence

Ion channels are polymorphic membrane proteins whose high-resolution structures offer images of individual conformations, giving us starting points for identifying the complex and transient allosteric changes that give rise to channel physiology. Here, we report live-cell imaging of voltage-dependent structural changes of voltage-gated Kv2.1 channels using peptidyl tarantula toxins labeled with an environment-sensitive fluorophore, whose spectral shifts enable identification of voltage-dependent conformation changes in the resting voltage sensing domain (VSD) of the channel. We synthesize a new environment-sensitive, far-red fluorophore, julolidine phenoxazone (JP) azide, and conjugate it to tarantula toxin GxTX to characterize Kv2.1 VSD allostery during membrane depolarization. JP has an inherent response to the polarity of its immediate surroundings, offering site-specific structural insight into each channel conformation. Using voltage-clamp spectroscopy to collect emission spectra as a function of membrane potential, we find that they vary with toxin labeling site, the presence of Kv2 channels, and changes in membrane potential. With a high-affinity conjugate in which the fluorophore itself interacts closely with the channel, the emission shift midpoint is 50 mV more negative than the Kv2.1 gating current midpoint. This suggests that substantial conformational changes at the toxin-channel interface are associated with early gating charge transitions and these are not concerted with VSD motions at more depolarized potentials. These fluorescent probes enable study of conformational changes that can be correlated with electrophysiology, putting channel structures and models into a context of live-cell membranes and physiological states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Peptides derived from human galectin-3 N-terminal tail interact with its carbohydrate recognition domain in a phosphorylation-dependent manner

Highlights: •Galectin-3 is composed of a carbohydrate recognition domain and an N-terminal tail. •Synthetic peptides derived from the tail are shown to interact with the CRD. •This interaction is modulated by Ser- and Tyr-phosphorylation of the peptides. -- Abstract: Galectin-3 (Gal-3) is a multi-functional effector protein that functions in the cytoplasm and the nucleus, as well as extracellularly following non-classical secretion. Structurally, Gal-3 is unique among galectins with its carbohydrate recognition domain (CRD) attached to a rather long N-terminal tail composed mostly of collagen-like repeats (nine in the human protein) and terminating in a short non-collagenous terminal peptide sequence unique in this lectin family and not yet fully explored. Although several Ser and Tyr sites within the N-terminal tail can be phosphorylated, the physiological significance of this post-translational modification remains unclear. Here, we used a series of synthetic (phospho)peptides derived from the tail to assess phosphorylation-mediated interactions with {sup 15}N-labeled Gal-3 CRD. HSQC-derived chemical shift perturbations revealed selective interactions at the backface of the CRD that were attenuated by phosphorylation of Tyr 107 and Tyr 118, while phosphorylation of Ser 6 and Ser 12 was essential. Controls with sequence scrambling underscored inherent specificity. Our studies shed light on how phosphorylation of the N-terminal tail may impact on Gal-3 function and prompt further studies using phosphorylated full-length protein.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Insight into small molecule binding to the neonatal Fc receptor by X-ray crystallography and 100 kHz magic-angle-spinning NMR

Aiming at the design of an allosteric modulator of the neonatal Fc receptor (FcRn)–Immunoglobulin G (IgG) interaction, we developed a new methodology including NMR fragment screening, X-ray crystallography, and magic-angle-spinning (MAS) NMR at 100 kHz after sedimentation, exploiting very fast spinning of the nondeuterated soluble 42 kDa receptor construct to obtain resolved proton-detected 2D and 3D NMR spectra. FcRn plays a crucial role in regulation of IgG and serum albumin catabolism. It is a clinically validated drug target for the treatment of autoimmune diseases caused by pathogenic antibodies via the inhibition of its interaction with IgG. We herein present the discovery of a small molecule that binds into a conserved cavity of the heterodimeric, extracellular domain composed of an α-chain and β2-microglobulin (β2m) (FcRnECD, 373 residues). X-ray crystallography was used alongside NMR at 100 kHz MAS with sedimented soluble protein to explore possibilities for refining the compound as an allosteric modulator. Proton-detected MAS NMR experiments on fully protonated [ 13 C, 15 N]-labeled FcRnECD yielded ligand-induced chemical-shift perturbations (CSPs) for residues in the binding pocket and allosteric changes close to the interface of the two receptor heterodimers present in the asymmetric unit as well as potentially in the albumin interaction site. X-ray structures with and without ligand suggest the need for an optimized ligand to displace the α-chain with respect to β2m, both of which participate in the FcRn ECD –IgG interaction site. Our investigation establishes a method to characterize structurally small molecule binding to nondeuterated large proteins by NMR, even in their glycosylated form, which may prove highly valuable for structure-based drug discovery campaigns.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2003

Quantum dots as strain- and metabolism-specific microbiological labels

Biologically conjugated quantum dots (QDs) have shown great promise as multiwavelength fluorescent labels for on-chip bioassays and eukaryotic cells. However, use of these photoluminescent nanocrystals in bacteria has not previously been reported, and their large size (3 to 10 nm) makes it unclear whether they inhibit bacterial recognition of attached molecules and whether they are able to pass through bacterial cell walls. Here we describe the use of conjugated CdSe QDs for strain- and metabolism-specific microbial labeling in a wide variety of bacteria and fungi, and our analysis was geared toward using receptors for a conjugated biomolecule that are present and active on the organism's surface. While cell surface molecules, such as glycoproteins, make excellent targets for conjugated QDs, internal labeling is inconsistent and leads to large spectral shifts compared with the original fluorescence, suggesting that there is breakup or dissolution of the QDs. Transmission electron microscopy of whole mounts and thin sections confirmed that bacteria are able to extract Cd and Se from QDs in a fashion dependent upon the QD surface conjugate.

NASA Center JPL↗

NASA NTRS2000

H, C, N, and O Isotopic Substitution Studies of the 2165 cm (4.62 micron) "XCN" Feature Produced by UV Photolysis of Mixed Molecular Ices

To better understand the chemical species that gives rise to the 2165/cm (4.62 micron) "XCN" absorption feature seen towards embedded protostars such as W33A, we have performed laboratory studies using deuterium (H-2) isotopic labeling. We report the observation of a small but significant deuterium isotope shift for the "XCN" peak which demonstrates that the atomic motion(s) causing the "XCN" band in the laboratory samples must involve hydrogen. We also report the results of C-13, N-15 and O-18 labeling experiments that are consistent with previously reported values.

Bernstein, Max P.↗

DOE OSTI2010

Conformational Exchange in a Membrane Transport Protein Is Altered in Protein Crystals

Successful macromolecular crystallography requires solution conditions that may alter the conformational sampling of a macromolecule. Here, site-directed spin labeling is used to examine a conformational equilibrium within BtuB, the Escherichia coli outer membrane transporter for vitamin B{sub 12}. Electron paramagnetic resonance (EPR) spectra from a spin label placed within the N-terminal energy coupling motif (Ton box) of BtuB indicate that this segment is in equilibrium between folded and unfolded forms. In bilayers, substrate binding shifts this equilibrium toward the unfolded form; however, EPR spectra from this same spin-labeled mutant indicate that this unfolding transition is blocked in protein crystals. Moreover, crystal structures of this spin-labeled mutant are consistent with the EPR result. When the free energy difference between substates is estimated from the EPR spectra, the crystal environment is found to alter this energy by 3 kcal/mol when compared to the bilayer state. Approximately half of this energy change is due to solutes or osmolytes in the crystallization buffer, and the remainder is contributed by the crystal lattice. These data provide a quantitative measure of how a conformational equilibrium in BtuB is modified in the crystal environment, and suggest that more-compact, less-hydrated substates will be favored in protein crystals.

36 MATERIALS SCIENCE↗

DOE OSTI2015

The generation of arbitrary order, non-classical, Gauss-type quadrature for transport applications

A method is presented, based upon the Stieltjes method (1884), for the determination of non-classical Gauss-type quadrature rules, and the associated sets of abscissae and weights. The method is then used to generate a number of quadrature sets, to arbitrary order, which are primarily aimed at deterministic transport calculations. The quadrature rules and sets detailed include arbitrary order reproductions of those presented by Abu-Shumays in [4,8] (known as the QR sets, but labelled QRA here), in addition to a number of new rules and associated sets; these are generated in a similar way, and we label them the QRS quadrature sets. The method presented here shifts the inherent difficulty (encountered by Abu-Shumays) associated with solving the non-linear moment equations, particular to the required quadrature rule, to one of the determination of non-classical weight functions and the subsequent calculation of various associated inner products. Once a quadrature rule has been written in a standard form, with an associated weight function having been identified, the calculation of the required inner products is achieved using specific variable transformations, in addition to the use of rapid, highly accurate quadrature suited to this purpose. The associated non-classical Gauss quadrature sets can then be determined, and this can be done to any order very rapidly. In this paper, instead of listing weights and abscissae for the different quadrature sets detailed (of which there are a number), the MATLAB code written to generate them is included as Appendix D. The accuracy and efficacy (in a transport setting) of the quadrature sets presented is not tested in this paper (although the accuracy of the QRA quadrature sets has been studied in [12,13]), but comparisons to tabulated results listed in [8] are made. When comparisons are made with one of the azimuthal QRA sets detailed in [8], the inherent difficulty in the method of generation, used there, becomes apparent, with the highest order tabulated sets showing unexpected anomalies. Although not in an actual transport setting, the accuracy of the sets presented here is assessed to some extent, by using them to approximate integrals (over an octant of the unit sphere) of various high order spherical harmonics. When this is done, errors in the tabulated QRA sets present themselves at the highest tabulated orders, whilst combinations of the new QRS quadrature sets offer some improvements in accuracy over the original QRA sets. Finally, in order to offer a quick, visual understanding of the various quadrature sets presented, when combined to give product sets for the purposes of integrating functions confined to the surface of a sphere, three-dimensional representations of points located on an octant of the unit sphere (as in [8,12]) are shown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Large Scale Unsupervised Domain Adaptation of Segmentation Networks with Adversarial Learning

Most current state-of-the-art methods for semantic segmentation on remote sensing imagery require large labeled data, which is scarcely available. Due to the distribution shifting phenomenon inherent in remote sensing imagery, the reuse of pre-trained models on new areas of interest rarely yield satisfactory results. In this paper, we approach this problem from an adversarial learning perspective toward unsupervised domain adaptation. The core concept is to infuse fully convolutional neural networks and adversarial networks for semantic segmentation assuming the structures in the scene and objects of interest are similar in two set of images. Models are trained on a source dataset where ground truth is available and adapted to new target dataset iteratively via a adversarial loss on unlabeled samples. We use two real large scale datasets to validate the framework: 1) cross city road extraction and 2) cross country building extraction. The preliminary results show the usefulness of considering adversarial learning for indirect re-use of the pre-trained models. Experimental validation suggests significant benefits over models without adaptation.

Deng, Xueqing↗

DOE OSTI2011

Conformational Exchange in a Membrane Transport Protein Is Altered in Protein Crystals

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2023

Leveraging Automated Fiber Placement Computer Aided Process Planning Framework for Defect Validation and Dynamic Layup Strategies

Process planning represents an essential stage of the Automated Fiber Placement (AFP) workflow. It develops useful and efficient machine processes based upon the working material, composite design, and manufacturing resources. The current state of process planning requires a high degree of interaction from the process planner and could greatly benefit from increased automation. Therefore, a list of key steps and functions are created to identify the more difficult and time-consuming phases of process planning. Additionally, a set of metrics must exist by which to evaluate the effectiveness of the manufactured laminate from the machine code created during the Process Planning stage. Layup strategies, in addition to dog ears, stagger shifts, steering constraints, and starting points, represented the group of functions labeled as process optimization and ranked the highest in terms of priority for automation. The laminates resulting from the selected parameters are evaluated through the occurrences of principal defect metrics such as fiber gaps, overlaps, angle deviation and steering violations. This document presents an automated software solution to the layup strategy and starting point selection phase of process planning. A series of ply scenarios are generated with variations of these ply parameters and evaluated according to a set of metrics entered by the Process Planner. These metrics are generated through use of the Analytical Hierarchy Process (AHP), where relative importance between each of the fiber features are defined. The ply scenarios are selected which reduce the overall fiber feature scores based on the defects the Process Planner wishes to minimize.

HiCAM↗

DOE OSTI2022

Deep transfer operator learning for partial differential equations under conditional shift

Transfer learning enables the transfer of knowledge gained while learning to perform one task (source) to a related but different task (target), hence addressing the expense of data acquisition and labelling, potential computational power limitations and dataset distribution mismatches. Here, we propose a new transfer learning framework for task-specific learning (functional regression in partial differential equations) under conditional shift based on the deep operator network (DeepONet). Task-specific operator learning is accomplished by fine-tuning task-specific layers of the target DeepONet using a hybrid loss function that allows for the matching of individual target samples while also preserving the global properties of the conditional distribution of the target data. Inspired by conditional embedding operator theory, we minimize the statistical distance between labelled target data and the surrogate prediction on unlabelled target data by embedding conditional distributions onto a reproducing kernel Hilbert space. We demonstrate the advantages of our approach for various transfer learning scenarios involving nonlinear partial differential equations under diverse conditions due to shifts in the geometric domain and model dynamics. Our transfer learning framework enables fast and efficient learning of heterogeneous tasks despite considerable differences between the source and target domains.

42 ENGINEERING↗

DOE OSTI2019

Uniformly 15N-Labeled Recombinant Ricin A-chain as an Internal Retention Time Standard for Increased Confidence in Forensic Identification of Ricin by Untargeted Nanoflow Liquid Chromatography-Tandem Mass Spectrometry

Ricin, a toxic protein from the castor plant, is of forensic and biosecurity interest because of its high toxicity and common occurrence in crimes and attempted crimes. Qualitative methods to detect ricin are therefore needed. Untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics methods are well-suited because of their high speci-ficity. Specificity in LC-MS/MS comes from both the LC and MS components. However, modern untargeted proteomics methods often use nanoflow LC, which has less reproducible retention times than standard-flow LC, making it challenging to use retention time as a point of identification in a forensic assay. We address this challenge by using retention times rela-tive to a standard, namely uniformly 15N–labeled ricin A-chain produced recombinantly in a bacterial expression system. This material, added as an internal standard prior to trypsin digestion, produces a stable isotope labeled standard for every ricin tryptic peptide in the sample. We show that the MS signals for 15N and natural isotopic abundance ricin peptides are distinct, with mass shifts that correspond to the numbers of nitrogen atoms in each peptide or fragment. We also show that, as expected, labeled and unlabeled peptides coelute, with relative retention time differences of less than 0.2%.

ricin, mass spectrometry, isotope, nitrogen-15, re↗

DOE OSTI2025

A Thorough Characterization of the Tellurocyanate Anion

Tellurocyanate, [TeCN] − , is the heaviest group 16 congener of the cyanate anion, [OCN] − . Due to the relative instability of the C─Te bond, tellurocyanate chemistry has seen only scarce attention. Here, we present the facile synthesis and thorough characterization of [K@crypt-222][TeCN]. The anion is essentially linear with interatomic distances C─N = 1.150(6)Å and C─Te = 2.051(4)Å, thus approximating a C≡N triple bond and for C─Te a bond order between 1 and 2. Fully 13 C and 15 N labeled [Te 13 C 15 N] − allowed for the extraction of chemical shifts and all possible coupling constants ( 13 C = 77.8 ppm, 15 N = 285.7 ppm, 125 Te = −566 ppm, 1 J 13C-15N = 8 Hz, 1 J 13C-125Te = 748 Hz, 2 J1 5N-125Te = 55 Hz), which were also determined independently by quantum chemical calculations. In the series [ChCN] − (Ch = O─Te), [TeCN] − shows the strongest spin-orbit coupling (SOC) induced heavy-atom effect on the light-atom shielding (SO-HALA-effect). In contrast, 15 N shifts are also well described without considering relativistic effects and/or SOC. Negative-ion photoelectron spectroscopy was used to extract the electron affinity (EA = 3.034 eV) and spin-orbit splitting (3807 cm −1 ) of [TeCN] • . These values continue the trends of falling EA and rising SOC in the series [ChCN] • .

Bonding analysis↗