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Geometry and Unoccupied Electronic States of Ba and BaO on W(001)

A study aimed at understanding the geometrical and electronic properties of barium and oxygen coadsorbed on the tungsten(001) surface has been carried out by means of work-function measurements (Delta-phi), Auger-electron spectroscopy, low-energy electron diffraction, inverse photoelectron spectroscopy, and relativistic-electronic-structure calculations. A report of the experimental measurements and a comparison with theoretical results from embedded-cluster-model calculations are presented. Our experimental studies show that the work function of the W(001) surface (phi = 4.63 eV) is lowered to approximately 2.3-2.4 eV by coadsorption of 1 ML of Ba and O regardless of the order of deposition of these two species. The technique of IPS in the isochromat mode was used to determine the unoccupied electronic-energy band structure for ordered c (2 X 2) Ba and O layers on W(001). Several spectral features are observed above the Fermi level (E(F)), which we assign to transitions into Ba and W d-states. The measured two-dimensional electronic band structure is independent of the order of Ba and O deposition. Using embedded-cluster-model calculations, we investigated two possible adsorption configurations of an ordered c(2 X 2) adlayer of Ba and O on W(001): 'tilted,' where Ba and O are placed on alternate fourfold-hollow sites, and 'upright,' where the adsorbed atoms lay above the same site with Ba outer-most. The calculated densities of states for the tilted geometry show distinct peaks above E(F) originating from Ba and W d-orbitals and are in good agreement with the experimental results.

Lamouri, A.↗

Safety and antiviral activity of triple combination broadly neutralizing monoclonal antibody therapy against HIV-1: a phase 1 clinical trial

HIV-1 therapy with single or dual broadly neutralizing antibodies (bNAbs) has shown viral escape, indicating that at least a triple bNAb therapy may be needed for robust suppression of viremia. We performed a two-part study consisting of a single-center, randomized, double-blind, dose-escalation, placebo-controlled first-in-human trial of the HIV-1 V2-glycan-specific antibody PGDM1400 alone or in combination with the V3-glycan-specific antibody PGT121 in 24 adults without HIV in part 1, as well as a multi-center, open-label trial of the combination of PGDM1400, PGT121 and the CD4-binding-site antibody VRC07-523LS in five viremic adults living with HIV not on antiretroviral therapy (ART) in part 2. The primary endpoints were safety, tolerability and pharmacokinetics for both parts and antiviral activity among viremic adults living with HIV and not on ART for part 2 of the study. The secondary endpoints were changes in CD4 + T cell counts and development of HIV-1 sequence variations associated with PGDM1400, PGT121 and VRC07-523LS resistance in part 2. Intravenously administered PGDM1400 was safe and well-tolerated at doses up to 30 mg kg -1 and when given in combination with PGT121 and VRC07-523LS. A single intravenous infusion of 20 mg kg -1 of each of the three antibodies reduced plasma HIV RNA levels in viremic individuals by a maximum mean of 2.04 log10 copies per ml; however, viral rebound occurred in all participants within a median of 20 days after nadir. Rebound viruses demonstrated partial to complete resistance to PGDM1400 and PGT121 in vitro, whereas susceptibility to VRC07-523LS was preserved. Viral rebound occurred despite mean VRC07-523LS serum concentrations of 93 µg ml -1 . The trial met the pre-specified endpoints. Our data suggest that future bNAb combinations likely need to achieve broad antiviral activity, while also maintaining high serum concentrations, to mediate viral control.

60 APPLIED LIFE SCIENCES↗

Alkaline-SDS cell lysis of microbes with acetone protein precipitation for proteomic sample preparation in 96-well plate format

Plate-based proteomic sample preparation offers a solution to the large sample throughput demands in the biotechnology field where hundreds or thousands of engineered microbes are constructed for testing is routine. Meanwhile, sample preparation methods that work efficiently on broader microbial groups are desirable for new applications of proteomics in other fields, such as microbial communities. Here, we detail a step-by-step protocol that consists of cell lysis in an alkaline chemical buffer (NaOH/SDS) followed by protein precipitation with high-ionic strength acetone in 96-well format. The protocol works for a broad range of microbes ( e . g ., Gram-negative bacteria, Gram-positive bacteria, non-filamentous fungi) and the resulting proteins are ready for tryptic digestion for bottom-up quantitative proteomic analysis without the need for desalting column cleanup. The yield of protein using this protocol increases linearly with respect to the amount of starting biomass from 0.5–2.0 OD*mL of cells. By using a bench-top automated liquid dispenser, a cost-effective and environmentally-friendly option to eliminating pipette tips and reducing reagent waste, the protocol takes approximately 30 minutes to extract protein from 96 samples. Tests on mock mixtures showed expected results that the biomass composition structure is in close agreement with the experimental design. Lastly, we applied the protocol for the composition analysis of a synthetic community of environmental isolates grown on two different media. This protocol has been developed to facilitate rapid, low-variance sample preparation of hundreds of samples and allow flexibility for future protocol development.

59 BASIC BIOLOGICAL SCIENCES↗

Large-scale experimental validation of thermochemical water-splitting oxides discovered by defect graph neural networks

Thermochemical water-splitting (TCH) based on 2-step thermal redox cycles in metal oxides is a promising approach to generating H 2 , but state-of-the-art (SOTA) CeO 2 has several practical limitations, which has motivated continued materials discovery efforts in this field. Here, in this study, we improve upon a SOTA defect graph neural network (dGNN) surrogate model's oxygen vacancy predictions and combine them with materials project phase diagrams to down-select and discover structurally diverse, experimentally known metal oxides whose TCH performance was previously unknown. Amongst twelve candidates selected based on our high-throughput screening and down-selection criteria, we achieved ∼80% accuracy in identifying materials with stable redox cycling and hydrogen production in stagnation flow reactor water-splitting experiments. Closer to 100% accuracy can be achieved if higher-accuracy, hybrid DFT-predicted vacancy formation energies were computed and used in lieu of the most uncertain dGNN-based screening predictions, as they correct false positives to true negatives. Notably, two discovered candidates, Sr 3 PrMn 2 O 8 and Ba 2 Fe 2 O 5 , display hydrogen yields greater than CeO 2 under specific redox conditions. In conclusion, these results demonstrate our ability to computationally predict and experimentally validate promising candidate TCH materials that have the potential to compete with CeO 2 .

08 HYDROGEN↗

A Field Guide to Corralling the Chaos: A Conceptual Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long-term monitoring are often constrained by scope, and opportunistic studies often lack pre-disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre-disturbance data collection is not a feasible option. To address this gap, we present a conceptual framework that intentionally integrates modeling and empirical observation in an iterative, stepwise model–experiment workflow. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre-disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an ‘ex-post-facto’ approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path towards more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience.

Coastal Biogeochemistry↗

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗

KG-Hub—building and exchanging biological knowledge graphs

Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract–transform–load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial–environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification.

59 BASIC BIOLOGICAL SCIENCES↗

Fusion of Test and Analysis: Artemis I Booster to Mobile Launcher Interface Validation

NASA is in the midst of bold and exciting next steps in human exploration and spaceflight. The designs of the new Space Launch System (SLS), the Orion spacecraft and the Exploration Ground Systems (EGS) for vehicle processing and launch are essentially complete and there has been significant progress in manufacturing and assembly of specific hardware for the Artemis I and Artemis II missions. Equally as important, the program level and integrated system level testing and analyses are also well underway to support integrated verification, validation, and Certificate of Flight Readiness (CoFR) for Artemis I. Testing and analysis are key to addressing technical challenges faced by the Artemis missions. Building block approaches are required that provide the right balance between component, element, and/or system level testing that satisfies verification and validation objectives where uncertainties are quantified and minimized. Artemis I is a system of systems that requires a fusion of test and analysis that adeptly characterizes critical interfaces between major program elements. An example of this fusion involves characterizing the interface between the SLS booster and the Mobile Launcher (ML) Vertical Support Post (VSP) interfaces. Proper characterization of this interface represents a number of challenges beginning with the fact that it is a mating of ground support structure in the form of a civil structure to flight hardware. Both sides of the interface are built to different construction standards, but are governed by interface requirements to ensure compatibility when mated. From past program experience, the flexibility at the booster to ML interface is critical in developing accurate prelaunch stacking and cryogenic preloads, squat loads, and pad separation release of preloads and squat loads. This same premise holds for Artemis I. To characterize the asymmetric characteristics at this interface, careful consideration of static forces due to gravity loading with the commensurate effects due to leveling during booster stacking (i.e., spacing and shimming) and nonlinear geometric forces are necessary for inclusion in pre-test assessments. This paper will look at these issues for the upcoming Booster Pull Test in which two boosters will be installed on the ML and one of these boosters will undergo static lateral loading followed afterwards with dynamic excitation into resonance and free-decay. This paper evaluates the booster to ML interface characteristics by characterizing the interface flexibility between the booster aft skirt and the ML VSP interfaces. Furthermore, this paper methodically evaluates the effect of the following on the test outcome: gravitational effects on the booster and ML, the effects of VSP leveling, spacing, and shimming under gravitational loading during booster stacking, the effect of geometric nonlinear follower force due to cg offset as booster is laterally displaced, and the system coupling between the booster under test, ML, and the second booster. Simulated results for a static load pull and dynamic excitation provide insight into the differences in measurement responses when boundary conditions and geometric conditions are included and not included.

Joel W Sills Jr.↗

An Assessment of Machine Learning Applied to Ultrasonic Nondestructive Evaluation

In the United States, the nuclear industry performs inservice inspection (ISI) through nondestructive examination (NDE) methods in accordance with guidelines specified in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section XI, Rules for Inservice Inspection of Nuclear Power Plant Components. Ultrasonic nondestructive testing and evaluation (NDT&E) is one of the more commonly used techniques for inspecting Class 1 structural components in nuclear power systems. As the number of qualified NDE inspectors declines, the nuclear industry is looking to take advantage of advances in automation to enhance inspection capabilities. Advances in computational power, cloud-based computing, and machine learning algorithms make automated data analysis possible. Machine learning (ML) has shown huge potential in automated data analyses for ultrasonic NDE in the context of weld inspections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Observations and Parameterizations of Particle Size Distributions in Deep Tropical Cirrus and Stratiform Precipitation Clouds: Results from In-Situ Observations in TRMM Field Campaigns

In this study, we report on the evolution of particle size distributions (PSDs) and habits as measured during slow, Lagrangian-type spiral descents through deep subtropical and tropical cloud layers in Florida, Brazil, and Kwajalein, Marshall Islands, most of which were precipitating. The objective of the flight patterns was to learn more about how the PSDs evolved in the vertical and to obtain information of the vertical structure of microphysical properties. New instrumentation yielding better information on the concentrations of particles in the size (D) range between 0.2 and 2 cm, as well as improved particle imagery, produced more comprehensive observations for tropical stratiform precipitation regions and anvils than have been available previously. Collocated radar observations provided additional information on the vertical structure of the cloud layers sampled. Most of the spirals began at cloud top, with temperatures (T) as low as -50 C, and ended at cloud base or below the melting layer (ML). The PSDs broadened from cloud top towards cloud base, with the largest particles increasing in size from several millimeters at cloud top to one centimeter or larger towards cloud base. Some continued growth was noted in the upper part of the ML. Concentrations of particles less than 1 mm in size decreased with decreasing height. The result was a consistent change in the PSDs in the vertical. Similarly, systematic changes in the size dependence of the particle cross-sectional area was noted with decreasing height. Aggregation-as ascertained from both the changes in the PSDs and evolution of particle habits as observed in high detail with the cloud particle imager (CPI) probe-was responsible for these trends. The PSDs were generally well-represented by gamma distributions of the form N = N0 gamma D microns e- lambda gamma D that were fitted to the PSDs over 1-km horizontal intervals throughout the spirals. The intercept (N0 gamma), slope (lambda gamma), and dispersion (microns) values were derived for each PSD. Exponential curves (N = N0e- lambdaD; micron = 0) were also fitted to the distributions. The lambda gamma values for given spirals varied systematically with temperature as did the values of lambda (exponential), and the data generally conformed to values found in previous studies involving exponential fits to size distributions in mid-latitude frontal and cirrus layers. Considerable variability often noted in the PSD properties during the loops of individual spirals was manifested primarily in large changes in N0 gamma and N0, but micron, lambda gamma and lambda remained fairly stable. Temperature is not found to be the sole factor controlling lambda gamma or lambda but is a primary one. Direct relationships were found between lambda gamma and N0 gamma or lambda gamma and micron for the gamma distributions and lambda and N0 for the exponential. The latter relationship was not found as distinctly in earlier studies; observed PSDs in this study had better fidelity with less scatter. The micron values changed monotonically with T over the range of temperatures and were directly related to N0 gamma or lambda gamma, thereby reducing the number of variables in the PSD functional equation to two. In the upper part of the ML, N0 and lambda continued to decrease, and in the lower part these values began to increase as the largest particles melted. We developed general expressions relating various bulk microphysical, radar, and radiative transfer-related variables to N0 gamma and lambda gamma, useful for both tropical and mid-latitude clouds. These relationships facilitate the specification of a number of bulk properties in cloud and climate models. The results presented in this paper apply best to temperatures between 0 and -40 C, for which the measured radar reflectivities fall in the range of 0 to 25 dBZe.

Heymsfield, Andrew J.↗

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

Uzun-Kaymak, I. U. (ORCID:0000000276251493)↗

Phosphate binding protein as the biorecognition element in a biosensor for phosphate

This work explores the potential use of a member of the periplasmic family of binding proteins, the phosphate binding protein (PBP), as the biorecognition element in a sensing scheme for the detection of inorganic phosphate (Pi). The selectivity of this protein originates from its natural role which, in Escherichia coli, is to serve as the initial receptor for the highly specific translocation of Pi to the cytoplasm. The single polypeptide chain of PBP is folded into two similar domains connected by three short peptide linkages that serve as a hinge. The Pi binding site is located deep within the cleft between the two domains. In the presence of the ligand, the two globular domains engulf the former in a hinge-like manner. The resultant conformational change constitutes the basis of the sensor development. A mutant of PBP (MPBP), where an alanine was replaced by a cysteine residue, was prepared by site-directed mutagenesis using the polymerase chain reaction (PCR). The mutant was expressed, from plasmid pSD501, in the periplasmic space of E. coli and purified in a single chromatographic step on a perfusion anion-exchange column. Site-specific labeling was achieved by attaching the fluorophore, N-[2-(1-maleimidyl)ethyl]-7-(diethylamino)coumarin-3-carboxamide (MDCC), to the protein through the sulfhydryl group of the cysteine moiety. Steady-state fluorescence studies of the MPBP-MDCC conjugate showed a change in the intensity of the signal upon addition of Pi. Calibration curves for Pi were constructed by relating the intensity of the fluorescence signal with the amount of analyte present in the sample. The sensing system was first developed and optimized on a spectrofluorometer using ml volumes of sample. It was then adapted to be used on a microtiter plate arrangement with microliter sample volumes. The system's versatility was finally proven by developing a fiber optic fluorescence-based sensor for monitoring Pi. In all three cases the detection limits for the analyte were in the sub-microMolar range. It was also demonstrated that the sensing system was selective for phosphate over other structurally-similar anions, paving the way for the design and development of a new family of biosensors utilizing the specific binding properties of periplasmic proteins. c2003 Elsevier B.V. All rights reserved.

NASA Program Fundamental Space Biology↗

On the 2018 Outburst of the Accreting Millisecond X-Ray Pulsar Swift J1756.9-2508 As Seen with NICER

We report on the coherent timing analysis of the 182 Hz accreting millisecond X-ray pulsar SwiftJ1756.92508during its 2018 outburst as observed with the Neutron Star Interior Composition Explorer (NICER). Combiningour NICER observations with Rossi X-ray Timing Explorer observations of the 2007 and 2009 outbursts, we alsostudied the long-term spin and orbital evolution of this source. We find that the binary system is well describedby a constant orbital period model, with an upper limit on the orbital period derivative of Pb < 7.4 ´ 10-13 ss1.Additionally, we improve upon the source coordinates through astrometric analysis of the pulse arrival times,finding R.A.=17h56m57 18±0 08 and decl.=25°0627 8±3 5, while simultaneously measuring thelong-term spin frequency derivative as n = -7.3 ´ 10-16 Hzs1. We briefly discuss the implications of thesemeasurements in the context of the wider population of accreting millisecond pulsars. We reported on the coherent timing analysis of the 2018 outburst of Swift J1756 as observed with NICER. Consistent with analyses of the previous outbursts (Krimm et al. 2007b; Patruno et al. 2010), we find that the X-ray pulsations have energy dependent amplitudes; the fractional amplitude of the fundamental increases with energy, whereas the fractional amplitude of the harmonic shows a slight decline with energy. This energy dependent behavior is not unusual in AMXPs (Patruno & Watts 2012) and can be interpreted in terms of the thermal emission from the stellar hotspot and reprocessing in the accretion column (e.g., Gierliński et al. 2002; Ibragimov & Poutanen 2009). The pulse arrival times of the 2018 outburst are well described by a timing model consisting of a circular orbit with a constant spin frequency. The pulse phases with respect to this model do not show spurious residuals with time or orbital phase, and no evidence is found that the pulse arrival times exhibit an additional delay associated with passing through the gravitational well of the companion star (Shapiro delay). We note, however, that the expected Shapiro delay is given as (Shapiro et al. 1971) Equation (5) where Φ is the orbital phase, G is the gravitational constant, c is the speed of light, and i is the inclination. Even for the maximum allowed companion mass, ${M}_{C}=0.030\,{M}_{\odot }$ (Krimm et al. 2007b, but see Section 4.2 for more details) and an inclination of 90°, the largest delay we can expect is only 4 μs. As this time-delay is smaller than the uncertainty on our phase residuals by nearly two orders of magnitude (see Figure 1), we are not sensitive to Shapiro delays in Swift J1756. Comparing our measurements for the 2018 outburst with those of the 2007 and 2009 outbursts as observed with RXTE, we analyzed the long-term evolution of this source. We found that the binary system is consistent with having a constant orbital period and that the pulsar shows a spin frequency derivative of $\dot{\nu }=-7.3\times {10}^{-16}\,\mathrm{Hz}\,{{\rm{s}}}^{-1}$. 4.1. Spin-down Evolution The long-term spin frequency derivative measured in Swift J1756 is of the same order as the spin frequency derivatives measured in other AMXPs (Hartman et al. 2008; Patruno 2010; Riggio et al. 2011). This frequency change is most likely driven by the neutron star's loss of rotational energy. If so, then the spin-down luminosity is given as Equation (6) where I represents the neutron star moment of inertia. The long-term spin-down of a neutron star is usually assumed to be dominated by the braking torque associated with a spinning magnetic field. Assuming this mechanism is responsible for the observed spin-down in Swift J1756, we can compute the magnetic dipole moment as (Spitkovsky 2006) Equation (7) where α is the misalignment angle between the rotational and magnetic poles. Considering α = 0°–90°, we then find a magnetic field strength of $B\simeq (4\mbox{--}6)\times {10}^{8}$ G at the stellar magnetic poles. This magnetic field strength estimate is in line with those obtained for other accreting millisecond pulsars (see Mukherjee et al. 2015 and references therein). 4.2. Orbit Evolution The observed long-term binary evolution of Swift J1756 is consistent with this source having a constant orbital period and a lower limit on the evolutionary timescale of Equation (8) Binary evolution theory predicts that systems of this type evolve due to angular momentum loss through gravitational radiation (Kraft et al. 1962; Rappaport et al. 1982; Verbunt 1993). For conservative mass transfer, the binary period derivative is given by di Salvo et al. (2008), Equation (9) where MNS is the neutron star mass, $q={M}_{C}/{M}_{\mathrm{NS}}$ is the binary mass ratio, and −1/3 < n < 1 is the mass–radius index of the companion star. Depending on the source inclination, Krimm et al. (2007b) derived a companion mass of ${M}_{C}\,=0.007\mbox{--}0.022\,{M}_{\odot }$ for a neutron star mass of 1.4 ${M}_{\odot }$. For a neutron star mass of 2.2 ${M}_{\odot }$, the allowed range increased to ${M}_{C}=0.009\mbox{--}0.030\,{M}_{\odot }$. In both cases, they assumed an upper limit on the inclination of i < 85°, motivated by the fact that Swift J1756 does not show eclipses in its light curve. Accounting for the extreme cases of stellar masses and n, the binary may either be contracting or expanding. In either case, however, the rate of change is limited to $| {\dot{P}}_{b}| \lesssim 7\times {10}^{-14}$ s s−1, which is well below the upper limit obtained in this work. Although the binary evolution timescale we obtain for Swift J1756 is consistent with theory, it is worth noting that this is not generally true for low-mass X-ray binaries (see Patruno et al. 2017, for a comprehensive discussion). The AMXP SAX J1808.4–3658, in particular, has been found to evolve on a much shorter timescale, with a first derivative on the orbital period of $3.5\times {10}^{-12}$ s s−1 (Hartman et al. 2008; Patruno et al. 2012; Sanna et al. 2017a). Two models have been proposed to explain this discrepancy: highly nonconservative mass transfer due to irradiation of the companion star by the pulsar (di Salvo et al. 2008; Burderi et al. 2009), and spin–orbit coupling in the companion star (Hartman et al. 2008, 2009). While the latter depends on the companion star, and may vary from source to source, the former should operate in all AMXPs (see also Patruno 2017; Sanna et al. 2017c), including Swift J1756. The spin-down luminosity impinging on the companion star can be estimated as Equation (10) where ${\dot{E}}_{\mathrm{abl}}$ is the ablation luminosity, RL2 is the Roche lobe radius of the companion (Eggleton 1983), and a the binary separation. The irradiation fraction is $f={\dot{E}}_{\mathrm{abl}}/{\dot{E}}_{\mathrm{sd}}$, which, accounting for the range of allowed neutron star and companion masses, evaluates to f = 0.15%–0.35%. The associated mass loss for the companion is given by Equation (11) such that, assuming an efficiency of η = 100%, ${\dot{M}}_{C}\,\sim -3\times {10}^{-10}\,{M}_{\odot }$ yr−1. The effect of this mass loss on the orbital period follows through the relation (Frank et al. 2002) Equation (12) giving a period derivative due to mass loss of ${\dot{P}}_{b,\mathrm{ML}}\,=5\times {10}^{-12}$ s s−1. This value is well above our limit on the period derivative. Hence, in order for this mechanism to be consistent with our observations of Swift J1756, the efficiency at which the companion star converts the incident luminosity into mass loss must be η < 15%. This value is very different from the 40% required in SAX J1808.4–3658 (Patruno et al. 2016) and is instead in line with the <5% efficiency determined for IGR J00291+5934 (Patruno 2017). This work was supported by NASA through the NICER mission and the Astrophysics Explorers Program, and made use of data and software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC). P.B. was supported by an NPP fellowship at NASA Goddard Space Flight Center. D.A. acknowledges support from the Royal Society.

Bult, Peter↗

Facilitating Machine Learning Collaborations Between Labs, Universities, And Industry

It is clear from numerous recent community reports, papers, and proposals that machine learning is of tremendous interest for particle accelerator applications. The quickly evolving landscape continues to grow in both the breadth and depth of applications including physics modeling, anomaly detection, controls, diagnostics, and analysis. Consequently, laboratories, universities, and companies across the globe have established dedicated machine learning (ML) and data science efforts aiming to make use of these new state-of-the-art tools. The current funding environment in the U.S. is structured in a way that supports specific application spaces rather than larger collaboration on community software. Here, we discuss the existing collaboration bottlenecks and how a shift in the funding environment, and how we develop collaborative tools, can help fuel the next wave of ML advancements for particle accelerators.

Edelen, J.P.↗

Beat-by-beat stroke volume assessment by pulsed Doppler in upright and supine exercise

The instantaneous stroke volume (SV) and cardiac output (Q) in eight male subjects during steady-state supine (S) and upright (U) exercises at 300 kpm/min is assessed by a 3.0-MHz pulsed Doppler echocardiograph. The mean transients in heart rate (HR), SV, and Q for each posture were determined and the center-line blood velocities obtained in the ascending aorta. Results show that the mean supine values for SV and Q at rest and exercise were 111 ml and 6.4 l/min and 112 ml and 9.7 l/min, respectively. The corresponding results for U were 76 ml and 5.6 l/min and 92 ml and 8.4 l/min, respectively. The values compare favorably with previous studies utilizing invasive procedures. The transient response of Q following the onset of exercise in U was about twice as fast as in S because of the rapid and almost immediate upsurge in SV. The faster rise in aortic flow in U with exercise represented and additional volume (184 ml) of blood passing through the aorta compared with S in the first 20 exercises. It is suggested that the rapid mobilization of pooled venous blood from the leg veins during U was responsible for the increased blood flow.

Loeppky, J. A.↗

To the Moon! Space Launch System Modal Testing with Video and Motion Magnification

MIT Lincoln Laboratory and NASA Marshall Space Flight Center have been collaborating on using video camera measurements and motion magnification for modal testing of large aerospace components for several years. This presentation will discuss results from the Space Launch System Integrated Modal Test (IMT) and Dynamic Rollout/Rollback Test (DRRT) in support of the Artemis I mission. During the IMT, the data collection focused on operational mode shapes. In addition, the cameras were repositioned mid-test to better understand the physics of a low-frequency torsion mode. The non-contact nature of video data capture allowed for the quick redeployment of the cameras while not causing any delay in test schedule, whereas traditional instrumentation would have required a pause in testing to attach the sensors to the test article. The motion magnification analysis was able to find the low-frequency operational mode shapes and help the test team better understand the physics of the torsion mode. Building upon the success of the IMT motion magnification work, a camera system was used during the DRRT to find operational mode shapes, if the physics of the low-frequency torsion mode remained with different boundary conditions, and relative deflection of the vehicle and ML tower during the roll. In this paper we will present operational mode shape results, discuss the physics of the torsion mode, and review experimental setup idiosyncrasies to help the community in designing video camera measurement systems.

optical↗

Recommendations for Comprehensive and Independent Evaluation of Machine Learning‐Based Earth System Models

Abstract Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for weather forecasting, producing forecasts that rival modern physics‐based models. Given the importance of deepening our understanding and improving predictions of the Earth system on all time scales, efforts are now underway to develop Earth‐system models (ESMs) capable of representing all components of the coupled Earth system (or their aggregated behavior) and their response to external changes over long timescales. Building trust in ESMs is a much more difficult problem than for weather forecast models, not least because the model must represent the alternate (e.g., future or paleoclimatic) coupled states of the system for which there are no direct observations. Given that the physical principles that enable predictions about the response of the Earth system are often not explicitly coded in these ML‐based models, demonstrating the credibility of ML‐based ESMs thus requires us to build evidence of their consistency with the physical system. To this end, this paper puts forward five recommendations to enhance comprehensive, standardized, and independent evaluation of ML‐based ESMs to strengthen their credibility and promote their wider use.

54 ENVIRONMENTAL SCIENCES↗

Control of iodine and tellurium for use in domestic molybdenum-99 production efforts

Three initial proof-of-concept experiments were performed to test the removal of I and Te from solutions containing Mo for potential abatement during chemical processing to purify 99 Mo. All three proof-of-concept experiments produced results indicating that further optimization could provide methods for I and/or Te abatement from multiple matrices. Decamp and Happel (2013) describe the use of CL resin from Eichrom Technologies loaded with Ag + combined with Amberlite XAD-4 in the chromatographic separation of irradiated fission products in 1 M HNO 3 to separate iodine species where iodide and iodate react with Ag + and I2 adheres to the Amberlite resin. The method worked well under processing conditions in a medical isotope facility although many separation methods use higher concentrations of HNO 3 which could adversely impact the Ag + loading. The experiment performed here used a roughly 2 mL column of CL resin loaded with Ag + and Amberlite XAD-4 to separate µg quantities of I, Te, and Mo in 3 M HNO 3 .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗