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At least 1,261 records · Page 70

Fast Semi-automated Filtration Method for Non-targeted LC-QTOF Data of Aged Nitroplasticizer Samples

A full dataset of aged nitroplasticizer (NP) is composed of more than 2000 unique mass-to-charges (m/z) when combining the non-targeted data obtained from both positive and negative electrospray ionization modes in time-of-flight mass spectrometry. Therefore, manual processing of these data often takes days, weeks, or even months to scrutinize for mechanistic insights. To effectively extract meaningful signals that represent vital degradation intermediates in the early NP degradation mechanism, a semi-automated postprocessing workflow for data filtering, tailored to the aging experiment of NP, has been developed. The automated portion of this workflow is written in a Python code (using pandas, numpy, and matplotlib libraries), which removes more than 65% of potential false signals within seconds via four threshold-based adjustable filters: signal sensitivity, coefficient of variation, number of measurements, and retention time variability. As for the manual portion, a pattern-based inspection method is employed to reduce another 23% or more false positives, which greatly simplifies data visualization and results in less than 3% of potential candidate m/z needing in-depth data interpretation. As a positive control, known compounds are verified. Using this semi-automated data reduction method, the amount of time required is reduced to a matter of hours for data filtering in the non-targeted datasets of aged NP, which saves more time and effort for compound identification.

36 MATERIALS SCIENCE↗

Structural principles of distinct assemblies of the human α4β2 nicotinic receptor

Fast chemical communication in the nervous system is mediated by neurotransmitter-gated ion channels. The prototypical member of this class of cell surface receptors is the cation-selective nicotinic acetylcholine receptor. As with most ligand-gated ion channels, nicotinic receptors assemble as oligomers of subunits, usually as hetero-oligomers and often with variable stoichiometries. This intrinsic heterogeneity in protein composition provides fine tunability in channel properties, which is essential to brain function, but frustrates structural and biophysical characterization. The α4β2 subtype of the nicotinic acetylcholine receptor is the most abundant isoform in the human brain and is the principal target in nicotine addiction. This pentameric ligand-gated ion channel assembles in two stoichiometries of α- and β-subunits (2α:3β and 3α:2β). Both assemblies are functional and have distinct biophysical properties, and an imbalance in the ratio of assemblies is linked to both nicotine addiction and congenital epilepsy. Here we leverage cryo-electron microscopy to obtain structures of both receptor assemblies from a single sample. Antibody fragments specific to β2 were used to ‘break’ symmetry during particle alignment and to obtain high-resolution reconstructions of receptors of both stoichiometries in complex with nicotine. Furthermore, the results reveal principles of subunit assembly and the structural basis of the distinctive biophysical and pharmacological properties of the two different stoichiometries of this receptor.

60 APPLIED LIFE SCIENCES↗

Dissociative recombination by frame transformation to Siegert pseudostates: A comparison with a numerically solvable model

Here, we present a simple two-dimensional model of the indirect dissociative recombination process. The model has one electronic and one nuclear degree of freedom and it can be solved to high precision, without making any physically motivated approximations, by employing the exterior complex scaling method together with the finite-elements method and discrete variable representation. The approach is applied to solve a model for dissociative recombination of H 2 + in the singlet ungerade channels, and the results serve as a benchmark to test validity of several physical approximations commonly used in the computational modeling of dissociative recombination for real molecular targets. The second, approximate, set of calculations employs a combination of multichannel quantum defect theory and frame transformation into a basis of Siegert pseudostates. The cross sections computed with the two methods are compared in detail for collision energies from 0 to 2 eV.

74 ATOMIC AND MOLECULAR PHYSICS↗

Cost of Wind Energy Review: 2024 Edition [Slides]

The primary elements of this analysis include: Estimated LCOE for (1) a representative land-based wind energy project installed in a moderate wind resource in the United States, (2) a representative fixed-bottom offshore wind energy project installed in the U.S. North Atlantic, and (3) a representative floating offshore wind energy project installed off the U.S. Pacific Coast. It also updates the LCOE estimates for representative residential-, commercial-, and large-scale distributed wind projects installed in a moderate wind resource in the United States. A sensitivity analyses is included that shows the range of effects that basic LCOE variables could have on the cost of wind energy for land-based and offshore wind projects and provides updated Fiscal Year 2024 values for land-based and offshore wind energy used for Government Performance and Results Act (GPRA) reporting and illustrated progress toward established GPRA targets.

17 WIND ENERGY↗

Collinear Structure Functions of the Nucleon: Status and Future

While our ultimate goal is a complete three-dimensional picture of the nucleon in terms of its fundamental constituents, there are still important lessons to be learned about its “one?dimensional” collinear parton distribution functions (PDFs) like f1(x) and g1(x). There are rigorous proofs for factorization and universality (process independence) which make these PDFs fundamental. They also appear as limits of Generalized Parton Distributions (GPD) and as integrals of transverse momentum-dependent (TMD) parton distribution functions. Experimentally, the unpolarized structure functions F1(x,Q 2 ),F2(x,Q 2 ) have been studied over a huge kinematic range in both variables. Information on the polarized structure functions g1(x,Q 2 ),g2(x,Q 2 ) is somewhat more limited, both in kinematics and in statistical precision. In both cases, much less is known about the neutron than the proton, due to the absence of a free neutron target. Accessing these structure functions at large x (where valence quarks dominate) has been challenging due to the high luminosity and the high resolution required. Finally, much information can be extracted from studying higher twist contributions to these structure functions and the connection between the DIS limit and the region where nucleon resonance excitation dominates. I present an overview of recent experimental results (with special emphasis on the valence region and the transition from quark to hadronic degrees of freedom). I will also give an outlook on the next round of experiments coming online with the energy-upgraded Jefferson Lab electron beam, and future projects like the Electron Ion Collider.

Kuhn, Sebastian E.↗

Arctic Mixed-Phase Cloud Base Ice Precipitation Properties Over the NSA Site

Cloud-climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long-lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud-base properties a more appealing target for inference and evaluation of model simulations. This data set provides more than 1800 samples of cloud-base ice precipitation properties over Utqiagvik, North Slope of Alaska, all of which were retrieved using the synthesis of ARM radar and lidar measurements. The retrieved ice precipitation variables in this data set include, among others, the ice number concentration, water content, PSD parameters, precipitation rate, mass-weighted fall velocity, vertical air motion, and effective radius, all of which are highly valuable for model evaluation and a general understanding of polar cloud sink processes. Each variable sample includes its mean value and associated uncertainty. Additional variables based on ARM measurements (liquid layer statistics, etc.) are included in this data set. The retrieval algorithm and analysis of this data set are described in Silber (JGR, 2023, https://doi.org/10.1029/2022JD038202).

54 ENVIRONMENTAL SCIENCES↗

Bundle Data Approach at GES DISC Targeting Natural Hazards

Severe natural phenomena such as hurricane, volcano, blizzard, flood and drought have the potential to cause immeasurable property damages, great socioeconomic impact, and tragic loss of human life. From searching to assessing the Big, i.e., massive and heterogeneous scientific data (particularly, satellite and model products) in order to investigate those natural hazards, it has, however, become a daunting task for Earth scientists and applications researchers, especially during recent decades. The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has served Big Earth science data, and the pertinent valuable information and services to the aforementioned users of diverse communities for years. In order to help and guide our users to online readily (i.e., with a minimum effort) acquire their requested data from our enormous resource at GES DISC for studying their targeted hazard event, we have thus initiated a Bundle Data approach in 2014, first targeting the hurricane event topic. We have recently worked on new topics such as volcano and blizzard. The bundle data of a specific hazard event is basically a sophisticated integrated data package consisting of a series of proper datasets containing a group of relevant (knowledge--based) data variables readily accessible to users via a system-prearranged table linking those data variables to the proper datasets (URLs). This online approach has been developed by utilizing a few existing data services such as Mirador as search engine; Giovanni for visualization; and OPeNDAP for data access, etc. The online Data Cookbook site at GES DISC is the current host for the bundle data. We are now also planning on developing an Automated Virtual Collection Framework that shall eventually accommodate the bundle data, as well as further improve our management in Big Data.

GES DISC↗

Spectral Characterization of Modern Spacecraft Materials

One of the observational parameters of interest in ground-based optical measurements is ascertaining material properties using broadband filter photometry and spectroscopy for orbiting targets. Broadband photometry can provide reflectance measurements that can aid in color-color indices and assess if objects can be classified into families or taxonomies. However, these reflectance properties can vary due to aspect angle, phase angle, and general degradation of the target’s exterior material. Spectral characterization can aid in material characterization utilizing known absorption bands and spectra signatures, but these signatures are affected by the same conditions described for remote observations. When utilizing ground-based measurements, it is well understood that material characterization is subject to variability due to space weathering and/or other external events (i.e., collision or explosion). The focus of this study is on space weathering effects on spacecraft materials in low Earth orbit. To better assess how materials are affected by the harsh space environment, specifically modern materials, a collection of materials was analyzed in both its pristine condition and after electron bombardment. This sample collection is part of an upcoming mission with the Materials International Space Station Experiment Flight Facility (MISSE-FF) that will be launched in 2022. These laboratory analyses on the samples will provide a ground truth to compare with the in-situ collected data. The data will also be stored in the NASA Johnson Space Center’s Spacecraft Materials Spectral Database that is available to U. S. citizens and maintained by the Orbital Debris Program Office. The following paper provides an overview of the materials investigated, laboratory and database overview, and spectral results for both pristine and post-electron exposed conditions. The spectral signature data highlights which materials are stable, or remain relatively unchanged, and which materials vary significantly due to exposure and material configuration (variations due to rotation of the sample on a flat surface). Initial results on changes in spectral directional reflectance of the materials as a function of incident illumination direction are also presented. This data also will benefit the space situational awareness community with spectral characterization of novel materials that can support their respective optical measurements focused on material identification.

Heather M Cowardin↗

Electrified vehicle DC power conversion with distributed control

An electrified vehicle has a battery pack comprising series-connected battery units providing a main voltage. To supply a lower voltage bus equally from all battery units, a plurality of DC/DC converters are powered by respective units and have their outputs in parallel. A central module has an outer loop controller generating a target current to regulate the bus voltage to a predetermined voltage and has an allocator distributing the target current into a plurality of allocated current commands according to respective states of charge of the battery units. A plurality of local controllers each adjusts a current of a respective DC/DC converter. Each local controller receives a respective allocated current command as a respective feedforward control variable. Each local controller uses an error between the bus voltage and the predetermined voltage to be integrated as a respective feedback control variable only when the error is above a threshold.

33 ADVANCED PROPULSION SYSTEMS↗

Bayesian Inference with Latent Hamiltonian Neural Networks (L-HNNs)

When sampling for Bayesian inference, one popular approach is to use Hamiltonian Monte Carlo (HMC) and the No-U-Turn Sampler (NUTS). However, HMC and NUTS can require numerous numerical gradients of the target density and can prove slow in practice. We propose Hamiltonian neural networks (HNNs) with HMC and NUTS for solving Bayesian inference problems [1, 2]. Once trained, HNNs do not require gradients of the target density while sampling. Moreover, they satisfy important properties such as perfect time reversibility and Hamiltonian conservation, making them well suited for use within HMC and NUTS because stationarity can be shown. We also propose an HNN extension called latent HNNs (L-HNNs), which predict latent variable outputs. Compared to HNNs, L-HNNs offer improved expressivity and a reduction in integration errors. Finally, we propose employing L-HNNs in NUTS with an online error monitoring scheme to prevent degeneracy of the sampling in regions of low probability density. We demonstrate L-HNNs in NUTS with online error monitoring by using several example cases involving complex, heavy-tailed, and high local curvature probability densities. Overall, L-HNNs in NUTS with online error monitoring satisfactorily inferred these probability densities. Compared to traditional NUTS, L-HNNs in NUTS with online error monitoring improved the effective sample size (ESS) per gradient by an order of magnitude.

97 MATHEMATICS AND COMPUTING↗

STITCHES: creating new scenarios of climate model output by stitching together pieces of existing simulations

Abstract. Climate model output emulation has long been attempted to support impact research, mainly to fill in gaps in the scenario space. Given the computational cost of running coupled earth system models (ESMs), which are usually the domain of supercomputers and require on the order of days to weeks to complete a century-long simulation, only a handful of different scenarios are usually chosen to externally force ESM simulations. An effective emulator, able to run on standard computers in times of the order of minutes rather than days could therefore be used to derive climate information under scenarios that were not run by ESMs. Lately, the necessity of accounting for internal variability has also made the availability of initial-condition ensembles, under a specific scenario, important, further increasing the computational demand. At least so far, emulators have been limited to simplified ESM-like output, either seasonal, annual, or decadal averages of basic quantities, like temperature and precipitation, often emulated independently of one another. With this work, we propose a more comprehensive solution to ESM output emulation. Our emulator, STITCHES, uses existing archives of earth system models' (ESMs) scenario experiments to construct ESM-like output under new scenarios or enrich existing initial-condition ensembles, which is what other emulators also aim to do. Importantly, however, STITCHES' output has the same characteristics of the ESM output it sets out to emulate: multivariate, spatially resolved, and high frequency, representing both the forced component and the internal variability around it. STITCHES extends the idea of time sampling – according to which climate outcomes are stratified by the global warming level at which they manifest themselves, irrespective of the scenario and time at which they occur – to the construction of a continuous history of ESM-like output over the whole 21st century, consistent with a 21st-century trajectory of global surface air temperature (GSAT) derived from the scenario that has been chosen as the target of the emulation. STITCHES does so by first splitting the target GSAT trajectory into decade-long windows, then matching each window in turn to a decade-long window within an existing model simulation from the available scenario runs according to its proximity to the target in absolute size of the temperature anomaly and its rate of change. A look-up table is therefore created of a sequence of existing experiment–time-window combinations that, when stitched together, create a GSAT trajectory “similar” to the target. Importantly, we can then stitch together much more than GSAT from these windows, i.e., any output that the ESM has saved for these existing experiment–time-window combinations, at any frequency and spatial scale available in its archive. We show that the stitching does not introduce artifacts in the great majority of cases (we look at temperature and precipitation at monthly frequency and on the native grid of the ESM and at an index of ENSO activity, the Southern Oscillation Index). This is true even if the criteria for the identification of the decades to be stitched together are chosen to work for a smoothed time series of annual GSAT, a result we expect given the larger amount of noise affecting most other variables at finer spatial scales and higher frequencies, which therefore are more “forgiving” of the stitching. We successfully test the method's performance over many ESMs and scenarios. Only a few exceptions surface, but these less-than-optimal outcomes are always associated with a scarcity of the archived simulations from which we can gather the decade-long windows that form the building blocks of the emulated time series. In the great majority of cases, STITCHES' performance is satisfactory according to metrics that reward consistency in trends, interannual and inter-ensemble variance, and autocorrelation structure of the time series stitched together. The method therefore can be used to create ESM-like output according to new scenarios, on the basis of a trajectory of GSAT produced according to that scenario, which could be easily obtained by a simple climate model. It can also be used to increase the size of existing initial-condition ensembles. There are aspects of our emulator that will immediately disqualify it for specific applications, like when climate information is needed whose characteristics result from accumulated quantities over windows of times longer than those used as pieces by STITCHES, droughts longer than a decade for example. But for many applications, we argue that a stitched product can satisfy the climate information needs of impact researchers. STITCHES cannot emulate ESM output from scenarios that result in GSAT trajectories outside of the envelope available in the archive, nor can it emulate trajectories with shapes different from existing ones (overshoots with negative derivative, for example). Therefore, the size and characteristics of the available archives of ESM output are the principal limitations for STITCHES' deployment. Thus, we argue for the possibility of designing scenario experiments within, for example, the next phase of the Coupled Model Intercomparison Project according to new principles, relieved of the need to produce a number of similar trajectories that vary only in radiative forcing strength but more strategically covering the space of temperature anomalies and rates of change.

54 ENVIRONMENTAL SCIENCES↗

Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration

Launched in February 2013, the Landsat-8 carries on-board the Thermal Infrared Sensor (TIRS), a two-band thermal pushbroom imager, to maintain the thermal imaging capability of the Landsat program. The TIRS bands are centered at roughly 10.9 and 12 micrometers (Bands 10 and 11 respectively). They have 100 m spatial resolution and image coincidently with the Operational Land Imager (OLI), also on-board Landsat-8. The TIRS instrument has an internal calibration system consisting of a variable temperature blackbody and a special viewport with which it can see deep space; a two point calibration can be performed twice an orbit. Immediately after launch, a rigorous vicarious calibration program was started to validate the absolute calibration of the system. The two vicarious calibration teams, NASA/Jet Propulsion Laboratory (JPL) and the Rochester Institute of Technology (RIT), both make use of buoys deployed on large water bodies as the primary monitoring technique. RIT took advantage of cross-calibration opportunity soon after launch when Landsat-8 and Landsat-7 were imaging the same targets within a few minutes of each other to perform a validation of the absolute calibration. Terra MODIS is also being used for regular monitoring of the TIRS absolute calibration. The buoy initial results showed a large error in both bands, 0.29 and 0.51 W/sq m·sr·micrometers or -2.1 K and -4.4 K at 300 K in Band 10 and 11 respectively, where TIRS data was too hot. A calibration update was recommended for both bands to correct for a bias error and was implemented on 3 February 2014 in the USGS/EROS processing system, but the residual variability is still larger than desired for both bands (0.12 and 0.2 W/sq m·sr·micrometers or 0.87 and 1.67 K at 300 K). Additional work has uncovered the source of the calibration error: out-of-field stray light. While analysis continues to characterize the stray light contribution, the vicarious calibration work proceeds. The additional data have not changed the statistical assessment but indicate that the correction (particularly in band 11) is probably only valid for a subset of data. While the stray light effect is small enough in Band 10 to make the data useful across a wide array of applications, the effect in Band 11 is larger and the vicarious results suggest that Band 11 data should not be used where absolute calibration is required.

TIIRS↗

Revealing Fast Cu-Ion Transport and Enhanced Conductivity at the CuInP 2 S 6 –In 4/3 P 2 S 6 Heterointerface

Van der Waals layered ferroelectrics, such as CuInP 2 S 6 (CIPS), offer a versatile platform for miniaturization of ferroelectric device technologies. Control of the targeted composition and kinetics of CIPS synthesis enables the formation of stable self-assembled heterostructures of ferroelectric CIPS and nonferroelectric In 4/3 P 2 S 6 (IPS). Here, we use quantitative scanning probe microscopy methods combined with density functional theory (DFT) to explore in detail the nanoscale variability in dynamic functional properties of the CIPS-IPS heterostructure. Within, we report evidence of fast ionic transport which mediates an appreciable out-of-plane electromechanical response of the CIPS surface in the paraelectric phase. Further, we map the nanoscale dielectric and ionic conductivity properties as we thermally stimulate the ferroelectric-paraelectric phase transition, recovering the local dielectric behavior during this phase transition. Finally, aided by DFT, we reveal a substantial and tunable conductivity enhancement at the CIPS/IPS interface, indicating the possibility of engineering its interfacial properties for next generation device applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The interplay of DNA repair context with target sequence predictably biases Cas9-generated mutations

Abstract Repair of double-stranded breaks generated by CRISPR/Cas9 is highly dependent on the flanking DNA sequence. To learn about interactions between DNA repair and target sequence, we measure frequencies of over 236,000 distinct Cas9-generated mutational outcomes at over 2800 synthetic target sequences in 18 DNA repair deficient mouse embryonic stem cells lines. We classify the outcomes in an unbiased way, finding a specialised role forPrkdc(DNA-PKcs protein) andPolmin creating 1 bp insertions matching the nucleotide on the protospacer-adjacent motif side of the break, a variable involvement ofNbnandPolqin the creation of different deletion outcomes, and uni-directional deletions dependent on both end-protection and end-resection. Using our dataset, we build predictive models of the mutagenic outcomes of Cas9 scission that outperform the current standards. This work improves our understanding of DNA repair gene function, and provides avenues for more precise modulation of Cas9-generated mutations.

Science & Technology - Other Topics↗

Angle resolved x-ray photoelectron spectroscopy (ARXPS) analysis of lanthanum oxide for micro-flexography printing

Micro-flexography printing was developed in patterning technique from micron to nano scale range to be used for graphic, electronic and bio-medical device on variable substrates. In this work, lanthanum oxide (La{sub 2}O{sub 3}) has been used as a rare earth metal candidate as depositing agent. This metal deposit was embedded on Carbon (C) and Silica (Si) wafer substrate using Magnetron Sputtering technique. The choose of Lanthanum as a target is due to its wide application in producing electronic devices such as thin film battery and printed circuit board. The La{sub 2}O{sub 3} deposited on the surface of Si wafer substrate was then analyzed using Angle Resolve X-Ray Photoelectron Spectroscopy (ARXPS). The position for each synthetic component in the narrow scan of Lanthanum (La) 3d and O 1s are referred to the electron binding energy (eV). The La 3d narrow scan revealed that the oxide species of this particular metal is mainly contributed by La{sub 2}O{sub 3} and La(OH){sub 3}. The information of oxygen species, O{sup 2-} component from O 1s narrow scan indicated that there are four types of species which are contributed from the bulk (O{sup 2−}), two chemisorb component (La{sub 2}O{sub 3}) and La(OH){sub 3} and physisorp component (OH). Here, it is proposed that from the adhesive and surface chemical properties of La, it is suitable as an alternative medium for micro-flexography printing technique in printing multiple fine solid lines at nano scale. Hence, this paper will describe the capability of this particular metal as rare earth metal for use in of micro-flexography printing practice. The review of other parameters contributing to print fine lines will also be described later.

36 MATERIALS SCIENCE↗

Duty-Cycle Predictive Control of Quasi-Z-Source Modular Cascaded Converter Based Photovoltaic Power System

A duty-cycle predictive control is proposed for dc grid integration of front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The post-stage qZS half-bridge dc-dc converter deals with PV maximum power point tracking, dc grid integration, and dc-link voltage balance; whereas, the front-end isolation converters operate at a constant duty cycle of 50%. Thus, it saves control hardware resources while overcoming challenges from PV-panel voltage variations and dc-bus voltage limit. The proposed control uses the derived circuit model to predict the global active-state duty cycle for grid-connected current control and predict the shoot-through duty cycles for dc-link voltage balance, achieving a fast and accurate tracking target. The proposed control method has advantages of: i) eliminating weighting factors that exist in conventional model predictive control (MPC), ii) no sophisticated loop parameters design that exists in proportional-integral (PI) control, iii) operating at constant switching frequency that is different from the conventional MPC with variable switching frequency. Simulation and experimental tests are carried out to verify the effectiveness of the proposed control method and compare with the PI-based control system.

42 ENGINEERING↗